+ All Categories
Home > Documents > Safety and Risk Management in Hospitals

Safety and Risk Management in Hospitals

Date post: 27-Dec-2015
Category:
Upload: rochady-setianto
View: 53 times
Download: 0 times
Share this document with a friend
Popular Tags:
70
Safety and risk management in hospitals Michel Dückers, PhD Marjan Faber, PhD Juliëtte Cruijsberg, MSc Richard Grol, PhD Lisette Schoonhoven, PhD Michel Wensing, PhD IQ Scientific Institute for Quality of Healthcare, Radboud University Nijmegen Medical Centre December 2009
Transcript

Safety and risk management in hospitalsMichel Dückers, PhD

Marjan Faber, PhD

Juliëtte Cruijsberg, MSc

Richard Grol, PhD

Lisette Schoonhoven, PhD

Michel Wensing, PhD

IQ Scientific Institute for Quality of Healthcare,Radboud University Nijmegen Medical Centre

December 2009

Acknowledgements

This study was produced as part of the Quest for Quality and Improved Performance (QQUIP), an initiative of the Health Foundation. Thanks are due to anonymous reviewers.

QQUIP and the Quality Enhancing Interventions project

QQUIP (Quest for Quality and Improved Performance) is a five-year research initiative of the Health Foundation. QQUIP provides independent reports on a wide range of data about the quality of healthcare in the UK. It draws on the international evidence base to produce information on where healthcare resources are currently being spent, whether they provide value for money and how interventions in the UK and around the world have been used to improve healthcare quality.

The Quality Enhancing Interventions component of the QQUIP initiative provides a series of structured evidence-based reviews of the effectiveness of a wide range of interventions designed to improve the quality of healthcare. The six main categories of Quality Enhancing Interventions for which evidence will be reviewed are shown below.

For more information visit www.health.org.uk/qquip

Published by:

The Health Foundation90 Long AcreLondon WC2E 9RATelephone: 020 7257 8000Facsimile: 020 7257 8001

www.health.org.uk

Registered charity number 286967Registered company number 1714937

First published December 2009

ISBN 978-1-906461-13-3

Copyright The Health Foundation

All rights reserved, including the right of reproduction in whole or in part in any form.

Every effort has been made to obtain permission from copyright holders to reproduce material. The publishers would be pleased to rectify any errors or omissions brought to their attention.

Dückers et al

Safety and risk management in hospitals

i

Contents

Glossary of acronyms iii

Executive summary iv

1. Introduction 1Safety and risk management concepts and definitions 1A continuous process 2Safety and risk management in hospitals 5A new research contribution 5

2. Objectives and methods 6Objectives 6 Methods 6 Data sources and searches 6 Search strategy 6 Study selection and data extraction 7

3. Results 11About the studies found 11 Number of studies 11 Methodological quality 11 Research setting 11Detection 11 Incident reports 13 Analysis techniques 14Mitigating factors 16 Actions to reduce risk 16 Reducing the number and severity of medication errors 16 Reducing the number and severity of fall incidents 18 Reducing diagnostic errors 19 Reducing the number and severity of adverse events and risks 19 Other safety or risk effects 20

4. Discussion 21 Main findings 21 Detection 21 Actions to reduce risk 21 Resilience 22Limitations 22

Contents

Dückers et al

Safety and risk management in hospitals

ii

Future research 23 Effectiveness detection 23 Continuous safety and risk management and resilience 23 Combined safety and risk management and implementation science 24 Expanding and improving safety and risk management research 24

References 25

Appendix A: Example of a search strategy and results 30

Appendix B: EPOC methodological filter 31

Appendix C: Study topics and interventions per SRM activity, sorted by design 32

Appendix D: Quality of study design 34

Appendix E: Included studies, sorted by alphabetical order 36

Contents

Dückers et al

Safety and risk management in hospitals

iii

Glossary of acronyms

ADE – adverse drug event

AE – adverse event

AIMS – Australian Incident Monitoring System

ARIMA – autoregressive integrated moving average

CBA – controlled before-after study

CI – criticality indices

CIT – critical incident technique

CPOE – computerised physician order entry

CWS – comparison with standards

EPOC – Effective Practice and Organisation of Care Group

FMEA – failure mode and effect analysis

MeSH – Medical Subject Heading

ICPS – International Classification for Patient Safety

IOM – Institute of Medicine

ITS – interrupted time series study

IV – intravenous

NICU – neonatal intensive care unit

OACM – organisational accident causation model

PDA – personal digital assistant

QEI – Quality Enhancing Interventions

QQUIP – Quest for Quality and Improved Performance

RCA – root cause analysis

RCT – randomised controlled trial

SEA – significant event auditing

SRM – safety and risk management

UBA – uncontrolled before-after study

WHO – World Health Organization

Glossary of acronyms

Dückers et al

Safety and risk management in hospitals Executive summary

iv

Executive summary

IntroductionPatient safety has become a matter of interest to healthcare professionals, governments and researchers worldwide. During the last decade, many studies have been conducted to assess the prevalence, severity and causes of a large variety of different types of adverse events in hospitals, as well as the effectiveness of various approaches to enhance safety.

ObjectivesThe objectives of this systematic review were:

1. to synthesise the evidence on the effectiveness of detection, mitigation and actions to reduce risks in hospitals; and

2. to identify and describe the components of interventions that are responsible for effectiveness.

MethodsThirteen literature databases were examined in May and June 2008 following a predefined search strategy. We included studies of sufficient methodological quality if these dealt with the effects of safety and risk management (SRM) in a hospital setting. At least two reviewers assessed the title and abstracts of unique studies. Two reviewers, working independently, studied the retrieved full-text articles and extracted information on their methods and results.

ResultsThirty-eight studies were included in the final review:

• three systematic reviews

• six randomised controlled trials (RCTs)

• four controlled before-after studies (CBAs)

• nine interrupted time series studies (ITSs)

• sixteen uncontrolled before-after studies (UBAs).

The types of interventions and outcomes were classified into three categories (two studies fitted in more than one category):

1. detection (nine studies)

2. mitigating factors (no studies)

3. actions to reduce risks (thirty-one studies).

Dückers et al

Safety and risk management in hospitalsExecutive summary

v

Detection

Studies could be divided into two categories: incident reports and analysis techniques.

Incident reports

All studies showed positive effects on the quality and/or quantity of reports. Specific findings were:

• The total error rate was higher in studies using voluntary reporting than in a study using mandatory reporting.

• Voluntary incident reporting may be associated with under-reporting in specific professions and in specific types of incidents.

• Nurses reported considerably more often than doctors.

• Incidents involving medication are reported most frequently.

• Feedback to the reporter is seen as an important way of encouraging staff to continue reporting incidents.

• Multi-institutional reporting, where information is gathered about adverse events in different hospitals and analysed centrally, identified rare but important problems.

• Paper-based reporting sometimes helps to increase reporting rates rather than a web-based tool.

Analysis techniques

Many publications were found relating to analysis techniques in industry and healthcare, although these did not focus on effects or effectiveness. Only two evaluations were identified; both showed positive results. However, systematic evidence on the effectiveness of safety analysis remains limited.

Mitigating factors

Mitigating factors are actions or circumstances that prevent or moderate the progression of an incident towards harming a patient. We did not identify any studies that fitted in this category.

Actions to reduce risks

The majority of the studies we examined dealt with this topic.

Actions taken to reduce risk concentrate on preventing the reoccurrence of the same or similar safety incidents, and on improving system resilience. The main patient outcome categories were:

• medication errors (for example, computerised physician order entry [CPOE]; pharmacist participation in rounds; education tools; clinical decision support systems; bar coding; organisation-wide safety programmes; smart-pump technology – an infusion system that checks that medication programming is within pre-established institutional limits before infusion can begin; structured order sheets – a standardised order sheet containing a number of pre-structured information categories; the Breakthrough Series, which uses a collaborative approach to enhance learning and reduce medication errors; failure mode and effect analysis [FMEA]

• fall incidents (for example, multi-component falls prevention programmes; flooring types; types of physiotherapy)

Dückers et al

Safety and risk management in hospitals Executive summary

• diagnostic errors (for example, computerised decision support and web-based reminder systems)

• adverse events and risks (for example, reporting systems; computerised clinical information systems; retrospective medical-record screening and review; or a combination of interventions, including multidisciplinary rounds led by doctors, and culture interventions)

• simulated survival (for example, human simulation training).

ConclusionResearch evidence for safety interventions in hospitals has remained limited. Published studies predominantly report on positive effects; however, the methodological quality of the studies is generally weak. The diversity of the collected material made it problematic to combine studies quantitatively. SRM interventions applied in a hospital setting are multifaceted and therefore it was difficult to disentangle the effects from the context in which they were implemented. This makes it challenging to formulate recommendations for future implementation to professionals and policy-makers. There is therefore a pressing need for high-quality evaluations of the effectiveness – and cost-effectiveness – of SRM interventions.

vi

Dückers et al

Safety and risk management in hospitals

1

1. Introduction

1. Introduction

This study is part of the Health Foundation’s QQUIP (Quest for Quality and Improved Performance) research initiative. One of the three main focuses of QQUIP is the Quality Enhancing Interventions (QEI) programme, which includes a series of structured, evidence-based reviews of the effectiveness of a wide range of interventions designed to improve the quality of healthcare. The programme aims to answer the question: ‘What works to improve quality and performance?’ There are six categories in the QEI programme, and this study falls within the category of ‘organisational interventions’ and focuses on safety and risk management (SRM).

Patient safety has increasingly become a matter of interest to governments, health professionals and scholars internationally. Over the last decade a great deal of research has been conducted to assess the prevalence, severity and causes of many different types of adverse events, as well as the effectiveness of efforts and approaches to enhance safety, and reduce risks and adverse events. SRM interventions relate to a wide variety of organisational aspects linked to safety and risks, ranging from co-ordination, resource allocation and standardisation in healthcare organisations, to issues of human resource management, communication, information technology, and inter-institutional improvement initiatives.

Safety and risk management concepts and definitionsThe MeSH is the US National Library of Medicine’s controlled vocabulary thesaurus. It consists of sets of terms that name descriptors in a hierarchical structure. This allows users to search at various levels of specificity. The Medical Subject Heading (MeSH) of ‘safety management’ was introduced in 1994. It encompasses:

the development of systems to prevent accidents, injuries, and other adverse occurrences in an institutional setting. The concept includes prevention or reduction in adverse events or incidents involving employees, patients, or facilities. Examples include plans to reduce injuries from falls or plans for fire safety to promote a safe institutional environment.

(MeSH 2009)

Safety management belongs to the MeSH tree of ‘risk management’, a heading that was introduced in 1990. Risk management involves:

the process of minimizing risk to an organization by developing systems to identify and analyze potential hazards to prevent accidents, injuries, and other adverse occurrences, and by attempting to handle events and incidents which do occur in such a manner that their effect and cost are minimized. Effective risk management has its greatest benefits in application to insurance in order to avert or minimize financial liability.

(MeSH 2009)

The World Health Organization (WHO) Conceptual Framework for the International Classification for Patient Safety (ICPS) offers a definition of SRM, restricted to a healthcare setting:

activities or measures taken by an individual or a health care organization to prevent, remedy or mitigate the occurrence or reoccurrence of a real or potential (patient) safety event.

(WHO, World Alliance for Patient Safety 2009)

Dückers et al

Safety and risk management in hospitals

2

1. Introduction

The ICPS aims to define, harmonise and group a standardised set of patient safety concepts – with agreed definitions, and labelled with preferred terms – into an internationally acceptable classification in a way that is conducive to learning and to improving patient safety over time and across borders (Sherman et al 2009).

A widely accepted definition of ‘patient safety’ comes from the Institute of Medicine (IOM). In To err is human patient safety is described ‘as the freedom from accidental injury due to medical care or from medical error’ (IOM 2000). The ICPS provides another definition:

the reduction of risk of unnecessary harm associated with healthcare to an acceptable minimum. An acceptable minimum refers to the collective notions of given current knowledge, resources available and the context in which care was delivered weighed against the risk of non-treatment or other treatment.

(WHO, World Alliance for Patient Safety 2009)

None of the definitions presented so far conflict with each other. They all refer to intentional actions, activities and measures: part of an organisational improvement or learning process in a healthcare setting. Other relevant phrases relating to patient safety are ‘medical error’, ‘near miss’ and ‘adverse event’. Again a leading definition comes from the ICPS:

An error is a failure to carry out a planned action as intended or application of an incorrect plan. Errors may manifest by doing the wrong thing (commission) or by failing to do the right thing (omission), at either the planning or execution phase.

(WHO, World Alliance for Patient Safety 2009)

Fallowfield and Fleissig (2004) suggest that medical errors should be distinguished from negligence or malpractice, insofar as the first is accidental while the second two are deliberate violations of a rule or standard of behaviour. Furthermore, medical errors do not lead to observable injury to the patient in all cases. The situations that did not cause harm to patients, but could have done, are described as ‘near miss’ (Wilson et al 1996). The term ‘adverse event’ is used for incidents in which the person receiving healthcare was harmed (Leape et al 1993). In their study, Leape et al identified a range of factors that contribute to adverse patient events, categorising them as diagnostic, treatment, preventive and other.

A continuous process In its simplest form, SRM in healthcare can be conceptualised as a continuous process in which healthcare providers respond to safety incidents, medical errors and expected risks. A logical starting point for an attempt to collect and synthesise the evidence on effective SRM interventions is to make an inventory of key concepts. An understanding of the patient safety literature, however, has been compromised by the inconsistent use of language (Runciman et al 2009). Similar patient safety concepts use different terms (for example ‘near miss’, ‘close call’), and identical terms are used to embrace several concepts (for example ‘medical error’ for errors, violations and system failures – see also Runciman et al 2006; Elder, Pallerla and Regan 2006. To meet the need for clarification and standardisation, the WHO’s World Alliance for Patient Safety has undertaken a project to develop an ICPS.

The current conceptual framework for the ICPS consists of three categories that are linked in several ways semantically (see Box 1). Two of the categories relate to the ‘clinically meaningful’ categorisation of an incident (based on incident types and patient outcomes) and ‘descriptive information’ about the context of the incident, including patient characteristics, incident characteristics, contributing factors/hazards and organisational outcomes. The third category, ‘proactive and reactive system resilience’, affects the activities and measures relating to SRM, and is the focus of this study. Within the ICPS, a distinction is made between detection, mitigating factors, ameliorating actions and actions taken to reduce risk (see Figure 1).

Dückers et al

Safety and risk management in hospitals

3

1. Introduction

Box 1: Ten classes within the conceptual framework for the ICPS

Clinically meaningful incident categorization• Incident type is a descriptive term for a category made up of incidents of a common nature

grouped because of shared, agreed features, such as ‘clinical process/procedure’, ‘resources/organizational management’ or ‘medication/IV fluid’ incident.

• Patient outcome is the impact upon a patient, which is wholly or partially attributable to an incident. Patient outcomes can be classified according to type of harm, degree of harm and any social and/or economic impact.

Descriptive information providing context for the incident• Patient characteristics categorize patient demographics, the original reason for seeking care and

the primary diagnosis.

• Incident characteristics classify the information about the circumstances surrounding the incident, such as where and when in the patient’s journey through the healthcare system the incident occurred, who was involved and who reported it.

• Contributing factors/hazards are the circumstances, actions or influences which are thought to have played a part in the origin or development of an incident or to increase the risk of an incident. Examples are human factors such as behaviour, performance or communication; system factors, such as work environment and external factors beyond the control of the organization, such as the natural environment or legislative policy. More than one contributing factor and/or hazard is typically involved in a single patient safety incident.

• Organizational outcomes refer to the impact upon an organization which is wholly or partially attributable to an incident such as an increased use of resources to care for the patient, media attention or legal ramifications.

System resilience (proactive and reactive risk management)The concept of ‘resilience’ in the context of the ICPS is defined as the degree to which a system continuously prevents, detects, mitigates or ameliorates hazards or incidents so that an organization can ‘bounce back’ to its original ability to provide core functions.

• Actions taken to reduce risk concentrate on steps taken to prevent the reoccurrence of the same or similar patient safety incident and on improving system resilience. Actions taken to reduce risk are those actions taken to reduce, manage or control any future harm, or probability of harm, associated with an incident. These actions may be directed toward the patient (provision of adequate care, decision support), toward staff (training, availability of policies/protocols), toward the organization (improved leadership/guidance, proactive risk assessment), and toward therapeutic agents and equipment (regular audits, forcing functions). Detection, mitigating factors and ameliorating actions both influence and inform the actions taken to reduce risk.

• Detection is defined as an action or circumstance that results in the discovery of an incident. For example, an incident could be detected by a change in the patient’s status, or via a monitor, alarm, audit, review or risk assessment. Detection mechanisms may be built into the system as official barriers or informally developed.

• Mitigating factors are actions or circumstances that prevent or moderate the progression of an incident toward harming the patient. Mitigating factors are designed to minimize the harm to the patient after the error has occurred and triggered damage control mechanisms.

• If the incident does result in harm, ameliorating actions can be introduced. Ameliorating actions are those actions taken or circumstances altered to make better or to compensate any harm after an incident. Ameliorating actions apply to the patient (clinical management of an injury, apologizing) and to the organization (staff debriefing, culture change and claims management).

Source: Sherman H, Castro G, Fletcher M et al (2009). ‘Towards an International Classification for Patient Safety: the conceptual framework’. International Journal for Quality in Health Care, vol 21, pp 4–7, by permission of Oxford University Press

Dückers et al

Safety and risk management in hospitals

4

1. Introduction

actio

ns ta

ken

to re

duce

ris

k

detection

actions taken to reduce risk

mitigating factors

ameliorating actions

contributing factors/hazards

organisational outcomes

influences informs

influences informs

influences informs

patient characteristics incident characteristicsincident

type

informs informs

patient outcome

influences informs

System resillience (proactive and reactive risk management)

Descriptive information

Clinically meaningful recognisable categories for incident identification

Figure 1: Conceptual framework for the ICPS

Source: Sherman H, Castro G, Fletcher M et al (2009). ‘Towards an International Classification for Patient Safety: the conceptual framework’. International Journal for Quality in Health Care, vol 21, p 4, by permission of Oxford University Press

Dückers et al

Safety and risk management in hospitals

5

1. Introduction

Safety and risk management in hospitals

This review focuses on SRM in hospitals. Most research on the effectiveness of SRM strategies has been carried out in hospital settings, with little in primary and community settings or in people’s homes (Øvretveit 2008). In terms of risk, hospitals are a relatively hazardous working environment for both patients and staff. Hospital staff must continuously deal with adverse events and numerous potential risks relating to surgery, anaesthetics and patient transfers: for example, wound infections, medication errors, wrong-site surgery. The relatively high risk of unsafe situations makes the hospital sector an important setting for an assessment of various approaches to SRM.

A new research contribution There is a substantial body of research in the area of patient safety. It is an ongoing challenge to keep track of the growing literature base and to categorise study findings and their implications in an orderly way. In their systematic review, Hoff et al (2004) examined the relationship between system features and safety outcomes. They considered the evidence available on associations between organisational dynamics, medical errors and patient safety. Their contribution involved an exploration of the relevance of, among others, culture, organisational structure, teams, feedback, opinion leaders, board leadership, educational programmes and information technology. Only a small number of studies confirmed a relationship between system components and errors or safety. This is an important finding. A possible explanation might be that the distance between system features and medical errors and safety events as investigated by Hoff et al (2004) is too large. A complementary perspective is that the field of organisational dynamics covers important conditions but that the association between conditions and safety outcomes depends on the successful implementation of specific SRM interventions. In other words, interventions – and not the organisational features – are linked more directly to patient safety. The effectiveness of such interventions, implemented within hospital organisations, is the main focus of our systematic review.

Given the gradual progress that is being made in the development of an international taxonomy and conceptual framework (see Figure 1), we apply our review on the effectiveness of SRM interventions from a system resilience perspective. The concept of resilience as defined by the ICPS is ‘the degree to which a system continuously prevents, detects, mitigates or ameliorates hazards or incidents’ so that an organisation can ‘bounce back’ to its original ability to provide core functions (Sherman et al 2009). Resilience is, in that sense, closely linked to actions to reduce risk. We underline the notion that, together, detection and mitigation can impede the progression of an incident from reaching and/or harming a patient. However, we refrain from placing undue emphasis on the effectiveness of ameliorating actions (that is, responses to harm), unless a direct influence is assessed of reactive ‘damage control’ actions on the dependent variable. Variables may include the number and severity of medical errors, adverse events, events reported, or hazards/root causes identified.

Dückers et al

Safety and risk management in hospitals

6

2. Objectives and methods

2. Objectives and methods

ObjectivesThe objectives of this study were to synthesise the evidence on the effectiveness of detection, mitigation and actions to reduce risks in hospitals, and to identify and describe the components of interventions that are responsible for effectiveness.

MethodsData sources and searches

A search for all relevant articles published before May 2008 was conducted in May and June 2008 of the following databases:

• PubMed

• PsycINFO

• Embase

• Cochrane Database of Systematic Reviews

• Database of Abstracts of Reviews of Effects (DARE)

• Cochrane Central Register of Controlled Trials

• Health Technology Assessment (HTA)

• NHS Economic Evaluation Database (NHS EED)

• Cumulative Index to Nursing and Allied Health Literature (CINAHL)

• King’s Fund

• World Health Organization Library and Information System (WHOLIS)

• CSA Sociological Abstracts

• Web of Science.

Search strategy

When searching for SRM literature, it became apparent at an early stage that we would need to apply additional limits, rather than just combining SRM with hospital terms as sector restrictors. Hospitals – together with risk and safety management (both as text words and MeSH headings) – resulted in almost 16,000 hits in PubMed, even when we applied a design filter from the Cochrane Effective Practice and Organisation of Care Group (EPOC). We therefore added a number of patient safety-related phrases to the search strategy. The final search strategy was based on SRM in relation to medical errors, adverse events, incidents and near misses, restricted to the hospital sector (see Box 2). An example of a search strategy from one database can be found in Appendix A.

Dückers et al

Safety and risk management in hospitals

7

2. Objectives and methods

Box 2: Search strategy

Search term

#1 ‘risk management’ (all fields, if possible MeSH)

#2 ‘safety management’ (all fields, if possible MeSH)

#3 2 OR 3

#4 ‘medical error(s)’ (all fields, if possible MeSH)

#5 ‘incident(s)’ (all fields)

#6 ‘adverse event(s)’ (all fields)

#7 ‘near miss(es)’

#8 4 OR 5 OR 6 OR 7

#9 ‘hospital(s)’ (all fields, if possible MeSH)

#10 3 AND 8 AND 9

#11 EPOC methodological filter

#12 10 AND 11

Study selection and data extraction

Types of studies

To determine which studies to include, we used a general hierarchy of evidence classification (from higher to lower validity):

• systematic reviews of reviews

• systematic reviews of studies

• individual randomised controlled trials

• quasi-experimental studies (for example, experimental studies without randomisation)

• controlled observational studies (for example, cohort or case-control studies)

• observational studies without a control group (for example, interrupted time series studies, uncontrolled before-after studies or case series).

Based on an exploration of available experimental studies, we considered all systematic reviews, randomised controlled trials (RCTs), controlled before-after studies (CBAs), interrupted time series studies (ITSs) and uncontrolled before-after studies (UBAs) as candidates for inclusion. To ensure that primarily studies with the preferred design were included in the study, we used a methodological filter (see Appendix B). We excluded studies that were not published in English, case studies or studies that did not include comparisons with a control group or pre-intervention episodes.

Dückers et al

Safety and risk management in hospitals

8

2. Objectives and methods

Types of interventions and setting

The review focused on three types of organisational interventions:

1. Detection: an action or circumstance that results in the discovery of an incident.

2. Mitigating factor: an action or circumstance that prevents or moderates the progression of an incident towards harming a patient.

3. Actions to reduce risks: actions taken to reduce, manage or control any future harm, or probability of harm, associated with an incident.

Types of outcome measures

SRM can influence different sorts of outcomes and this review focused on two types: the effects on safety and risk, and the effects on incident reporting and tracking. In the first case, outcomes were associated with changes in the safety and risk situation, so an SRM intervention was considered effective if it led to specific outcomes, such as the reduction in the number of (possible) incidents, errors, near misses and adverse events. In the second case, since an effective SRM cannot take place without adequate detection, it is likely that effective detection techniques will result in an increased quality or quantity of reported incidents (see Box 3).

Box 3: Types of outcome measures

Effects Examples

Effects on safety and risks Reducing the frequency or severity of:

• fall incidents

• wound infections

• misuse

• medication errors

Effects on incident reporting and tracking • Frequency

• Categories and severity/seriousness

• Willingness to report

• Differences between groups of practitioners (eg nursing staff or doctors)

Study selection procedure

Two reviewers, working independently, screened the papers found based on title and abstract, or, if necessary, the complete text. A third reviewer was consulted in those cases in which discrepancies were found.

We excluded studies from our review if they did not report any actual changes in the safety and risk situation, or any effect on monitored or reported incidents and risks. We also excluded studies if the intervention was not clearly defined.

Dückers et al

Safety and risk management in hospitals

9

2. Objectives and methods

Data extraction

One reviewer carried out the data extraction of full-text studies, and a second reviewer checked this using a pre-structured extraction form. The content of each paper included was summarised in descriptive texts. In the case of systematic reviews (of reviews), the topic, setting, search period, data sources, number of included studies, main outcomes (see Box 3) and conclusions were described. For non-review papers, the study setting and the nature of the intervention were described. For all included papers, an indication of the strength of the study was reported, based on the extent to which EPOC criteria for reviews, RCTs, CBAs and ITSs were met (as defined by The Cochrane Collaboration). The methodological quality of the reviews was determined by the quality of the studies they included, as well as the extent to which a systematic approach was followed. Criteria taken into account were:

• at least two authors scored eligibility

• authors used inclusion and exclusion criteria

• designs were judged using predefined criteria (EPOC, Jahad, etc)

• at least two authors scored findings

• authors used data extraction forms.

RCTs were assessed using seven criteria:

1. protection against selection bias

2. protection against contamination (for example, randomising organisations/professionals rather than individual patients)

3. protection against exclusion bias

4. follow-up of patients or episodes of care

5. comparability of baseline measurements

6. protection against detection bias (blinded assessment of primary outcomes)

7. reliability of primary outcome measures.

CBAs were judged using seven criteria:

1. protection against contamination

2. protection against exclusion bias

3. follow-up of patients or episodes of care

4. comparability of baseline measurements

5. protection against detection bias

6. characteristics for studies using second site as control

7. reliability of primary outcome measures.

The methodological quality of ITSs were determined using eight criteria:

1. intervention was independent of other changes

2. data analysed appropriately (autoregressive integrated moving average [ARIMA] or time series regression)

3. reason given for number of points pre and post intervention

4. shape of intervention effect was specified

Dückers et al

Safety and risk management in hospitals

10

2. Objectives and methods

5. intervention unlikely to affect data collection

6. protection against detection bias

7. completeness of data set

8. reliability of outcome measures.

UBAs were rated on one criteria only: the reliability of the primary outcome measure.

The summarising labelling of the methodological quality was based on two rules:

• Rule 1: if zero to two of the criteria were not fulfilled, for example, rated as ‘not done’ or ‘unclear’, in the case of an RCT, CBA or ITS, the study was considered strong. Studies were classed as moderate when three to maximally half of the criteria were not fulfilled. With weak studies, more than half of the criteria were not fulfilled.

• Rule 2: extra weight was given to fundamental characteristics of different studies, as critical aspects of the methodological quality had to be guaranteed. Strong RCTs and CBAs were rated as moderate if the comparability of control groups was not fulfilled. UBAs were rated as weak if the criterion on the reliability of the primary outcome measure was not fulfilled.

Synthesis of data

Our discussion of the evidence on SRM interventions has been organised into the activities described in the ICPS conceptual framework. We have described relevant characteristics for each activity, such as the study objectives and design, the nature of the intervention and the effects reported. Detailed information, for example, about the country, research setting and the statistical tests applied, can be found in Appendix E.

Dückers et al

Safety and risk management in hospitals

11

3. Results

3. Results

About the studies foundNumber of studies

Initially, we retrieved 3,772 references to studies from the various literature databases. Applying an EPOC design filter, in preparation for the first screening round, helped to reduce this to 1,872 studies. PubMed provided approximately 65 per cent of the studies. After checking the total number of studies for duplicates, we examined the abstracts of 1,645 unique studies using inclusion criteria (see Figure 2).

Two reviewers subsequently assessed 146 full-text articles and included 38 studies (see Appendix C for further details):

• three systematic reviews

• six randomised controlled trials (RCTs)

• four controlled before-after studies (CBAs)

• nine interrupted time series studies (ITSs)

• sixteen uncontrolled before-after studies (UBAs).

Methodological quality

We considered the design of four studies to be strong (Berner et al 2006; Paoletti et al 2007; Schneider et al 2006; Walsh et al 2008) and the design of seven studies to be moderate (Kozer et al 2005; Leape et al 1999; Lehmann et al 2007; Schwendimann et al 2006; Simon et al 2005; Snijders et al 2007; Voeffray et al 2006). The methodological quality of the remaining 27 studies was weak. (See Appendix D for further details.) Major limitations of these weak studies were the absence of studies with strong designs, and unclear descriptions of review procedures. In the case of RCTs, CBAs and ITSs, there was often uncertainty about the extent to which a perceived change was independent of other changes. The authors of most RCTs and CBAs could not guarantee the absence of contamination of interventions (that is, the possibility that the intervention reached the comparison group). ITSs were rarely examined with appropriate statistical techniques. The reliability of the outcome measure of many UBAs is unclear. In general, interventions were multifaceted or otherwise poorly specified.

Research setting

More than half of the material relates to studies in the USA. The other studies described interventions implemented in the UK, Australia, Canada, Hong Kong, the Netherlands and Switzerland. A limited number of studies made no distinction in the specialty or the types of patients treated. Other studies focused on: acute care, medical wards, ambulatory care, general internal medicine, paediatrics, cardiology, surgery, geriatrics, intensive care, and chemotherapy.

DetectionNine studies were identified on detection approaches. Studies could be divided into two categories: incident reports and analysis techniques. Two systematic reviews focused on incident reporting systems and their characteristics in relation to the size of effects (Simon et al 2005; Snijders et al 2007). Four empirical studies also described the effects of reporting systems, mainly voluntary or non-punitive

Dückers et al

Safety and risk management in hospitals

12

3. Results

Figure 2: Changes in the number of studies included during the review process

Total number of studies found (unfiltered) 3,772

PubMed 2,694PsycINFO 32Embase 285Cochrane Database of Systematic Reviews 13Database of Abstracts of Reviews of Effects 3Cochrane Central Register of Controlled Trials 11Health Technology Assessment database 4NHS Economic Evaluation Database 3CINAHL 557King’s Fund database 70WHOLIS 1CSA Sociological Abstracts 5Web of Science 94

Total number of studies found (filtered) 1,872

PubMed 1,197PsycINFO 19Embase 129Cochrane Database of Systematic Reviews 13Database of Abstracts of Reviews of Effects 3Cochrane Central Register of Controlled Trials 11Health Technology Assessment database 4NHS Economic Evaluation Database 3CINAHL 368King’s Fund database 70WHOLIS 1CSA Sociological Abstracts 5Web of Science 49

Unique studies: 1,645

Included after abstract scan: 146

Included for data extraction: 38

Extracted after EPOC filter: 1,900

Duplicates: 227

Excluded after abstract scan: 1,537

Excluded after full-text review: 108

Dückers et al

Safety and risk management in hospitals

13

3. Results

systems (Harris et al 2007; Lehmann et al 2007; Plews-Ogan et al 2004; Stump 2000). The other studies addressed an intervention package (Evans et al 2007), the Breakthrough Series, which uses a collaborative learning approach (Silver and Antonow 2000), and a multidisciplinary team addressing medication-related patient safety (Sim and Joyner 2002).

Incident reports

Effectiveness of reporting systems

The methodological quality of the studies in this category was moderate or weak. All of the studies reported positive effects on the quality or quantity of reported medical errors and incidents. One of the reviews (Simon et al 2005) assessed the effectiveness of hospital incident reporting systems in improving hospital and clinic performance in terms of patient safety, clinical outcomes, costs and operations. The authors included 11 studies published between 1994 and 2004: four with control conditions and seven uncontrolled evaluations. The main findings were that incident reporting and chart-review detection were less reliable than direct observation. The conclusion of the second review (Snijders et al 2007) was similar. Here the scope was narrowed to characteristics of incident reporting systems in neonatal intensive care units (NICU) in relation to type, aetiology, outcome and preventability of incidents. The search period was restricted to January 1980 and January 2006 and resulted in the inclusion of uncontrolled studies: eight prospective and two retrospective. Medication incidents were most frequently reported. Available data in the NICU showed that the total error rate was much higher in studies using voluntary reporting than in a study using mandatory reporting. Multi-institutional reporting, where information is gathered about adverse events in different hospitals and analysed centrally, identified rare but important errors. A substantial number of incidents were potentially harmful.

Various studies showed that the number of reports can be increased significantly by different approaches. Harris et al (2007) presented an increase of reporting incidence in their study of patient-safety event reporting in three intensive care units (medical, surgical and cardiothoracic). The introduction of a new, voluntary, card-based event reporting system was compared to existing online tools. In both systems, nurses submitted the majority of the reports (nurses 67.1 per cent; doctors 23.1 per cent; other reporters 9.5 per cent). However, with the paper-based system, the greatest increase in reporting related to doctors.

In a study by Lehmann et al (2007) the significant increase in the number of reports per month (from 19 to 102), and a change in the type of errors, was attributed to a revised medication event reporting policy that was implemented throughout the hospital in 2005. This policy was preceded by strategy sessions with the senior management about non-punitive reporting in the autumn of 1999 and small-scale implementation in October 2000.

Plews-Ogan et al (2004) described a substantial increase in the reporting of adverse events and near misses after the implementation of clinician-based near miss/adverse event voluntary reporting, coupled with systems analysis and redesign as a model for continuous quality improvement. The study took place in the ambulatory setting.

In a study by Stump (2000) the number of reported events increased considerably within one year after the medication error reporting process was redesigned in one hospital. The new process differed from the old one in the following ways:

• It was non-punitive.

• The central pharmacy department received a report within 48 hours rather than two to three months.

• A unified database was used instead of a fragmented process.

Dückers et al

Safety and risk management in hospitals

14

3. Results

• Near misses could be captured in every stage of the medication-use process and not only during the dispensing process.

• Structured check-box reports were used instead of handwritten free text.

• Staff at department level were involved in reviewing the data.

Effects of interventions other than reporting systems

Evans et al (2007) described a significant improvement in reporting in inpatient areas and in emergency departments after an intervention package was implemented. This included:

• a questionnaire and focus group to identify barriers for reporting

• a manual to improve knowledge

• education sessions

• the redesign of reporting processes to address concerns

• a one-page report form replacing the existing three-page form

• the introduction of a free-call telephone service

• the mailing of four feedback newsletters

• presentations being given at meetings.

Silver and Antonow (2000) reported how a Breakthrough Series model was applied to reduce the number of medication errors reported. Teams consisting of staff from quality improvement, pharmacy and medical departments attended seminars and acquired knowledge to enhance error reporting. Sim and Joyner (2002) linked an increase in reporting of medication variances to the introduction of a multidisciplinary team, formed to address medication-related patient safety initiatives. The team was set up in a community hospital that had a wide variety of acute care, critical care, emergency care and surgical and diagnostic services.

In summary, all studies, regardless of the quality of their design and the different interventions, described attempts to enhance incident and risk reporting. Nevertheless, incident reporting and chart review were found to be less reliable, complete and precise than observation. Nurses reported more often than doctors. There are also indications that the number of incidents reported was lower with mandatory rather than voluntary reporting.

Analysis techniques

Extensive literature is available on different analysis techniques. Woloshynowych et al (2005), for example, wrote an extensive and detailed publication on the nature and characteristics of different methods in industry and healthcare such as the Australian Incident Monitoring System (AIMS), the critical incident technique (CIT), comparison with standards (CWS), failure mode and effect analysis (FMEA), the organisational accident causation model (OACM), root cause analysis (RCA) and significant event auditing (SEA).

The study identified the following positive aspects of these methods:

• They contribute to priority setting.

• They emphasise the system and not the individual.

• They localise weak spots and risks.

Dückers et al

Safety and risk management in hospitals

15

3. Results

Negative elements included the following:

• They can be time consuming or complex.

• Their outcomes depend on the level of available expertise.

• A comprehensive answer is not always guaranteed.

Although relevant, the above study and other studies addressing reactive (for example, critical incident technique) or proactive (for example, FMEA) analysis techniques could not be included in this review as they do not focus on effects or effectiveness.

Two examples of studies that address the results of FMEA show that it enables changes to be monitored. Bonnabry et al (2005) conducted an FMEA to compare risks associated with the old and new process, to quantify the improved safety of the new process, and to identify the major residual risks in paediatric parental nutrition. A multidisciplinary team carried out the FMEA by following a series of process steps:

1. prescription

2. transmission to pharmacy

3. pharmaceutical validation

4. label production

5. compounding

6. quality control.

Several changes were implemented:

• new prescription software

• direct recording on a server

• automatic printing of the labels

• the creation of a file used to pilot an automatic compounder.

In the new process, the sum of the criticality indices (CI) of all 18 identified failure modes was reduced by 59 per cent compared with the old process. In the new process, the CIs of the different failure modes were reduced by a mean factor of seven.

Robinson et al (2006) also used FMEA to identify the elements of risk in chemotherapy, with the aim of implementing appropriate improvement strategies. The results of the analysis helped them to implement strategies in three processes: prescribing, dispensing and administration. The study concluded that it was feasible to improve potential error rates for prescribing, dispensing and administration. Actual effects were addressed in a later section of the study.

The main conclusion to be drawn in relation to different analysis methods and techniques is that, despite an abundance of descriptive material, information on their reliability and accuracy is limited. We did not find any studies comparing the effectiveness of analysis techniques.

Dückers et al

Safety and risk management in hospitals

16

3. Results

Mitigating factorsMitigating factors are designed to minimise the harm to a patient after an error has occurred and has triggered damage-control mechanisms (see Box 1 on page 3). We did not identify any studies that fitted in this category.

Actions to reduce riskThe remaining studies included in this review address interventions aimed at reducing risks. Actions taken to reduce risk concentrate on preventing the reoccurrence of the same or similar safety incidents and on improving system resilience (see Box 1). The main patient outcome categories were medication errors, fall incidents, diagnostic errors, human simulation training, adverse events, and safety risks.

Reducing the number and severity of medication errors

Medication was by far the largest category of safety improvement and risk-reduction interventions. We identified ten different types of interventions:

• computerised physician order entry (CPOE)

• pharmacist participation in doctors’/post-admission rounds

• education tools

• a clinical decision support system on a personal digital assistant (PDA)

• bar-code technology

• an organisation-wide safety programme

• smart-pump technology

• structured order sheets

• the Breakthrough Series

• failure mode and effect analysis (FMEA).

Computerised physician order entry

Four studies evaluated the effectiveness of CPOE implementation. One of them was a systematic review conducted by Shamliyan et al (2008). The hypothesis was tested that medication errors and adverse clinical events decrease with CPOE compared with handwritten orders by doctors in paediatric and adult patients, independent of patient and provider characteristics. The search period ranged from 1995 to 2004, and 12 studies were included: one RCT, nine UBAs and two studies with an unclear design. The main conclusion was that CPOE implementation was associated with a significant reduction in medication errors in adult and paediatric populations. However, results should be interpreted with caution. Effects may have been overestimated due to the use of non-randomised uncontrolled interventions. Implementation of CPOE was not associated with a substantial improvement in patient safety, and the studies did not allow broad generalisability. Two other studies also reported positive effects of CPOE (King et al 2003; Voeffray et al 2006). The authors of a fourth study – about CPOE in paediatric inpatient care – did not consider it as effective in reducing medication errors as it is in adult inpatient care (Walsh et al 2008).

Dückers et al

Safety and risk management in hospitals

17

3. Results

Pharmacist participation in doctors’/post-admission rounds

Two studies described how pharmacist participation in doctors’/post-admission rounds led to lower rates of preventable adverse drug events (Leape et al 1999) and enhanced accuracy of medication history (Fertleman et al 2005).

Education tools

Three studies examined the effectiveness of education tools. Simpson et al (2004) concluded that the impact of a combined risk-management/clinical pharmacist-led education programme on medication errors in an NICU was significantly positive. The results were similar to an assessment by Schneider et al (2006) of the influence of an interactive CD-ROM programme on the rate of medication administration errors made by nurses. However, this second approach did not contribute to a significantly reduced administration error rate. A study by Manning et al (2007) highlighted that a new web-based educational tool was not accompanied by a reduction in self-reported error rate either.

Clinical decision support system

Berner et al (2006) evaluated the effectiveness of a clinical decision support system on a PDA. The intervention group with the PDA decision support tool revealed a significantly lower mean proportion of cases per doctor with unsafe prescriptions for the intervention group than the control group, after adjustment for baseline rates.

Bar-code technology

Two studies dealt with the effectiveness of bar-code technology. Paoletti et al (2007) described the implementation of a multidisciplinary approach to systematically decrease medication errors by using observation methodology, electronic medication-administration records and bar-coded medication administration. The medication error rate decreased significantly in one of the two intervention groups and remained unchanged in the other. In the second study (Poon et al 2006) the implementation of bar-code technology resulted in a considerable reduction in dispensing errors and potential adverse drug events (ADEs).

Organisation-wide safety programme

Cohen et al (2005) focused on a possible reduction in adverse drug events as a result of an organisation-wide safety programme. The positive results – a significant reduction in ADE rate and the proportion of patients with ADEs – were attributed to a programme that included:

• the formation of a patient safety council

• assigning a full-time safety specialist

• the implementation of an event reporting system

• the introduction of drug protocols

• weekly medication-profile audits

• order standardisation.

Smart-pump technology

Smart-pump technology is an infusion system that checks that medication programming is within pre-established institutional limits before infusion can begin. Larsen et al (2005) conducted a study to determine whether combining standard drug concentrations with smart-pump technology reduced reported medication-infusion errors. They found that the significant reduction in the number of reported errors was associated with continuous medication infusions.

Dückers et al

Safety and risk management in hospitals

18

3. Results

Structured order sheet

Kozer et al (2005) concluded that a structured order sheet (a standardised order sheet containing a number of pre-structured information categories) is effective in reducing the incidence of medication errors in paediatric emergency departments. The intervention group used a new structured order sheet instead of the regular blank order sheets, which resulted in a statistically significant reduction.

The Breakthrough Series

Silver and Antonow (2000) conducted an evaluation of the Breakthrough Series (described on page 14). Analysis of this model, which used a collaborative approach to increase knowledge among teams of staff, demonstrated a significant decrease in overall error frequency and a significant increase in error detection and prevention.

Failure mode and effect analysis

The FMEA conducted by Robinson et al (2006) has also been described earlier (see page 15). After the implementation of improvement strategies, which resulted from the analysis, improvements were achieved in the potential prescribing error rate, actual dispensing errors and actual administration errors. The use of pre-printed standard order sets increased.

Reducing the number and severity of fall incidents

Multi-component falls prevention programmes

Five of the seven studies addressing interventions to reduce the number and/or severity of fall incidents are multi-component falls prevention programmes. Dempsey (2004) and Donoghue et al (2005) both reported positive results. Dempsey tested a falls prevention programme in an acute medical area, which was re-evaluated five years later to determine if the effects had been sustained. The conclusion was that the number of falls reduced by 55 per cent between 1995 and 1996. In 2001, the rate of patient falls had exceeded pre-research levels. Donoghue et al carried out research to find out whether a companion observer programme helped to prevent high-risk inpatients on an acute aged care ward from falling. Patients at high risk were accompanied in a room staffed by volunteer companion observers. The 128 observers worked in two-hour shifts, on weekdays from 8.00am to 8.00pm. Their primary objective was to keep patients company and to notice if they became increasingly agitated or showed risky behaviour. If this was the case, then they gently reassured the patient and, if necessary, contacted a nurse. The fall rate decreased by 44 per cent.

Another programme proved partly effective. Williams et al (2007) evaluated a systematic, co-ordinated approach to limit the severity and minimise the number of falls in an acute care hospital. Patients were classified according to three levels of risk: low, medium and high. Appropriate interventions (environment, mobility, elimination) were developed for each risk level on a fall care plan for each patient. Analysis showed a significant reduction in the number of falls (9.5 per 1,000 occupied bed days before and 8.0 per 1,000 occupied bed days after), although not in the severity of falls.

In the remaining studies, the intended decrease was not detected. Schwendimann et al (2006) examined an interdisciplinary falls prevention programme based on:

1. screening of all patients at admission for risk of falls

2. examination of patients considered at risk of falling

3. interventions for all patients to provide safety in the hospital

4. interventions for patients considered at risk of falling

5. reassessment of those patients who fell.

Dückers et al

Safety and risk management in hospitals

19

3. Results

After the implementation, a decrease in falls was observed, but this was not significant. There were no considerable differences over time in individual departments, and the annual proportion of minor and major injuries did not decrease. Lane (1999) evaluated the effectiveness of a falls prevention programme in reducing the patient fall rate. The programme also identified patients at risk of falling and established guidelines for interventions promoting patient safety. However, the study reported an insignificant change in patient fall rate per 1,000 patients days and an insignificant decrease in injuries.

Other interventions

In a falls prevention interventions review, Gillespie et al (2003) extracted two other studies, which did not deal with a falls prevention programme, but with different interventions. Donald et al (2000) compared two flooring types – carpet and vinyl – in hospital bed areas, and two types of physiotherapy – conventional therapy and additional leg strengthening exercises – in avoiding falls. No significant effect was found for either intervention. Tideiksaar et al (1993) examined the clinical efficacy of a bed alarm system in reducing falls from bed on a geriatric evaluation and treatment unit. The system functioned effectively, activating an alarm in all cases when patients were transferring from their bed and, with the exception of one case, nurses could respond quickly to help patients and prevent bed falls. Although there was a clinical trend towards reduced falls in the experimental group, this was not significant enough to make a statistical difference in bed falls between the experimental group with the bed alarm system and the four control groups.

Reducing diagnostic errors

A third category of outcomes was the reduction in diagnostic errors. Two studies about reminder systems were included, with both reporting significant improvements. Ramnarayan et al (2006a) examined the impact of a web-based diagnostic reminder system on clinicians’ decisions in an acute paediatric setting during assessments that were characterised by diagnostic uncertainty. After the introduction of the diagnostic computerised decision support system, the percentage of unsafe diagnostic workups decreased significantly from 45.2 per cent to 32.7 per cent. Ramnarayan et al (2006b) assessed the impact of a diagnostic reminder system on the quality of clinical decisions made by various grades of clinicians during acute assessment. The mean count of diagnostic errors of omission decreased significantly, and the mean diagnostic quality score increased. The number of irrelevant diagnoses increased from 0.7 to 1.4, but did not result in a corresponding increase in the number of irrelevant or deleterious tests and treatments.

Reducing the number and severity of adverse events and risks

Four studies fit within this category. The review of institutional reporting systems by Simon et al (2005) has been discussed on page 13. In this review the authors also assessed the effectiveness of reporting systems as an SRM intervention to improve safety and reduce risks. The majority (7 out of 11) of the included studies reported no reduction in medical errors and adverse events after implementing incident reporting systems.

The three other studies mainly reported positive results. A wide variety of approaches has been studied in attempts to reduce the number and severity of adverse events and risks, using information and communication technology (ICT) programmes, FMEA or multi-component intervention packages.

Fraenkel et al (2003) described the effects of a computerised clinical information system, implemented in an intensive care unit. Significant reductions occurred in the following incidents: medication, intravenous, ventilation and other incidents.

Dückers et al

Safety and risk management in hospitals

20

3. Results

Jain et al (2006) reported a variety of positive results. They evaluated a combination of different interventions that were implemented individually over a 12-month period, including:

• multidisciplinary rounds led by doctors

• daily bed-flow meetings to access bed availability

• evidence-based practices relating to three quality initiatives

• culture change, with a forum on team decision-making.

In a third study, the number of patient attendances associated with an adverse event decreased significantly between the first and last quarter of the study year (Wolff and Bourke 2002). Retrospective screening of patient files took place in two phases. After three months, several interventions were implemented:

• a variety of actions aimed at preventing events from recurring (changes in hospital policies, focused auditing, discussion with staff, implementation of guidelines)

• weekly adverse event reports/quarterly reports

• encouragement of staff to report clinical incidents.

In the light of the findings of the studies in this category, it is important to emphasise that the number of adverse events is generally an unreliable patient safety measure as the risk of under-reporting is substantial.

Other safety or risk effects

While most of the studies could be organised into the following categories: adverse events in general, medication errors, fall incidents, and diagnostic errors, one study could not be categorised in this way. DeVita et al (2005) found that simulated survival rates improved significantly after human simulation training in an educational environment to develop multidisciplinary team skills. The course components were:

• a web-based presentation and pre-test before the course

• a brief reinforcing training session on the day of the course

• three out of five different simulated scenarios, each followed by debriefing and analysis with the team.

Dückers et al

Safety and risk management in hospitals

21

4. Discussion

4. Discussion

The primary study objectives of this review were:

1. to synthesise the evidence on the effectiveness of detection, mitigation and actions to reduce risks in hospitals; and

2. to identify and describe the components of interventions that are responsible for effectiveness.

The study covered a wide variety of conditions and interventions related to safety and risks. We categorised the collected studies within different safety and risk management (SRM) interventions, as part of the International Classification for Patient Safety (ICPS) framework (see Box 1and page 3 and Figure 1 on page 4).

Main findingsDetection

The first type of intervention is detection. All the studies we included that deal with incident reporting (incident reporting systems, intervention packages, the Breakthrough Series, and efforts by a multidisciplinary team) indicate a positive effect of the interventions on the quality and/or quantity of reports. Most of the research on detection addresses reporting systems. When identifying the effective components of these systems, one finding is that voluntary incident reporting may lead to under-reporting (Plews-Ogan et al 2004). The total error rate was higher in studies using voluntary reporting than in a study using mandatory reporting (Snijders et al 2007). In practice, nurses report considerably more events than do doctors (Simon et al 2005; Harris et al 2007). Feedback to the reporter is seen as an important factor in safeguarding the willingness of staff to continue to report incidents and near misses (Simon et al 2005). In the case of neonatology, Snijders et al (2007) found that multi-institutional reporting identified uncommon but relevant errors. Moreover, Harris et al (2007) concluded that paper-based reporting sometimes works better than a web-based tool. The effective components of the other interventions to advance reporting are part of a larger intervention package, which therefore makes it impossible to disentangle the effective components from the whole programme.

A second detection activity concerns analysis methods. Despite a large number of papers devoted to this subject, research addressing the effectiveness and efficiency of safety analysis is scarce (see also Vincent 2004). There are indications that analysis techniques are effective in identifying potential risks or root causes, and in monitoring changes. One study by Robinson et al (2006), which had a weak design, shows that applying an FMEA has positive results, although information about which method works best in which circumstances – in terms of effectiveness, efficiency, accuracy and reliability – was not provided.

Actions to reduce risk

No studies on mitigating factors were identified. The majority of the studies, which were also those with the strongest study designs, dealt with actions to reduce risk. The collected evidence contributes to the knowledge about what works in general in reducing the number and severity of medication errors, fall incidents, diagnostic errors and adverse events. Unfortunately, however, it often remains unclear what the effective component was and why it worked. This is because SRM interventions are embedded in the structure and process of healthcare organisations. Furthermore, the diversity of the collected material, combined with the limited evidence for each topic, makes it difficult to draw generic conclusions or to conduct a quantitative meta analysis.

Dückers et al

Safety and risk management in hospitals

22

4. Discussion

Resilience

Resilience is the degree to which a system continuously prevents, detects, mitigates or ameliorates hazards or incidents so that an organisation can ‘bounce back’ to its original ability to provide core functions (see Box 1 on page 3). Within the context of ‘resilience’, SRM is linked to implementation science and concepts such as continuous quality improvement, cyclical quality management systems, and organisational learning. Improving safety and risk reduction, based on collected information about incidents and risks, or analysis results, requires some sort of learning or feedback mechanism. The study by Robinson et al (2006) provides a case in which analysis results were used as input for improvement. However, Simon et al (2005) concluded that many of the studies in their review on institutional reporting systems suffered from a flaw: that they are based on the assumption that incident data will automatically improve safety performance by directing system or institutional interventions, and by affecting health provider knowledge and skills via feedback.

In many of the studies included in our review, the relationship between detection, mitigation and risk reduction actions could not be verified. A general conclusion is that the initiation of reporting systems is likely to contribute to an increase in the number of reports. The real challenge, however, relates not to the quantity or quality of reports but to the degree to which professionals or organisations use the collected information to generate improvement. Feedback is considered a conditio sine qua non for learning and, thus, for continuous SRM. Still, the practical feasibility of feedback must be considered with some reservations. There is limited evidence about effective forms of safety feedback within healthcare (Benn et al 2009), and a Cochrane review of audit and feedback, which included more than 100 trials, showed a very modest improvement in professional performance overall (Jamtvedt et al 2006).

LimitationsThere are several reasons to view the findings of the studies we reviewed with caution and to question their usefulness in initiatives that translate them to new settings. These reasons are set out below:

• It seems highly probable that the published research on SRM has a substantial publication bias. Almost 90 per cent of the studies included in our review reported positive results.

• More than two-thirds of the included studies were of a low methodological quality. The available research is mainly comprised of uncontrolled observational evaluations. In many of the studies, the sample size was relatively small, and details were described poorly. This therefore limited the ability of the researchers to determine whether patients with particular characteristics – for example, age or morbidity – were more or less likely to respond to, for example, fall incident or medication safety interventions. In particular, the effects reported in the UBAs should be interpreted with caution.

• Interventions were often embedded in multifaceted intervention packages or programmes. In these cases, it was not possible to isolate the impact of specific components from other activities and conditions. This is not necessarily problematic, but it does make it challenging to determine what exactly caused an effect, or lack of effect.

• Most studies provided limited information on the costs relating to the intervention. Without this information, policy-makers, programme designers, managers and/or professionals cannot make informed decisions about the costs and benefits of improvement schemes.

• By taking ‘safety and risk management’ as a starting point, this review identified research linked to this term in the literature. Such an open approach allowed us to obtain a general sense of reference and guidance, instead of directly focusing on specific applications. This is an explorative approach, in which the term itself defines the scope. However, as a result, not all of the safety research performed in the context of quality improvement has been included.

Dückers et al

Safety and risk management in hospitals

23

4. Discussion

We therefore recommend extending the search strategy of future literature studies by using key phrases from the evolving ICPS framework. Our decision to select studies with strong research designs follows from the study objectives, but this means that relevant information from studies not meeting this threshold was excluded. As a result, only a selection of safety items were presented in this review, while highly relevant items such as infection control were omitted.

Future researchEffectiveness detection

By linking our review to the ICPS framework, we have the opportunity to locate gaps in the international literature on SRM. Most of the evidence discussed in this review affects detection and risk reduction measures. Researchers need to feel encouraged to proceed with the evaluation of the effectiveness of these and other detection interventions. In particular, we recommend the further assessment and comparison of analysis techniques (and their role as a window on the system – see, for example, Vincent 2004). It is important to learn more about their effectiveness, efficiency and accuracy. One way of exploring this area tentatively is for experts with practical experience of particular analysis methods to analyse the same incident (in the case of causes) or process (in the case of failure modes) and study whether their findings are similar. If they are, research could identify whether differences found can be attributed to the method or way the analysis was conducted. In this way, it may be possible to decide whether the result of an applied risk analysis method depends on the type of analysis or on the presence of specific conditions during the implementation. Likewise, the impact of analysis techniques may be best studied in combination with safety improvement interventions.

Continuous safety and risk management and resilience

Although the poor availability of material on mitigation is interesting, it is in the area of continuous SRM and resilience where we perceive the greatest need for original and system-oriented evaluations of effectiveness. How do SRM interventions contribute to continuous learning? Testable hypotheses can be formulated in relation to positive influences of various SRM approaches and conditions within hospitals, such as:

• the application of integrated safety frameworks

• organisational culture

• safety culture

• leadership styles

• guidelines

• performance management

• continuous quality improvement techniques

• multidisciplinary teams joining a quality improvement collaborative.

Although high expectations are often raised, in the current review no evidence on these topics was found in relation to SRM outcomes. This finding reflects that of other studies: for example, the research evidence concerning collaboratives (Schouten et al 2008), as well as the low number of studies identified by Hoff et al (2004) that verify the relationship between organisational features and patient safety. Compared with the review by Hoff et al, which focused on conditions, our emphasis on interventions resulted in a relatively large number of studies describing positive effects on safety and risk outcomes. Nevertheless, the possibilities for future research are enormous.

Dückers et al

Safety and risk management in hospitals

24

4. Discussion

Combined safety and risk management and implementation science

There is currently a substantial body of research on organisational changes in healthcare settings, but quality and safety systems have seldom been studied in rigorous evaluations, so their effectiveness remains unproven (Wensing et al 2006). Authors of studies identified in this review have highlighted the importance of follow-up measurements and the issue of sustainability (Dempsey 2004; Kozer et al 2005), and sustainability of implementation outcomes and changed practices is a highly relevant research area (Greenhalgh et al 2005; Grol et al 2007). We strongly recommend that research on the improvement of patient safety links to, and builds on, the extensive and rich world of quality improvement research and implementation science (Grol et al 2008). For example, it is not clear whether and how knowledge about the success and failure of the implementation of SRM interventions is used in dissemination decisions locally, nationally or internationally (in the case of effect studies published in international journals). Dissemination without a good understanding of the idiosyncrasies of a particular innovation may be a waste of time or may even be counterproductive.

Expanding and improving safety and risk management research

A conclusion that can be drawn from this review is that it is surprising – given the international attention focusing on patient safety – that the evidence base for SRM in a hospital setting is so limited. SRM needs to be approached like any intervention in healthcare in that it should prove its effectiveness – and cost effectiveness – before wide implementation is promoted. At this point, the number and quality of published studies on SRM interventions is too small to support conclusions about effectiveness in a systems perspective. Therefore, considerable expansion and improvement in research on SRM is much needed and would be of great value.

Dückers et al

Safety and risk management in hospitals

25

References

References

Benn J, Koutanji M, Wallace L et al (2009). ‘Feedback from incident reporting: Information and action to improve patient safety’ Quality and Safety in Healthcare, vol 18, pp 11–21.

Berner ES, Houston TK, Ray MN et al (2006). ‘Improving ambulatory prescribing safety with a handheld decision support system: a randomized controlled trial’. Journal of the American Medical Informatics Association (JAMIA), vol 13, pp 171–179.

Bonnabry P, Cingria L, Sadeghipour F et al (2005). ‘Use of a systematic risk analysis method to improve safety in the production of paediatric parenteral nutrition solutions’. Quality and Safety in Health Care, vol 14, pp 93–98.

Cohen MM, Kimmel NL, Benage MK et al (2005). ‘Medication safety program reduces adverse drug events in a community hospital’. Quality and Safety in Health Care, vol 14, pp 169–174.

Dempsey J (2004). ‘Falls prevention revisited: a call for a new approach’. Journal of Clinical Nursing, vol 13, pp 479–485.

DeVita MA, Schaefer J, Lutz J et al (2005). ‘Improving medical emergency team (MET) performance using a novel curriculum and a computerized human patient simulator’. Quality and Safety in Health Care, vol 14, pp 326–331.

Donald IP, Pitt K, Armstrong E et al (2000). ‘Preventing falls on an elderly care rehabilitation ward’. Clinical Rehabilitation, vol 14, pp 178–185.

Donoghue J, Graham J, Mitten-Lewis S et al (2005). ‘A volunteer companion-observer intervention reduces falls on an acute aged care ward’. International Journal of Health Care Quality Assurance Incorporating Leadership in Health Services, vol 18, pp 24–31.

Elder NC, Pallerla H and Regan S (2006). ‘What do family physicians consider an error? A comparison of definitions and physician perception’. BMC Family Practice, vol 7, p 73.

Evans SM, Smith BJ, Esterman A et al (2007). ‘Evaluation of an intervention aimed at improving voluntary incident reporting in hospitals’. Quality and Safety in Health Care, vol 16, pp 169–175.

Fallowfield LJ and Fleissig A (2004). ‘Communication with patients in the context of medical error’. Health Care Risk Special Report, vol 10, pp 12–14.

Fertleman M, Barnett N and Patel T (2005). ‘Improving medication management for patients: the effect of a pharmacist on post-admission ward rounds’. Quality and Safety in Health Care, vol 14, pp 207–211.

Fraenkel DJ, Cowie M and Daley P (2003). ‘Quality benefits of an intensive care clinical information system’. Critical Care Medicine, vol 31, pp 120–125.

Gillespie LD, Gillespie WJ, Robertson MC et al (2003). ‘Interventions for preventing falls in elderly people. Cochrane Database of Systematic Reviews, Issue 4, Art no. CD000340.

Dückers et al

Safety and risk management in hospitals

26

References

Greenhalgh T, Robert G, Bate P et al (2005). Diffusion of innovations in Health Service Organisations: a systematic literature review. London: Blackwell Publishing.

Grol R, Berwick DM and Wensing M (2008). ‘On the trail of quality and safety in health care’. British Medical Journal, vol 336, pp 74–76.

Grol R, Bosch MC, Hulscher MEJL et al (2007). ‘Planning and studying improvement in patient care: the use of theoretical perspectives’. Milbank Quarterly, vol 85, pp 93–138.

Harris CB, Krauss MJ, Coopersmith CM et al (2007). ‘Patient safety event reporting in critical care: a study of three intensive care units’. Critical Care Medicine, vol 35, pp 1,068–1,076.

Hoff T, Jameson L, Hannan E et al (2004). ‘A review of the literature examining linkages between organizational factors, medical errors, and patient safety’. Medical Care Research and Review, vol 61, pp 3–37.

Institute of Medicine (2000). To err is human: building a safer health system. Washington DC: National Academy Press.

Jain M, Miller L, Belt D et al (2006). ‘Decline in ICU adverse events, nosocomial infections and cost through a quality improvement initiative focusing on teamwork and culture change’. Quality and Safety in Health Care, vol 15, pp 235–239.

Jamtvedt G, Young JM, Kristoffersen DT et al (2006). ‘Audit and feedback: effects on professional practice and health care outcomes’. Cochrane Database of Systematic Review, Issue 2, Art no. CD000259.

King WJ, Paice N, Rangrej J et al (2003). ‘The effect of computerized physician order entry on medication errors and adverse drug events in pediatric inpatients’. Pediatrics, vol 112, pp 506–509.

Kozer E, Scolnik D, MacPherson A et al (2005). ‘Using a preprinted order sheet to reduce prescription errors in a pediatric emergency department: a randomized, controlled trial’. Pediatrics, vol 116, pp 1,299–1,302.

Lane AJ (1999). ‘Evaluation of the fall prevention program in an acute care setting’. Orthopaedic Nursing, vol 18, pp 37–43.

Larsen GY, Parker HB, Cash J et al (2005). ‘Standard drug concentrations and smart-pump technology reduce continuous-medication-infusion errors in pediatric patients’. Pediatrics, vol 116, e21–e25.

Leape LL, Cullen DJ, Clapp MD et al (1999). ‘Pharmacist participation on physician rounds and adverse drug events in the intensive care unit’. Journal of the American Medical Association, vol 282, pp 267–270.

Leape LL, Lawthers AG, Brennan TA et al (1993). ‘Preventing medical injury’. Quality Review Bulletin, vol 19, pp 144–149.

Dückers et al

Safety and risk management in hospitals

27

References

Lehmann DF, Page N, Kirschman K et al (2007). ‘Every error a treasure: improving medication use with a nonpunitive reporting system’. Joint Commission Journal on Quality and Patient Safety, vol 33, pp 401–407.

Manning DM, O’Meara JG, Williams AR et al (2007). ‘3D: a tool for medication discharge education’. Quality and Safety in Health Care, vol 16, pp 71–76.

MeSH (2009). Available at www.nlm.nih.gov/mesh/MBrowser.html. Accessed 29 August 2009.

Øvretveit J (2008). Which interventions are effective for improving patient safety? A synthesis of research and policy issues. Copenhagen/Stockholm: WHO HEN/MMC Karolinska.

Paoletti RD, Suess TM, Lesko MG et al (2007). ‘Using bar-code technology and medication observation methodology for safer medication administration’. American Journal of Health-System Pharmacy, vol 64, pp 536–543.

Plews-Ogan ML, Nadkarni MM, Forren S et al (2004). ‘Patient safety in the ambulatory setting. A clinician-based approach’. Journal of General Internal Medicine, vol 19, pp 719–725.

Poon EG, Cina JL, Churchill W et al (2006). ‘Medication dispensing errors and potential adverse drug events before and after implementing bar code technology in the pharmacy’. Annals of Internal Medicine, vol 145, pp 426–434.

Ramnarayan P, Roberts GC, Coren M et al (2006a). ‘Assessment of the potential impact of a reminder system on the reduction of diagnostic errors: a quasi-experimental study’. BMC Medical Informatics and Decision Making, vol 6, p 22.

Ramnarayan P, Winrow A, Coren M et al (2006b). ‘Diagnostic omission errors in acute paediatric practice: impact of a reminder system on decision-making’. BMC Medical Informatics and Decision Making, vol 6, p 37.

Robinson DL, Heigham M and Clark J (2006). ‘Using Failure Mode and Effects Analysis for safe administration of chemotherapy to hospitalized children with cancer’. Joint Commission Journal on Quality and Patient Safety, vol 32, pp 161–166.

Runciman WB, Williamson JAH, Deakin A et al (2006). ‘An integrated framework for safety, quality and risk management: an information and incident management system based on a universal patient safety classification’. Quality and Safety in Health Care, vol 15, i82–i90.

Runciman W, Hibbert P, Thomson R et al (2009). ‘Towards an International Classification for Patient Safety: key concepts and terms’. International Journal for Quality in Health Care, vol 21, pp 18–26.

Schneider PJ, Pedersen CA, Montanya KR et al (2006). ‘Improving the safety of medication administration using an interactive CD-ROM program’. American Journal of Health-System Pharmacy, vol 63, pp 59–64.

Schouten LMT, Hulscher MEJL, Van Everdingen JJE et al (2008). ‘Evidence for the impact of quality improvement collaboratives: systematic review’. British Medical Journal, vol 336, pp 1,491–1,494.

Dückers et al

Safety and risk management in hospitals

28

References

Schwendimann R, Buhler H, De Geest S et al (2006). ‘Falls and consequent injuries in hospitalized patients: effects of an interdisciplinary falls prevention program’. BMC Health Services Research, vol 6, p 69.

Shamliyan TA, Duval S, Du J et al (2008). ‘Just what the doctor ordered. Review of the evidence of the impact of computerized physician order entry system on medication errors’. Health Services Research, vol 43, pp 32–53.

Sherman H, Castro G, Fletcher M et al (2009). ‘Towards an International Classification for Patient Safety: the conceptual framework’. International Journal for Quality in Health Care, vol 21, pp 2–8.

Silver MP and Antonow JA (2000). ‘Reducing medication errors in hospitals: a peer review organization collaboration’. Joint Commission Journal on Quality and Patient Safety, vol 26, pp 332–340.

Sim TA and Joyner J (2002). ‘A multidisciplinary team approach to reducing medication variance’. Joint Commission Journal on Quality and Patient Safety, vol 28, pp 403–409.

Simon A, Lee RC, Cooke DL et al (2005). Institutional medical incident reporting systems: a review. Alberta: AHFMR, Health Technology Assessment Unit.

Simpson JH, Lynch R, Grant J et al (2004). ‘Reducing medication errors in the neonatal intensive care unit’. Archives of Disease in Childhood: Fetal and Neonatal Edition, vol 89, F480–F482.

Snijders C, van Lingen RA, Molendijk A et al (2007). ‘Incidents and errors in neonatal intensive care: a review of the literature’. Archives of Disease in Childhood: Fetal and Neonatal Edition, vol 92, F391–F398.

Stump LS (2000). ‘Re-engineering the medication error-reporting process: removing the blame and improving the system’. American Journal of Health-System Pharmacy, vol 57, Suppl 4, S10–S17.

Thomson R, Lewalle P, Sherman H et al (2009). ‘Towards an International Classification for Patient Safety: a Delphi survey’. International Journal for Quality in Health Care, vol 21, pp 9–17.

Tideiksaar R, Feiner CF and Maby J (1993). ‘Falls prevention – the efficacy of a bed alarm system in an acute-care setting’. Mount Sinai Journal of Medicine, vol 60, pp 522–527.

Voeffray M, Pannatier A, Stupp R et al (2006). ‘Effect of computerisation on the quality and safety of chemotherapy prescription’. Quality and Safety in Health Care, vol 15, pp 418–421.

Vincent C (2004). ‘Analysis of clinical incidents: a window on the system not a search for root causes’. Quality and Safety in Health Care, vol 13, pp 242–243.

Walsh KE, Landrigan CP, Adams WG et al (2008). ‘Effect of computer order entry on prevention of serious medication errors in hospitalized children’. Pediatrics, vol 121, e421–e427.

Wensing M, Wollersheim H and Grol R (2006). ‘Organisational interventions to implement improvements in patient care: a structured review of reviews’. BMC Implementation Science, vol 1, p 2.

Dückers et al

Safety and risk management in hospitals

29

References

Williams TA, King G, Hill AM et al (2007). ‘Evaluation of a falls prevention programme in an acute tertiary care hospital’. Journal of Clinical Nursing, vol 16, pp 316–324.

Wilson RM, Runciman WB, Gibberd RW et al (1996). ‘Quality in Australian health care study’. Medical Journal of Australia, vol 164, p 754.

Wolff AM and Bourke J (2002). ‘Detecting and reducing adverse events in an Australian rural base hospital emergency department using medical record screening and review’. Emergency Medical Journal, vol 19, pp 35–40.

Woloshynowych M, Rogers S, Taylor-Adams S et al (2005). ‘The investigation and analysis of critical incidents and adverse events in healthcare’. Health Technology Assessment, vol 9, pp 1–143.

World Health Organization, World Alliance for Patient Safety (2009). The conceptual framework for the International Classification for Patient Safety. Geneva: World Health Organization.

Dückers et al

Safety and risk management in hospitals

30

Appendix A: Example of a search strategy and results

Appendix A: Example of a search strategy and results

Search results: PubMed, 29 May 2008

Search term No. of hits

#1 ‘medical error’ [text word] 517

#2 ‘medical errors’ [text word] 7,480

#3 ‘medical errors’ [MeSH] 57,441

#4 1 OR 2 OR 3 57,871

#5 ‘incident’ [text word] 22,827

#6 ‘incidents’ [text word] 7,670

#7 5 OR 6 29,138

#8 ‘adverse event’ [text word] 6,182

#9 ‘adverse events’ [text word] 31,743

#10 8 OR 9 35,427

#11 ‘near miss’ [text word] 468

#12 ‘near misses’ [text word] 237

#13 11 OR 12 653

#14 4 OR 7 OR 10 OR 13 121,257

#15 ‘risk management’ [text word] 12,602

#16 ‘risk management’ [MeSH] 107,835

#17 15 OR 16 109,272

#18 ‘safety management’ [text word] 8,952

#19 ‘safety management’ [MeSH] 8,788

#20 18 OR 19 8,952

#21 17 OR 20 109,398

#22 ‘hospital’ [text word] 610,365

#23 ‘hospitals’ [text word] 224,372

#24 ‘hospitals’ [MeSH] 156,732

#25 22 OR 23 OR 24 714,103

#26 14 AND 21 AND 25 2,694

#27 EPOC filter (see Appendix B) 7,422,048

#28 26 AND 27 1,197

Dückers et al

Safety and risk management in hospitals

31

Appendix B: EPOC methodological filter

Appendix B: EPOC methodological filter

Randomized Controlled Trial [publication type] OR Controlled Clinical Trial [publication type] OR Comparative Study OR Evaluation Studies OR ‘comparative study’ OR ‘effects’ OR ‘effect’ OR ‘evaluations’ OR ‘evaluating’ OR ‘evaluation’ OR ‘evaluates’ OR ‘changing’ OR ‘changes’ OR ‘change’ OR ‘interventions’ OR ‘intervention’ OR ‘impact’ OR ‘random allocation’ OR ‘post test’ OR ‘posttest’ OR ‘pre test’ OR ‘pretest’ OR ‘time series’ OR ‘experimental’ OR ‘experiments’ OR ‘experiment’ OR ‘intervention studies’ OR ‘intervention study’ OR ‘controlled clinical trial’ OR ‘randomised controlled trial’ OR ‘randomized controlled trial’

Source: The Cochrane Effective Practice and Organisation of Care (EPOC) Group

Dückers et al

Safety and risk management in hospitals

32

Appendix C: Study topics and interventions per SRM activity

Dückers et al

Safety and risk management in hospitals

33

Appendix C: Study topics and interventions per SRM activity

Ap

pen

dix

C: S

tud

y to

pic

s an

d in

terv

enti

on

s p

er S

RM

act

ivit

y, s

ort

ed b

y d

esig

n

Act

ivit

yS

RM

top

icR

evie

wR

CT

CB

AIT

SU

BA

Inte

rven

tio

n

1D

etec

tio

n2

01

33

Qua

ntity

and

qua

lity

of

repo

rts

+-

--

-In

stitu

tiona

l med

ical

inci

dent

rep

ortin

g sy

stem

s (S

imon

et a

l 20

05)*

+-

--

-C

hara

cter

istic

s of

inci

dent

rep

ortin

g sy

stem

s (S

nijd

ers

et a

l 20

07)

Num

ber o

f rep

orts

--

+-

-In

terv

entio

n pa

ckag

e: e

duca

tion,

a r

ange

of r

epor

ting

optio

ns, e

nhan

ced

repo

rt m

anag

emen

t an

d fe

edba

ck (

Eva

ns e

t al 2

007

)

--

-+

-N

ew, v

olun

tary

, car

d-ba

sed

even

t rep

ortin

g sy

stem

(H

arris

et a

l 20

07)

--

-+

-R

evis

ed, n

on-p

uniti

ve m

edic

atio

n ev

ent r

epor

ting

polic

y (L

ehm

ann

et a

l 20

07)

--

-+

-C

hang

ing

the

trad

ition

al, m

ulti-

tiere

d in

cide

nt r

epor

ting

syst

em fo

r med

icat

ion

erro

rs to

a

stan

dard

ised

, non

-pun

itive

med

icat

ion-

use

varia

nce

proc

ess

(Stu

mp

200

0)

--

--

+V

olun

tary

nea

r mis

s/ad

vers

e ev

ent r

epor

ting,

com

bine

d w

ith s

yste

m a

naly

sis

and

rede

sign

(P

lew

s-O

gan

et a

l 20

04)

--

--

+B

reak

thro

ugh

Ser

ies

to r

educ

e m

edic

atio

n er

rors

(S

ilver

and

Ant

onow

20

00

)*

--

--

+M

ultid

isci

plin

ary

team

add

ress

ing

med

icat

ion-

rela

ted

patie

nt s

afet

y in

itiat

ives

: num

ber o

f va

rianc

e re

port

s (S

im a

nd J

oyne

r 20

02)

2M

itig

atin

g f

acto

rs0

00

00

3A

ctio

ns

to r

edu

ce r

isk

26

36

14

Adv

erse

eve

nts

(uns

peci

fied)

+-

--

-In

stitu

tiona

l med

ical

inci

dent

rep

ortin

g sy

stem

s (S

imon

et a

l 20

05)*

--

-+

-C

linic

al in

form

atio

n sy

stem

(F

raen

kel e

t al 2

003

)

--

--

+Te

amw

ork

and

cultu

re c

hang

e (J

ain

et a

l 20

06

)

--

--

+U

se o

f FM

EA

to id

entif

y ris

k, a

nd fo

r im

plem

entin

g st

rate

gies

(R

obin

son

et a

l 20

06

)

--

--

+R

etro

spec

tive

med

ical

-rec

ord

scre

enin

g an

d cl

inic

al r

evie

w fo

llow

ed b

y ap

prop

riate

qua

lity

impr

ovem

ent a

ctio

ns (

Wol

ff a

nd B

ourk

e 20

02)

Med

icat

ion

erro

rs/a

dver

se

drug

eve

nts

+-

--

Com

pute

risat

ion

of p

hysi

cian

ord

ers:

pre

scrip

tion

(Sha

mliy

an e

t al 2

008

)

-+

--

-D

ecis

ion

supp

ort t

ool o

n pe

rson

al d

igita

l ass

ista

nt (

Ber

ner e

t al 2

00

6)

-+

--

-S

truc

ture

d or

der s

heet

(K

ozer

et a

l 20

05)

-+

--

-N

ew w

eb-b

ased

edu

catio

n to

ol c

ompa

red

with

a s

tand

ard

educ

atio

n to

ol (

Man

ning

et a

l 20

07)

Dückers et al

Safety and risk management in hospitals

32

Appendix C: Study topics and interventions per SRM activity

Dückers et al

Safety and risk management in hospitals

33

Appendix C: Study topics and interventions per SRM activity

-+

--

-In

tera

ctiv

e C

D-R

OM

pro

gram

me

(Sch

neid

er e

t al 2

00

6)

--

+-

-C

ompu

teris

ed p

hysi

cian

ord

er e

ntry

sys

tem

with

out c

linic

al d

ecis

ion

supp

ort (

Kin

g et

al 2

003

)

--

+-

-P

harm

acis

t par

ticip

atio

n in

the

ICU

at t

he ti

me

of d

rug

pres

crib

ing

(Lea

pe e

t al 1

999

)

--

+-

-O

bser

vatio

n m

etho

dolo

gy a

nd e

lect

roni

c m

edic

atio

n re

cord

s: b

ar-c

ode

tech

nolo

gy

(Pao

lett

i et a

l 20

07)

--

-+

-O

rgan

isat

ion-

wid

e sa

fety

pro

gram

me

(Coh

en e

t al 2

005

)

--

-+

-C

ombi

ned

risk

man

agem

ent/

clin

ical

pha

rmac

ist-

led

educ

atio

n pr

ogra

mm

e

(Sim

pson

et a

l 20

04)

--

-+

-C

ompu

teris

ed p

hysi

cian

ord

er e

ntry

sys

tem

(V

oeff

ray

et a

l 20

06

)

--

-+

-C

ompu

teris

ed p

hysi

cian

ord

er e

ntry

sys

tem

, che

ck d

osag

e w

ith a

lert

func

tion

(W

alsh

et a

l 20

08)

--

--

+P

harm

acis

t par

ticip

atio

n on

pos

t-ad

mis

sion

war

d ro

unds

(F

ertle

man

et a

l 20

05)

--

--

+C

ombi

ning

sta

ndar

d dr

ug c

once

ntra

tions

with

sm

art-

pum

p te

chno

logy

: inf

usio

n

(Lar

sen

et a

l 20

05)

--

--

+B

ar-c

ode

tech

nolo

gy (

disp

ensi

ng e

rror

s an

d po

tent

ial A

DE

s (P

oon

et a

l 20

06

)

--

--

+B

reak

thro

ugh

Ser

ies

to r

educ

e m

edic

atio

n er

rors

(S

ilver

and

Ant

onow

20

00

)*

Sev

erity

and

/or n

umbe

r of

fall

inci

dent

s-

+-

--

Com

paris

on o

f car

pet a

nd v

inyl

floo

ring

type

s in

bed

are

as a

nd tw

o ty

pes

of p

hysi

othe

rapy

(D

onal

d et

al 2

00

0)

-+

--

-B

ed a

larm

sys

tem

(T

idei

ksaa

r et a

l 199

3)

--

-+

-In

terd

isci

plin

ary

falls

pre

vent

ion

prog

ram

me

(Sch

wen

dim

ann

et a

l 20

06

)

--

--

+C

ompa

nion

obs

erve

r pro

gram

me,

bas

ed o

n 12

8 vo

lunt

eer o

bser

vers

(D

onog

hue

et a

l 20

05)

--

--

+F

all r

isk

asse

ssm

ent a

nd p

reve

ntio

n pr

ogra

mm

e (D

emps

ey 2

004

)

--

--

+F

alls

pre

vent

ion

prog

ram

me

(Lan

e 19

99)

--

--

+S

yste

mat

ic, c

o-o

rdin

ated

app

roac

h (W

illia

ms

et a

l 20

07)

Dia

gnos

tic e

rror

s-

--

-+

Web

-bas

ed d

iagn

ostic

rem

inde

r sys

tem

on

clin

icia

ns’ d

ecis

ions

(R

amna

raya

n et

al 2

00

6a)

--

--

+C

ompu

teris

ed d

ecis

ion

supp

ort (

a di

agno

stic

rem

inde

r sys

tem

) ((R

amna

raya

n et

al 2

00

6b)

Sim

ulat

ed s

urvi

val r

ates

--

--

+H

uman

sim

ulat

ion

trai

ning

/edu

catio

nal e

nviro

nmen

t to

deve

lop

team

ski

lls (

DeV

ita e

t al 2

005

)

* In

clud

ed m

ore

than

onc

e in

this

tabl

e

AD

E =

adv

erse

dru

g ev

ent

FM

EA

= fa

ilure

mod

e an

d ef

fect

s an

alys

is

ICU

= in

tens

ive

care

uni

t.

Dückers et al

Safety and risk management in hospitals

34

Appendix D: Quality of study design

Dückers et al

Safety and risk management in hospitals

35

Appendix D: Quality of study design

Des

ign

Fir

st a

uth

or

A1

A2

A3

A4

A5

B1

B2

CD

1D

2E

FG

1G

2H

IJ

KL

MN

OP

QO

vera

ll q

ual

ity

Rev

iew

(3)

Sha

mliy

an 2

008

121

00

11?

-?

?+

Wea

k

Sim

on 2

005

110

40

7?

++

??

Mod

erat

e

Sni

jder

s 20

0710

??

??

++

-?

?M

oder

ate

RC

T (

6)B

erne

r 20

06+

-+

NA

++

?S

tron

g

Don

ald

2000

??

NA

++

??

Wea

k

Koz

er 2

005

++

NA

+-

+?

Mod

erat

e

Man

ning

200

7+

?N

A-

NA

+?

Wea

k

Sch

neid

er 2

006

++

+N

A+

+?

Str

ong

Tid

eiks

aar

1993

??

NA

++

??

Wea

k

CB

A (

4)E

vans

200

7+

??

+?

-?

Wea

k

Kin

g 20

03?

NA

NA

+?

--

Wea

k

Leap

e 19

99?

NA

NA

++

-+

Mod

erat

e

Pao

letti

200

7-

NA

NA

++

++

Str

ong

ITS

(9)

Coh

en 2

005

??

-?

+-

+?

Wea

k

Frae

nkel

200

3?

?-

--

??

?W

eak

Har

ris 2

007

??

--

-?

??

Wea

k

Lehm

ann

2007

+?

-+

+?

?+

Mod

erat

e

Sch

wen

dim

ann

2006

??

+-

++

++

Mod

erat

e

Sim

pson

200

4-

+-

--

--

?W

eak

Stu

mp

2000

-?

--

-+

??

Wea

k

Voe

ffray

200

6?

+-

++

+?

?M

oder

ate

Wal

sh 2

008

?+

++

++

+-

Str

ong

UB

A (

16)

Dem

psey

200

4?

Wea

k

DeV

ita 2

005

+W

eak

Don

oghu

e 20

05+

Wea

k

Fert

lem

an 2

005

?W

eak

Jain

200

6?

Wea

k

Lane

199

9+

Wea

k

Lars

en 2

005

?W

eak

Ple

ws-

Oga

n 20

04?

Wea

k

Poo

n 20

06+

Wea

k

Ram

nara

yan

2006

a?

Wea

k

Ram

nara

yan

2006

b+

Wea

k

Rob

inso

n 20

06?

Wea

k

Silv

er 2

000

?W

eak

Sim

200

2?

Wea

k

Will

iam

s 20

07+

Wea

k

Wol

ff 20

02?

Wea

k

Ap

pen

dix

D: Q

ual

ity

of s

tud

y d

esig

n

Dückers et al

Safety and risk management in hospitals

34

Appendix D: Quality of study design

Dückers et al

Safety and risk management in hospitals

35

Appendix D: Quality of study design

Des

ign

Fir

st a

uth

or

A1

A2

A3

A4

A5

B1

B2

CD

1D

2E

FG

1G

2H

IJ

KL

MN

OP

QO

vera

ll q

ual

ity

Rev

iew

(3)

Sha

mliy

an 2

008

121

00

11?

-?

?+

Wea

k

Sim

on 2

005

110

40

7?

++

??

Mod

erat

e

Sni

jder

s 20

0710

??

??

++

-?

?M

oder

ate

RC

T (

6)B

erne

r 20

06+

-+

NA

++

?S

tron

g

Don

ald

2000

??

NA

++

??

Wea

k

Koz

er 2

005

++

NA

+-

+?

Mod

erat

e

Man

ning

200

7+

?N

A-

NA

+?

Wea

k

Sch

neid

er 2

006

++

+N

A+

+?

Str

ong

Tid

eiks

aar

1993

??

NA

++

??

Wea

k

CB

A (

4)E

vans

200

7+

??

+?

-?

Wea

k

Kin

g 20

03?

NA

NA

+?

--

Wea

k

Leap

e 19

99?

NA

NA

++

-+

Mod

erat

e

Pao

letti

200

7-

NA

NA

++

++

Str

ong

ITS

(9)

Coh

en 2

005

??

-?

+-

+?

Wea

k

Frae

nkel

200

3?

?-

--

??

?W

eak

Har

ris 2

007

??

--

-?

??

Wea

k

Lehm

ann

2007

+?

-+

+?

?+

Mod

erat

e

Sch

wen

dim

ann

2006

??

+-

++

++

Mod

erat

e

Sim

pson

200

4-

+-

--

--

?W

eak

Stu

mp

2000

-?

--

-+

??

Wea

k

Voe

ffray

200

6?

+-

++

+?

?M

oder

ate

Wal

sh 2

008

?+

++

++

+-

Str

ong

UB

A (

16)

Dem

psey

200

4?

Wea

k

DeV

ita 2

005

+W

eak

Don

oghu

e 20

05+

Wea

k

Fert

lem

an 2

005

?W

eak

Jain

200

6?

Wea

k

Lane

199

9+

Wea

k

Lars

en 2

005

?W

eak

Ple

ws-

Oga

n 20

04?

Wea

k

Poo

n 20

06+

Wea

k

Ram

nara

yan

2006

a?

Wea

k

Ram

nara

yan

2006

b+

Wea

k

Rob

inso

n 20

06?

Wea

k

Silv

er 2

000

?W

eak

Sim

200

2?

Wea

k

Will

iam

s 20

07+

Wea

k

Wol

ff 20

02?

Wea

k

A1:

nu

mbe

r of s

tudi

es in

clud

ed. A

2: n

umbe

r of R

CTs

in

clud

ed. A

3: n

umbe

r of C

BA

s in

clud

ed.

A4:

num

ber o

f IT

Ss

incl

uded

. A5

: num

ber o

f UB

As

incl

uded

B1:

sc

orin

g of

elig

ibili

ty b

y at

leas

t tw

o au

thor

s.

B2

: aut

hors

use

d in

clus

ion

and

excl

usio

n cr

iteria

C:

desi

gns

wer

e ju

dged

usi

ng p

rede

fined

cri

teria

(E

PO

C,

Jaha

d, e

tc)

D1:

sco

ring

of fi

ndin

gs b

y at

leas

t tw

o au

thor

s. D

2: a

utho

rs

used

dat

a ex

trac

tion

form

s

E:

conc

ealm

ent o

f allo

catio

n (p

rote

ctio

n ag

ains

t sel

ectio

n bi

as)

F:

prot

ectio

n ag

ains

t con

tam

inat

ion

(eg

rand

omis

ing

orga

nisa

tion

/pro

fess

iona

ls r

athe

r tha

n in

divi

dual

pa

tient

s)

G1:

fol

low

-up

of p

rofe

ssio

nals

(pr

otec

tion

agai

nst e

xclu

sion

bi

as).

G2

: fol

low

-up

of p

atie

nts

or e

piso

des

of c

are

H:

base

line

mea

sure

men

t (no

diff

eren

ces)

I:

blin

ded

asse

ssm

ent o

f prim

ary

outc

ome

(s) (

prot

ectio

n ag

ains

t det

ectio

n bi

as)

J:

char

acte

rist

ics

for s

tudi

es u

sing

sec

ond

site

as

cont

rol

K:

the

inte

rven

tion

is in

depe

nden

t of o

ther

cha

nges

L:

data

wer

e an

alys

ed a

ppro

pria

tely

(A

RIM

A o

r tim

e se

ries

reg

ress

ion)

M:

reas

on fo

r the

num

ber o

f poi

nts

pre

and

post

in

terv

entio

n gi

ven

N:

shap

e of

the

inte

rven

tion

effe

ct w

as s

peci

fied

O:

inte

rven

tion

unlik

ely

to a

ffec

t dat

a co

llect

ion

P:

com

plet

enes

s of

dat

a se

t

Q:

relia

ble

prim

ary

outc

ome

mea

sure

(s)

+ =

done

- = n

ot d

one

? =

uncl

ear

NA

= n

ot a

vaila

ble

Dückers et al

Safety and risk management in hospitals

36

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

37

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Ber

ner,

200

6

US

A

RC

T

Am

bula

tory

/out

patie

nt c

are,

ge

nera

l int

erna

l med

icin

e

Inte

rven

tion

grou

p:

N =

34

(pre

-inte

rven

tion)

N =

31

(pos

t-in

terv

entio

n)C

ontr

ol g

roup

:N

= 3

4 (p

re-in

terv

entio

n)N

= 2

8 (p

ost-

inte

rven

tion)

Per

iod

= N

C (

8-m

onth

fo

llow

-up)

Aim

To e

valu

ate

the

effe

ctiv

enes

s of

a P

DA

-bas

ed C

DS

S o

n N

SA

ID p

resc

ribin

g sa

fety

by

inte

rnal

med

icin

e re

side

nts

in

the

outp

atie

nt s

ettin

g

Inte

rven

tio

nP

DA

with

CD

SS

Co

ntr

ol

PD

A w

ithou

t CD

SS

Pri

mar

y o

utc

om

eP

ropo

rtio

n of

cas

es

per d

octo

r with

uns

afe

NS

AID

pre

scrip

tions

AN

CO

VA

Sig

nific

ant r

educ

tion

(0.2

3 ve

rsus

0.

45 u

nsaf

e pr

escr

iptio

n ca

ses

per

doct

or [I

ver

sus

C],

F =

4.2

4, p

< 0

.05,

ef

fect

siz

e =

0.5

4)

Res

iden

ts p

rovi

ded

with

a

PD

A-b

ased

CD

SS

for N

SA

ID

pres

crib

ing

mad

e fe

wer

uns

afe

trea

tmen

t dec

isio

ns th

an

part

icip

ants

usi

ng a

PD

A w

ithou

t th

e C

DS

S

Coh

en, 2

005

US

A

ITS

Hos

pita

l car

e

N =

10

–20

char

t rev

iew

s of

dis

char

ged

patie

nts

per

mon

th

Per

iod

= 20

01–2

003

(6

mon

ths

base

line,

9 m

onth

s im

plem

enta

tion,

21-

mon

th

follo

w-u

p)

Aim

To a

sses

s th

e im

pact

of

a w

ide

rang

ing

safe

ty

prog

ram

me

on p

atie

nt h

arm

Inte

rven

tio

nC

ombi

ned

inte

rven

tion,

in

clud

ing

:•

form

atio

n of

a p

atie

nt

safe

ty c

ounc

il•

assi

gnin

g a

full-

time

safe

ty s

peci

alis

t•

impl

emen

tatio

n of

eve

nt

repo

rtin

g sy

stem

• in

trod

uctio

n of

dru

g pr

otoc

ols

• w

eekl

y m

edic

atio

n pr

ofile

au

dits

• or

der s

tand

ardi

satio

n

Co

ntr

ol

NA

1. A

DE

rat

e pe

r 1,0

00

dose

s de

liver

ed

2. A

DE

rat

e pe

r 1,0

00

patie

nt d

ays

3. P

ropo

rtio

n of

pa

tient

s w

ith a

n A

DE

4.

Num

ber o

f AD

Es

asso

ciat

ed w

ith

patie

nt h

arm

pe

r tot

al d

oses

de

liver

ed

5. C

ost s

avin

g

Chi

-squ

are

test

for t

rend

s

1. S

igni

fican

t red

uctio

n (m

edia

n =

2.04

[1.7

9–2

.70,

IQR

] in

base

line

vers

us 0

.65

[0.4

1–0.

87] p

ost-

inte

rven

tion,

p

= 0.

001

) 2.

Sig

nific

ant r

educ

tion

(med

ian

= 5.

07 [3

.79

–6.

02] i

n ba

selin

e ve

rsus

1.

30 [0

.87–

1.71

] pos

t-in

terv

entio

n,

p =

0.0

01)

3. S

igni

fican

t dec

line

(27%

at b

asel

ine

vers

us 9

% p

ost-

inte

rven

tion,

RR

=

0.33

, p <

0.0

01)

4. S

igni

fican

t red

uctio

n (R

R =

0.1

2 [0

.04

–0.

38, 9

5% C

I], p

< 0

.001

)5.

With

4,4

00

AD

Es

prev

ente

d ea

ch

year

, ann

ual c

ost s

avin

gs a

re

appr

oxim

atel

y $1

0,0

00,

00

0

Hig

hly

effe

ctiv

e, in

expe

nsiv

e pr

ogra

mm

e

Ap

pen

dix

E: I

ncl

ud

ed s

tud

ies,

so

rted

by

alp

hab

etic

al o

rder

Dückers et al

Safety and risk management in hospitals

36

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

37

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Dem

psey

, 20

04

Aus

tral

ia

UB

A

Acu

te m

edic

al a

rea

Per

iod

= Ja

nuar

y –

June

19

95 (

pre

-inte

rven

tion)

, Ja

nuar

y –

June

199

6 (p

ost-

inte

rven

tion)

, 20

01

(re

-eva

luat

ion

5 ye

ars

post

-in

terv

entio

n)

Aim

To te

st th

e ef

fect

iven

ess

of a

fa

lls p

reve

ntio

n pr

ogra

mm

e in

an

acu

te m

edic

al w

ard

Inte

rven

tio

nF

alls

pre

vent

ion

prog

ram

me,

co

nsis

ting

of a

n as

sess

men

t to

ol, a

n al

ert g

raph

ic, a

nd

educ

atio

n fo

r pat

ient

and

sta

ff

Co

ntr

ol

NA

Fal

l rat

e (p

er 1

,00

0 O

BD

) N

on-p

aire

d t-

test

Sig

nific

ant r

educ

tion

in fa

ll ra

te

(3.6

3 pr

e-in

terv

entio

n ve

rsus

2.2

9 po

st-in

terv

entio

n [p

= 0

.05

])

Fiv

e ye

ars

post

-inte

rven

tion,

fall

rate

ha

s do

uble

d (6

.8, s

igni

fican

ce n

ot

pres

ente

d)

Mar

gina

lly e

ffec

tive

falls

pr

even

tion

prog

ram

me,

but

re

sults

wer

e no

t sus

tain

able

af

ter 5

yea

rs

DeV

ita, 2

005

US

A

UB

A

Adv

ance

car

diac

life

su

ppor

t/m

edic

al e

mer

genc

y te

am

N =

10

cour

ses

and

138

indi

vidu

als

Per

iod

= M

arch

20

02 –

May

20

03

Aim

To d

evel

op m

ultid

isci

plin

ary

team

ski

lls a

nd im

prov

e M

ET

pe

rfor

man

ce

Inte

rven

tio

nH

uman

sim

ulat

ion

trai

ning

in

an e

duca

tiona

l env

ironm

ent t

o de

velo

p m

ultid

isci

plin

ary

team

sk

ills.

Cou

rse

com

pone

nts:

1. W

eb-b

ased

pre

sent

atio

n an

d pr

e-t

est b

efor

e th

e co

urse

2. B

rief r

einf

orci

ng tr

aini

ng

sess

ion

on th

e da

y of

the

cour

se3.

Thr

ee o

f fiv

e di

ffer

ent

sim

ulat

ed s

cena

rios

each

fo

llow

ed b

y4.

Deb

riefin

g an

d an

alys

is

with

the

team

Co

ntr

ol

NA

Pri

mar

y o

utc

om

e1.

Suc

cess

ful c

risis

m

anag

emen

t re

sulti

ng in

m

anne

quin

‘s

urvi

val’

Sec

on

dar

y o

utc

om

e2.

Com

plet

ion

of

orga

nisa

tiona

l and

pa

tient

car

e ta

sks

Non

-par

amet

ric te

sts:

Coc

hran

’s Q

an

d K

enda

ll’s

W

1. S

igni

fican

t im

prov

ed o

vera

ll si

mul

ator

‘sur

viva

l’ fr

om 0

% to

90

%

acro

ss th

e th

ree

sess

ions

in a

day

’s

cour

se (

Coc

hran

’s Q

= 1

2.6,

p

= 0.

002

). M

ost i

mpr

ovem

ent

betw

een

the

first

and

the

seco

nd

sess

ions

(p

= 0.

014)

rat

her t

han

betw

een

the

seco

nd a

nd th

ird

sess

ions

(p

= 0.

180

) (po

st-h

oc

anal

ysis

) 2.

Sig

nific

antly

impr

oved

ove

rall

task

co

mpl

etio

n ra

te fr

om 3

1% to

89

%,

and

each

sim

ulat

or r

ole

impr

oved

fr

om 1

0 to

45%

dur

ing

the

first

se

ssio

n to

80

to 9

5% d

urin

g th

e th

ird s

essi

on (

Ken

dall’

s W

= 0

.91,

p

< 0.

001

). Im

prov

emen

t firs

t and

se

cond

ses

sion

s (p

= 0

.002

) and

be

twee

n se

cond

and

third

(p

= 0

.011

) (po

st-h

oc a

naly

sis)

Trai

ning

mul

tidis

cipl

inar

y te

ams

usin

g si

mul

atio

n te

chno

logy

is

feas

ible

and

eff

ectiv

e in

im

prov

ing

team

per

form

ance

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

38

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

39

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Don

ald,

20

00

Uni

ted

Kin

gdom

RC

T

Eld

erly

car

e re

habi

litat

ion

war

d in

a c

omm

unity

ho

spita

l

N =

54

Per

iod

= F

ebru

ary

– S

epte

mbe

r 199

6 (9

mon

ths)

Aim

Com

paris

on o

f tw

o flo

orin

g ty

pes

– ca

rpet

and

vin

yl –

in

the

bed

area

s, a

nd tw

o ty

pes

of p

hysi

othe

rapy

conv

entio

nal t

hera

py a

nd

addi

tiona

l leg

str

engt

heni

ng

exer

cise

s –

in a

void

ing

falls

Inte

rven

tio

n 1

1a. A

ssig

ned

to w

ard

area

w

ith v

inyl

floo

r cov

erin

g an

d co

nven

tiona

l phy

siot

hera

py,

once

or t

wic

e da

ily1b

. As

1a p

lus

seat

ed le

g st

reng

then

ing

exer

cise

s (h

ip fl

exor

s an

d an

kle

dors

iflex

ors)

Inte

rven

tio

n 2

2a. A

ssig

ned

to w

ard

area

with

car

pet a

nd

conv

entio

nal p

hysi

othe

rapy

2b. A

s 2a

plu

s se

ated

leg

stre

ngth

enin

g ex

erci

ses

(hip

flex

ors

and

ankl

e do

rsifl

exor

s)

1. N

umbe

r of f

alle

rs

durin

g ad

mis

sion

2. N

umbe

r of f

ract

ure

falls

Man

n-W

hitn

ey U

-tes

t and

Chi

-squ

are

with

Fis

her’s

exa

ct te

st

1. N

o di

ffer

ence

in n

umbe

r of f

alle

rs:

• a

dditi

onal

exe

rcis

e gr

oup

vers

us

conv

entio

nal p

hysi

othe

rapy

= 4

fa

lls v

ersu

s 7

falls

, RR

= 0

.21,

95

% C

I = 0

.04

–1.2

(p

= 0.

12)

• c

arpe

t ver

sus

viny

l = 1

0 fa

lls

vers

us 1

fall,

RR

= 8

.30,

95%

C

I = 0

.95

–73

(p =

0.0

5)2.

No

fall

resu

lted

in a

frac

ture

The

re is

no

evid

ence

to s

uppo

rt

eith

er in

terv

entio

n in

pre

vent

ing

falls

on

a re

habi

litat

ion

war

d

Dückers et al

Safety and risk management in hospitals

38

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

39

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Don

oghu

e,

2005

Aus

tral

ia

UB

A

Acu

te a

ged

care

/eld

er c

are

war

d

N =

3,9

72 O

BD

(20

01),

3,

455

OB

D (

2002

),

num

bers

not

pre

sent

ed fo

r 20

03/2

004

Per

iod

= Ja

nuar

y 20

01

– A

ugus

t 20

02 (

pre

-in

terv

entio

n 19

mon

ths)

, A

ugus

t 20

02 –

Apr

il 20

04

(pos

t-in

terv

entio

n 15

m

onth

s)

Aim

To p

reve

nt h

igh-

risk

inpa

tient

s on

an

acut

e ag

ed c

are

war

d fr

om fa

lling

Inte

rven

tio

nP

atie

nts

at h

igh

risk

of

falli

ng a

re a

ccom

pani

ed b

y vo

lunt

eer C

Os

on w

eekd

ays

8.0

0am

–8.

00p

m. T

heir

prim

ary

obje

ctiv

e w

as to

ob

serv

e pa

tient

s fo

r sig

ns

of in

crea

sing

agi

tatio

n or

ris

ky b

ehav

iour

and

, if

need

ed, t

o re

assu

re th

e pa

tient

or c

onta

ct a

nur

se.

The

CO

s w

ere

also

invo

lved

in

oth

er a

ctiv

ities

, suc

h as

co

nver

satio

ns, p

layi

ng c

ards

, re

adin

g ou

t lou

d, p

layi

ng

mus

ic, p

ract

ical

hel

p in

find

ing

belo

ngin

g sa

nd s

ettin

g up

m

eals

Co

ntr

ol

NA

Fal

l rat

e (p

er 1

,00

0 O

BD

)C

hi-s

quar

e te

st

Sig

nific

antly

dec

reas

ed fa

ll ra

te. 1

5.6

falls

/1,0

00

OB

D (

SD

= 6

.5) (

befo

re)

vers

us 8

.8 fa

lls/1

,00

0 O

BD

(S

D =

3.0

) (a

fter

), O

R =

0.5

6 [9

5% C

I = 0

.45

–0.

68],

p <

0.0

001

Sig

nific

ant p

ositi

ve e

ffec

t of

inte

rven

tion

on fa

ll ra

te

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

40

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

41

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Eva

ns, 2

007

Aus

tral

ia

CB

A

Inpa

tient

car

e on

ICU

s,

surg

ical

uni

ts, m

edic

al u

nits

an

d E

Ds

Inte

rven

tion

(I) u

nits

: N =

10

Con

trol

(C

) uni

ts: N

= 1

0In

eac

h ar

m: 3

5,0

00

OB

Ds

at b

asel

ine

and

durin

g st

udy

perio

d

Inte

rven

tion

rollo

ut w

as

stag

gere

d, fr

om J

une

– A

ugus

t 20

03, w

ith

units

impl

emen

ting

the

inte

rven

tion

over

a 4

0-w

eek

perio

d

Aim

To a

sses

s th

e ef

fect

iven

ess

of a

n in

terv

entio

n pa

ckag

e in

ord

er to

impr

ove

volu

ntar

y in

cide

nt r

epor

ting

Inte

rven

tio

n•

Que

stio

nnai

re a

nd fo

cus

grou

p to

iden

tify

barr

iers

fo

r inc

iden

t rep

ortin

g•

Man

ual t

o im

prov

e kn

owle

dge

• E

duca

tion

sess

ions

• R

edes

ign

of r

epor

ting

proc

esse

s to

add

ress

co

ncer

ns•

One

-pag

e re

port

form

re

plac

ing

the

exis

ting

thre

e-p

age

form

and

a

free

-cal

l tel

epho

ne

serv

ice

• F

our f

eedb

ack

new

slet

ters

and

pr

esen

tatio

ns a

t mee

tings

Co

ntr

ol

No

inte

rven

tion,

ie u

sual

err

or

repo

rtin

g pr

oced

ures

1. In

cide

nt r

epor

ting

rate

s pe

r 10,

00

0 O

BD

or p

er 1

0,0

00

ED

atte

ndan

ces

2. R

epor

ter

desi

gnat

ion

3. R

epor

ting

form

at4.

Typ

es o

f inc

iden

ts

repo

rted

Fis

her’s

exa

ct te

st, b

inom

ial

regr

essi

on a

naly

sis

and

Poi

sson

re

gres

sion

ana

lysi

s

1. S

igni

fican

t inc

reas

e in

rep

ortin

g ra

tes

in in

patie

nt c

are

(add

ition

al

60.3

rep

orts

/10,

00

0 O

BD

[95%

CI

= 23

.8–

96.

8],

p <

0.0

01) a

nd in

ED

s (a

dditi

onal

39.

5 re

port

s/10

,00

0 E

D

atte

ndan

ces

[95%

= C

I 17.

0–

62.0

],

p <

0.0

01)

2. M

ore

repo

rts

wer

e ge

nera

ted

: •

by d

octo

rs in

ED

s (a

dditi

onal

9.5

re

port

s/10

,00

0 E

D a

ttend

ance

s [9

5% C

I = 2

.2–1

6.8

], p

= 0

.001

)•

by n

urse

s in

inpa

tient

are

as

(add

ition

al 5

9.0

repo

rts/

10,0

00

OB

Ds

[95%

CI =

23.

9–

94.1

],

p <

0.0

01)

• an

onym

ousl

y (a

dditi

onal

20.

2 re

port

s/10

,00

0 O

BD

s an

d E

D

atte

ndan

ces

com

bine

d [9

5% C

I =

12.6

–27.

8],

p <

0.0

01)

3. M

ajor

ity (

79%

) of r

epor

ts in

I-un

its

wer

e re

port

ed u

sing

one

-pag

e fo

rm,

with

21%

sub

mitt

ed th

roug

h th

e ca

ll ce

ntre

4. R

elat

ive

num

ber o

f fal

l-re

late

d re

port

s de

crea

sed

in I-

units

(36

.1%

be

fore

ver

sus

23.8

% a

fter

, RR

=

2.01

[95%

CI =

1.7

–2.3

], p

< 0

.001

).

I-un

its h

ad m

ore

docu

men

tatio

n-re

late

d, c

linic

al m

anag

emen

t an

d ag

gres

sion

-rel

ated

inci

dent

s co

mpa

red

with

C-u

nits

The

inte

rven

tion

units

rep

orte

d a

grea

ter v

arie

ty a

nd n

umbe

r of

inci

dent

s du

ring

the

stud

y, w

ith

impr

oved

rep

ortin

g by

doc

tors

fr

om a

low

bas

elin

e. T

here

was

co

nsid

erab

le h

eter

ogen

eity

be

twee

n re

port

ing

rate

s in

di

ffer

ent t

ypes

of u

nits

Dückers et al

Safety and risk management in hospitals

40

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

41

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Fer

tlem

an,

2005

Uni

ted

Kin

gdom

UB

A

Acu

te m

edic

al s

ervi

ces

– ge

nera

l hos

pita

l

N =

62

patie

nts

(p

re-in

terv

entio

n)N

= 5

7 pa

tient

s (in

terv

entio

n)

Per

iod

= A

pril

– Ju

ly 2

003

Aim

To r

educ

e m

edic

atio

n er

rors

an

d pr

escr

ibin

g co

sts

Inte

rven

tio

nA

dditi

on o

f a p

harm

acis

t to

the

post

-tak

e m

edic

al te

am

Co

ntr

ol

NA

1. A

ccur

acy

of

med

icat

ion

hist

ory

2. P

resc

ribin

g co

sts

3. M

edic

atio

n-as

soci

ated

ris

ks

Chi

-squ

are

test

1. D

etec

ted

disc

repa

ncie

s be

twee

n th

e ad

mis

sion

and

the

phar

mac

ist-

deriv

ed d

rug

hist

ory

incr

ease

d fr

om 5

3% to

98%

(pr

e-in

terv

entio

n ve

rsus

inte

rven

tion

perio

d)2.

Mea

n sa

ving

from

dru

gs s

topp

ed

durin

g ad

mis

sion

was

£88

.60

per

patie

nt p

er y

ear d

urin

g in

terv

entio

n pe

riod

vers

us £

5.52

in p

re-

inte

rven

tion

perio

d3.

Maj

ority

of r

ecom

men

datio

ns

by p

harm

acis

t wer

e of

min

or o

r m

oder

ate

sign

ifica

nce

(53%

and

53

% r

espe

ctiv

ely)

and

5%

wer

e cl

assi

fied

as p

reve

ntin

g a

pote

ntia

lly

maj

or in

cide

nt

The

pre

senc

e of

a p

harm

acis

t on

a p

ost-

take

war

d ro

und

impr

oved

the

accu

racy

of

drug

-his

tory

doc

umen

tatio

n,

redu

ced

pres

crib

ing

cost

s an

d de

crea

sed

the

pote

ntia

l ris

k to

pa

tient

s

Frae

nkel

, 20

03

Aus

tral

ia

ITS

(bu

t ana

lyse

d as

UB

A)

ICU

in o

ne h

ospi

tal

N =

12

beds

Per

iod

= Ja

nuar

y 19

95 –

D

ecem

ber 1

998

(23

mon

ths

pre

-inte

rven

tion

and

25

mon

ths

post

-inte

rven

tion)

Aim

To q

uant

ify th

e qu

ality

be

nefit

s an

d st

aff p

erce

ptio

ns

of a

com

pute

rised

clin

ical

in

form

atio

n sy

stem

im

plem

enta

tion

in a

n IC

U

Inte

rven

tio

nC

linic

al in

form

atio

n sy

stem

, rep

laci

ng p

aper

-ba

sed

char

ts o

f pat

ient

ob

serv

atio

ns, c

linic

al r

ecor

ds,

resu

lts r

epor

ting

and

drug

pr

escr

ibin

g

Co

ntr

ol

NA

1. F

requ

ency

of

clin

ical

AE

s2.

Per

cept

ion

of ti

me

take

n in

nur

sing

do

cum

enta

tion

Chi

-squ

are

test

1. N

umbe

r of c

linic

al A

Es

by c

ateg

ory:

• M

edic

atio

n in

cide

nts

decr

ease

d fr

om 8

5 to

55

(p <

0.0

5)•

Intr

aven

ous

inci

dent

s de

crea

sed

from

140

to 4

6 (p

< 0

.001

)•

Ven

tilat

ion

inci

dent

s de

crea

sed

from

51

to 1

0 (p

< 0

.001

)•

Pre

ssur

e ul

cers

rem

aine

d st

able

(c

hang

ed fr

om 7

1 to

51,

p =

0.1

52)

• O

ther

inci

dent

s in

crea

sed

from

20

1 to

323

(p

< 0.

001

)

2. S

igni

fican

t dec

reas

e in

per

cent

age

of n

urse

s sp

endi

ng le

ss th

an 1

0 m

inut

es d

ocum

entin

g no

tes

(22%

be

fore

ver

sus

82%

aft

er, p

< 0

.001

)

Sig

nific

ant r

educ

tion

in n

umbe

r of

key

AE

s, a

long

side

pos

itive

nu

rsin

g st

aff p

erce

ptio

ns a

bout

tim

e in

vest

men

t

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

42

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

43

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Har

ris, 2

007

US

A

ITS

(bu

t ana

lyse

d as

UB

A)

Med

ical

ICU

, sur

gica

l IC

U

and

card

ioth

orac

ic IC

U

Pre

-inte

rven

tion:

16,

089

patie

nt d

ays

Pos

t-in

terv

entio

n: 1

7,12

6 pa

tient

day

s

Per

iod

= Ja

nuar

y 20

02

– M

ay 2

004

(10

mon

ths

pre

-inte

rven

tion,

14

mon

ths

inte

rven

tion

and

5 m

onth

s po

st-in

terv

entio

n)

Aim

To in

crea

se p

atie

nt-s

afet

y ev

ent r

epor

ting

in th

ree

ICU

s us

ing

a ne

w, v

olun

tary

, car

d-ba

sed

even

t rep

ortin

g sy

stem

an

d to

com

pare

and

eva

luat

e ob

serv

ed d

iffer

ence

s in

re

port

ing

amon

g he

alth

care

w

orke

rs a

cros

s IC

Us

Inte

rven

tio

nIm

plem

enta

tion

of a

n an

onym

ous

pape

r-ba

sed

erro

r rep

ort t

ool (

as o

ppos

ed

to e

xist

ing

onlin

e to

ols)

Co

ntr

ol

NA

1. R

epor

ted

patie

nt-

safe

ty e

vent

s/1,

00

0 pa

tient

day

s2.

Rep

orte

r de

sign

atio

n3.

Sev

erity

of r

epor

ted

inci

dent

s

Chi

-squ

are

test

1. S

igni

fican

t inc

reas

e in

rep

ortin

g ra

tes

(pre

-inte

rven

tion

= 20

.4

even

ts/1

,00

0 pa

tient

day

s ve

rsus

41

.7 r

epor

ted

even

ts/1

,00

0 pa

tient

da

ys p

ost-

inte

rven

tion;

rat

e ra

tio =

2.

05 [9

5% C

I = 1

.79

–2.3

4])

2. N

urse

s su

bmitt

ed th

e m

ajor

ity

of r

epor

ts (

post

-inte

rven

tion:

nu

rses

= 6

7.1%

, doc

tors

= 2

3.1%

, ot

her r

epor

ters

= 9

.5%

). D

octo

rs

expe

rienc

ed th

e gr

eate

st in

crea

se

in r

epor

ting

rate

(do

ctor

s: 4

3-f

old,

nu

rses

: 1.7

-fol

d, o

ther

rep

orte

rs:

4.3

-fol

d) r

elat

ive

to p

re-in

terv

entio

n ra

tes

3. S

igni

fican

t diff

eren

ces

in

the

repo

rtin

g of

har

m b

y jo

b de

scrip

tion:

31.

1% o

f rep

orts

from

nu

rses

, 36.

2% fr

om o

ther

sta

ff

and

17.0

% fr

om d

octo

rs d

escr

ibed

ev

ents

that

did

not

rea

ch/a

ffec

t th

e pa

tient

(p

< 0.

001

); 3

3.9

% o

f re

port

s fr

om d

octo

rs, 2

7.2%

from

nu

rses

and

13.

0%

from

oth

er s

taff

de

scrib

ed e

vent

s th

at c

ause

d ha

rm

(p <

0.0

05)

Rep

ortin

g ra

tes

incr

ease

d si

gnifi

cant

ly, w

ith s

igni

fican

t di

ffer

ence

s in

rep

ortin

g be

havi

our b

y ty

pe o

f hea

lthca

re

wor

ker a

nd IC

U ty

pe

Dückers et al

Safety and risk management in hospitals

42

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

43

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Jain

, 20

06

US

A

UB

A

Med

ical

sur

gica

l IC

U (

28

beds

)

N =

ran

dom

rev

iew

of a

t le

ast 2

0 ch

arts

per

mon

th (±

20

% s

ampl

ing)

Per

iod

= O

ctob

er 2

00

0 –

Oct

ober

20

02 (

base

line)

, O

ctob

er 2

002

– O

ctob

er

2003

(in

terv

entio

n)

Aim

Red

uctio

n in

AE

s in

ICU

s by

Q

I foc

usin

g on

team

wor

k an

d cu

lture

cha

nge

Inte

rven

tio

nC

ombi

ned

inte

rven

tion,

in

clud

ing

:1.

doc

tor-

led

mul

tidis

cipl

inar

y ro

unds

2. d

aily

bed

-flo

w m

eetin

gs to

ac

cess

bed

ava

ilabi

lity

3. im

plem

enta

tion

of

evid

ence

-bas

ed p

ract

ices

re

late

d to

thre

e qu

ality

in

itiat

ives

4. c

ultu

re c

hang

e w

ith a

foru

m

on te

am d

ecis

ion-

mak

ing

The

inte

rven

tions

wer

e im

plem

ente

d on

e-b

y-on

e ov

er

a 12

-mon

th p

erio

d

Co

ntr

ol

NA

1. A

Es

per I

CU

day

2. V

entil

ator

-as

soci

ated

pn

eum

onia

rat

e pe

r 1,

00

0 ve

ntila

tion

days

3. B

lood

stre

am

infe

ctio

n ra

te p

er

1,0

00

line

days

4. N

osoc

omia

l urin

ary

trac

t inf

ectio

n ra

te

per 1

,00

0 ca

thet

er

days

5. L

OS

per

epi

sode

6. M

orta

lity

rate

7. C

osts

per

ICU

ep

isod

e

Chi

-squ

are

test

1. S

tron

g do

wnw

ard

tren

d (s

igni

fican

ce n

ot p

rovi

ded)

2. S

igni

fican

tly lo

wer

infe

ctio

n ra

te

(7.5

at b

asel

ine

vers

us 3

.2 a

t fol

low

-up

, p =

0.0

40)

3. S

igni

fican

tly lo

wer

infe

ctio

n ra

te

(5.9

at b

asel

ine

vers

us 3

.1 a

t fol

low

-up

, p =

0.0

31)

4. N

o si

gnifi

cant

cha

nge

5. D

ownw

ard

tren

d (s

igni

fican

ce n

ot

prov

ided

by

the

auth

ors)

6. N

o si

gnifi

cant

cha

nge

7. D

ecre

ased

by

21%

(fr

om $

3,40

6 to

$

2,97

3, s

igni

fican

ce n

ot p

rovi

ded)

QI m

ay h

ave

cont

ribut

ed to

im

prov

emen

ts

Kin

g, 2

003

Can

ada

CB

A

Pae

diat

ric in

patie

nt c

are

N =

2 m

edic

al in

patie

nt u

nits

(in

terv

entio

n) a

nd 1

med

ical

an

d 2

surg

ical

uni

ts (

cont

rol)

Per

iod

= A

pril

1993

– M

arch

19

96

(bas

elin

e 36

mon

ths)

, A

pril

199

6 –

Dec

embe

r 19

96

(impl

emen

tatio

n 9

mon

ths)

, Jan

uary

199

7 –

Dec

embe

r 199

9 (p

ost-

inte

rven

tion

36 m

onth

s)

Aim

To a

sses

s th

e im

pact

of a

C

PO

E s

yste

m o

n m

edic

atio

n er

rors

and

AD

Es

in p

aedi

atric

in

patie

nts

Inte

rven

tio

nC

PO

E w

ithou

t clin

ical

de

cisi

on s

uppo

rt, i

nter

face

d w

ith th

e la

bora

tory

sys

tem

, bu

t not

with

the

phar

mac

y co

mpu

ter

Co

ntr

ol

Han

dwrit

ten

med

icat

ion

orde

rs

1. M

edic

atio

n er

ror

rate

(pe

r 1,0

00

patie

nt d

ays)

2. P

oten

tial A

DE

s ra

te3.

AD

Es

rate

Poi

sson

ana

lysi

s of

rat

e ra

tios

1. S

igni

fican

t red

uctio

n (R

R =

1.5

4 [9

5% C

I = 1

.27–

1.88

], p

< 0

.001

)2.

Sig

nific

ant i

ncre

ase

(RR

= 0

.24

[95%

CI =

0.0

9–

0.68

], p

< 0

.001

)3.

No

chan

ge (

RR

= 1

.30

[95%

CI =

0.

47–

3.52

], p

= 0

.60

)

The

ove

rall

med

icat

ion

erro

r rat

e an

d po

tent

ial A

DE

s de

crea

sed,

w

ithou

t an

effe

ct o

n A

DE

s

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

44

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

45

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Koz

er, 2

005

Can

ada

RC

T

Pae

diat

ric E

D

N =

376

ord

er s

heet

s (in

terv

entio

n [I

] gro

up)

N =

411

ord

er s

heet

s (c

ontr

ol [C

] gro

up)

Per

iod

= Ju

ly 2

001

Aim

To d

eter

min

e w

heth

er th

e us

e of

a s

truc

ture

d or

der

shee

t red

uces

the

inci

denc

e of

med

icat

ion

erro

rs in

pa

edia

tric

ED

Inte

rven

tio

nU

se o

f pre

-prin

ted,

form

atte

d pr

escr

iptio

n or

der s

heet

s

Co

ntr

ol

Use

of b

lank

pre

scrip

tion

orde

r she

ets

1. M

edic

atio

n er

ror

rate

2. M

edic

atio

n er

ror

seve

rity

Chi

-squ

are

test

and

mul

tivar

iabl

e lo

gist

ic r

egre

ssio

n

1. S

igni

fican

t red

uctio

n (9

.8%

in

I-gr

oup

vers

us 1

6.6%

in C

-gro

up,

OR

= 0

.55

[95%

CI =

0.3

4–

0.9

0],

p

< 0.

05)

2. S

igni

fican

t red

uctio

n (3

.7%

in

I-gr

oup

vers

us 8

.8%

in C

-gro

up,

OR

= 0

.39

[95%

CI =

0.2

1–0.

77],

p

< 0.

05)

The

use

of p

re-p

rinte

d st

ruct

ured

ord

er fo

rms

sign

ifica

ntly

red

uces

med

icat

ion

erro

r rat

es a

nd s

ever

ity o

f the

er

rors

am

ong

paed

iatr

ic p

atie

nts

in th

e E

D

Lane

, 199

9

US

A

UB

A

Med

ical

-sur

gica

l/cr

itica

l ca

re p

atie

nts

N =

101

(ba

selin

e)N

= 9

8 (p

ost-

inte

rven

tion)

Per

iod

= 19

88 (

base

line)

, 19

95 (

post

-inte

rven

tion)

Aim

To e

valu

ate

the

effe

ctiv

enes

s of

a fa

lls p

reve

ntio

n pr

ogra

mm

e in

red

ucin

g pa

tient

fall

rate

Inte

rven

tio

nF

alls

pre

vent

ion

prog

ram

me,

in

clud

ing

:•

iden

tifyi

ng p

atie

nts

at r

isk

of fa

lling

• es

tabl

ishi

ng g

uide

lines

for

inte

rven

tions

pro

mot

ing

patie

nt s

afet

y fo

r pat

ient

s

at r

isk

Co

ntr

ol

NA

1. F

all r

ate

(fal

ls p

er

1,0

00

patie

nt d

ays)

2. In

jury

rat

e af

ter f

all

(num

ber o

f inj

urie

s pe

r 10

0 fa

lls)

Sta

tistic

al m

etho

dolo

gy is

unc

lear

1. N

o ch

ange

in fa

ll ra

te (

2.27

[b

asel

ine

] ver

sus

3.89

[pos

t-in

terv

entio

n],

p >

0.0

5)2.

Dec

reas

e in

inju

ry r

ate

(27.

7%

[bas

elin

e] v

ersu

s 8.

2% [p

ost-

inte

rven

tion

], p

-val

ue n

ot p

rovi

ded)

No

effe

ct o

f fal

ls p

reve

ntio

n pr

ogra

mm

e in

inpa

tient

s at

ris

k of

falli

ng

Dückers et al

Safety and risk management in hospitals

44

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

45

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Lars

en, 2

005

US

A

UB

A

Pae

diat

ric in

patie

nt c

are

N =

12,

109

infu

sion

dos

es

(pre

-inte

rven

tion)

N =

12,

377

infu

sion

dos

es

(pos

t-in

terv

entio

n)

Per

iod

= 20

02 (1

2 m

onth

s pr

e-in

terv

entio

n), 2

003

(12

mon

ths

post

-inte

rven

tion)

Aim

To d

eter

min

e if

com

bini

ng

stan

dard

dru

g co

ncen

trat

ions

w

ith s

mar

t-pu

mp

tech

nolo

gy

redu

ces

repo

rted

med

icat

ion-

infu

sion

err

ors

Inte

rven

tio

n1.

Sta

ndar

d dr

ug

conc

entr

atio

ns

deve

lopm

ent

2. ‘S

mar

t’ sy

ringe

pum

ps

sele

ctio

n cr

iteria

3. H

uman

-eng

inee

red

med

icat

ion

labe

ls r

epla

cing

ph

arm

acy-

gene

rate

d la

bels

Co

ntr

ol

NA

1. R

epor

ted

CM

I err

or

rate

(pe

r 1,0

00

dose

s)2.

Adh

eren

ce to

in

terv

entio

n

2-sa

mpl

e te

st o

f pro

port

ion

1. E

rror

rat

e de

crea

sed

from

3.1

to

0.8

per 1

,00

0 do

ses

(abs

olut

e ris

k re

duct

ion

= 2.

3 [9

5% C

I = 1

.1-3

.4],

p

< 0.

001

)2.

87%

of C

MIs

in n

eona

tal I

CU

s an

d >

99%

in o

ther

are

as o

f the

hos

pita

l us

ed s

tand

ard

drug

con

cent

ratio

ns

afte

r the

impl

emen

tatio

n

The

use

of s

tand

ard

drug

co

ncen

trat

ions

, sm

art s

yrin

ge

pum

ps a

nd u

ser-

frie

ndly

la

bels

red

uces

rep

orte

d er

rors

as

soci

ated

with

CM

Is. S

tand

ard

drug

con

cent

ratio

ns c

an b

e ch

osen

to a

llow

mos

t neo

nate

s to

rec

eive

nee

ded

med

icat

ions

w

ithou

t con

cern

s re

late

d to

ex

cess

flui

d ad

min

istr

atio

n

Leap

e, 1

999

US

A

CB

A

Inte

nsiv

e ca

re

Inte

rven

tion

(I) g

roup

:N

= 7

5 (p

re-in

terv

entio

n)N

= 7

5 (p

ost-

inte

rven

tion)

Con

trol

(C

) gro

up:

N =

50

(pre

-inte

rven

tion)

N =

75

(pos

t-in

terv

entio

n)

Per

iod

= F

ebru

ary

1993

July

199

3 (p

re-in

terv

entio

n),

Oct

ober

199

4 –

July

199

5 (p

ost-

inte

rven

tion)

Aim

To m

easu

re th

e ef

fect

of

phar

mac

ist p

artic

ipat

ion

on

med

ical

rou

nds

in th

e IC

U o

n th

e ra

te o

f pre

vent

able

AD

Es

caus

ed b

y or

derin

g er

rors

Inte

rven

tio

nS

enio

r pha

rmac

ist

part

icip

ates

in d

octo

rs’ r

ound

s (e

ach

mor

ning

), is

pre

sent

in

the

unit

for c

onsu

ltatio

n an

d as

sist

ance

to th

e nu

rsin

g st

aff

durin

g th

e re

st o

f the

mor

ning

, an

d is

ava

ilabl

e on

cal

l as

nece

ssar

y th

roug

hout

the

day

Co

ntr

ol

Usu

al p

ract

ice

whe

re th

e ph

arm

acis

t is

avai

labl

e in

the

unit

for p

art o

f the

day

, but

do

es n

ot m

ake

roun

ds

1. R

ate

of A

DE

s (p

er

1,0

00

patie

nt d

ays)

2. R

ate

of p

reve

ntab

le

AD

Es

in th

e or

derin

g st

age

(per

1,

00

0 pa

tient

day

s)3.

Acc

epta

nce

of in

terv

entio

n re

com

men

ded

by

the

phar

mac

ist

Unp

aire

d t-

test

1. S

igni

fican

t red

uctio

n (1

1.6

[I-g

roup

, af

ter]

ver

sus

46.6

[C-g

roup

, aft

er],

p

< 0.

001

)2.

Sig

nific

ant r

educ

tion

(3.5

[I-g

roup

, af

ter]

ver

sus

12.4

[C-g

roup

, aft

er],

p

< 0.

001

)3.

Maj

ority

(36

6 of

398

) of t

he

phar

mac

ist i

nter

vent

ions

wer

e re

late

d to

dru

g or

derin

g, o

f whi

ch

362

(99

%) w

ere

acce

pted

by

doct

ors

Pre

senc

e of

pha

rmac

ist w

as

asso

ciat

ed w

ith a

sub

stan

tially

lo

wer

AD

E r

ate

and

high

ac

cept

ance

rat

e

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

46

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

47

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Lehm

ann,

20

07

US

A

ITS

(bu

t ana

lyse

d as

UB

A)

Med

ical

uni

vers

ity h

ospi

tal

N =

1 h

ospi

tal

Per

iod

= O

ctob

er 1

999

– A

pril

2007

(in

terv

entio

n st

arte

d in

Oct

ober

20

00

)

Aim

Dev

elop

men

t of a

non

-pu

nitiv

e re

port

ing

syst

em

and

CP

OE

to d

ecre

ase

the

pote

ntia

l for

dru

g ha

rm

Inte

rven

tio

n•

Str

ateg

y se

ssio

ns w

ith

seni

or m

anag

emen

t abo

ut

non-

puni

tive

repo

rtin

g (A

utum

n 19

99)

• R

evis

ed m

edic

atio

n ev

ent

repo

rtin

g po

licy

(Oct

ober

20

00

)•

Impl

emen

tatio

n of

CP

OE

th

roug

hout

the

orga

nisa

tion

(Dec

embe

r 20

05)

Co

ntr

ol

NA

1. T

he n

umbe

r of e

rror

re

port

s re

ceiv

ed

per m

onth

2. T

he ty

pe o

f re

port

ed e

rror

s

AN

OV

A

1. S

igni

fican

t inc

reas

e (1

9 re

port

s be

fore

inte

rven

tion

star

ted

vers

us

102

repo

rts

afte

r sta

rt, p

< 0

.001

)2.

The

type

of r

epor

ted

erro

rs

chan

ged.

In p

re-in

terv

entio

n ph

ase,

maj

ority

of r

epor

ted

inci

dent

s oc

curr

ed a

fter

med

icat

ion

adm

inis

trat

ion,

lead

ing

to a

ctua

l pa

tient

har

m o

r del

ayed

car

e. In

po

st-in

terv

entio

n ph

ase,

maj

ority

of

rep

orte

d er

rors

occ

urre

d du

ring

med

icat

ion-

use

proc

esse

s be

fore

ac

tual

dru

g ad

min

istr

atio

n

Sig

nific

ant i

ncre

ase

in th

e nu

mbe

r of r

epor

ts a

nd

subs

tant

ial c

hang

e in

type

of

repo

rted

err

ors

Dückers et al

Safety and risk management in hospitals

46

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

47

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Man

ning

, 20

07

US

A

RC

T

Hos

pita

l dis

char

ge p

atie

nts

N =

138

Per

iod

= M

ay 2

004

Feb

ruar

y 20

05

Aim

To d

eter

min

e w

heth

er th

e 3D

m

edic

atio

n di

scha

rge

form

, re

lativ

e to

MD

W, r

educ

es

self-

repo

rted

med

icat

ion

erro

rs a

nd im

prov

es

patie

nt s

atis

fact

ion

and

unde

rsta

ndin

g

Inte

rven

tio

nA

new

edu

catio

n to

ol (

3D).

F

eatu

res

incl

ude:

1. S

pace

in w

hich

a ta

blet

or

pill

is a

ffix

ed a

nd d

ispl

ayed

2. T

rade

nam

e3.

Uni

t str

engt

h4.

Num

ber (

and

/or f

ract

ion)

of

units

to b

e ta

ken

5. P

urpo

se (

indi

catio

n)6.

Com

men

t/ca

utio

n7.

Lar

ger f

ont

8. C

ard

stoc

k du

rabi

lity

9. A

rec

onci

liatio

n fe

atur

e

Co

ntr

ol

Sta

ndar

d M

DW

1. N

umbe

r of

self-

repo

rted

m

edic

atio

n er

rors

2. P

atie

nt s

atis

fact

ion

with

dis

char

ge fo

rm3.

Pat

ient

un

ders

tand

ing

of p

resc

ribed

m

edic

atio

n in

stru

ctio

ns

T-te

st a

nd M

ann-

Whi

tney

U-t

est

1. N

o ef

fect

(I-

grou

p ve

rsus

C-g

roup

=

0.78

[SD

= 0

.42

] ver

sus

0.79

[SD

=

0.41

], p

= 0

.876

)2.

No

effe

ct (

I = g

roup

ver

sus

C-g

roup

=

4.24

[SD

= 0

.70

] ver

sus

4.26

[SD

=

0.88

], p

= 0

.520

4)3.

Bet

ter u

nder

stan

ding

of m

edic

atio

n in

stru

ctio

ns (

I-gr

oup

vers

us

C-g

roup

= 1

.96

[SD

= 0

.76

] ver

sus

1.66

[SD

= 0

.69

], p

= 0

.028

2)

Bot

h to

ols

are

asso

ciat

ed w

ith

high

leve

ls o

f pat

ient

sat

isfa

ctio

n an

d lo

w r

ates

of s

elf-

repo

rted

m

edic

atio

n er

ror.

3D a

ppea

rs to

pr

omot

e pa

tient

und

erst

andi

ng

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

48

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

49

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Pao

lett

i, 20

07

US

A

CB

A

Inpa

tient

nur

sing

uni

ts

Inte

rven

tion

1 (c

ardi

ac

tele

met

ry u

nit)

:N

= 3

08 d

oses

(p

re-in

terv

entio

n)

N =

318

dos

es (

post

-in

terv

entio

n)

Inte

rven

tion

2 (m

edic

al-

surg

ical

uni

t):

N =

320

dos

es

(pre

-inte

rven

tion)

N =

310

dos

es (

post

-in

terv

entio

n)

Con

trol

(ca

rdia

c te

lem

etry

un

it):

N =

30

6 do

ses

(pre

-inte

rven

tion)

N

= 3

06

dose

s (p

ost-

inte

rven

tion)

Per

iod

= 20

03–2

005

(im

plem

enta

tion

perio

d =

Aug

ust 2

003

– J

uly

2004

)

Aim

The

impl

emen

tatio

n of

a

mul

tidis

cipl

inar

y ap

proa

ch

to s

yste

mat

ical

ly d

ecre

ase

med

icat

ion

erro

rs

Inte

rven

tio

nT

he u

se o

f obs

erva

tion

met

hodo

logy

, ele

ctro

nic

med

icat

ion-

adm

inis

trat

ion

reco

rds

and

bar-

code

d m

edic

atio

n ad

min

istr

atio

n

Co

ntr

ol

Usu

al c

are

1. M

edic

atio

n er

ror

rate

2. A

ccur

acy

rate

of

med

icat

ion

adm

inis

trat

ion

Sta

tistic

al m

etho

dolo

gy is

unc

lear

1. M

edic

atio

n er

ror r

ates

dec

reas

ed

(-35

.9%

cha

nge

from

bas

elin

e,

p =

0.03

5) in

inte

rven

tion

grou

p 2,

was

unc

hang

ed in

inte

rven

tion

grou

p 1

(-24

.1%

cha

nge

from

ba

selin

e, p

= 0

.065

) and

was

un

chan

ged

in c

ontr

ol g

roup

(5.

1%

chan

ge fr

om b

asel

ine,

p =

0.7

62).

2.

Impr

oved

acc

urac

y ra

te (

86.5

%

befo

re v

ersu

s 97

% a

fter

, p-v

alue

no

t pro

vide

d)

Mul

tidis

cipl

inar

y ap

proa

ch

redu

ced

erro

r rat

es, b

ut d

id n

ot

reac

h st

atis

tical

sig

nific

ance

Dückers et al

Safety and risk management in hospitals

48

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

49

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Ple

ws-

Oga

n,

2004

US

A

UB

A

Am

bula

tory

inte

rnal

m

edic

ine

prac

tice

N =

NC

Per

iod

= 1

year

bef

ore

and

1 ye

ar a

fter

the

impl

emen

tatio

n

Aim

To d

eter

min

e th

e fe

asib

ility

an

d ef

fect

iven

ess

of c

linic

ian-

base

d ne

ar m

iss/

AE

vol

unta

ry

repo

rtin

g, c

oupl

ed w

ith

syst

em a

naly

sis

and

rede

sign

as

a m

odel

for c

ontin

uous

qu

ality

impr

ovem

ent i

n th

e am

bula

tory

set

ting

Inte

rven

tio

n•

Rep

ortin

g sy

stem

for n

ear

mis

s or

AE

s•

Roo

t cau

se a

naly

sis

by

com

mitt

ee•

Impr

ovem

ents

of p

ract

ice,

ed

ucat

ion,

sys

tem

s an

d eq

uipm

ent

Co

ntr

ol

NA

1. C

linic

al-b

ased

nea

r m

isse

s an

d A

Es

2. T

ype

of r

epor

ter

3. T

ype

of e

rror

4. A

ccep

tanc

e of

re

com

men

datio

ns

Sta

tistic

al m

etho

dolo

gy is

unc

lear

1. N

umbe

r of r

epor

ts in

crea

sed

from

5

to 1

00

repo

rts

(incl

udin

g 83

nea

r m

isse

s an

d 17

AE

s)2.

44%

of t

he e

vent

s w

ere

repo

rted

by

doct

ors,

22%

by

resi

dent

s, 3

1% b

y nu

rses

and

3%

by

man

ager

s3.

Err

ors

invo

lved

med

icat

ion

(47%

), la

b or

X-r

ay (

22%

),

offic

e ad

min

istr

atio

n (2

1%) a

nd

com

mun

icat

ion

proc

esse

s (1

0%

)4.

75%

of r

ecom

men

datio

ns w

ere

impl

emen

ted

durin

g th

e st

udy

perio

d

The

inte

rven

tion

was

eff

ectiv

e in

incr

easi

ng e

rror

rep

ortin

g an

d in

pro

mot

ing

syst

em c

hang

e to

im

prov

e ca

re a

nd p

reve

nt e

rror

s

Poo

n, 2

00

6

US

A

UB

A

Tert

iary

car

e (7

35-b

ed)

acad

emic

med

ical

cen

tre

N =

155

,16

4 (p

re-

inte

rven

tion)

and

253

,98

4 (p

ost-

inte

rven

tion)

di

spen

sed

med

icat

ion

dose

s

Per

iod

= 20

03–2

004

(20

m

onth

s)

Aim

Red

uctio

n in

dis

pens

ing

erro

rs a

nd p

oten

tial A

DE

s by

ba

r-co

de te

chno

logy

Inte

rven

tio

nA

bar

-cod

e-a

ssis

ted

stor

age

and

retr

ieva

l sys

tem

im

plem

ente

d in

thre

e co

nfig

urat

ions

(in

two,

all

dose

s w

ere

scan

ned

once

du

ring

the

disp

ensi

ng p

roce

ss

and

in o

ne, a

dos

e w

as

scan

ned

if se

vera

l dos

es o

f th

e sa

me

med

icat

ion

wer

e be

ing

disp

ense

d)

Co

ntr

ol

NA

Pri

mar

y o

utc

om

es1.

Tar

get d

ispe

nsin

g er

ror r

ate

2. T

arge

t pot

entia

l A

DE

s ra

te

Sec

on

dar

y o

utc

om

e3.

Nat

ure

of ta

rget

er

rors

Fis

her e

xact

test

Ove

rall

effe

ct, a

cros

s th

e th

ree

conf

igur

atio

ns:

1. 8

5% r

educ

tion

(err

or r

ate

pre

= 0.

37%

ver

sus

post

= 0

.06%

)2.

74%

red

uctio

n (A

DE

rat

e pr

e =

0.17

% v

ersu

s po

st =

0.0

4%)

3. D

ecre

ase

in w

rong

med

icat

ion

erro

r ra

te (

56%

red

uctio

n)

Sub

stan

tial d

ecre

ase

in

disp

ensi

ng e

rror

s an

d po

tent

ial

AD

Es

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

50

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

51

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Ram

nara

yan,

20

06a

Uni

ted

Kin

gdom

UB

A

Pae

diat

ric e

mer

genc

y ro

om

N =

751

cas

e ep

isod

es,

hand

led

by 7

6 do

ctor

s (ie

co

nsul

tant

, reg

istr

ar, s

enio

r ho

use

offic

er o

r stu

dent

)

Per

iod

= F

ebru

ary

– A

ugus

t 20

02

Aim

To a

sses

s th

e im

pact

of a

no

vel d

iagn

ostic

rem

inde

r sy

stem

(IS

AB

EL)

on

the

qual

ity o

f clin

ical

dec

isio

ns

mad

e by

var

ious

gra

des

of c

linic

ians

dur

ing

acut

e as

sess

men

t

Inte

rven

tio

nW

eb-b

ased

dia

gnos

tic

rem

inde

r sys

tem

that

su

gges

ts im

port

ant d

iagn

oses

du

ring

clin

ical

ass

essm

ent,

ie

a C

DS

S

Co

ntr

ol

NA

Pri

mar

y o

utc

om

e1.

Num

ber o

f di

agno

stic

err

ors

of

omis

sion

Sec

on

dar

y o

utc

om

es2.

Qua

lity

of

diag

nost

ic te

st

orde

ring

and

trea

tmen

t pla

n3.

Num

ber o

f irr

elev

ant

diag

nose

s co

ntai

ned

with

in th

e di

agno

stic

wor

kup

4. P

ropo

rtio

n of

ca

se e

piso

des

in w

hich

at l

east

on

e ad

ditio

nal

‘impo

rtan

t’ di

agno

sis,

test

or

trea

tmen

t dec

isio

n w

as c

onsi

dere

d by

the

doct

or a

fter

C

DS

S c

onsu

ltatio

n5.

Add

ition

al ti

me

take

n fo

r CD

SS

co

nsul

tatio

n

Two

-way

mix

ed-m

odel

AN

OV

A

1. S

igni

fican

t red

uctio

n (5

.5 [S

D =

1.6

] er

rors

bef

ore

vers

us 5

.0 [S

D =

1.5

] er

rors

aft

er, p

< 0

.001

)2.

Mea

n di

agno

stic

qua

lity

scor

e in

crea

sed

sign

ifica

ntly

(in

crea

se =

0.

044,

95%

CI =

0.0

32–

0.05

4,

p <

0.0

01).

Als

o qu

ality

of t

est-

orde

ring

plan

s an

d tr

eatm

ent p

lan

impr

oved

sig

nific

antly

3. N

umbe

r of i

rrel

evan

t dia

gnos

es

incr

ease

d fr

om 0

.7 to

1.4

(in

crea

se

= 0.

7, 9

5% C

I = 0

.5–

0.75

), b

ut

num

ber o

f irr

elev

ant o

r del

eter

ious

te

sts

and

trea

tmen

ts r

emai

ned

unch

ange

d4.

In 1

2.5%

of c

ases

at l

east

one

di

agno

stic

dec

isio

n w

as a

dded

; in

9.3%

of c

ases

one

test

dec

isio

n w

as a

dded

; in

6.5%

one

trea

tmen

t st

ep w

as a

dded

5. M

edia

n ad

ditio

nal t

ime

take

n fo

r C

DD

S c

onsu

ltatio

n w

as 1

min

(IQ

R

= 30

sec

–2 m

in 4

sec

)

The

pro

visi

on o

f pat

ient

- and

co

ntex

t-sp

ecifi

c re

min

ders

re

duce

d di

agno

stic

om

issi

ons

acro

ss a

ll su

bjec

t gra

des

for a

ra

nge

of c

ases

, and

incr

ease

d di

agno

stic

and

trea

tmen

t qua

lity,

w

ithou

t a la

rge

incr

ease

in

wor

kloa

d

Dückers et al

Safety and risk management in hospitals

50

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

51

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Ram

nara

yan,

20

06b

Uni

ted

Kin

gdom

UB

A

Acu

te a

mbu

lato

ry p

aedi

atric

ca

re

N =

177

pat

ient

s, a

cros

s 4

care

uni

ts

Per

iod

= D

ecem

ber 2

002

Apr

il 20

03

Aim

To e

xam

ine

the

impa

ct o

f a

web

-bas

ed d

iagn

ostic

re

min

der s

yste

m o

n cl

inic

ians

’ de

cisi

ons

in a

n ac

ute

paed

iatr

ic s

ettin

g du

ring

asse

ssm

ents

cha

ract

eris

ed

by d

iagn

ostic

unc

erta

inty

Inte

rven

tio

nC

DS

S fo

r dia

gnos

tics

Co

ntr

ol

NA

Pri

mar

y o

utc

om

e 1.

Pro

port

ion

of

‘uns

afe’

dia

gnos

tic

wor

kups

follo

win

g C

DS

S c

onsu

ltatio

n

Sec

on

dar

y o

utc

om

es2.

Qua

lity

scor

es fo

r di

agno

stic

wor

kup

and

clin

ical

act

ion

plan

s3.

Tim

e ta

ken

by s

ubje

cts

to

com

plet

e C

DS

S

usag

e4.

Num

ber o

f di

agno

ses

incl

uded

in

the

diag

nost

ic

asse

ssm

ent

McN

emar

test

for p

aire

d pr

opor

tions

1. S

igni

fican

t dec

reas

e (4

5.2%

uns

afe

wor

kups

bef

ore

and

32.7

% u

nsaf

e w

orku

ps a

fter

CD

SS

con

sulta

tion,

p

< 0.

001

)2.

Dia

gnos

tic q

ualit

y sc

ores

incr

ease

d by

6.8

6 po

ints

(95

% C

I = 4

.0–

9.7)

af

ter C

DS

S c

onsu

ltatio

n. C

linic

al

plan

sco

res

impr

ovem

ent w

as

smal

ler i

n m

agni

tude

(1.5

poi

nts

incr

ease

, SD

= 6

.7)

3. M

edia

n tim

e sp

ent o

n th

e C

DS

S =

1

min

38

sec

(IQ

R =

50

sec–

3 m

in

21 s

ec)

4. N

umbe

r of d

iagn

oses

incr

ease

d fr

om 2

.2 to

3.2

, whe

reas

num

ber o

f te

sts

orde

red

rose

from

2.7

to 2

.9

The

qua

lity

of d

iagn

ostic

s im

prov

ed s

igni

fican

tly a

nd

diag

nost

ic o

mis

sion

err

ors

wer

e re

duce

d

Rob

inso

n, 2

00

6

US

A

UB

A

Pae

diat

ric o

ncol

ogy

N =

NC

Per

iod

= 20

01–2

004

(in

terv

entio

n in

20

02)

Aim

To a

sses

s th

e im

pact

of

iden

tifyi

ng th

e el

emen

ts

of r

isk

and

impl

emen

ting

appr

opria

te s

trat

egie

s

Inte

rven

tio

nU

se o

f fai

lure

mod

e an

d ef

fect

s an

alys

is (

FM

EA

) to

iden

tify

risk

and

for

impl

emen

ting

stra

tegi

es.

Str

ateg

ies

coul

d be

im

plem

ente

d in

thre

e ar

eas:

1. P

resc

ribin

g pr

oces

s2.

Dis

pens

ing

proc

ess

3. A

dmin

istr

atio

n pr

oces

s

Co

ntr

ol

NA

1. P

resc

ribin

g er

ror

rate

2. D

ispe

nsin

g er

ror

rate

3. A

dmin

istr

atio

n er

ror

rate

4. U

sage

rat

e of

re

prin

ted

stan

dard

or

der s

ets

Sta

tistic

al m

etho

dolo

gy is

unc

lear

1. T

he p

oten

tial p

resc

ribin

g er

ror r

ate

decr

ease

d fr

om 2

3% to

14%

2. A

ctua

l dis

pens

ing

erro

rs d

ecre

ased

fr

om 3

to 1

3. A

ctua

l adm

inis

trat

ion

erro

rs

decr

ease

d fr

om 4

to 3

4. U

se o

f rep

rinte

d st

anda

rd o

rder

se

ts in

crea

sed

from

22%

to 4

5% in

20

03 a

nd 7

6% in

20

05

The

CP

OE

sys

tem

, whi

ch w

as

desi

gned

bas

ed o

n an

FM

EA

, im

prov

es th

e pr

escr

ibin

g st

age

of th

e ch

emot

hera

py p

roce

ss

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

52

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

53

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Sch

neid

er,

200

6

US

A

RC

T

3 co

mm

unity

hos

pita

ls

N =

30

nurs

es (1

5 in

in

terv

entio

n an

d 15

in

cont

rol g

roup

)

Per

iod

= 6

wee

ks

(1 w

eek

base

line,

2

wee

ks a

fter

com

plet

ion

of th

e in

terv

entio

n/p

ost-

inte

rven

tion

asse

ssm

ent)

Aim

To e

xam

ine

the

impa

ct o

f an

inte

ract

ive

CD

-RO

M

prog

ram

me

on th

e ra

te o

f m

edic

atio

n ad

min

istr

atio

n er

rors

mad

e by

nur

ses

Inte

rven

tio

nE

duca

tiona

l CD

-RO

M: B

asic

M

edic

atio

n A

dmin

istr

atio

n

Co

ntr

ol

Usu

al c

are;

no

inte

rven

tion

1. E

rror

rat

e du

e to

de

viat

ion

from

sa

fe a

dmin

istr

atio

n pr

actic

es2.

Pre

para

tion

and

adm

inis

trat

ion

erro

r ra

te3.

Err

or r

ate

due

to

devi

atio

ns fr

om

pres

crib

ed th

erap

y

AN

OV

A a

nd lo

gist

ic r

egre

ssio

n an

alys

is

1. S

igni

fican

t dec

reas

e (O

R =

0.3

8 [9

5% C

I = 0

.19

–0.

74],

p =

0.0

04)

2. E

rror

rat

es in

crea

sed

(OR

= 1

.92

[95%

CI =

0.8

1–4.

58],

p =

0.1

4)3.

No

diff

eren

ce in

err

or r

ate

betw

een

grou

ps (

OR

= 1

.03

[95%

CI =

0.

23–

4.62

], p

= 0

.97)

An

inte

ract

ive

CD

-RO

M e

nabl

ed

nurs

es to

app

ly th

e in

form

atio

n le

arne

d to

iden

tify

erro

rs in

m

edic

atio

n ad

min

istr

atio

n an

d to

impr

ove

adhe

renc

e to

saf

e m

edic

atio

n ad

min

istr

atio

n pr

actic

es. O

ther

cat

egor

ies

of m

edic

atio

n er

rors

wer

e no

t af

fect

ed

Sch

wen

dim

ann,

20

06

Sw

itzer

land

ITS

Inte

rnal

med

icin

e, g

eria

tric

an

d su

rger

y in

patie

nt

depa

rtm

ents

N =

34,

972

patie

nts

Per

iod

= 19

99–2

003

(60

m

onth

s) w

ith in

terv

entio

n st

artin

g in

20

00

Aim

To e

xam

ine

inpa

tient

fall

rate

s an

d co

nseq

uent

in

jurie

s be

fore

and

aft

er

the

impl

emen

tatio

n of

th

e in

terd

isci

plin

ary

falls

pr

even

tion

prog

ram

me

(IF

P)

Inte

rven

tio

nIF

P:

• S

cree

ning

of a

ll pa

tient

s at

adm

issi

on fo

r ris

k of

fa

lls•

Exa

min

atio

n of

pat

ient

s co

nsid

ered

at r

isk

of

falli

ng•

Inte

rven

tions

for a

ll pa

tient

s to

pro

vide

saf

ety

in th

e ho

spita

l•

Inte

rven

tion

in p

atie

nts

cons

ider

ed a

t ris

k of

fa

lling

• R

eass

essm

ent o

f tho

se

patie

nts

who

fell

Co

ntr

ol

NA

1. In

patie

nt fa

ll ra

te

(per

1,0

00

patie

nt

days

)2.

Con

sequ

ent i

njur

y ra

te (

per y

ear)

Gen

eral

line

ar m

odel

, AN

OV

A,

Chi

-squ

are

test

1. F

all r

ates

fluc

tuat

ed fr

om 9

.1 fa

lls

per 1

,00

0 pa

tient

day

s in

the

first

ha

lf of

199

9 to

8.6

falls

in th

e se

cond

hal

f of 2

003

(p

= 0.

086

)2.

Ann

ual p

ropo

rtio

n of

min

or in

jurie

s de

crea

sed

from

32.

6% in

199

9 to

28.

1% in

20

03 (

p =

0.01

5) a

nd

annu

al p

ropo

rtio

n of

maj

or in

jurie

s in

crea

sed

from

2.5

% in

199

9 to

3.

9%

in 2

003

(p

= 0.

014)

Fal

l rat

es d

id n

ot c

hang

e af

ter

the

impl

emen

tatio

n of

the

IFP,

w

here

as m

inor

inju

ry r

ate

decr

ease

d an

d m

ajor

inju

ry r

ate

incr

ease

d

Dückers et al

Safety and risk management in hospitals

52

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

53

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Sha

mliy

an,

2007

Wor

ldw

ide

Rev

iew

Set

ting

: In

patie

nt (

N=

10),

out

patie

nt

(N =

1),

em

erge

ncy

depa

rtm

ent (

N =

1)

Num

ber o

f inc

lude

d st

udie

s:N

= 1

2 (1

RC

T, 9

UB

A a

nd 2

un

clea

r)

Sea

rch

perio

d: 1

990

–20

05

Eng

lish

Cou

ntrie

s: n

o re

stric

tions

Aim

To te

st th

e hy

poth

esis

th

at m

edic

atio

n er

rors

an

d ad

vers

e cl

inic

al

even

ts d

ecre

ase

afte

r co

mpu

teris

atio

n co

mpa

red

with

han

dwrit

ten

phys

icia

n or

ders

in p

aedi

atric

and

ad

ult p

atie

nts,

inde

pend

ent

of p

atie

nt a

nd p

rovi

der

char

acte

ristic

s

Inte

rven

tio

nC

PO

E s

yste

m C

on

tro

lH

andw

ritte

n ph

ysic

ian

orde

rs

1. M

edic

atio

n er

rors

2. W

rong

dru

g du

e to

pr

escr

ibin

g er

rors

3. W

rong

dos

e du

e to

pr

escr

ibin

g er

rors

4. A

DE

s

Met

a-an

alys

is w

ith fi

xed

and

rand

om

effe

cts

mod

els

1. S

igni

fican

t red

uctio

n (p

oole

d O

R =

0.

14 [9

5% C

I = 0

.05

–0.

43])

2. N

o ch

ange

(po

oled

OR

= 0

.80

[9

5% C

I = 0

.27–

2.36

])3.

Sig

nific

ant r

educ

tion

(poo

led

OR

=

0.44

[95%

CI =

0.2

3–

0.85

])4.

Sig

nific

ant r

educ

tion

(poo

led

OR

=

0.52

[95%

CI =

0.3

0–

0.91

])

Impl

emen

tatio

n of

CP

OE

was

as

soci

ated

with

a s

igni

fican

t re

duct

ion

in m

edic

atio

n er

rors

. R

esul

ts s

houl

d be

inte

rpre

ted

with

cau

tion:

pos

sibl

e ov

eres

timat

ion

due

to u

sing

no

n-ra

ndom

ised

unc

ontr

olle

d in

terv

entio

ns. U

se o

f CP

OE

not

as

soci

ated

with

a s

ubst

antia

l im

prov

emen

t in

patie

nt s

afet

y.

Stu

dies

do

not a

llow

bro

ad

gene

ralis

abili

ty

Silv

er, 2

00

0

US

A

UB

A

Acu

te c

are

hosp

itals

Bas

elin

e: 1

2 ho

spita

ls, 3

41

com

plet

ed s

urve

ysF

ollo

w-u

p: 9

hos

pita

ls, 2

19

com

plet

ed s

urve

ys

Per

iod

= A

utum

n 19

97

(bas

elin

e), A

utum

n 19

98

(fol

low

-up)

Aim

Im

prov

e th

e ho

spita

l’s

med

icat

ion

syst

em, i

n or

der t

o re

duce

med

icat

ion

erro

r rat

es

Inte

rven

tio

nB

reak

thro

ugh

Ser

ies

mod

el:

• te

ams

(QI,

phar

mac

y,

med

ical

sta

ff)

• im

prov

ing

info

rmat

ion

acce

ss•

stan

dard

isin

g an

d si

mpl

ifyin

g m

edic

atio

n pr

oced

ures

• re

stric

ting

phys

ical

ac

cess

to p

oten

tially

le

thal

dru

gs•

educ

atin

g cl

inic

al s

taff

ab

out m

edic

atio

ns•

QI f

acili

tato

rs•

enha

nced

err

or r

epor

ting

Co

ntr

ol

NA

A. R

espo

nden

t ob

serv

ing

med

icat

ion

erro

r:1.

All

erro

rs2.

Med

iatio

n or

derin

g3.

Tra

nscr

iptio

n an

d ve

rific

atio

n4.

Dis

pens

ing

and

deliv

ery

5. M

edic

atio

n ad

min

istr

atio

n

B. R

espo

nden

t in

dica

ting

erro

rs

wer

e di

scov

ered

and

pr

even

ted

C. R

espo

nden

t in

dica

ting

mos

t rec

ent

obse

rved

err

or w

as

repo

rted

:1.

All

erro

rs2.

Err

or r

each

ing

the

patie

nt

Logi

stic

reg

ress

ion,

with

pos

t-ho

c an

alys

is

A1:

sig

n –

decr

ease

from

20.

8% to

15

.2%

(O

R =

0.6

2, p

= 0

.00

6)

A2

: non

-sig

n –

decr

ease

from

23.

0%

to

16.

4% (

OR

= 0

.63,

p =

0.0

68)

A3

: sig

n –

decr

ease

from

24.

4% to

15

.7%

(O

R =

0.4

7, p

= 0

.003

)

A4:

non

-sig

n –

decr

ease

from

20.

2%

to 1

6.2%

(O

R =

0.6

8, p

= 0

.127

)

A5

: non

-sig

n –

decr

ease

from

15.

5%

to 1

2.5%

(O

R =

0.7

3, p

= 0

.278

)

B: s

ign

– in

crea

se fr

om 5

1.2%

to

57.6

% (

OR

= 1

.32,

p =

0.0

32)

C1:

non

-sig

n –

incr

ease

from

29.

0%

to

32.3

% (

OR

= 1

.16,

p =

0.3

37)

C2

: sig

n –

incr

ease

from

43.

9%

to

54.

5% (

OR

= 1

.67,

p =

0.0

13)

Sur

vey

resu

lts s

ugge

st th

at th

e ch

ange

s im

plem

ente

d in

the

orga

nisa

tions

may

hav

e re

duce

d m

edic

atio

n er

rors

and

impr

oved

ca

paci

ty fo

r err

or d

etec

tion

and

prev

entio

n

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

54

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

55

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Sim

, 20

02

US

A

UB

A

Com

mun

ity h

ospi

tal w

ith a

w

ide

varie

ty o

f acu

te c

are,

cr

itica

l car

e, e

mer

genc

y ca

re a

nd s

urgi

cal a

nd

diag

nost

ic s

ervi

ces

N =

NC

Per

iod

= M

ay 2

001

Janu

ary

2002

(9

mon

ths)

Aim

To a

ddre

ss m

edic

atio

n-re

late

d pa

tient

saf

ety

initi

ativ

es

Inte

rven

tio

nA

mul

tidis

cipl

inar

y te

am

was

form

ed to

add

ress

m

edic

atio

n-re

late

d pa

tient

sa

fety

initi

ativ

es, f

ocus

ing

on:

• le

ader

ship

• st

rate

gic

plan

ning

• an

alys

es o

f AE

s•

fost

erin

g ef

fect

ive

team

wor

k•

impr

ovin

g ca

re-d

eliv

ery

proc

esse

s •

enga

ging

pat

ient

s in

car

e de

liver

y

Co

ntr

ol

NA

Num

ber o

f rep

orts

of

med

icat

ion

varia

nces

Sta

tistic

al m

etho

dolo

gy n

ot r

epor

ted

The

num

ber o

f rep

orts

dou

bled

With

in a

nin

e-m

onth

per

iod

the

num

ber o

f var

ianc

e re

port

s do

uble

d. A

sub

com

mitt

ee

was

form

ed w

ith th

e sp

ecifi

c re

spon

sibi

lity

of r

evie

win

g th

e re

port

s on

a w

eekl

y ba

sis

Sim

on, 2

005

US

A, U

nite

d K

ingd

om,

Aus

tral

ia, H

ong

Kon

g/C

hina

, C

anad

a

Rev

iew

Num

ber o

f inc

lude

d st

udie

s:N

= 1

1 (4

con

trol

led

obse

rvat

iona

l stu

dies

and

7

unco

ntro

lled

obse

rvat

iona

l st

udie

s)

Sea

rch

perio

d =

1994

–20

04

Lang

uage

: Eng

lish

Aim

To a

sses

s th

e ef

fect

iven

ess

of h

ospi

tal i

ncid

ent r

epor

ting

syst

ems

in im

prov

ing

hosp

ital

and

clin

ic p

erfo

rman

ce

in te

rms

of p

atie

nt s

afet

y,

clin

ical

out

com

e, c

osts

and

op

erat

ions

Inte

rven

tio

nIn

cide

nt r

epor

ting

syst

ems

Co

ntr

ol

No

inci

dent

rep

ortin

g sy

stem

; us

ual c

are

1. M

edic

al e

rror

s2.

AE

s3.

Acc

urac

y of

in

cide

nt r

epor

ting

syst

ems

Nar

rativ

e an

alys

is

1.+

2. M

ajor

ity o

f the

stu

dies

(7

out

of 1

1) r

epor

ted

no r

educ

tion

in

med

ical

err

ors

and

AE

s af

ter

impl

emen

tatio

n of

inci

dent

rep

ortin

g sy

stem

s 3.

Inci

dent

rep

ortin

g an

d ch

art-

revi

ew

dete

ctio

n ar

e le

ss a

ccur

ate

than

di

rect

obs

erva

tion

Inci

dent

rep

ortin

g ca

n pr

ovid

e va

luab

le q

ualit

ativ

e an

d qu

antit

ativ

e da

ta r

elev

ant

to in

cide

nts

and

AE

s, w

hich

in

turn

can

pot

entia

lly g

uide

or

gani

satio

nal a

nd c

linic

al

inte

rven

tions

to d

ecre

ase

risks

. How

ever

, the

ben

efits

of

inci

dent

rep

ortin

g ar

e no

t wel

l es

tabl

ishe

d

Dückers et al

Safety and risk management in hospitals

54

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

55

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Sim

pson

, 20

04

Uni

ted

Kin

gdom

ITS

Neo

nata

l IC

U

N =

NC

Per

iod

= Ja

nuar

y 20

02 –

Ja

nuar

y 20

03

Aim

To d

escr

ibe

the

med

icat

ion

erro

rs o

ccur

ring

with

in a

ne

onat

al IC

U, a

nd a

sses

s th

e im

pact

of a

com

bine

d ris

k m

anag

emen

t/cl

inic

al

phar

mac

ist-

led

educ

atio

n pr

ogra

mm

e on

thes

e er

rors

Inte

rven

tio

nC

ombi

ned

risk

man

agem

ent/

clin

ical

pha

rmac

ist-

led

educ

atio

n pr

ogra

mm

e

Co

ntr

ol

NA

1. M

edic

atio

n er

ror

rate

(pe

r 1,0

00

activ

ity d

ays)

2. M

edic

atio

n er

ror

type

3. M

edic

atio

n er

ror

caus

e

Stu

dent

’s t-

test

1. M

onth

ly m

edic

atio

n er

ror r

ates

fell

from

a m

ean

(SD

) of 2

4.1

(1.7

) per

1,

00

0 ne

onat

al a

ctiv

ity d

ays

to 5

.1

(3.6

) per

1,0

00

days

(p

< 0.

001

) in

the

follo

win

g th

ree

mon

ths.

T

he s

ubse

quen

t cha

nge

of ju

nior

m

edic

al s

taff

was

ass

ocia

ted

with

a

sign

ifica

nt in

crea

se in

med

icat

ion

erro

rs to

12.

2 (3

.6) p

er 1

,00

0 ne

onat

al a

ctiv

ity d

ays

(p =

0.0

37)

2. A

tota

l of 1

05 e

rror

s w

ere

iden

tifie

d:

4 se

rious

, 45

pote

ntia

lly s

erio

us

and

56 m

inor

. The

4 s

erio

us

erro

rs in

clud

ed tw

o te

nfol

d do

se

mis

calc

ulat

ions

3.

Mos

t (71

%) o

f the

err

ors

wer

e du

e to

poo

r pre

scrib

ing

The

inte

rven

tion,

with

in th

e co

ntex

t of a

ris

k m

anag

emen

t pr

ogra

mm

e, is

eff

ectiv

e in

re

duci

ng m

edic

atio

n er

ror r

ates

Sni

jder

s, 2

007

Wor

ldw

ide

Rev

iew

Neo

nata

l IC

U

Num

ber o

f inc

lude

d st

udie

s:N

= 1

0 (8

pro

spec

tive

stud

ies

and

2 re

tros

pect

ive

stud

ies)

Sea

rch

perio

d: J

anua

ry

1980

– J

anua

ry 2

00

6

Lang

uage

s: E

nglis

h,

Ger

man

, Dut

ch, F

renc

h

Aim

To e

xam

ine

the

char

acte

ristic

s of

inci

dent

re

port

ing

syst

ems

in n

eona

tal

ICU

s in

rel

atio

n to

type

, ae

tiolo

gy, o

utco

me

and

prev

enta

bilit

y of

inci

dent

s

Inte

rven

tio

nV

ario

us m

odes

of i

ncid

ent

repo

rtin

g sy

stem

s

Co

ntr

ol

NC

Cha

ract

eris

tics

of

inci

dent

rep

ortin

g sy

stem

s

Nar

rativ

e an

alys

is

Ove

rall,

med

icat

ion

inci

dent

s w

ere

mos

t fre

quen

tly r

epor

ted.

Tot

al e

rror

ra

te w

as m

uch

high

er in

stu

dies

usi

ng

volu

ntar

y re

port

ing

than

in a

stu

dy

usin

g m

anda

tory

rep

ortin

g. M

ulti-

inst

itutio

nal r

epor

ting

iden

tifie

d ra

re

but i

mpo

rtan

t err

ors.

A s

ubst

antia

l nu

mbe

r of i

ncid

ents

wer

e po

tent

ially

ha

rmfu

l. W

hen

a sy

stem

app

roac

h w

as u

sed,

man

y co

ntrib

utin

g fa

ctor

s w

ere

iden

tifie

d. In

form

atio

n ab

out t

he

impa

ct o

f sys

tem

cha

nges

on

patie

nt

safe

ty w

as s

carc

e

Mul

ti-in

stitu

tiona

l, vo

lunt

ary,

no

n-pu

nitiv

e, s

yste

m-b

ased

in

cide

nt r

epor

ting

is li

kely

to

gene

rate

val

uabl

e in

form

atio

n on

type

, aet

iolo

gy, o

utco

me

and

prev

enta

bilit

y of

inci

dent

s in

the

neon

atal

ICU

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

56

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

57

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Stu

mp,

20

00

US

A

ITS

Hos

pita

l car

e

N =

1 h

ospi

tal

Per

iod

= F

irst q

uart

er 1

997

– se

cond

qua

rter

of 2

00

0 (in

terv

entio

n st

arte

d in

199

7 an

d co

mpl

eted

in J

une

1999

)

Aim

To r

edes

ign

the

med

icat

ion

erro

r rep

ortin

g pr

oces

s

Inte

rven

tio

nA

ser

ies

of in

terv

entio

ns w

as

impl

emen

ted

to o

ptim

ise

med

ical

err

or r

epor

ting.

C

ompa

red

with

the

hist

oric

al

repo

rtin

g pr

oces

s, th

e ne

w

proc

ess

incl

uded

:•

non

-pun

itive

rep

ortin

g•

cen

tral

pha

rmac

y de

part

men

t rec

eivi

ng

repo

rt w

ithin

48

hour

s ra

ther

than

2–

3 m

onth

s•

a u

nifie

d da

taba

se in

stea

d of

a fr

agm

ente

d pr

oces

s•

nea

r mis

ses

capt

ured

in

eve

ry s

tage

of

med

icat

ion-

use

proc

ess

and

not o

nly

in d

ispe

nsin

g pr

oces

s•

str

uctu

red

chec

k-bo

x re

port

s in

stea

d of

ha

ndw

ritte

n fr

ee te

xt•

sta

ff a

t ope

ratio

nal l

evel

in

volv

ed in

rev

iew

ing

data

Co

ntr

ol

NA

Num

ber o

f rep

orte

d ev

ents

Sta

tistic

al m

etho

dolo

gy is

unc

lear

Incr

ease

in n

umbe

r of r

epor

ted

even

ts

from

app

roxi

mat

ely

45 to

276

per

qu

arte

r with

in o

ne y

ear o

f the

sta

rt o

f th

e im

plem

enta

tion

Alte

rnat

ive

med

ical

err

or

repo

rtin

g pr

oces

s in

crea

ses

the

num

ber o

f rep

orte

d in

cide

nts

Dückers et al

Safety and risk management in hospitals

56

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

57

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Tid

eiks

aar,

1993

US

A

RC

T

Ger

iatr

ic h

ospi

tal u

nit

N =

70

patie

nts

(35

inte

rven

tion

+ 35

con

trol

)

Per

iod

= 9

mon

ths

Aim

To e

xam

ine

the

clin

ical

ef

ficac

y of

a b

ed a

larm

sy

stem

in r

educ

ing

falls

from

be

d on

a g

eria

tric

eva

luat

ion

and

trea

tmen

t uni

t

Inte

rven

tio

nB

ed a

larm

sys

tem

dur

ing

hosp

ital s

tay

Co

ntr

ol

Usu

al c

are,

with

out b

ed a

larm

1. N

umbe

r of p

atie

nts

sust

aini

ng fa

ll fr

om

bed

2. N

umbe

r of p

atie

nts

sust

aini

ng o

ther

fa

lls

1. N

o st

atis

tical

diff

eren

ce in

falls

from

be

d be

twee

n th

e ex

perim

enta

l (N

= 1

) and

con

trol

(N

= 4

) gro

up

(p =

1.0

0)

2. C

linic

al tr

end

tow

ards

red

uced

falls

in

the

expe

rimen

tal g

roup

The

dat

a su

gges

t tha

t bed

al

arm

sys

tem

s ar

e be

nefic

ial i

n gu

ardi

ng a

gain

st b

ed fa

lls a

nd

are

an a

ccep

tabl

e m

etho

d of

pr

even

ting

falls

Voe

ffra

y, 2

00

6

Sw

itzer

land

ITS

Che

mot

hera

py u

nit o

f the

ph

arm

acy

serv

ice

with

in a

ho

spita

l

N =

940

pre

scrip

tions

(pr

e-

inte

rven

tion)

N =

978

pre

scrip

tions

(po

st-

inte

rven

tion)

Per

iod

= 36

mon

ths

(15

mon

ths

pre

-inte

rven

tion,

21

mon

ths

post

-inte

rven

tion)

Aim

Red

ucin

g th

e nu

mbe

r of

pre

scrip

tion

erro

rs b

y im

plem

entin

g a

CP

OE

sys

tem

Inte

rven

tio

nC

PO

E, s

uch

that

a

pres

crip

tion

by a

juni

or d

octo

r is

firs

t val

idat

ed b

y a

seni

or

doct

or o

nlin

e be

fore

bei

ng

proc

esse

d. A

fter

val

idat

ion

the

orde

r is

auto

mat

ical

ly

tran

sfer

red

to n

ursi

ng s

taff

an

d ph

arm

acy

serv

ices

. A

ny c

orre

ctio

n on

initi

al

pres

crip

tion

is tr

ansm

itted

to

all p

rofe

ssio

nals

invo

lved

Co

ntr

ol

NA

Pre

scrip

tion

erro

r rat

e (p

er 1

00

pres

crip

tion

prot

ocol

s)

Bin

omia

l tes

t

1. S

igni

fican

t red

uced

err

or r

ate

(15%

be

fore

ver

sus

5% a

fter

)2.

Ave

rage

err

or r

ate

with

han

dwrit

ten

pres

crip

tions

gre

ater

than

with

co

mpu

teris

ed p

resc

riptio

ns (1

3.1%

ve

rsus

0.6

%)

3. N

umbe

r of e

rror

s re

duce

d dr

amat

ical

ly w

hen

50%

of p

roto

cols

w

ere

pres

crib

ed th

roug

h C

PO

E

Err

ors

alm

ost d

isap

pear

ed a

fter

im

plem

enta

tion

of C

PO

E

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

58

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

59

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Wal

sh, 2

008

US

A

ITS

Pae

diat

ric s

ervi

ce in

a

gene

ral h

ospi

tal

N =

627

adm

issi

ons

Per

iod

= S

epte

mbe

r 20

01 –

May

20

02 (

pre

-in

terv

entio

n), A

pril

2002

June

20

02 (

impl

emen

tatio

n)

Sep

tem

ber 2

002

– M

ay

2003

(po

st-in

terv

entio

n)

Aim

To e

valu

ate

the

effe

ct o

f C

PO

E o

n th

e ra

te o

f inp

atie

nt

paed

iatr

ic m

edic

atio

n er

rors

Inte

rven

tio

nU

se o

f a c

omm

erci

al

CP

OE

sys

tem

. Aft

er o

rder

en

try,

the

syst

em u

ses

a w

eigh

t-ba

sed

dosa

ge

calc

ulat

or to

aut

omat

ical

ly

chec

k m

edic

atio

n do

sage

, ge

nera

ting

wro

ng d

osag

e al

erts

. Oth

er fe

atur

es in

clud

e dr

ug–

drug

inte

ract

ion

aler

ts

and

alle

rgy

aler

ts. A

ll C

PO

E

user

s at

tend

ed a

two

-hou

r tr

aini

ng s

essi

on

Pre

-CP

OE

situ

atio

n: n

ursi

ng

med

icat

ion

reco

rds

wer

e pa

per b

ased

, and

onl

y th

e ho

spita

l pha

rmac

y w

as

auto

mat

ed w

ith a

sys

tem

to

chec

k dr

ug–

drug

inte

ract

ion

and

alle

rgie

s

Co

ntr

ol

NA

1. O

vera

ll m

edic

atio

n er

ror r

ate

2. S

erio

us m

edic

atio

n er

ror r

ate

3. N

on-in

terc

epte

d se

rious

inte

ract

ions

4. P

reve

ntab

le A

DE

s5.

Rat

e of

dos

ing

erro

rs6.

Rat

e of

ad

min

istr

atio

n er

rors

Tim

e se

ries

anal

ysis

(P

roc

Aut

oreg

) an

d un

ivar

iate

ana

lysi

s

1. N

o ch

ange

(44

.7 e

rror

s/1,

00

0 pa

tient

day

s [b

efor

e] v

ersu

s 50

.9

erro

rs [a

fter

], IR

R =

1.1

4 [9

5% C

I =

0.80

–1.5

1])

2. N

o ch

ange

(31

.7 e

rror

s/1,

00

0 pa

tient

day

s [b

efor

e] v

ersu

s 33

.0

erro

rs [a

fter

], IR

R =

1.0

4 [9

5% C

I =

0.70

–1.5

4])

3. N

o ch

ange

(23

.1 e

rror

s/1,

00

0 pa

tient

day

s [b

efor

e] v

ersu

s 20

.6

erro

rs [a

fter

], IR

R =

0.8

9 [9

5% C

I =

0.69

–1.7

8])

. Tim

e se

ries

anal

ysis

sh

owed

a s

tatis

tical

ly s

igni

fican

t dr

op (

7%, p

= 0

.049

5).

4. N

o ch

ange

(7.

9 er

rors

/1,0

00

patie

nt d

ays

[bef

ore

] ver

sus

6.5

erro

rs [a

fter

], IR

R =

0.8

3 [9

5% C

I =

0.37

–1.8

74])

5. N

o ch

ange

(8

erro

rs/1

,00

0 pa

tient

day

s [b

efor

e] v

ersu

s 11

er

rors

/1,0

00

patie

nt d

ays

[aft

er];

p

= N

C)

6. N

o ch

ange

(6

erro

rs/1

,00

0 pa

tient

da

ys [b

efor

e] v

ersu

s 4

erro

rs/1

,00

0 pa

tient

day

s [a

fter

]; p

= N

C)

CP

OE

in p

aedi

atric

inpa

tient

ca

re is

not

eff

ectiv

e in

red

ucin

g m

edic

atio

n er

rors

Dückers et al

Safety and risk management in hospitals

58

Appendix E: Included studies, sorted by alphabetical order

Dückers et al

Safety and risk management in hospitals

59

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Will

iam

s, 2

007

Aus

tral

ia

UB

A

Med

ical

war

ds o

f 1 h

ospi

tal

N =

1,3

57 p

atie

nt

adm

issi

ons

Per

iod

= D

ecem

ber 2

002

May

20

04 (

Dec

embe

r 20

02 –

May

20

03 p

re-

inte

rven

tion,

Dec

embe

r 20

03 –

May

20

04 p

ost-

inte

rven

tion)

Aim

To e

valu

ate

a sy

stem

atic

, co

-ord

inat

ed a

ppro

ach

to

limit

the

seve

rity

of fa

lls a

nd

min

imis

e th

eir n

umbe

r in

an

acut

e ca

re h

ospi

tal

Inte

rven

tio

nP

atie

nts

wer

e cl

assi

fied

base

d on

thre

e le

vels

of

risk:

low

, med

ium

, hig

h.

App

ropr

iate

inte

rven

tions

(e

nviro

nmen

t, m

obili

ty,

elim

inat

ion)

wer

e de

velo

ped

for e

ach

risk

leve

l in

an

indi

vidu

al fa

ll ca

re p

lan

Co

ntr

ol

NA

1. N

umbe

r of f

alls

per

1,

00

0 O

BD

2. S

ever

ity o

f fal

ls

The

Man

n-W

hitn

ey U

-tes

t and

S

tude

nt’s

t-te

st

1. S

igni

fican

t red

uctio

n in

falls

(9

.5/1

,00

0 O

BD

[bef

ore

] ver

sus

8.0

/1,0

00

OB

D [a

fter

] [95

% C

I of

the

diff

eren

ce =

-0.

14–

-0

.16

], p

< 0

.001

)2.

No

chan

ge in

sev

erity

of f

alls

App

roac

h w

as e

ffec

tive

in

redu

cing

fall

inci

denc

e

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.

Dückers et al

Safety and risk management in hospitals

60

Appendix E: Included studies, sorted by alphabetical order

Fir

st a

uth

or,

ye

ar, c

ou

ntr

yS

tud

y d

esig

nIn

terv

enti

on

Ou

tco

me

mea

sure

sA

nal

ysis

an

d r

esu

lts

Ove

rall

con

clu

sio

n

Wol

ff, 2

002

Aus

tral

ia

UB

A

ED

N =

2,5

75 (

pre

-inte

rven

tion)

N =

2,3

71, 2

,461

, 2,3

92,

2,66

4, 2

,720

, 2,3

73 a

nd

2,49

4 (p

ost-

inte

rven

tion)

Per

iod

= O

ctob

er –

D

ecem

ber 1

997

(pre

-in

terv

entio

n), J

anua

ry 1

998

– S

epte

mbe

r 199

9 (p

ost-

inte

rven

tion)

Aim

To d

eter

min

e if

retr

ospe

ctiv

e m

edic

al r

ecor

d sc

reen

ing

and

clin

ical

rev

iew

follo

wed

by

app

ropr

iate

act

ion

can

effe

ctiv

ely

dete

ct a

nd r

educ

e A

Es

in a

n E

D

Inte

rven

tio

nR

etro

spec

tive

scre

enin

g of

pa

tient

file

s in

two

phas

es:

by c

ompu

ter w

ith 5

gen

eral

pa

tient

out

com

e cr

iteria

; ‘p

ositi

ve’ f

iles

by h

and

by

nurs

e. E

D d

irect

or s

cree

ned

AE

s. T

hen,

pre

vent

ive

actio

n w

as ta

ken:

• c

hang

es in

hos

pita

l po

licie

s•

foc

used

aud

iting

• s

taff

dis

cuss

ion

• g

uide

line

impl

emen

tatio

n•

wee

kly/

quar

terly

rep

orts

• p

rom

otio

n of

clin

ical

-in

cide

nt r

epor

ting

Co

ntr

ol

NA

Num

ber o

f ED

at

tend

ance

s as

soci

ated

with

an

AE

Chi

squ

are

test

Sig

nific

ant d

ecre

ase

from

84

(3.2

6%)

in fi

rst q

uart

er to

12

(0.4

8%) i

n la

st

quar

ter (

RR

red

uctio

n =

85.3

% [9

5%

CI =

62.

7%–1

00

%],

p <

0.0

001

)

AE

s in

ED

s ca

n be

eff

icie

ntly

de

tect

ed a

nd th

eir r

ate

redu

ced

usin

g re

tros

pect

ive

med

ical

re

cord

scr

eeni

ng to

geth

er w

ith

clin

ical

rev

iew

, ana

lysi

s an

d ac

tion

to p

reve

nt r

ecur

renc

es

AD

E =

adv

erse

dru

g ev

ent;

AE

= a

dver

se e

vent

; AN

CO

VA

= a

naly

sis

of c

ovar

ianc

e; A

NO

VA

= a

naly

sis

of v

aria

nce;

C =

con

trol

gro

up; C

DS

S =

clin

ical

dec

isio

n su

ppor

t sys

tem

; CI =

con

fiden

ce in

terv

al;

CP

OE

= c

ompu

teris

ed p

hysi

cian

ord

er e

ntry

; CM

I = c

ontin

uous

med

icat

ion

infu

sion

; CO

= c

ompa

nion

obs

erve

rs; E

D =

em

erge

ncy

depa

rtm

ent;

I = in

terv

entio

n gr

oup;

ICU

= in

tens

ive

care

uni

t;

IQR

= in

ter

quar

tile

rang

e; IT

S =

inte

rrup

ted

time

serie

s; L

OS

= le

ngth

of s

tay;

MD

W =

med

icat

ion

disc

harg

e sh

eet;

ME

T =

med

ical

em

erge

ncy

team

; N =

num

ber;

NA

= n

ot a

pplic

able

; NC

= n

ot c

lear

; N

SA

ID =

non

-ste

roid

al a

nti-i

nfla

mm

ator

y dr

ug; O

BD

= o

ccup

ied

bed

day;

OR

= o

dds

ratio

; PD

A =

per

sona

l dig

ital a

ssis

tant

; QI =

qua

lity

impr

ovem

ent;

RC

T =

ran

dom

ised

con

trol

led

tria

l; R

R =

rel

ativ

e ris

k;

SD

= s

tand

ard

devi

atio

n; U

BA

= u

ncon

trol

led

befo

re-a

fter.


Recommended