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International Journal for Quality in Health Care 2004; Volume 16, Supplement 1:pp. i11i25 10.1093/intqhc/mzh032

Using clinical indicators in a qualityimprovement programme targetingcardiac care

ANNABEL HICKEY1, IAN SCOTT1, CHARLES DENARO2, NEIL STEWART1, CAMERON BENNETT2AND THERESE THEILE2

1Department of Internal Medicine, Princess Alexandra Hospital, Brisbane, 2Department of Internal Medicine, Royal Brisbane Hospital,Brisbane, Australia

Abstract

Rationale. The Brisbane Cardiac Consortium, a quality improvement collaborationof clinicians from three hospitals and Wvedivisions of general practice, developed and reported clinical indicators as mea

sures of the quality of care received by patientswith acute coronary syndromes or congestive heart failure.

Development of indicators. An expert panel derived indicators that measured gapsbetween evidence and practice. Datacollected from hospital records and general practice heart-check forms were usedto calculate process and outcome indicatorsfor each condition. Our indicators were reliable (kappa scores 0.71.0) and widelyaccepted by clinicians as having face validity.Independent review of indicator-failed, in-hospital cases revealed that, for 27of 28 process indicators, clinically legitimatereasons for withholding speciWc interventions were found in


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Project rationale and conception

Improving quality of health care requires performance measurementand feedback. Various programmes targeting cardiaccare have combined the use of clinical indicators with otherquality improvement interventions in identifying and closing

the gaps between routine care and evidence-based best practice[14].

However, in the successful development and use of clinicalindicators, several dimensions need to be carefully considered:

(i) deWning the purpose of measurement; (ii) determiningtarget standards of care; (iii) formulating data collectionmethods; (iv) converting data into usable clinical indicators;and (v) maximizing the impact of indicator feedback. In thisreport we describe our experience in undertaking these stepswithin a multifaceted quality improvement programme targeting

in-hospital and post-hospital care of patients admittedwith acute coronary syndromes (ACS) or congestive heartfailure (CHF). An overview of our programme is provided inBox 1.Address reprint requests to A. Hickey, Clinical Services Evaluation Unit, Princess Alexandra Hospital, Ipswich Road,Woolloongabba, Brisbane, Queensland, Australia 4102. E-mail: [email protected]

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A. Hickey et al.Box 1 Overview of the Brisbane Cardiac ConsortiumThe Brisbane Cardiac Consortium (BCC) was one of four quality improvement consortia in Australia to receive 2 yearsfunding from the federal government under the Clinical Support Systems Program (CSSP) auspiced by the Royal Australian

College of Physicians. The program targeted the in-hospital and post-hospital care of patients admitted with acute coronarysyndromes (ACS) and congestive heart failure (CHF). The program ran from October1, 2000, to August 31, 2002, andinvolved three teaching hospitals [Royal Brisbane (800 beds), Princess Alexandra(700 beds) and Queen Elizabeth IIHospitals (260 beds)] and four Divisions of General Practice within metropolitanBrisbane.Program objectives were to optimize care using systematic processes of performance measurement and feedback combinedwith various quality improvement interventions. The latter included dissemination of locally developed clinical practice

guidelines and other forms of decision support, academic detailing of patients and clinicians by clinical pharmacists,provision of patient self-management resources, and close liaison between hospital and general practitioners andcommunity pharmacists regarding future patient management.Primary outcome measures were changes in clinical indicators between baseline (1/10/0017/4/01) and post-intervention(15/3/0230/8/02) periods as measured on all consecutive patients who met pre-speciWed case deWnitions.* Post-hospitalcare indicators were collected on a subset of patients who satisWed eligibilitycriteria** and gave informed consent to posthospitalfollow-up.The program saw participation of 2495 patients (1584 with ACS; 911 with CHF), 10

cardiologists, 17 general physicians, 20emergency physicians, 5 clinical pharmacists, 50 medical registrars, 200 residents, 150 nursing staff, and 1020 generalpractitioners.

*ACS: clinical diagnosis of ACS + elevation of cardiac enzyme markers (troponinor creatine kinase levels elevated to more than 1.5 and

2.0 times upper normal reference range respectively). CHF: clinical diagnosis and at least 3 key clinical signs (elevated jugular venouspressure, gallop rhythm, chest crackles to mid-zones bilaterally, pedal oedema,or pulmonary oedema or cardiomegaly on chest X-ray).**Absence of major co-morbidity (physical or psychological) which precluded ability to self-care, permanent resident in the greaterBrisbane area, community-living, and ability to speak English.Development and design of clinicalindicators

Defining the purpose of measurement

We wanted indicators that would guide and motivate internalquality improvement activities in hospital and general practice,and not be used merely for monitoring purposes byexternal agencies. To engage health care providers we wantedour indicators to be clinically relevant to speciWc processes of

care that demonstrated an accepted link with desired healthoutcomes [5]. We aimed to present aggregate indicator data atthe level of facility or, where sample size was large enough,


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at a departmental or group general practice level. As the targetgroups were identiWable groups of clinicians, we considered itvital that the indicators were robustly accurate.

Determining standards and indicators usingmultidisciplinary teams

We speciWed the target standards of care in a set of clinicalpractice guideline recommendations derived from a systematicreview of the research evidence [68]. These guidelines weredeveloped over a period of 5 months, using formal group consensusmethods, by multidisciplinary panels of general physicians(n = 5), cardiologists (n = 5), general practitioners (GPs;n = 12), clinical pharmacists (n = 2), and advanced physiciantrainees (n = 3). These panels contained expertise in clinicalcontent and measurement, and represented the interests ofpotential users of the indicators [9]. The development work

was coordinated by the programme manager in liaison with the

eight-member Clinical Guideline Working Group.

The same multidisciplinary team derived sets of clinicalindicators from guideline recommendations and a review ofindicators published by other groups [10,11]. Indicatorsrelated to both process (what care was given to whom) andoutcome (what was the end result of care), were designed tobe as explicit and objective as possible, and were developedby group consensus.

Methods

Data collection

Data used to calculate in-hospital care indicators wereabstracted by trained nurses from hospital medical recordsretrieved shortly after discharge. Post-hospital care data werecollected using a 1-page heart-check form completed duringGP consultations at 3, 6, and 12 months post-discharge. Examplesof data forms used are provided in supplementary data.We restricted data elements for each indicator to those thatwere objectively veriWable and easily retrieved from medicalrecords or GP case notes.

Conversion of data into useful clinical indicators

Improving care processes known to have a direct link withhealth outcomes was our prime objective. To this end, processindicators predominated over outcome indicators, particularly

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Cardiac clinical indicators

as large, risk-adjusted samples are required to detect signiWcantchanges in outcome indicators (such as in-hospital deathor 30-day readmission) given their relatively low event rates(in our experience 70% of all dataWelds, with 95% completion for medication use.

Validity. We validated in-hospital process indicators byindependently reviewing charts of all seemingly eligiblepatients who failed to receive speciWc interventions in the Wrst


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and last 6-month periods for those indicators that showed afailure rate of >20% (see below). The only indicator forwhich clinically legitimate reasons were detected for withholdingcare in >5% of indicator-failed cases was prescriptionof warfarin in patients with CHF. In 64 of 113 (56%) patientsdeemed eligible for warfarin but who did not receive thisdrug, review disclosed relative contra-indications such as

frailty or risk of falls in 43 (67%) of cases.

Impact. To inXuence clinician behaviour, we chose indicatorsthat had the capacity to signal the existence of important evidence-practice gaps and that were potentially amenable tochange [16,17]. We presented indicator values in easy to interpretgraphical and tabular formats, which depicted changes inindicator rates over time ( Figures 1 and 2) and which included areference standard (or target) of 100% of highly eligible patientsreceiving the stated intervention. In addition, we employed variousstrategies (see below) to enhance the ability of indicatorfeedback to stimulate clinician attempts to improve care [18,19].

Maximization of clinical indicator impact

Feedback of in-hospital care indicators occurred at 6-monthlyintervals, while feedback of post-discharge (general practice)indicators occurred over two rounds separated by 18 months,as follow-up data were collected more slowly and the patientsample was only one-third that of the in-hospital sample.

Dissemination

We disseminated results via hospital unit meetings, hospital anddivisions of general practice newsletters, drug and therapeutics

bulletins, grand round presentations, educational meetings,and in-service training sessions. We ensured doctors, nurses,and clinical pharmacists at all levels were exposed to indicatorfeedback [20].

Feedback partnered with education and discussion

Clinical audit and periodic feedback, in isolation, engenderonly moderate levels of change [21]. Lack of skills, knowledge,and leadership are some of the known barriers to practiceimprovement [22]. Consequently, we coupled indicator feedbackin hospitals with small group discussions about guidelinerecommendations and the signiWcance of the indicator Wndings.Practice improvement was promoted through citing casestudies of successful innovation elsewhere, and the formationof interdisciplinary groups that took responsibility forimproving speciWc care processes [23].

Customized indicator analyses

Encouraged by the work of others [17], and receiving localrequests, we provided more personalized reports to individualhospital consultants about performance within his or herunit if patient samples were large enough to give statisticallymeaningful trends. These reports compared that consultants

performance with peers from all three hospitals andincluded patient demographics to reconcile any differencesin case mix.


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Feedback from providers and modificationsto the original plan

Clinician responses to reported indicators in the Wrst feedbackround centred, not surprisingly, on data quality and face validity,


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A. Hickey et al.Table 1 Process indicators for in-hospital careIndicator Eligibility criteria

................................................................................

.........................................................................

Inclusions Exclusions

................................................................................

................................................................................

........................................................

Acute coronary syndromes

Presentation

ECG: proportion of patientsreceiving ECG within10 minutes of hospitalremoval

Thrombolysis: proportionof highly eligible patientsreceiving thrombolysis

Time to lysis: proportionof highly eligible patientsreceiving thrombolysiswithin 60 and 30 minutes

of hospital arrival

In-hospital courseCardiac counselling:proportion of highly eligiblepatients receiving in-hospitalcardiac counselling

Assessment of serum lipids:proportion of patientsundergoing testing of serumlipids

Discharge status1 -blocker: proportion ofhighly eligible patientsprescribed -blocker

Anti-platelet agents:proportion of highlyeligible patients prescribedanti-platelet agents (aspirinor clopidogrel)

ACE inhibitors: proportion

of highly eligible patientsprescribed ACE inhibitors


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Lipid-lowering agents:proportion of highlyeligible patients prescribedlipid-lowering agents

All patients

Patients with ST segmentelevation or new left bundlebranch block

All highly eligible patientsreceiving thrombolysis

All patients

All patients

All patients

All patients

Past history or in-hospitalonset of congestive heartfailure, LV ejection fraction4.0 mmol/l

Nil

Recent trauma or surgery, cardiopulmonaryresuscitation, prior cerebrovascular accident ortransient ischaemic attack, uncontrolled hypertension(>180/100 mmHg), coagulopathy, active gastrointestinalbleeding, late (>12 hours) presentation, patientrefusal, uncertain diagnosis, or scheduled for primaryangioplasty

Nil

Nil

Nil

Asthma, severe chronic obstructive pulmonarydisease (FEV1


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adverse drug reaction

Adverse drug reaction


continued

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Table 1 continued

Indicator Eligibility criteria

................................................................................

.....................................................................


................................................................................

................................................................................

........................................................

Cardiac rehabilitation:

proportion of highlyeligible patients referredto outpatient cardiacrehabilitation programme

Coronary angiography:proportion of highly eligiblepatients undergoing earlycoronary angiography (duringindex admission or scheduledwithin 30 days of discharge)

Non-invasive risk stratiWcation:proportion of highly eligiblepatients undergoing noninvasiverisk assessment(during index admission orwithin 30 days of discharge)

Congestive heart failure

At presentationRecording underlying causes:proportion of patients forwhom underlying causes forheart failure were recorded inhospital notes

Recording acute precipitants:proportion of patients forwhom acute precipitantswere recorded in hospital notes

Fluid regimens: proportionof patients for whom aXuid management regimenwas explicitly recorded in

hospital notes

Daily weigh: proportion


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of patients undergoingdaily weighing in assessingeffectiveness of diuresis

DVT prophylaxis: proportionof patients receiving DVTprophylaxis

Dietitian review: proportionof patients receiving dietitianreview re: salt and Xuid intake

Testing of thyroid function:proportion of patientsundergoing thyroid functiontesting

All patients

Recurrent angina orreinfarction, or NSTEMIinfarction or inducibleischaemia on non-invasivetesting

All patients

All patients

All patients

All patients

All patients

All patients

All patients

Atrial Wbrillation as newarrhythmia

Primary or rescue angioplasty, age >75 years, currentsmoker, severe COPD, stroke with hemiplegic deWcit,renal disease (serum creatinine =0.2 mmol/l), advancedliver disease, advanced cancer, alcohol/drug dependence,living in residential care

Coronary angiography (performed or scheduled) or otherexclusions as listed under coronary angiography

Nil

Nil

Nil

Nil

Concurrent warfarin therapy


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Nil


continued

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A. Hickey et al.Table 1 continuedIndicator Eligibility criteria

................................................................................

.......................................................................


................................................................................

................................................................................

........................................................

Assessment left ventricularfunction: proportion ofpatients who have undergone

left ventricular imaging eitherduring index admission orwithin previous 12 months

Clinical pharmacist review:proportion of patientsreceiving review by clinicalpharmacist

Discharge status1ACE inhibitors: proportionof highly eligible patientsprescribed ACE inhibitor at

discharge

ACE inhibitor dose:proportion of highlyeligible patients prescribedACE inhibitors at dischargewho receive target dose

-blockers: proportion ofhighly eligible patientsprescribed -blockers atdischarge

Warfarin: proportion of highlyeligible patients prescribedwarfarin at discharge

Deleterious agents: proportionof patients who did not receivedeleterious agents (class Iantiarrhythmic agents,verapamil, diltiazem, NSAIDs,tricyclic antidepressants)

Clinic follow-up: proportionof patients scheduled foroutpatient clinic review within


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4 weeks of discharge

All patients

All patients

LV ejection fraction 0.3 mmol/l, systolic blood pressure


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racy and justiWcation of the method of indicator calculation. indicator-failed patients. Only four clinicians accepted this offerThe rigorous research approach to measurement can appear at and none asked for the reported indicators to be revised.odds with the more pragmatic process of measurement for In the second round we emphasized indicators for whichimprovement [24]. Clinicians experiencing difWculty in accepting improvement in

care would result in the greatest gains in

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Cardiac clinical indicatorsTable 2 Process indicators for post-discharge care measured at 3, 6, and 12 months following hospital discharge

Indicator Description

................................................................................

................................................................................

........................................................

Acute coronary syndromes

Anti-platelet agent Proportion of patients receiving anti-platelet therapy-blockers Proportion of patients receiving -blockersACE inhibitor Proportion of patients receiving ACE inhibitorLipid-lowering agents Proportion of patients receiving lipid-lowering therapyControl of serum lipids Proportion of patients achieving serum cholesterol


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and statisticiansDevelop database logic checks to alert when incorrectdata are being entered, e.g. discharge date that is before anadmission date

Pilot test the indicators and data collection methods andreWne them over a set period (in our case, 3 months) and

update data entry manual accordingly

Monitor data reliability with frequent interim analyses andregular meetings of data collectors to ensure consistency ofdata item interpretation and measurement

Undertake re-abstraction audits of randomly selectedhospital charts in assessing level of agreement amongabstracters (inter-rater reliability)

patient outcome. We offered potential solutions based on literaturereviews and action research conducted elsewhere. We

collaborated with various groups in providing more customizeddata that better informed their attempts to improve care.

This support-giving approach was further consolidated inthe third round of feedback, by which time data quality was

no longer an issue. Various multidisciplinary groups were nowacting across professional boundaries to improve speciWcaspects of care [23]. At this time, we surveyed a representativesample (n = 150) of hospital clinicians about the usefulnessand impact of indicator feedback. Although the response ratewas low (25%), >70% of respondents found feedback usefuland wished to continue receiving it, while 52% reported that

it had resulted in changes to practice.

During the course of our implementation, we modiWed theproject design as a result of clinician feedback and internalre-appraisal.

Brevity and clarity. Our Wrst post-discharge care feedbacknewsletter to GPs met with almost universal dismissal onthe grounds that it contained too much uninterpretable datathat could not be assimilated by busy practitioners.Consequently we restricted ourselves to simple tables andboxed key messages (see Figure 3), which elicited positiveresponses.

Liberalization of eligibility criteria. With certain pharmacologicalindicators (e.g. warfarin, ACE inhibitors) we found that byusing restricted indications and inclusive contra-indications,very few patients demonstrated eligibility for treatment, andthus the indicator was rendered useless. In such cases we created,by consensus, a new version of the indicator with moreliberal eligibility criteria that still accorded with evidence-based clinical decision-making.

Balancing effort of validation with the need for timely feedback. Wefound that repeated minor corrections of the raw data aimed

at maximizing validity of the calculated indicator did notmake any signiWcant difference to the reported indicatorvalue, and simply delayed its timely release which, in turn,


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reduced its impact on clinicians. We reconWrmed Hannansdictum: do not wait for better dataperfect should not bethe enemy of good [25].


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100806040Series 1Series 2

Series 3Series 4200

A. Hickey et al.Discharge status

% of eligible patients receiving treatment

B-B A-A ACE-I LLA Heparin

Figure 1 Graphical feedback of consecutive series of values of process indicators for in-hospital care of patients with acutecoronary syndromes. Series 1: patients discharged 17 October 2000 to 16 April 2001 (note: no data on heparin use werecollected for patients in this series). Series 2: patients discharged 17 April 2001 to 20 September 2001. Series 3: patientsdischarged 21 September 2001 to 18 February 2002. Series 4: patients discharged19 February 2002 to 31 August 2002. A-A,patients receiving anti-platelet agents; ACE-I, patients receiving angiotensin-converting enzyme inhibitors; B-B, patients receiving-blocker; LLA, patients receiving lipid-lowering agents; Heparin, patients receiving heparin infusion.


Avoiding frequent minor changes in indicator deWnition [26]. Whiledata sets should allow for changes in indicator deWnitions toreXect evidence-based changes in practice, minor changesserved only to confuse clinicians wanting to make comparisonsacross feedback periods. We ceased making differentversions of the same indicators after the Wrst round for reasonsother than those mandated by the publication of resultsof important, new clinical trials.

Discontinuation of indicator reports based on small samples. We originallyenvisaged a 3-month rather than a 6-month cycle for in-hospital feedback. While we desired timely indicator feedback,the shorter cycle span led to smaller patient samples which, forsome indicators with low event rates, introduced excess randomerror [27]. While statistical process control methods [28,29] couldhave been used to correct for such error, we were concerned thatadding such analyses to our feedback formats would have jeopardizedtheir interpretability to the majority of clinicians.

Discontinuation of formal feedback sessions. By the third roundof feedback, hospital clinicians did not desire feedback to beaccompanied by formal discussion sessions, suggesting that

external facilitation becomes redundant once the culture ofimprovement has been established.


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Results

Preliminary results

Baseline process indicators suggested suboptimal performancein several areas [30,31], with subsequent improvement in most

indicators and signiWcant change in 17 of 40 (Tables 47). It isimpossible to gauge the extent to which these improvementsin care can be attributed solely to clinical indicator feedbackamong several concurrent quality improvement interventions.However, focus group discussions and results of the previouslymentioned questionnaire survey suggested that indicatorfeedback had stimulated changes in practice.

Lessons learned and future plans

Our experience yielded several lessons that are guiding futureplans. Firstly, keep the number of data elements to a minimum.

Our dataset for in-hospital care comprised 171 variablesfor ACS and 204 for CHF, many relating to patient demographicsand clinical characteristics, which we reasoned wererelevant to determining process-of-care eligibility or conductingrisk-adjusted outcome comparisons. In retrospect, a largefraction of these data (and the effort involved in collectingthem) added little to the validity of reported indicators and wasnot required for case-mix adjustment in the presence of casedeWnitions and standardized patient ascertainment. In a furtherextension of our work, data elements have been reducedto 50 for ACS and 45 for CHF [32]. Secondly, more economicalmethods of data collection and entry are worth exploring. Inthe absence of universal electronic medical records, proformas

that are read by text recognition software are being trialed[33], which affords more rapid importation of data into databasesand reduction in transcription errors.

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by guest on October 8, 2011intqhc.oxfordjournals.orgDownloaded fromFigure 2 Tabular feedback of clinical indicators for in-hospital care of acute coronary syndromes.

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A. Hickey et al.by guest on October 8, 2011intqhc.oxfordjournals.orgDownloaded fromFigure 3 Feedback forms relating to post-discharge (general practice) care.i20


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by guest on October 8, 2011intqhc.oxfordjournals.orgDownloaded fromFigure 3 continued

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A. Hickey et al.Table 4 Changes in process and outcome indicators for in-hospital care for acutecoronary syndromesIndicator Baseline (n = 428) Final remeasurement period(1/10/0017/4/01) (n = 436) (15/2/0230/8/02)

................................................................................

................................................................................

........................................................

PresentationElectrocardiograph within 10 minutes of presentation1Lysis administrationLysis in 60 minutesLysis in 30 minutes

In-hospital course

Lipid levels checkedNon-invasive risk stratiWcation testsCoronary angiographyIn-hospital cardiac counselling1

Discharge status-blockerAnti-platelet agentsACE inhibitors1Lipid-lowering agents1Referral to outpatient cardiac rehabilitation1

Outcomes

In-hospital mortalityRe-admission (same cause) in 30 daysMedian length of hospital stay (days)1

ACE, angiotensin-converting enzyme.1SigniWcant change (P = 0.05).

Thirdly, in terms of sustainability, our costings suggest thatmeasurement and feedback systems used ~50% (or $500 000)of the programme budget, which was expended on 2500 patients

(i.e. approximately $200 per patient). Trends in the datasuggest that costs are more than likely to be offset by improvementsin health outcomes such as the observed 1-day reductionin median length of hospital stay for patients with ACS. Theminimization of datasets and the use of previously mentionedscanning technology will signiWcantly reduce this infrastructurecost.In the Queensland state public hospital system, our revisedmethods for measuring and reporting clinical indicator dataare being continued in the three consortium hospitals andextended to 14 other large hospitals under the auspices of theCardiac Collaborative of the Queensland Health Collaborativefor Healthcare Improvement [32]. Our indicator experienceis also assisting the Cardiac Society of Australia and

New Zealand (CSANZ) [34] and the National Institute of ClinicalStudies (NICS) [35] to develop national indicator sets forACS and CHF, respectively, and to inform the quality


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improvement strategies that these organizations may want tosponsor in the future.

As a result of our programme, Wve divisions of generalpractice representing all GPs in metropolitan Brisbane havebecome involved in clinical audit and feedback. However, thelong-term continuation of this activity in its current form is

proving to be a challenge due to the expense and labourinvolved. Less than ideal response rates limit the sample size,

145/238 (61%)49/49 (100%)35/39 (71%)17/49 (35%)

311/428 (73%)17/57 (30%)41/45 (91%)168/351 (48%)

212/251 (84%)301/318 (95%)105/143 (73%)165/202 (82%)24/351 (8%)

28/379 (7.4%)26/351 (7.4%)

7.0

170/244 (70%)

39/39 (100%)28/39 (72%)16/39 (41%)

336/436 (77%)17/55 (31%)43/46 (93%)212/371 (57%)

202/239 (85%)321/334 (96%)113/139 (81%)197/223 (88%)64/371 (17%)

23/394 (5.8%)17/371 (4.6%)

6.0

requiring longer feedback cycles in order to accrue meaningfuldata.

Performance measurement and feedback are an integralpart of quality improvement initiatives. We attempted to

develop a sustainable system of indicator collection andreporting as part of a programme targeting care of two commoncardiac conditions associated with signiWcant mortality


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and morbidity. Taking a patient-centred focus, we providedfeedback for indicators targeting both hospital and communityproviders. At an organizational level, our methodology isbeing extended to multiple public hospitals throughout ourstate, while the smaller, less resourced divisions of generalpractice are building on their experience to develop lowercost systems for ongoing clinical audit.

Acknowledgements

We are appreciative of the extensive support given byQueensland Health, and the cooperation of the members ofthe clinical indicator expert panels and others involved in indicatoranalysis, in particular: Dr Kathleen Armstrong, Dr JohnAtherton, Dr John Bennett, Mr Neil Cottrell, Dr ChristineFawcett, Dr Judy Flores, Dr Andrew Galbraith, Dr PaulGarrahy, Ms Ann Hadwyn, Professor Tom Marwick, Dr AlisonMudge, Dr Mark Morris, Dr Bronwyn Pierce, Ms DanielaSanders, and Ms Justine Thiele. The authors gratefully acknowledge

the funding support of the Australian Commonwealth


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Table 5 Changes in process and outcome indicators for in-hospital care for congestive heart failure

Indicator

Baseline (n = 220) Re-measurement period (n = 235)(1/10/0017/4/01) (15/2/0230/8/02)

................................................................................

................................................................................

........................................................

In-hospital courseRecording underlying causes 188/220 (85%) 215/235 (91%)Recording precipitating factors1 160/220 (75%) 211/235 (90%)Limiting Xuids1 89/220 (40%) 128/235 (54%)

Weighing daily1 121/220 (55%) 148/235 (63%)DVT prophylaxis1 31/104 (30%) 94/128 (73%)Dietician review 38/220 (17%) 44/235 (19%)Thyroid function test1 16/31 (52%) 41/52 (79%)Echo cardiograph 135/220 (61%) 164/235 (70%)Clinical pharmacist review1 105/191 (55%) 142/219 (65%)

Discharge statusACE inhibitors 58/71 (82%) 61/71 (86%)ACE inhibitor target dose 82/136 (60%) 108/164 (66%)-blocker1 47/135 (35%) 88/152 (58%)Warfarin 22/50 (44%) 27/63 (41%)Deleterious agents (avoidance of) 180/191 (94%) 214/219 (98%)

Physician clinic follow-up1 87/191 (46%) 130/219 (59%)

OutcomesIn-hospital mortality1 21/212 (9.9%) 11/230 (4.8%)Re-admission (same cause) in 30 days 10/199 (5.0%) 13/224 (5.8%)Median length of hospital stay (days) 7.0 7.0

ACE, angiotensin-converting enzyme; DVT, deep venous thrombosis.1SigniWcant change (P = 0.05).

Table 6 Changes in process indicators for post-hospital care (acute coronary syndromes)

Indicator 3 month follow-up6 month follow-up

..................................................................................................................................................................

Baseline (n = 95) Remeasurement (n = 89) Baseline (n = 93) Remeasurement (n = 104)

................................................................................

................................................................................

........................................................


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Anti-platelet agent 81% 90% 83% 87%-blocker 65% 74% 61% 70%ACE inhibitor 59% 57% 61% 63%Lipid-lowering agents 81% 81% 81% 83%Control of serum lipids 50% 44% 60% 68%Smoking cessation 17% 50%1 15% 39%1

ACE, angiotensin-converting enzyme.1SigniWcant change (P = 0.05).

Table 7 Changes in process indicators for post-hospital care (congestive heart failure)

Indicator 3 month follow-up6 month follow-up

................................................................................

.. .............................................................................

.....

Baseline (n = 47) Remeasurement (n = 38) Baseline (n = 45) Remeasurement (n = 54)

................................................................................

................................................................................

........................................................

ACE inhibitor 72% 87% 69% 69%ACE inhibitor dose 55% 66% 63% 70%

-blocker 38% 66%1 38% 48%Control of blood pressure 63% 74% 45% 68%1Weight monitoring 69% 100%1 57% 69%Exercise prescription 40% 58%1 44% 63%1


1SigniWcant change (P = 0.05).

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A. Hickey et al.Department of Health and Ageing who made this programmepossible through the Clinical Support Systems Program(a joint initiative with the Royal Australasian College ofPhysicians).

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32.Queensland Health Collaborative for Healthcare ImprovementCardiac Collaborative, Brisbane, Australia. http://www.qheps.health.qld.gov.au/chi/home.htm Accessed 11 December 2002.

33.Thoma G. Automating the production of bibliographic recordsfor medline. An R&D report of the Communications EngineeringBranch Lister Hill National Center for Biomedical Communications,National Library of Medicine. Bethesda, MD:National Library of Medicine. http://archive.nlm.nih.gov/pubs/thoma/mars2001.php Accessed September 2001.34.Cardiac Society of Australia and New Zealand/National HeartFoundation of Australia Acute Coronary Syndrome WorkingGroup, Sydney, Australia. http://www.csanz.edu.au Accessed11 December 2002.

35. National Institute of Clinical Studies Heart Failure Data ExpertGroup, Melbourne, Australia. http://www.nicsl.com.au Accessed11 March 2003.Accepted for publication 21 November 2003

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