Human Factors Underlying Adverse Medical Events: Revisit...

Fu-Jen Journal of Medicine Vol. 3 No. 2, 2020

Retrospect RCA with HFACS

Yu-Hsun Cheng, Sheng-Hui Hung, Tung-Wen Ko, Pa-Chun Wang

99

Submitted October, 11, 2019

Final version accepted February,

02, 2020.

Original Research Article

Human Factors Underlying Adverse

Medical Events: Revisit Root Cause Anal-

ysis Cases Using the HFACS.

Cite as: Yu-Hsun Cheng,

Sheng-Hui Hung, Tung-Wen Ko,

Pa-Chun Wang.

Human Factors Underlying Ad-

verse Medical Events: Revisit

Root Cause Analysis Cases Using

the HFACS. Fu-Jen Journal of

Medicine 3(2): 99-111, 2020.

DOI:

10.3966/181020932020091803002

Yu-Hsun Cheng1, Sheng-Hui Hung

1,2, Tung-Wen Ko

3, Pa-Chun

Wang1,4,*

1Department of Quality Management, Cathay General Hospital, Taipei,

Taiwan.

2Institute of Health Policy and Management, National Taiwan Universi-

ty, Taipei, Taiwan.

3Center for Healthcare Quality Management, Cheng Hsin General Hos-

pital, Taipei, Taiwan.

4Fu Jen Catholic University School of Medicine, New Taipei City, Tai-

wan.

*Corresponding author. E-mail address:

[email protected] (Pa-Chun Wang).

ABSTRACT Background: Appropriate management of adverse medical events (AMEs) is the corner-

stone of patient safety. Root cause analysis (RCA) is used to investigate serious or

high-frequency errors, but is limited by its inability to explain a broader scope of factors.

We re-reviewed RCA cases to understand the underlying human, organizational, or system-

ic factors affecting AMEs. Methods: A total of 40 consecutive RCA cases (2012-2016) were

retrieved from the AMEs database. A panel was organized to retrospectively re-review these

cases using the Human Factor Analysis and Classification System HFACS. Results: For

active failures, errors stemmed largely from performance-based (95%), judgment and deci-

sion-making errors (87.5%). Incorrectly followed procedures (81.6%) and accidental

equipment operation (50%) were the most common types of performance-based errors. In-

adequate real-time assessment (68.6%) and inappropriate operative actions (68.6%) were

the most common decision-making errors. For sources of latent failure, teamwork problems

(27.5%), including failure to effectively communicate (81.8%), and communicate critical

information (72.7%) were common. Inadequate supervision (92.9%) or command over-

sights (92.9%) were the most common problems related to inadequate supervision (35%).

Organizational program/policy risks not adequately assessed (50%) were the most common

problems related to policy and process problem (25%). Conclusions: The HFACS review

enhances our understanding of human factors underlying AMEs. The HFACS reveals latent

supervisory, organizational, or systematic problems that cannot be addressed through tradi-

tional RCA. Keywords: patient safety, adverse events, root cause analysis, human factors

Fu-Jen Journal of Medicine Vol. 3 No. 2, 2020.


Yu-Hsun Cheng, Sheng-Hui Hung, Tung-Wen Ko, Pa-Chun Wang 100

INTRODUCTION Patient safety involves the reduction of patient

harm from potentially avoidable unintended

outcomes [1]. Studies have revealed that 50%–

80% of adverse medical events (AMEs) are pre-

ventable [2-4]; to eliminate such errors, the ap-

propriate management of AMEs hence repre-

sents the cornerstone of patient safety work.

Through incident reporting, investigation, and

analysis, healthcare providers can correct or

re-engineer their care processes to prevent inci-

dent recurrence [2,5]. One of the most popular

tools for investigating AMEs is root cause anal-

ysis (RCA). RCA reconstructs a chain of errors

to identify the deviation of care from normal

processes. Nonetheless, with a lack of standard-

ized nomenclature and investigation procedures,

RCA report conclusions are sometimes too sub-

jective and nonspecific to facilitate any actiona-

ble safety improvement plans [5-7]. According

to the UK Health and Safety Executive defini-

tion, human factors are environmental, organiza-

tional, occupational, or individual human char-

acteristics, which influence behavior at work

such that health and safety are affected [8]. Hu-

mans and systems are prone to errors, and stud-

ies have showed that nearly 70% of medical

errors involve human factors [2-4]. Reason’s

Swiss cheese model described the penetration of

causative human errors through layers of defen-

sive barriers, leading to system collapse [9].

With much focus on the temporal sequence and

severity of departure from accepted practices in

an incident, the effectiveness of RCA is often

challenged by its incapability of exploring un-

derlying human, organization, or even systemic

factors [5-7]. Reason and others have proposed

that errors can occur at 4 levels: 1) unsafe acts

(operator actions), 2) preconditions for unsafe

acts (environmental factors contributing to er-

rors), 3) inadequate supervision (management

actions affecting the operator), and 4) organiza-

tional influences (organizational culture, policies,

and procedures that affect the operator) [9].

Based on this theory, Wiegmann and Shappell

developed the Human Factor Analysis Classifi-

cation System (HFACS) to describe human fac-

tors causing accidents from 4 tiers of categories.

Each of these categories consists of nanocodes to

represent specific human behavior or system

problems leading to errors [9-10]. The tier for

unsafe acts involves actual provider actions (er-

rors or rule violations) directly leading to events.

The tier representing preconditions for unsafe

acts includes operational, personnel, and envi-

ronmental factors. The supervision tier addresses

leadership problems, operational planning, fail-

ure or correction, and supervisory ethics. The

tier for organizational influences deals with re-

source management, organizational climate, and

operational processes (Supplement Table 1). The

HFACS provides standardized investigation

processes for the systematic analysis of common

causes of adverse events across national defense,

nuclear power, navy, aviation, and healthcare

industries. Taiwan launched its nationwide

AME-reporting system, the Taiwan Patient

Safety Reporting System (TPR), in 2004. RCA

methodology was subsequently introduced to the

healthcare industry by the Joint Commission of

Taiwan [11]. Since 2012, appropriate manage-

ment of AMEs has been listed as a national pa-

tient safety goal [12]; RCA is required by the

Ministry of Health and Welfare for major AMEs.

Aside from RCA, a comprehensive, structural,

reliable, and valid framework is urgently re-

quired to further guide organizational or even

national patient safety policies. In this study, we

used the HFACS to review our RCA cases, aim-

ing to investigate human factors underlying se-

vere or frequent AMEs.

MATERIALS AND METHODS Through continuous sampling, 40 consecutive

RCA cases (2012-2016) were retrieved from a

hospital’s (Cathay General Hospital, Taipei,

Taiwan) AME-reporting system database. The

database contains AMEs relating to areas such as

medication, patient falls, surgery, transfusion,

clinical care, public accidents, security, hospital

violence, tube-related complication, unplanned

cardiopulmonary resuscitation, laboratory testing

and examination, and anesthesia. The RCA cases

were sentinel or high-frequency events classified

according to severity assessment category (SAC)

[11,13]. The SAC is an evaluation method for

categorizing AMEs by severity of effect on pa-

tients' health and risk of incident reoccurrence.

The HFACS has been modified (from the US

Department of Defense version 7.0) and trans-

lated into Mandarin Chinese with authorization

from the original developers [10]. The Chi-

nese-version HFACS for Taiwan is a valid in-

strument (content validity index: 0.9, Cronbach’s

α: >0.7, interrater reliability Κ: 0.4-1.0) equiva-

lent to the original English version. [9] The

HFACS contains 4 tiers, 13 subitems, and 109

nanocodes (Supplement Table 1). A panel of 6

reviewers was established. All reviewers were

from clinical or management (quality and patient

safety management) backgrounds. Reviewers all




finished human factor education and were

trained to use the HFACS through a consensus

meeting. Each RCA case was randomly assigned

to 2 reviewers. Human factors leading to partic-

ular AMEs were identified and confirmed when

2 reviewers reached agreement. The distribution

of errors among tiers, subitems, and nanocodes

are provided with descriptive statistics (%). The

study was approved by the Institutional Review

Board of Cathay General Hospital

(CGH-P105095).

RESULTS AMEs related to laboratory testing and examina-

tion (n = 16), clinical care (n = 9), and medica-

tion (n = 7) were the most commonly observed

in the RCA. Most AMEs in this cohort are

ranked as being SAC level 3 (n = 15) or 4 (n =

17) (Table 1).

Acts (Active Failures)

This tier of errors contains 3 subitems and 13

nanocodes. In the 40 RCA cases, perfor-

mance-based errors for 38 (95%) and judgment

and decision-making errors for 35 (87.5%) com-

prised the most common error types, with viola-

tion for 6 (15%) less common. Procedure fol-

lowed incorrectly for 31 out of 38 (81.6%) was

the most common performance-based problem.

Inadequate real-time risk management for 24 out

of 35 (68.6%) was the most common judgment

or decision error. All of the rule violations were

workaround types for 6 out of 6 (100%) (Figure

1).

Preconditions(Latent Failures)

This tier of errors has 9 subitems and 58 nano-

codes. In the 40 RCA cases, teamwork for 11

(27.5%) and environmental for 8 (20%) factors

contributed to most of the errors, with mental

and physical state the next most common factor

for 7 (17.5%). Communication for 9 out of 11

(81.8%) and information relay for 8 out of 11

(72.7%) were the most common issues related to

teamwork. Few contributors mentioned failures

related to technical errors for 4 (50%) or physi-

cal for 1 (12.5%) environment. Not paying at-

tention for 4 out of 7 (57.1%) and negative habit

transfer for 4 out of 7 (57.1%) were common

mental contributes noted for 7 (100%). Overcon-

fidence was the most common problem related

to emotional status for 4 out of 7 (57.1%). Fa-

tigue was observed in only 2 cases for 2 out of 2

physical problems (100%) (Figure 2).

Supervision(Direct Supervisory Chain of

Command)


nanocodes. In the 40 RCA cases, inadequate

supervision for 14 (35%) and inappropriately

planned operations for 11 (27.5%) factors con-

tributed to most of the respective errors, fol-

lowed by supervisory violations for 7 (17.5%).

Supervisory or command oversights for 13 out

of 14 (92.9%) were the most common sources of

supervision inadequacy. Authorized unnecessary

hazards for 7 out of 11 (63.6%) were the most

common inappropriately planned operations.

Failure to enforce rules for 6 out of 7 (85.7%)

was the most common supervisory violation

(Figure 3).

Organization Influence (Upper-Level Man-

agement)


nanocodes. In the 40 RCA cases, policy and

process issues for 10 (25%) and resources prob-

lem for 8 (20%) were major concerns. Few of

the respective problems are related to climate

and cultural influences for 2 (5%) or to person-

nel selection and staffing for 1 (2.5%). Poorly

assessed organizational programs or policy risks

for 5 out of 10 (50%) were the most common

policy and process problems. Failure to provide

adequate operational information resources for 4

out of 8 (50%) and command and control re-

source deficiency for 3 out of 8 (37.5%) were

the main resource management problems. Little

was revealed regarding organizational climate

and culture (n = 1 out of 2, 50%) or staffing for 1

out of 1 (100%) (Figure 4).

DISCUSSION Health care is a complex system comprising

many high-reliability organizations (HROs). The

vulnerability of HROs stems from the participa-

tion of multidisciplinary teams in the processes

along a variety of patient care timelines. How-

ever, humans and systems are inherently prone

to errors; the appropriate management of AMEs

is acknowledged to be the cornerstone of patient

safety. AMEs should be reported, investigated,

analyzed, and handled appropriately.[14] Theo-

retically, by analyzing the pattern of key defects,

providers can fix errors and re-engineer their

care processes to reduce the possibility of AME

recurrence. Taiwan established its nationwide

TPR in 2004; so far, 7000 health care facilities

have participated, and the database has accumu-

lated more than 0.55 million AMEs.[11] Infor-

mation generated from the TPR database can

improve patient safety at individual, organiza-

tional, or even national levels. However, despite

relentless efforts, few substantial improvements

have been achieved in patient safety [15-17].

Since its introduction in Taiwan in 2006, the use

of RCA for AMEs has encountered some diffi-

culties: 1) No structural and standardized




framework exists for investigation;

cross-institution variability and interrater relia-

bility are often ignored. 2) Conclusions are often

subjective, and corrective recommendations are

less actionable, relying on individual reviewers’

professional backgrounds and their experiences.

3) Much focus on event reconstruction and oper-

ator performance means that factors relating to

human behavior, organizational culture, and

system weakness are not comprehensively ad-

dressed [6,7,17,18]. Traditionally, attempts to

improve patient safety in the health care industry

are largely reactive in nature, identifying and

correcting errors in care processes [19,20].

Causes of defects are not thoroughly understood.

Proactive approaches must be taken to address

systematic problems within a complex system

[7,20]. Research suggests that human error is a

causal factor in the occurrence of AMEs. AME

investigation targets have moved from skill defi-

ciency toward decision-making, attitudes, super-

visory factors, and even organizational climate

or culture. HFACS methodology is based on the

Swiss cheese model that also emphasizes active

and latent failures [9,21]. The study provides

some noteworthy findings. First, most AMEs, as

expected, involve active failures such as failure

to follow procedure, accidental operation of

equipment, inadequate real-time risk manage-

ment, and inappropriate action. These are all

sharp ends in classic RCA; environment, physi-

cal, and mental factors are less prevalent. This

proves that retrospectively determining addi-

tional causal factors is difficult when infor-

mation has not been collected during preliminary

investigation (Figure 1). Second, team-

work-related problems, particularly in relation to

communication and information relay, are well

addressed. This may be attributed to the dec-

ade-long, institution-wide, routine crew resource

management training in the respective research

hospital (Figure 2). Third, the HFACS success-

fully reflects the importance of supervisory roles

in the occurrence of AMEs, and this cannot be

overlooked (Figure 3). Fourth, latent failures,

especially in organizational climate or cultural

dimensions, have been less frequently addressed

in incident reports, a limitation of traditional

RCA. However, the HFACS review suggests

room for improvement in resource allocation and

policy modification within the hospital. The

results of studies can make the organization

think about how to improve the patient safety

and management process from the perspective of

human factors, such as improving the comfort of

the working environment and replacing and

equipment resources to prevent personnel from

affecting the medical quality and patient safety

due to the environment or equipment. Need to

appropriate assessment of applicability and ade-

quate training of manpower is required. The

management and control of risks should be fully

evaluate and grasp resource management, and

leaders need to participate in and promote medi-

cal quality and patient safety activities to en-

hance its culture. (Figure 4). No panacea exists

to ensure patient safety, and improvement targets

originate largely from event investigation find-

ings. Unfortunately, factors identified from

AMEs are often self-explanatory with little value

for further action correction. Reinforcement of

policy or processes, redundant education, or

repetitious training are formulaic, overprescribed

RCA recommendations. The use of HFACS in

this study proves that a structural prospective

AME investigation format can potentially help

with proactive patient safety management. We

suggest developing an interview guideline for

the routine use of HFACS as a complement to

RCA in every AME investigation. This study is a

retrospective study. The underlying human fac-

tors can be under-estimated owing to the lack of

related information in the original RCA reports.

CONCLUSION The HFACS review in this study enhances our

understanding of human factors in AMEs that

had previously been insufficiently scrutinized.

Aside from active process and communication

errors, the HFACS enables the prospective in-

vestigation of latent supervisory, organizational,

or systematic problems that cannot be addressed

through traditional RCA.

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TABLE

Table 1. Incidences by Category (N=40)

Category/SAC SAC 4 SAC 3 SAC 2 SAC 1 total

Laboratory and ex-

amination events

4 10 2 0 16 (40.0%)

Clinical care event 6 2 1 0 9 (22.5%)

Medication event 5 0 2 0 7 (17.5%)

Surgery-related event 1 1 2 0 4 (10.0%)

Transfusion-related

event

1 1 0 0 2 (5.0%)

Tube event 0 1 0 0 1 (2.5%)

Public accident 0 0 1 0 1 (2.6%)

Total 17 (42.5%) 15 (37.5%) 8 (20.0%) 0 40 (100%)

SAC 11,13: Severity Assessment Code, SAC




FIGURES

Figure 1. Active Failures (N=40)

1/6 (16.7%)

6/6 (100.0%)

6/40 (15.0%)

2/35 (5.7%)

7/35 (20.0%)

24/35 (68.6%)

24/35 (68.6%)

35/40 (87.5%)

4/38 (10.5%)

4/38 (10.5%)

7/38 (18.4%)

19/38 (50.0%)

31/38 (81.6%)

38/40 (95.0%)

0 5 10 15 20 25 30 35 40

Commits Widespread/Routine Violation

Performs Work-Around Violation

Ignored a Caution/Warning

Failure to Prioritize Tasks Adequately

Wrong Choice of Action During an Operation

Inadequate Real‐Time Risk Assessment

Rushed or Delayed a Necessary Action

Breakdown in Visual Scan

Over-Controlled/Under-Controlled Aircraft/Vehicle/System

Unintended Operation of Equipment

Procedure Not Followed Correctly

Performance-Based Errors

Judgment and Decision Making Errors

Violations




Figure 2. Preconditions (Latent Failures or Conditions) (N=40)

1/4 (25.0%)

2/4 (50.0%)

4/8 (50.0%)

1/1 (100.0%)

1/8 (12.5%)

8/40 (20.0%)

0 5 10 15 20 25 30 35 40

Seat and Restraint System Problems

Instrumentation & Warning System Issues

Noise Interference

Environment

Physical Environment

Technological Environment

2/7 (28.6%)

2/7 (28.6%)

2/7 (28.6%)

3/7 (12.9%)

4/7 (51.1%)

4/7 (57.1%)

7/7 (100.0%)

2/4 (50.0%)

4/4 (100.0%)

4/7 (57.1%)

1/2 (50.0%)

2/2 (100.0%)

2/7 (28.6%)

7/40 (17.5%)

0 5 10 15 20 25 30 35 40

Technical or Procedural Knowledge Not Retained After Training

Interference/Interruption

Task Over/Under Saturation

Distraction

Negative Habit Transfer

Not Paying Attention

Complacency

Overconfidence

Physical Illness/Injury

Fatigue

Physical and Mental State

Physical Problem

State of Mind

Mental Awareness

2/11 (18.2%)

3/11 (27.3%)

3/11 (27.3%)

4/11 (36.4%)

8/11 (72.27%)

9/11 (81.8%)

11/40 (27.5%)

0 5 10 15 20 25 30 35 40

Inadequate Task Delegation

Task/Mission Planning/Briefing/Debriefing Inadequate

Failure of Crew/Team Leadership

Standard/Proper Terminology Not Used

Critical Information Not Communicated

Failed to Effectively Communicate

Teamwork




Figure 3. Supervision (Direct Supervisory Chain of Command) (N=40)

Figure 4. Organization Influence (Upper-Level Management, Command Level) (N=40)

1/14 (7.1%)

1/14 (7.1%)

2/14 (14.3%)

3/14 (21.4%)

13/14 (92.9%)

14/40 (35.0%)

5/11 (45.5%)

5/11 (45.5%)

7/11 (63.6%)

11/40 (27.5%)

4/7 (57.1%)

6/7 (85.7%)

7/40 (17.5%)

0 5 10 15 20 25 30 35 40

Selected Individual with Lack of Proficiency

Improper Role‐modeling

Failed to Provide Proper Training

Failed to Identify/Correct Risky or Unsafe Practices

Supervisory/Command Oversight Inadequate

Performed Inadequate Risk Assessment ‐Formal

Selected Individual with Lack of Current or Limited Experience

Authorized Unnecessary Hazard

Allowing Unwritten Policies to Become Standard

Failure to Enforce Existing Rules

Supervisory Violations

Planned Inappropriate Operations

Inadequate Supervision

1/2 (50.0%)

1/2 (50.0%)

2/40 (5.0%)

1/10 (10.0%)

5/10 (50.0%)

10/40 (25.0%)

1/1 (100.0%)

1/40 (2.5%)

1/8 (12.5%)

1/8 (12.5%)

3/8 (3.5%)

4/8 (50.0%)

8/40 (20.0%)

0 5 10 15 20 25 30 35 40

Organizational Over-confidence or Under-confidence in Equipment

Organizational Culture (attitude/ actions) Allows for Unsafe Task/Mission

Purchasing or Providing Poorly Designed or Unsuitable Equipment

Organizational Program/Policy Risks not Adequately Assessed

Failure to Provide Adequate Manning/ Staffing Resources

Failure to remove inadequate worn-out equipment in timely manner

Inadequate infrastructure

Command and control resources are deficient

Failure to provide adequate operational information resources

Resource Problems

Personnel Selection & Staffing

Policy and Process Issues

Climate/Culture Influences




Supplement Table 1- HFACS Content of Human Factor Analysis Classifi-

cation System [9] Tier main level sub-item nano code

Tier 1 Unsafe Acts

Perfor-

mance-Based

Errors

Unintended operation of equipment

Checklist not followed correctly

Procedure not followed correctly

Over-controlled/under-controlled aircraft/vehicle/system

Breakdown in visual scan

Rushed or delayed a necessary action

Judgment & De-

cision-Making

Errors

Inadequate real‐time risk assessment

Failure to prioritize tasks adequately

Ignored a caution/warning

Wrong choice of action during an operation

Violations

Performs work-around violation

Commits widespread/routine violation

Extreme violation-lack of discipline

Tier 2 Preconditions

Environment

Physical environment

Environmental conditions affecting vision

Vibration effects vision or balance

Heat/cold stress impairs performance

External force of object impeded an individual’s

movement

Lights of other vehicle/vessel/aircraft affected vision

Noise interference

Technological environment

Seat and restraint system problems

Instrumentation & warning system issues

Visibility restrictions (not weather related)

Controls and switches are inadequate

Automated system creates unsafe situation

Workspace incompatible with operation

Personal equipment interference

Communication equipment inadequate

Physical and

Mental State

Physical problem

Substance effects (alcohol, supplements, medications,

drugs)

Loss of consciousness (sudden or prolonged onset)

Physical illness/injury

Fatigue

Inadequate adaptation to darkness

Dehydration

Body size/movement limitations

Physical strength & coordination (inappropriate for

task demands)

Nutrition/diet

State of mind

Psychological problem

Life stressors

Emotional state

Personality style

Overconfidence




Pressing

Complacency

Motivation

Motivational exhaustion (burnout)

Sensory misperception

Motion illusion-kinesthetic

Turning illusion/balance-vestibular

Visual illusion

Misperception of changing environment

Misinterpreted/ misread instrument

Misinterpretation of auditory/sound cues

Spatial disorientation

Temporal/time distortion

Mental awareness

Not paying attention

Fixation

Task over/under saturation

Confusion

Negative habit transfer

Distraction

Geographically lost

Interference/interruption

Technical or procedural knowledge not retained after

training

Inaccurate expectation

Teamwork

Failure of crew/team leadership

Inadequate task delegation

Rank/position intimidation

Lack of assertiveness

Critical information not communicated

Standard/proper terminology not used

Failed to effectively communicate

Task/mission planning/briefing/debriefing inadequate

Tier 3 Supervision

Supervisory Vio-

lations

Failure to enforce existing rules

Allowing unwritten policies to become standard

Directed individual to violate existing regulations

Authorized unqualified individuals for task

Planned Inappro-

priate Operations

Directed task beyond personnel capabilities

Inappropriate team composition

Selected individual with lack of current or limited experience

Performed inadequate risk assessment ‐formal

Authorized unnecessary hazard

Inadequate Su-

pervision

Supervisory/command oversight inadequate

Improper role‐modeling

Failed to provide proper training

Failed to provide appropriate policy/guidance

Personality conflict with supervisor

Lack of supervisory responses to critical information

Failed to identify/correct risky or unsafe practices

Selected individual with lack of proficiency

Tier 4 Organizational

Influences

Resource Prob-

lems

Command and control resources are deficient

Inadequate infrastructure




Failure to remove inadequate worn-out equipment in timely

manner

Failure to provide adequate operational information resources

Fail to provide adequate funding

Personnel Selec-

tion & Staffing

Personnel recruiting & selection policies are inadequate

Failure to provide adequate manning/ staffing resources

Policy & Process

Issues

Pace of ops-tempo/workload

Organizational program/policy risks not adequately assessed

Provided inadequate procedural guidance or publications

Organizational (formal) training is inadequate or unavailable

Flawed doctrine/philosophy

Inadequate program management

Purchasing or providing poorly designed or unsuitable equip-

ment

Climate/Culture

Influences

Organizational culture (attitude/ actions) allows for unsafe

task/mission

Organizational over-confidence or under-confidence in equip-

ment

Unit mission/aircraft/vehicle/equipment change or unit deacti-

vation

Organizational structure is unclear or inadequate




Human Factors Underlying Adverse Medical Events: Revisit Root Cause Analysis

Cases Using the HFACS

以 HFACS重新檢視根本原因分析案例：挖掘造成醫療不良

事件之人為因素

鄭伃洵 1洪聖惠 1,2柯彤文 3王拔群 1,4,*

中文摘要

背景：醫療不良事件(AMEs)的管理是促進病人安全的基石。根本原因分析

(RCA)是探討重大病人安全不良事件問題，但是由於無法解釋更廣泛的因素而受

到限制。本研究使用人為因素分類與分析工具(HFACS)回溯審視醫療不良事件，

以了解影響醫療不良事件的人為因素及各層面中錯誤原因之分佈或系統性問題。

方法：本研究回溯 2012-2016年間有做過根本原因分析之醫療不良事件，以連續

性取樣方式(continuous sampling)收集 40例醫療不良事件，以人為因素分類與分

析工具(HFACS)去系統性的挖掘每件案例發生錯誤之原因。結果：在行為層面中，

分析結果主要為基礎技能錯誤(95%)、判斷和決策錯誤(87.5%)，其中在基礎技能

錯誤當中以未依程序作業執行(81.6%)及未如預期設備操作(50%)佔多數；判斷和

決策錯誤中以現場風險評估不確實(68.6%)及採取錯的步驟/行為(68.6%)佔多數。

而在先決條件層面中，以團隊合作(27.5%)為主要因素包含溝通不良(81.8%)及重

要訊息未以正確的方式即時傳達(72.7%)佔多數。在監督層面當中，以監督不周

(92.9%)或監督不妥當(92.9%)為主要因素。在組織政策和流程方面(50%)，以組織

系統的政策/風險未充分評估(35%)為主要因素。結論：本研究進一步了解醫療不

良事件在過去使用根本原因分析未探討到的人為因素，反映出潛在的監督、組織

行為或系統性的問題，促進病人安全預防錯誤再發生。

關鍵字：病人安全、醫療不良事件、根本原因分析、人為因素

1國泰醫療財團法人國泰綜合醫院品質管理部

2國立臺灣大學健康政策與管理研究所

3振興醫療財團法人振興醫院醫療品質管理中心

4輔仁大學醫學院

*通訊作者：王拔群電子信箱 [email protected]

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