Improved FMEA Methods for Proactive Healthcare Risk Analysis

325 Pages·2019·6.322 MB·English

by  Hu-Chen Liu

Hu-Chen Liu
Improved FMEA
Methods for
Proactive
Healthcare Risk
Analysis
Improved FMEA Methods for Proactive Healthcare
Risk Analysis
Hu-Chen Liu
Improved FMEA Methods
for Proactive Healthcare
Risk Analysis
123
Hu-ChenLiu
Schoolof Economics andManagement
TongjiUniversity
Shanghai, China
Collegeof Economics andManagement
ChinaJiliang University
Zhejiang, China
ISBN978-981-13-6365-8 ISBN978-981-13-6366-5 (eBook)
https://doi.org/10.1007/978-981-13-6366-5
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Preface
The healthcare industry is labeled with high technology and high risk. With the
increasingroleofhealthcaretechnologies,thefastpaceofmedicalscience,andthe
industry’s ever-changing regulatory, legal, political, and reimbursement climate,
healthcare risk management has become more complex over time. Healthcare risk
exists in the whole medical service process, which may lead to death or serious
physicalorpsychologicalinjurytoapatientorpatients.Forthesereasons,hospitals
and other healthcare organizations are expanding their risk management programs
from ones that are primarily reactive and avoid legal exposure, to ones that are
increasingly proactive and prevent medical errors of the entire healthcare system.
Failuremodeandeffectsanalysis(FMEA)isaproactiveriskassessmenttechnique
forexaminingallfailuremodes inasystem,assessing theircauses andeffects,and
eliminatingorreducingthehighest-riskfailuresbyriskmitigationefforts.Overthe
last couple of decades, FMEA tool has been extensively used for safety and reli-
ability analysis of processes, systems, and equipment in the healthcare industry.
However, the conventional FMEA method has been criticized as having many
inherent insufficiencies, which affect its effectiveness and efficiency in the health-
care risk management.
Consideringthecomplexityanduncertaintyofhealthcarerisk,thisbookprovides
an in-depth and systematic introduction to the improved FMEA methods for
proactive healthcare risk analysis. In addition, many empirical healthcare risk anal-
ysis cases associated with healthcare process, hospital management, and medical
equipmentareincludedtodemonstratethenewFMEAmethodsbeingproposed.The
book is organized into the following four parts, which comprise 13 chapters.
Part I consists of two chapters (Chaps. 1–2) which introduce the background
knowledgeregardinghealthcareriskmanagementandreviewtheliteratureapplying
FMEA for healthcare risk analysis. Concretely speaking, Chap. 1 offers a broad
perspective on the fundamentals of this book, covering healthcare system, health-
care risk, and proactive healthcare risk management. Chapter 2 makes a compre-
hensive literature survey of the academic researches employing FMEA method to
mitigate healthcare risk and promote patient safety, based on which the current
researchtrendsand futureresearchdirectionsinthisarea ofresearchareindicated.
v
vi Preface
PartIIconsistsofsixchapters(Chaps.3–8)whichintroducetheimprovedFMEA
methods and their applications to healthcare process. Specifically, Chaps. 3 and 4
presenttheFMEAmethodusinginterval2-tuplehybridweighteddistance(ITHWD)
measure and the FMEA method using cluster analysis and prospect theory, respec-
tively. The two risk priority methods are applied to blood transfusion process to
illustrate their feasibility and effectiveness. Chapter 5 reports an FMEA method
based on interval 2-tuple linguistic ELimination Et Choix Traduisant la REalité
(ELECTRE)approachandillustratesitbyariskevaluationexampleofprotonbeam
radiotherapy. Chapter 6 proposes an alternative FMEA based on interval-valued
intuitionistic fuzzy sets (IVIFSs) and multi-attributive border approximation area
comparison (MABAC) method, and gives its illustration with a case study of radi-
ationtherapy.Chapter7isconcernedwiththeriskrankingmethodforFMEAusing
combination weighting and fuzzy VIsekriterijumska optimizacija i KOmpromisno
Resenje (VIKOR) anduses a riskanalysis exampleingeneralanesthesia process to
demonstrate the proposed FMEA method. Chapter 8 is dedicated to an uncertain
linguistic FMEA method, which uses gray relational analysis-technique for order
preference by similarity to ideal solution (GRA-TOPSIS) approach for the risk
ranking offailure modes, and applies it to a practical risk analysis case of endotra-
cheal tube (ETT) suctioning.
PartIIIconsistsofthreechapters(Chaps.9–11)whichintroducethreeimproved
FMEA methods and their applications to hospital management. In Chap. 9, we
describeariskassessmentapproachintegratingcloudmodelandpreferenceranking
organization method for enrichment evaluation (PROMETHEE) and show its
application in the working process of emergency department. Chapter 10 puts
forward arisk priority methodfor FMEA whichcombinesCOmplexPRoportional
ASsessment (COPRAS) and analytic network process (ANP), and verifies its
practicalityviaacasestudyofhospitalservicediagnosing.InChap.11,wepresent
anFMEAmethodbyapplyingfuzzysettheoryandmulti-objectiveoptimizationby
ratioanalysisplusthefullmultiplicativeform(MULTIMOORA)forfailuremodes
assessment and ranking, and apply it for the prevention of infant abduction in a
hospital.
Part IV consists of two chapters (Chaps. 12–13) which introduce the improved
FMEA methods applied to medical equipment. Specifically, Chap. 12 develops a
risk analysis model combining interval 2-tuple linguistic variables with GRA
method.Furthermore,thisFMEA modelisappliedfor analyzingtheriskofC-arm
X-ray machine to illustrate its feasibility and applicability. Chapter 13 proposes a
novel FMEA method that utilizes hesitant 2-tuple linguistic term sets to copy with
the uncertain assessments of FMEA team members, and a modified qualitative
flexible multiple criteria method (QUALIFLEX) to obtain the risk prioritization of
failuremodes.Finally,ariskanalysisexampleconcerningC-armX-raymachineis
given to demonstrate the proposed FMEA method.
This book is very interesting for practitioners and academics working in the
fields of healthcare risk management, quality management, operational research,
and management science and engineering, etc. It can be considered as the guiding
document for how a healthcare organization proactively identifies, manages, and
Preface vii
mitigates the risk of patient harm. This book can also serve as a useful reference
source for postgraduateandseniorundergraduate students incourses related tothe
fields indicated above.Thebookcontains alargenumberofillustrations. Thiswill
help the reader to understand otherwise difficult concepts and models.
We would like to acknowledge support from the National Natural Science
Foundation of China (Nos. 61773250 and 71671125), the NSFC key program
(No.71432007),andtheProgramforShanghaiYouthTop-NotchTalent.Finally,I
am grateful to my family for their constant love, understanding, and support.
Shanghai, China Hu-Chen Liu
January 2019
Contents
Part I Proactive Healthcare Risk Management
1 Healthcare Risk Management from a Proactive Perspective. . . . . . 3
1.1 Healthcare System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Healthcare Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 Healthcare Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2 FMEA for Proactive Healthcare Risk Analysis: A Systematic
Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 The Classical FMEA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.3 Literature Review Methodology. . . . . . . . . . . . . . . . . . . . . . . . 18
2.4 Detailed Review Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.4.1 Application of FMEA to Healthcare Process . . . . . . . . 26
2.4.2 Application of FMEA to Hospital Management . . . . . . 29
2.4.3 Application of FMEA to Hospital Informatization . . . . 31
2.4.4 Application of FMEA to Medical Equipment
and Production. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.5 Findings and Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.5.1 Applied Areas of FMEA. . . . . . . . . . . . . . . . . . . . . . . 32
2.5.2 FMEA Methods Adopted . . . . . . . . . . . . . . . . . . . . . . 33
2.5.3 Bibliometric Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
ix
x Contents
Part II Improved FMEA Methods and Their Applications
to Healthcare Process
3 FMEA Using ITHWD Measure and Its Application to Blood
Transfusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.2 Preliminaries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.2.1 2-Tuple Linguistic Variables. . . . . . . . . . . . . . . . . . . . 52
3.2.2 Interval 2-Tuple Linguistic Variables. . . . . . . . . . . . . . 53
3.3 Interval 2-Tuple Distance Measures . . . . . . . . . . . . . . . . . . . . . 54
3.4 The Proposed FMEA Method . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.5 Illustrative Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.5.1 Implementation of the Proposed Method . . . . . . . . . . . 60
3.5.2 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.5.3 Comparison and Discussion . . . . . . . . . . . . . . . . . . . . 66
3.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4 FMEA Using Cluster Analysis and Prospect Theory
and Its Application to Blood Transfusion . . . . . . . . . . . . . . . . . . . . 73
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.2 Related Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.3 Hesitant Linguistic Term Sets . . . . . . . . . . . . . . . . . . . . . . . . . 76
4.4 The Proposed LGFMEA Method. . . . . . . . . . . . . . . . . . . . . . . 78
4.4.1 Risk Experts Clustering . . . . . . . . . . . . . . . . . . . . . . . 79
4.4.2 Risk Assessment Aggregation . . . . . . . . . . . . . . . . . . . 81
4.4.3 Risk Factor Weighting . . . . . . . . . . . . . . . . . . . . . . . . 83
4.4.4 Failure Mode Ranking . . . . . . . . . . . . . . . . . . . . . . . . 84
4.5 Case Study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.5.1 Background Description . . . . . . . . . . . . . . . . . . . . . . . 86
4.5.2 Implementation Results. . . . . . . . . . . . . . . . . . . . . . . . 88
4.5.3 Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5 FMEA Using ITL-ELECTRE Approach and Its Application
to Proton Beam Radiotherapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
5.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
5.3 Preliminary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.4 The Proposed FMEA Method . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.4.1 Failure Mode Evaluations . . . . . . . . . . . . . . . . . . . . . . 101
5.4.2 Risk Factor Weights. . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.4.3 Failure Mode Ranking . . . . . . . . . . . . . . . . . . . . . . . . 106
Contents xi
5.5 Case Study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
5.5.1 Implementation of the Proposed Method . . . . . . . . . . . 110
5.5.2 Comparison and Discussion . . . . . . . . . . . . . . . . . . . . 118
5.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
6 FMEA Using IVIFSs and MABAC Method and Its Application
to Radiation Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
6.2 Preliminary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
6.3 The Proposed FMEA Method . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.3.1 Evaluate the Risk of Failure Modes. . . . . . . . . . . . . . . 131
6.3.2 Determine the Weights of Risk Factors . . . . . . . . . . . . 134
6.3.3 Derive the Ranking of Failure Modes . . . . . . . . . . . . . 136
6.4 Illustrative Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
6.5 Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
6.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
7 FMEA Using Combination Weighting and Fuzzy VIKOR
and Its Application to General Anesthesia . . . . . . . . . . . . . . . . . . . 151
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
7.2 Preliminaries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
7.2.1 Fuzzy Set Theory. . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
7.2.2 Fuzzy AHP Method . . . . . . . . . . . . . . . . . . . . . . . . . . 157
7.2.3 Shannon Entropy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
7.2.4 Fuzzy VIKOR Method . . . . . . . . . . . . . . . . . . . . . . . . 159
7.3 The Proposed FMEA Method . . . . . . . . . . . . . . . . . . . . . . . . . 161
7.4 Illustrative Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
7.4.1 Implementation of the Proposed Method . . . . . . . . . . . 163
7.4.2 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 167
7.4.3 Comparison and Discussion . . . . . . . . . . . . . . . . . . . . 167
7.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
8 FMEA Using Uncertain Linguistic GRA-TOPSIS and Its
Application to Endotracheal Suctioning . . . . . . . . . . . . . . . . . . . . . 173
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
8.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
8.3 Preliminaries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
8.3.1 Linguistic Variables . . . . . . . . . . . . . . . . . . . . . . . . . . 176
8.3.2 Two-Dimensional Uncertain Linguistic Variables. . . . . 177
8.4 The Proposed Method for FMEA. . . . . . . . . . . . . . . . . . . . . . . 179