reducing medication errors using lss methodology: a
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Reducing medication errors using LSS methodology: Asystematic literature review and key findings
Citation for published version:Trakulsunti, Y, Antony, J, Ghadge, A & Gupta, S 2018, 'Reducing medication errors using LSSmethodology: A systematic literature review and key findings', Total Quality Management and BusinessExcellence, pp. 1-19. https://doi.org/10.1080/14783363.2018.1434771
Digital Object Identifier (DOI):10.1080/14783363.2018.1434771
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Publisher Rights Statement:This is an Accepted Manuscript of an article published by Taylor & Francis in Total Quality Management &Business Excellence on 12/2/2018, available online:http://www.tandfonline.com/10.1080/14783363.2018.1434771
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Download date: 02. May. 2022
Reducing medication errors using LSS methodology: A systematic
literature review and key findings
Yaifa Trakulsuntia*, Jiju Antonya, Abhijeet Ghadgea and Sandeep Guptaa
aDepartment of Business Management, School of Social Sciences, Heriot-Watt University, Edinburgh,
Scotland
The paper aims to systematically review the literature of Lean, Six Sigma, Lean Six Sigma
(LSS) intervention and its tools and techniques to reduce medication errors in hospitals. Subject
specific journals according to the top journal ranking lists in the Business School and Healthcare
sector are used for assessment. Eight databases including Medline, PubMed, EBSCOhost, Web
of Knowledge, Scopus, Embase, CINAHL and PsycINFO were used to collect relevant articles
from year 1996-2016. A total of 24 studies were identified from the search which have met the
criteria for the systematic literature review. There is a noticeable increase of interest in the
application of process excellence methodologies such as Lean, Six Sigma and Lean Six Sigma
to reduce medication errors especially in the developed countries. Many themes have emerged
in this paper including: tools and techniques of Lean and Six Sigma in the context of medication
errors, Lean and Six Sigma methodology, types of medication errors, LSS project selection,
benefits, challenges and success factors. The results of this study are expected to benefit
healthcare practitioners in implementing the LSS methodology to reduce medication errors.
Keywords: Lean; Six Sigma; Lean Six Sigma; Medication errors; Healthcare; Systematic
Literature Review
1. Introduction
Medication error is one the primary causes leading to the patient morbidity and mortality
(Christopher et al., 2014). According to the National Coordinating Council for Medication
Error Reporting and Prevention (2017), medication error is a ‘preventable event that may cause
or lead to inappropriate medication use or patient harm while the medication is in the control
of the health care professional, patient, or consumer’. Medication errors can occur at every
stage of the medication delivery, stemming from prescribing, transcribing, dispensing and
administration. The severity of medication errors range from trivial to life-threatening (Walsh
et al., 2013). Medication errors have become a global issue and have been reported in different
part of the world (World Health Organization, 2016). Medication errors cause at least one death
every day and injure approximately 1.3 million people every year in the USA (U.S. Food and
Drug Administration, 2016). A study in the UK found that a prescription error may affect 12%
of all primary care patients and, 38% in those aged 75 years and above (World Health
Organization, 2016). Another study in Mexico revealed that 58% of prescriptions contained an
error, mostly due to dosage regimen and inappropriate drug selection (Zavaleta-bustos et al.,
2008). In Australia, the error rates of administration ranged from 15% to 20%, when the
administration is based on a ward stock system (Runciman et al., 2003). In Canada, 4% of
inpatients have experience of dispensing or administration errors (Covenant Health, 2015).
However, in Thailand, the rate of medication errors in Thai hospitals has not been estimated
due to a lack of national data (Chumchit et al., 2015). Evidence shows that medication errors
contribute to patient injury and death and further contributes to a detrimental economic
outcome. In the UK, medication errors cost the National Health Service (NHS) up-to £770
million for adverse drug reaction and inpatient harm in the hospitals (Torjesen, 2014). Unless
a new approach is implemented to prevent medication errors, patients will continue to die or
be injured as a result of such errors (Crane & Crane, 2006). Therefore, it is extremely important
for the healthcare sectors to employ an appropriate process excellence methodology to reduce
medication errors for improving patient safety and thereby a reduction in the financial costs.
The healthcare managers have been unsuccessful in utilizing effective tools and processes to
reduce medication errors (Hussain et al., 2015). Buttigieg et al. (2016) claimed that quality in
healthcare worldwide has been improved by continuous improvement (CI). It is widely
implemented in every type and size of organization, from manufacturing to the public sector,
to manage the achievement of quality (Brown et al., 2008). The most popular business
strategies for employment of continuous improvement in the manufacturing and service sectors
are Lean and Six Sigma (Albiliwi et al., 2015). Lean focuses on the elimination of waste and
non-value added activities from the process, improvement of speed and reduction of
operational costs. Six Sigma, on the other hand, aims to reduce variation within a process which
can result in defects or errors. Lean or Six Sigma is appropriate to solve specific problems
(Laureani & Antony, 2017a). However, the integration of Lean and Six Sigma can contribute
to better outcomes than the separate implementation of each methodology (Bhat et al., 2014).
Lean Six Sigma (LSS) uses appropriate tools from both philosophy through the implementation
of DMAIC methodology (Albiliwi et al., 2015; Laureani & Antony, 2017b ). Multiple
researchers have implemented Lean, Six Sigma and LSS in several areas of the healthcare
sector (e.g. Bhat et al., 2014; Gijo & Antony, 2014; Gijo et al., 2013). However, a systematic
literature review of Lean, Six Sigma and LSS to reduce medication errors has not yet been
reported in the current literature.
Therefore, the aim of this study is to systematically review the literature of Lean, Six
Sigma, LSS intervention and its tools and techniques to answer the following research
questions:
• What tools and techniques of Lean and Six Sigma have been used to reduce medication
errors?
• What are the benefits, challenges and success factors of LSS that have led to a reduction
in medication errors?
• What is the current status in the use of process excellence methodologies to reduce
medication errors in the global context?
2. Methodology
In this study, a systematic review was conducted to find the relevant articles by following four
main steps: (1) ascertain the inclusion and exclusion criteria; (2) identify the sources of
information used to collect the articles and search strategy; (3) describe the study selection
process; and (4) specify the data extraction process. These four steps have also been found in
previous systematic literature review studies such as Balaid et al. (2016), Burns et al. (2016)
and Teo et al. (2016). The following steps have been used in the systematic literature review
methodology.
2.1 Eligibility criteria
The eligibility criteria are identified to ensure that the included articles are relevant to the study
(Balaid et al., 2016). In this review, inclusion criteria included the academic articles in peer
reviewed journals published in English between January 1996 and December 2016. Articles
were included when they clearly discussed the implementation of Lean, Six Sigma, LSS and
its tools and techniques to reduce medication errors or improve medication management. In
contrast, exclusion criteria included grey literature such as books, magazines, conference
papers, white papers, editorials etc. Studies published in all languages other than English,
published before January 1996 were also excluded. The review excluded studies that discussed
other methodologies, e.g., continuous improvement such as total quality management (TQM),
Kaizen, technology to reduce medication errors, improve medication management and
reconciliation.
2.2 Information sources and search strategy
The articles were initially retrieved through subject specific journals and key academic
databases. Subject specific journals were identified based on the top journal ranking lists in the
Business School and Healthcare sectors. Primary databases used included Medline, PubMed,
EBSCOhost, Web of Knowledge, Scopus, Embase, CINAHL and PsycINFO. These eight
Figure 1. Study selection process.
academic databases were selected because they provided relevant journal articles
covering several fields of study such as Biomedicine, Health, Pharmacological, Social
Science, and Natural Science. The search strategy began with the identification of
keywords, search strings and applying search intervention in the selected databases. The
following search strings: “Lean” AND “Medication Error” “Six Sigma AND Medication
Error” “Lean Six Sigma AND Medication Errors” “Tool and Technique AND
Medication Error” “Quality Tool AND Medication Error” and “Quality Technique AND
Figure 1. Study selection process.
Relevant articles identified through database search:
Medline (n = 1955), PubMed (n = 1377), EBSCOhost (41), Web of Knowledge (n = 418), Scopus (n =857), Embase (n = 662), CINAHL (n = 48), PsycINFO (n= 11)
Total records (n = 5369)
Article retrieved from subject specialized journal search (n =2)
Reasons for exclusion Excluded based on title and abstract Duplicate articles Met the exclusion criteria
- Not peer reviewed - Published before
January 1996 - Published in languages
other than English
Full text article reviewed for eligibility
n = 42
Reasons for exclusion Met the exclusion criteria
- Article discussed methodologies other than Lean, Six Sigma, LSS and its tools and techniques
Articles included in the study n = 24
Lean (n =5) Six Sigma (n=5) Lean Six Sigma (4) Tools and techniques (10)
Medication Error” were applied to search all of the relevant articles from the selected
journals and aforementioned databases.
2.3 Study selection process
Figure 1 presents the selection process of the study. In each step, the number of included and
excluded studies are documented with explanations for exclusion (Tranfield et al., 2003). A
total of 5,369 articles were initially retrieved from searching the databases and an additional
two articles from the subject specific journals. The reviewers independently screen the titles
and abstracts by applying the inclusion and exclusion criteria (Ozawa & Sripad, 2013).
Duplicate studies and articles subject to the exclusion criteria were discarded at this stage. The
remaining 42 full-text articles were carefully reviewed based on the inclusion and exclusion
criteria. Eighteen articles had to be excluded because they discussed methodologies other than
Lean, Six Sigma, LSS and its tools and techniques. Finally, 24 final articles were selected for
the inclusion in the study for further analysis.
2.4 Data extraction
The data from the included articles were extracted and stored on the data extraction form to
reduce human error and bias (Tranfield et al., 2003). The authors independently reviewed each
article and carefully placed the data into MS excel spreadsheets (Balaid et al., 2016). The
extracted data included year of publication, journal and article title, objective, type of study,
authors’ country, tools and techniques used, key findings, benefits, challenges, and success
factors. These items were linked to research questions and the overall aim of the research
(Balaid et al., 2016). Finally, the included studies are represented in a form of table providing
a summary and visual presentation of the studies (Denyer & Tranfield, 2009).
3. Key findings
3.1 Publication trend
The study shows the publication trend of Lean, Six Sigma, LSS and its tools and techniques
implementation in the healthcare sector to reduce medication errors and improve medication
management. As shown in Figure 2, a study by McNally et al. (1997) used failure mode and
effect analysis (FMEA) to eliminate possible medication errors in a ward stock drug
distribution system in an Australian hospital. It is interesting to note that, in 2004, Six Sigma
was first applied to reduce dispensing error in a pharmacy department in Taiwan (Chan, 2004).
The following year LSS was implemented to reduce medication order entry errors in a mid-
sized hospital (Esimai, 2005) while Lean was first implemented to reduce missing dose
incidents in 2009 in a university hospital inpatient pharmacy (Hintzen et al., 2009). In 2015,
four papers were published about the reduction in medication errors. A study by Critchley
(2015) used Lean methodology to improve medication administration safety in a community
hospital in Canada, while Rodriguez-Gonzalez et al. (2015) used FMEA to improve medication
administration process in a hospital setting in Spain. Hussain et al. (2015) recommended the
implementation of the Toyota Production System (TPS), combined with human performance
improvement (HPI), to eliminate medication errors in the hospitals. However, Luton et al.
(2015) used Lean and Six Sigma methodology to reduce the occurrence of errors in the
preparation, dispensing, and administration of human milk and formula. Although, few studies
were published between 2003 and 2016, the trend shows an increase between the selected
periods.
3.2 Country distribution
The country of the selected studies was classified according to the origin of the first author of
the articles. Figure 3 shows that the USA has the highest number of publications, which
accounts for 60% compared with other countries. Spain is second in term of number of
publications with three articles which employed FMEA to reduce medication errors in the
medication process. The other countries - England, Iran, Taiwan, Italy, Canada and Australia -
have published one article each on the search topic.
Figure 2. Trend of publication between 1996 and 2016.
The study demonstrates that the USA is the leading country reporting Lean, Six Sigma
and LSS implementation to eliminate medication errors in hospitals. In Asia, a study conducted
in Taiwan by Chan (2004) shows improvement in pharmacist dispensing errors at an outpatient
clinic through the implementation of Six Sigma. In other Asian countries such as Thailand,
Malaysia and Indonesia, there is a lack of data on medication errors, resources and government
support (Salmasi et al., 2015) which may lead to the limited research on medication errors in
Figure 3. Selected study distribution based on country of publication.
Figure 2. Trend of publication between 1996 and 2016.
Figure 3. Selected study distribution based on country of publication.
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Figure 2. Trend of publication between 1996 and 2016.
Figure 3. Selected study distribution based on country of publication.
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the Asian countries. The review also found that a study by Critchley (2015) from Canada was
the only published research using lean methodology to improve medication administration
safety in a community hospital; Whereas other countries mostly focused on FMEA adoption
to reduce possible medication errors in the medication process.
3.3 Methodology category
Figure 4 presents the distribution of types of articles reporting implementation of Lean, Six
Sigma, LSS and its tools and techniques used to reduce medication errors in the healthcare
sector. The findings of the analysis demonstrated that over three-quarters of the papers were
based on case studies because LSS methodology can be applied in a particular organization to
evaluate the benefits of LSS implementation. The remainder were conceptual, theoretical or
technical studies.
Figure 4. Selected study distribution
based on type of methodologies.
Figure 5. Selected studies distribution
based on number of authors.
3.4 Number of authors
The distribution of number of authors is shown in Figure 5. In total, 24 articles were selected
for review and as can be seen, the majority of the selected studies were written by three to
seven authors, followed by two authors whereas a few articles were written by single and more
Figure 4. Selected study distribution based on type of methodologies.
Figure 5. Selected studies distribution based on number of authors.
19, 79%
3, 13%
1, 4%
1, 4%
Case study Conceptual Theritical Technical
3, 12%
4, 17%
16, 67%
1, 4%
single Two Three to seven More than seven
Figure 4. Selected study distribution based on type of methodologies.
Figure 5. Selected studies distribution based on number of authors.
19, 79%
3, 13%
1, 4%
1, 4%
Case study Conceptual Theritical Technical
3, 12%
4, 17%
16, 67%
1, 4%
single Two Three to seven More than seven
than seven authors. The highest number of co-authors was nine, for the publication by
Aboumatar et al. (2010), applying LSS solutions to reduce the possibility of chemotherapy
preparation errors.
3.5 Tools and techniques of Lean Six Sigma in the context of medication errors
From the reviewed articles, 22 lean tools which were aimed at reducing errors in the medication
process were identified. These included process mapping, brainstorming, Voice of the
Customer (VOC), standardized operating procedures, poka-yoke, cause and effect diagram,
Value Stream Mapping (VSM), just in time (JIT), process observation and analysis, time and
motion study, work cell optimization, visual process controls, workplace inspection, 5 why
root cause analysis, A3 problem solving report, one-piece flow, Kanban, spaghetti diagram,
bird’s eye view maps, 5S practice, standardized weekly audit and two bin replenishment.
Figure 6 shows the top five lean tools which are widely used to reduce medication errors. It is
interesting to highlight that process mapping is the most popular lean tool to reduce such errors
because it visually represents the process steps and helps to identify the potential errors in the
medication delivery process.
Figure 6. Top five lean tools used to reduce medication errors.
Figure 6. Top five lean tools used to reduce medication errors.
Figure 7. Pareto chart demonstrating types of medication errors.
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Process mapping
Standardized operating
procedures
Value stream map
Visual process control
Poka-yoke
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In addition, 22 Six Sigma tools and techniques were extracted from the review. These
tools and techniques are widely used in the Six Sigma implementation and included process
mapping, problem definition, data collection and analysis, pareto diagram, simple linear
regression, brainstorming, Quality Function Deployment (QFD), VOC, Pugh selection
analysis, control chart, cause and effect analysis, FMEA, review historical chart, baseline
measurement, poka-yoke, run chart, t-test, chi square, process control plan, standardized
operation procedures, SIPOC (Supplier-Input-Process-Output-Customer) analysis and QFD
matrix. Table 1 shows Lean and Six Sigma tools and techniques are used against the DMAIC
roadmap by five studies. It should be noted that Lean tools which are used in DMAIC
methodology include process mapping, brainstorming and poka-yoke.
Table 1 Lean Six Sigma tools used in various phases of DMAIC methodology.
Study title
Define
Measure Analysis Improve Control
lean Six Sigma reduces medication errors (Esimai, 2005).
Problem definition
Project charter
Process mapping
Data collection and analysis Pareto diagram
Brainstorming
Brainstorming
Standardized operating procedures
Simple linear regression analysis
Hospital reduces medication errors using DMAIC and QFD (Bentiz et al., 2007).
Not mentioned Process mapping
Brainstorming
QFD Pugh Selection Matrix
VOC
Control chart
Use of six sigma to improve pharmacist dispensing errors at an outpatient clinic (Chan, 2004).
Review historical data
Baseline measurement
Data collection and analysis
Process mapping Poka-yoke
Control chart Run chart
Using Six Sigma to reduce medication errors in a Home - Delivery Pharmacy Service (Castle et al., 2005).
Process mapping
Data collection and analysis
Brainstorming
Process control plan
Poka-yoke Linear regression analysis
Control chart
Applying Lean Six Sigma to improve medication management (Nayar, et al., 2016)
Process mapping
Data collection and analysis
Brainstorming
Brainstorming
Brainstorming
Moreover, the tools and techniques of LSS are used across the medication process
including prescribing, transcribing, dispensing and administration, as shown in Table 2. FMEA
is a Six Sigma tool used in every stage of medication process, because it could identify the
potential of medication errors in every phase of the medication process. Other tools and
techniques such as process mapping and data collection and analysis are used in prescribing
and dispensing phase. However, in transcribing phase, FMEA is a single tool used to reduce
errors because of the limitation of the literature.
3.6 Lean Six Sigma project selection
The selection of the right project is a critical activity within any continuous improvement
initiative (Sharma & Chetiya, 2010).If organizations do not select the right project at the early
phase of the initiative, the LSS initiative could be a waste of resources, potentially leading to
frustration for many within an organization. Antony (2004) provided eight key guidelines for
the selection of LSS projects; (1) projects should be linked to a business strategy plan and
organization goals; (2) projects should represent a major improvement in both financial
improvement and process performance improvement; (3) projects should be doable in less than
six months; (4) project goals must be clearly identified and measureable; (5) project selection
criteria should be created; (6) the projects should be supported and approved by senior
management; (7) project deliverables should be defined in terms of their impact on one or more
critical characteristics in the products or services; (8) projects must be selected based on
realistic and good metrics. However, in this review, none of the selected studies discuss how
to select LSS projects and what criteria should be used to select the project. Only five studies
mentioned project team members without explaining the criteria to select such members
(Bentiz et al., 2007; Castle et al., 2005; Chan, 2004; Esimai, 2005; Luton et al., 2015) and their
responsibilities and project’s goals (Benitez et al., 2007; Castle et al., 2005; Luton et al., 2015).
Table 2 Lean Six Sigma tools and techniques used in medication process.
Prescribing
Transcribing
Dispensing
Administration
Process mapping Cause and effect analysis Poka-yoke FMEA Data collection and analysis Linear regression analysis Control chart Process control plan Brainstorming
FMEA Process mapping Data collection and analysis Linear regression analysis Control chart Process control plan Brainstorming Review historical data VOC Baseline measurement Poka-yoke Run chart FMEA
Value Stream Mapping
Just in time Process observation and analysis Time and motion study Work cell optimization Visual process control
Workplace inspection t-test Chi-square Linear and logistic regression analysis FMEA 5 why root cause analysis A3 problem solving report Project team charter SIPOC Spaghetti diagram Bird's eye view maps Standard operating procedures Cause and effect analysis Run chart 5 S
3.7 Lean and Six Sigma methodologies
Six Sigma has the ability to reduce variability from processes from two major methodologies :
DMAIC and Design for Six Sigma (DFSS) (Aboelmaged, 2011). DMAIC consists of five
phases of continuous improvement cycle: Define the scope and identify the problem associated
with the process; Measure the baseline performance showing the current state of the problem;
Analyse the root causes of the problem; Improve the current state by deriving the root causes
of the problem; and Control the sustainability of process performance (Wang & Chen, 2010).
It is important to note that Six Sigma methodology is used to tackle problems in existing
processes and the stringent assumption we always make is that the design is robust. In contrast,
DFSS methodology employs the following five phases: define; measure; analyse; design;
optimise and, verify (DMADOV) to replace existing systems with new processes (Albiliwi et
al., 2017).
The authors observed from the analysis of current literature that only five selected
studies have implemented DMAIC methodology to reduce medication errors in different
categories. Benitez et al. (2007) and Esimai (2005) followed the DMAIC methodology to
improve the order medication entry process. Benitez et al. (2007) revealed that, during the
improve phase, DFSS is implemented to design one standard medication order process which
can be used in whole hospital units except an emergency unit (EU). As a result of DFSS
initiatives, the chronological sheet from all patient charts is replaced by the existing patient
care activity record (PCAR). After the process change, the percentage of order entry accuracy
improved by 90% to less than 0.04 per bed every month for four month. Chan (2004)
implemented DMAIC methodology to reduce dispensing errors in a pharmacy department
which can reduce 230 errors per million in dispensing errors. A study by Castle et al. (2005)
used DMAIC methodology to reduce several types of medication errors including wrong drug
selection, wrong direction and sound-alike/look-alike (SALA) errors in a home-delivery
pharmacy service. A case study conducted by Nayar et al. (2013) used the DMAIC process
step to improve medication management of dual care veteran patients.
Lean methodology includes five key principles: define value; define value stream;
create flow; establish pull based on customer requirement; and seek perfection (Carlborg et al.,
2013). This study found that of the selected studies most use only lean tools to reduce
medication errors. However, the study conducted by Critchley (2015) implemented Lean
methodology to improve medication administration safety in a community hospital in the
community hospital in Canada.
3.8 Types of medication errors
Types of medication errors can be classified based on different factors such as the medication
process and the underlying cause. Medication errors can occur at every stage of the medication
process stemming from prescription, transcribing, dispensing and administration of the drug
by the nurse. Prescription error encompasses faults in the dose selection, omitted transcription
and poor handwriting (Velo & Minuz, 2009). Medication ordering errors occur when the
incorrect drug is ordered by physicians (Stefanacci & Riddle, 2016). Dispensing errors are
linked to the pharmacy where such errors involve the dispensing of an incorrect medication or
dosage form to the patient (Roy et al., 2005), misinterpretation of the order, name confusion,
poor labeling and poor packaging and design (Fisher et al., 2001; Revere & Black, 2003).
Administration errors include omission error, wrong time errors, improper dose errors, wrong
dosage (Stefanacci & Riddle, 2016) improper route of administration and wrong patient
(Revere & Black, 2003).
The review of literature indicated that administration error is the most dominant type
of medication error, as shown in Figure 7. This demonstrates that errors occurring in the
administration phase need to be greatly reduced, followed by reduction in dispensing,
preparation and prescription errors. The study also found that administration errors are the area
where Lean thinking and FMEA have most been used to reduce errors, while Six Sigma is
commonly used to reduce dispensing errors in the pharmacy department.
Figure 7. Pareto chart demonstrating types of medication errors.
3.9 Benefits
3.9.1 Lean and Six Sigma
Figure 8 presents the benefits of Lean, Six Sigma and LSS in the context of medication errors
from a thorough review of various case studies and other pertinent literature. The key benefit
of such interventions through process excellence methodologies is the reduction of errors in
the medication process such as missing medication (Hintzen et al., 2009), expired medication
errors (Hussain et al., 2015) and order entry errors by the pharmacy (Benitez et al., 2007;
Esimai, 2005), mostly occurring in the pharmacy department in the hospital. In terms of
financial benefits, the implementation of LSS has reduced the estimated labour cost of
$550,000 in a mid-sized hospital (Esimai, 2005) and can save the hospital inpatient pharmacy
$82,650 annually by reducing the number of errors and missing doses (Hintzen et al., 2009).
Moreover, the implementation of Six Sigma can also improve staff working performance. For
instance, Chan (2004) mentioned that the reduction in the number of human errors during the
Figure 6. Top five lean tools used to reduce medication errors.
Figure 7. Pareto chart demonstrating types of medication errors.
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Standardized operating
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Value stream map
Visual process control
Poka-yoke
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process of their working can improve staff frontline performance after the adoption of Six
Sigma methodology.
Figure 8. Pareto chart for benefits derived from LSS and its tools and techniques
adoption to reduce medication errors.
3.9.2 FMEA
FMEA has its own benefits such as reduction of medication errors in the prescribing,
preparation, validation, dispensing and administration process (Arenas Villafranca et al., 2014;
Lago et al., 2012; Rodriguez-Gonzalez et al., 2015; Sheridan-Leos & Schulmeister, 2006).
Another benefit of FMEA is the improvement of safety in the medication preparation process
(Aboumatar et al., 2010), prescription process (Kunac & Reith, 2005) administration process
(Riehle et al., 2008; Rodriguez-Gonzalez et al., 2015) and drug delivery process (Lago et al.,
2012).
Figure 8. Pareto chart for benefits derived from LSS and its tools and techniques
adoption to reduce medication errors.
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3.10 Challenges
The challenges of LSS identified from a thorough review of the literature include: lack of top
management support and availability of data. A study by Castle et al. (2005) identified that a
team implementing a Six Sigma project to reduce medication errors in a home-delivery
pharmacy service encountered many impediments in the early phase. Firstly, it was difficult to
gain agreement to make changes in the process and senior management buy-in to agree to this
transformation. People in the organization are afraid of unknown and do not understand the
need for change when important change occurs (Banuelas Coronado & Antony, 2002).
Secondly, there were variations among pharmacies in the data collection process which can
contribute to contradictory medication error reporting and, finally, there was a lack of advanced
data collection tools. Four researchers further report the challenge of FMEA implementation
to reduce errors in the medication process. The major challenge of FMEA adoption is that it is
a costly and time consuming processes Also, it can be challenging for those who are
inexperienced (Sheridan-Leos & Schulmeister, 2006). Although, FMEA can be considered as
of great value, there is little evidence to support that it can be used for quantitative prioritization
of the failures of the process because it lacks both reliability and validity (Velez-Diaz-Pallares
et al., 2013).
3.11 Critical Success Factors
Critical success factors are important to the successful implementation of any quality
improvement initiates (Desai et al., 2012). It can help people to understand what factors are
important for making LSS successful and what factors are not important to the success (Antony
& Banuelas, 2002). In the review, seven success factors were extracted from LSS
implementation to reduce medication errors including understanding of LSS tools and
techniques and its philosophy, top management support, training, staff engagement, leadership
capability, appropriate team formation or implementation infrastructure and cultural change.
According to the literature, understanding LSS tools and techniques and its philosophy
plays a big role in LSS implementation. Before implementation of an LSS project, appropriate
management support helps the team towards specific needs and goals by understanding Lean
tools and philosophy (Hintzen et al., 2009) and Six Sigma philosophy (Chan, 2004). A clear
vision from the top management (Luton et al., 2015) and appropriate management support for
dedicated offline resources from senior administration are critical factors leading to the success
of LSS projects (Ching et al., 2013; Hintzen et al., 2009). Top management of the organization
must drive LSS initiatives (Banuelas Coronado & Antony, 2002). The LSS initiative will be
difficult without the top management support and commitment (Pande et al., 2000).Training is
another significant factor leading to successful projects. As reported by Castle et al. (2005), the
entire team received training as green or black belts while the executive staff or project sponsor
trained as Lean Six Sigma yellow belts (Hintzen et al., 2009). The belt system assists the
execution of LSS project throughout the organization (Antony&Banuelas, 2002). Critchley
(2015) states that the level of staff engagement in identifying opportunities to improve and
implement solutions to those opportunities using Lean tools is a key factor leading to the
success of the project. Moreover, leadership involvement is required to lead to patient safety
improvement (Critchley, 2015). Leadership has the ability to motivate people in the
organization and encourage them to collaborate in order to achieve the business goals (Pamfilie
et al., 2012). Identifying appropriate team members is another factor leading to the success of
the project. For example, a team member is selected based on the basis of the alignment of their
daily responsibility with the project’s objective in order to maximize resources (Castle et al.,
2005). Embedding LSS into the healthcare culture also results in the success of the project
(Luton et al., 2015).
It is important to highlight that in the literature, the implantation of FMEA in the context
of medication errors has shown its own success factors which include staff engagement,
multidisciplinary team, well-communicated plan, use of an FMEA facilitator, leadership
sponsor and sufficient resources.
4. Discussion and Implications
The systematic review identified 24 research papers from eight databases and subject specific
journals. The low sample size of selected studies was also found in other systematic literature
review articles such as Andersen et al. (2014), Moraros et al. (2016), Mason et al. (2015),
Deblois & Lepanto (2016), Burns et al. (2016), Materla et al. (2017) and Vest & Gamm (2009).
As Albiliwi et al. (2015) mention, when conducting a literature review there is no agreed
minimum number of papers to be reviewed. Additionally, of the 24 studies included in this
review, five applied Lean, five used Six Sigma, four used LSS and 10 used LSS tools and
techniques. It can be considered that 40% of the selected studies included FMEA
implementation, because it is one of the Six Sigma tools used in the improve phase of the
methodology. The literature also indicates that the implementation of Lean, Six Sigma, LSS
and FMEA increased between 2015 and 2016 which accords with the study of Mason et al.
(2015). The USA is the leading country that reports the highest number of Lean, Six Sigma,
LSS and FMEA publications. Albiliwi et al. (2015) report that the USA published the largest
number of LSS articles in the manufacturing sector. However, in Europe, a few papers have
been published on Lean, Six Sigma, LSS and FMEA to reduce medication errors. In Asia,
Thailand is far behind the USA because of a lack of knowledge to select the tools, lack of
project selection criteria and lack of resources (Nonthaleerak & Hendry, 2008).
Tools and techniques, benefits, challenges, success factors of Lean, Six Sigma, LSS
and FMEA are explored in the literature. The literature shows that Lean and Six Sigma tools
implemented across DMAIC methodology mostly use non-statistical tools especially in the
improve phase. FMEA is the only six sigma tool used to identify the potential errors in every
phase of the medication process. However, other tools such as process mapping and cause and
effect analysis could be used in the four phases of the medication process to understand the
current medication process flow and cause of errors. The literature also shows that
administration errors are the most dominant type targeted by healthcare practitioners to reduce.
This demonstrates that there is a high rate of possible errors in the medication administration
process (Najar et al., 2016). The review of literature reveals that Lean, Six Sigma and LSS
implementation can reduce errors in the medication delivery process. However, the
implementation of FMEA has shown its own benefit which is the reduction of potential errors
in the medication process. Additionally, from the analysis of literature, important factors which
are responsible for medication errors’ reduction are identified including manpower such as
minimizing distraction and workload of the staff members; machinery such as using automatic
dispensing machine and computerized physician order management (CPOM); environment
such as an improved medication room layout and method, such as using LSS methodology.
Moreover, the finding of this review indicates that lack of top management support and the
data collection process are the most challenging factors in the implementation of Lean and Six
Sigma to reduce medication errors, whereas time constraints and cost are the barriers of FMEA
adoption. The success factors which are the same for Lean and Six Sigma include
understanding the toolkit and training. This finding, similar to that of Pepper & Spedding
(2010), indicates that training staff is a keystone to gaining significant results. However,
Albiliwi et al. (2015) claim that Six Sigma training is costly for many organizations.
Researchers argue that it is necessary for organizations to invest in training staff before the
implementation of the LSS project. However, training alone would not guarantee the successful
project. Also, coaching and mentoring by champions and experts are needed, but this has not
been mentioned in the current literature. Additionally, the findings of LSS critical success
factors in reducing medication errors are very similar to critical success factors in healthcare
sectors in several aspects including support and commitment of top management, appropriate
training and education, staff commitment to process improvement and understanding of LSS
methodology and its associated tools and techniques. In healthcare, many researchers mention
that project selection and prioritization is critical to the success of the project (Antony et al.,
2007; Desai et al., 2012; Manville et al., 2012; Bhat et al., 2016), however, this factor has not
appeared to be critical in the context of medication errors. Selection of the right project can
help the management and staff to realise the true benefits and strengths of LSS (Bhat et al.,
2016).
The key research gaps in the current literature are identified. The extant literature does
not provide a roadmap to guide practitioners to follow for the implementation of Lean, Six
Sigma or LSS to reduce medication errors. The current literature highlights that very few
studies use pure Lean, Six Sigma and LSS to reduce medication errors. Previous studies have
shown a lack of understanding in how to use LSS tools and techniques. There are a few papers
published on the fundamental challenges in the use of LSS methodology to tackle medication
errors. Moreover, several limitations of this study have been identified. The number of included
studies is very limited because medication error is a very specific area for review when
compared with other sectors such as manufacturing and healthcare.
The key findings of the review can be used as a guideline for healthcare practitioners
before implementation of an LSS project to reduce medication errors by considering their
benefits, challenges and success factors. Also, this study is valuable for healthcare sectors
seeking to reduce errors in the medication process.
5. Conclusions and agenda for future research
The key finding of the systematic literature review reveals that there is a noticeable increase of
interest in the Lean, Six Sigma and LSS application to reduce medication errors especially in
the developed countries. Continuous improvement methodologies such as Lean, Six Sigma and
LSS can be implemented to reduce errors in the medication delivery process. Furthermore, the
integration of Lean and Six Sigma may lead to better results, because practitioners can use
tools from both philosophies. Lean tools can be employed to improve the workplace
environment which could reduce staff stress and dose miscalculation while six sigma tools can
be utilised to reduce errors in the medication process. Also, practitioners can draw upon FMEA
to reduce the potential of medication errors and improve the safety of medication processes.
Additionally, healthcare practitioners should consider the challenge of Lean, Six Sigma or LSS
before beginning the LSS project. Project team members should understand the purpose of the
Lean and Six Sigma philosophy and its tools and techniques as well as undergoing the training.
However, lack of management support and insufficient data collection processes can lead to
the failure of the project.
The review reveals that the current literature does not provide a Lean, Six Sigma or
LSS road map for practitioners to follow in order to reduce medication errors in their hospitals.
Therefore, this could be a fruitful area for the future research. Moreover, another important
topic for consideration is that the previous literature does not discuss how to select LSS projects
and what criteria to use to select such projects. Furthermore, there is a need to understand how
the LSS toolkit can be implemented against each phase of DMAIC methodology.
References
Aboelmaged, M. G. (2010). Reconstructing six sigma barriers in manufacturing and service organizations: The effects of organizational parameters. International Journal for Quality & Reliability Management, 28(5), 519–541. doi:10.1108/02656711111132562.
Aboumatar, H. J., Winner, L., Davis, R., Peterson, A., Hill, R., Frank, S., … Farmer, D. (2010). Applying Lean Sixma solutions to mistake-proof in Chemotherapy. The Joint Commission Journal on Quality and Patient Safety, 36(2), 79–86.
Albiliwi, S., Antony, J., & Abdul Halim Lim, S. (2015). A systematic review of Lean Six Sigma for the manufacturing industry. Business Process Management Journal, 21(3), 665–691. doi:10.1108/BPMJ-03-2014-0019
Albiliwi, S., Antony, J., Arshed, N., & Ghadge, A. (2017).Implemenation of Lean Six Sigma
in Saudi Arabian organization: findings from a survey. International Journal of Quality & Reliability Management, 34(4), 508–529. Andersen, H., Røvik, K. A., & Ingebrigtsen, T. (2014). Lean thinking in hospitals: is there a
cure for the absence of evidence? A systematic review of reviews. BMJ Open, 4, 1–8. doi:10.1136/bmjopen-2013-003873
Antony, J., & Banuelas, R. (2002). Key ingredients for the effective implementation of Six Sigma program. Measuring Business Excellence, 6(4), 20–27.
Antony, J. (2004). Six Sigma in the UK sevice organisations: results from a pilot survey. Managerial Auditing Journal, 19(8), 1006–1013. doi:10.1108/02686900410557908
Antony, J., Antony, F., Kumar, M., & Rae Cho, B. (2007). Six sigma in service organisations: benefits, challenges and difficulties, common myths. International Journal of Quality & Reliability Management, 24(3), 294-311.
Arenas Villafranca, J. J., Gómez Sánchez, A., Nieto Guindo, M., & Faus Felipe, V. (2014). Using failure mode and effects analysis to improve the safety of neonatal parenteral nutrition. American Journal of Health-System Pharmacy, 71, 1210–1218. doi:10.2146/ajhp130640
Ashley, L., Dexter, R., Marshall, F., McKenzie, B., Ryan, M., & Armitage, G. (2011). Improving the safety of chemotherapy administration: An oncology nurse-led failure mode and effects analysis. Oncology Nursing Forumursing Forum, 38(6), 436–444. doi:10.1188/11.ONF.E436-E444
Balaid, A., Abd Rozan, M. Z., Hikmi, S. N., & Memon, J. (2016). Knowledge maps: A systematic literature review and directions for future research. International Journal of Information Management, 36, 451–475.
Bañuelas, R., & Antony, J. (2003). Going from Six Sigma to design for Six Sigma: an exploratory study using analytic hierarchy process. The TQM Magazine, 15(5), 334–344. doi:10.1108/09544780310487730
Benitez, Y., Forrester, L., Hurst, C., & Turpin, D. (2007). Hospital reduces medication errors using DMAIC and QFD. Quality Progress, 40(1), 38–45.
Buttigiet, S. C., Gauci, D., & Dey P. (2016) Countinuous improvement in a Maltese hosptital using logical framework analysis. Journal of Health Organization and Management, 30 (7), 1026-1046. doi: 10.1108/JHOM-11-2015-0185
Bhat, S., Gijo, E. V., & Jnanesh, N. A. (2014). Application of Lean Six Sigma methodology in the registration process of a hospital. International Journal of Productivity and Performance Management, 63(5), 613–643. doi:10.1108/IJPPM-11-2013-0191
Bhat, S., Gijo, E.V. & Jnanesh, N.A. (2016). Productivity and performance improvement in the medical records department of a hospital. International Journal of Productivity and Performance Management, 65(1), pp.98–125.
Brown, A., Eatock, J., Dixon, D., Meenan, B. J., & Anderson, J. (2008). Quality and continuous improvement in medical device manufacturing. The TQM Magazine, 20(6), 1754–2731. doi: 10.1108/17542730810909329
Burns, D. K., Jones, A. P., & Suhrcke, M. (2016). The relationship between international trade and non-nutritional health outcomes: A systematic review of quantitative studies. Social Science & Medicine, 152, 9–17
Carlborg, P., Kindström, D., & Kowalkowski, C. (2013). A Lean approach for service productivity improvements: Synergy or oxymoron? Managing Service Quality: An International Journal, 23(4), 291–304. doi:10.1108/MSQ-04-2013-0052
Castle, L., Franzblau-Isaac, E., & Paulsen, J. (2005). Using Six Sigma to reduce medication errors in a home-delivery pharmacy service. Journal on Quality and Patient Safety, 31(6), 319–324.
Covenant Health (2015). Medication safety: An overview. Retrieved from http://extcontent.covenanthealth.ca/Medication_Safety_An_Overview__2015_(MH)Version1_22apr15.et.pdf
Chan, A. L. F. (2004). Use of six sigma to improve pharmacist dispensing errors at outpatient clinic. American Journal of Medical Quality, 19(3), 128–131.
Ching, J. M., Long, C., Williams, B. L., & Blackmore, C. C. (2013). Using lean to improve medication administration safety: In search of the “perfect dose.” The Joint Commission Journal on Quality and Patient Safety, 39(5), 195–204. doi:10.1016/S1553-7250(13)39026-6
Christopher, W., Burkle, C., & Lanier, W. (2014). Medication errors : An overview for Clinicians. Mayo Clinic Proceedings, 89(8).
Chumchit, C., Amrumpai, Y., & Treesak, C. (2015). Recognition on Medication Safety and Look-alike / Sound-alike Medication Problems in Thai Public Hospitals. Silpakorn University Science and Technology Journal, 9(2), 40–51.
Crane, J., & Crane, F. G. (2006). Preventing medication errors in hospitals through a systems approach and technological innovation: a prescription for 2010. Hospital Topics, 84(4), 3–8. doi:10.3200/HTPS.84.4.3-8
Critchley, S. (2015). Improving medication administration safety in a community hospital setting using Lean methodology. Journal of Nursing Care Quality, 30(4), 345–351. doi:10.1097/NCQ.0000000000000112
Deblois, S., & Lepanto, L. (2016). Lean and Six Sigma in acute care: a systematic review of reviews. International Journal of Health Care Quality Assurance, 29(2), 192–208. doi:10.1108/09526860710819440
Denyer, D., & Tranfield, D. (2009). Producing a systematic review. In Buchanan D. & Bryman A. (Eds). The Sage handbook of organizational research methods (pp.671-689). Thousand Oaks, CA: Sage Publications.
Desai, D. A., Antony, J., & Patel, M. B. (2012). An assessment of the critical success factors for Six Sigma implementation in Indian industries. International Journal of Productivity and Performance Management, 61(4), 426-444. doi: 10.1108/17410401211212670
Esimai, G. (2005). Lean six sigma reduces medication errors. Quality Progress, (April), 51–57.
Fisher, M., Norris, D., Camac, K., & Hawkshaw, B. (2001). A comparison of medication errors between two storage sites. Contemporary Nurse, 11(1), 55–59. doi: 10.5172/conu.11.1.55
Gijo, E. V., & Antony, J. (2014). Reducing patient waiting time in outpatient department using Lean Six Sigma methodology. Quality and Reliability Engineering International, 30, 1481–1491. doi:10.1002/qre.1552
Gijo, E. V., Antony, J., Hernandez, J., & Scaria, J. (2013). Reducing patient waiting time in a pathology department using the Six Sigma methodology. Leadership in Health Services, 26(4), 1751–1879. doi:10.1108/LHS-02-2012-0004
Hintzen, B. L., Knoer, S. J., Van Dyke, C. J., & Milavitz, B. S. (2009). Effect of lean process improvement techniques on a university hospital inpatient pharmacy. American Journal of Health-System Pharmacy, 66, 2042–2047.
Hussain, A., Steward, L. M., Rivers, P. A., & Muchus, G. (2015). Managerial process improvement: a lean approach to eliminating medication delivery. International Journal of Health Care Quality Assurance, 28(1), 55–63.
Kunac, D. L., & Reith, D. M. (2005). Identification of priorities for medication safety in neonatal intensive care. Drug Safety, 28(3), 251–261.
Lago, P., Bizzarri, G., Scalzotto, F., Parpaiola, A., Amigoni, A., Putoto, G., & Perilongo, G.(2012). Use of FMEA analysis to reduce risk of errors in prescribing and administering
drugs in paediatric wards: a quality improvement report. BMJ Open, 2, 1–9. doi:10.1136/bmjopen-2012-001249
Laureani, A. & Antony, J. (2017a). Leadership and Lean Six Sigma : a systematic literature review. Total Qaulity Management & Business Excellence, 1-29. doi:10.1080/14783363.2017.1288565
Laureani, A. & Antony, J. (2017b). Leadership characteristics for Lean Six Sigma. Total Qaulity Management & Business Excellence, 1-29. doi:
10.1080/14783363.2015.1090291 Luton, A., Bondurant, P. G., Campbell, A., Conkin, C., Hernandez, J., & Hurst, N. (2015).
Got (the Right) milk? How a blended Quality Improvement approach catalyzed change. Advances in Neonatal Care, 15(5). doi: 10.1097/ANC.0000000000000228
Manville, G., Greatbanks, R., Krishnasamy, R., & Parker, D. W. (2012). Critical success factors for Lean Six Sigma programmes: a view from middle management. International Journal of Quality & Reliability Management, 29(1), 7–20. https://doi.org/http://dx.doi.org/10.1108/MRR-09-2015-0216
Mason, S. E., Nicolay, C. R., & Darzi, A. (2015). The use of Lean and Six Sigma methodologies in surgery: A systematic review. The Surgeon, 13(2), 91–100.
Materla, T., Cudney, E.A. & Antony J. (2017). The application of Kano model in the healthcare industry : a systematic literature review. Total Quality Management & Business Excellence. doi: 10.1080/14783363.2017.1328980
McNally, K. M., Page, M. A., & Sunderland, B. V. (1997). Failure-mode and effects analysis in improving a drug distribution system. American Journal of Health-System Pharmacy, 54, 171–177.
Moraros, J., Lemstra, M., & Nwankwo, C. (2016). Lean interventions in healthcare: Do they actually work? A systematic literature review. International Journal for Quality in Health Care, 28(2), 150–165. doi:10.1093/intqhc/mzv123
Najar, A. V., Ghane, H., Ebrahimipour, H., Nouri, G. A., & Dadpour, B. (2016). Identification of priorities for medication safety in the neonatal intensive care unit via failure mode and effect analysis. Iranian Journal of Neonatology, 7(2), 28–34.
Nayar, P., Ojha, D., Fetrick, A., & Nguyen, A. T. (2016). Applying lean six sigma to improve medication management . International Journal of Health Care Quality Assurance, 29(1), 16–23. doi: 10.1108/IJHCQA-02-2015-0020.
National Coordinating Council for Medication Error Reporting and Prevention. (2017), About Medication Errors. Retrieved from http://www.nccmerp.org/about-medication-errors
Nonthaleerak, P., & Hendry, L. (2008). study evidence Exploring the six sigma phenomenon using multiple case study evidence. International Journal of Operations & Production Managemen, 28(3), 279–303. https://doi.org/10.1108/01443570810856198
Ozawa, S., & Sripad, P. (2013). How do you measure trust in the health system? A systematic review of the literature. Social Science & Medicine, 91, 10–14.
Pamfilie, R., Petcu, A.J., & Draghici, M. (2012). The importance of leadership in driving a strategic Lean Six Sigma management. Procedia- Social and Behavioral Science, 58, 187-196
Pande, P. S., Neuman, R. P., & Cavanagh, R. R. (2000). The Six Sigma way: How GE, Motorola, and other top companies are honing their performance. New York: McGraw-Hill.
Pepper, M. P., & Spedding, T. A. (2010). The evolution of Lean Six Sigma. International Journal for Quality & Reliability Management, 27(2), 138–155. doi:10.1108/02656711011014276
Revere, L., & Black, K. (2003). Integrating Six Sigma with total quality management: a case example for measuring medication errors. Journal of Healthcare Management, 48(6),
377-391. Riehle, M. A., Bergeron, D., & Hyrkäs, K. (2008). Improving process while changing practice:
FMEA and medication administration. Nursing Management, 39(2), 28–33. Rodriguez-Gonzalez, C. G., Martin-Barbero, M. L., Herranz-Alonso, A., Durango-Limarquez,
M. I., Hernandez-Sampelayo, P., & Sanjurjo-Saez, M. (2015). Use of failure mode, effect and criticality analysis to improve safety in the medication administration process. Journal of Evaluation in Clinical Practice, 21, 549–559. doi:10.1111/jep.12314
Roy, V., Gupta, P., & Srivastava, S. (2005). Chapter - 14 Medication Errors : Causes & Prevention (pp. 60–64).
Runciman, W. B., Roughead, E. E., Semple, S. J., & Adams, R. J. (2003). Adverse drug events and medication errors in Australia. International Journal for Quality in Health Care, 15, 49–60.
Salmasi, S., Khan, T. M., Hong, Y. H., & Ming, L. C. (2015). Medication errors in the Southeast Asian countries : A systematic review. Plos One, 10(9), 1-19. doi: 10.1371/journal.pone.0136545
Sharma, S., & Chetiya, A. R. (2010). Six Sigma project selection: an analysis of responsible factors. International Journal of Lean Six Sigma, 1(4), 280–292. doi: 10.1108/20401461011096069
Sheridan-Leos, N., & Schulmeister, L. (2006). Failure Mode and Effect Analysis TM : Clinical Journal of Oncology Nursing, 10(3), 393–399.
Stefanacci, R. G., & Riddle, A. (2016). Preventing medication errors. Geriatric Nursing, 37(4), 307–310.
Teo, C. H., Ng, C. J., Booth, A., & White, A. (2016). Barriers and facilitators to health screening in men: A systematic review. Social Science and Medicine, 165, 168–176.
Torjesen, I. (2014), Medication errors cost the NHS up to £2.5bn a year. Retrieved from http://www.pharmaceutical-journal.com.sci-hub.cc/news-and-analysis/medication-errors-cost-the-nhs-up-to-25bn-a-year/20066893.article
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review*. British Journal of Management, 14, 207–222.
U.S. Food and Drug Administration. (2016).Medication errors reports. Retrieved from https://www.fda.gov/Drugs/DrugSafety/MedicationErrors/ucm080629.htm
Velez-Diaz-Pallares, M., Delgado-Silveira, E., Carretero-Accame, M. E., & Bermejo-Vicedo, T. (2013). Using healthcare failure mode and effect analysis to reduce medication errors in the process of drug prescription, validation and dispensing in hospitalised patients. BMJ Quality & Safety, 22, 42–52. doi: 10.1136/bmjqs-2012-000983
Velo, G. P., & Minuz, P. (2009). Medication errors: Prescribing faults and prescription errors. British Journal of Clinical Pharmacology, 67(6), 624–628. doi: 10.1111/j.1365-2125.2009.03425.x
Vest, J. R., & Gamm, L. D. (2009). A critical review of the research literature on Six Sigma, Lean and StuderGroup’s Hardwiring Excellence in the United States: the need to demonstrate and communicate the effectiveness of transformation strategies in healthcare. Implementation Science, 4(38), 1-9. doi: 10.1186/1748-5908-4-35
Walsh, K. ., Roblin, D. ., Weigart, S. ., Houlahan, K. ., Degar, B., Amy, B., … Mazor, K. . (2013). Medication Errors in the Home : A Multisite Study of Children With Cancer. Pediatrics, 131(5), 1406–1414.
Wang, F.& Chen, K. (2010). Applying Lean Six Sigma and TRIZ methodology in banking services, Total Quality Management & Business Excellence, 21(3), 301- 315. doi: 10.1080/14783360903553248
World Health Organization. (2016), Data and statistics. Retrieved from http://www.euro.who.int/en/health-topics/Health-systems/patient-safety/data-and-statistics.
Zavaleta-bustos, M., Castro-pastrana, L. I., Reyes-hernández, I., López-luna, M. A., & Bermúdez-camps, I. B. (2008). Prescription errors in a primary care university unit : urgency of pharmaceutical care in Mexico. Brazilian Journal of Pharmaceutical Sciences, 44(1), 115–125.