Abstract

Purpose

Lean is a widely used quality improvement methodology initially developed and used in the automotive and manufacturing industries but recently expanded to the healthcare sector. This systematic literature review seeks to independently assess the effect of Lean or Lean interventions on worker and patient satisfaction, health and process outcomes, and financial costs.

Data sources

We conducted a systematic literature review of Medline, PubMed, Cochrane Library, CINAHL, Web of Science, ABI/Inform, ERIC, EMBASE and SCOPUS.

Study selection

Peer reviewed articles were included if they examined a Lean intervention and included quantitative data. Methodological quality was assessed using validated critical appraisal checklists. Publically available data collected by the Saskatchewan Health Quality Council and the Saskatchewan Union of Nurses were also analysed and reported separately.

Data extraction

Data on design, methods, interventions and key outcomes were extracted and collated.

Results of data synthesis

Our electronic search identified 22 articles that passed methodological quality review. Among the accepted studies, 4 were exclusively concerned with health outcomes, 3 included both health and process outcomes and 15 included process outcomes. Our study found that Lean interventions have: (i) no statistically significant association with patient satisfaction and health outcomes; (ii) a negative association with financial costs and worker satisfaction and (iii) potential, yet inconsistent, benefits on process outcomes like patient flow and safety.

Conclusion

While some may strongly believe that Lean interventions lead to quality improvements in healthcare, the evidence to date simply does not support this claim. More rigorous, higher quality and better conducted scientific research is required to definitively ascertain the impact and effectiveness of Lean in healthcare settings.

Introduction

Globally, healthcare systems are at a cross roads. Many political and healthcare leaders, and in fact the public itself is calling for, if not demanding, the redesign of healthcare delivery. The concern is fuelled by ever increasing costs and high expectations, while at the same time having surprisingly low rates of patient adherence to care and high rates of adverse events [1]. In response, many jurisdictions have attempted to introduce standardized protocols like Lean.

Lean is a widely used quality improvement methodology. Lean thinking was first developed in the automotive and manufacturing industries but it has recently expanded to the healthcare sector. Lean thinking begins with identifying and ‘removing waste’ in order to ‘add value’ to the customer or patient [2]. The Lean Enterprise Institute articulates five main principles of Lean: specify value from the standpoint of the customer, identify all the steps in the value stream and eliminate steps that do not create value, make the steps flow smoothly toward the customer, let customers pull value from the next upstream activity and begin the process again until a state of perfection is reached [3].

The introduction of these principles placed ‘customer value’ and ‘removing waste’ at the centre of Lean thinking. In this manner, the process is essentially driven by ‘what customers want’ and then organizational steps are taken to define which activities are considered to be ‘value-adding’ as opposed to ‘non-value adding’. ‘Value adding’ activities are encouraged because they directly contribute to creating a product or service a customer wants. On the other hand, ‘non-value adding’ activities are considered a waste and need to be removed or avoided [4].

To date, there have been a limited number of reviews of Lean or Lean interventions in healthcare. One of the reviews started with 207 articles under consideration. However, when the authors applied their inclusion criteria of only accepting papers that were published in peer review journals and studies that had quantifiable data available, it left them with merely 19 papers (9.2%) for critical appraisal [5].

Among the papers accepted, it was noted that the vast majority of studies had methodological limitations that undermined the validity of the results. These limitations included weak study designs, lack of statistical analysis, inappropriate statistical assumptions, inappropriate analysis, failure to rule out alternative hypotheses, no adjustment for confounding, selection bias and lack of control groups. The studies also did not review long-term organizational change, long-term impact or the independent effect of Lean while controlling for other organizational or staffing changes occurring at the same time [5]. Although this review was well-conducted, it was not a systematic literature review and it did not include a quality control checklist.

In North America, there are many examples of Lean healthcare interventions but the largest Lean transformation in the world was attempted in the province of Saskatchewan, Canada [6]. The Health Quality Council (HQC) of Saskatchewan concludes on its website that Lean increases patient safety by eliminating errors, increases patient satisfaction, reduces cost and improves patient health outcomes [7].

On the surface, Lean thinking seems to be an approach that generates positive results [8]. Yet, its application in healthcare has been controversial and its effectiveness questioned. As such, the purpose of this systematic literature review is to independently assess the effect of Lean thinking and Lean interventions on worker and patient satisfaction, health and process outcomes and financial costs.

Methods

We conducted an extensive systematic literature review on the following electronic databases: Medline, PubMed, Cochrane Library, CINAHL, Web of Science, ABI/Inform, ERIC, EMBASE and SCOPUS.

Searches were carried out using the following keywords: Lean Production System, Lean enterprise, Lean manufacturing, Virginia Mason Production System, Toyota Production System, Just in time production, Kaizen, HoshinKanri, Lean method, Lean thinking, Lean intervention, Lean healthcare, Lean principles, Lean process, Muda and Healthcare.

Peer-reviewed articles

Articles had to satisfy the following inclusion criteria to be considered: published in English, publicly available, peer reviewed, examined a Lean intervention and included quantitative data. These liberal criteria allowed the inclusion of a wide variety of relevant articles in our study. However, it also served as a means to exclude news reports, blog commentary, informational/promotional pieces and general ‘feel good’ success stories that lacked the necessary quantitative data to be able to critically judge the information presented.

The identification and approval of studies was carried out in three steps. First, the authors examined titles and abstracts to remove duplicates. Second, two of the authors (C.N. and M.L.) reviewed the full-text articles for relevance with regard to the field of healthcare and conformity to the inclusion criteria. Third, methodological quality was assessed by using validated critical appraisal checklists. The diffusion of innovations in health service checklists helped the authors assess the baseline comparability of the groups in each study, the research design, outcome measures and potential sources of bias. They were originally modelled after the Cochrane Effective Practice and Organization of Care Group for interventions in service delivery and organization [9]. Studies that scored >50% on the quality checklist were accepted (i.e. satisfied 6 or more out of 11 questions for before and after studies). Any disagreement between the two authors (C.N. and M.L.) was resolved by additional review and, if required, with a tie-breaking vote by the third author (J.M).

Grey literature

As mentioned, the largest Lean healthcare transformation in the world was attempted in the province of Saskatchewan, Canada [6]. The HQC has been surveying tens of thousands of patients over the years about their experiences in Saskatchewan hospitals. For the purposes of this systematic review, February 2012 was used as the cut-off point for the evaluation of pre- and post-Lean data as it coincided with the official date of the signed provincial contract with a Lean consultant firm [10]. A 26-month period was used to collect and analyse data on a monthly basis before Lean implementation (December 2009 to January 2012) and after Lean implementation (February 2012 to March 2014). This high quality data collected by certified Lean professionals have sample sizes ranging from 17 698 to 92 127 patients with a response rate of ∼51% and it is publicly available on a web site [11]. Additionally, the largest healthcare union or association in the province, the Saskatchewan Union of Nurses (SUN), contracted an external professional polling company to randomly survey 1500 nurses about their Lean experience in 2014 [12]. All 1500 nurses contacted, participated in the telephone survey.

Results

We identified a total of 1056 peer-reviewed articles of which 164 were removed as duplicates, 768 were removed due to lack of relevance to healthcare and 76 were removed because they did not meet the inclusion criteria. Among the 48 articles that were assessed for methodological quality, 22 articles passed [13–34] and 26 articles failed the checklist review [35–60] (Fig. 1 and Table 1). The original two reviewers (C.N. and M.L.) independently assessed and agreed on 43 studies with a tie breaking vote required by the third reviewer (J.M.) on five out of the 48 studies. Once finalized, the data from the included studies was pooled and summarized and confidence intervals for rate ratios were calculated with an established software application (SPSS 22.0).

Table 1

Detailed list of eligible peer review articles from the literature search

Articles that passed methodology review
 
First author's last name, year of publication, country where study was done Study design Number of participants Location of intervention (ex. Emergency department) Intervention Intervention goal Type of outcome Quality scores Outcome rate ratio and 95% CI 
Health outcome studies 
Jha, 2012, USA [13Retrospective cohort 6 000 000 Hospital Pay for performance Reduce 30 day mortality rate Health outcome 9/11 Pass 30 day mortality rate
0.08 (−0.30 to 0.46) 
McCulloch, 2010, UK [14Interrupted time series 2083 Emergency surgery ward PDCA Reduced risk of care related harm Health outcome 6/11 Pass Adverse events
0.91 (0.72–1.16) 
Muder, 2008, USA [15Pre-/post-test 215 ICU and a surgical unit Hand hygiene, contact precautions, active surveillance (TPS) Reduce incidence of MRSA Health outcome 7/11 Pass MRSA infections per 1000 patient days
2.47 (1.87–3.27) 
Ellingson, 2011, USA [16Pre-/post- test 109 Veteran affairs hospital surgical ward Systems and behaviour change to increase adherence to infection control precautions Reduce in MRSA incidence rates Health outcome 7/11 Pass MRSA incidence rate ratio
0.99 (0.98–1.01) 
Process outcome studies 
Murrell, 2011, USA [17Pre-/post-test 64 907 Emergency department Rapid triage and treatment ED length of stay and physician wait time Process outcome 7/11 Pass Unable to compute RR
Length of stay reduced from 4.2 (4.2–4.3) to 3.6 (3.6–3.7) hours
Physician start time reduced from 62.2 (61.5–63.0) to 41.9 (41.5–42.4) minutes 
Kelly, 2007, Australia [18Pre-/post-test 63 085 Emergency department Streaming of patients from triage, reallocation of medical and nursing staff (VSM) Reduce number of patients who leave without being seen Process outcome 8/11 Pass Left without being seen
0.99 (0.92–1.08) 
Naik, 2012, USA [19Pre-/post-test 22,527 Emergency department Identify and eliminate areas of waste Emergency wait time Process outcome 6/11 Pass Unable to compute RR
Wait time reduced from 4.6 (4.5–4.9) to 4.0 (3.7–4.1) hours 
Simons F, 2014, Netherlands [20Pre-/post-test 8,009 Operating room of University medical centre DMAIC using A3 intervention Door movements in the operating room Process outcome 6/11 Pass Unable to compute RR
Door movements reduced by 78% from an average of between 15 and 20 times per hour during surgery to 4 times per hour 
Burkitt, 2009, USA [21Retrospective pre-/post 2,550 Veteran affairs surgical center Staff training on hand hygiene, systematic culturing of all admissions, patient isolation Increase appropriateness of perioperative antibiotics and reduction in length of stay Process outcomes 7/11 Pass Length of stay
0.91 (0.76–1.08) 
Weaver, 2013, USA [22Pre-/post-test 2444 Mental health clinic Identify and eliminate areas of waste (TPS) Improving number who attend first appointment, reduce wait for appointment Process outcome 9/11 Pass Number who attended first appointment
1.0 (1.0–1.0)
Wait reduced from 11 days to 8 days 
LaGanga, 2011, USA [23Pre-/post-test 1726 Mental health center Remove over booking Increase capacity to admit new patients and reduce no-shows Process outcome 7/11 Pass No shows
1.13 (1.03–1.23) 
van Vliet, 2010, Netherlands [24Pre-/post-test 1207 Eye hospital Identify and eliminate areas of waste Reduce patient visits Process outcome 9/11 Pass Patient visits
1.84 (1.33–2.56) 
Martin, 2013, UK [25Pre-/post-test 500 Radiology department Value stream analysis (VSM) Reduce patient journey time Process outcome 6/11 Pass Unable to compute.
No pre and post raw data—only percentage changes were given 
White, 2014, Ireland [26Cross-sectional study 338 Hospital Implementation of productive ward program Improve work engagement Process outcome 7/11 Pass Overall work engagement score1.06 (0.96–1.18) 
Ulhassan, 2014, Sweden [27Pre-/post-test 263 Emergency department and two cardiology wards Identify and eliminate areas of waste (DMAIC) Improve teamwork Process outcome 8/11 Pass Overall inclusion
1.02 (0.74–1.42)
Overall trust
1.04 (0.79–1.38)
Overall productivity
1.0 (1.0–1.0) 
Collar, 2012, USA [28Pre-/post-test 234 Otolaryngology operating room Identify and eliminate areas of waste (DMAIC) Improve efficiency and workflow Process outcome 7/11 Pass Unable to compute due to data not being provided.
Turn-over time reduced from 38.4 min to 29 min 
Blackmore, 2013, USA [29Retrospective cohort 200 Breast clinic Identify and eliminate areas of waste Improve timeliness of diagnosis and reduce surgical consults Process outcome 6/11 Pass Reduced surgical consults
4.60 (1.82–11.62) 
Simons P, 2014, Netherlands [30Pre-/post-test 167 Radiotherapy department Implementation of a standard operating procedure Improve compliance to patient safety tasks Process outcome 8/11 Pass Overall compliance
0.96 (0.58–1.58) 
Mazzocato, 2012, Sweden [31Case study 156 Accident and Emergency department Identify and eliminate areas of waste, system restructuring Increase number of patients seen and discharged within four hours Process outcome 10/13 Pass Discharged within four hours
1.07 (0.92–1.26) 
Health and process outcome studies 
Vermeulen, 2014, Canada [32Pre-/post-test
Only study with control group 
6 845 185 Emergency department Training and system redesign Left without being seen, discharged within 48 h, readmitted within 72 h, died within 7 days of discharge Process and health outcome 8/11 Pass In comparison to control group:
Left without being seen
1.05 (0.77–1.43)
Discharged within 48 h
1.19 (0.72–1.98)
Readmitted within 72 h of discharge
1.0 (1.0–1.0)
Died within 7 days of discharge
1.03 (0.84–1.26) 
Yousri, 2011, UK [33Pre-/post-test 608 Hospital Identify and eliminate areas of waste Overall mortality, 30 day mortality, door to theatre time, admission to a trauma ward Health and process outcome 6/11 Pass 30 day mortality rate
1.71 (0.70–4.17)
Door to theatre time within 24 h
1.17 (0.86–1.60)
Admission to trauma bed
1.03 (0.90–1.20) 
Ford, 2012, USA [34Pre-/post-test 219 Emergency department Value stream analysis (VSM) Reduce time dependant stroke care and stroke mimic Process outcome and health outcome 7/11 Pass Percent of patients with DNT < 60 min
1.50 (1.21–1.86)
Stroke mimic
0.64 (0.26–1.58) 
Articles that failed methodology review 
First author's last name, year of publication, country where study was done Study design Number of participants Location of intervention (ex. Emergency department) Intervention Intervention goal Type of outcome Quality scores Major methodological drawbacks 
Health outcome studies 
Ulhassan, 2013, Sweden [35Pre-/post-test 4399 Cardiology department Changes to work structure and process Improve patient care Health outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Outcomes were not blinded

 
Wang, 2014, China [36Pre-/post-test 622 Nephrology department Training, treatment of high risk patients, specialized outpatient clinic Incidence of peritonitis Health outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Data did not cover most episodes of intervention at follow-up

 
Process outcome studies 
Wong, 2012, USA [37Pre-/post-test 234 616 Cytology laboratory New imaging system, workflow redesign Turnaround time, productivity and screening quality Process outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes measures were not blinded

 
Lodge, 2008, UK [38Post-test 9297 Division of diagnostics and clinical support Intranet based waiting list for radiology services Reduce radiology wait times Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • No formal statistical analysis was done

 
Willoughby, 2010, Canada [39Pre-/post-test 1728 Emergency department Visual reminders, standard process worksheets (PDCA) Improve wait times Process outcome 1/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Piggott, 2011, Canada [40Pre-/post-test 1666 Emergency department Identify and eliminate areas of waste (VSM) Time to ECG, time to see MD, time to aspirin administration Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Mazzocato, 2014, Sweden [41Pre-/post-test 1046 Emergency department Identify and eliminate areas of waste (VSM) To reduce time to see MD, to increase number of patients leaving within 4 h, reduce number present at 4pm shift Process outcome 5/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • No formal statistical analysis was done

 
Richardson, 2014, USA [42Pre-/post-test 565 Emergency department Educational training Decrease wasted nursing time Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Wojtys, 2009, USA [43Pre-/post-test 454 Sport medicine practice Identify and eliminate areas of waste (VSM) Improve patient scheduling Process outcome 1/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Niemeijer, 2012, Netherlands [44Pre-/post-test 445 Traumatology department Identify and eliminate areas of waste (DMAIC) Reduce length of stay and cost Process outcome 1/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • No formal statistical analysis was done

 
Hakim, 2014, USA [45Pre-/post-test 361 Medical and surgical units Identify and eliminate areas of waste (PDCA) Improve admission medication reconciliation Process outcome 3/11 Fail 
  • Insufficient follow-up time

  • Primary outcome measures not reliable

  • Primary outcome measure was not valid

 
van Lent, 2009, Netherlands [46Pre-/post-test 255 Chemotherapy day unit Identify and eliminate areas of waste (PDCA) Data efficiency, patient satisfaction and staff satisfaction Process outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Bhat, 2014, India [47Case study 224 Outpatient health information department Identify and eliminate areas of waste (DMAIC) Reduce registration time Process outcome 2/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Al-Araidah, 2010, Jordan [48Case study 217 Inpatient pharmacy Identify and eliminate areas of waste (DMAIC) Lead time reduction Process outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Hydes, 2012, UK [49Pre-/post-test 178 Hospital Value stream analysis (VSM) Improve efficiency and patient satisfaction Process outcome 2/11 Fail 
  • Insufficient data points for statistical analysis

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Smith, 2011, USA [50Pre-/post-test 171 Cystic fibrosis clinic Identify and eliminate areas of waste (DMAIC) Decrease non-value added time Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Kullar, 2010, UK [51Post-test 141 Cochlear implant unit Value stream analysis (VSM) Wait time for cochlear implantation Process outcome 1/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Siddique, 2012, UK [52Post-test 80 (or 129) General surgery department One stop cholecystectomy clinic Waiting list time, number of hospital visits and pre op admissions Process outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Lunardini, 2014, USA [53Case series 38 Operating room Value stream analysis (VSM) To optimize instrument utilization Process outcome 4/13 Fail 
  • Insufficient data points for statistical analysis, outcomes were not blinded, primary outcome measure was not reliable

 
Yeh, 2011, Taiwan [54Pre-/post-test 36 Private hospital Identify and eliminate areas of waste (DMAIC) Improve door to balloon time (AMI revascularization), length of stay Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Luther, 2014, UK [55Pre-/post-test 20 Medical admission unit ward Identify and eliminate areas of waste (PDCA) Improve patient handover Process outcome 3/11 Fail 
  • Insufficient data points for statistical analysis

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Shah, 2013, USA [56Pre-/post-test 17 Breast imaging centre Identify and eliminate areas of waste (VSM) Improve workflow Process outcome 2/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • Primary outcome measure was not reliable

 
Gijo, 2013, India [57Case study Not stated Pathology department Identify and eliminate areas of waste (DMAIC) Reduce wait time Process outcome 2/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Belter, 2012, USA [58Pre-/post-test Not stated Oncology outpatient Identify and eliminate areas of waste (DMAIC) Decrease patient wait times and improve communication Process outcome 2/11 Fail 
  • Insufficient data points for statistical analysis

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Snyder, 2009, USA [59Pre-/post-test Not stated Rural healthcare organization Training Decrease supply time, patient wait time, documentation in EMR within 30 minutes Process outcome 0/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • No formal statistical analysis done

 
Silva, 2012, USA [60Pre-/post-test Not stated Clinical engineering department Identify and eliminate areas of waste (DMAIC) Improve medical equipment inventory control Process outcome 0/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Articles that passed methodology review
 
First author's last name, year of publication, country where study was done Study design Number of participants Location of intervention (ex. Emergency department) Intervention Intervention goal Type of outcome Quality scores Outcome rate ratio and 95% CI 
Health outcome studies 
Jha, 2012, USA [13Retrospective cohort 6 000 000 Hospital Pay for performance Reduce 30 day mortality rate Health outcome 9/11 Pass 30 day mortality rate
0.08 (−0.30 to 0.46) 
McCulloch, 2010, UK [14Interrupted time series 2083 Emergency surgery ward PDCA Reduced risk of care related harm Health outcome 6/11 Pass Adverse events
0.91 (0.72–1.16) 
Muder, 2008, USA [15Pre-/post-test 215 ICU and a surgical unit Hand hygiene, contact precautions, active surveillance (TPS) Reduce incidence of MRSA Health outcome 7/11 Pass MRSA infections per 1000 patient days
2.47 (1.87–3.27) 
Ellingson, 2011, USA [16Pre-/post- test 109 Veteran affairs hospital surgical ward Systems and behaviour change to increase adherence to infection control precautions Reduce in MRSA incidence rates Health outcome 7/11 Pass MRSA incidence rate ratio
0.99 (0.98–1.01) 
Process outcome studies 
Murrell, 2011, USA [17Pre-/post-test 64 907 Emergency department Rapid triage and treatment ED length of stay and physician wait time Process outcome 7/11 Pass Unable to compute RR
Length of stay reduced from 4.2 (4.2–4.3) to 3.6 (3.6–3.7) hours
Physician start time reduced from 62.2 (61.5–63.0) to 41.9 (41.5–42.4) minutes 
Kelly, 2007, Australia [18Pre-/post-test 63 085 Emergency department Streaming of patients from triage, reallocation of medical and nursing staff (VSM) Reduce number of patients who leave without being seen Process outcome 8/11 Pass Left without being seen
0.99 (0.92–1.08) 
Naik, 2012, USA [19Pre-/post-test 22,527 Emergency department Identify and eliminate areas of waste Emergency wait time Process outcome 6/11 Pass Unable to compute RR
Wait time reduced from 4.6 (4.5–4.9) to 4.0 (3.7–4.1) hours 
Simons F, 2014, Netherlands [20Pre-/post-test 8,009 Operating room of University medical centre DMAIC using A3 intervention Door movements in the operating room Process outcome 6/11 Pass Unable to compute RR
Door movements reduced by 78% from an average of between 15 and 20 times per hour during surgery to 4 times per hour 
Burkitt, 2009, USA [21Retrospective pre-/post 2,550 Veteran affairs surgical center Staff training on hand hygiene, systematic culturing of all admissions, patient isolation Increase appropriateness of perioperative antibiotics and reduction in length of stay Process outcomes 7/11 Pass Length of stay
0.91 (0.76–1.08) 
Weaver, 2013, USA [22Pre-/post-test 2444 Mental health clinic Identify and eliminate areas of waste (TPS) Improving number who attend first appointment, reduce wait for appointment Process outcome 9/11 Pass Number who attended first appointment
1.0 (1.0–1.0)
Wait reduced from 11 days to 8 days 
LaGanga, 2011, USA [23Pre-/post-test 1726 Mental health center Remove over booking Increase capacity to admit new patients and reduce no-shows Process outcome 7/11 Pass No shows
1.13 (1.03–1.23) 
van Vliet, 2010, Netherlands [24Pre-/post-test 1207 Eye hospital Identify and eliminate areas of waste Reduce patient visits Process outcome 9/11 Pass Patient visits
1.84 (1.33–2.56) 
Martin, 2013, UK [25Pre-/post-test 500 Radiology department Value stream analysis (VSM) Reduce patient journey time Process outcome 6/11 Pass Unable to compute.
No pre and post raw data—only percentage changes were given 
White, 2014, Ireland [26Cross-sectional study 338 Hospital Implementation of productive ward program Improve work engagement Process outcome 7/11 Pass Overall work engagement score1.06 (0.96–1.18) 
Ulhassan, 2014, Sweden [27Pre-/post-test 263 Emergency department and two cardiology wards Identify and eliminate areas of waste (DMAIC) Improve teamwork Process outcome 8/11 Pass Overall inclusion
1.02 (0.74–1.42)
Overall trust
1.04 (0.79–1.38)
Overall productivity
1.0 (1.0–1.0) 
Collar, 2012, USA [28Pre-/post-test 234 Otolaryngology operating room Identify and eliminate areas of waste (DMAIC) Improve efficiency and workflow Process outcome 7/11 Pass Unable to compute due to data not being provided.
Turn-over time reduced from 38.4 min to 29 min 
Blackmore, 2013, USA [29Retrospective cohort 200 Breast clinic Identify and eliminate areas of waste Improve timeliness of diagnosis and reduce surgical consults Process outcome 6/11 Pass Reduced surgical consults
4.60 (1.82–11.62) 
Simons P, 2014, Netherlands [30Pre-/post-test 167 Radiotherapy department Implementation of a standard operating procedure Improve compliance to patient safety tasks Process outcome 8/11 Pass Overall compliance
0.96 (0.58–1.58) 
Mazzocato, 2012, Sweden [31Case study 156 Accident and Emergency department Identify and eliminate areas of waste, system restructuring Increase number of patients seen and discharged within four hours Process outcome 10/13 Pass Discharged within four hours
1.07 (0.92–1.26) 
Health and process outcome studies 
Vermeulen, 2014, Canada [32Pre-/post-test
Only study with control group 
6 845 185 Emergency department Training and system redesign Left without being seen, discharged within 48 h, readmitted within 72 h, died within 7 days of discharge Process and health outcome 8/11 Pass In comparison to control group:
Left without being seen
1.05 (0.77–1.43)
Discharged within 48 h
1.19 (0.72–1.98)
Readmitted within 72 h of discharge
1.0 (1.0–1.0)
Died within 7 days of discharge
1.03 (0.84–1.26) 
Yousri, 2011, UK [33Pre-/post-test 608 Hospital Identify and eliminate areas of waste Overall mortality, 30 day mortality, door to theatre time, admission to a trauma ward Health and process outcome 6/11 Pass 30 day mortality rate
1.71 (0.70–4.17)
Door to theatre time within 24 h
1.17 (0.86–1.60)
Admission to trauma bed
1.03 (0.90–1.20) 
Ford, 2012, USA [34Pre-/post-test 219 Emergency department Value stream analysis (VSM) Reduce time dependant stroke care and stroke mimic Process outcome and health outcome 7/11 Pass Percent of patients with DNT < 60 min
1.50 (1.21–1.86)
Stroke mimic
0.64 (0.26–1.58) 
Articles that failed methodology review 
First author's last name, year of publication, country where study was done Study design Number of participants Location of intervention (ex. Emergency department) Intervention Intervention goal Type of outcome Quality scores Major methodological drawbacks 
Health outcome studies 
Ulhassan, 2013, Sweden [35Pre-/post-test 4399 Cardiology department Changes to work structure and process Improve patient care Health outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Outcomes were not blinded

 
Wang, 2014, China [36Pre-/post-test 622 Nephrology department Training, treatment of high risk patients, specialized outpatient clinic Incidence of peritonitis Health outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Data did not cover most episodes of intervention at follow-up

 
Process outcome studies 
Wong, 2012, USA [37Pre-/post-test 234 616 Cytology laboratory New imaging system, workflow redesign Turnaround time, productivity and screening quality Process outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes measures were not blinded

 
Lodge, 2008, UK [38Post-test 9297 Division of diagnostics and clinical support Intranet based waiting list for radiology services Reduce radiology wait times Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • No formal statistical analysis was done

 
Willoughby, 2010, Canada [39Pre-/post-test 1728 Emergency department Visual reminders, standard process worksheets (PDCA) Improve wait times Process outcome 1/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Piggott, 2011, Canada [40Pre-/post-test 1666 Emergency department Identify and eliminate areas of waste (VSM) Time to ECG, time to see MD, time to aspirin administration Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Mazzocato, 2014, Sweden [41Pre-/post-test 1046 Emergency department Identify and eliminate areas of waste (VSM) To reduce time to see MD, to increase number of patients leaving within 4 h, reduce number present at 4pm shift Process outcome 5/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • No formal statistical analysis was done

 
Richardson, 2014, USA [42Pre-/post-test 565 Emergency department Educational training Decrease wasted nursing time Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Wojtys, 2009, USA [43Pre-/post-test 454 Sport medicine practice Identify and eliminate areas of waste (VSM) Improve patient scheduling Process outcome 1/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Niemeijer, 2012, Netherlands [44Pre-/post-test 445 Traumatology department Identify and eliminate areas of waste (DMAIC) Reduce length of stay and cost Process outcome 1/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • No formal statistical analysis was done

 
Hakim, 2014, USA [45Pre-/post-test 361 Medical and surgical units Identify and eliminate areas of waste (PDCA) Improve admission medication reconciliation Process outcome 3/11 Fail 
  • Insufficient follow-up time

  • Primary outcome measures not reliable

  • Primary outcome measure was not valid

 
van Lent, 2009, Netherlands [46Pre-/post-test 255 Chemotherapy day unit Identify and eliminate areas of waste (PDCA) Data efficiency, patient satisfaction and staff satisfaction Process outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Bhat, 2014, India [47Case study 224 Outpatient health information department Identify and eliminate areas of waste (DMAIC) Reduce registration time Process outcome 2/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Al-Araidah, 2010, Jordan [48Case study 217 Inpatient pharmacy Identify and eliminate areas of waste (DMAIC) Lead time reduction Process outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Hydes, 2012, UK [49Pre-/post-test 178 Hospital Value stream analysis (VSM) Improve efficiency and patient satisfaction Process outcome 2/11 Fail 
  • Insufficient data points for statistical analysis

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Smith, 2011, USA [50Pre-/post-test 171 Cystic fibrosis clinic Identify and eliminate areas of waste (DMAIC) Decrease non-value added time Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Kullar, 2010, UK [51Post-test 141 Cochlear implant unit Value stream analysis (VSM) Wait time for cochlear implantation Process outcome 1/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Siddique, 2012, UK [52Post-test 80 (or 129) General surgery department One stop cholecystectomy clinic Waiting list time, number of hospital visits and pre op admissions Process outcome 4/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 
Lunardini, 2014, USA [53Case series 38 Operating room Value stream analysis (VSM) To optimize instrument utilization Process outcome 4/13 Fail 
  • Insufficient data points for statistical analysis, outcomes were not blinded, primary outcome measure was not reliable

 
Yeh, 2011, Taiwan [54Pre-/post-test 36 Private hospital Identify and eliminate areas of waste (DMAIC) Improve door to balloon time (AMI revascularization), length of stay Process outcome 3/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Luther, 2014, UK [55Pre-/post-test 20 Medical admission unit ward Identify and eliminate areas of waste (PDCA) Improve patient handover Process outcome 3/11 Fail 
  • Insufficient data points for statistical analysis

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Shah, 2013, USA [56Pre-/post-test 17 Breast imaging centre Identify and eliminate areas of waste (VSM) Improve workflow Process outcome 2/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • Primary outcome measure was not reliable

 
Gijo, 2013, India [57Case study Not stated Pathology department Identify and eliminate areas of waste (DMAIC) Reduce wait time Process outcome 2/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Belter, 2012, USA [58Pre-/post-test Not stated Oncology outpatient Identify and eliminate areas of waste (DMAIC) Decrease patient wait times and improve communication Process outcome 2/11 Fail 
  • Insufficient data points for statistical analysis

  • No formal statistical test was used

  • Primary outcome measure was not reliable

 
Snyder, 2009, USA [59Pre-/post-test Not stated Rural healthcare organization Training Decrease supply time, patient wait time, documentation in EMR within 30 minutes Process outcome 0/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Insufficient data points for statistical analysis

  • No formal statistical analysis done

 
Silva, 2012, USA [60Pre-/post-test Not stated Clinical engineering department Identify and eliminate areas of waste (DMAIC) Improve medical equipment inventory control Process outcome 0/11 Fail 
  • Intervention could not be said to be independent of other changes over time

  • Primary outcome measure was not reliable

  • Outcomes were not blinded

 

DMAIC: define, measure, analyse, improve, control; PDCA: plan do check act; TPS: Toyota production system; VSM: value stream mapping; DNT: door to needle time.

Rate ratio <1 is intervention resulted in negative outcome; rate ratio >1 is intervention resulted in positive outcome.

Figure 1

Prisma flow diagram of the included studies.

Figure 1

Prisma flow diagram of the included studies.

Among the 22 studies accepted, none used high quality experimental study designs (i.e. randomized controlled trials) or even lesser quality quasi-experimental study designs (i.e. prospective longitudinal cohorts). All study designs were of relatively low quality with almost all using before and after study designs without control groups. In fact, only one accepted study had a control group [26]. Among accepted studies, 4 were exclusively concerned with health outcomes, 3 included both health and process outcomes and 15 included process outcomes only (Fig. 2).

Figure 2

Diagrammatic mapping of included studies to specific outcomes.

Figure 2

Diagrammatic mapping of included studies to specific outcomes.

Health outcomes

Among the four accepted studies with health outcomes, only one found a statistically significant impact of Lean. They found a reduced relative rate of MRSA infections (RR = 2.47, 95% CI 1.87–3.27), although absolute reductions were very small [15]. The largest study by far included six million patients. This study found no impact of Lean on 30-day mortality rate post-hospital discharge (RR = 0.08, 95% CI −0.30 to 0.46) [13]. The other two studies under this category found no statistically significant impact on adverse events (RR = 0.91, 95% CI 0.72–1.16) or on MRSA incidence (RR = 0.99, 95% CI 0.98–1.01) [14,16] (Table 1).

Process outcomes

Among the 15 accepted studies that examined a vast array of process outcomes (including wait times, patient flow and workplace engagement, inclusion and productivity), only 2 found a statistically significant positive effect of Lean. The benefits included reduced patient visits (RR = 1.84, 95% CI 1.33–2.56) and reduced surgical consults (RR = 4.60, 95% CI 1.82–11.62) [24,29]. In five studies, rate ratios and confidence intervals were not computed because the authors did not include raw data (only summary data). None of the accepted studies reviewed actual financial costs (Table 1).

Health and process outcomes

Of the three articles that evaluated both health and process outcomes, only one article reported a positive effect of Lean in that it improved time dependent stroke care (RR = 1.50, 95% CI 1.21–1.86) [34]. Conversely, in a large study of over 6.8 million patients, Lean had no statistically significant impact on patients leaving without being seen (RR = 1.05, 95% CI 0.77–1.43), patients discharged within 48 h of presentation (RR = 1.19, 95% CI 0.72–1.98) or number of patients readmitted to the hospital within 72-h of discharge (RR = 1.00, 95% CI 1.00–1.00) [32] (Table 1).

The largest Lean healthcare transformation in the world – results from Saskatchewan

The HQC of Saskatchewan surveyed tens of thousands of patients discharged from hospitals pre- and post-Lean [11]. In this systematic review, the most relevant 30 outcomes are reported under the umbrella of 5 broad groupings, which include: self-reported health, hospital experience, communication, respect and patient management. Among the 30 outcomes considered, Lean had no statistically significant impact in 27 of them (Table 2). For example, 30 574 patients were surveyed on self-reported health with no observed impact from Lean (RR = 1.00, 95% CI 0.98–1.04). When measuring direct outcomes for 90 000 patients on their experience with doctors (RR = 1.01, 95% CI 1.00–1.02) and nurses (RR = 1.00, 95% CI 0.99–1.01), no effect of Lean was observed. Only three outcomes showed statistically significant positive outcomes of Lean including: staff washing or disinfecting their hands (RR = 1.179 07, 95% CI 1.05–1.10), staff checking ID bands (RR = 1.08, 95% CI 1.06–1.10) and patients given safety brochures (RR = 1.56, 95% CI 1.49–1.63). The results are found in Table 2.

Table 2

Data collected by the Saskatchewan health quality council

Saskatchewan health quality council—pre- and post-Lean data
 
SHQC variables Pre-Lean (December 2009–January 2012)
 
Post-Lean (February 2012–March 2014)
 
Total sample size (nRate ratio 95% CI 
Sample size (N) LCL–UCL Sample size (nLCL–UCL 
Reported health 
 High self-reported health 16 637 34.52 26.78–37.96 13 937 34.75 26.16–38.58 30 574 1.00 0.98–1.04 
Hospital experience 
 Patient experience—quality of care transitions 42 435 31.48 28.45–35.43 36 000 32.80 28.09–35.78 78 435 1.02 1.00–1.03 
 Percentage of patients rating their hospital as 9 or 10/10 16 526 51.95 47.42–59.38 13 803 52.93 46.76–60.05 30 329 1.01 0.99–1.04 
 Percentage of patients reporting they would definitely recommend the hospital to family and friends 16 498 58.8 52.78–64.60 13 828 57.38 52.13–65.25 30 326 0.98 0.94–1.01 
Communication 
 Patient experience—quality of communication with nurses 50 162 68.30 64.26–70.71 41 965 69.31 63.91–71.07 92 127 1.01 1.00–1.02 
 Patient experience—Quality of communication with doctors 49 826 73.78 70.36–76.47 41 593 73.93 70.01–76.81 91 419 1.00 0.99–1.01 
 Percentage of patients reporting they always received good communication about medicines 18 852 50.19 43.55–54.78 16 504 49.94 43.08–55.26 35 356 0.99 0.97–1.02 
 Percentage of patients responding nurses always listened to them carefully 16 750 63.60 56.93–68.46 14 045 64.76 56.30–69.08 30 795 1.02 1.00–1.04 
 Percentage of patients responding nurses always explained things clearly 16 699 63.95 57.53–69.03 13 937 64.90 56.88–69.68 30 636 1.01 1.00–1.03 
 Percentage of patients responding doctors always explained things clearly 16 637 67.07 61.02–72.30 13 885 66.98 60.39–72.93 30 522 1.00 0.99–1.01 
 Percentage of patients responding doctors always listened to them carefully 16 562 70.92 65.07–75.99 13 830 71.52 64.46–76.61 30 392 1.00 0.99–1.02 
 Treatment plan explained clearly 15 753 77.79 73.25–83.37 13 201 78.58 72.69–83.93 28 954 1.01 1.00–1.01 
 Family encouraged to participate in care plan 13 955 80.60 75.47–85.78 11 809 81.31 74.92–86.33 25 764 1.00 0.99–1.02 
 Percentage of patients reporting staff took their preferences into account discussing health needs 12 886 24.88 19.16–30.93 10 980 26.28 18.56–31.52 23 866 1.05 1.00–1.10 
 Percentage of patients reporting staff always told them what their new medicine was for 9468 64.17 54.65–70.10 8292 63.29 54.00–70.67 17 760 0.99 0.97–1.01 
 Percentage of patients reporting staff always talked to them about medication side effects 9413 36.09 28.32–43.58 8245 36.54 27.67–44.22 17 658 1.01 0.97–1.05 
Respect 
 Percentage of patients responding nurses always treated them with courtesy and respect 16 800 77.28 71.41–81.50 14 056 78.26 70.85–81.87 30 856 1.00 0.99–1.01 
 Percentage of patients responding doctor always treated them with courtesy and respect 16 661 83.27 78.51–87.48 13 906 83.25 78.00–87.99 30 567 1.00 0.99–1.01 
 Staff respect culture, beliefs, values 15 753 92.23 89.18–95.68 13 221 92.43 88.83–96.03 28 974 1.00 0.99–1.01 
 Doctors treated patients as a partner in care 15 736 82.47 78.04–87.34 13 159 83.3 77.52–87.85 28 895 1.01 1.00–1.02 
 Staff treated patients as a partner in care 15 552 78.85 73.68–83.80 13 054 80.07 73.13–84.34 28 606 1.02 1.00–1.03 
 Doctors respect culture, beliefs, values 15 493 93.81 87.18–91.45 12 948 94.39 91.13–97.49 28 441 1.00 1.00–1.00 
Patient care management 
 Percentage of patients responding their pain was always well managed 22 183 63.90 57.35–67.38 19 174 61.55 56.90–67.82 41 357 0.96 0.95–0.98 
 Percentage of patients reporting they always received help they needed when they wanted it 17 599 60.50 53.98–65.39 15 737 59.12 53.57–65.60 33 336 0.98 0.96–1.01 
 Unnecessarily long wait time for room 16 607 79.45 74.62–84.29 13 889 79.18 74.08–84.83 30 496 1.00 0.99–1.02 
 Staff washed or disinfected their hands 16 529 43.49 36.41–48.27 13 839 46.71 35.76–48.91 30 368 1.07 1.05–1.10 
 Discharge organization 16 432 27.71 23.05–33.91 13 753 27.88 22.45–34.50 30 185 1.00 0.97–1.10 
 Suffered medical error 15 976 3.70 1.26–5.75 13 352 3.77 1.10–6.00 29 328 0.98 0.87–1.10 
 Staff checked ID band before care 14 085 60.52 50.31–63.18 12 224 65.42 49.73–63.76 26 309 1.08 1.06–1.10 
 Given patient safety brochure 10 854 30.64 18.58–41.42 8980 36.63 17.85–42.16 19 834 1.56 1.49–1.63 
Saskatchewan health quality council—pre- and post-Lean data
 
SHQC variables Pre-Lean (December 2009–January 2012)
 
Post-Lean (February 2012–March 2014)
 
Total sample size (nRate ratio 95% CI 
Sample size (N) LCL–UCL Sample size (nLCL–UCL 
Reported health 
 High self-reported health 16 637 34.52 26.78–37.96 13 937 34.75 26.16–38.58 30 574 1.00 0.98–1.04 
Hospital experience 
 Patient experience—quality of care transitions 42 435 31.48 28.45–35.43 36 000 32.80 28.09–35.78 78 435 1.02 1.00–1.03 
 Percentage of patients rating their hospital as 9 or 10/10 16 526 51.95 47.42–59.38 13 803 52.93 46.76–60.05 30 329 1.01 0.99–1.04 
 Percentage of patients reporting they would definitely recommend the hospital to family and friends 16 498 58.8 52.78–64.60 13 828 57.38 52.13–65.25 30 326 0.98 0.94–1.01 
Communication 
 Patient experience—quality of communication with nurses 50 162 68.30 64.26–70.71 41 965 69.31 63.91–71.07 92 127 1.01 1.00–1.02 
 Patient experience—Quality of communication with doctors 49 826 73.78 70.36–76.47 41 593 73.93 70.01–76.81 91 419 1.00 0.99–1.01 
 Percentage of patients reporting they always received good communication about medicines 18 852 50.19 43.55–54.78 16 504 49.94 43.08–55.26 35 356 0.99 0.97–1.02 
 Percentage of patients responding nurses always listened to them carefully 16 750 63.60 56.93–68.46 14 045 64.76 56.30–69.08 30 795 1.02 1.00–1.04 
 Percentage of patients responding nurses always explained things clearly 16 699 63.95 57.53–69.03 13 937 64.90 56.88–69.68 30 636 1.01 1.00–1.03 
 Percentage of patients responding doctors always explained things clearly 16 637 67.07 61.02–72.30 13 885 66.98 60.39–72.93 30 522 1.00 0.99–1.01 
 Percentage of patients responding doctors always listened to them carefully 16 562 70.92 65.07–75.99 13 830 71.52 64.46–76.61 30 392 1.00 0.99–1.02 
 Treatment plan explained clearly 15 753 77.79 73.25–83.37 13 201 78.58 72.69–83.93 28 954 1.01 1.00–1.01 
 Family encouraged to participate in care plan 13 955 80.60 75.47–85.78 11 809 81.31 74.92–86.33 25 764 1.00 0.99–1.02 
 Percentage of patients reporting staff took their preferences into account discussing health needs 12 886 24.88 19.16–30.93 10 980 26.28 18.56–31.52 23 866 1.05 1.00–1.10 
 Percentage of patients reporting staff always told them what their new medicine was for 9468 64.17 54.65–70.10 8292 63.29 54.00–70.67 17 760 0.99 0.97–1.01 
 Percentage of patients reporting staff always talked to them about medication side effects 9413 36.09 28.32–43.58 8245 36.54 27.67–44.22 17 658 1.01 0.97–1.05 
Respect 
 Percentage of patients responding nurses always treated them with courtesy and respect 16 800 77.28 71.41–81.50 14 056 78.26 70.85–81.87 30 856 1.00 0.99–1.01 
 Percentage of patients responding doctor always treated them with courtesy and respect 16 661 83.27 78.51–87.48 13 906 83.25 78.00–87.99 30 567 1.00 0.99–1.01 
 Staff respect culture, beliefs, values 15 753 92.23 89.18–95.68 13 221 92.43 88.83–96.03 28 974 1.00 0.99–1.01 
 Doctors treated patients as a partner in care 15 736 82.47 78.04–87.34 13 159 83.3 77.52–87.85 28 895 1.01 1.00–1.02 
 Staff treated patients as a partner in care 15 552 78.85 73.68–83.80 13 054 80.07 73.13–84.34 28 606 1.02 1.00–1.03 
 Doctors respect culture, beliefs, values 15 493 93.81 87.18–91.45 12 948 94.39 91.13–97.49 28 441 1.00 1.00–1.00 
Patient care management 
 Percentage of patients responding their pain was always well managed 22 183 63.90 57.35–67.38 19 174 61.55 56.90–67.82 41 357 0.96 0.95–0.98 
 Percentage of patients reporting they always received help they needed when they wanted it 17 599 60.50 53.98–65.39 15 737 59.12 53.57–65.60 33 336 0.98 0.96–1.01 
 Unnecessarily long wait time for room 16 607 79.45 74.62–84.29 13 889 79.18 74.08–84.83 30 496 1.00 0.99–1.02 
 Staff washed or disinfected their hands 16 529 43.49 36.41–48.27 13 839 46.71 35.76–48.91 30 368 1.07 1.05–1.10 
 Discharge organization 16 432 27.71 23.05–33.91 13 753 27.88 22.45–34.50 30 185 1.00 0.97–1.10 
 Suffered medical error 15 976 3.70 1.26–5.75 13 352 3.77 1.10–6.00 29 328 0.98 0.87–1.10 
 Staff checked ID band before care 14 085 60.52 50.31–63.18 12 224 65.42 49.73–63.76 26 309 1.08 1.06–1.10 
 Given patient safety brochure 10 854 30.64 18.58–41.42 8980 36.63 17.85–42.16 19 834 1.56 1.49–1.63 

Pre- and post-Lean periods were identical (26 months each).

In 2014, the SUN randomly surveyed 1500 nurses on their Lean experience [12]. Among nurses who had direct experience with Lean (729–173 nurses—depending on the variable), 15 outcomes were reviewed. All 15 outcomes reported a statistically significant negative effect of Lean on nurse engagement, usefulness, patient care, time for patient care, workplace issues, availability of supplies, workload, stress and patient safety (Table 3). For example, the following outcomes were reduced, nurse engagement (RR = 0.50, 95% CI 0.40–0.65), quality of patient care (RR = 0.23, 95% CI 0.17–0.31) and patient safety (RR = 0.44, 95% CI 0.37–0.53) while the nurses workload and stress levels increased (RR = 0.29, 95% CI 0.24–0.35) (Table 3).

Table 3

Data collected by the Saskatchewan Union of Nurses

Saskatchewan Union of Nurses (SUN)—Lean Healthcare 2014 Survey
 
 Strongly disagree (%) Strongly agree (%) n Rate ratio 95% CI 
Experience with Leana 
 Lean activities engage frontline registered nurses 23.00 10.00 729 0.50 0.40–0.65 
 Ideas put forward by registered nurses are taken seriously 30.50 6.10 729 0.27 0.20–0.37 
 Registered nurse input is meaningfully incorporated into the Lean process 35.70 6.00 729 0.25 0.18–0.33 
 Registered nurses feel safe and supported in voicing criticisms and concerns about Lean initiatives 41.00 5.60 729 0.21 0.16–0.30 
 Lean is a useful support for the nursing process 38.30 4.00 729 0.17 0.11–0.24 
 Lean leads to improvements in direct patient care 38.20 5.80 729 0.23 0.17–0.31 
 Lean has resulted in policies and procedures that improve the workplace 29.10 5.20 729 0.23 0.17–0.33 
 Declined
 
Improved
 
n
 
Rate ratio
 
95% CI
 
Did Lean decline, stay the same or improveb 
 The quality of supplies 42.20 9.90 1173 0.37 0.31–0.44 
 The availability of supplies 50.50 17.90 1173 0.58 0.52–0.66 
 The time available for direct patient care 41.40 10.40 1173 0.38 0.32–0.47 
 Workload and stress 49.50 7.90 1173 0.29 0.24–0.35 
 Patient safety 31.00 10.60 1173 0.44 0.37–0.53 
 The ability to meet professional standards in the nursing process 34.50 9.30 1173 0.37 0.31–0.45 
 Time and opportunity for clinical education and training 35.00 7.50 1173 0.33 0.27–0.41 
 Staff morale and engagement 58.20 7.80 1173 0.30 0.25–0.36 
Saskatchewan Union of Nurses (SUN)—Lean Healthcare 2014 Survey
 
 Strongly disagree (%) Strongly agree (%) n Rate ratio 95% CI 
Experience with Leana 
 Lean activities engage frontline registered nurses 23.00 10.00 729 0.50 0.40–0.65 
 Ideas put forward by registered nurses are taken seriously 30.50 6.10 729 0.27 0.20–0.37 
 Registered nurse input is meaningfully incorporated into the Lean process 35.70 6.00 729 0.25 0.18–0.33 
 Registered nurses feel safe and supported in voicing criticisms and concerns about Lean initiatives 41.00 5.60 729 0.21 0.16–0.30 
 Lean is a useful support for the nursing process 38.30 4.00 729 0.17 0.11–0.24 
 Lean leads to improvements in direct patient care 38.20 5.80 729 0.23 0.17–0.31 
 Lean has resulted in policies and procedures that improve the workplace 29.10 5.20 729 0.23 0.17–0.33 
 Declined
 
Improved
 
n
 
Rate ratio
 
95% CI
 
Did Lean decline, stay the same or improveb 
 The quality of supplies 42.20 9.90 1173 0.37 0.31–0.44 
 The availability of supplies 50.50 17.90 1173 0.58 0.52–0.66 
 The time available for direct patient care 41.40 10.40 1173 0.38 0.32–0.47 
 Workload and stress 49.50 7.90 1173 0.29 0.24–0.35 
 Patient safety 31.00 10.60 1173 0.44 0.37–0.53 
 The ability to meet professional standards in the nursing process 34.50 9.30 1173 0.37 0.31–0.45 
 Time and opportunity for clinical education and training 35.00 7.50 1173 0.33 0.27–0.41 
 Staff morale and engagement 58.20 7.80 1173 0.30 0.25–0.36 

Note: Rate ratio <1 = negative impact of intervention; rate ratio >1 = positive impact of intervention.

an, sample size—individuals who say they have been involved personally in a workplace Lean initiative. Likert scale was used (where 1 means ‘strongly disagree’ and 5 means ‘strongly agree’).

bn, sample size—individuals who say their workplace has gone through a Lean improvement process (denominator equals 1500).

Discussion

The purpose of this systematic literature review was to independently assess the effect of Lean thinking or Lean interventions on worker and patient satisfaction, health and process outcomes and financial costs.

For worker satisfaction, the largest study was carried out by the SUN. With every outcome reviewed, Lean had an overall negative effect on worker satisfaction [12]. Among other accepted studies from the electronic search of peer reviewed articles, Lean was shown to have no impact on workplace engagement, inclusion and productivity [26,27]. These outcomes are surprising in that worker engagement and input are essential for Lean principles to succeed [2].

For patient satisfaction, the largest dataset available has been collected by the Saskatchewan HQC [11]. When measuring direct outcomes for patient experience with doctors and nurses, no statistically significant positive or negative effect of Lean was observed. In the 22 studies accepted from the electronic search of peer reviewed articles, none directly evaluated patient satisfaction. That is also surprising because Lean reportedly begins with identifying and ‘removing waste’ in order to ‘add value’ to the customer or patient [2]. That said, it is unclear if other variables, like reduced number of medical consultations were used as proxy outcomes for patient satisfaction and what the patient's perception is (positive or negative) as a result of receiving less visits with their physician [24,29].

Among health outcomes like mortality, no study found a statistically significant impact of Lean. As mentioned previously, the largest study included six million patients and found no impact of Lean on 30-day mortality rate post-hospital discharge [13]. This is perhaps not surprising as Lean potentially only influences healthcare delivery. It obviously has no impact on complex health outcomes like patient adherence to care, let alone the behavioural or social determinants of health [1].

With regard to safety and errors, our systematic review shows that one study found no impact on adverse events while two studies had conflicting results on the impact of Lean on MRSA incidence [14–16]. The suggested impact of Lean on variables like adverse events is interesting because hospitals everywhere have successfully implemented various safety interventions that have proved effective but are not directly related with Lean. For example, the Agency for Healthcare Research and Quality estimates that 1.3 million fewer patients were harmed in American hospitals from 2010 to 2013. These outcomes were mostly due to common sense efforts to reduce surgical site infections, adverse drug events and other preventable incidents. As such, it is unclear what, if any, was the independent effect of Lean in comparison to a multitude of other diverse initiatives to promote safety and reduce errors in healthcare [61].

Although reduced financial cost is a reported benefit of Lean, it is worthy to note that we were unable to identify a single study that had actual quantifiable data to that effect. The province of Saskatchewan appears to be the only jurisdiction with actual financial cost information. External consultant fees were originally estimated to be $40.5 million but were reduced to $35 million when the Lean contract was terminated early [62]. Additionally, $17 million per year was required for internal kaizen promotion offices or $51 million total over the first 3 years. In return, official estimates of cost savings from the Saskatchewan health regions totalled $56934.26 [63]. If the numbers reported are accurate and true, it will mean that $1511 was spent on Lean for every one dollar saved by the province.

Strengths and limitations

The key strengths of our study are that it was a systematic review of Lean interventions in healthcare, it used a quality control checklist, and included a separate examination of both peer-reviewed articles and grey literature. There are also several limitations to our study. First, there are many and quite differing definitions of Lean in healthcare. This study did not attempt to strictly define what Lean is but rather relied on the definitions used by the authors of the articles included in our systematic review. Second, the outcomes were too diverse to permit a meta-analysis. Third, the study designs under review did not incorporate the use of control groups and therefore, it is unclear if the results are actually valid or what the results would be in comparison with a control group. Finally, the pre Lean HQC data for the province of Saskatchewan includes three small pilot projects in three health regions. However, month-to-month comparisons pre- and post-Lean found no statistically significant difference from the small pilot projects.

Comparison of findings

The results of our systematic review on Lean thinking and Lean interventions in healthcare provide additional insight and support the findings of other recent systematic reviews [5,64]. For example, Vest et al. [5] concluded that Lean interventions mainly focused on process outcomes in healthcare. Similarly, a Lean review completed by Mason et al. [64] found that the studies demonstrated improved process outcomes.

However, both Vest et al. [5] and Mason et al. [64] acknowledged that when critically examined, only a few articles met the inclusion criteria for their respective reviews. While Lean was found to be successful in some process outcomes, there were several and serious concerns with the reported study findings. Specifically, they noted that the articles reviewed were fraught with systematic bias, imprecision and serious methodological limitations, which undermined the validity of the results and made measuring and interpreting the true and independent effect of Lean on process and healthcare outcomes unclear and difficult.

Conclusion

The findings of our systematic review suggest that Lean interventions have: (i) no statistically significant association with patient satisfaction and health outcomes, (ii) a negative association with financial costs and worker satisfaction and (iii) potential yet inconsistent benefits on process outcomes like patient flow (reduced patient visits, reduced surgical consults, improved time dependent care) and safety (washing hands, staff checking ID bands and giving patients safety brochures).

More rigorous, higher quality and better conducted scientific research is required to definitively ascertain the impact and effectiveness of Lean in healthcare settings.

While some may strongly believe that Lean interventions lead to quality improvements in healthcare, the evidence to date simply does not support this claim. It is far more likely that Lean is but one of many strategies that might or might not have an impact on healthcare delivery.

The reality is that there are a multitude of internal and external variables that impact complex healthcare and process outcomes and that the independent effect of a specific intervention such as Lean is potentially minimal. For now, the question remains whether continuing to heavily invest in Lean is bringing us closer to or taking us further away from a much needed, viable, long-term solution to an increasingly problematic and unsustainable healthcare delivery system.

Authors’ contributions

J.M. and M.L. contributed to the original conception and design of the study. C.N. and M.L. were responsible for the acquisition of data. M.L. was in charge of the data analysis. J.M., M.L. and C.N. contributed to the interpretation of the data and the drafting of and critical revisions to the manuscript. All authors read and approved the final manuscript.

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Conflict of interest statement

None declared.

References

1
Lemstra
M
.
Saskatchewan Health
 .
Regina
:
Benchmark Publishing
,
2012
.
2
Institute for Healthcare Improvement
.
Going Lean in Healthcare. IHI Innovation Series White Paper
.
Cambridge
:
Institute for Healthcare Improvement
,
2005
.
www.IHI.org (26 January 2015, date last accessed)
.
3
Lean Enterprise Institute
.
Principles of Lean
 .
Lean Enterprise Institute
,
2015
.
www.lean.org (28 January 2015, date last accessed)
.
4
Joosten
T
Bongers
I
Janssen
R
.
Application of Lean thinking to health care: issues and observations
.
Int J Qual Health Care
 
2009
;
21
:
341
7
.
5
Vest
JR
Gamm
LD
.
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 Sci
 
2009
;
4
:
35
.
6
Saskatoon Star Phoenix
.
Lean Machine
.
Saskatoon
,
2014
.
www.thestarphoenix.com (26 January 2015, date last accessed)
.
7
Health Quality Council of Saskatchewan
.
Continuous Improvement: Lean
 .
Saskatoon
:
Health Quality Council
,
2015
.
www.hqc.sk.ca (26 January 2015, date last accessed)
.
8
Katz-Navon
T
Naveh
E
Stern
Z
.
The moderate success of quality of care improvement efforts: three observations on the situation
.
Int J Qual Health Care
 
2007
;
19
:
4
7
.
9
Greenhalgh
T
Robert
G
Bate
P
et al
Diffusion of Innovations in Health Service Organizations: A Systematic Literature Review
 .
Malden, MA
:
Blackwell Publishing Ltd
,
2005
.
10
Saskatchewan Ministry of Health
.
Contract Agreement: Province of Saskatchewan & John Black & Associates LLC
.
http://www.health.gov.sk.ca/lean-contract (16 February 2015, date last accessed)
.
11
Health Quality Council of Saskatchewan
.
Quality Insight: Measuring, Learning, Improving
 .
Saskatoon
:
Health Quality Council
,
2015
(accessed 26 January 2015)
. .
12
Saskatchewan Union of Nurses
.
Lean Healthcare 2014 Member Survey
 .
Regina
:
Praxis Analytics
,
2014
.
13
Jha
AK
Joynt
KE
Orav
EJ
et al
The Long-term effect of premier pay for performance on patient outcomes
.
New Engl J Med
 
2012
;
366
:
1606
15
.
14
McCulloch
P
Kreckler
S
New
S
et al
Effect of a ‘Lean’ intervention to improve safety processes and outcomes on a surgical emergency unit
.
BMJ (Online)
 
2010
;
341
:
1043
6
.
15
Muder
RR
Cunningham
C
McCray
E
et al
Implementation of an industrial systems-engineering approach to reduce the incidence of methicillin-resistant Staphylococcus aureus infection
.
Infect Control Hosp Epidemiol
 
2008
;
29
:
702
8
.
16
Ellingson
K
Muder
RR
Jain
R
et al
Sustained reduction in the clinical incidence of methicillin-resistant Staphylococcus aureus colonization or infection associated with a multifaceted infection control intervention
.
Infect Control Hosp Epidemiol
 
2011
;
32
:
1
8
.
17
Murrell
KL
Offerman
SR
Kauffman
MB
.
Applying Lean: implementation of a rapid triage and treatment system
.
West J Emerg Med
 
2011
;
12
:
184
91
.
18
Kelly
A
Bryant
M
Cox
L
et al
Improving emergency department efficiency by patient streaming to outcomes-based teams
.
Australian Health Rev
 
2007
;
31
:
16
21
.
19
Naik
T
Duroseau
Y
Zehtabchi
S
et al
A structured approach to transforming a large Public Hospital Emergency Department via Lean methodologies
.
J Healthcare Qual: Promoting Excellence Healthcare
 
2012
;
34
:
86
97
.
20
Simons
F
Aij
K
Widdershoven
G
et al
Patient safety in the operating theatre: how A3 thinking can help reduce door movement
.
Int J Qual Health Care.
 
2014
;
26
:
366
71
.
21
Burkitt
KH
Mor
MK
Jain
R
et al
Toyota production system quality improvement initiative improves perioperative antibiotic therapy
.
Am J Manag Care
 
2009
;
15
:
633
42
.
22
Weaver
A
Greeno
CG
Goughler
DH
et al
The impact of system level factors on treatment timeliness: utilizing the Toyota production system to implement direct intake scheduling in a semi-rural community mental health clinic
.
J Behav Health Serv Res
 
2013
;
40
:
294
305
.
23
LaGanga
LR
.
Lean service operations: reflections and new directions for capacity expansion in outpatient clinics
.
J Oper Manage
 
2011
;
29
:
422
33
.
24
van Vliet
EJ
Sermeus
W
van Gaalen
CM
et al
Efficacy and efficiency of a Lean cataract pathway: a comparative study
.
Qual Saf Health Care
 
2010
;
19
:
e13
.
25
Martin
AJ
Hogg
P
Mackay
S
.
A mixed model study evaluating Lean in the transformation of an Orthopaedic Radiology service
.
Radiography
 
2013
;
19
:
2
6
.
26
White
M
Wells
JS
Butterworth
T
.
The impact of a large-scale quality improvement programme on work engagement: Preliminary results from a national cross-sectional-survey of the ‘Productive Ward
’.
Int J Nurs Stud
 
2014
;
27
Ulhassan
WMP
Sandahl
CP
Westerlund
HP
et al
Antecedents and characteristics of Lean thinking implementation in a Swedish Hospital: a case study
.
Qual Manag Health Care
 
2013
;
22
:
48
61
.
28
Collar
RM
Shuman
AG
Feiner
S
et al
Lean management in academic surgery
.
J Am College Surgeons
 
2012
;
214
:
928
36
.
29
Blackmore
CC
Edwards
JW
Searles
C
et al
Nurse practitioner-staffed clinic at Virginia Mason improves care and lowers costs for women with benign breast conditions
.
Health Affairs
 
2013
;
32
:
20
6
.
30
Simons
PAM
Houben
R
Benders
J
et al
Does compliance to patient safety tasks improve and sustain when radiotherapy treatment processes are standardized?
Eur J Oncol Nurs
 
2014
;
18
:
459
65
.
31
Mazzocato
P
Holden
RJ
Brommels
M
et al
How does Lean work in emergency care? A case study of a Lean-inspired intervention at the Astrid Lindgren Children's hospital, Stockholm, Sweden
.
BMC Health Serv Res
 
2012
;
12
:
28
.
32
Vermeulen
MJ
Stukel
TA
Guttmann
A
et al
Evaluation of an Emergency Department Lean process improvement program to reduce length of stay
.
Ann Emerg Med
 
2014
;
64
:
427
38
.
33
Yousri
TA
Khan
Z
Chakrabarti
D
et al
Lean thinking: can it improve the outcome of fracture neck of femur patients in a district general hospital?
Injury
 
2011
;
42
:
1234
7
.
34
Ford
AL
Williams
JA
Spencer
M
et al
Reducing door-to-needle times using Toyota's Lean manufacturing principles and value stream analysis
.
Stroke
 
2012
;
43
:
3395
8
.
35
Ulhassan
WMP
Sandahl
CP
Westerlund
HP
et al
Antecedents and characteristics of Lean thinking implementation in a Swedish Hospital: a case study
.
Qual Manag Health Care
 
2013
;
22
:
48
61
.
36
Wang
J
Zhang
H
Liu
J
et al
Implementation of a continuous quality improvement program reduces the occurrence of peritonitis in PD
.
Renal Failure
 
2014
;
36
:
1029
32
.
37
Wong
R
Levi
AW
Harigopal
M
et al
The positive impact of simultaneous implementation of the BD focal point GS imaging system and Lean principles on the operation of gynecologic cytology
.
Arch Pathol Lab Med
 
2012
;
136
:
183
9
.
38
Lodge
A
Bamford
D
.
New development: using Lean techniques to reduce radiology waiting times
.
Public Money Manage
 
2008
;
28
:
49
52
.
39
Willoughby
KA
Chan
BTB
Strenger
M
.
Achieving wait time reduction in the emergency department
.
Leadersh Health Serv
 
2010
;
23
:
304
19
.
40
Piggott
Z
Weldon
E
Strome
T
et al
Application of Lean principles to improve early cardiac care in the emergency department
.
Can J Emerg Med
 
2011
;
13
:
325
32
.
41
Mazzocato
P
Thor
J
Bäckman
U
et al
Complexity complicates Lean: lessons from seven emergency services
.
J Health Organ Manag
 
2014
;
28
:
266
88
.
42
Richardson
D
Rupp
V
Long
K
et al
Using Lean methodology to decrease wasted RN time in seeking supplies in emergency departments
.
J Nurs Adm
 
2014
;
44
:
606
11
. .
43
Wojtys
EM
Schley
L
Overgaard
KA
et al
Applying Lean techniques to improve the patient scheduling process
.
J Healthcare Qual: Promoting Excellence Healthcare
 
2009
;
31
:
10
6
.
44
Niemeijer
GCPM
Trip
AP
de Jong
LJM
et al
Impact of 5 years of Lean six sigma in a University Medical Center
.
Qual Manag Health Care
 
2012
;
21
:
262
8
.
45
Hakim
H
.
Not just for cars: Lean methodology
.
Nurs Manag
 
2014
;
45
:
39
43
.
46
van Lent
WA
Goedbloed
N
van Harten
WH
.
Improving the efficiency of a chemotherapy day unit: applying a business approach to oncology
.
Eur J Cancer
 
2009
;
45
:
800
6
.
47
Bhat
S
Gijo
EV
Jnanesh
NA
.
Application of Lean Six Sigma methodology in the registration process of a hospital
.
Int J Product Perform Manag
 
2014
;
63
:
613
43
.
48
Al-Araidah
O
Momani
A
Khasawneh
M
et al
Lead-time reduction utilizing Lean tools applied to healthcare: the inpatient pharmacy at a local hospital
.
J Healthcare Qual: Promoting Excellence Healthcare
 
2010
;
32
:
59
66
.
49
Hydes
T
Hansi
N
Trebble
TM
.
Lean thinking transformation of the unsedated upper gastrointestinal endoscopy pathway improves efficiency and is associated with high levels of patient satisfaction
.
BMJ Qual Safety
 
2012
;
21
:
63
9
.
50
Smith
C
Wood
S
Beauvais
B
.
Thinking Lean: implementing DMAIC methods to improve efficiency within a cystic fibrosis clinic
.
J Healthcare Quality
 
2011
;
33
:
37
46
.
51
Kullar
P
Harris
F
Lloyd
SK
et al
The use of Lean Thinking techniques in implementing the Department of Health, UK, 18-week waiting time directive for cochlear implantation
.
Cochlear Implants Int: Interdisciplinary J
 
2010
;
11
:
133
45
.
52
Siddique
K
Elsayed
S
Cheema
R
et al
One-stop cholecystectomy clinic: an application of Lean thinking--can it improve the outcomes?
J Perioper Pract
 
2012
;
22
:
360
5
. .
53
Lunardini
D
Arington
R
Canacari
EG
et al
Lean principles to optimize instrument utilization for spine surgery in an academic medical center: an opportunity to standardize, cut costs, and build a culture of improvement
.
Spine
 
2014
;
39
:
1714
7
.
54
Yeh
HL
Lin
CS
Su
CT
et al
Applying Lean six sigma to improve healthcare: an empirical study
.
Afr J Bus Manag
 
2011
;
5
:
12356
70
.
55
Luther
V
Hammersley
D
Chekairi
A
.
Improving patient handover between teams using a business improvement model: PDSA cycle
.
Br J Hosp Med
 
2014
;
75
:
44
7
.
56
Shah
CJ
Sullivan
JR
Gonyo
MB
et al
Practice policy and quality initiatives: using Lean principles to improve screening mammography workflow
.
RadioGraphics
 
2013
;
33
:
1505
17
.
57
Gijo
EV
Antony
J
Hernandez
J
et al
Reducing patient waiting time in a pathology department using the Six Sigma methodology
.
Leadersh Health Serv
 
2013
;
26
:
253
67
.
58
Belter
D
Halsey
J
Severtson
H
et al
Evaluation of outpatient oncology services using Lean methodology
.
Oncol Nurs Forum
 
2012
;
39
:
136
40
.
59
Snyder
KD
McDermott
M
.
A rural hospital takes on Lean
.
J Healthcare Qual
 
2009
;
31
:
23
8
.
60
Silva
APS
Palermo
JM
Gibertoni
A
et al
Inventory quality control in clinical engineering: a Lean Six Sigma approach
.
2012 Pan American Health Care Exchanges, PAHCE 2012 - Conference, Workshops, and Exhibits Cooperation / Linkages: An Independent Forum for Patient Aare and Technology Support
;
2012
.
61
Agency for Healthcare Research and Quality
.
17% Percent Reduction in Hospital-Acquired Conditions
 .
Rockville, MD
:
Agency for Healthcare Research and Quality
,
2014
.
http://www.ahrq.gov/news/newsroom/speech/sp120114.html (4 February 2015, date last accessed)
.
62
Canadian Broadcast Corporation
.
Controversial Lean Company's Contract Ending Early
 .
Regina
:
Canadian Broadcast Corporation
,
2014
.
www.cbc.ca (4 February 2015, date last accessed)
.
63
Regina Leader Post
.
Mandryk: Wall must avoid another Lean mess
.
Regina
:
Regina. Leader Post
,
2015
.
www.leaderpost.com (4 February 2015, date last accessed)
.
64
Mason
SE
Nicolay
CR
Darzi
A
.
The use of Lean and Six Sigma methodologies in surgery: a systematic review
.
Surgeon
 
2014
;
13
:
1
10
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com