Evidence map›Paper›PMID 34462263›Full record

ArticleBMJ open quality2021

Reducing surgical cancellations: a successful application of Lean Six Sigma in healthcare.

Stijn Schretlen, Paulien Hoefsmit, Suzanne Kats, Geofridus van Merode, Jos Maessen, Reinier Zandbergen

Open access · goldAbstract read
In one paragraph

Article in BMJ open quality, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
5.6field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 26 citations in OpenAlex.

  1. Augmenting healthcare systems for pandemic preparedness: a Lean Six Sigma perspective.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2026
    Review
  2. Key Performance Indicators Applied in Medicine.International archives of otorhinolaryngology · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Reducing last-minute cancellations of elective urological surgery-effectiveness of specialist nurse preoperative assessment.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2023
    Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Stijn Schretlen *Integrated Health Solutions, Medtronic plc, Maastricht, Nederland, The Netherlands stijn.schretlen@mumc.nl.ORCID 0000-0001-9190-2269
Paulien Hoefsmit *Cardiothoracic Surgery, Amsterdam UMC Locatie AMC, Amsterdam, North Holland, The Netherlands.ORCID 0000-0003-4019-7197
Suzanne KatsHeart+Vascular Centre, Maastricht University Medical Centre+, Maastricht, Limburg, The Netherlands.
Geofridus van MerodeFaculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre+, Maastricht, Limburg, The Netherlands.ORCID 0000-0003-1918-3487
Jos MaessenHeart+Vascular Centre, Maastricht University Medical Centre+, Maastricht, Limburg, The Netherlands.
Reinier ZandbergenHeart+Vascular Centre, Maastricht University Medical Centre+, Maastricht, Limburg, The Netherlands.
Maastricht University Medical Centre · NLAmsterdam University Medical Centers · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe COVID-19 pandemic emphasises the need to use healthcare resources efficient and effective to guarantee access to high-quality healthcare in an affordable manner. Surgical cancellations have a negative impact on these. We used the Lean Six Sigma (LSS) methodology to reduce cardiac surgical cancellations in a University Medical Center in the Netherlands, where approximately 20% of cardiac surgeries were being cancelled.

methodA multifunctional project team used the data-driven LSS process improvement methodology and followed the 'DMAIC' improvement cycle (Define, Measure, Analyse, Improve, Control). Through all DMAIC phases, real-world data from the hospital information system supported the team during biweekly problem-solving sessions. This quality improvement study used an 'interrupted time series' study design. Data were collected between January 2014 and December 2016, covering 20 months prior and 16 months after implementation. Outcomes were number of last-minute coronary artery bypass graft cancellations, number of repeated diagnostics, referral to treatment time and patient satisfaction. Statistical process control charts visualised the change and impact over time. Students two-sample t-test was used to test statistical significance. A p<0.05 was considered as statistically significant.

resultsLast-minute cancellations were reduced by 50% (p=0.010), repeated preoperative diagnostics (X-ray) declined by 67% (p=0.021), referral to treatment time reduced by 35% (p=0.000) and patient Net Promoter Score increased by 14% (p=0.005).

conclusionThis study shows that LSS is an effective quality improvement approach to help healthcare organisations to deliver more safe, timely, effective, efficient, equitable and patient-centred care. Crucial success factors were the use of a structured data-driven problem-solving approach, focus on patient value and process flow, leadership support and engagement of involved healthcare professionals through the entire care pathway. Ongoing monitoring of key performance indicators is helpful in engaging the organisation to maintain continuous process improvement and sustaining long-term impact.

Indexed as

COVID-19Total Quality ManagementHumansPandemicsPatient SatisfactionSARS-CoV-2lean managementquality improvementroot cause analysissix sigmasurgery

Identifiers

PMID34462263
PMCPMC8407222
OpenAlexW3196837176

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.