Article Text

Use of statistical process control in quality improvement projects in abdominal surgery: a PRISMA systematic review
  1. Yara Lima de Mendonca1,2,
  2. Rubiana Sarto3,
  3. Hannes Titeca1,
  4. Rob Bethune1,2,
  5. Andrew Salmon1
  1. 1University of Exeter, Exeter, UK
  2. 2Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
  3. 3Lewisham and Greenwich NHS Trust, London, UK
  1. Correspondence to Dr Yara Lima de Mendonca; yara.mendonca{at}


Background The use of quality improvement methodology has increased in recent years due to a perceived benefit in effectively reducing morbidity, mortality and length of stay. Statistical process control (SPC) is an important tool to evaluate these actions, but its use has been limited in abdominal surgery. Previous systematic reviews have examined the use of SPC in healthcare, but relatively few surgery-related articles were found at that time.

Objective To perform a systematic review (SR) to evaluate the application of SPC on abdominal surgery specialties between 2004 and 2019.

Methods An SR following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram was completed using Embase and Ovid Medline with terms related to abdominal surgery and SPC.

Results A total of 20 articles were selected after applying the exclusion criteria. Most of the articles came from North America, Europe and Australia, and half have been published in the last 5 years. The most common outcome studied was surgical complications. Urology, colorectal and paediatric surgery made up most of the articles. Articles show the application of SPC in various outcomes and the use of different types of graphs, demonstrating flexibility in using SPC. However, some studies did not use SPC in a robust way and these studies were of variable quality.

Conclusion This study shows that SPCs are being applied increasingly for most surgical specialties; however, it is still less used than in other fields, such as anaesthesia. We identified conceptual errors in several studies, such as issues with the design or incorrect data analysis. SPCs can be used to increase the quality of surgical care; the use should increase, but critically, the analysis needs to improve to prevent erroneous conclusions being drawn.

  • Continuous quality improvement
  • Quality improvement
  • Surgery
  • Length of Stay

Data availability statement

This study did not generate any new data.” to meet the University of Exeter’s recommendation:

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.


  • Quality improvement (QI) methodology is a valuable tool in helping develop safe and effective services for patients.

  • Statistical process control (SPC) is vital for QI as it is used to study variation and evaluate changes in the underlying process.

  • SPC can be applied to surgery to evaluate numerous outcomes including infections, postoperative complication rates and overall surgical performance.


  • This study extends previous findings from past systematic reviews from 2004 to 2020, focusing on surgical specialties.

  • Our results identified some important misapplications of SPC.


  • Developing new QI strategies for abdominal surgery could reduce patient complications and costs.

  • The use of SPC still needs to be developed and applied correctly to enhance the quality and effectiveness of the healthcare system.


The quality improvement (QI) approach is a useful way to help to increase safety and effective services for patients and healthcare teams during contact with healthcare services.1 For example, each year in the USA, 150 000 patients have surgical site infections (SSIs), and 44 000–98 000 deaths arise from medical errors.2 3 In the context of the National Health Service (NHS) in England, QI has been pursued through clinical governance, with financial and clinical quality at all levels.4 5 However, not all changes represent an improvement.6 To achieve these aims, changes based on statistical analysis of the data need to be robustly applied.7

Statistical process control (SPC) was developed in the 1920s for industrial improvement and is now also used in healthcare.6 8 SPC can be used in healthcare measuring variations and can control data and analysis over time.9–11 SPC charts allow data to be visualised to identify variations such as common or special causes and appropriate actions to be taken.12 13 The Shewhart chart is used to assign variation as common or special cause by plotting the data (in the form of a mean or median rate) along with control limits, typically up to 3 SDs above and below the mean.14 Cumulative summation (CUSUM) charts are used for variation when the subgroup is one, but are harder to construct than SPCs and less intuitive: data are gathered at the level of single patients, such as used for review outcomes for rare diseases.15 16

The main objective of SPC charts is to identify special cause variations which demonstrates a change in outcome including: infections, postoperative complication rates and overall surgical performance.1 10 14 17 Changes in healthcare processes need to be evaluated to measure patient benefits and avoid errors or undesirable consequences. For example, in Bristol, where 35 infants died after cardiac surgery between 1991 and 1995, an evaluation of the process after the first deaths (and the high mortality rate) may well have prevented subsequent deaths. This case, known as ‘Bristol Children’s Hosptial Scandal’, is one of the landmarks for the importance of the correct implementation of Plan–Do–Study–Act (PDSA) cycle and analysis of change in data.18

A systematic review (SR) by Thor et al6 looked at the application of SPC in healthcare between 1966 and June 2004 and found publications from 20 fields of healthcare. Although colorectal surgery has high rates of SSI and anastomotic leak, and urology has procedures that can cause significant sequelae, none of these publications looked at abdominal surgery.2 19 The aim of this study is to conduct an SR of SPC applied to abdominal surgery specialties, starting in 2004 when the time period of the SR from Thor et al ended.6 Suggestions for future improvements was also developed.


An electronic systematic search of Embase and Ovid Medline using the subheadings related to surgical specialties “gynecology surgery”, “gynaecology surgery”, “general surgery”, “colorectal surgery”, “intestine surgery”, “urology”, “abdominal surgery”, “surgery”, “vascular”, “operating theatre”, “operating room” and terms for quality improvement “statistical process”, “run chart”, “Shewhart”, “cumulative summation” were combined. These terms were derived from the major abdominal surgery areas and synonyms were taken into account using the Thesaurus tool (online supplemental appendix 1). Articles published between 1 January 2004 and 31 December 2019 were included. Other articles from additional sources (such as using references from chosen articles) that fitted our inclusion criteria were also included. The review strategy was running the search by two independent authors (YLdM and AS); the second independent author had performed many SRs.

Supplemental material

The inclusion criteria were (1) English language, (2) full-text articles and (3) articles about surgical procedures; and exclusion criteria were (1) other types of publication (eg, opinion, editorial, poster), (2) articles about medical education (since it is not entirely a clinical outcome) (3) articles from other surgery-related areas (eg, anaesthesia), and (4) articles using other methodologies than SPC, such as funnel plots.20

The final search was conducted in June 2020. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. 21 A flow chart of our literature review following PRISMA guidelines is shown in figure 1.

Figure 1

Preferred Reporting Items for Systematic Reviews and Meta-Analyses diagram (adapted from Moher et al48).


Our initial search returned 489 papers, 470 after deduplication. A total of 452 papers were excluded after applying all exclusion criteria. Two other articles22 23 were included after a review of the articles’ references. The exclusions were publications other than articles (239), articles related to areas other than abdominal surgery (169), focusing on medical education (38), languages other than English (4) and using different analysis to process charts (2). The total number of articles which match the criteria was 20 (table 1).

Table 1

Articles from systematic review

Articles came from different fields of surgery, predominately urology, colorectal surgery and paediatric surgery (figure 2).

Figure 2

Percentage of articles coming from different surgical specialties.

The articles collect data from North America, Europe and Australia (table 2). Half of articles were published in the last 5 years of the search period (figure 3). Most articles deal with data from a single institution (90%).

Table 2

Countries of data collection

As shown in figure 4, most studies were of retrospective cohort design, analysing results of the implementation after it happens. Two articles used the retrospective cohort design to create a control group and prospective cohort to evaluate changing results. The choice of charts is essential to allow for appropriate analysis. The preference was slightly for the Shewhart chart and its variations (55%), followed by CUSUM charts (45%).

Figure 4

Percentage of articles with each study design.

Different studies consider different outcomes, demonstrating the versatility of SPC. However, most consider morbidity, mortality and surgical complications as their primary outcomes, which allow a comprehensive evaluation of surgical procedure and postoperative care (figure 5).

Figure 5

Percentage of primary outcomes.

Colorectal surgery

Bowles and Watters22 developed a retrospective study of postoperative complications and mortality to analyse surgeons’ performance. They presented CUSUM charts to surgeons to provide individualised feedback. These charts can provide immediate and visually appealing feedback. This type of analysis appears feasible, and it is essential to create a study with risk adjustment. Not risk adjusting can bring inaccuracies for evaluation which can compromise the quality of the results and consequently, the generalisability of the data.

Lawson et al24 chose to analyse the hospitals’ performance using statistical control charts with risk stratification, developing outcome measures of morbidity and mortality, using a retrospective study design. They found that control charts failed to identify 38.5% of hospitals with worsening performance. This shows that SPC is not a perfect method and is complementary to other methods. They noted that their results from a tertiary centre are not comparable with community hospitals.

Keller et al10 found that unforeseen increases in length of stay (LOS) can impact patient outcomes. Their objective was to use SPC to identify process outliers to reduce LOS. They made a retrospective study to evaluate the results of a single surgeon. They found that outliers were patients with more comorbidities and longer operation times, and there were higher complication rates in elective open surgery (57.1%) and elective laparoscopic surgery (77.6%). They concluded that SPC could rapidly identify outliers, improve patient results and save resources.

Keller et al25 evaluated retrospectively the impact of anaesthetic block with intravenous acetaminophen on LOS and postoperative complications. They used a control chart to evaluate LOS, which was reduced from 3.7 to 2.6 days on average. Conclusion was that SPC could be used to reduce LOS.

Paediatric surgery

Sibanda et al16 conducted a retrospective study supporting the use of CUSUM for monitoring paediatric surgical outcomes such as the treatment of jaundice in relation to biliary atresia, a rare disease that can require early liver transplantation. This showed a failure rate of 29.8% which is less than the England and Wales average (43%). They concluded that CUSUM charts are adequate to routinely monitor paediatric surgical results.

Slusher et al26 suggest that reducing the variability of treatments tends to improve results. They analysed the implementation of new guidelines for appendicectomy. They analysed the difference between immediate versus interval appendectomy and duration of antibiotics using Shewhart charts showing adherence, complications and readmission. Their results suggested more efficient patient care and reduced antibiotics post-discharge (25% to 4%) in the interval appendicectomy group. However, no change in LOS was shown. They concluded that the reduction of variability could be key for future improvements.

In contrast, Mansfield et al27 evaluated a standardised care protocol to reduce LOS of patients with gastroschisis. They used Shewhart charts as part of their analysis and found that the LOS reduced from 34 days to 29 days, concluding that this QI methodology can help to reduce LOS. The incidence of gastroschisis in 2004 was 4.4 in 10 000 in the UK.28 This is an infrequent event and is better analysed with CUSUM charts instead of SPC as this method considers patients as individual units and can detect small changes.14 29

Nordin et al30 evaluated results from a prevention bundle to reduce SSI after gastrointestinal surgeries, which can cause substantial morbidity. Prevention bundles are evidence-based interventions placed together to improve patients’ results, but they are not as common for paediatric patients.31 They used SPC to analyse SSI rates and LOS for procedures including stoma closure. They used a retrospective cohort to create control limits and then prospectively analysed the data after the implementation of change. They demonstrated a reduction of SSI decreasing from 11.3% to 8.0%, cost reduction but no change in LOS.


Chalasani et al19 looked at results of radical cystectomy, which has a 25% complication rate. They created CUSUM charts to analyse morbidity and mortality with the acceptable rates being determined by a literature review. They indicated that CUSUM could provide visual indicators of when unexpected results are getting closer to benchmark limits.

Williams et al32 studied robot-assisted radical prostatectomy, which is gaining preference for prostate cancer treatment, despite the additional costs and training. They used CUSUM to analyse retrospective patient outcomes during this changeover period, evaluating positive surgical margin rates (PSMRs) using robot-assisted technique compared with open surgery. They found that PSMR exceeded the unacceptable limits within the first 50 patients, but subsequently lowered into the acceptable range.

Siddiqui and Izawa33 had a different approach studying radical cystectomy. They found that systematic methods are more capable of evaluating earlier changes than other methods. They use the work of Chalasani et al19 to demonstrate how CUSUM charts are an adequate method to analyse surgical outcomes.

Chan and Pautler34 related the increasing importance of evidence-based practice associated with quality measures. They analysed results of patients undergoing robot-assisted radical prostatectomy and used CUSUM to analyse surgical complications. They demonstrated that the process stayed out of control for all parameters during the beginning of the analysis and then returned to acceptable rates. They concluded that CUSUM is effective for quality assurance.

Bariatric surgery

Mueller et al35 evaluated retrospectively a change of technique to Roux-en-Y gastric bypass to reduce gastrojejunostomy stricture. They changed from longitudinal to transverse enterotomy closure after 97 patients and chose CUSUM analysis to compare rates of stricture between these two techniques. They demonstrated the superiority of the new technique with few complications (16% to 0%) and readmissions (15.5% to 6.0%).

Nossaman et al36 use an SPC to measure the adherence to guidelines regarding nil by mouth (NBM) status preoperatively. Patients being NBM for longer periods were associated with higher incidence complications and longer LOS. They used an SPC to demonstrate a statistical improvement; however, their chart did not include control limits which are essential for appropriate interpretation.

Lee et al37 evaluated retrospectively the identification of hypoglycaemia after post-gastric bypass using an algorithm. They used control charts to analyse the correlations between the outliers identified and those identified by the algorithm. They found high agreement between the charts and the algorithm, with a sensitivity of 89% and specificity of 86%.


O’Brien and Pillai17 reviewed rates of uterine perforation after the insertion of intrauterine devices. They calculated the annual perforation rate and used an SPC to evaluate if these rates were expected. They found an annual rate of perforation of 1.3 per 1000 insertions, which remained within limits and a peak of perforation was found at 3 months post partum. They used their single-centre data to create upper and lower limits, creating specific control limits for the centre.

Dyrkorn et al23 evaluated retrospectively the success of a single institution QI project with a bundle to reduce the rate of SSI in caesarean section. Pre-intervention, the institution had a caesarean SSI rate of 17.4%, while the national caesarean SSI rate was 8%. The SPC used to evaluate the QI project demonstrated a reduction of 3.1% after the introduction of the bundle.

General surgery

Berrisford et al38 aimed to reduce postoperative complications for patients with early squamous oesophagus cancer by ligating the left gastric artery prior to oesophagectomy. They used prospective CUSUM analysis between 55 control group patients (no ligature) and 22 intervention group patients (ligature). The morbidity of the control group was 20% and 10% in the intervention group.


Schrem et al39 used CUSUM charts to retrospectively analyse liver transplant mortality results after a perceived increase.40 They aimed to identify outliers and specific causes and effects for these results from a single centre. They divided 30 years of transplantation into three different time contexts (eras). During the third era, mortality had risen to 15.4%, possibly associated with the introduction of the Model for End-Stage Liver Disease criteria. After an adaptation to the new allocation system, the mortality dropped again to 8.9%. They concluded that other centres should use SPC charts to monitor their own units mortality.


This systematic review look at the use of SPC within abdominal surgical specialties. The increased use of QI methodology comes from the rising cost of treatments and technologies, a concern in countries such as the UK which have a publicly funded system.

Our initial search had 470 hits and after exclusions, we found 20 articles relating to SPC in abdominal surgical specialties published between 2004 and 2019. This lack of work for general surgery does not reflect the NHS reality because general surgery performed 1.3 million procedures in 2013/2014.41 Abdominal surgery has a considerable risk of complications and SPCs should be used to analyse local data to detect any change in performance, particularly in relation to change in surgical practice.6 25 42

Different data require different types of analysis to display data that can be easily understood. Vogel et al43 found that morbidity and mortality meetings, when associated with PDSA cycles, can improve quality for colorectal surgery.44

Overall, the Shewhart chart is the most common chart used, but in studies that look at changes in surgical techniques, CUSUM was used instead for their evaluation.35 39 CUSUM chart is useful when considering data from small modifications during the process, data are infrequent or difficult to obtain but with important clinical outcomes.12 45 It is important to highlight that CUSUM charts use well-defined calculations to generate upper limits to identify a process without control.14 However, most articles did not show this calculation (we cannot be completely sure that they used the normal/correct calculations) or used other data such as national average failure data or literature review to set their limits. None of the studies discussed this as a potential limitation.

Another point of comparison is the variation in control limits used in articles with Shewhart graphs. Control limits evaluate if the variation is from common causes (expected) or special causes (unexpected), based on SD or sigma (‘σ’).12 46 The convention for control charts is to use ±3 SD, but Ilieş et al2 concluded that tighter control limits (±1 SD) could result in more accurate charts which are more likely to identify more positives (true or false) for additional investigation. However, some articles lack an explanation of what control limits were set which could lead to misinterpretation.

Our study has several strengths, such as using a previous systematic review as a basis and using the PRISMA process. We identified the lack of studies using SPC for abdominal surgery compared with other fields. SPCs should be used more frequently to evaluate QI projects and drive better patient care.2 47 Several articles had conceptual problems, demonstrating that SPC use still needs to be developed and applied correctly to each reality. One weakness of this work is the fact that we did not follow all the databases used in the article from Thor et al6 which could result in the non-detection of publication bias. The English language inclusion criteria could have resulted in relevant articles being excluded; however, English is the most prevalent language used for scientific writing. Another drawback is the lack of discussion about the different types of Shewhart charts, but it was not our major objective. Despite these weaknesses, our results are essential for future actions and demonstrated the need for appropriate use of SPCs.


This study research shows that SPCs are being applied increasingly for most surgical specialties; however, they are still less used than in other fields, such as anaesthesia. We identified conceptual errors in several studies, such as issues with the design or incorrect data analysis. These can mislead results and raise concerns around the correct application of the method more widely. SPCs can be used to increase the quality of surgical care; the use should increase, but critically, the analysis needs to improve to prevent erroneous conclusions being drawn.

Data availability statement

This study did not generate any new data.” to meet the University of Exeter’s recommendation:

Ethics statements

Patient consent for publication

Ethics approval

Ethical approval was considered unnecessary in this systematic review.


Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.


  • Deceased 2021

  • Contributors YLdM—initial research during master's degree at University of Exeter; study design, application of methodology and analysis of results. RS—review of data and peer review. HT—statistical review and peer review. RB—study design and results/analysis review. AS—study design, article second author, review of the articles/results/analysis review.

  • Funding The authors did not received any specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.