Control Charts in Healthcare Quality ImprovementA Systematic Review on Adherence to Methodological Criteria
received:06 June 2011
accepted:05 March 2012
20 January 2018 (online)
Objectives: Use of Shewhart control charts in quality improvement (QI) initiatives is increasing. These charts are typically used in one or more phases of the Plan Do Study Act (PDSA) cycle to monitor summaries of process and outcome data, abstracted from clinical information systems, over time. We summarize methodological criteria of Shewhart control charts and investigate adherence of published QI studies to these criteria.
Methods: We searched Medline, Embase and CINAHL for studies using Shewhart control charts in QI processes in direct patient care. We extracted methodological criteria for Shewhart control charts, and for the use of these charts in PDSA cycles, from textbooks and methodological literature.
Results: We included 34 studies, presenting 64 control charts of which 40 control charts plotted two phases of the PDSA cycle. The criterion to use 10–35 data points in a control chart was least adhered to (48.4% non-adherence). Other criteria were: transformation of the data in case of a skewed distribution (43.7% non adherence), when comparing data from two phases of the PDSA cycle the Plan phase (the first phase) needs to be stable (40.0% non-adherence), using a maximum of four different rules to detect special cause variation (14.1% non-adherence), and setting control limits at three standard deviations from the mean (all control charts adhered).
Conclusion: There is room for improvement with regard to the methodological construction of Shewhart control charts used in QI processes. Higher adherence to all methodological criteria will decrease the risk of incorrect conclusions about the process being monitored.
- 1 Committee on Quality of Health Care in America Crossing the Quality Chasm: A New Health System for the 21st Century - Improving the 21st-century Health Care System. Washington D.C.: National Academy Press; 2009: 39-60.
- 2 Holzer K, Gall W. Utilizing IHE-based Electronic Health Record systems for secondary use. Methods Inf Med 2011; 50 (04) 319-325.
- 3 Varkey PF, Reller MK FAU, Resar R, Resar RK. Basics of quality improvement in health care. Mayo Clin Proc 2007; 82 (06) 735-739.
- 4 Nembhard I, Alexander J, Hoff T, Ramanujam R. Why Does the Quality of Health Care Continue to Lag? Insights from Management Research. The Academy of Management Perspectives ARCHIVE 2009; 23 (01) 24-42.
- 5 Speroff T, O’Connor GT. Study designs for PDSA quality improvement research. Qual Manag Health Care 2004; 13 (01) 17-32.
- 6 Langley GJ, Moen RD. Using the Model for Improvement. The improvement guide. San Francisco: A Wiley Imprint; 2009: 89-108.
- 7 Thor J, Lundberg J, Ask J, Olsson J, Carli C, Harenstam KP. et al. Application of statistical process control in healthcare improvement: systematic review. Qual Saf Health Care 2007; 16 (05) 387-399.
- 8 Eslami S, Abu-Hanna A, de Keizer NF, Bosman RJ, Spronk PE, de JE. et al. Implementing glucose control in intensive care: a multicenter trial using statistical process control. Intensive Care Med 2010; 36 (09) 1556-1565.
- 9 Amin SG. Control charts 101: a guide to health care applications. Qual Manag Health Care 2001; 9 (03) 1-27.
- 10 Benneyan JC, Lloyd RC, Plsek PE. Statistical process control as a tool for research and healthcare improvement. Qual Saf Health Care 2003; 12 (06) 458-464.
- 11 Carey RG, Stake LV. Improving Healthcare with Control Charts: Basic and Advanced SPC Methods and Case Studies. Milwaukee: ASQ Quality Press; 2001
- 12 Carey RG. How do you know that your care is improving? Part II: Using control charts to learn from your data. J Ambul Care Manage 2002; 25 (02) 78-88.
- 13 Carey RG. Constructing powerful control charts. J Ambul Care Manage 2002; 25 (04) 64-70.
- 14 Hart MK, Hart RF. Statistical Process Control for Health Care. Pacific Grove: Brooks Cole; 2001
- 15 Hart MK, Lee KY, Hart RF, Robertson JW. Application of attribute control charts to risk-adjusted data for monitoring and improving health care performance. Qual Manag Health Care 2003; 12 (01) 5-19.
- 16 Hart MK, Robertson JW, Hart RF, Lee KY. Application of variables control charts to risk-adjusted time-ordered healthcare data. Qual Manag Health Care 2004; 13 (02) 99-119.
- 17 Matthes N, Ogunbo S, Pennington G, Wood N, Hart MK, Hart RF. Statistical process control for hospitals: methodology, user education, and challenges. Qual Manag Health Care 2007; 16 (03) 205-214.
- 18 Mohammed MA, Worthington P, Woodall WH. Plotting basic control charts: tutorial notes for healthcare practitioners. Qual Saf Health Care 2008; 17 (02) 137-145.
- 19 Benneyan JC. The design, selection, and performance of statistical control charts for healthcare process improvement. Int J Six Sigma and Competitive Advantage 2008; 4 (03) 209-239.
- 20 Carey RG. Measuring health care quality. How do you know your care has improved?. Eval Health Prof 2000; 23 (01) 43-57.
- 21 Hart MK, Robertson JW, Hart RF, Schmaltz S. X and s charts for health care comparisons. Qual Manag Health Care 2006; 15 (01) 2-14.
- 22 Bell R, Krivich MJ, Boyd MS. Charting patient satisfaction. Mark Health Serv 1997; 17 (02) 22-29.
- 23 Bluth EI, Havrilla M, Blakeman C. Quality improvement techniques: value to improve the timeliness of preoperative chest radiographic reports. AJR Am J Roentgenol 1993; 160 (05) 995-998.
- 24 Carey RG, Teeters JL. CQI case study: reducing medication errors. Jt Comm J Qual Improv 1995; 21 (05) 232-237.
- 25 Guinane CS, Sikes JI, Wilson RK. Using the PDSA cycle to standardize a quality assurance program in a quality improvement-driven environment. Jt Comm J Qual Improv 1994; 20 (12) 696-705.
- 26 Oniki TA, Clemmer TP, Arthur LK, Linford LH. Using statistical quality control techniques to monitor blood glucose levels. Proc Annu Symp Comput Appl Med Care 1995: 586-590.
- 27 Ornstein SM, Jenkins RG, Lee FW, Sack JL, LaKier EI, Roskin SD. et al. The computer-based patient record as a CQI tool in a family medicine center. Jt Comm J Qual Improv 1997; 23 (07) 347-361.
- 28 Schnelle JF, Newman DR, Fogarty T. Statistical quality control in nursing homes: assessment and management of chronic urinary incontinence. Health Serv Res 1990; 25 (04) 627-637.
- 29 Vitez TS, Macario A. Setting performance standards for an anesthesia department. J Clin Anesth 1998; 10 (02) 166-175.
- 30 Al-Hussein FA. A tale of two audits: statistical process control for improving diabetes care in primary care settings. Qual Prim Care 2008; 16 (01) 53-60.
- 31 Baker RA, Newland RF. Continous quality improvement of perfusion practice: the role of electronic data collection and statistical control charts. Perfusion 2008; 23 (01) 7-16.
- 32 Boe DT, Riley W, Parsons H. Improving service delivery in a county health department WIC clinic: an application of statistical process control techniques. Am J Public Health 2009; 99 (09) 1619-1625.
- 33 Bonetti PO, Waeckerlin A, Schuepfer G, Frutiger A. Improving time-sensitive processes in the intensive care unit: the example of ‘door-to-needle time’ in acute myocardial infarction. Int J Qual Health Care 2000; 12 (04) 311-317.
- 34 Chaboyer W, Johnson J, Hardy L, Gehrke T, Panuwatwanich K. Transforming care strategies and nursing-sensitive patient outcomes. J Adv Nurs 2010; 66 (05) 1111-1119.
- 35 Curran E, Harper P, Loveday H, Gilmour H, Jones S, Benneyan J. et al. Results of a multicentre randomised controlled trial of statistical process control charts and structured diagnostic tools to reduce ward-acquired meticillin-resistant Staphylococcus aureus: the CHART Project. J Hosp Infect 2008; 70 (02) 127-135.
- 36 Curran ET, Benneyan JC, Hood J. Controlling methicillin-resistant Staphylococcus aureus: a feedback approach using annotated statistical process control charts. Infect Control Hosp Epidemiol 2002; 23 (01) 13-18.
- 37 Duclos A, Touzet S, Soardo P, Colin C, Peix JL, Lifante JC. Quality monitoring in thyroid surgery using the Shewhart control chart. Br J Surg 2009; 96 (02) 171-174.
- 38 Ernst MM, Wooldridge JL, Conway E, Dressman K, Weiland J, Tucker K. et al. Using quality improvement science to implement a multidisciplinary behavioral intervention targeting pediatric inpatient airway clearance. J Pediatr Psychol 2010; 35 (01) 14-24.
- 39 Greene RA, Beckman H, Chamberlain J, Partridge G, Miller M, Burden D. et al. Increasing adherence to a community-based guideline for acute sinusitis through education, physician profiling, and financial incentives. Am J Manag Care 2004; 10 (10) 670-678.
- 40 Harrington G, Watson K, Bailey M, Land G, Borrell S, Houston L. et al. Reduction in hospitalwide incidence of infection or colonization with methicillin-resistant Staphylococcus aureus with use of antimicrobial hand-hygiene gel and statistical process control charts. Infect Control Hosp Epidemiol 2007; 28 (07) 837-844.
- 41 Huang RL, Donelli A, Byrd J, Mickiewicz MA, Slovis C, Roumie C. et al. Using quality improvement methods to improve door-to-balloon time at an academic medical center. J Invasive Cardiol 2008; 20 (02) 46-52.
- 42 Hyrkas K, Lehti K. Continuous quality improvement through team supervision supported by continuous self-monitoring of work and systematic patient feedback. J Nurs Manag 2003; 11 (03) 177-188.
- 43 Krimsky WS, Mroz IB, McIlwaine JK, Surgenor SD, Christian D, Corwin HL. et al. A model for increasing patient safety in the intensive care unit: increasing the implementation rates of proven safety measures. Qual Saf Health Care 2009; 18 (01) 74-80.
- 44 McCann E, Baines EA, Gray JR, Procter AM. Improving service delivery by evaluation of the referral pattern and capacity in a clinical genetics setting. Am J Med Genet C Semin Med Genet 2009; 151C (03) 200-206.
- 45 Mertens WC, Higby DJ, Brown D, Parisi R, Fitzgerald J, Benjamin EM. et al. Improving the care of patients with regard to chemotherapy-induced nausea and emesis: the effect of feedback to clinicians on adherence to antiemetic prescribing guidelines. J Clin Oncol 2003; 21 (07) 1373-1378.
- 46 Mohammed MA, Booth K, Marshall D, Brolly M, Marshall T, Cheng KK. et al. A practical method for monitoring general practice mortality in the UK: findings from a pilot study in a health board of Northern Ireland. Br J Gen Pract 2005; 55 (518) 670-676.
- 47 Mukhtar SA, Hoffman NE, MacQuillan G, Semmens JB. The hospital mortality project: a tool for using administrative data for continuous clinical quality assurance. HIM J 2008; 37 (02) 9-18.
- 48 Peterson A, Carlhed R, Lindahl B, Lindstrom G, Aberg C, Andersson-Gare B. et al. Improving guideline adherence through intensive quality improvement and the use of a National Quality Register in Sweden for acute myocardial infarction. Qual Manag Health Care 2007; 16 (01) 25-37.
- 49 Ratcliffe MB, Khan JH, Magee KM, McElhinney DB, Hubner C. Collection of process data after cardiac surgery: initial implementation with a Java-based intranet applet. Ann Thorac Surg 2000; 69 (06) 1817-1821.
- 50 Ryckman FC, Schoettker PJ, Hays KR, Connelly BL, Blacklidge RL, Bedinghaus CA. et al. Reducing surgical site infections at a pediatric academic medical center. Jt Comm J Qual Patient Saf 2009; 35 (04) 192-198.
- 51 Salaripour M, McKernan P, Devlin R. A multidisciplinary approach to reducing outbreaks and nosocomial MRSA in a university-affiliated hospital. Healthc Q 2006; 9 Spec No 54-60.
- 52 Saturno PJ, Felices F, Segura J, Vera A, Rodriguez JJ. Reducing time delay in the thrombolysis of myocardial infarction: an internal quality improvement project. ARIAM Project Group. Analisis del Retraso en Infarto Agudo de Miocardio. Am J Med Qual 2000; 15 (03) 85-93.
- 53 Sorokin R, Gottlieb JE. Enhancing patient safety during feeding-tube insertion: a review of more than 2,000 insertions. JPEN J Parenter Enteral Nutr 2006; 30 (05) 440-445.
- 54 Stockman T, Krishnan S. Acceptance of PACS utilizing a PACS QI Program. Radiol Manage 2006; 28 (02) 16-17.
- 55 Vallance-Owen A, Cubbin S, Warren V, Matthews B. Outcome monitoring to facilitate clinical governance; experience from a national programme in the independent sector. J Public Health (Oxf) 2004; 26 (02) 187-192.
- 56 Nelson LS. Technical Aids. Journal of Quality Technology 1984; 16 (04) 238-239.