A three-dimensional model of error and safety in surgical health care microsystems. Rationale, development and initial testing

BMC Surgery

Ken Catchpole¹  Peter McCulloch¹ 

[1] Quality, Reliability, Safety and Teamwork Unit, Nuffield Department of Surgical Sciences, University of Oxford, Level 6 John Radcliffe Hospital, Headley Way, Oxford OX3 9DU UK

关键词: culture;    theory, system;    medical error;    surgery;    Patient safety;   

Others  :  1123434
DOI  :  10.1186/1471-2482-11-23

 received in 2011-01-21, accepted in 2011-09-05,  发布年份 2011

【 摘 要 】

Background

Research estimates of inadvertent harm to patients undergoing modern healthcare demonstrate a serious problem. Much attention has been paid to analysis of the causes of error and harm, but researchers have typically focussed either on human interaction and communication or on systems design, without fully considering the other components. Existing models for analysing harm are principally derived from theory and the analysis of individual incidents, and their practical value is often limited by the assumption that identifying causal factors automatically suggests solutions. We suggest that new models based on observation are required to help analyse healthcare safety problems and evaluate proposed solutions. We propose such a model which is directed at "microsystem" level (Ward and operating theatre), and which frames problems and solutions within three dimensions.

Methods

We have developed a new, simple, model of safety in healthcare systems, based on analysis of real problems seen in surgical systems, in which influences on risk at the "microsystem" level are described in terms of only 3 dimensions - technology, system and culture. We used definitions of these terms which are similar or identical to those used elsewhere in the safety literature, and utilised a set of formal empirical and deductive processes to derive the model. The "3D" model assumes that new risks arise in an unpredictable stochastic manner, and that the three defined dimensions are interactive, in an unconstrained fashion. We illustrated testing of the model, using analysis of a small number of incidents in a surgical environment for which we had detailed prospective observational data.

Results

The model appeared to provide useful explanation and categorisation of real events. We made predictions based on the model, which are experimentally verifiable, and propose further work to test and refine it.

Conclusion

We suggest that, if calibrated by application to a large incident dataset, the 3D model could form the basis for a quantitative statistical method for estimating risk at microsystem levels in many acute healthcare settings.

【 授权许可】

   
2011 McCulloch and Catchpole; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

【 参考文献 】

• [1]Limits to medicine: medical nemesis, the expropriation of health Ivan Illich London : Boyars 1976.
• [2]Brennan TA, Leape LL, Laird NM, Hebert L, Localio AR, Lawthers AG, Newhouse JP, Weiler PC, Hiatt HH: Incidence of adverse events and negligence in hospitalized patients. Results of the Harvard Medical Practice Study I. N Engl J Med 1991, 324(6):370-6.
• [3]Gawande AA, Thomas EJ, Zinner MJ, Brennan TA: The incidence and nature of surgical adverse events in Colorado and Utah in 1992. Surgery 1999, 126(1):66-75.
• [4]Wilson RM, Runciman WB, Gibberd RW, Harrison BT, Newby L, Hamilton JD: The Quality in Australian Health Care Study. Med J Aust 1995, 163(9):458-471.
• [5]Vincent C, Neale G, Woloshynowych M: Adverse events in British hospitals: Preliminary retrospective record review. BMJ 2001, 322:517-519.
• [6]Baker GR, Norton PG, Flintoft V, Blais R, Brown A, Cox J, et al.: The Canadian Adverse Events Study: the incidence of adverse events among hospital patients in Canada. CMAJ 2004, 170(11):1678-1686.
• [7]Kohn LT, Corrigan J, Donaldson MS: To err is human: building a safer health system. Washington, D.C: National Academy Press; 1999.
• [8]Department of Health: An organisation with a memory: report of an expert group on learning from adverse events in the NHS. London: Stationery Office; 2000.
• [9]Comstock GW, O'Brien RJ: "Tuberculosis" in Evans AS and Brachman PS "Bacterial infections of humans; epidemiology and control. 2nd edition. NY Plenum Publishing; 1991:745-772.
• [10]RL Wears High reliability organisations: Keep the celebrations short Qual Saf Health Care 2005, 14:154.
• [11]McCulloch P, Mishra A, Handa A, Dale T, Hirst G, Catchpole K: The effects of aviation-style non-technical skills training on technical performance and outcome in the operating theatre. Qual Saf Health Care 2009, 18(2):109-115.
• [12]Reason J: Human error. New York: Cambridge University Press; 1990.
• [13]Amalberti R, Vincent C, Auroy Y, de Saint Maurice G: Violations and migrations in health care: a framework for understanding and management. Qual Saf Health Care 2006, 15(Suppl 1):i66-71.
• [14]Nemeth C, Wears R, Woods D, Hollnagel E, Cook R: Minding the Gaps: Creating Resilience in Health Care. In Advances in Patient Safety: New Directions and Alternative Approaches (Vol. 3: Performance and Tools). Edited by Henriksen K, Battles JB, Keyes MA, Grady ML. Rockville (MD): Agency for Healthcare Research and Quality (US); 2008.
• [15][http:/ / www1.imperial.ac.uk/ medicine/ about/ institutes/ patientsafetyservicequality/ cpssq_publications/ resources_tools/ the_london_protocol/ ] webcite (accessed 17th August 2011)
• [16]Carayon P, Schoofs Hundt A, Karsh B-T, Gurses AP, Alvarado CJ, Smith M, Flatley Brennan P: Work system design for patient safety: the SEIPS model. Quality and Safety in Health Care 2006, 15(Supplement 1):i50-i58.
• [17]More than words: Final Technical Report, January 2009. Conceptual Framework for the International Classification for Patient Safety. [http://www.who.int/patientsafety/taxonomy/icps_full_report.pdf] webcite (accessed 30/6/11)
• [18]Lingard L, Espin S, Whyte S, Regehr G, Baker GR, Reznick R, Bohnen J, Orser B, Doran D, Grober E: Communication failures in the operating room: an observational classification of recurrent types and effects. Qual Saf Health Care 2004, 13(5):330-4.
• [19]Catchpole KR, Giddings AE, de Leval MR, Peek GJ, Godden PJ, Utley M, Gallivan S, Hirst G, Dale T: Identification of systems failures in successful paediatric cardiac surgery. Ergonomics 2006, 49(5-6):567-88.
• [20]Kreckler S, Catchpole KR, New SJ, Handa A, McCulloch PG: Quality and safety on an acute surgical ward: an exploratory cohort study of process and outcome. Ann Surg 2009, 250(6):1035-40.
• [21]van Wagtendonk I, Smits M, Merten H, Heetveld MJ, Wagner C: Nature, causes and consequences of unintended events in surgical units. Br J Surg 2010, 97(11):1730-40.
• [22]Regenbogen SE, Greenberg CC, Studdert DM, Lipsitz SR, Zinner MJ, Gawande AA: Patterns of technical error among surgical malpractice claims: an analysis of strategies to prevent injury to surgical patients. Ann Surg 2007, 246(5):705-11.
• [23]Vincent C, Moorthy K, Sarker SK, Chang A, Darzi AW: Systems approaches to surgical quality and safety: from concept to measurement. Ann Surg 2004, 239(4):475-82.
• [24]Haynes AB, Weiser TG, Berry WR, Lipsitz SR, Breizat AH, Dellinger EP, Dziekan G, Herbosa T, Kibatala PL, Lapitan MC, Merry AF, Reznick RK, Taylor B, Vats A, Gawande AA, Safe Surgery Saves Lives Study Group: Changes in safety attitude and relationship to decreased postoperative morbidity and mortality following implementation of a checklist-based surgical safety intervention. BMJ Qual Saf 2011, 20(1):102-7.
• [25]Catchpole KR, Giddings AE, Wilkinson M, Hirst G, Dale T, de Leval MR: Improving patient safety by identifying latent failures in successful operations. Surgery 2007, 142(1):102-10.
• [26]Berry DJ: Medical technology risks: looking beyond the obvious. J Healthc Risk Manag 1993, 13(4):36-42.
• [27]Top ten hazards of medical technology 2011 [https://www.ecri.org/Products/Pages/Top-10-Hazards-Resources.aspx] webcite
• [28]Nieva VF, Sorra J: Safety culture assessment: a tool for improving patient safety in healthcare organizations. Qual Saf Health Care 2003, 12(Suppl 2):ii17-23.
• [29]Ashcroft DM, Morecroft C, Parker D, Noyce PR: Safety culture assessment in community pharmacy: development, face validity, and feasibility of the Manchester Patient Safety Assessment Framework. Qual Saf Health Care 2005, 14(6):417-21.
• [30]Sexton JB, Helmreich RL, Neilands TB, Rowan K, Vella K, Boyden J, Roberts PR, Thomas EJ: The Safety Attitudes Questionnaire: psychometric properties, benchmarking data, and emerging research. BMC Health Serv Res 2006, 6:44. BioMed Central Full Text
• [31]Vincent C, Moorthy K, Sarker SK, Chang A, Darzi AW: Systems approaches to surgical quality and safety: from concept to measurement. Ann Surg 2004, 239(4):475-82.
• [32]Catchpole KR, Giddings AE, de Leval MR, Peek GJ, Godden PJ, Utley M, Gallivan S, Hirst G, Dale T: Identification of systems failures in successful paediatric cardiac surgery. Ergonomics 2006, 49(5-6):567-88.
• [33]Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, Sam J, Haynes RB: Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005, 293(10):1223-38.
• [34]Franklin BD, O'Grady K, Donyai P, Jacklin A, Barber N: The impact of a closed-loop electronic prescribing and administration system on prescribing errors, administration errors and staff time: a before-and-after study. Qual Saf Health Care 2007, 16(4):279-84.
• [35]Donabedian A: Evaluating the quality of medical care. Millbank Mem Fund Q 1966, 44:166-206.
• [36]Reason J: Managing the Risks of Organizational Accidents. Ashgate Publications, Farnham, UK; 1997.
• [37]Molloy GJ, O'Boyle CA: The SHEL model: a useful tool for analyzing and teaching the contribution of Human Factors to medical error. Acad Med 2005, 80(2):152-5.