مدل ارزیابی سیاست‌های مدیریت ریسک بالینی

نوع مقاله: علمی - پژوهشی

نویسندگان

گروه مهندسی صنایع، دانشگاه ایوان‌کی، گرمسار، ایران

چکیده

خطاهای بالینی نه تنها باعث کاهش سطح ایمنی بیمار، آسیب به سلامتی و حتی مرگ بیمار شده و بلکه منجر به از دست رفتن وجه پزشک و برند بیمارستان می‌گردد. بر اساس آمار سازمان جهانی بهداشت، اشتباهات پزشکی هشتمین علت مرگ افراد است. وجود سیستم مدیریت ریسک بالینی ابزاری نظام‌مند است جهت به حداقل رساندن خطا و پیشگیری از بروز خطاهای سیستماتیک است. برخورداری از این سیستم اثربخش، نیازمند شناسایی ساختار سیستمی مولد رفتار مشکل‌زا و همچنین یافتن سیاست‌های مناسب بهبود است.پژوهش حاضر بر شناسایی ساختار سیستمی مؤثر بر رخداد خطاهای بالینی در بیمارستان‌ها با رویکرد پویایی‌شناسی سیستم تمرکز دارد. در این رویکرد پس از نگاشت ساختار سیستمی مولد مسئله، حلقه‌های بازخوردی بازنمایی می‌شود. همچنین با ارائه یک مدل شبیه‌سازی، امکان ارزیابی سیستمی اثربخشی سیاست‌های مدیریتی امکان‌پذیر است.نتایج نشان می‌دهد سیاست‌های ایجاد پرونده الکترونیک سلامت، فرهنگ ایمنی بیمار و حاکمیت بالینی در کاهش خطاهای بالینی نقش مؤثری دارند. از این میان سیاست بهبود فرهنگ ایمنی بیمار سیاستی است که با بیشترین اثربخشی معرفی می‌گردد.نظام سلامت ایران علی‌رغم رشد زیرساخت‌های سلامت و سیاست‌گذاری‌های جدید، خطاهای پزشکی با روند در حال رشد مواجه است و این موضوع به یکی از چالش‌های مهم سیاست‌گذاران حوزه سلامت تبدیل شده است. توسعه زیرساخت و تلاش برای بهبود شاخص‌های عملکردی بدون برخورداری از درک سیستمی از مسئله، منجر به کاهش میزان خطاهای بالینی در بیمارستان‌ها و مراکز سلامت نخواهد شد.

کلیدواژه‌ها


عنوان مقاله [English]

Modeling Evaluation of Clinical Risk Management Policies

نویسندگان [English]

  • Mahdi Bastan
  • Elaheh Zadfallah
  • Alimohammad Ahmadvand
Department of Industrial Engineering, University of Eyvanakey, Garmsar, Iran
چکیده [English]

Objective: Clinical errors reduce patient's safety, damage their health and even can be cause of death. On the other hand, it leads to the loss of the physician’s image and hospital's brand. According to the World Health Organization’s report, medical errors are the eighth cause of people death. Having an appropriate clinical risk management system as a systematic tool is crucial for minimizing errors and preventing systematic errors. It requires identifying the systemic structure of the problematic behavior generator as well as finding efficient improvement policies.
Methods: The present research focuses on identifying the systemic structure affecting the occurrence of clinical errors in hospitals with System Dynamics approach. Based on this methodology, after mapping the system structure, feedback loops are represented. Also, by presenting a simulation model, it is possible to have a model-based assessment of management policies.
Results:The results show that management policies such as implementing Electronic Health Record and clinical governance and also creation patient safety culture have a significant effect on reducing clinical errors. Among them, the promoting patient safety culture is introduced as the most effective policy.
Conclusion: In Iran’s health system, despite the growth of health infrastructure and new improvement policies, medical errors continue to increase with increasing trends, and this has become one of the important issues of health policy makers. Infrastructure development and efforts to improve performance indicators without having a systemic insight of the problem will not reduce clinical errors in hospitals and health centers.

کلیدواژه‌ها [English]

  • Clinical Risk Management
  • Electronic health record
  • patient safety
  • Clinical Governance
  • system dynamics
  1. Abbasi, E., Bastan, M., & Ahmadvand. A. (2016). A system dynamics model for mobile banking adoption. The 12th International Conference on Industrial Engineering (IIEC2016), Tehran, Iran.
  2. Bagherian M., Abadi, H., et al. (2012). the frequency and causes of medical errors in referral files to the general office of legal medicine of isfahan province. Health information management, 9(1).
  3. Baker, G.R., et al. (2004). The canadian adverse events study: the incidence of adverse events among hospital patients in canada. Canadian medical association journal, 170(11), 1678-1686.
  4. Brown, A.S. (2011). Clinical trials risk: a new assessment tool. Clinical Governance: An International Journal, 16(2), 103-110.
  5. Bastan, M., et al. (2018). Sustainable development of agriculture: a system dynamics model. Kybernetes, 47(1), 142-162.
  6. Bastan, M., et al. (2018). A simulation model of mobile banking acceptance by bank customers using the system dynamics approach. Journal of Industrial Management Studies, 16(50), 257-284. (In Persian)
  7. Carroll, R., (2009). Risk management handbook for health care organizations, John Wiley & Sons. 30(90).
  8. Ceresia, F., & Montemaggiore. G.B. (2013). Applying the system dynamics approach in evaluating clinical risk management policies in three healthcare companies. The 31st International Conference of the System Dynamics Society.
  9. Dean, B., et al. (2002). Causes of prescribing errors in hospital inpatients: a prospective study. The Lancet, 359(9315), 1373-1378.
  10. Donaldson, M.S., Corrigan, J.M., & Kohn, L.T. (2000). To err is human: building a safer health system. National Academies Press.
  11. Fernández-Castelló, A.I., et al. (2018). An experience in integrated management of clinical risks. Journal of Healthcare Quality Research, 33(6), 311-318.
  12. Gallagher, T.H., et al. (2006). US and Canadian physicians' attitudes and experiences regarding disclosing errors to patients. Archives of Internal Medicine, 166(15), 1605-1611.
  13. Guo, S. (2016). Systemic analysis and modelling of diagnostic errors in medicine. City University London.
  14. Jalalifar, F., Sepehri, M.M., & Naghibi, F. (2016). Identification of the most important risky stage in medincne delivery process in a hospital, based on the fuzzy analytical hierarchy process, The 12th International Conference on Industrial Engineering (IIEC2016), Tehran, Iran (in Persian)

 

  1. Okoroh, M., Ilozor, B., & Gombera. P. (2006). Modelling of risk management in health care facilities. Facilities, 24(5/6), 197-210.
  2. Ker, K., et al. (2010). Caffeine for the prevention of injuries and errors in shift workers. The Cochrane Library.
  3. Levin, S.K., et al. (2019). Adherence to planned risk management interventions in Swedish forensic care: What is said and done according to patient records. International Journal of Law and Psychiatry, 64, 71-82.
  4. Masnick, K., & McDonnell. G. (2010). A model linking clinical workforce skill mix planning to health and health care dynamics. Human resources for health, 8(1), 11.
  5. Jankuj, M., & Voracek, J. (2015). Dynamic modelling of national healthcare system. Measuring Business Excellence, 19(3), 76-89.
  6. Ministry of Health and Medical Education, N., (2009). Comparison of some of the performance indicators of the ministry of health and medical education (2005-2009), News and information center of the ministry of health and medical education.
  7. Riazi, H., Fathi R., & Bitaraf, E. (2017). Electronic health record development, concepts, standards and solutions, Ministry of health and medical education: Tehran, Iran
  8. Shanafelt, T., Sinsky, C. A., & Swensen, S. (2017). Preventable deaths in american hospitals.
  9. Soheilinia, H., & Sepehri, M.M. (2015). Errors reduction management in the operating room processes with the help of HFMEA, in The 12th international conference on industrial engineering (IIEC2016). Tehran, Iran (In Persian)
  10. Stavert-Dobson, A. (2015). Health information systems: managing clinical risk. Springer.
  11. Valentina, A., Ceresia, F., & Casiglia, A.C. (2014). The clinical risk management in a hospital ward: a case-study adopting system dynamics approach, The 32th International conference of the system dynamics society, Delft, The Netherlands.
  12. Vincent, C. (2001). Clinical risk management: Enhancing patient safety. BMJ books.
  13. Nicholls, S., et al. (2000). Clinical governance: its origins and its foundations. British Journal of Clinical Governance, 5(3), 172-178.
  14. Zadfallah, E., Bastan, M., & Ahmadvand., A.M. (2017). A qualitative system dynamics approach to clinical risk management. The 13th international conference on industrial engineering, Babolsar, Iran.