THE PROBLEM OF KNOWLEDGE TRANSLATION IN HEALTHCARE: TOOLS FOR ITS SOLUTION IN THE AREA OF PATIENT SAFETY

Cover Page
  • Authors: Kleymenova E.B.1, Nazarenko G.I.2, Payushchik S.A.1, Yashina L.P.1
  • Affiliations:
    1. General Medical Center of the Bank of Russia
    2. Institute of Modern Information Technologies in Medicine, Federal Research Center «Computer Science and Control» of the Russian Academy of Sciences
  • Issue: Vol 73, No 2 (2018)
  • Pages: 105-114
  • Section: HEALTH CARE MANAGEMENT: CURRENT ISSUES
  • URL: https://vestnikramn.spr-journal.ru/jour/article/view/887
  • DOI: https://doi.org/10.15690/vramn887

Abstract


Adherence to evidence-based clinical guidelines enhances patient safety, but the level of knowledge implementation into routine practice remains unsatisfactory. The concept of knowledge translation (KT) was proposed as a «process that includes the synthesis, dissemination, exchange, and ethically sound application of knowledge» to define the framework of knowledge transfer from research to practical activities aimed at improving the quality and safety of healthcare. Although Russian authors pay much attention to translational medicine, the problem of implementation research is poorly discussed. Modern information technologies including clinical decision support systems (CDSS) play a crucial role in KT, but the evidence of their effectiveness is poor. The authors describe a systematic approach to the practical implementation of knowledge imbedded in clinical guidelines based on the use of CDSS. CDSS implementation was accompanied by organizational measures that ensured the overall success: creation of standard operating protocols and quality register, clinical audit with feedback, and staff training. The effectiveness of this approach in reducing the risk of inhospital complications in Moscow general hospital is illustrated by the example of hospital-acquired venous thromboembolism (HA-VTE) prevention. Implementation of a comprehensive program for HA-VTE prevention in 2014−2016 helped to increase the coverage with VTE and bleeding risk assessment from 15% to 80% (p<0.0001), to reduce the frequency of pharmacological prophylaxis defects from 50.6% to 23% (p=0.01), to increase the compliance with anticoagulant use from 50% to 76% (p=0.0005), without increasing the rate of hemorrhagic complications. The HA-VTE rates decreased from 10 to 4.25 cases per 1000 overall hospital admissions (p=0.001), from 8 to 1.27 cases per 1000 operations in surgical patients (p=0.001) and from 12 to 6.38 cases per 1000 hospitalizations in therapeutic patients (p=0.06; with a statistically significant downward linear trend for HA-VTE rate, p=0.038).


E. B. Kleymenova

General Medical Center of the Bank of Russia

Email: e.kleymenova@gmail.com
ORCID iD: 0000-0002-8745-6195

Russian Federation

Moscow

G. I. Nazarenko

Institute of Modern Information Technologies in Medicine, Federal Research Center «Computer Science and Control» of the Russian Academy of Sciences

Email: gerasimnazarenko@gmail.com
ORCID iD: 0000-0002-0026-7720

Moscow

S. A. Payushchik

General Medical Center of the Bank of Russia

Author for correspondence.
Email: lyashina1@yandex.ru
ORCID iD: 0000-0003-1357-0056

Moscow

L. P. Yashina

General Medical Center of the Bank of Russia

Email: svetlanapay@gmail.com
ORCID iD: 0000-0002-7350-0423

Moscow

  1. Kohn LT, Corrigan JM, Donaldson MS. To err is human: Building a safer health system. Washington: National City Press; 2000.
  2. Dubrovsky AS, Bishop A, Biron A, et al. “We Should Talk”— moving knowledge into action by learning to engage patients, families, and healthcare staff to communicate for patient safety. Healthc Manage Forum. 2016;29(4):141–145. doi: 10.1177/0840470416641119.
  3. Mitchell I, Schuster A, Smith K, et al. Patient safety incident reporting: a qualitative study of thoughts and perceptions of experts 15 years after ‘To Err is Human’. BMJ Qual Saf. 2016;25(2):92–99. doi: 10.1136/bmjqs-2015-004405.
  4. National Patient Safety Foundation. Free from Harm: Accelerating Patient Safety Improvement Fifteen Years after To Err Is Human [Internet]. Boston: National Patient Safety Foundation; 2015 [cited 2016 Feb 10]. Available from: http://www.npsf.org/?page=freefromharm.
  5. Hoesing H. Clinical practice guidelines: closing the gap between theory and practice [Internet]. A white paper by Joint Commission International. Joint Commission International; 2016 [cited 2017 Jul 14]. Available from: https://www.elsevier.com/__data/assets/pdf_file/0007/190177/JCI-Whitepaper_cpgs-closing-the-gap.pdf.
  6. Fonarow GC, Yancy CW, Hernandez AF, et al. Potential impact of optimal implementation of evidence-based heart failure therapies on mortality. Am Heart J. 2011;161(6):1024–1030. doi: 10.1016/j.ahj.2011.01.027.
  7. Joint Commission International. Joint Commission International Accreditation Standards for Hospitals. 5th ed. Oak Brook: Joint Commission Resources; 2014. 296 p.
  8. Clark R, Tonmukayakul U, Mangan Y, et al. Measuring adherence to evidence-based clinical practice guideline. J Evid Based Dent Pract. 2017;17(4):301–309. doi: 10.1016/j.jebdp.2017.05.001.
  9. Mearis M, Shega JW, Knoebel RW. Does adherence to national comprehensive cancer network guidelines improve pain-related outcomes? An evaluation of inpatient cancer pain management at an academic medical center. J Pain Symptom Manage. 2014;48(3):451–458. doi: 10.1016/j.jpainsymman.2013.09.016.
  10. Farfan M, Bautista M, Bonilla G, et al. Worldwide adherence to ACCP guidelines for thromboprophylaxis after major orthopedic surgery: a systematic review of the literature and meta-analysis. Thromb Res. 2016;141:163–170. doi: 10.1016/j.thromres.2016.03.029.
  11. Borchard A, Schwappach DL, Barbir A, Bezzola P. A systematic review of the effectiveness, compliance, and critical factors for implementation of safety checklists in surgery. Ann Surg. 2012;256(6):925–933. doi: 10.1097/SLA.0b013e3182682f27.
  12. Cabana MD, Rand CS, Powe NR, et al. Why don’t physicians follow clinical practice guidelines? JAMA. 1999;282(15):1458. doi: 10.1001/jama.282.15.1458.
  13. Glasziou P, Haynes B. The paths from research to improved health outcomes. ACP J Club. 2005;142(2):A8–10.
  14. Asonganyi E, Vaghasia M, Rodrigues C, et al. Factors affecting compliance with clinical practice guidelines for pap smear screening among healthcare providers in africa: systematic review and meta-summary of 2045 individuals. PLoS One. 2013;8(9):e72712. doi: 10.1371/journal.pone.0072712.
  15. Keiffer MR. Utilization of clinical practice guidelines: barriers and facilitators. Nurs Clin North Am. 2015;50(2):327–345. doi: 10.1016/j.cnur.2015.03.007.
  16. Straus SE, Tetroe J, Graham I. Defining knowledge translation. CMAJ. 2009;181(3-4):165–168. doi: 10.1503/cmaj.081229.
  17. Pablos-Mendez A, Chunharas S, Lansang MA, et al. Knowledge translation in global health. Bull World Health Organ. 2005;83(10):723.
  18. www.unitedhealthfoundation.org [Internet]. Haynes RB. Evidence-based medicine and knowledge translation: horse and carriage. United Health Foundation Commentary. April, 2007 [cited 2009 Oct 23]. Available from: http://www.unitedhealthfoundation.org/ebm.html.
  19. Khoddam H, Mehrdad N, Peyrovi H, et al. Knowledge translation in health care: a concept analysis. Med J Islam Repub Iran. 2014;28:98.
  20. Щербо С.Н. Трансляционная медицина // Медицинский алфавит. ― 2012. ― Т.2. ― №10 ― С. 5–6.
  21. Сучков С.В., Ридинг С., Чжао А.В., и др. Трансляционная медицина как уникальный инструмент развития национальных и международных систем охраны здоровья (Часть 1) // Высокотехнологическая медицина. ― 2015. ― Т.2. ― №1 ― С. 42–46.
  22. Paltsev MA, Belushkina NN. Translational medicine ― a new stage in the development of molecular medicine. Molekulyarnaya meditsina. 2012;(4):3−6. (In Russ).
  23. Ponomarenko GN. The concept of translational medicine in physiotherapy and rehabilitation. Fizioterapiya, bal’neologiya i reabilitatsiya. 2014;(3):4−12. (In Russ).
  24. Shlyakhto EV, Konradi AO, Galagudza MM. Translational medicine: yesterday, today, tomorrow. Vestnik Roszdravnadzora. 2016;(1):47−51. (In Russ).
  25. Dougherty D, Conway PH. The «3T’s» road map to transform US health care: the «how» of high-quality care. JAMA. 2008;299(19):2319−2321. doi: 10.1001/jama.299.19.2319.
  26. Cohrs RJ, Martin T, Ghahramani P, et al. Translational medicine definition by the European Society for Translational Medicine. New Horiz Transl Med. 2015;2(3):86–88. doi: 10.1016/j.nhtm.2014.12.002.
  27. Damschroder LJ, Aron DC, Keith RE, et al. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4:50. doi: 10.1186/1748-5908-4-50.
  28. Green LW, Ottoson JM, Garcia C, Hiatt RA. Diffusion theory and knowledge dissemination, utilization, and integration in public health. Annu Rev Public Health. 2009;30:151–174. doi: 10.1146/annurev.publhealth.031308.100049.
  29. www.g-i-n.net [Internet]. Introduction to the G-I-N Adaptation Working Group [cited 2017 Jul 20]. Available from: http://www.g-i-n.net/working-groups/adaptation/introduction-g-i-n-adaptation-wg.
  30. www.g-i-n.net [Internet]. The ADAPTE Collaboration. The ADAPTE Process: Resource Toolkit for Guideline Adaptation. V. 2.0. 2009. 94 р [cited 2017 Jul 20]. Available from: http://www.g-i-n.net/document-store/working-groups-documents/adaptation/adapte-resource-toolkit-guideline-adaptation-2-0.pdf.
  31. Eccles MP, Mittman BS. Welcome to implementation science. Implement Sci. 2006;1:1. doi: 10.1186/1748-5908-1-1.
  32. Powell BJ, Waltz TJ, Chinman MJ, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10:21. doi: 10.1186/s13012-015-0209-1.
  33. Powell BJ, Stanick CF, Halko HM, et al. Toward criteria for pragmatic measurement in implementation research and practice: a stakeholder-driven approach using concept mapping. Implement Sci. 2017;12(1):118. doi: 10.1186/s13012-017-0649-x.
  34. Tricco AC, Ashoor HM, Cardoso R, et al. Sustainability of knowledge translation interventions in healthcare decision making: a scoping review. Implement Sci. 2016;11:55. doi: 10.1186/s13012-016-0421-7.
  35. Shekelle PG, Ortiz E, Rhodes S, et al. Validity of the Agency For Healthcare Research and Quality clinical practice guidelines: how quickly do guidelines become outdated? JAMA. 2001;286(12):1461–1467. doi: 10.1001/jama.286.12.1461.
  36. Schreiber G. Knowledge engineering and management: the Common KADS methodology. Cambridge: MIT Press; 2000.
  37. Jaspers M, Smeulers M, Vermeulen H, Peute L. Effects of clinical decision-support systems on practitioner performance and patient outcomes: a synthesis of high-quality systematic review findings. J Am Med Inform Assoc. 2011;18(3):327−334. doi: 10.1136/amiajnl-2011-000094.
  38. Bryan C, Boren S. The use and effectiveness of electronic clinical decision support tools in the ambulatory /primary care setting: a systematic review of the literature. Inform Prim Care. 2008;16(2):79−91. doi: 10.14236/jhi.v16i2.679.
  39. Bright TJ, Wong A, Dhurjati R, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157(1):29−43. doi: 10.7326/0003-4819-157-1-201207030-00450.
  40. Moja L, Kwag KH, Lytras T, et al. Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. Am J Publ Health. 2014;104(12):e12−22. doi: 10.2105/AJPH.2014.302164.
  41. Kuperman G, Bobb A, Payne T, et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc. 2007;14(1):29−40. doi: 10.1197/jamia.M2170.
  42. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005;330(7494):765–772. doi: 10.1136/bmj.38398.500764.8F.
  43. Koutkias V, Bouaud J. Computerized clinical decision support: contributions from 2015. Yearb Med Inform. 2016;(1):170−177. doi: 10.15265/iy-2016-055.
  44. Carli-Ghabarou D, Seidling HM, Bonnabry P, Lovis C. A survey-based inventory of clinical decision support systems in computerised provider order entry in Swiss hospitals. Swiss Med Wkly. 2013;143:w13894. doi: 10.4414/smw.2013.13894.
  45. Cresswell KM, Lee L, Slee A, et al. Qualitative analysis of vendor discussions on the procurement of Computerised Physician Order Entry and Clinical Decision Support systems in hospitals. BMJ Open. 2015;5(10):e008313. doi: 10.1136/bmjopen-2015-008313.
  46. Field TS, Rochon P, Lee M, et al. Costs associated with developing and implementing a computerized clinical decision support system for medication dosing for patients with renal insufficiency in the long-term care setting. J Am Med Inform Assoc. 2008;15(4):466−472. doi: 10.1197/jamia.M2589.
  47. Boxwala AA, Rocha BH, Maviglia S, et al. A multi-layered framework for disseminating knowledge for computer-based decision support. J Am Med Inform Assoc. 2011;18 Suppl 1:i132−i139. doi: 10.1136/amiajnl-2011-000334.
  48. www.hl7.org [Internet]. Section 3: Clinical and Administrative Domains. Section 6: Rules and References. HL7 Version 3 Standard: GELLO, A Common Expression Language, Release 2 [cited 2017 Jul 20]. Available from: http://www.hl7.org/implement/standards/product_brief.cfm?product_id=5.
  49. Fox J, Gutenstein M, Khan O, et al. OpenClinical.net: a platform for creating and sharing knowledge and promoting best practice in healthcare. Computers in Industry. 2015;66:63−72. doi: 10.1016/j.compind.2014.10.001.
  50. Rodriguez-Loya S, Kawamoto K. Newer architectures for clinical decision support. In: Berner ES, editor. Clinical decision support systems. Theory and practice. 3rd ed. NewYork: Springer; 2016. pp. 87−97.
  51. Zhang YF, Gou L, Tian Y, et al. Design and development of a sharable clinical decision support system based on a semantic web service framework. J Med Syst. 2016;40(5):118. doi: 10.1007/s10916-016-0472-y.
  52. Esmaeilzadeh P, Sambasivan M, Kumar N, Nezakati H. Adoption of clinical decision support systems in a developing country: antecedents and outcomes of physician’s threat to perceived professional autonomy. Int J Med Informatics. 2015;84(8):548−560. doi: 10.1016/j.ijmedinf.2015.03.007.
  53. Назаренко Г.И., Клейменова Е.Б., Жуйков М.Ю., и др. Система автоматизации клинических руководств и аудита лечения // Врач и информационные технологии. ― 2014. ― №2 ― С. 23−32.
  54. Назаренко Г.И., Клейменова Е.Б., Константинова М.В., и др. Система автоматизации клинических руководств и аудита лечения (сакрал) в неврологии // Врач. ― 2014. ― №9 ― С. 84–87.
  55. Maviglia S, Sordo M. Practical approaches to knowledge management: focus on clinical decision support. MEDINFO 2015. Proceedings of the 15th World Congress on Health (Medical) Informatics; 2015 Aug 19–23; Sao Paulo, Brazil.
  56. qualityindicators.ahrq.gov [Internet]. Agency for Healthcare Research and Quality (AHRQ). Patient Safety Indicators Overview [cited 2017 May 30]. Available from: https://www.qualityindicators.ahrq.gov/Modules/psi_resources.aspx.
  57. ointcommission.org [Internet]. America’s Hospitals: Improving Quality and Safety. The Joint Commission’s Annual Report 2015 [cited 2016 Nov 5]. Available from: https://www.jointcommission.org/annualreport.aspx.
  58. Engebretsen E, Sandset TJ, Ødemark J. Expanding the knowledge translation metaphor. Health Res Policy Syst. 2017;15(1):19. doi: 10.1186/s12961-017-0184-x.

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