Andrius Budrionis
Norwegian Centre for e-health research, University Hospital of North Norway
Luis Marco-Ruiz
Norwegian Centre for e-health research, University Hospital of North Norway
Kassaye Yitbarek Yigzaw
Norwegian Centre for e-health research, University Hospital of North Norway
Johan Gustav Bellika
Norwegian Centre for e-health research, University Hospital of North Norway
Download articlePublished in: Proceedings from The 14th Scandinavian Conference on Health Informatics 2016, Gothenburg, Sweden, April 6-7 2016
Linköping Electronic Conference Proceedings 122:1, p. 1-5
Published: 2016-03-31
ISBN: 978-91-7685-776-2
ISSN: 1650-3686 (print), 1650-3740 (online)
The Learning Healthcare System paradigm promises fast progression of knowledge extracted from health data into clinical practice for improving health for populations, personalizing care and minimizing costs (the Triple Aim). It is, however, less clear how these ideas should be adopted to address the challenges of healthcare worldwide. While challenges are global, the healthcare systems and their organization are highly country-dependent, thus requiring a customized development approach and tailored impact measures. This paper sketches high-level ideas of demonstrating the potential benefits of the learning healthcare in North Norway. The implementation serves as a pilot project for measuring the impact of the paradigm on healthcare delivery, patient outcome and estimating the consumption of resources for a large-scale (national) deployment.
[1] Balas E, Boren S. Managing clinical knowledge for health care improvement. Yearb. Med. Inform. 2000 Patient-Centered Syst., Schattauer Verlagsgesellschaft mbH; 2000, p. 65–70.
[2] Morris ZS, Wooding S, Grant J. The answer is 17 years, what is the question: understanding time lags in translational research. J R Soc Med 2011;104:510–20.
doi: 10.1258/jrsm.2011.110180.
[3] Institute of Medicine (US) Roundtable on Evidence-Based Medicine. The Learning Healthcare System:
Workshop Summary. Washington (DC): National Academies Press (US); 2007.
[4] Berwick DM, Nolan TW, Whittington J. The Triple Aim: Care, Health, And Cost. Health Aff (Millwood) 2008;27:759–69. doi: 10.1377/hlthaff.27.3.759.
[5] Ohno-Machado L, Agha Z, Bell DS, Dahm L, Day ME, Doctor JN, et al. pSCANNER: patient-centered Scalable National Network for Effectiveness Research. J Am Med Inform Assoc JAMIA 2014;21:621–6. doi: 10.1136/amiajnl-2014-002751.
[6] Sledge GW, Hudis CA, Swain SM, Yu PM, Mann JT, Hauser RS, et al. ASCO’s approach to a learning health care system in oncology. J Oncol Pract Am Soc Clin Oncol 2013;9:145–8. doi: 10.1200/JOP.2013.000957.
[7] Deeny SR, Steventon A. Making sense of the shadows: priorities for creating a learning healthcare system based on routinely collected data. BMJ Qual Saf 2015;24:505–15. doi: 10.1136/bmjqs-2015-004278.
[8] Abernethy AP, Ahmad A, Zafar SY, Wheeler JL, Reese JB, Lyerly HK. Electronic patient-reported data capture as a foundation of rapid learning cancer care. Med Care 2010;48:S32–8. doi: 10.1097/MLR.0b013e3181db53a4.
[9] Berntsen G, Høyem A, Gammon D. Helsetjenesten fra pasientens ståsted. 2014.
[10] Marco-Ruiz L, Moner D, Maldonado JA, Kolstrup N, Bellika JG. Archetype-based data warehouse environment to enable the reuse of electronic health record data. Int J Med Inf 2015;84:702–14. doi: 10.1016/j.ijmedinf.2015.05.016.
[11] Bellika JG, Henriksen TS, Yigzaw KY. The Snow system - a decentralized medical data processing system. In: Llatas CF, García-Gómez JM, editors. Data Min. Clin. Med., Springer; 2014.
[12] Yigzaw KY, Bellika JG, Andersen A, Hartvigsen G, Fernandez-Llatas C. Towards privacy-preserving computing on distributed electronic health record data, ACM Press; 2013, p. 1–6. doi: 10.1145/2541534.2541593.
[13] Maldonado JA, Moner D, Boscá D, Fernández-Breis JT, Angulo C, Robles M. LinkEHR-Ed: a multi-reference model archetype editor based on formal semantics. Int J Med Inf 2009;78:559–70. doi: 10.1016/j.ijmedinf.2009.03.006.
[14] Archetype Query Language n.d. http://www.openehr.org/wiki/display/spec/Archetype+Query+Language+Description.
[15] Garde S, Chen R, Leslie H, Beale T, McNicoll I, Heard S. Archetype-based knowledge management for semantic interoperability of electronic health records. Stud Health Technol Inform 2009;150:1007–11.
[16] Helse-og omsorgsdepartementet. Digitale tjenester i helse- og omsorgssektoren. Regjeringen.no 2012. http://www.regjeringen.no/nb/dokumenter/meld-st-9-20122013/id708609/ (accessed January 30, 2015).
[17] Direktoratet for e-helse. Utredning av «Én innbygger – én journal». Direktoratet for e-helse; 2015.
[18] Damiani G, Pinnarelli L, Colosimo SC, Almiento R, Sicuro L, Galasso R, et al. The effectiveness of computerized clinical guidelines in the process of care: a systematic review. BMC Health Serv Res 2010;10:2. doi: 10.1186/1472-6963-10-2.
[19] Jeffery R, Iserman E, Haynes RB, CDSS Systematic Review Team. Can computerized clinical decision support systems improve diabetes management? A systematic review and meta-analysis. Diabet Med J Br Diabet Assoc 2013;30:739–45. doi: 10.1111/dme.12087.