Supporting Policy Definition in the e-Health Domain - A QCA based Method

eHealth is broadly considered as a promising strategy to improve the economic sustainability and quality of the healthcare service provision in Europe. Nevertheless, despite the enthusiastic declarations of eHealth potential, the adoption of IT in health care has progressed very slowly. A critical factor, not deeply addressed in literature, is related to the process of prioritization of the eHealth solution to adopt, in presence of financial constrains, external and internal pressure from a wide range of heterogeneous stakeholders, and conflicting information on different technological solutions. In this paper we introduce a method supporting policy definition in the eHealth domain. This method is based on a qualitative comparative analysis (QCA) of best practices and previous experiences performed through the lens of an analytic framework whose dimensions and categories are well situated in the eHealth context. This method could support policy-makers in the identification of the properties and characteristics of innovative projects at European level and to analyze the gap between the international scenario and the local context in order to understand trends and dynamics of development, to evaluate the best opportunities for innovation and, therefore, to assign priorities for the next investments by respecting the constraints of available resources.

[1]  Charles C. Ragin,et al.  Set Relations in Social Research: Evaluating Their Consistency and Coverage , 2006, Political Analysis.

[2]  Ritu Agarwal,et al.  Adoption of Electronic Health Records in the Presence of Privacy Concerns: The Elaboration Likelihood Model and Individual Persuasion , 2009, MIS Q..

[3]  Claudia Pagliari,et al.  Potential of electronic personal health records , 2007, BMJ : British Medical Journal.

[4]  J. Kahan,et al.  What Is eHealth (4): A Scoping Exercise to Map the Field , 2005, Journal of medical Internet research.

[5]  Danny Miller,et al.  Environmental Fit Versus Internal Fit , 1992 .

[6]  Steven R. Simon,et al.  Correlates of Electronic Health Record Adoption in Office Practices: A Statewide Survey , 2006, AMIA.

[7]  J. Mitchell Increasing the cost-effectiveness of telemedicine by embracing e-health , 2000, Journal of telemedicine and telecare.

[8]  D. Bates Physicians and ambulatory electronic health records. , 2005, Health affairs.

[9]  Graham Wright,et al.  A fatal case of bupropion (Zyban) hepatotoxicity with autoimmune features: Case report , 2005, Journal of medical case reports.

[10]  M L Campbell,et al.  Caring for people. , 1979, The Australian nurses' journal. Royal Australian Nursing Federation.

[11]  Gary Yohe Roadmap for adaptation , 2007 .

[12]  T. Ferris,et al.  Options for slowing the growth of health care costs. , 2008, The New England journal of medicine.

[13]  Hype Cycle for Healthcare Provider Applications and Systems , 2010 .

[14]  Peer C. Fiss A set-theoretic approach to organizational configurations , 2007 .

[15]  Steven R. Simon,et al.  Correlates of electronic health record adoption in office practices: a statewide survey. , 2007, Journal of the American Medical Informatics Association : JAMIA.

[16]  Guohua Bai,et al.  Guide to REgional Good Practice eHealth , 2007 .

[17]  Michael Rigby,et al.  Essential prerequisites to the safe and effective widespread roll-out of e-working in healthcare , 2006, Int. J. Medical Informatics.