Collective Expectations—Individual Action Implementing Electronic Booking Systems in Norwegian Health Care

Department of Telemedicine, University of Tromsø, N-9038 Tromsø, Norway.
International Journal of Medical Informatics (Impact Factor: 2). 07/2007; 76 Suppl 1:S104-12. DOI: 10.1016/j.ijmedinf.2006.05.029
Source: PubMed


We draw on an ongoing study of an electronic booking project at the University Hospital North Norway where general practitioners are given the opportunity to book appointments at the hospital for their patients. Electronic booking offers well-defined and standardised services as well as standardised procedures for preparing the patient for the appointment at the hospital. We examine how the standards inscribed in the booking system shape medical work and how they bring to the surface a social dilemma between collective and individual interests in how the key actors reflect on the consequences of the system. We combine two social theories, namely Actor Network Theory and the theory of collective action. As a conclusion, we argue that simple and well-defined cases of patients' problems and willingness among the general practitioners to undertake work traditionally conducted at the hospital are conditions for making electronic booking successful. However, when the patients' problems are unclear the booking system needs to be combined with traditional referrals. We also point to how the general practitioners' attitude towards the system is time-dependent. Their initial positive attitude towards the potential public goods produced by booking transforms into putting more weight on the individual interests.

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    • "Prior studies have conceptualized the healthcare system as a network of actors, each of which has specialized knowledge in support of treatment plan decisions (e.g., Ellingsen and Obstfelder, 2007; Hanseth et al., 2006; McGrath, 2002; Ramiller, 2007; Timpka et al., 2007). Specialization is necessary because individual actors are unable to acquire, store and process information in all areas of knowledge (Grant, 1996). "
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    ABSTRACT: Healthcare reform has emphasized coordinated and integrated care — patient-centered care — for a decade. To that end, policymakers have invested in integration of healthcare providers’ information flows. Research to date has studied healthcare actors’ information needs but overlooked communicative exchanges among all participants in coordinating treatment plan decisions. Consequently, while medical literature asserts that patients should depend on information from healthcare providers to enable patients’ participation in treatment plan decisions, the assertion has not been tested. To ameliorate this oversight, we conducted an empirical study of a patient-centered healthcare environment. Our study draws on dependency network diagramming (DND) and social network analysis (SNA) to elucidate the nature and structure of actors’ communications in support of their information dependencies. The findings illustrate that although patients are well supported by personal communications with healthcare providers, they are disenfranchised from the integrated information technology within and between healthcare providers and its potential to support patients’ participation in coordinated “patient-centered care” decisions. Furthermore, knowledge asymmetry between patients and healthcare providers should be considered in the selection and tailoring of healthcare information systems (IS).
    Proceedings of the 15th Americas Conference on Information Systems, AMCIS 2009, San Francisco, California, USA, August 6-9, 2009; 01/2009
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    ABSTRACT: Background: The extensive and rapidly expanding research literature on electronic patient records (EPRs) presents challenges to systematic reviewers. This literature is heterogeneous and at times conflicting, not least because it covers multiple research traditions with different underlying philosophical assumptions and methodological approaches. Aim: To map, interpret and critique the range of concepts, theories, methods and empirical findings on EPRs, with a particular emphasis on the implementation and use of EPR systems. Method: Using the meta-narrative method of systematic review, and applying search strategies that took us beyond the Medline-indexed literature, we identified over 500 full-text sources. We used ‘conflicting’ findings to address higher-order questions about how the EPR and its implementation were differently conceptualised and studied by different communities of researchers. Main findings: Our final synthesis included 24 previous systematic reviews and 94 additional primary studies, most of the latter from outside the biomedical literature. A number of tensions were evident, particularly in relation to: [1] the EPR (‘container’ or ‘itinerary’); [2] the EPR user (‘information-processer’ or ‘member of socio-technical network’); [3] organizational context (‘the setting within which the EPR is implemented’ or ‘the EPR-in-use’); [4] clinical work (‘decision-making’ or ‘situated practice’); [5] the process of change (‘the logic of determinism’ or ‘the logic of opposition’); [6] implementation success (‘objectively defined’ or ‘socially negotiated’); and [7] complexity and scale (‘the bigger the better’ or ‘small is beautiful’). Findings suggest that integration of EPRs will always require human work to re-contextualize knowledge for different uses; that whilst secondary work (audit, research, billing) may be made more efficient by the EPR, primary clinical work may be made less efficient; that paper, far from being technologically obsolete, currently offers greater ecological flexibility than most forms of electronic record; and that smaller systems may sometimes be more efficient and effective than larger ones. Conclusions: The tensions and paradoxes revealed in this study extend and challenge previous reviews and suggest that the evidence base for some EPR programs is more limited than is often assumed. We offer this paper as a preliminary contribution to a much-needed debate on this evidence and its implications, and suggest avenues for new research.

  • International Journal of Medical Informatics 07/2007; 76 Suppl 1:S1-3. DOI:10.1016/S1386-5056(07)00078-0 · 2.00 Impact Factor
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