The effects of interoperable information technology networks on patient safety: a realist synthesis

Abstract

Background Interoperable networks connect information technology systems of different organisations, allowing professionals in one organisation to access patient data held in another one. Health policy-makers in many countries believe that they will improve the co-ordination of services and, hence, the quality of services and patient safety. To the best of our knowledge, there have not been any previous systematic reviews of the effects of these networks on patient safety. Objectives The aim of the study was to establish how, why and in what circumstances interoperable information technology networks improved patient safety, failed to do so or increased safety risks. The objectives of the study were to (1) identify programme theories and prioritise theories to review; (2) search systematically for evidence to test the theories; (3) undertake quality appraisal, and use included texts to support, refine or reject programme theories; (4) synthesise the findings; and (5) disseminate the findings to a range of audiences. Design Realist synthesis, including consultation with stakeholders in nominal groups and semistructured interviews. Settings and participants Following a stakeholder prioritisation process, several domains were reviewed: older people living at home requiring co-ordinated care, at-risk children living at home and medicines reconciliation services for any patients living at home. The effects of networks on services in health economies were also investigated. Intervention An interoperable network that linked at least two organisations, including a maximum of one hospital, in a city or region. Outcomes Increase, reduction or no change in patients’ risks, such as a change in the risk of taking an inappropriate medication. Results We did not find any detailed accounts of the ways in which interoperable networks are intended to work and improve patient safety. Theory fragments were identified and used to develop programme and mid-range theories. There is good evidence that there are problems with the co-ordination of services in each of the domains studied. The implicit hypothesis about interoperable networks is that they help to solve co-ordination problems, but evidence across the domains showed that professionals found interoperable networks difficult to use. There is insufficient evidence about the effectiveness of interoperable networks to allow us to establish how and why they affect patient safety. Limitations The lack of evidence about patient-specific measures of effectiveness meant that we were not able to determine ‘what works’, nor any variations in what works, when interoperable networks are deployed and used by health and social care professionals. Conclusions There is a dearth of evidence about the effects of interoperable networks on patient safety. It is not clear if the networks are associated with safer treatment and care, have no effects or increase clinical risks. Future work Possible future research includes primary studies of the effectiveness of interoperable networks, of economies of scope and scale and, more generally, on the value of information infrastructures. Study registration This study is registered as PROSPERO CRD42017073004. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 40. See the NIHR Journals Library website for further project information.

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What Works Where and How for Uptake and Impact of Artificial Intelligence in Pathology: Review of Theories for a Realist Evaluation (Preprint)

“…Such an approach is recommended for realist reviews [23] and more generally for understanding the theories that underpin complex interventions and the contexts in which they are implemented [22]. Named author searches are used in the theory elicitation stage of realist reviews as a means of gathering opinion pieces, remembering that we are looking for theories rather than empirical evidence [24]. Eric Topol was chosen as an "opinion leader," given his popular science book on the topic of AI in health care [25] and his input into England's strategy on digital health training and education, including around AI [26].…”