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The implementation of the National Health Service's Care Record Service (NHS CRS) is the most ambitious information technology innovation ever undertaken in healthcare. This electronic health record system represents the key component of the National Programme for Information Technology. Its implementation is however proving extremely challenging. Building on a recent systematic review of the eHealth literature, we critically reflect on factors that can facilitate the implementation of the NHS CRS and suggest recommendations for a way forward to facilitate implementation efforts. [ABSTRACT FROM AUTHOR]

Background: Although the collection of patient ethnicity data is a requirement of publicly funded healthcare providers in the UK, recording of ethnicity is sub-optimal for reasons that remain poorly understood., Aims and Objectives: We sought to understand enablers and barriers to the collection and utilisation of ethnicity data within electronic health records, how these practices have developed and what benefit this information provides to different stakeholder groups., Methods: We undertook an in-depth, qualitative case study drawing on interviews and documents obtained from participants working as academics, managers and administrators within the UK., Results: Information regarding patient ethnicity was collected and coded as administrative patient data, and/or in narrative form within clinical records. We identified disparities in the classification of ethnicity, approaches to coding and levels of completeness due to differing local, regional and national policies and processes. Most participants could not identify any clinical value of ethnicity information and many did not know if and when data were shared between services or used to support quality of care and research., Conclusions: Findings highlighted substantial variations in data classification, and practical challenges in data collection and usage that undermine the integrity of data collected. Future work needs to focus on explaining the uses of these data to frontline clinicians, identifying resources that can support busy professionals to collect standardised data and then, once collected, maximising the utility of these data.

Purpose: Computerised decision support systems are designed to support clinicians in making decisions and thereby enhance the quality and safety of care. We aimed to undertake an interpretative review of the empirical evidence on computerised decision support systems, their contexts of use, and summarise evidence on the effectiveness of these tools and insights into how these can be successfully implemented and adopted., Methods: We systematically searched the empirical literature to identify systematic literature reviews on computerised decision support applications and their impact on the quality and safety of healthcare delivery over a 13-year period (1997-2010). The databases searched included: MEDLINE, EMBASE, The Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, The Cochrane Central Register of Controlled Trials, The Cochrane Methodology Register, The Health Technology Assessment Database, and The National Health Service (NHS) Economic Evaluation Database. To be eligible for inclusion, systematic reviews needed to address computerised decision support systems, and at least one of the following: impact on safety; quality; or organisational, implementation or adoption considerations., Results: Our searches yielded 121 systematic reviews relating to eHealth, of which we identified 41 as investigating computerised decision support systems. These indicated that, whilst there was a lack of investigating potential risks, such tools can result in improvements in practitioner performance in the promotion of preventive care and guideline adherence, particularly if specific information is available in real time and systems are effectively integrated into clinical workflows. However, the evidence regarding impact on patient outcomes was less clear-cut with reviews finding either no, inconsistent or modest benefits., Conclusions: Whilst the potential of clinical decision support systems in improving, in particular, practitioner performance is considerable, such technology may also introduce new risks resulting not only from technical challenges (such as data inaccuracies) but also from disruption of clinical workflows. Moving forward, there is a need for system development, procurement and implementation to be characterised by a user 'pull' and then tailor systems to the needs of users.

Background: The absence of meaningful end user engagement has repeatedly been highlighted as a key factor contributing to 'failed' implementations of electronic health records (EHRs), but achieving this is particularly challenging in the context of national scale initiatives. In 2002, the National Health Service (NHS) embarked on a so-called 'top-down' national implementation strategy aimed at introducing commercial, centrally procured, EHRs into hospitals throughout England., Objective: We aimed to examine approaches to, and experiences of, user engagement in the context of a large-scale EHR implementation across purposefully selected hospital care providers implementing early versions of nationally procured software., Methods: We conducted a qualitative, case-study based, socio-technically informed, longitudinal investigation, purposefully sampling and collecting data from four hospitals. Our data comprised a total of 123 semi-structured interviews with users and managers, 15 interviews with additional stakeholders, 43 hours of non-participant observations of meetings and system use, and relevant organisation-specific documents from each case study site. Analysis was thematic, building on an existing model of user engagement that was originally developed in the context of studying the implementation of relatively simple technologies in commercial settings. NVivo8 software was used to facilitate coding., Results: Despite an enduring commitment to the vision of shared EHRs and an appreciation of their potential benefits, meaningful end user engagement was never achieved. Hospital staff were not consulted in systems choice, leading to frustration; they were then further alienated by the implementation of systems that they perceived as inadequately customised. Various efforts to achieve local engagement were attempted, but these were in effect risk mitigation strategies. We found the role of clinical champions to be important in these engagement efforts, but progress was hampered by the hierarchical structures within healthcare teams. As a result, engagement efforts focused mainly on clinical staff with inadequate consideration of management and administrative staff., Conclusions: This work has allowed us to further develop an existing model of user engagement from the commercial sector and adapt it to inform user engagement in the context of large-scale eHealth implementations. By identifying key points of possible engagement, disengagement and re-engagement, this model will we hope both help those planning similar large-scale EHR implementation efforts and act as a much needed catalyst to further research in this neglected field of enquiry.