Optimising electronic prescribing in hospitals: a scoping review protocol

Introduction Electronic prescribing (ePrescribing) systems can improve the quality of prescribing decisions and substantially reduce the risk of serious medication errors in hospitals. However, realising these benefits depends on ensuring that relevant sociotechnical considerations are addressed. Optimising ePrescribing systems is essential to maximise the associated benefits and minimise the accompanying risks of these large-scale and expensive health informatics infrastructures. Methods We will undertake a systematic scoping review of the literature to identify strategies to achieve optimisation of ePrescribing systems. We will search Medline, Embase and CINAHL for the period 1 January 2010 to 1 June 2019 and the grey literature by using Google Scholar. Independent reviewers will screen the results using predefined inclusion and exclusion criteria and will extract data for narrative and thematic synthesis. Discussion This work will be published in a peer-reviewed journal and we will ensure that the findings are both accessible and interpretable to the public, academics, policymakers and National Health Service leaders.

[1]  Zachary Munn,et al.  Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach , 2018, BMC Medical Research Methodology.

[2]  A. Sheikh,et al.  Impact of a commercial order entry system on prescribing errors amenable to computerised decision support in the hospital setting: a prospective pre-post study , 2018, BMJ Quality & Safety.

[3]  J. Sim,et al.  Saturation in qualitative research: exploring its conceptualization and operationalization , 2017, Quality & Quantity.

[4]  David C. Classen,et al.  National trends in safety performance of electronic health record systems in children’s hospitals , 2017, J. Am. Medical Informatics Assoc..

[5]  David W. Bates,et al.  Ten key considerations for the successful optimization of large-scale health information technology , 2017, J. Am. Medical Informatics Assoc..

[6]  L. Given 100 Questions (and Answers) About Qualitative Research , 2016 .

[7]  Sarah P. Slight,et al.  Product Diversity and Spectrum of Choice in Hospital ePrescribing Systems in England , 2014, PloS one.

[8]  A. Sheikh,et al.  A toolkit to support the implementation of electronic prescribing systems into UK hospitals: preliminary recommendations , 2014, Journal of the Royal Society of Medicine.

[9]  C. Anandan,et al.  The Impact of eHealth on the Quality and Safety of Health Care: A Systematic Overview , 2011, PLoS medicine.

[10]  Robin Williams,et al.  e-Infrastructures: How Do We Know and Understand Them? Strategic Ethnography and the Biography of Artefacts , 2010, Computer Supported Cooperative Work (CSCW).

[11]  D. Levac,et al.  Scoping studies: advancing the methodology , 2010, Implementation science : IS.

[12]  Johanna I Westbrook,et al.  Review Paper: Does Computerized Provider Order Entry Reduce Prescribing Errors for Hospital Inpatients? A Systematic Review , 2009, J. Am. Medical Informatics Assoc..

[13]  Terry T. Kidd,et al.  Handbook of Research on Technology Project Management, Planning, and Operations , 2009 .

[14]  Aziz Sheikh,et al.  Information technology (IT) system users must be allowed to decide on the future direction of major national IT initiatives. But the task of redistributing power equally amongst stakeholders will not be an easy one. , 2009, Informatics in primary care.

[15]  P. Shekelle,et al.  Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care , 2006, Annals of Internal Medicine.

[16]  H. Arksey,et al.  Scoping studies: towards a methodological framework , 2005 .

[17]  D. Bates,et al.  Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. , 1998, JAMA.

[18]  William W. Stead,et al.  Review: Computer-based Physician Order Entry: The State of the Art , 1994, J. Am. Medical Informatics Assoc..