Electronic prescribing (ePrescribing) systems allow health-care professionals to enter prescriptions and manage medicines using a computer. We set out to find out how these ePrescribing systems are chosen, set up and used in English hospitals. Given that these systems are designed to improve medication safety, we looked at whether or not these systems affected the number of prescribing errors made (mistakes such as ordering the wrong dose of medication). We also tried to see whether or not the systems were good value for money (or more cost-effective). Finally, we made recommendations to help hospitals choose, set up and use ePrescribing systems. We found that setting up ePrescribing systems was very difficult because there is a need to take into consideration how different pharmacists, nurses and doctors work, and the different work that needs to be carried out for different diseases and medical conditions. We recorded a link between the implementation of ePrescribing systems and a reduction in some high-risk prescribing errors in two out of three study sites. Given that the error reductions corresponded to the warnings triggered by the system, we concluded that the system is likely to have caused the error reduction. Prescribing errors may lead to adverse events that lead to death, impaired quality of life and longer hospital stays. The cost of an ePrescribing system increased in proportion to reduced errors, reaching £4.31 per patient per year for the site that experienced the greatest reduction in prescribing errors (i.e. site S). This estimate is based on assumptions in the model and how much a health service is willing to pay for a unit of health benefit. To help professionals choose, set up and use ePrescribing systems in the future, we produced an online ePrescribing Toolkit (www.eprescribingtoolkit.com/; accessed 21 December 2019) that, with support from NHS England, is becoming widely used internationally

Avery, Anthony

Bates, David

Chuter, Antony

Coleman, Jamie

Cresswell, Kathrin

Girling, Alan

King, Abby

Lee, Lisa

Lilford, Richard

McCloughan, Lucy

Morrison, Zoe

Mozaffar, Hajar

Pontefract, Sarah

Robertson, Ann

Salema, Nde-Eshimuni

Shah, Sonal

Sheikh, Aziz

Slee, Ann

Slight, Sarah

Watson, Neil

Watson, Samuel

Wiegel, Valeri

Williams, Robin

English

Background: There is a need to identify approaches to reduce medication errors. Interest has converged on ePrescribing systems that incorporate computerised provider order entry and clinical decision support functionality. Objectives: We sought to describe the procurement, implementation and adoption of basic and advanced ePrescribing systems; to estimate their effectiveness and cost-effectiveness; and to develop a toolkit for system integration into hospitals incorporating implications for practice from our research. Design: We undertook a theoretically informed, mixed-methods, context-rich, naturalistic evaluation. Setting: We undertook six longitudinal case studies in four hospitals (sites C, E, J and K) that did not have ePrescribing systems at the start of the programme (three of which went live and one that never went live) and two hospitals (sites A and D) with embedded systems. In the three hospitals that implemented systems, we conducted interviews pre implementation, shortly after roll-out and at 1 year post implementation. In the hospitals that had embedded systems, we conducted two rounds of interviews, 18 months apart. We undertook a three-round eDelphi exercise involving 20 experts to identify 80 clinically important prescribing errors, which were developed into the Investigate Medication Prescribing Accuracy for Critical error Types (IMPACT) tool. We elicited the cost of an ePrescribing system at one (non-study) site and compared this with the calculated ‘headroom’ (the upper limit that the decision-maker should pay) for the systems (sites J, K and S) for which effectiveness estimates were available. We organised four national conferences and five expert round-table discussions to contextualise and disseminate our findings. Intervention: The implementation of ePrescribing systems with either computerised provider order entry or clinical decision support functionality. Main outcome measures: Error rates were calculated using the IMPACT tool, with changes over time represented as ratios of error rates (as a proportion of opportunities for errors) using Poisson regression analyses. Results: We conducted 242 interviews and 32.5 hours of observations and collected 55 documents across six case studies. Implementation was difficult, particularly in relation to integration and interfacing between systems. Much of the clinical decision support functionality in embedded sites remained switched off because of concerns about over alerting. Getting systems operational meant that little attention was devoted to system optimisation or secondary uses of data. The prescriptions of 1244 patients were audited pre computerised provider order entry and 1178 post computerised provider order entry implementation of system A at sites J and K, and system B at site S. A total of 21,138 opportunities for error were identified from 28,526 prescriptions. Across the three sites, for those prescriptions for which opportunities for error were identified, the error rate was found to reduce significantly post computerised provider order entry implementation, from 5.0% to 4.0% (p < 0.001). Post implementation, the overall proportion of errors (per opportunity) decreased significantly in sites J and S, but remained similar in site K, as follows: 4.3% to 2.8%, 7.4% to 4.4% and 4.0% to 4.4%, respectively. Clinical decision support implementation by error type was found to differ significantly between sites, ranging from 0% to 88% across clinical contraindication, dose/frequency, drug interactions and other error types (p < 0.001). Overall, 43 out of 78 (55%) of the errors had some degree of clinical decision support implemented in at least one of the hospitals. For the site in which no improvement was detected in prescribing errors (i.e. site K), the ePrescribing system represented a cost to the service for no countervailing benefit. Cost-effectiveness rose in proportion to reductions in error rates observed in the other sites (i.e. sites J and S). When a threshold value of £20,000 was used to define the opportunity cost, the system would need to cost less than £4.31 per patient per year, even in site S, where effectiveness was greatest. We produced an ePrescribing toolkit (now recommended for use by NHS England) that spans the ePrescribing life cycle from conception to system optimisation. Limitations: Implementation delays meant that we were unable to employ the planned stepped-wedge design and that the assessment of longer-term consequences of ePrescribing systems was impaired. We planned to identify the complexity of ePrescribing implementation in a number of contrasting environments, but the small number of sites means that we have to infer findings from this programme with considerable care. The lack of transparency regarding system costs is a limitation of our method. As with all health economic analyses, our analysis is subject to modelling assumptions. The research was undertaken in a modest number of early adopters, concentrated on high-risk prescribing errors and may not be generalisable to other hospitals. Conclusions: The implementation of ePrescribing systems was challenging. However, when fully implemented the ePrescribing systems were associated with a reduction in clinically important prescribing errors and our model suggests that such an effect is likely to be more cost-effective when clinical decision support is available. Careful system configuration considering clinical processes and workflows is important to achieving these potential benefits and, therefore, our findings may not be generalisable to all system implementations. Future work: Formative and summative evaluations of efforts will be central to promote learning across settings. Other priorities emerging from this work include the possibility of learning from international experiences and the commercial sector

Repository@Nottingham

Electronic prescribing systems in hospitals to improve medication safety: a multimethods research programme

Open Access Institutional Repository at Robert Gordon University

Electronic prescribing systems in hospitals to improve medication safety: a multimethods research programme.

Background: There is a need to identify approaches to reduce medication errors. Interest has converged on ePrescribing systems that incorporate computerised provider order entry and clinical decision support functionality. Objectives: We sought to describe the procurement, implementation and adoption of basic and advanced ePrescribing systems; to estimate their effectiveness and cost-effectiveness; and to develop a toolkit for system integration into hospitals incorporating implications for practice from our research. Design: We undertook a theoretically informed, mixed-methods, context-rich, naturalistic evaluation. Setting: We undertook six longitudinal case studies in four hospitals (sites C, E, J and K) that did not have ePrescribing systems at the start of the programme (three of which went live and one that never went live) and two hospitals (sites A and D) with embedded systems. In the three hospitals that implemented systems, we conducted interviews pre implementation, shortly after roll-out and at 1 year post implementation. In the hospitals that had embedded systems, we conducted two rounds of interviews, 18 months apart. We undertook a three-round eDelphi exercise involving 20 experts to identify 80 clinically important prescribing errors, which were developed into the Investigate Medication Prescribing Accuracy for Critical error Types (IMPACT) tool. We elicited the cost of an ePrescribing system at one (non-study) site and compared this with the calculated ‘headroom’ (the upper limit that the decision-maker should pay) for the systems (sites J, K and S) for which effectiveness estimates were available. We organised four national conferences and five expert round-table discussions to contextualise and disseminate our findings. Intervention: The implementation of ePrescribing systems with either computerised provider order entry or clinical decision support functionality. Main outcome measures: Error rates were calculated using the IMPACT tool, with changes over time represented as ratios of error rates (as a proportion of opportunities for errors) using Poisson regression analyses. Results: We conducted 242 interviews and 32.5 hours of observations and collected 55 documents across six case studies. Implementation was difficult, particularly in relation to integration and interfacing between systems. Much of the clinical decision support functionality in embedded sites remained switched off because of concerns about over alerting. Getting systems operational meant that little attention was devoted to system optimisation or secondary uses of data. The prescriptions of 1244 patients were audited pre computerised provider order entry and 1178 post computerised provider order entry implementation of system A at sites J and K, and system B at site S. A total of 21,138 opportunities for error were identified from 28,526 prescriptions. Across the three sites, for those prescriptions for which opportunities for error were identified, the error rate was found to reduce significantly post computerised provider order entry implementation, from 5.0% to 4.0% (p &lt; 0.001). Post implementation, the overall proportion of errors (per opportunity) decreased significantly in sites J and S, but remained similar in site K, as follows: 4.3% to 2.8%, 7.4% to 4.4% and 4.0% to 4.4%, respectively. Clinical decision support implementation by error type was found to differ significantly between sites, ranging from 0% to 88% across clinical contraindication, dose/frequency, drug interactions and other error types (p &lt; 0.001). Overall, 43 out of 78 (55%) of the errors had some degree of clinical decision support implemented in at least one of the hospitals. For the site in which no improvement was detected in prescribing errors (i.e. site K), the ePrescribing system represented a cost to the service for no countervailing benefit. Cost-effectiveness rose in proportion to reductions in error rates observed in the other sites (i.e. sites J and S). When a threshold value of £20,000 was used to define the opportunity cost, the system would need to cost less than £4.31 per patient per year, even in site S, where effectiveness was greatest. We produced an ePrescribing toolkit (now recommended for use by NHS England) that spans the ePrescribing life cycle from conception to system optimisation. Limitations: Implementation delays meant that we were unable to employ the planned stepped-wedge design and that the assessment of longer-term consequences of ePrescribing systems was impaired. We planned to identify the complexity of ePrescribing implementation in a number of contrasting environments, but the small number of sites means that we have to infer findings from this programme with considerable care. The lack of transparency regarding system costs is a limitation of our method. As with all health economic analyses, our analysis is subject to modelling assumptions. The research was undertaken in a modest number of early adopters, concentrated on high-risk prescribing errors and may not be generalisable to other hospitals. Conclusions: The implementation of ePrescribing systems was challenging. However, when fully implemented the ePrescribing systems were associated with a reduction in clinically important prescribing errors and our model suggests that such an effect is likely to be more cost-effective when clinical decision support is available. Careful system configuration considering clinical processes and workflows is important to achieving these potential benefits and, therefore, our findings may not be generalisable to all system implementations. Future work: Formative and summative evaluations of efforts will be central to promote learning across settings. Other priorities emerging from this work include the possibility of learning from international experiences and the commercial sector.</p

Salema, Nde Eshimuni

Edinburgh Research Explorer

Electronic prescribing systems in hospitals to improve medication safety:A multimethods research programme

https://nottingham-repository.worktribe.com/file/12036153/1/Electronic%20prescribing%20systems%20in%20hospitals%20to%20improve%20medication%20safety%3A%20a%20multimethods%20research%20programme

Electronic prescribing systems in hospitals to improve medication safety: a multimethods research programme.

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