Antony Chuter

Background: Hazardous prescribing is an important and expensive preventable cause of patient harm, which can be identified using electronic healthcare records. In our Programme Grant we investigated the large-scale roll-out of a type of clinical decision support called OptimiseRx ^® (First Databank, Hearst Health, Exeter, United Kingdom) (which had not been independently evaluated previously) and two large-scale roll-outs of pharmacist-led IT-based intervention (an intervention that had been shown to reduce hazardous prescribing in a cluster randomised trial). Objectives: To estimate harm and economic impact of specific hazardous prescribing events. To investigate whether a clinical decision support intervention (OptimiseRx) was associated with reduction in hazardous prescribing. To investigate whether a pharmacist-led IT-based intervention was associated with reduction in hazardous prescribing. To undertake economic and process evaluations of both interventions. Design and methods: The harm and economic impact of hazardous prescribing events were investigated using data from published sources to generate estimates of patient outcomes and cost associated with 11 prescribing safety indicators. An incomplete (not randomised) stepped-wedge design study with control groups was used to investigate the effectiveness of OptimiseRx (409 general practices). Incremental cost-effectiveness ratios were generated for OptimiseRx compared with standard care (cost per hazardous prescribing event prevented), subgroup analysis: cost per quality-adjusted life-year. Incomplete stepped-wedge design studies [East Midlands study (343 and 115 general practices); whole of England study (725 and 179 general practices)] investigated the effectiveness of pharmacist-led IT-based intervention. Incremental cost-effectiveness ratios were generated for pharmacist-led IT-based intervention compared with standard care (cost per hazardous prescribing event prevented, cost per quality-adjusted life-year). Data from interviews, focus groups, a survey and stakeholder events were analysed qualitatively to identify factors influencing the sustained implementation and operation of OptimiseRx or pharmacist-led IT-based intervention. Setting and participants: The interventions took place in general practices in England. The process evaluation involved clinicians, patients and other stakeholders in England. Interventions: Clinical decision support intervention (OptimiseRx). Pharmacist-led IT-based intervention. Main outcome measures: Changes in hazardous prescribing rates. Cost per quality-adjusted life-year. Data sources: Clinical Practice Research Datalink. ResearchOne. General practice clinical records. Process evaluation with clinicians, patients and other stakeholders. Results: All the hazardous prescribing events studied were associated with loss of quality-adjusted life-years. The costliest for the National Health Service were prescriptions of antipsychotics to patients with dementia (£1168 per patient) and anticoagulants in combination with nonsteroidal anti-inflammatory drugs (£1020 per patient). Of 409 practices included in the clinical decision support study, 227 (56%) were intervention practices. Deployment of OptimiseRx was associated with a 10% reduction in exposure to hazardous prescribing after 2 years (odds ratio 0.90, 95% confidence interval 0.88 to 0.92). OptimiseRx costs £14–48 per hazardous prescribing event prevented, depending on time point and patient volume. Based on two indicators only, OptimiseRx costs £236 per quality-adjusted life-year gained at 6 months and becomes dominant (quality-adjusted life-year increasing; cost saving) at 24 months. Of 343 general practices included in the East Midlands pharmacist-led IT-based intervention evaluation, we completed further data extraction for 115 (33.5%) of these. Pharmacist-led IT-based intervention was associated with a decrease in hazardous prescribing of 18% (adjusted odds ratio 0.82, 95% confidence interval 0.78 to 0.86) at 6 months, and 22% (adjusted odds ratio 0.78, 95% confidence interval 0.73 to 0.84) at 24 months post intervention. Pharmacist-led IT-based intervention generates approximately 0.15 quality-adjusted life-years per practice extra compared with no intervention. Expected savings do not fully offset delivery costs, so pharmacist-led IT-based intervention costs just over £1000 per practice. Pharmacist-led IT-based intervention was estimated to be £7449. With 12- and 24-month intervention effects, health gains rise to over 0.2 quality-adjusted life-years and net expenditure falls to < £800 per practice; around £3500 per quality-adjusted life-year gained. Of 725 practices that implemented pharmacist-led IT-based intervention nationally, we had usable data for only 179 because of the COVID-19 pandemic. For these practices, pharmacist-led IT-based intervention was associated with a reduction in hazardous prescribing of 11% (adjusted odds ratio 0.89, 95% confidence interval 0.86 to 0.92) at 6 months post intervention. The process evaluation studies demonstrated the importance of collaboration and system-level support for the clinical decision support and pharmacist-led IT-based interventions. Limitations: The main limitation was that we could not robustly evaluate the impact of OptimiseRx on serious harm outcomes and the analysis was limited for pharmacist-led IT-based intervention because of the COVID-19 pandemic. Future work: Further research is needed to determine whether interventions that reduce hazardous prescribing, also reduce serious harm to patients. Conclusions: Large-scale implementation of OptimiseRx was associated with reduced hazardous prescribing, at less than £50 per hazardous prescribing event avoided. Large-scale implementation of pharmacist-led IT-based intervention was also associated with reduced hazardous prescribing with a cost per quality-adjusted life-year of £7449. It should be noted, however, that these were quasi-experimental studies using observational data and so the findings may have been affected by unknown confounding. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Programme Grants for Applied Research programme (NIHR award ref: RP-PG-1214-20012) and is published in full in Programme Grants for Applied Research ; Vol. 14, No. 15. See the NIHR Funding and Awards website for further award information.

Aims: To develop, assess the feasibility and test the effectiveness and cost-effectiveness of a multifaceted ePrescribing-based Antimicrobial Stewardship intervention to safely reduce inappropriate antibiotic use in adult medical inpatient settings. Methods: We undertook a mixed-methods programme of work organised into four interlinked work packages: Work package 1: (a) planning, developing and optimising all elements of ePrescribing-based Antimicrobial Stewardship; and (b) carrying out qualitative, feasibility and process studies of ePrescribing-based Antimicrobial Stewardship implementation. Work package 2: agreeing secondary outcome measures through an expert consensus building workshop, developing the methods to collect outcome data and establishing the feasibility of evaluating ePrescribing-based Antimicrobial Stewardship through a hybrid cluster-randomised stepped-wedge trial. Work package 3: evaluating the effectiveness of ePrescribing-based Antimicrobial Stewardship in achieving our coprimary outcomes of reducing antibiotic consumption without any adverse impact on 30-day mortality through piloting and undertaking a formal evaluation. Work package 4: estimating the cost-effectiveness of ePrescribing-based Antimicrobial Stewardship, including cost-minimisation and sensitivity analyses through evidence synthesis and expert engagement. Our research (which started on 1 January 2019) was majorly disrupted by the COVID-19 pandemic, with members of the team being redeployed to clinical and government advisory roles, and limited opportunities to undertake hospital fieldwork compounded by strikes. These delays resulted in our trial plans being pushed back by ≈ 3 years, by which time it was no longer possible to recruit sufficient numbers of hospitals into the planned definitive trial. Following discussion with the funders, we aborted plans to run the pilot and definitive trials, replacing this with qualitative scoping work to understand the ways in which trusts had innovated in the intervening period to promote antimicrobial stewardship (work package 5). Results: We developed the ePrescribing-based Antimicrobial Stewardship intervention, comprising technical, educational and behavioural components and were able to agree secondary outcome measures and the cost-effectiveness model. The feasibility trial was undertaken in two hospitals in one trust, studying 24,884 antibiotic orders on 1958 admissions. This demonstrated that several aspects of the intervention were deliverable and that we were able to extract data on 20/43 outcome measures. Modelling of the coprimary outcomes, total antibiotic defined daily dose per admission, was feasible and enabled its variability to be estimated to support further research planning. There was, however, limited engagement of clinical staff with the training element of the intervention, which was initially only voluntary. Given the severe delays, many trusts had begun implementing their own approaches to deal with growing challenge of antimicrobial stewardship. As such, we were unable to find sufficient naive sites to progress the trial. Our additional qualitative scoping work identified the myriad ways in which trusts were attempting to respond to antimicrobial stewardship. These included order sets and order protocols, default durations, alerts for review, incorporation of guidelines, and audit and feedback functionality. Limitations: We identify five key limitations: (1) the COVID-19 pandemic caused major delays, and non-COVID research activities had a lower priority than front-line clinical work and COVID-related research. The timescale for the development work is, therefore, unlikely to be representative of the time it should take to develop an intervention of this scope outside of pandemic contexts. (2) Although there was considerable stakeholder input into the development of ePrescribing-based Antimicrobial Stewardship, this did not include the entire potential user population. Nurses were under-represented. Although not directly involved in prescribing, more engagement with nurses would have been useful because they were involved in medication management workflows. (3) Undertaking the work in one trust limits generalisability, although inclusion of several ward types should help ensure that our findings related to a breadth of clinical contexts. (4) Implementation of ePrescribing-based Antimicrobial Stewardship within Cerner Millennium (North Kansas City, Missouri, USA) means feasibility in other systems still needs to be established. (5) The add-on study of antimicrobial stewardship practices included views of antimicrobial stewardship pharmacists and consultant microbiologists but did not include all hospitals nor ward prescribers. Nonetheless, this study provided many valuable insights into approaches, including the need for development of evidence for different practices. Conclusions: We developed ePrescribing-based Antimicrobial Stewardship and conducted a feasibility trial of this in inpatient settings. This development and feasibility work was, however, undertaken during challenging circumstances resulting from a combination of the COVID-19 pandemic and National Health Service pressures, making it difficult for clinicians to fully engage. Delays with our work resulted in provisionally recruited trusts innovating in relation to antimicrobial stewardship such that it was no longer possible to deliver the planned follow-on pilot and definitive trials. In summary, ePrescribing-based Antimicrobial Stewardship is, in its present format, not suitable for use in National Health Service hospitals. Future work: Hospitals are currently pursuing a range of approaches in an attempt to promote antimicrobial stewardship. There is a need to develop a typology of these approaches and establish the strength of the underpinning evidence using naturalistic designs. Trial registration: This trial is registered as ISRCTN13429325. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Programme Grants for Applied Research Programme (NIHR award ref: RP-PG-0617-20009) and is published in full in Programme Grants for Applied Research ; Vol. 14, No. 12. See the NIHR Funding and Awards website for further award information.

Objectives Most medication errors occur in primary and long-term care, and a wide range of medication safety interventions have been implemented, but these are often expensive, with little evidence around cost-effectiveness. We report a systematic review of economic evaluations of these interventions within primary and long-term healthcare settings. Methods A comprehensive search was conducted in databases (Medline, Embase, Econlit and PsycINFO) for full economic evaluations of primary care interventions targeting all errors in the medication use process (January 2004 to September 2025). Methodological and reporting qualities were assessed using standard tools. Results From 8523 records, 44 studies evaluating interventions in general/family practice (22), community pharmacy (11) and nursing/care/residential homes (11) met the inclusion criteria, 24 of which were either pharmacy led (19) or multidisciplinary medication reviews (5). All but one study looked at prescribing or monitoring interventions only. A total of 12 studies included all patients, with 24 focusing on older adults (> 65 years) and 3 focusing on condition-specific groups. Most studies only included costs from a healthcare perspective (39). Outcomes ranged from prescribing errors (9), hospital utilisation (13) and health-related quality of life (15) to falls (6) and adverse drug events (6). In total, 21 studies carried out an incremental cost-effectiveness analysis (16 including the incremental cost per quality-adjusted life year gained), and 14 reported the intervention cost-effectiveness. Remaining studies were cost–consequence (18) and cost–benefit analyses (5). Study reporting quality varied considerably, with lack of transparency in the design of the decision-analytic model, varied reporting of costs, little consideration of indirect costs or the impact of loss of trust on future use of healthcare, limitations in handling of uncertainty or discounting and very little patient involvement around targeting patients or designing interventions. Of the ten studies using decision models, all scored poorly for model validation. The quality of studies has not improved over time. Conclusions While some interventions demonstrated cost-effectiveness, study quality was variable, with generally poorly validated models. Study heterogeneity precluded meaningful direct comparison between studies. Significant research gaps remain as studies focused mainly on prescribing and monitoring errors, there was little or no investigation of technology-based interventions and there was inadequate targeting of patients most vulnerable to harm.

The COVID-19-Curated and Open Analysis and Research Platform (CO-CONNECT) project worked with 22 organizations across the United Kingdom to build a federated platform, enabling researchers to instantaneously and dynamically query federated datasets to find relevant data for their study. Finding relevant data takes time and effort, reducing the efficiency of research. Although data controllers could understand the value of such a system, there were significant challenges and delays in setting up the platform in response to COVID-19. This paper aims to present the challenges and lessons learned from the CO-CONNECT project to support other similar initiatives in the future. The project encountered many challenges, including the impacts of lockdowns on collaboration, understanding the new architecture, competing demands on people’s time during a pandemic, data governance approvals, different levels of technical capabilities, data transformation to a common data model, access to granular-level laboratory data, and how to engage public and patient representatives meaningfully on a highly technical project. To overcome these challenges, we developed a range of methods to support data partners such as explainer videos; regular, short, “touch base” videoconference calls; drop-in workshops; live demos; and a standardized technical onboarding documentation pack. A 4-stage data governance process emerged. The patient and public representatives were fully integrated team members. Persistence, patience, and understanding were key. We make 8 recommendations to change the landscape for future similar initiatives. The new architecture and processes developed are being built upon for non–COVID-19–related data, providing an infrastructural legacy.

Background: Antibiotic resistant infections cause over 700,000 deaths worldwide annually. As antimicrobial stewardship (AMS) helps minimise the emergence of antibiotic resistance resulting from inappropriate use of antibiotics in healthcare, we developed ePAMS+ (ePrescribing-based Anti-Microbial Stewardship), an ePrescribing and Medicines Administration (EPMA) system decision-support tool complemented by educational, behavioural and organisational elements. Methods: We conducted a non-randomised before-and-after feasibility trial, implementing ePAMS+ in two English hospitals using the Cerner Millennium EPMA system. Wards of several specialties were included. Patient participants were blinded to whether ePAMS+ was in use; prescribers were not. A mixed-methods evaluation aimed to establish: acceptability and usability of ePAMS+ and trial processes; feasibility of ePAMS+ implementation and quantitative outcome recording; and a Fidelity Index measuring the extent to which ePAMS+ was delivered as intended. Longitudinal semi-structured interviews of doctors, nurses and pharmacists, alongside non-participant observations, gathered qualitative data; we extracted quantitative prescribing data from the EPMA system. Normal linear modelling of the defined daily dose (DDD) of antibiotic per admission quantified its variability, to inform sample size calculations for a future trial of ePAMS+ effectiveness. Results: The research took place during the SARS-CoV-2 pandemic, from April 2021 to November 2022. 60 qualitative interviews were conducted (33 before ePAMS+ implementation, 27 after). 1,958 admissions (1,358 before ePAMS+ implementation; 600 after) included 24,884 antibiotic orders. Qualitative interviews confirmed that some aspects of ePAMS+ , its implementation and training were acceptable, while other features (e.g. enabling combinations of antibiotics to be prescribed) required further development. ePAMS+ uptake was low (28 antibiotic review records from 600 admissions; 0.047 records per admission), preventing full development of a Fidelity Index. Normal linear modelling of antibiotic DDD per admission showed a residual variance of 1.086 (log-transformed scale). Unavailability of indication data prevented measurement of some outcomes (e.g. number of antibiotic courses per indication). Conclusions: This feasibility trial encountered unforeseen circumstances due to contextual factors and a global pandemic, highlighting the need for careful adaptation of complex intervention implementations to the local setting. We identified key refinements to ePAMS+ to support its wider adoption in clinical practice, requiring further piloting before a confirmatory effectiveness trial. Trial registration: ISRCTN Registry ISRCTN13429325, 24 March 2022.

Background: Antimicrobial resistance (AMR) represents a growing concern for public health. Objective: We sought to explore the challenges associated with development and implementation of a complex intervention designed to improve AMS in hospitals. Methods: We conducted a qualitative evaluation of a complex AMS intervention with educational, behavioral, and technological components in 5 wards of an English hospital. At 2 weeks and 7 weeks after initiating the intervention, we interviewed 25 users of the intervention, including senior and junior prescribers, a senior nurse, a pharmacist, and a microbiologist. Topics discussed included perceived impacts of different elements of the intervention and facilitators and barriers to effective use. Interviews were supplemented by 2 observations of ward rounds to gain insights into AMS practices. Data were audio-recorded, transcribed, and inductively and deductively analyzed thematically using NVivo12. Results: Tracing the adoption and impact of the various components of the intervention was difficult, as it had been introduced into a setting with competing pressures. These particularly affected behavioral and educational components (eg, training, awareness-building activities), which were often delivered ad hoc. We found that the participatory intervention design had addressed typical use cases but had not catered for edge cases that only became visible when the intervention was delivered in real-world settings (eg, variations in prescribing workflows across different specialties and conditions). Conclusions: Effective user-focused design of complex interventions to promote AMS can support acceptance and use. However, not all requirements and potential barriers to use can be fully anticipated or tested in advance of full implementation in real-world settings.

Background: Healthcare laboratory systems produce and capture a vast array of information, yet do not always report all of this to the national infrastructure within the United Kingdom. The global COVID-19 pandemic brought about a much greater need for detailed healthcare data, one such instance being laboratory testing data. The reporting of qualitative laboratory test results (e.g. positive, negative or indeterminate) provides a basic understanding of levels of seropositivity. However, to better understand and interpret seropositivity, how it is determined and other factors that affect its calculation (i.e. levels of antibodies), quantitative laboratory test data are needed. Method: 36 data attributes were collected from 3 NHS laboratories and 29 CO-CONNECT project partner organisations. These were assessed against the need for a minimum dataset to determine data attribute importance. An NHS laboratory feasibility study was undertaken to assess the minimum data standard, together with a literature review of national and international data standards and healthcare reports. Results: A COVID serology minimum data standard (CSMDS) comprising 12 data attributes was created and verified by 3 NHS laboratories to allow national granular reporting of COVID serology results. To support this, a standardised set of vocabulary terms was developed to represent laboratory analyser systems and laboratory information management systems. Conclusions: This paper puts forward a minimum viable standard for COVID-19 serology data attributes to enhance its granularity and augment the national reporting of COVID-19 serology laboratory results, with implications for future pandemics.

Objectives To estimate the number and burden of medication errors associated with prescription information transfer within the National Health Service (NHS) in England and the impact of implementing an interoperable prescription information system (a single digital prescribing record shared across NHS settings) in reducing these errors. Methods We constructed a probabilistic mathematical model. We estimated the number of transition medication errors that would be undetected by standard medicines reconciliation, based on published literature, and scaled this up based on the annual number of hospital admissions. We used published literature to estimate the proportion of errors that lead to harm and applied this to the number of errors to estimate the associated burden (healthcare resource use and deaths). Finally, we used reported effect sizes for electronic prescription information sharing interventions to estimate the impact of implementing an interoperable prescription information system on number of errors and resulting harm. Results Annually, around 1.8 million (95% credibility interval (CrI) 1.3 to 2.6 million) medication errors were estimated to occur at hospital transitions in England, affecting approximately 380 000 (95% CrI 260 397 to 539 876) patient episodes. Harm from these errors affects around 31 500 (95% CrI 22 407 to 42 906) patients, with 36 500 (95% CrI 25 093 to 52 019) additional bed days of inpatient care (costing around £17.8 million (95% CrI £12.4 to £24.9 million)) and >40 (95% CrI 9 to 146) deaths. Assuming the implementation of an interoperable prescription information system could reduce errors by 10% and 50%, there could be 180 000–913 000 fewer errors, 3000–15 800 fewer people who experience harm and 4–22 lives saved annually. Conclusions An interoperable prescription information system could provide major benefits for patient safety. Likely additional benefits include healthcare professional time saved, improved patient experience and care quality, quicker discharge and enhanced cross-organisational medicines optimisation. Our findings provide vital safety and economic evidence for the case to adopt interoperable prescription information systems.

BACKGROUND Antimicrobial resistance (AMR) represents a growing concern for public health. OBJECTIVE We sought to explore the challenges associated with development and implementation of a complex intervention designed to improve AMS in hospitals. METHODS We conducted a qualitative evaluation of a complex AMS intervention with educational, behavioral, and technological components in 5 wards of an English hospital. At 2 weeks and 7 weeks after initiating the intervention, we interviewed 25 users of the intervention, including senior and junior prescribers, a senior nurse, a pharmacist, and a microbiologist. Topics discussed included perceived impacts of different elements of the intervention and facilitators and barriers to effective use. Interviews were supplemented by 2 observations of ward rounds to gain insights into AMS practices. Data were audio-recorded, transcribed, and inductively and deductively analyzed thematically using NVivo12. RESULTS Tracing the adoption and impact of the various components of the intervention was difficult, as it had been introduced into a setting with competing pressures. These particularly affected behavioral and educational components (eg, training, awareness-building activities), which were often delivered ad hoc. We found that the participatory intervention design had addressed typical use cases but had not catered for edge cases that only became visible when the intervention was delivered in real-world settings (eg, variations in prescribing workflows across different specialties and conditions). CONCLUSIONS Effective user-focused design of complex interventions to promote AMS can support acceptance and use. However, not all requirements and potential barriers to use can be fully anticipated or tested in advance of full implementation in real-world settings.

UNSTRUCTURED The COVID-19-Curated and Open Analysis and Research Platform (CO-CONNECT) project worked with 22 organizations across the United Kingdom to build a federated platform, enabling researchers to instantaneously and dynamically query federated datasets to find relevant data for their study. Finding relevant data takes time and effort, reducing the efficiency of research. Although data controllers could understand the value of such a system, there were significant challenges and delays in setting up the platform in response to COVID-19. This paper aims to present the challenges and lessons learned from the CO-CONNECT project to support other similar initiatives in the future. The project encountered many challenges, including the impacts of lockdowns on collaboration, understanding the new architecture, competing demands on people’s time during a pandemic, data governance approvals, different levels of technical capabilities, data transformation to a common data model, access to granular-level laboratory data, and how to engage public and patient representatives meaningfully on a highly technical project. To overcome these challenges, we developed a range of methods to support data partners such as explainer videos; regular, short, “touch base” videoconference calls; drop-in workshops; live demos; and a standardized technical onboarding documentation pack. A 4-stage data governance process emerged. The patient and public representatives were fully integrated team members. Persistence, patience, and understanding were key. We make 8 recommendations to change the landscape for future similar initiatives. The new architecture and processes developed are being built upon for non–COVID-19–related data, providing an infrastructural legacy.