Developing a complex intervention to improve prescribing safety in primary care:mixed methods feasibility and optimisation pilot study

Objectives (A) To measure the extent to which different candidate outcome measures identified high-risk prescribing that is potentially changeable by the data-driven quality improvement in primary care (DQIP) intervention.(B) To explore the value of reviewing identified high-risk prescribing to clinicians.(C) To optimise the components of the DQIP intervention.  Design Mixed method study.  Setting General practices in two Scottish Health boards.  Participants 4 purposively sampled general practices of varying size and socioeconomic deprivation.  Outcome measures Prescribing measures targeting (1) high-risk use of the non-steroidal anti-inflammatory drugs (NSAIDs) and antiplatelets; (2) ‘Asthma control’ and (3) ‘Antithrombotics in atrial fibrillation (AF)’.  Intervention The prescribing measures were used to identify patients for review by general practices. The ability of the measures to identify potentially changeable high-risk prescribing was measured as the proportion of patients reviewed where practices identified a need for action. Field notes were recorded from meetings between researchers and staff and key staff participated in semistructured interviews exploring their experience of the piloted intervention processes.  Results Practices identified a need for action in 68%, 25% and 18% of patients reviewed for prescribing measures (1), (2) and (3), respectively. General practitioners valued being prompted to review patients, and perceived that (1) ‘NSAID and antiplatelet’ and (2) ‘antithrombotics in AF’ were the most important to act on. Barriers to initial and ongoing engagement and to sustaining improvements in prescribing were identified.  Conclusions ‘NSAIDs and antiplatelets’ measures were selected as the most suitable outcome measures for the DQIP trial, based on evidence of this prescribing being more easily changeable. In response to the barriers identified, the intervention was designed to include a financial incentive, additional ongoing feedback on progress and reprompting review of patients, whose high-risk prescribing was restarted after a decision to stop.  Trial registration number Clinicaltrials.govNCT01425502

Process evaluation of the Data-driven Quality Improvement in Primary Care (DQIP) trial:Quantitative examination of variation between practices in recruitment, implementation and effectiveness

Objectives: - The cluster randomised trial of the Data-driven Quality Improvement in Primary Care (DQIP) intervention showed that education, informatics and financial incentives for general medical practices to review patients with ongoing high-risk prescribing of non-steroidal anti-inflammatory drugs and antiplatelets reduced the primary end point of high-risk prescribing by 37%, where both ongoing and new high-risk prescribing were significantly reduced. This quantitative process evaluation examined practice factors associated with (1) participation in the DQIP trial, (2) review activity (extent and nature of documented reviews) and (3) practice level effectiveness (relative reductions in the primary end point). Setting/participants: - Invited practices recruited (n=33) and not recruited (n=32) to the DQIP trial in Scotland, UK. Outcome measures: - (1) Characteristics of recruited versus non-recruited practices. Associations of (2) practice characteristics and 'adoption? (self-reported implementation work done by practices) with documented review activity and (3) of practice characteristics, DQIP adoption and review activity with effectiveness. Results: - (1) Recruited practices had lower performance in the quality and outcomes framework than those declining participation. (2) Not being an approved general practitioner training practice and higher self-reported adoption were significantly associated with higher review activity. (3) Effectiveness ranged from a relative increase in high-risk prescribing of 24.1% to a relative reduction of 77.2%. High-risk prescribing and DQIP adoption (but not documented review activity) were significantly associated with greater effectiveness in the final multivariate model, explaining 64.0% of variation in effectiveness. Conclusions: - Intervention implementation and effectiveness of the DQIP intervention varied substantially between practices. Although the DQIP intervention primarily targeted review of ongoing high-risk prescribing, the finding that self-reported DQIP adoption was a stronger predictor of effectiveness than documented review activity supports that reducing initiation and/or re-initiation of high-risk prescribing is key to its effectiveness

Balancing measures or a balanced accounting of improvement impact:a qualitative analysis of individual and focus group interviews with improvement experts in Scotland

Background As quality improvement (QI) programmes have become progressively larger scale, the risks of implementation having unintended consequences are increasingly recognised. More routine use of balancing measures to monitor unintended consequences has been proposed to evaluate overall effectiveness, but in practice published improvement interventions hardly ever report identification or measurement of consequences other than intended goals of improvement. Methods We conducted 15 semistructured interviews and two focus groups with 24 improvement experts to explore the current understanding of balancing measures in QI and inform a more balanced accounting of the overall impact of improvement interventions. Data were analysed iteratively using the framework approach. Results Participants described the consequences of improvement in terms of desirability/undesirability and the extent to which they were expected/unexpected when planning improvement. Four types of consequences were defined: expected desirable consequences (goals); expected undesirable consequences (trade-offs); unexpected undesirable consequences (unpleasant surprises); and unexpected desirable consequences (pleasant surprises). Unexpected consequences were considered important but rarely measured in existing programmes, and an improvement pause to take stock after implementation would allow these to be more actively identified and managed. A balanced accounting of all consequences of improvement interventions can facilitate staff engagement and reduce resistance to change, but has to be offset against the cost of additional data collection. Conclusion Improvement measurement is usually focused on measuring intended goals, with minimal use of balancing measures which when used, typically monitor trade-offs expected before implementation. This paper proposes that improvers and leaders should seek a balanced accounting of all consequences of improvement across the life of an improvement programme, including deliberately pausing after implementation to identify and quantitatively or qualitatively evaluate any pleasant or unpleasant surprises

Process evaluation of the Data-driven Quality Improvement in Primary Care (DQIP) trial: Case study evaluation of adoption and maintenance of a complex intervention to reduce high-risk primary care prescribing

Objective To explore how different practices responded to the Data-driven Quality Improvement in Primary Care (DQIP) intervention in terms of their adoption of the work, reorganisation to deliver the intended change in care to patients, and whether implementation was sustained over time.  Design Mixed-methods parallel process evaluation of a cluster trial, reporting the comparative case study of purposively selected practices.  Setting Ten (30%) primary care practices participating in the trial from Scotland, UK.  Results Four practices were sampled because they had large rapid reductions in targeted prescribing. They all had internal agreement that the topic mattered, made early plans to implement including assigning responsibility for work and regularly evaluated progress. However, how they internally organised the work varied. Six practices were sampled because they had initial implementation failure. Implementation failure occurred at different stages depending on practice context, including internal disagreement about whether the work was worthwhile, and intention but lack of capacity to implement or sustain implementation due to unfilled posts or sickness. Practice context was not fixed, and most practices with initial failed implementation adapted to deliver at least some elements. All interviewed participants valued the intervention because it was an innovative way to address on an important aspect of safety (although one of the non-interviewed general practitioners in one practice disagreed with this). Participants felt that reviewing existing prescribing did influence their future initiation of targeted drugs, but raised concerns about sustainability.  Conclusions Variation in implementation and effectiveness was associated with differences in how practices valued, engaged with and sustained the work required. Initial implementation failure varied with practice context, but was not static, with most practices at least partially implementing by the end of the trial. Practices organised their delivery of changed care to patients in ways which suited their context, emphasising the importance of flexibility in any future widespread implementation

Hepatic Impairment as a Risk Factor for Drug Safety: Suitability and Comparison of Four Liver Scores as Screening Tools

Hepatic impairment (HI) influences the pharmacokinetics and pharmacodynamics of drugs and represents an important risk factor for drug safety. A reliable screening tool for HI identification at hospital admission by pharmacists would be desirable but is currently lacking. Therefore, we tested four liver scores as potential screening instruments. We retrospectively recorded liver/bile diagnoses, symptoms and abnormalities (summarized as hepatic findings) of 200 surgical patients followed by an assessment of the relevance of these findings for drug therapy (rating). The agreement between the Model of Endstage Liver Disease (MELD), Non-alcoholic fatty liver disease fibrosis score (NFS), Fibrosis 4 index (FIB-4), and aspartate-aminotransferase to platelet ratio index (APRI) and the rating was quantified by Cohen’s Kappa. The performance of the scores in this setting was further evaluated by their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Of 200 patients, 18 (9%) had hepatic findings relevant for drug therapy. Fair agreement was found for FIB-4 and MELD and slight agreement for APRI and NFS compared to the rating. The highest values for sensitivity, specificity, PPV, and NPV were 41.2% (MELD), 99.3% (APRI), 66.7% (APRI), and 93.6% (MELD), respectively. Due to low performance, none of the scores can be recommended for clinical use as a single screening tool for HI at hospital admission

Prioritisation of Adverse Drug Events Leading to Hospital Admission and Occurring during Hospitalisation: A RAND Survey

(1) Adverse drug events (ADEs) are a common cause of emergency department visits and occur frequently during hospitalisation. Instruments that facilitate the detection of the most relevant ADEs could lead to a more targeted and efficient use of limited resources in research and practice. (2) We conducted two consensus processes based on the RAND/UCLA appropriateness method, in order to prioritise ADEs leading to hospital admission (panel 1) and occurring during hospital stay (panel 2) for inclusion in future ADE measurement instruments. In each panel, the experts were asked to assess the overall importance of each ADE on a four-point Likert scale (1 = not important to 4 = very important). ADEs with a median rating of >= 3 without disagreement were defined as prioritised. (3) The 13 experts in panel 1 prioritised 38 out of 65 ADEs, while the 12 experts in panel 2 prioritised 34 out of 63 ADEs. The highest rated events were acute kidney injury and hypoglycaemia (both panels), as well as Stevens-Johnson syndrome in panel 1 and rhabdomyolysis in panel 2. (4) The survey led to a set of ADEs for which there was consensus that they were of particular importance as presentations of acute medication-related harm, thereby providing a focus for further medication safety research and clinical practice

Pro's and con's of the stepped wedge design in cluster randomised trials of quality improvement interventions: two current examples.

The stepped wedge design, under which all trial participants receive the intervention but the order in which the intervention is received is randomised, is potentially useful to rigorously evaluate organisational interventions to improve quality and safety. We use two examples of cluster-randomised stepped-wedge trials (DQIP and GP-POLY) to illustrate advantages and disadvantages of the design in evaluations of complex prescribing improvement interventions in primary care. DQIP is nearing completion and GP-POLY will start in 2013. The intervention in both DQIP and GP-Poly involves outreach visits by researchers for education and informatics tool training, making sequential roll out a logistic necessity. The stepped wedge allows for this by design, but trial durations may be prolonged compared to parallel-arm trials and other designs, and arranging initiation visits to fit with randomisation schedules is challenging. Since all participants receive the intervention and there are multiple repeated measurements, practice sample size requirements in DQIP and GP-POLY were reduced compared to a parallel-arm design, but power calculations are more complex. Recruitment may be improved by offering the intervention to all participants, but creates potential problems for retention and avoiding contamination in practices with long lags between recruitment and intervention start. Because of the vulnerability of stepped wedge trials to time varying confounding, avoiding changes in intervention delivery to successive cohorts is important and needs careful planning. The stepped wedge design is attractive for cluster randomised trials of quality improvement interventions, especially when staggering of intervention delivery is inevitable, but presents challenges for implementation that need careful planning. Oral presentation presented at the 2nd Clinical Trials Methodology Conference 2013: Methodology matters, 18-19 November 2013, Edinburgh, UK

Safer Prescribing:A Trial of Education, Informatics, and Financial Incentives

BACKGROUND High-risk prescribing and preventable drug-related complications are common in primary care. We evaluated whether the rates of high-risk prescribing by primary care clinicians and the related clinical outcomes would be reduced by a complex intervention. METHODS In this cluster-randomized, stepped-wedge trial conducted in Tayside, Scotland, we randomly assigned participating primary care practices to various start dates for a 48-week intervention comprising professional education, informatics to facilitate review, and financial incentives for practices to review patients’ charts to assess appropriateness. The primary outcome was patient-level exposure to any of nine measures of high-risk prescribing of nonsteroidal antiinflammatory drugs (NSAIDs) or selected antiplatelet agents (e.g., NSAID prescription in a patient with chronic kidney disease or coprescription of an NSAID and an oral anticoagulant without gastroprotection). Prespecified secondary outcomes included the incidence of related hospital admissions. Analyses were performed according to the intention-to-treat principle, with the use of mixed-effect models to account for clustering in the data. RESULTS A total of 34 practices underwent randomization, 33 of which completed the study. Data were analyzed for 33,334 patients at risk at one or more points in the preintervention period and for 33,060 at risk at one or more points in the intervention period. Targeted high-risk prescribing was significantly reduced, from a rate of 3.7% (1102 of 29,537 patients at risk) immediately before the intervention to 2.2% (674 of 30,187) at the end of the intervention (adjusted odds ratio, 0.63; 95% confidence interval [CI], 0.57 to 0.68; P<0.001). The rate of hospital admissions for gastrointestinal ulcer or bleeding was significantly reduced from the preintervention period to the intervention period (from 55.7 to 37.0 admissions per 10,000 person-years; rate ratio, 0.66; 95% CI, 0.51 to 0.86; P = 0.002), as was the rate of admissions for heart failure (from 707.7 to 513.5 admissions per 10,000 person-years; rate ratio, 0.73; 95% CI, 0.56 to 0.95; P = 0.02), but admissions for acute kidney injury were not (101.9 and 86.0 admissions per 10,000 person-years, respectively; rate ratio, 0.84; 95% CI, 0.68 to 1.09; P = 0.19). CONCLUSIONS A complex intervention combining professional education, informatics, and financial incentives reduced the rate of high-risk prescribing of antiplatelet medications and NSAIDs and may have improved clinical outcomes

Pharmacist and Data-driven Quality Improvement in Primary Care (P-DQIP):A qualitative study of anticipated implementation factors informed by the Theoretical Domains Framework

Objectives: The quality and safety of drug therapy in primary care are global concerns. The Pharmacist and Data driven Quality Improvement in Primary care (P-DQIP) intervention aims to improve prescribing safety via an informatics tool which facilitates proactive management of drug therapy risks (DTRs) by health-board employed pharmacists with established roles in general practices. Study objectives were (1) to identify and prioritise factors that could influence P-DQIP implementation from the perspective of practice pharmacists, and (2) to identify potentially effective, acceptable and feasible strategies to support P-DQIP implementation. Design: Semi-structured face-to-face interviews using a Theoretical Domains Framework (TDF) informed topic guide. The framework method was used for data analysis. Identified implementation factors were prioritised for intervention based on research team consensus. Candidate intervention functions, behaviour change techniques (BCTs) and policies targeting these were identified from the Behaviour Change Wheel. The final intervention content and modes of delivery were agreed with local senior pharmacists. Setting: General practices from three Health and Social Care Partnerships (HSCPs) in NHS Tayside. Participants: 14 NHS employed practice pharmacists. Results: Identified implementation factors were linked to thirteen theoretical domains (all except intentions) and six (skill, memory/attention/decision-making, behavioural regulation, reinforcement, environmental context/resources, social influences) were prioritised. Three intervention functions (training, enablement, and environmental restructuring) were relevant and were served by two policy categories (guidelines, communication/marketing) and eight BCTs (Instructions on how to perform a behaviour, problem solving, action planning, prompt/cues, goal setting, self-monitoring, feedback, restructuring the social environment). Intervention components encompass an informatics tool, written educational material, a workshop for pharmacists, promotional activities, and small financial incentives. Conclusions: This study explored pharmacists’ perceptions of implementation factors which could influence management of DTRs in general practices to inform implementation of P-DQIP, which will initially be implemented in one Scottish health board with parallel evaluation of effectiveness and implementation