Overprescribing of potentially harmful medication: an observational study in England's general practice.

BACKGROUND: Overprescribing of potentially harmful medication in UK general practice has a complex association with socioeconomic deprivation. AIM: To assess trends in general practice prescribing of five high-risk medications and their relationship to deprivation. DESIGN & SETTING: We conducted an observational study using general practice data from three English regions with varied socio-demographic factors: West Yorkshire and Harrogate (WY), Black Country and West Birmingham (BC), and Surrey and East Sussex (SE). METHOD: Practice-level prescribing data was obtained from 2016-2021 for five drug classes: opioids, hypnotics, gabapentinoids, non-steroidal anti-inflammatory drugs (NSAIDs) and antibacterials. Prescribing trends were demonstrated using a linear model. RESULTS: Reduction in NSAID, Opioid, Hypnotic and Antibacterial prescriptions, and the increase in gabapentinoid prescriptions, were significant at each financial-year time period. Index of Multiple Deprivation (IMD) was positively associated with all drug classes except antibacterials, which showed a positive association when incorporating the interaction term between IMD and age.When adjusting for IMD and population, region was independently associated with prescribing rate. Compared to WY, IMD had a smaller association with prescribing in BC for NSAIDs (Coefficient -0.01578, P=0.004) and antibacterials (Coefficient -0.02769, P=0.007), whereas IMD had a greater association with prescribing in SE for NSAIDs (Coefficient 0.02443, P<.001), opioids (Coefficient 0.08919 p<.001), hypnotics (Coefficient 0.09038 p<.001), gabapentinoids (Coefficient 0.1095, P<.001) and antibacterials (Coefficient 0.01601, P=0.19). CONCLUSION: The association of socioeconomic deprivation with overprescribing of high-risk medication in general practice varies by region and drug type. Geographical location is associated with overprescribing, independent of socioeconomic status.

The effects of an evidence- and theory-informed feedback intervention on opioid prescribing for non-cancer pain in primary care: A controlled interrupted time series analysis.

BACKGROUND: The rise in opioid prescribing in primary care represents a significant international public health challenge, associated with increased psychosocial problems, hospitalisations, and mortality. We evaluated the effects of a comparative feedback intervention with persuasive messaging and action planning on opioid prescribing in primary care. METHODS AND FINDINGS: A quasi-experimental controlled interrupted time series analysis used anonymised, aggregated practice data from electronic health records and prescribing data from publicly available sources. The study included 316 intervention and 130 control primary care practices in the Yorkshire and Humber region, UK, serving 2.2 million and 1 million residents, respectively. We observed the number of adult patients prescribed opioid medication by practice between July 2013 and December 2017. We excluded adults with coded cancer or drug dependency. The intervention, the Campaign to Reduce Opioid Prescribing (CROP), entailed bimonthly, comparative, and practice-individualised feedback reports to practices, with persuasive messaging and suggested actions over 1 year. Outcomes comprised the number of adults per 1,000 adults per month prescribed any opioid (main outcome), prescribed strong opioids, prescribed opioids in high-risk groups, prescribed other analgesics, and referred to musculoskeletal services. The number of adults prescribed any opioid rose pre-intervention in both intervention and control practices, by 0.18 (95% CI 0.11, 0.25) and 0.36 (95% CI 0.27, 0.46) per 1,000 adults per month, respectively. During the intervention period, prescribing per 1,000 adults fell in intervention practices (change -0.11; 95% CI -0.30, -0.08) and continued rising in control practices (change 0.54; 95% CI 0.29, 0.78), with a difference of -0.65 per 1,000 patients (95% CI -0.96, -0.34), corresponding to 15,000 fewer patients prescribed opioids. These trends continued post-intervention, although at slower rates. Prescribing of strong opioids, total opioid prescriptions, and prescribing in high-risk patient groups also generally fell. Prescribing of other analgesics fell whilst musculoskeletal referrals did not rise. Effects were attenuated after feedback ceased. Study limitations include being limited to 1 region in the UK, possible coding errors in routine data, being unable to fully account for concurrent interventions, and uncertainties over how general practices actually used the feedback reports and whether reductions in prescribing were always clinically appropriate. CONCLUSIONS: Repeated comparative feedback offers a promising and relatively efficient population-level approach to reduce opioid prescribing in primary care, including prescribing of strong opioids and prescribing in high-risk patient groups. Such feedback may also prompt clinicians to reconsider prescribing other medicines associated with chronic pain, without causing a rise in referrals to musculoskeletal clinics. Feedback may need to be sustained for maximum effect.

General practice responses to opioid prescribing feedback: a qualitative process evaluation.

BACKGROUND: The rise in opioid prescribing in primary care represents a significant public health challenge, associated with increased psychosocial problems, hospitalisations, and mortality. An evidence-based bimonthly feedback intervention to reduce opioid prescribing was developed and implemented, targeting 316 general practices in West Yorkshire over 1 year. AIM: To understand how general practice staff received and responded to the feedback intervention. DESIGN AND SETTING: Qualitative process evaluation involving semi-structured interviews, guided by Normalisation Process Theory (NPT), of primary care healthcare professionals targeted by feedback. METHOD: Participants were purposively recruited according to baseline opioid prescribing levels and degree of change following feedback. Interview data were coded to NPT constructs, and thematically analysed. RESULTS: Interviews were conducted with 21 staff from 20 practices. Reducing opioid prescribing was recognised as a priority. While high achievers had clear structures for quality improvement, feedback encouraged some less structured practices to embed changes. The non-prescriptive nature of the feedback reports allowed practices to develop strategies consistent with their own ways of working and existing resources. Practice concerns were allayed by the credibility of the reports and positive experiences of reducing opioid prescribing. The scale, frequency, and duration of feedback may have ensured a good overall level of practice population reach. CONCLUSION: The intervention engaged general practice staff in change by targeting an issue of emerging concern, and allowing adaption to different ways of working. Practice efforts to reduce opioid prescribing were reinforced by regular feedback, credible comparative data showing progress, and shared experiences of patient benefit.

Establishing a primary care audit and feedback implementation laboratory: a consensus study.

BACKGROUND: There is a significant variation among individual primary care providers in prescribing of potentially problematic, low-value medicines which cause avoidable patient harm. Audit and feedback is generally effective at improving prescribing. However, progress has been hindered by research waste, leading to unanswered questions about how to include audit and feedback for specific problems and circumstances. Trials of different ways of providing audit and feedback in implementation laboratories have been proposed as a way of improving population healthcare while generating robust evidence on feedback effects. However, there is limited experience in their design and delivery. AIM: To explore priorities, feasibility, and ethical challenges of establishing a primary care prescribing audit and feedback implementation laboratory. DESIGN AND SETTING: Two-stage Delphi consensus process involving primary care pharmacy leads, audit and feedback researchers, and patient and public. METHOD: Participants initially scored statements relating to priorities, feasibility, and ethical considerations for an implementation laboratory. These covered current feedback practice, priority topics for feedback, usefulness of feedback in improving prescribing and different types of prescribing data, acceptability and desirability of different organization levels of randomization, options for trial consent, different methods of delivering feedback, and interest in finding out how effective different ways of presenting feedback would be. After receiving collated results, participants then scored the items again. The consensus was defined using the GRADE criteria. The results were analyzed by group and overall score. RESULTS: Fourteen participants reached consensus for 38 out of 55 statements. Addressing antibiotic and opioid prescribing emerged as the highest priorities for action. The panel supported statements around addressing high-priority prescribing issues, taking an "opt-out" approach to practice consent if waiving consent was not permitted, and randomizing at lower rather than higher organizational levels. Participants supported patient-level prescribing data and further research evaluating most of the different feedback methods we presented them with. CONCLUSIONS: There is a good level of support for evaluating a wide range of potential enhancements to improve the effects of feedback on prescribing. The successful design and delivery of a primary care audit and feedback implementation laboratory depend on identifying shared priorities and addressing practical and ethical considerations.

An adaptable implementation package targeting evidence-based indicators in primary care: A pragmatic cluster-randomised evaluation.

BACKGROUND: In primary care, multiple priorities and system pressures make closing the gap between evidence and practice challenging. Most implementation studies focus on single conditions, limiting generalisability. We compared an adaptable implementation package against an implementation control and assessed effects on adherence to four different evidence-based quality indicators. METHODS AND FINDINGS: We undertook two parallel, pragmatic cluster-randomised trials using balanced incomplete block designs in general practices in West Yorkshire, England. We used 'opt-out' recruitment, and we randomly assigned practices that did not opt out to an implementation package targeting either diabetes control or risky prescribing (Trial 1); or blood pressure (BP) control or anticoagulation in atrial fibrillation (AF) (Trial 2). Within trials, each arm acted as the implementation control comparison for the other targeted indicator. For example, practices assigned to the diabetes control package acted as the comparison for practices assigned to the risky prescribing package. The implementation package embedded behaviour change techniques within audit and feedback, educational outreach, and computerised support, with content tailored to each indicator. Respective patient-level primary endpoints at 11 months comprised the following: achievement of all recommended levels of haemoglobin A1c (HbA1c), BP, and cholesterol; risky prescribing levels; achievement of recommended BP; and anticoagulation prescribing. Between February and March 2015, we recruited 144 general practices collectively serving over 1 million patients. We stratified computer-generated randomisation by area, list size, and pre-intervention outcome achievement. In April 2015, we randomised 80 practices to Trial 1 (40 per arm) and 64 to Trial 2 (32 per arm). Practices and trial personnel were not blind to allocation. Two practices were lost to follow-up but provided some outcome data. We analysed the intention-to-treat (ITT) population, adjusted for potential confounders at patient level (sex, age) and practice level (list size, locality, pre-intervention achievement against primary outcomes, total quality scores, and levels of patient co-morbidity), and analysed cost-effectiveness. The implementation package reduced risky prescribing (odds ratio [OR] 0.82; 97.5% confidence interval [CI] 0.67-0.99, p = 0.017) with an incremental cost-effectiveness ratio of £1,359 per quality-adjusted life year (QALY), but there was insufficient evidence of effect on other primary endpoints (diabetes control OR 1.03, 97.5% CI 0.89-1.18, p = 0.693; BP control OR 1.05, 97.5% CI 0.96-1.16, p = 0.215; anticoagulation prescribing OR 0.90, 97.5% CI 0.75-1.09, p = 0.214). No statistically significant effects were observed in any secondary outcome except for reduced co-prescription of aspirin and clopidogrel without gastro-protection in patients aged 65 and over (adjusted OR 0.62; 97.5% CI 0.39-0.99; p = 0.021). Main study limitations concern our inability to make any inferences about the relative effects of individual intervention components, given the multifaceted nature of the implementation package, and that the composite endpoint for diabetes control may have been too challenging to achieve. CONCLUSIONS: In this study, we observed that a multifaceted implementation package was clinically and cost-effective for targeting prescribing behaviours within the control of clinicians but not for more complex behaviours that also required patient engagement. TRIAL REGISTRATION: The study is registered with the ISRCTN registry (ISRCTN91989345).

Developing a complex intervention to support timely engagement with palliative care for patients with advanced cancer in primary and secondary care in the UK: a study protocol.

INTRODUCTION: For patients with advanced cancer, timely access to palliative care can improve quality of life and enable patients to participate in decisions about their end-of-life care. However, in a UK population of 2500 patients who died from cancer, one-third did not receive specialist palliative care, and of those who did, the duration of involvement was too short to maximise the benefits. Initiating a conversation about palliative care is challenging for some health professionals and patients often have unmet information needs and misconceptions about palliative care. We will work closely with patients and health professionals to develop a patient decision aid and health professional training module designed to facilitate a timely and informed conversation about palliative care. METHODS AND ANALYSIS: This study is being conducted over 24 months from November 2017 to October 2019 and follows the UK Medical Research Council framework for developing complex interventions and the International Patient Decision Aids Guideline. The Ottawa Decision Support Framework underpins the study. The Supporting Timely Engagement with Palliative care (STEP) intervention will be developed though an iterative process informed by interviews and focus groups with patients with advanced cancer, oncologists, general practitioners and palliative care doctors. An expert panel will also review each iteration. The expert panel will consist of a patient representative with experience of palliative care, health professionals who are involved in advanced cancer care decision-making, a medical education expert and the National Council for Palliative Care director of transformation. The feasibility and acceptability of the decision aid and doctor training will be tested in oncology and general practice settings. ETHICS AND DISSEMINATION: Ethical approval for the study has been granted by the Office for Research Ethics Committees Northern Ireland (ORECNI), approval reference 17/NI/0249. Dissemination and knowledge transfer will be conducted via publications, national bodies and networks, and patient and family groups.

Is palliative care support associated with better quality end-of-life care indicators for patients with advanced cancer? A retrospective cohort study.

OBJECTIVES: This study aimed to establish the association between timing and provision of palliative care (PC) and quality of end-of-life care indicators in a population of patients dying of cancer. SETTING: This study uses linked cancer patient data from the National Cancer Registry, the electronic medical record system used in primary care (SystmOne) and the electronic medical record system used within a specialist regional cancer centre. The population resided in a single city in Northern England. PARTICIPANTS: Retrospective data from 2479 adult cancer decedents who died between January 2010 and February 2012 were registered with a primary care provider using the SystmOne electronic health record system, and cancer was certified as a cause of death, were included in the study. RESULTS: Linkage yielded data on 2479 cancer decedents, with 64.5% who received at least one PC event. Decedents who received PC were significantly more likely to die in a hospice (39.4% vs 14.5%, P<0.005) and less likely to die in hospital (23.3% vs 40.1%, P<0.05), and were more likely to receive an opioid (53% vs 25.2%, P<0.001). PC initiated more than 2 weeks before death was associated with avoiding a hospital death (≥2 weeks, P<0.001), more than 4 weeks before death was associated with avoiding emergency hospital admissions and increased access to an opioid (≥4 weeks, P<0.001), and more than 33 weeks before death was associated with avoiding late chemotherapy (≥33 weeks, no chemotherapy P=0.019, chemotherapy over 4 weeks P=0.007). CONCLUSION: For decedents with advanced cancer, access to PC and longer duration of PC were significantly associated with better end-of-life quality indicators.

To what extent can behaviour change techniques be identified within an adaptable implementation package for primary care? A prospective directed content analysis.

BACKGROUND: Interpreting evaluations of complex interventions can be difficult without sufficient description of key intervention content. We aimed to develop an implementation package for primary care which could be delivered using typically available resources and could be adapted to target determinants of behaviour for each of four quality indicators: diabetes control, blood pressure control, anticoagulation for atrial fibrillation and risky prescribing. We describe the development and prospective verification of behaviour change techniques (BCTs) embedded within the adaptable implementation packages. METHODS: We used an over-lapping multi-staged process. We identified evidence-based, candidate delivery mechanisms-mainly audit and feedback, educational outreach and computerised prompts and reminders. We drew upon interviews with primary care professionals using the Theoretical Domains Framework to explore likely determinants of adherence to quality indicators. We linked determinants to candidate BCTs. With input from stakeholder panels, we prioritised likely determinants and intervention content prior to piloting the implementation packages. Our content analysis assessed the extent to which embedded BCTs could be identified within the packages and compared them across the delivery mechanisms and four quality indicators. RESULTS: Each implementation package included at least 27 out of 30 potentially applicable BCTs representing 15 of 16 BCT categories. Whilst 23 BCTs were shared across all four implementation packages (e.g. BCTs relating to feedback and comparing behaviour), some BCTs were unique to certain delivery mechanisms (e.g. 'graded tasks' and 'problem solving' for educational outreach). BCTs addressing the determinants 'environmental context' and 'social and professional roles' (e.g. 'restructuring the social and 'physical environment' and 'adding objects to the environment') were indicator specific. We found it challenging to operationalise BCTs targeting 'environmental context', 'social influences' and 'social and professional roles' within our chosen delivery mechanisms. CONCLUSION: We have demonstrated a transparent process for selecting, operationalising and verifying the BCT content in implementation packages adapted to target four quality indicators in primary care. There was considerable overlap in BCTs identified across the four indicators suggesting core BCTs can be embedded and verified within delivery mechanisms commonly available to primary care. Whilst feedback reports can include a wide range of BCTs, computerised prompts can deliver BCTs at the time of decision making, and educational outreach can allow for flexibility and individual tailoring in delivery.

Using primary care data for health research in England - an overview.

In contrast to secondary care, where handwritten records remain widespread, electronic patient records have long been a key feature of UK general practice. By 1996, 96% of general practices were computerised and now almost every primary care consultation in the UK is recorded on a computerised clinical system. Consequently, we now have a vast repository of patient health data that spans decades, which could be used to address a range of important research questions. Unfortunately, accessing primary care data for health researchers can be a burdensome, confusing and time-consuming process. Understanding the way in which primary care data are recorded and 'coded' is not intuitive to those unfamiliar with general practice. The requirements of information governance mean that some data, or data presented in particular ways, are not available at all. This review provides a practical overview of the types of data recorded in primary care, the bodies responsible for them and how they can be accessed.

New models of care: a liaison psychiatry service for medically unexplained symptoms and frequent attenders in primary care.

Aims and method This paper describes the process of setting up and the early results from a new liaison psychiatry service in primary care for people identified as frequent general practice attenders with long-term conditions or medically unexplained symptoms. Using a rapid evidence synthesis, we identified existing service models, mechanisms to identify and refer patients, and outcomes for the service. Considering this evidence, with local contingencies we defined options and resources. We agreed a model to set up a service in three diverse general practices. An evaluation explored the feasibility of the service and of collecting data for clinical, service and economic outcomes. Results High levels of patient and staff satisfaction, and reductions in the utilisation of primary and secondary healthcare, with associated cost savings are reported. Clinical implications A multidisciplinary liaison psychiatry service integrated in primary care is feasible and may be evaluated using routinely collected data.

Self-management toolkit and delivery strategy for end-of-life pain: the mixed-methods feasibility study.

BACKGROUND: Pain affects most people approaching the end of life and can be severe for some. Opioid analgesia is effective, but evidence is needed about how best to support patients in managing these medicines. OBJECTIVES: To develop a self-management support toolkit (SMST) and delivery strategy and to test the feasibility of evaluating this intervention in a future definitive trial. DESIGN: Phase I - evidence synthesis and qualitative interviews with patients and carers. Phase II - qualitative semistructured focus groups and interviews with patients, carers and specialist palliative care health professionals. Phase III - multicentre mixed-methods single-arm pre-post observational feasibility study. PARTICIPANTS: Phase I - six patients and carers. Phase II - 15 patients, four carers and 19 professionals. Phase III - 19 patients recruited to intervention that experienced pain, living at home and were treated with strong opioid analgesia. Process evaluation interviews with 13 patients, seven carers and 11 study nurses. INTERVENTION: Self-Management of Analgesia and Related Treatments at the end of life (SMART) intervention comprising a SMST and a four-step educational delivery approach by clinical nurse specialists in palliative care over 6 weeks. MAIN OUTCOME MEASURES: Recruitment rate, treatment fidelity, treatment acceptability, patient-reported outcomes (such as scores on the Brief Pain Inventory, Self-Efficacy for Managing Chronic Disease Scale, Edmonton Symptom Assessment Scale, EuroQol-5 Dimensions, Satisfaction with Information about Medicines Scale, and feasibility of collecting data on health-care resource use for economic evaluation). RESULTS: Phase I - key themes on supported self-management were identified from evidence synthesis and qualitative interviews. Phase II - the SMST was developed and refined. The delivery approach was nested within a nurse-patient consultation. Phase III - intervention was delivered to 17 (89%) patients, follow-up data at 6 weeks were available on 15 patients. Overall, the intervention was viewed as acceptable and valued. Descriptive analysis of patient-reported outcomes suggested that interference from pain and self-efficacy were likely to be candidates for primary outcomes in a future trial. No adverse events related to the intervention were reported. The health economic analysis suggested that SMART could be cost-effective. We identified key limitations and considerations for a future trial: improve recruitment through widening eligibility criteria, refine the SMST resources content, enhance fidelity of intervention delivery, secure research nurse support at recruiting sites, refine trial procedures (including withdrawal process and data collection frequency), and consider a cluster randomised design with nurse as cluster unit. LIMITATIONS: (1) The recruitment rate was lower than anticipated. (2) The content of the intervention was focused on strong opioids only. (3) The fidelity of intervention delivery was limited by the need for ongoing training and support. (4) Recruitment sites where clinical research nurse support was not secured had lower recruitment rates. (5) The process for recording withdrawal was not sufficiently detailed. (6) The number of follow-up visits was considered burdensome for some participants. (7) The feasibility trial did not have a control arm or assess randomisation processes. CONCLUSIONS: A future randomised controlled trial is feasible and acceptable. STUDY AND TRIAL REGISTRATION: This study is registered as PROSPERO CRD42014013572; Current Controlled Trials ISRCTN35327119; and National Institute for Health Research (NIHR) Portfolio registration 162114. FUNDING: The NIHR Health Technology Assessment programme.

Variations in achievement of evidence-based, high-impact quality indicators in general practice: An observational study.

BACKGROUND: There are widely recognised variations in the delivery and outcomes of healthcare but an incomplete understanding of their causes. There is a growing interest in using routinely collected 'big data' in the evaluation of healthcare. We developed a set of evidence-based 'high impact' quality indicators (QIs) for primary care and examined variations in achievement of these indicators using routinely collected data in the United Kingdom (UK). METHODS: Cross-sectional analysis of routinely collected, electronic primary care data from a sample of general practices in West Yorkshire, UK (n = 89). The QIs covered aspects of care (including processes and intermediate clinical outcomes) in relation to diabetes, hypertension, atrial fibrillation, myocardial infarction, chronic kidney disease (CKD) and 'risky' prescribing combinations. Regression models explored the impact of practice and patient characteristics. Clustering within practice was accounted for by including a random intercept for practice. RESULTS: Median practice achievement of the QIs ranged from 43.2% (diabetes control) to 72.2% (blood pressure control in CKD). Considerable between-practice variation existed for all indicators: the difference between the highest and lowest performing practices was 26.3 percentage points for risky prescribing and 100 percentage points for anticoagulation in atrial fibrillation. Odds ratios associated with the random effects for practices emphasised this; there was a greater than ten-fold difference in the likelihood of achieving the hypertension indicator between the lowest and highest performing practices. Patient characteristics, in particular age, gender and comorbidity, were consistently but modestly associated with indicator achievement. Statistically significant practice characteristics were identified less frequently in adjusted models. CONCLUSIONS: Despite various policy and improvement initiatives, there are enduring inappropriate variations in the delivery of evidence-based care. Much of this variation is not explained by routinely collected patient or practice variables, and is likely to be attributable to differences in clinical and organisational behaviour.

Prescribed opioids in primary care: cross-sectional and longitudinal analyses of influence of patient and practice characteristics.

OBJECTIVES: To examine trends in opioid prescribing in primary care, identify patient and general practice characteristics associated with long-term and stronger opioid prescribing, and identify associations with changes in opioid prescribing. DESIGN: Trend, cross-sectional and longitudinal analyses of routinely recorded patient data. SETTING: 111 primary care practices in Leeds and Bradford, UK. PARTICIPANTS: We observed 471 828 patient-years in which all patients represented had at least 1 opioid prescription between April 2005 and March 2012. A cross-sectional analysis included 99 847 patients prescribed opioids between April 2011 and March 2012. A longitudinal analysis included 49 065 patient-years between April 2008 and March 2012. We excluded patients with cancer or treated for substance misuse. MAIN OUTCOME MEASURES: Long-term opioid prescribing (4 or more prescriptions within 12 months), stronger opioid prescribing and stepping up to or down from stronger opioids. RESULTS: Opioid prescribing in the adult population almost doubled for weaker opioids over 2005-2012 and rose over sixfold for stronger opioids. There was marked variation among general practices in the odds of patients stepping up to stronger opioids compared with those not stepping up (range 0.31-3.36), unexplained by practice-level variables. Stepping up to stronger opioids was most strongly associated with being underweight (adjusted OR 3.26, 1.49 to 7.17), increasing polypharmacy (4.15, 3.26 to 5.29 for 10 or more repeat prescriptions), increasing numbers of primary care appointments (3.04, 2.48 to 3.73 for over 12 appointments in the year) and referrals to specialist pain services (5.17, 4.37 to 6.12). Compared with women under 50 years, men under 50 were less likely to step down once prescribed stronger opioids (0.53, 0.37 to 0.75). CONCLUSIONS: While clinicians should be alert to patients at risk of escalated opioid prescribing, much prescribing variation may be attributable to clinical behaviour. Effective strategies targeting clinicians and patients are needed to curb rising prescribing, especially of stronger opioids.

Action to Support Practices Implement Research Evidence (ASPIRE): protocol for a cluster-randomised evaluation of adaptable implementation packages targeting 'high impact' clinical practice recommendations in general practice.

BACKGROUND: There are recognised gaps between evidence and practice in general practice, a setting which provides particular challenges for implementation. We earlier screened clinical guideline recommendations to derive a set of 'high impact' indicators based upon criteria including potential for significant patient benefit, scope for improved practice and amenability to measurement using routinely collected data. We aim to evaluate the effectiveness and cost-effectiveness of a multifaceted, adaptable intervention package to implement four targeted, high impact recommendations in general practice. METHODS/DESIGN: The research programme Action to Support Practice Implement Research Evidence (ASPIRE) includes a pair of pragmatic cluster-randomised trials which use a balanced incomplete block design. Clusters are general practices in West Yorkshire, United Kingdom (UK), recruited using an 'opt-out' recruitment process. The intervention package adapted to each recommendation includes combinations of audit and feedback, educational outreach visits and computerised prompts with embedded behaviour change techniques selected on the basis of identified needs and barriers to change. In trial 1, practices are randomised to adapted interventions targeting either diabetes control or risky prescribing and those in trial 2 to adapted interventions targeting either blood pressure control in patients at risk of cardiovascular events or anticoagulation in atrial fibrillation. The respective primary endpoints comprise achievement of all recommended target levels of haemoglobin A1c (HbA1c), blood pressure and cholesterol in patients with type 2 diabetes, a composite indicator of risky prescribing, achievement of recommended blood pressure targets for specific patient groups and anticoagulation prescribing in patients with atrial fibrillation. We are also randomising practices to a fifth, non-intervention control group to further assess Hawthorne effects. Outcomes will be assessed using routinely collected data extracted 1 year after randomisation. Economic modelling will estimate intervention cost-effectiveness. A process evaluation involving eight non-trial practices will examine intervention delivery, mechanisms of action and unintended consequences. DISCUSSION: ASPIRE will provide 'real-world' evidence about the effects, cost-effectiveness and delivery of adapted intervention packages targeting high impact recommendations. By implementing our adaptable intervention package across four distinct clinical topics, and using 'opt-out' recruitment, our findings will provide evidence of wider generalisability. TRIAL REGISTRATION: ISRCTN91989345.

Optimizing primary care research participation: a comparison of three recruitment methods in data-sharing studies.

BACKGROUND: Recruitment of representative samples in primary care research is essential to ensure high-quality, generalizable results. This is particularly important for research using routinely recorded patient data to examine the delivery of care. Yet little is known about how different recruitment strategies influence the characteristics of the practices included in research. OBJECTIVE: We describe three approaches for recruiting practices to data-sharing studies, examining differences in recruitment levels and practice representativeness. METHODS: We examined three studies that included varying populations of practices from West Yorkshire, UK. All used anonymized patient data to explore aspects of clinical practice. Recruitment strategies were 'opt-in', 'mixed opt-in and opt-out' and 'opt-out'. We compared aggregated practice data between recruited and not-recruited practices for practice list size, deprivation, chronic disease management, patient experience and rates of unplanned hospital admission. RESULTS: The opt-out strategy had the highest recruitment (80%), followed by mixed (70%) and opt-in (58%). Practices opting-in were larger (median 7153 versus 4722 patients, P = 0.03) than practices that declined to opt-in. Practices recruited by mixed approach were larger (median 7091 versus 5857 patients, P = 0.04) and had differences in the clinical quality measure (58.4% versus 53.9% of diabetic patients with HbA1c ≤ 59 mmol/mol, P < 0.01). We found no differences between practices recruited and not recruited using the opt-out strategy for any demographic or quality of care measures. CONCLUSION: Opt-out recruitment appears to be a relatively efficient approach to ensuring participation of typical general practices. Researchers should, with appropriate ethical safeguards, consider opt-out recruitment of practices for studies involving anonymized patient data sharing.

Does a local financial incentive scheme reduce inequalities in the delivery of clinical care in a socially deprived community? A longitudinal data analysis.

BACKGROUND: Socioeconomic deprivation is associated with inequalities in health care and outcomes. Despite concerns that the Quality and Outcomes Framework pay-for-performance scheme in the UK would exacerbate inequalities in primary care delivery, gaps closed over time. Local schemes were promoted as a means of improving clinical engagement by addressing local health priorities. We evaluated equity in achievement of target indicators and practice income for one local scheme. METHODS: We undertook a longitudinal survey over four years of routinely recorded clinical data for all 83 primary care practices. Sixteen indicators were developed that covered five local clinical and public health priorities: weight management; alcohol consumption; learning disabilities; osteoporosis; and chlamydia screening. Clinical indicators were logit transformed from a percentage achievement scale and modelled allowing for clustering of repeated measures within practices. This enabled our study of target achievements over time with respect to deprivation. Practice income was also explored. RESULTS: Higher practice deprivation was associated with poorer performance for five indicators: alcohol use registration (OR 0.97; 95 % confidence interval 0.96,0.99); recorded chlamydia test result (OR 0.97; 0.94,0.99); osteoporosis registration (OR 0.98; 0.97,0.99); registration of repeat prednisolone prescription (OR 0.98; 0.96,0.99); and prednisolone registration with record of dual energy X-ray absorptiometry (DEXA) scan/referral (OR 0.92; 0.86,0.97); practices in deprived areas performed better for one indicator (registration of osteoporotic fragility fracture (OR 1.26; 1.04,1.51). The deprivation-achievement gap widened for one indicator (registered females aged 65-74 with a fracture referred for a DEXA scan; OR 0.97; 0.95,0.99). Two other indicators indicated a similar trend over two years before being withdrawn (registration of fragility fracture and over-75 s with a fragility fracture assessed and treated for osteoporosis risk). For one indicator the deprivation-achievement gap reduced over time (repeat prednisolone prescription (OR 1.01; 1.01,1.01). Larger practices and those serving more affluent areas earned more income per patient than smaller practices and those serving more deprived areas (t = -3.99; p =0.0001). CONCLUSIONS: Any gaps in achievement between practices were modest but mostly sustained or widened over the duration of the scheme. Given that financial rewards may not reflect the amount of work undertaken by practices serving more deprived patients, future pay-for-performance schemes also need to address fairness of rewards in relation to workload.

'Just another incentive scheme': a qualitative interview study of a local pay-for-performance scheme for primary care.

BACKGROUND: A range of policy initiatives have addressed inequalities in healthcare and health outcomes. Local pay-for-performance schemes for primary care have been advocated as means of enhancing clinical ownership of the quality agenda and better targeting local need compared with national schemes such as the UK Quality and Outcomes Framework (QOF). We investigated whether professionals' experience of a local scheme in one English National Health Service (NHS) former primary care trust (PCT) differed from that of the national QOF in relation to the goal of reducing inequalities. METHODS: We conducted retrospective semi-structured interviews with primary care professionals implementing the scheme and those involved in its development. We purposively sampled practices with varying levels of population socio-economic deprivation and achievement. Interviews explored perceptions of the scheme and indicators, likely mechanisms of influence on practice, perceived benefits and harms, and how future schemes could be improved. We used a framework approach to analysis. RESULTS: Thirty-eight professionals from 16 general practices and six professionals involved in developing local indicators participated. Our findings cover four themes: ownership, credibility of the indicators, influences on behaviour, and exacerbated tensions. We found little evidence that the scheme engendered any distinctive sense of ownership or experiences different from the national scheme. Although the indicators and their evidence base were seldom actively questioned, doubts were expressed about their focus on health promotion given that eventual benefits relied upon patient action and availability of local resources. Whilst practices serving more affluent populations reported status and patient benefit as motivators for participating in the scheme, those serving more deprived populations highlighted financial reward. The scheme exacerbated tensions between patient and professional consultation agendas, general practitioners benefitting directly from incentives and nurses who did much of the work, and practices serving more and less affluent populations which faced different challenges in achieving targets. CONCLUSIONS: The contentious nature of pay-for-performance was not necessarily reduced by local adaptation. Those developing future schemes should consider differential rewards and supportive resources for practices serving more deprived populations, and employing a wider range of levers to promote professional understanding and ownership of indicators.