Search

Abstract Background Healthcare workers perform clinical behaviours which impact on patient diagnoses, care, treatment and recovery. Some methods of supporting healthcare workers in changing their behaviour make use of social norms by exposing healthcare workers to the beliefs, values, attitudes or behaviours of a reference group or person. This review aimed to evaluate evidence on (i) the effect of social norms interventions on healthcare worker clinical behaviour change and (ii) the contexts, modes of delivery and behaviour change techniques (BCTs) associated with effectiveness. Methods Systematic review and meta-analysis of randomised controlled trials. Searches were undertaken in seven databases. The primary outcome was compliance with a desired healthcare worker clinical behaviour and the secondary outcome was patient health outcomes. Outcomes were converted into standardised mean differences (SMDs). We performed meta-analyses and presented forest plots, stratified by five social norms BCTs (social comparison, credible source, social reward, social incentive and information about others’ approval). Sources of variation in social norms BCTs, context and mode of delivery were explored using forest plots, meta-regression and network meta-analysis. Results Combined data from 116 trials suggested that social norms interventions were associated with an improvement in healthcare worker clinical behaviour outcomes of 0.08 SMDs (95%CI 0.07 to 0.10) (n = 100 comparisons), and an improvement in patient health outcomes of 0.17 SMDs (95%CI 0.14 to 0.20) (n = 14), on average. Heterogeneity was high, with an overall I 2 of 85.4% (healthcare worker clinical behaviour) and 91.5% (patient health outcomes). Credible source was more effective on average, compared to control conditions (SMD 0.30, 95%CI 0.13 to 0.47, n = 7). Social comparison also appeared effective, both on its own (SMD 0.05, 95%CI 0.03 to 0.08, n = 33) and with other BCTs, and seemed particularly effective when combined with prompts/cues (0.33, 95%CI 0.22 to 0.44, n = 5). Conclusions Social norms interventions appeared to be an effective method of changing the clinical behaviour of healthcare workers and have a positive effect on patient health outcomes in a variety of health service contexts. Although the overall result is modest and variable, there is the potential for social norms interventions to be applied at large scale. Trial registration PROSPERO CRD42016045718 .

Abstract Background Improving medication safety is a major concern in primary care settings worldwide. The Salford Medication safety dASHboard (SMASH) intervention provided general practices in Salford (Greater Manchester, UK) with feedback on their safe prescribing and monitoring of medications through an online dashboard, and input from practice-based trained clinical pharmacists. In this study we explored how staff working in general practices used the SMASH dashboard to improve medication safety, through interactions with the dashboard to identify potential medication safety hazards and their workflow to resolve identified hazards. Methods We used a mixed-methods study design involving quantitative data from dashboard user interaction logs from 43 general practices during the first year of receiving the SMASH intervention, and qualitative data from semi-structured interviews with 22 pharmacists and physicians from 18 practices in Salford. Results Practices interacted with the dashboard a median of 12.0 (interquartile range, 5.0–15.2) times per month during the first quarter of use to identify and resolve potential medication safety hazards, typically starting with the most prevalent hazards or those they perceived to be most serious. Having observed a potential hazard, pharmacists and practice staff worked together to resolve that in a sequence of steps (1) verifying the dashboard information, (2) reviewing the patient’s clinical records, and (3) deciding potential changes to the patient’s medicines. Over time, dashboard use transitioned towards regular but less frequent (median of 5.5 [3.5–7.9] times per month) checks to identify and resolve new cases. The frequency of dashboard use was higher in practices with a larger number of at-risk patients. In 24 (56%) practices only pharmacists used the dashboard; in 12 (28%) use by other practice staff increased as pharmacist use declined after the initial intervention period; and in 7 (16%) there was mixed use by both pharmacists and practice staff over time. Conclusions An online medication safety dashboard enabled pharmacists to identify patients at risk of potentially hazardous prescribing. They subsequently worked with GPs to resolve risks on a case-by-case basis, but there were marked variations in processes between some practices. Workload diminished over time as it shifted towards resolving new cases of hazardous prescribing.

Abstract Background Risk prediction models are commonly used in practice to inform decisions on patients’ treatment. Uncertainty around risk scores beyond the confidence interval is rarely explored. We conducted an uncertainty analysis of the QRISK prediction tool to evaluate the robustness of individual risk predictions with varying modelling decisions. Methods We derived a cohort of patients eligible for cardiovascular risk prediction from the Clinical Practice Research Datalink (CPRD) with linked hospitalisation and mortality records (N = 3,855,660). Risk prediction models were developed using the methods reported for QRISK2 and 3, before adjusting for additional risk factors, a secular trend, geographical variation in risk and the method for imputing missing data when generating a risk score (model A–model F). Ten-year risk scores were compared across the different models alongside model performance metrics. Results We found substantial variation in risk on the individual level across the models. The 95 percentile range of risks in model F for patients with risks between 9 and 10% according to model A was 4.4–16.3% and 4.6–15.8% for females and males respectively. Despite this, the models were difficult to distinguish using common performance metrics (Harrell’s C ranged from 0.86 to 0.87). The largest contributing factor to variation in risk was adjusting for a secular trend (HR per calendar year, 0.96 [0.95–0.96] and 0.96 [0.96–0.96]). When extrapolating to the UK population, we found that 3.8 million patients may be reclassified as eligible for statin prescription depending on the model used. A key limitation of this study was that we could not assess the variation in risk that may be caused by risk factors missing from the database (such as diet or physical activity). Conclusions Risk prediction models that use routinely collected data provide estimates strongly dependent on modelling decisions. Despite this large variability in patient risk, the models appear to perform similarly according to standard performance metrics. Decision-making should be supplemented with clinical judgement and evidence of additional risk factors. The largest source of variability, a secular trend in CVD incidence, can be accounted for and should be explored in more detail.

Abstract Background Health workers routinely carry out clinical behaviours, such as prescribing, test-ordering or hand-washing, which impact on patient diagnoses, care, treatment and recovery. Social norms are the implicit or explicit rules that a group uses to determine values, beliefs, attitudes and behaviours. A social norms intervention seeks to change the clinical behaviour of a target health worker by exposing them to the values, beliefs, attitudes or behaviours of a reference group or person. This study aims to find out whether or not social norms interventions are effective ways of encouraging health workers to carry out desired behaviours and to identify which types of social norms intervention, if any, are most effective. Methods A systematic review will be conducted. The inclusion criteria are a population of health professionals, a social norms intervention that seeks to change a clinical behaviour, and randomised controlled trials. Searches will be undertaken in MEDLINE, EMBASE, CINAHL, British Nursing Index, ISI Web of Science, PsycINFO and Cochrane trials. Titles and abstracts will be reviewed against the inclusion criteria to exclude any that are clearly ineligible. Two reviewers will independently screen all the remaining full texts to identify relevant papers. For studies which meet our inclusion criteria, two reviewers will extract data independently, code for behaviour change techniques and assess quality using the Cochrane risk of bias tool. The primary outcome measure will be compliance with desired behaviour. To assess the effect of social norms on the behaviour of health workers, we will perform fixed effects meta-analysis and present forest plots, stratified by behaviour change technique. We will explore sources of variation using meta-regression and may use multi-component-based network meta-analysis to explore which forms of social norms are more likely to be effective, if our data meet the necessary requirements. Discussion The study will provide evidence regarding the effectiveness of different methods of applying social norms to change the clinical behaviour of health professionals. We will disseminate the research to academics, health workers and members of the public and use the findings from the review to plan future research on the use of social norms with health workers. Systematic review registration PROSPERO CRD42016045718. Future protocol changes will be clearly stated in PROSPERO.

Abstract Background Providing health professionals with quantitative summaries of their clinical performance when treating specific groups of patients (“feedback”) is a widely used quality improvement strategy, yet systematic reviews show it has varying success. Theory could help explain what factors influence feedback success, and guide approaches to enhance effectiveness. However, existing theories lack comprehensiveness and specificity to health care. To address this problem, we conducted the first systematic review and synthesis of qualitative evaluations of feedback interventions, using findings to develop a comprehensive new health care-specific feedback theory. Methods We searched MEDLINE, EMBASE, CINAHL, Web of Science, and Google Scholar from inception until 2016 inclusive. Data were synthesised by coding individual papers, building on pre-existing theories to formulate hypotheses, iteratively testing and improving hypotheses, assessing confidence in hypotheses using the GRADE-CERQual method, and summarising high-confidence hypotheses into a set of propositions. Results We synthesised 65 papers evaluating 73 feedback interventions from countries spanning five continents. From our synthesis we developed Clinical Performance Feedback Intervention Theory (CP-FIT), which builds on 30 pre-existing theories and has 42 high-confidence hypotheses. CP-FIT states that effective feedback works in a cycle of sequential processes; it becomes less effective if any individual process fails, thus halting progress round the cycle. Feedback’s success is influenced by several factors operating via a set of common explanatory mechanisms: the feedback method used, health professional receiving feedback, and context in which feedback takes place. CP-FIT summarises these effects in three propositions: (1) health care professionals and organisations have a finite capacity to engage with feedback, (2) these parties have strong beliefs regarding how patient care should be provided that influence their interactions with feedback, and (3) feedback that directly supports clinical behaviours is most effective. Conclusions This is the first qualitative meta-synthesis of feedback interventions, and the first comprehensive theory of feedback designed specifically for health care. Our findings contribute new knowledge about how feedback works and factors that influence its effectiveness. Internationally, practitioners, researchers, and policy-makers can use CP-FIT to design, implement, and evaluate feedback. Doing so could improve care for large numbers of patients, reduce opportunity costs, and improve returns on financial investments. Trial registration PROSPERO, CRD42015017541

Abstract Background Audit and feedback (A&F) is a common quality improvement strategy with highly variable effects on patient care. It is unclear how A&F effectiveness can be maximised. Since the core mechanism of action of A&F depends on drawing attention to a discrepancy between actual and desired performance, we aimed to understand current and best practices in the choice of performance comparator. Methods We described current choices for performance comparators by conducting a secondary review of randomised trials of A&F interventions and identifying the associated mechanisms that might have implications for effective A&F by reviewing theories and empirical studies from a recent qualitative evidence synthesis. Results We found across 146 trials that feedback recipients’ performance was most frequently compared against the performance of others (benchmarks; 60.3%). Other comparators included recipients’ own performance over time (trends; 9.6%) and target standards (explicit targets; 11.0%), and 13% of trials used a combination of these options. In studies featuring benchmarks, 42% compared against mean performance. Eight (5.5%) trials provided a rationale for using a specific comparator. We distilled mechanisms of each comparator from 12 behavioural theories, 5 randomised trials, and 42 qualitative A&F studies. Conclusion Clinical performance comparators in published literature were poorly informed by theory and did not explicitly account for mechanisms reported in qualitative studies. Based on our review, we argue that there is considerable opportunity to improve the design of performance comparators by (1) providing tailored comparisons rather than benchmarking everyone against the mean, (2) limiting the amount of comparators being displayed while providing more comparative information upon request to balance the feedback’s credibility and actionability, (3) providing performance trends but not trends alone, and (4) encouraging feedback recipients to set personal, explicit targets guided by relevant information.

Abstract Background In primary health care, patient safety failures can arise in service access, doctor-patient relationships, communication between care providers, relational and management continuity, or technical procedures. Through the lens of multimorbidty, and using qualitative ethnographic methods, our study aimed to illuminate safety issues in primary care. Methods Data were triangulated from electronic health records (EHRs); observation of primary care consultations; annual interviews with patients, (informal) care providers and GPs. A thematic analysis of observation, interview and field note material sought to describe the patient safety issues encountered and any associated factors or processes. A more detailed longitudinal description of 6 cases was used to contextualise safety issues identified in observation, interviews and EHRs. Results Twenty-six patients were recruited. Events which could lead to harm were found in all areas of a framework based on published literature. “Under” and “over” consultation as a precursor of safety failures emerged through thematic analysis of observation and interview material. Other findings concerned workload (for doctors and patients) and the limitations of short consultation times. There were differences in health data collected directly from the patients versus that found in EHRs. Examples included reference to a stroke history and diagnoses for CKD and hypertension. Case study analysis revealed specific issues which appeared contextual to safety concerns, mostly around the management of polypharmacy and patient medication adherence. Clinical imperatives appear around risk management, but the study findings point to a potential conflict with patient expectations around investigation, diagnosis and treatment. Discussion Patient safety work involves further burdens on top of existing workload for both clinicians and patients. In this conceptualisation, safety work seemingly forms part of a negative feedback loop with patient safety itself. A line of argument drawn from the triangulation of findings from different sources, points to a tension between the desirability of a minimally disruptive medicine versus safety risks possibly associated with ‘under’ or ‘over’ consultation. Multimorbidity acts as a magnifier of tensions in the delivery of health services and quality care in general practice. More attention should be put on system design than patient or professional behaviour.

Abstract Background Following an initial NHS Health Check appointment, the National Institute for Health and Care Excellence (NICE) suggest patients with QRISK2 scores of ≥10% should be offered advice on lifestyle and the risks and benefits of starting a statin. NICE recommend GPs should ascertain patients’ pre-existing knowledge of cardiovascular disease risk, explore health beliefs, assess readiness to change, offer support, and engage family members. Condensing this complex discussion into a short consultation may result in inadequate patient understanding of the benefits of preventive measures. An alternative approach is needed. We propose a digital adjunct giving patients the opportunity to interact with their health check results from home before returning to see their GP. Before embarking on funding applications we sought the views of patients and members of the public. Methods We consulted the Primary Care Research in Manchester Engagement Resource (PRIMER), an established departmental Patient and Public Involvement (PPI) group (N = 9) and then ran a workshop with 19 members of the public, co-facilitated by 4 members of PRIMER. Following a brief presentation on the background to the project, attendees were split into four groups and introduced to Ketso, a toolkit for creative engagement. Ketso was used to encourage group discussions regarding the project idea. Results This PPI work improved the study design and proposed intervention. Discussions focussed on three themes: 1) positive feedback, 2) challenges and solutions, and 3) improvements/alternatives. Positive feedback included benefits to the NHS and patients. Challenges identified related to: 1) access, 2) data security, 3) engagement, and 4) negative consequences. Workshop members generated various solutions to these challenges and made additional suggestions for improvement relating to: 1) population (e.g. also including those with QRISK2 scores ≤10%), 2) duration (e.g. ongoing access to provide continued feedback), and 3) platform content (e.g. signposting to relevant services). Conclusions This PPI work helped identify potential challenges and solutions not previously considered by the research team. Findings have informed the subsequent intervention design and strengthened the bid for funding. We aim to ensure ongoing patient and public involvement in all future stages.

Abstract Background In primary care, older patients with multimorbidity (two or more long-term conditions) are especially likely to experience patient safety incidents. Risks to safety in this setting arise as a result of patient, staff and system factors; particularly where these interact or fail to do so. Recent research and policy highlight the important contribution patients can make to improving safety. Older patients with multimorbidity may have the most to gain from increasing their involvement but before interventions can be developed to support them to improve their patient safety, more needs to be known about how this is threatened and how patients respond to perceived threats. We sought to identify and describe threats to patient safety in primary care among older people with multimorbidity, to provide a better understanding of how these are experienced and to inform the development of interventions to reduce risks to patient safety. Methods Twenty-six older people, aged 65 or over, with multimorbidity were recruited to a longitudinal qualitative study. At baseline, data on their health and healthcare were collected through semi-structured interviews. Data were analysed thematically, using a framework developed from a previous synthesis of qualitative studies of patient safety in primary care. Results Threats to patient safety were organised into six themes, across three domains of health and care. These encompassed all aspects of the patient journey, from access to everyday management. Across the journey, many issues arose due to poor communication, and uncoordinated care created extra burdens for patients and healthcare staff. Patients’ sense of safety and trust in their care providers were especially threatened when they felt their needs were ignored, or when they perceived responses from staff as inappropriate or insensitive. Conclusions For older patients with multimorbidity, patient safety is intrinsically linked to the challenges people face when managing health conditions, navigating the healthcare system, and negotiating care. We consider the implications of this for the development of interventions to reduce threats to patient safety. Potential patient-centred mechanisms include providing patients with more realistic expectations for primary care, and supporting them to communicate their needs and concerns more effectively.

Abstract Background Audit and feedback is a common intervention for supporting clinical behaviour change. Increasingly, health data are available in electronic format. Yet, little is known regarding if and how electronic audit and feedback (e-A&F) improves quality of care in practice. Objective The study aimed to assess the effectiveness of e-A&F interventions in a primary care and hospital context and to identify theoretical mechanisms of behaviour change underlying these interventions. Methods In August 2016, we searched five electronic databases, including MEDLINE and EMBASE via Ovid, and the Cochrane Central Register of Controlled Trials for published randomised controlled trials. We included studies that evaluated e-A&F interventions, defined as a summary of clinical performance delivered through an interactive computer interface to healthcare providers. Data on feedback characteristics, underlying theoretical domains, effect size and risk of bias were extracted by two independent review authors, who determined the domains within the Theoretical Domains Framework (TDF). We performed a meta-analysis of e-A&F effectiveness, and a narrative analysis of the nature and patterns of TDF domains and potential links with the intervention effect. Results We included seven studies comprising of 81,700 patients being cared for by 329 healthcare professionals/primary care facilities. Given the extremely high heterogeneity of the e-A&F interventions and five studies having a medium or high risk of bias, the average effect was deemed unreliable. Only two studies explicitly used theory to guide intervention design. The most frequent theoretical domains targeted by the e-A&F interventions included ‘knowledge’, ‘social influences’, ‘goals’ and ‘behaviour regulation‘, with each intervention targeting a combination of at least three. None of the interventions addressed the domains ‘social/professional role and identity’ or ‘emotion’. Analyses identified the number of different domains coded in control arm to have the biggest role in heterogeneity in e-A&F effect size. Conclusions Given the high heterogeneity of identified studies, the effects of e-A&F were found to be highly variable. Additionally, e-A&F interventions tend to implicitly target only a fraction of known theoretical domains, even after omitting domains presumed not to be linked to e-A&F. Also, little evaluation of comparative effectiveness across trial arms was conducted. Future research should seek to further unpack the theoretical domains essential for effective e-A&F in order to better support strategic individual and team goals.

The original article [1] contained an error in the abstract. The mentioned cohort size now correctly states ‘N = 3,855,660’.