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OBJECTIVE Developing primary care is an important current health policy goal in the U.S. and England. Information on patients' experience can help to improve the care of people with diabetes. We describe the experiences of people with diabetes in primary care and examine how these experiences vary with increasing comorbidity. RESEARCH DESIGN AND METHODS Using data from 906,578 responders to the 2012 General Practice Patient Survey (England), including 85,760 with self-reported diabetes, we used logistic regressions controlling for age, sex, ethnicity, and socioeconomic status to analyze patient experience using seven items covering three domains of primary care: access, continuity, and communication. RESULTS People with diabetes were significantly more likely to report better experience on six out of seven primary care items than people without diabetes after adjusting for age, sex, ethnicity, and socioeconomic status (adjusted differences 0.88-3.20%; odds ratios [ORs] 1.07-1.18; P < 0.001). Those with diabetes and additional comorbid long-term conditions were more likely to report worse experiences, particularly for access to primary care appointments (patients with diabetes alone compared with patients without diabetes: OR 1.22 [95% CI 1.17-1.28] and patients with diabetes plus three or more conditions compared with patients without diabetes: OR 0.87 [95% CI 0.83-0.91]). CONCLUSIONS People with diabetes in England report primary care experiences that are at least as good as those without diabetes for most domains of care. However, improvements in primary care are needed for diabetes patients with comorbid long-term conditions, including better access to appointments and improved communication. [ABSTRACT FROM AUTHOR]

Background: There has been significant investment in pharmacists working in UK general practice to improve the effective and safe use of medicines. However, evidence of how to optimise collaboration between GPs and pharmacists in the context of polypharmacy (multiple medication) is lacking., Aim: To explore GP and pharmacist views and experiences of in-person, interprofessional collaborative discussions (IPCDs) as part of a complex intervention to optimise medication use for patients with polypharmacy in general practice., Design and Setting: A mixed-method process evaluation embedded within the Improving Medicines use in People with Polypharmacy in Primary Care (IMPPP) trial conducted in Bristol and the West Midlands, between February 2021 and September 2023., Method: Audio-recordings of IPCDs between GPs and pharmacists, along with individual semi-structured interviews to explore their reflections on these discussions, were used. All recordings were transcribed verbatim and analysed thematically., Results: A total of 14 practices took part in the process evaluation from February 2022 to September 2023; 17 IPCD meetings were audio-recorded, discussing 30 patients (range 1-6 patients per meeting). In all, six GPs and 13 pharmacists were interviewed. The IPCD was highly valued by GPs and pharmacists who described benefits, including: strengthening their working relationship; gaining in confidence to manage more complex patients; and learning from each other. It was often challenging, however, to find time for the IPCDs., Conclusion: The model of IPCD used in this study provided protected time for GPs and pharmacists to work together to deliver whole-patient care, with both professions finding this beneficial. Protected time for interprofessional liaison and collaboration, and structured interventions may facilitate improved patient care., (© The Authors.)

Background: Deprescribing of antihypertensive medications is recommended for some older patients with low blood pressure and frailty. The OPTiMISE trial showed that this deprescribing can be achieved with no differences in blood pressure control at 3 months compared with usual care. We aimed to examine effects of deprescribing on longer-term hospitalisation and mortality., Methods: This randomised controlled trial enrolled participants from 69 general practices across central and southern England. Participants aged 80 years or older, with systolic blood pressure less than 150 mm Hg and who were receiving two or more antihypertensive medications, were randomly assigned (1:1) to antihypertensive medication reduction (removal of one antihypertensive) or usual care. General practitioners and participants were aware of the treatment allocation following randomisation but individuals responsible for analysing the data were masked to the treatment allocation throughout the study. Participants were followed up via their primary and secondary care electronic health records at least 3 years after randomisation. The primary outcome was time to all-cause hospitalisation or mortality. Intention-to-treat analyses were done using Cox regression modelling. A per-protocol analysis of the primary outcome was also done, excluding participants from the intervention group who did not reduce treatment or who had medication reinstated during the initial trial 12-week follow-up period. This study is registered with the European Union Drug Regulating Authorities Clinical Trials Database (EudraCT2016-004236-38) and the ISRCTN Registry (ISRCTN97503221)., Findings: Between March 20, 2017, and Sept 30, 2018, a total of 569 participants were randomly assigned. Of these, 564 (99%; intervention=280; control=284) were followed up for a median of 4·0 years (IQR 3·7-4·3). Participants had a mean age of 84·8 years (SD 3·4) at baseline and 273 (48%) were women. Medication reduction was sustained in 109 participants at follow-up (51% of the 213 participants alive in the intervention group). Participants in the intervention group had a larger reduction in antihypertensives than the control group (adjusted mean difference -0·35 drugs [95% CI -0·52 to -0·18]). Overall, 202 (72%) participants in the intervention group and 218 (77%) participants in the control group experienced hospitalisation or mortality during follow-up (adjusted hazard ratio [aHR] 0·93 [95% CI 0·76 to 1·12]). There was some evidence that the proportion of participants experiencing the primary outcome in the per-protocol population was lower in the intervention group (aHR 0·80 [0·64 to 1·00])., Interpretation: Half of participants sustained medication reduction with no evidence of an increase in all-cause hospitalisation or mortality. These findings suggest that an antihypertensive deprescribing intervention might be safe for people aged 80 years or older with controlled blood pressure taking two or more antihypertensives., Funding: British Heart Foundation and National Institute for Health and Care Research., Competing Interests: Declaration of interests JPS reports funding from the Wellcome Trust/Royal Society, National Institute for Health and Care Research (NIHR), British Heart Foundation, and Stroke Association; payment for consultancy from DoctorLink; is a Data Safety Monitoring Board member for the Hypertension Treatment in Nigeria Study sponsored by Northwestern University; and is Secretary and trustee for the British and Irish Hypertension Society. GAF is Board non-executive Director for the National Institute for Health and Care Excellence. FDRH reports honoraria for lectures from Pfizer/BMS, Bayer, Boehringer Ingelheim, and AstraZeneca; and is chair of the European Primary Care Cardiovascular Society and International Primary Care Cardiovascular Society. SdL has received research grants to his university for investigator-led cardiometabolic research from Bristol Myers Squibb, Eli Lilly, GSK, MSD, Novo Nordisk, Pfizer, Sanofi, and Seqirus; has been a member of advisory boards for AstraZeneca, GSK, Sanofi, and Seqirus; and has received medical writing support provided by AstraZeneca, GSK, and Pfizer. JM reports funding from an NIHR Senior Investigator Award and honoraria for lectures from Bristol Myers Squibb and Pfizer. RAP reports NIHR funding to his institution for other research related to medicines use and Medical Research Council funding to his institution unrelated to this project. L-MY reports NIHR funding to her institution for other research. RJM reports funding from the NIHR, British Heart Foundation, and Stroke Association; has received royalties, consulting fees (paid to his institution), and research equipment from Omron; has received royalties from Sensyne; and has received honoraria (paid to his institution) for lectures from the Finnish Hypertension Society and Canadian Hypertension Society., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: An increasing number of people are using multiple medications each day, named polypharmacy. This is driven by an ageing population, increasing multimorbidity, and single disease-focussed guidelines. Medications carry obvious benefits, yet polypharmacy is also linked to adverse consequences including adverse drug events, drug-drug and drug-disease interactions, poor patient experience and wasted resources. Problematic polypharmacy is 'the prescribing of multiple medicines inappropriately, or where the intended benefits are not realised'. Identifying people with problematic polypharmacy is complex, as multiple medicines can be suitable for people with several chronic conditions requiring more treatment. Hence, polypharmacy is often potentially problematic, rather than always inappropriate, dependent on clinical context and individual benefit vs risk. There is a need to improve how we identify and evaluate these patients by extending beyond simple counts of medicines to include individual factors and long-term conditions., Aim: To produce a Polypharmacy Assessment Score to identify a population with unusual levels of prescribing who may be at risk of potentially problematic polypharmacy., Methods: Analyses will be performed in three parts: 1. A prediction model will be constructed using observed medications count as the dependent variable, with age, gender and long-term conditions as independent variables. A 'Polypharmacy Assessment Score' will then be constructed through calculating the differences between the observed and expected count of prescribed medications, thereby highlighting people that have unexpected levels of prescribing. Parts 2 and 3 will examine different aspects of validity of the Polypharmacy Assessment Score: 2. To assess 'construct validity', cross-sectional analyses will evaluate high-risk prescribing within populations defined by a range of Polypharmacy Assessment Scores, using both explicit (STOPP/START criteria) and implicit (Medication Appropriateness Index) measures of inappropriate prescribing. 3. To assess 'predictive validity', a retrospective cohort study will explore differences in clinical outcomes (adverse drug reactions, unplanned hospitalisation and all-cause mortality) between differing scores., Discussion: Developing a cross-cutting measure of polypharmacy may allow healthcare professionals to prioritise and risk stratify patients with polypharmacy using unusual levels of prescribing. This would be an improvement from current approaches of either using simple cutoffs or narrow prescribing criteria., (© 2024. Crown.)

Background: Providing safety-netting advice (SNA) in out-of-hours primary care is a recognised standard of safe care but it is not known how frequently this occurs in practice., Aim: Assess the frequency and type of SNA documented in out-of-hours primary care and explore factors associated with its presence., Design and Setting: Retrospective cohort using the Birmingham Out-of-hours General Practice Research Database., Method: A stratified sample of 30 adult consultation records per month from July 2013 to February 2020 were assessed using a safety-netting coding tool. Associations were tested using linear and logistic regression., Results: The overall frequency of SNA per consultation was 78.0%, increasing from 75.7% (2014) to 81.5% (2019). The proportion of specific SNA and the average number of symptoms patients were told to look out for increased with time. The most common symptom to look out for was if the patients' condition worsened followed by if their symptoms persisted, but only one in five consultations included a time-frame to reconsult for persistent symptoms. SNA was more frequently documented in face-to-face treatment-centre encounters compared to telephone-consultations (Odds Ratio [OR]=1.77, p=0.02), for possible infections (OR=1.53, p=0.006), and less frequently for mental (vs. physical) health consultations (OR=0.33, p=0.002) and where follow-up was planned (OR=0.34, p<0.001)., Conclusion: The frequency of SNA documented in OOH was higher than previously reported during in-hours care. Over time, the frequency of SNA and proportion that contained specific advice increased, however this study highlights potential consultations where SNA could be improved, such as mental health and telephone consultations., (Copyright © 2024, The Authors.)

Introduction: Polypharmacy and multimorbidity pose escalating challenges. Despite numerous attempts, interventions have yet to show consistent improvements in health outcomes. A key factor may be varied approaches to targeting patients for intervention., Objectives: To explore how patients are targeted for intervention by examining the literature with respect to: understanding how polypharmacy is defined; identifying problematic polypharmacy in practice; and addressing problematic polypharmacy through interventions., Design: We performed a scoping review as defined by the Joanna Briggs Institute., Setting: The focus was on primary care settings., Data Sources: Medline, Embase, Cumulative Index to Nursing and Allied Health Literature and Cochrane along with ClinicalTrials.gov, Science.gov and WorldCat.org were searched from January 2004 to February 2024., Eligibility Criteria: We included all articles that had a focus on problematic polypharmacy in multimorbidity and primary care, incorporating multiple types of evidence, such as reviews, quantitative trials, qualitative studies and policy documents. Articles focussing on a single index disease or not written in English were excluded., Extraction and Analysis: We performed a narrative synthesis, comparing themes and findings across the collective evidence to draw contextualised insights and conclusions., Results: In total, 157 articles were included. Case-finding methods often rely on basic medication counts (often five or more) without considering medical history or whether individual medications are clinically appropriate. Other approaches highlight specific drug indicators and interactions as potentially inappropriate prescribing, failing to capture a proportion of patients not fitting criteria. Different potentially inappropriate prescribing criteria also show significant inconsistencies in determining the appropriateness of medications, often neglecting to consider multimorbidity and underprescribing. This may hinder the identification of the precise population requiring intervention., Conclusions: Improved strategies are needed to target patients with polypharmacy, which should consider patient perspectives, individual factors and clinical appropriateness. The development of a cross-cutting measure of problematic polypharmacy that consistently incorporates adjustment for multimorbidity may be a valuable next step to address frequent confounding., Competing Interests: Competing interests: DA reports research funding from Abbvie, Almirall, Celgene, Eli Lilly, Novartis, UCB and the Leo Foundation outside the submitted work. The other authors have no conflicts of interest to disclose., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Eliciting patients' ideas, concerns, expectations, and whether a problem has an 'effect' on their life (ICEE), is a widely recommended communication technique. However, it is not known how frequently ICEE components are raised in UK GP consultations., Aim: To assess the frequency of ICEE in routine GP consultations with adult patients and explore variables associated with ICEE., Design & Setting: An observational study was undertaken. It involved secondary analysis of a pre-existing archive of video-recorded, face-to-face GP consultations in the UK., Method: Observational coding of 92 consultations took place. Associations were assessed using binomial and ordered logistic regression., Results: Most consultations included at least one ICEE component (90.2%). The most common ICEE component per consultation was patient ideas (79.3%), followed by concerns (55.4%), expectations (51.1%), and then effects on life (42.4%). For all ICEE components patients more commonly initiated the ICEE dialogue, and in only three consultations (3.3%) did GPs directly ask patients about their expectations. Problems that were acute (odds ratio [OR] 2.98, 95% confidence interval [CI] = 1.36 to 6.53, P = 0.007) or assessed by GPs aged ≥50 years (OR 2.10, 95% CI = 1.07 to 4.13, P = 0.030) were associated with more ICEE components. Problems assessed later in the consultation (OR 0.60 per problem order increase, 95% CI = 0.41 to 0.87, P = 0.007) by patients aged ≥75 years (OR 0.40, 95% CI = 0.16 to 0.98, P = 0.046) and from the most deprived cohort (OR 0.39, 95% CI = 0.17 to 0.92, P = 0.032) were associated with fewer ICEE components. Patient ideas were associated with more patients being 'very satisfied' post-consultation (OR 10.74, 95% CI = 1.60 to 72.0, P = 0.014) and the opposite was true of concerns (OR 0.14, 95% CI = 0.02 to 0.86, P = 0.034)., Conclusion: ICEE components were associated with patient satisfaction and demographic variables. Further research is required to assess if the way ICEE are communicated affects these associations and other potential confounders., (Copyright © 2023, The Authors.)

Background: Older housebound people are an under-researched group for whom achieving good primary health care can be resource intensive., Aims: To describe the characteristics and healthcare use of older (≥65 years) housebound people; explore clinician views on delivery of care to housebound people; and assess the feasibility of using a new network of healthcare professionals to deliver high quality research., Design & Setting: Retrospective observational study of electronic GP records and clinician survey in England., Method: Clinical members of a new UK research network called the Primary care Academic CollaboraTive (PACT) will collect the data. For part A, around 20 GP practices will be recruited and clinicians will identify 20 housebound and 20 non-housebound people, matched by age and gender (around 400 total in each group). Anonymised data will be collected on characteristics (age, gender, ethnicity, deprivation decile), long-term conditions, prescribed medicines, quality of healthcare (via Quality Outcomes Framework targets), and continuity of care. Reports with benchmarked practice-level data will be provided to practices to identify areas for quality improvement and to enhance engagement. For part B, 2-4 clinicians will be recruited from around 50 practices in England (around 150 clinicians) to complete a survey about delivery of healthcare for housebound people. For part C, data will be collected to assess the feasibility of using the PACT network to deliver primary care research., Conclusion: Older housebound people are a neglected group both in terms of research and clinical care. Understanding the characteristics and use of primary healthcare of housebound people will help identify how to improve their care., (Copyright © 2023, The Authors.)

Background: Prescribing of strong opioids and antibiotics impacts patient safety, yet little is known about the effects GP wellness has on overprescribing of both medications in primary care., Aim: To examine associations between strong opioid and antibiotic prescribing and practice- weighted GP burnout and wellness., Design and Setting: A retrospective cross-sectional study was undertaken using prescription data on strong opioids and antibiotics from the Oxford- Royal College of General Practitioners Research and Surveillance Centre linking to a GP wellbeing survey overlaying the same 4-month period from December 2019 to April 2020., Method: Patients prescribed strong opioids and antibiotics were the outcomes of interest., Results: Data for 40 227 patients (13 483 strong opioids and 26 744 antibiotics) were linked to 57 practices and 351 GPs. Greater strong opioid prescribing was associated with increased emotional exhaustion (incidence risk ratio [IRR] 1.19, 95% confidence interval [CI] = 1.10 to 1.24), depersonalisation (IRR 1.10, 95% CI = 1.01 to 1.16), job dissatisfaction (IRR 1.25, 95% CI = 1.19 to 1.32), diagnostic uncertainty (IRR 1.12, 95% CI = 1.08 to 1.19), and turnover intention (IRR 1.32, 95% CI = 1.27 to 1.37) in GPs. Greater antibiotic prescribing was associated with increased emotional exhaustion (IRR 1.19, 95% CI = 1.05 to 1.37), depersonalisation (IRR 1.24, 95% CI = 1.08 to 1.49), job dissatisfaction (IRR 1.11, 95% CI = 1.04 to 1.19), sickness-presenteeism (IRR 1.18, 95% CI = 1.11 to 1.25), and turnover intention (IRR 1.38, 95% CI = 1.31 to 1.45) in GPs. Increased strong opioid and antibiotic prescribing was also found in GPs working longer hours (IRR 3.95, 95% CI = 3.39 to 4.61; IRR 5.02, 95% CI = 4.07 to 6.19, respectively) and in practices in the north of England (1.96, 95% CI = 1.61 to 2.33; 1.56, 95% CI = 1.12 to 3.70, respectively)., Conclusion: This study found higher rates of prescribing of strong opioids and antibiotics in practices with GPs with more burnout symptoms, greater job dissatisfaction, and turnover intentions; working longer hours; and in practices in the north of England serving more deprived populations., (© The Authors.)

Background: Antihypertensives reduce the risk of cardiovascular disease but are also associated with harms including acute kidney injury (AKI). Few data exist to guide clinical decision making regarding these risks., Aim: To develop a prediction model estimating the risk of AKI in people potentially indicated for antihypertensive treatment., Design and Setting: Observational cohort study using routine primary care data from the Clinical Practice Research Datalink (CPRD) in England., Method: People aged ≥40 years, with at least one blood pressure measurement between 130 mmHg and 179 mmHg were included. Outcomes were admission to hospital or death with AKI within 1, 5, and 10 years. The model was derived with data from CPRD GOLD ( n = 1 772 618), using a Fine-Gray competing risks approach, with subsequent recalibration using pseudo-values. External validation used data from CPRD Aurum ( n = 3 805 322)., Results: The mean age of participants was 59.4 years and 52% were female. The final model consisted of 27 predictors and showed good discrimination at 1, 5, and 10 years (C-statistic for 10-year risk 0.821, 95% confidence interval [CI] = 0.818 to 0.823). There was some overprediction at the highest predicted probabilities (ratio of observed to expected event probability for 10-year risk 0.633, 95% CI = 0.621 to 0.645), affecting patients with the highest risk. Most patients (>95%) had a low 1- to 5-year risk of AKI, and at 10 years only 0.1% of the population had a high AKI and low CVD risk., Conclusion: This clinical prediction model enables GPs to accurately identify patients at high risk of AKI, which will aid treatment decisions. As the vast majority of patients were at low risk, such a model may provide useful reassurance that most antihypertensive treatment is safe and appropriate while flagging the few for whom this is not the case., (© The Authors.)

Introduction: Polypharmacy is increasingly common, and associated with undesirable consequences. Polypharmacy management necessitates balancing therapeutic benefits and risks, and varying clinical and patient priorities. Current guidance for managing polypharmacy is not supported by high quality evidence. The aim of the Improving Medicines use in People with Polypharmacy in Primary Care (IMPPP) trial is to evaluate the effectiveness of an intervention to optimise medication use for patients with polypharmacy in a general practice setting., Methods: This trial will use a multicentre, open-label, cluster-randomised controlled approach, with two parallel groups. Practices will be randomised to a complex intervention comprising structured medication review (including interprofessional GP/pharmacist treatment planning and patient-facing review) supported by performance feedback, financial incentivisation, clinician training and clinical informatics (intervention), or usual care (control). Patients with polypharmacy and triggering potentially inappropriate prescribing (PIP) indicators will be recruited in each practice using a computerised search of health records. 37 practices will recruit 50 patients, and review them over a 26-week intervention delivery period. The primary outcome is the mean number of PIP indicators triggered per patient at 26 weeks follow-up, determined objectively from coded GP electronic health records. Secondary outcomes will include patient reported outcome measures, and health and care service use. The main intention-to-treat analysis will use linear mixed effects regression to compare number of PIP indicators triggered at 26 weeks post-review between groups, adjusted for baseline (pre-randomisation) values. A nested process evaluation will explore implementation of the intervention in primary care., Ethics and Dissemination: The protocol and associated study materials have been approved by the Wales REC 6, NHS Research Ethics Committee (REC reference 19/WA/0090), host institution and Health Research Authority. Research outputs will be published in peer-reviewed journals and relevant conferences, and additionally disseminated to patients and the public, clinicians, commissioners and policy makers., Isrctn Registration: 90146150 (28/03/2019)., Competing Interests: Competing interests: RAP, CCG and CS are in receipt of other funding from NIHR. CS is a NIHR Senior Investigator., (Copyright: © 2022 Payne RA et al.)

Objectives: To investigate whether better continuity of care is associated with increased prescribing of clinically relevant medication and improved medication adherence., Setting: Random sample of 300 000 patients aged 30+ in 2017 within 83 English general practitioner (GP) practices from the Clinical Practice Research Datalink., Design: Patients were assigned to a randomly selected index date in 2017 on which medication use and continuity of care were determined. Adjusted associations between continuity of care and the prescribing and adherence of five cardiovascular medication groups were examined using logistic regression., Participants: Continuity of Care Index was calculated for 173 993 patients with 4+ GP consultations 2 years prior to their index date and divided into five categories: absence of continuity, below-average continuity, average, above-average continuity and perfect continuity., Main Outcome Measures: (A) Prescription for statins (primary or secondary prevention separately), anticoagulants, antiplatelet agents and antihypertensives covering the patient's index date. (B) Adherence (>80%) estimated using medication possession ratio., Results: There was strong evidence (p<0.01) that prescription of all five cardiovascular medication groups increased with greater continuity of care. Patients with absence of continuity were less likely to be prescribed cardiovascular medications than patients with above-average continuity (statins primary prevention OR 0.73, 95% CI 0.59 to 0.85; statins secondary prevention 0.77, 95% CI 0.57 to 1.03; antiplatelets 0.55, 95% CI 0.33 to 0.92; antihypertensives 0.51, 95% CI 0.39 to 0.65). Furthermore, patients with perfect continuity were more likely to be prescribed cardiovascular medications than those with above-average continuity (statins primary prevention OR 1.23, 95% CI 1.01 to 1.49; statins secondary prevention 1.37, 95% CI 1.10 to 1.71; antiplatelets 1.37, 95% CI 1.08 to 1.74; antihypertensives 1.10, 95% CI 0.99 to 1.23). Continuity was generally not associated with medication adherence, except for adherence to statins for secondary prevention (OR 0.75, 95% CI 0.60 to 0.94 for average compared with above-average continuity)., Conclusion: Better continuity of care is associated with improved prescribing of medication to patients at higher risk of cardiovascular disease but does not appear to be related to patient's medication adherence., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: The study aims to explore the use of regression discontinuity analysis (RDA) to examine effects of prescription of statins on total cholesterol and adverse outcomes (type 2 diabetes, rhabdomyolysis and myopathy, myalgia and myositis, liver disease, CVD, and mortality)., Study Design and Setting: We conducted a prospective cohort study using the Clinical Practice Research Datalink including patients with QRISK scores of 10 to 30 in 2010 to 2013 who were last followed-up in October 2016. Comparing patients with QRISK≥20 and QRISK<20, we explored RDA assumptions, provided proof of concept analyses (total cholesterol as outcome), and investigated the effect of statins prescription on adverse outcomes., Result: RDA confirmed statin prescription reduced total cholesterol (Mean difference (MD) -1.33 mmol/L, 95%Confidence Interval (CI) -1.93 to -0.73). RDA provided little evidence for adverse effects on diabetes, myalgia and myositis, liver disease, CVD, or mortality. The RDA analysis findings are similar to RCT results. Findings from non-RDA analysis agree with published observational studies., Conclusion: RDA can be used with large routine clinical datasets to provide evidence on effects of medications which are prescribed according to a threshold. Testable RDA assumptions were satisfied, but confidence intervals were wide, partly due to the low compliance with the prescribing threshold., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Pleural empyema represents a significant healthcare burden due to extended hospital admissions and potential requirement for surgical intervention. This study aimed to assess changes in incidence and management of pleural empyema in England over the past 10 years and the potential impact of influenza on rates.Hospital Episode Statistics data were used to identify patients admitted to English hospitals with pleural empyema between 2008 and 2018. Linear regression was used to analyse the relationship between empyema rates and influenza incidence recorded by Public Health England. The relationship between influenza and empyema was further explored using serological data from a prospective cohort study of patients presenting with pleural empyema.Between April 2008 and March 2018 there were 55 530 patients admitted with pleural empyema. There was male predominance (67% versus 33%), which increased with age. Cases have increased significantly from 4447 in 2008 to 7268 in 2017. Peaks of incidence correlated moderately with rates of laboratory-confirmed influenza in children and young adults (r=0.30). For nine of the 10 years studied, the highest annual point incidence of influenza coincided with the highest admission rate for empyema (with a 2-week lag). In a cohort study of patients presenting to a single UK hospital with pleural empyema/infection, 24% (17 out of 72) had serological evidence of recent influenza infection, compared to 7% in seasonally matched controls with simple parapneumonic or cardiogenic effusions (p<0.001).Rates of empyema admissions in England have increased steadily with a seasonal variation that is temporally related to influenza incidence. Patient-level serological data from a prospective study support the hypothesis that influenza may play a pathogenic role in empyema development., Competing Interests: Conflict of interest: D.T. Arnold has nothing to disclose. Conflict of interest: F.W. Hamilton has nothing to disclose. Conflict of interest: T.T. Morris has nothing to disclose. Conflict of interest: T. Suri has nothing to disclose. Conflict of interest: A. Morley has nothing to disclose. Conflict of interest: V. Frost has nothing to disclose. Conflict of interest: I.B. Vipond has nothing to disclose. Conflict of interest: A.R. Medford has nothing to disclose. Conflict of interest: R.A. Payne has nothing to disclose. Conflict of interest: P. Muir has nothing to disclose. Conflict of interest: N.A. Maskell has nothing to disclose., (Copyright ©The authors 2021. For reproduction rights and permissions contact permissions@ersnet.org.)

Background: Ischaemic stroke and myocardial infarction (MI) are common after pneumonia and are associated with long-term mortality. Aspirin may attenuate this risk and should be explored as a therapeutic option., Methods: We extracted all patients with pneumonia (aged over 50 years) from the Clinical Practice Research Datalink (CPRD), a large UK primary care database, from inception until January 2019. We then performed a prior event rate ratio (PERR) analysis with propensity score matching (PSM), an approach that allows for control of measured and unmeasured confounding, with aspirin usage as the exposure and ischaemic events as the outcome. The primary outcome was the combined outcome of ischaemic stroke and MI. Secondary outcomes were ischaemic stroke and MI individually. Relevant confounders (smoking, comorbidities, age and gender) were included in the analysis., Findings: 48 743 patients were eligible for matching. Of these, 9864 were aspirin users who were matched to 9864 non-users. Aspirin users had a reduced risk of the primary outcome (adjusted hazard ratio 0.64, 95% CI 0.52-0.79) in the PERR analysis. For both secondary outcomes, aspirin use was also associated with a reduced risk for MI (hazard ratio 0.46, 95% CI 0.30-0.72) and stroke (hazard ratio 0.70, 95% CI 0.55-0.91), respectively., Interpretation: This study provides supporting evidence that aspirin use is associated with reduced ischaemic events after pneumonia in a primary care setting. This drug may have a future clinical role in preventing this important complication., Competing Interests: Conflict of interest: F. Hamilton reports grants from the National Institute for Health Research (NIHR) (the Academic Clinical Fellowship Scheme), during the conduct of the study. Conflict of interest: D. Arnold has nothing to disclose. Conflict of interest: W. Henley has nothing to disclose. Conflict of interest: R.A. Payne has nothing to disclose., (Copyright ©ERS 2021.)

Background: Health services have failed to respond to the pressures of multimorbidity. Improved measures of multimorbidity are needed for conducting research, planning services and allocating resources., Methods: We modelled the association between 37 morbidities and 3 key outcomes (primary care consultations, unplanned hospital admission, death) at 1 and 5 years. We extracted development ( n = 300 000) and validation ( n = 150 000) samples from the UK Clinical Practice Research Datalink. We constructed a general-outcome multimorbidity score by averaging the standardized weights of the separate outcome scores. We compared performance with the Charlson Comorbidity Index., Results: Models that included all 37 conditions were acceptable predictors of general practitioner consultations (C-index 0.732, 95% confidence interval [CI] 0.731-0.734), unplanned hospital admission (C-index 0.742, 95% CI 0.737-0.747) and death at 1 year (C-index 0.912, 95% CI 0.905-0.918). Models reduced to the 20 conditions with the greatest combined prevalence/weight showed similar predictive ability (C-indices 0.727, 95% CI 0.725-0.728; 0.738, 95% CI 0.732-0.743; and 0.910, 95% CI 0.904-0.917, respectively). They also predicted 5-year outcomes similarly for consultations and death (C-indices 0.735, 95% CI 0.734-0.736, and 0.889, 95% CI 0.885-0.892, respectively) but performed less well for admissions (C-index 0.708, 95% CI 0.705-0.712). The performance of the general-outcome score was similar to that of the outcome-specific models. These models performed significantly better than those based on the Charlson Comorbidity Index for consultations (C-index 0.691, 95% CI 0.690-0.693) and admissions (C-index 0.703, 95% CI 0.697-0.709) and similarly for mortality (C-index 0.907, 95% CI 0.900-0.914)., Interpretation: The Cambridge Multimorbidity Score is robust and can be either tailored or not tailored to specific health outcomes. It will be valuable to those planning clinical services, policymakers allocating resources and researchers seeking to account for the effect of multimorbidity., Competing Interests: Competing interests: None declared., (© 2020 Joule Inc. or its licensors.)

Competing Interests: Competing interests: We have read and understood BMJ policy on declaration of interests and have no relevant interests to declare. Provenance and peer review: Not commissioned; externally peer reviewed.

Polypharmacy is an increasing and global issue affecting primary care. Although sometimes appropriate, polypharmacy can also be problematic, leading to a range of adverse consequences. Deprescribing is the process of supervised withdrawal of an inappropriate medication and has the potential to reduce some of the problems associated with polypharmacy. It is a complex and sensitive process. We examine the issue of deprescribing from the perspective of primary care. Key steps in the deprescribing process are a review of medications and corresponding indications, consideration of harms, assessment of eligibility for discontinuation, prioritisation of medications and implementation of a stopping plan with appropriate monitoring. Patient involvement is a key feature of this process. Deprescribing should be considered in the context of end-of-life care and medication safety, but approaches are also required to identify other situations where deprescribing is appropriate. General practitioners are well positioned to facilitate deprescribing, usually through formal medication review, with decisions informed by a range of other healthcare professionals. Guidelines are available that help guide these processes. A range of studies have explored attitudes towards deprescribing; patients are generally supportive of the concept, although clinician views are varied. The successful implementation of deprescribing strategies still requires important patient and clinician barriers to be overcome, and clinical trial evidence of effectiveness and safety is essential., Competing Interests: Competing interests: None declared.

Aims: Prescribing multiple medications is associated with various adverse outcomes, and polypharmacy is commonly considered suggestive of poor prescribing. Polypharmacy might thus be associated with unplanned hospitalization. We sought to test this assumption., Methods: Scottish primary care data for 180 815 adults with long-term clinical conditions and numbers of regular medications were linked to national hospital admissions data for the following year. Using logistic regression (age, gender and deprivation adjusted), we modelled the association of prescribing with unplanned admission for patients with different numbers of long-term conditions., Results: Admissions were more common in patients on multiple medications, but admission risk varied with the number of conditions. For patients with one condition, the odds ratio for unplanned admission for four to six medications was 1.25 (95% confidence interval 1.11-1.42) vs. one to three medications, and 3.42 (95% confidence interval 2.72-4.28) for ≥10 medications vs. one to three medications. However, this effect was greatly reduced for patients with multiple conditions; amongst patients with six or more conditions, those on four to six medications were no more likely to have unplanned admissions than those taking one to three medications (odds ratio 1.00; 95% confidence interval 0.88-1.14), and those taking ≥10 medications had a modestly increased risk of admission (odds ratio 1.50; 95% confidence interval 1.31-1.71)., Conclusions: Unplanned hospitalization is strongly associated with the number of regular medications. However, the effect is reduced in patients with multiple conditions, in whom only the most extreme levels of polypharmacy are associated with increased admissions. Assumptions that polypharmacy is always hazardous and represents poor care should be tempered by clinical assessment of the conditions for which those drugs are being prescribed., (© 2014 The British Pharmacological Society.)

Background and Objective: Falls are a major cause of morbidity and mortality in the elderly. This study examined the frequency of hospital admission for falls or fractures, and the association with a recent change in the use of cardiovascular and psychotropic medications., Methods: We conducted a retrospective case-cohort study of 39,813 patients aged >65 years from 40 Scottish general practices. Data on current prescriptions, dates of drug changes (defined as increases in dose or starting new drugs), diagnoses and clinical measurements were extracted from primary care electronic records, linked to national hospital admissions data. Multivariable logistic regression was used to model the association of change in prescribing of cardiovascular or psychotropic medication with admission to hospital for falls or fractures in the following 60 days., Results: A total of 838 patients (2.1 %) were admitted in the 1-year study period. Following adjustment for factors including age, sex, socioeconomic deprivation, co-morbidity and current prescribing, changes in both cardiovascular and psychotropic medications were associated with subsequent admission for falls or fractures (odds ratio [OR] 1.54 [95 % confidence interval (CI) 1.17-2.03] and 1.68 [95 % CI 1.28-2.22], respectively). There was no evidence for a difference in the effect of change in medication for different cardiovascular drug types (p = 0.86), but there was evidence (p = 0.003) for variation in the association between change in different psychotropic medications and admission; the strongest associations were observed for changes in selective serotonin reuptake inhibitor (SSRI) antidepressants (OR 1.99 [95 % CI 1.29-3.08]), non-SSRI/tricyclic antidepressants (OR 4.39 [95 % CI 2.21-8.71]) and combination psychotropic medication (OR 3.05 [95 % CI 1.66-5.63])., Conclusions: Recent changes in psychotropic and cardiovascular medications are associated with a substantial increase in risk of hospital admission for falls and fractures. Caution should thus be taken when instigating prescribing changes in relation to these medicines, particularly in individuals already considered to be at high risk, such as those with multiple co-morbidities and the oldest old.

Background: Multimorbidity, the presence of more than 1 long-term disorder, is associated with increased use of health services, but unplanned admissions to hospital may often be undesirable. Furthermore, socioeconomic deprivation and mental health comorbidity may lead to additional unplanned admissions. We examined the association between unplanned admission to hospital and physical multimorbidity, mental health and socioeconomic deprivation., Methods: We conducted a retrospective cohort study using data from 180 815 patients aged 20 years and older who were registered with 40 general practices in Scotland. Details of 32 physical and 8 mental health morbidities were extracted from the patients' electronic health records (as of Apr. 1, 2006) and linked to hospital admission data. We then recorded the occurrence of unplanned or potentially preventable unplanned acute (nonpsychiatric) admissions to hospital in the subsequent 12 months. We used logistic regression models, adjusting for age and sex, to determine associations between unplanned or potentially preventable unplanned admissions to hospital and physical multimorbidity, mental health and socioeconomic deprivation., Results: We identified 10 828 (6.0%) patients who had at least 1 unplanned admission to hospital and 2037 (1.1%) patients who had at least 1 potentially preventable unplanned admission to hospital. Both unplanned and potentially preventable unplanned admissions were independently associated with increasing physical multimorbidity (for ≥4 v. 0 conditions, odds ratio [OR] 5.87 [95% confidence interval (CI) 5.45-6.32] for unplanned admissions, OR 14.38 [95% CI 11.87-17.43] for potentially preventable unplanned admissions), mental health conditions (for ≥1 v. 0 conditions, OR 2.01 [95% CI 1.92-2.09] for unplanned admissions, OR 1.80 [95% CI 1.64-1.97] for potentially preventable unplanned admissions) and socioeconomic deprivation (for most v. least deprived quintile, OR 1.56 [95% CI 1.43-1.70] for unplanned admissions, OR 1.98 [95% CI 1.63-2.41] for potentially preventable unplanned admissions)., Interpretation: Physical multimorbidity was strongly associated with unplanned admission to hospital, including admissions that were potentially preventable. The risk of admission to hospital was exacerbated by the coexistence of mental health conditions and socioeconomic deprivation.

Cardiovascular disease is a major, growing, worldwide problem. It is important that individuals at risk of developing cardiovascular disease can be effectively identified and appropriately stratified according to risk. This review examines what we understand by the term risk, traditional and novel risk factors, clinical scoring systems, and the use of risk for informing prescribing decisions. Many different cardiovascular risk factors have been identified. Established, traditional factors such as ageing are powerful predictors of adverse outcome, and in the case of hypertension and dyslipidaemia are the major targets for therapeutic intervention. Numerous novel biomarkers have also been described, such as inflammatory and genetic markers. These have yet to be shown to be of value in improving risk prediction, but may represent potential therapeutic targets and facilitate more targeted use of existing therapies. Risk factors have been incorporated into several cardiovascular disease prediction algorithms, such as the Framingham equation, SCORE and QRISK. These have relatively poor predictive power, and uncertainties remain with regards to aspects such as choice of equation, different risk thresholds and the roles of relative risk, lifetime risk and reversible factors in identifying and treating at-risk individuals. Nonetheless, such scores provide objective and transparent means of quantifying risk and their integration into therapeutic guidelines enables equitable and cost-effective distribution of health service resources and improves the consistency and quality of clinical decision making., (© 2012 The Author. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society.)