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Tammes P, Payne RA, Salisbury C, Chalder M, Purdy S, Morris RW. The impact of a named GP scheme on continuity of care and emergency hospital admission: a cohort study among older patients in England, 2012-2016. BMJ Open 2019; 9:e029103. [PMID: 31548353 PMCID: PMC6773345 DOI: 10.1136/bmjopen-2019-029103] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVE To investigate whether the introduction of a named general practitioner (GP, family physician) improved patients' healthcare for patients aged 75 and over in England. SETTING Random sample of 27 500 patients aged 65 to 84 in 2012 within 139 English practices from the Clinical Practice Research Datalink linked with Hospital Episode Statistics. DESIGN Prospective cohort approach, measuring patients' GP consultations and emergency hospital admissions 2 years before/after the intervention. Patients were grouped in (i) aged over 74 and (ii) younger than 75 in both periods in order to compare who were or were not subject to the intervention. Adjusted associations between the named GP scheme, continuity of care and emergency hospital admission were examined using multilevel modelling. INTERVENTION National Health Service policy to introduce a named accountable GP for patients aged over 74 in April 2014. MAIN OUTCOME MEASURES (A) Continuity of care index-score, (B) risk of emergency hospital admissions, (C) number of emergency hospital admissions. RESULTS The intervention was associated with a decrease in continuity index-scores of -0.024 (95% CI -0.030 to -0.018, p<0.001); there were no differences in the decrease between the two age groups (-0.005, 95% CI -0.014 to 0.005). In the pre-intervention and post-intervention periods, respectively, 15.4% and 19.4% patients had an emergency admission. The probability of an emergency hospital admission increased after the intervention (OR 1.156, 95% CI 1.064 to 1.257, p=0.001); this increase was bigger for patients over 74 (relative OR 1.191, 95% CI 1.066 to 1.330, p=0.002). The average number of emergency hospital admissions increased after the intervention (rate ratio (RR) 1.178, 95% CI 1.103 to 1.259, p<0.001); this increase was greater for patients over 74 (relative RR 1.143, 95% CI 1.052 to 1.242, p=0.001). CONCLUSION The introduction of the named GP scheme was not associated with improvements in either continuity of care or rates of unplanned hospitalisation.
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Silarova B, Sharp S, Usher-Smith JA, Lucas J, Payne RA, Shefer G, Moore C, Girling C, Lawrence K, Tolkien Z, Walker M, Butterworth A, Di Angelantonio E, Danesh J, Griffin SJ. Effect of communicating phenotypic and genetic risk of coronary heart disease alongside web-based lifestyle advice: the INFORM Randomised Controlled Trial. Heart 2019; 105:982-989. [PMID: 30928969 PMCID: PMC6582721 DOI: 10.1136/heartjnl-2018-314211] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 01/21/2019] [Accepted: 01/25/2019] [Indexed: 02/05/2023] Open
Abstract
Objective To determine whether provision of web-based lifestyle advice and coronary heart disease risk information either based on phenotypic characteristics or phenotypic plus genetic characteristics affects changes in objectively measured health behaviours. Methods A parallel-group, open randomised trial including 956 male and female blood donors with no history of cardiovascular disease (mean [SD] age=56.7 [8.8] years) randomised to four study groups: control group (no information provided); web-based lifestyle advice only (lifestyle group); lifestyle advice plus information on estimated 10-year coronary heart disease risk based on phenotypic characteristics (phenotypic risk estimate) (phenotypic group) and lifestyle advice plus information on estimated 10-year coronary heart disease risk based on phenotypic (phenotypic risk estimate) and genetic characteristics (genetic risk estimate) (genetic group). The primary outcome was change in physical activity from baseline to 12 weeks assessed by wrist-worn accelerometer. Results 928 (97.1%) participants completed the trial. There was no evidence of intervention effects on physical activity (difference in adjusted mean change from baseline): lifestyle group vs control group 0.09 milligravity (mg) (95% CI −1.15 to 1.33); genetic group vs phenotypic group −0.33 mg (95% CI −1.55 to 0.90); phenotypic group and genetic group vs control group −0.52 mg (95% CI −1.59 to 0.55) and vs lifestyle group −0.61 mg (95% CI −1.67 to 0.46). There was no evidence of intervention effects on secondary biological, emotional and health-related behavioural outcomes except self-reported fruit and vegetable intake. Conclusions Provision of risk information, whether based on phenotypic or genotypic characteristics, alongside web-based lifestyle advice did not importantly affect objectively measured levels of physical activity, other health-related behaviours, biological risk factors or emotional well-being. Trial registration number ISRCTN17721237; Pre-results.
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Rhodes KM, Turner RM, Payne RA, White IR. Computationally efficient methods for fitting mixed models to electronic health records data. Stat Med 2018; 37:4557-4570. [PMID: 30155902 PMCID: PMC6240345 DOI: 10.1002/sim.7944] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 06/27/2018] [Accepted: 07/20/2018] [Indexed: 11/12/2022]
Abstract
Motivated by two case studies using primary care records from the Clinical Practice Research Datalink, we describe statistical methods that facilitate the analysis of tall data, with very large numbers of observations. Our focus is on investigating the association between patient characteristics and an outcome of interest, while allowing for variation among general practices. We explore ways to fit mixed-effects models to tall data, including predictors of interest and confounding factors as covariates, and including random intercepts to allow for heterogeneity in outcome among practices. We introduce (1) weighted regression and (2) meta-analysis of estimated regression coefficients from each practice. Both methods reduce the size of the dataset, thus decreasing the time required for statistical analysis. We compare the methods to an existing subsampling approach. All methods give similar point estimates, and weighted regression and meta-analysis give similar standard errors for point estimates to analysis of the entire dataset, but the subsampling method gives larger standard errors. Where all data are discrete, weighted regression is equivalent to fitting the mixed model to the entire dataset. In the presence of a continuous covariate, meta-analysis is useful. Both methods are easy to implement in standard statistical software.
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Cherskov A, Pohl A, Allison C, Zhang H, Payne RA, Baron-Cohen S. Polycystic ovary syndrome and autism: A test of the prenatal sex steroid theory. Transl Psychiatry 2018; 8:136. [PMID: 30065244 PMCID: PMC6068102 DOI: 10.1038/s41398-018-0186-7] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 06/08/2018] [Indexed: 12/28/2022] Open
Abstract
Elevated levels of prenatal testosterone may increase the risk for autism spectrum conditions (autism). Given that polycystic ovary syndrome (PCOS) is also associated with elevated prenatal testosterone and its precursor sex steroids, a hypothesis from the prenatal sex steroid theory is that women with PCOS should have elevated autistic traits and a higher rate of autism among their children. Using electronic health records obtained from the Clinical Practice Research Datalink (CPRD) in the UK between 1990 and 2014, we conducted three matched case-control studies. Studies 1 and 2 examined the risk of PCOS in women with autism (n = 971) and the risk of autism in women with PCOS (n = 26,263), respectively, compared with matched controls. Study 3 examined the odds ratio (OR) of autism in first-born children of women with PCOS (n = 8588), matched to 41,127 controls. In Studies 1 and 2 we found increased prevalence of PCOS in women with autism (2.3% vs. 1.1%; unadjusted OR: 2.01, 95% CI: 1.22-3.30) and elevated rates of autism in women with PCOS (0.17% vs. 0.09%, unadjusted OR: 1.94 CI: 1.37-2.76). In Study 3 we found the odds of having a child with autism were significantly increased, even after adjustment for maternal psychiatric diagnoses, obstetric complications, and maternal metabolic conditions (unadjusted OR: 1.60, 95% CI: 1.28-2.00; adjusted OR: 1.35, 95% CI: 1.06-1.73). These studies provide further evidence that women with PCOS and their children have a greater risk of autism.
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Harshfield A, Abel GA, Barclay S, Payne RA. Do GPs accurately record date of death? A UK observational analysis. BMJ Support Palliat Care 2018; 10:e24. [PMID: 29950293 DOI: 10.1136/bmjspcare-2018-001514] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 04/17/2018] [Accepted: 06/06/2018] [Indexed: 01/01/2023]
Abstract
OBJECTIVE To examine the concordance between dates of death recorded in UK primary care and national mortality records. METHODS UK primary care data from the Clinical Practice Research Datalink were linked to Office for National Statistics (ONS) data, for 118 571 patients who died between September 2010 and September 2015. Logistic regression was used to examine factors associated with discrepancy in death dates between data sets. RESULTS Death dates matched in 76.8% of cases with primary care dates preceding ONS date in 2.9%, and following in 20.3% of cases; 92.2% of cases differed by <2 weeks. Primary care date was >4 weeks later than ONS in 1.5% of cases and occurred more frequently with deaths categorised as 'external' (15.8% vs 0.8% for cancer), and in younger patients (15.9% vs 1% for 18-29 and 80-89 years, respectively). General practices with the greatest discrepancies (97.5th percentile) had around 200 times higher odds of recording substantially discordant dates than practices with the lowest discrepancies (2.5th percentile). CONCLUSION Dates of death in primary care records often disagree with national records and should be treated with caution. There is marked variation between practices, and studies involving young patients, unexplained deaths and where precise date of death is important are particularly vulnerable to these issues.
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Burt J, Elmore N, Campbell SM, Rodgers S, Avery AJ, Payne RA. Developing a measure of polypharmacy appropriateness in primary care: systematic review and expert consensus study. BMC Med 2018; 16:91. [PMID: 29895310 PMCID: PMC5998565 DOI: 10.1186/s12916-018-1078-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Accepted: 05/15/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Polypharmacy is an increasing challenge for primary care. Although sometimes clinically justified, polypharmacy can be inappropriate, leading to undesirable outcomes. Optimising care for polypharmacy necessitates effective targeting and monitoring of interventions. This requires a valid, reliable measure of polypharmacy, relevant for all patients, that considers clinical appropriateness and generic prescribing issues applicable across all medications. Whilst there are several existing measures of potentially inappropriate prescribing, these are not specifically designed with polypharmacy in mind, can require extensive clinical input to complete, and often cover a limited number of drugs. The aim of this study was to identify what experts consider to be the key elements of a measure of prescribing appropriateness in the context of polypharmacy. METHODS Firstly, we conducted a systematic review to identify generic (not drug specific) prescribing indicators relevant to polypharmacy appropriateness. Indicators were subject to content analysis to enable categorisation. Secondly, we convened a panel of 10 clinical experts to review the identified indicators and assess their relative clinical importance. For each indicator category, a brief evidence summary was developed, based on relevant clinical and indicator literature, clinical guidance, and opinions obtained from a separate patient discussion panel. A two-stage RAND/UCLA Appropriateness Method was used to reach consensus amongst the panel on a core set of indicators of polypharmacy appropriateness. RESULTS We identified 20,879 papers for title/abstract screening, obtaining 273 full papers. We extracted 189 generic indicators, and presented 160 to the panel grouped into 18 classifications (e.g. adherence, dosage, clinical efficacy). After two stages, during which the panel introduced 18 additional indicators, there was consensus that 134 indicators were of clinical importance. Following the application of decision rules and further panel consultation, 12 indicators were placed into the final selection. Panel members particularly valued indicators concerned with adverse drug reactions, contraindications, drug-drug interactions, and the conduct of medication reviews. CONCLUSIONS We have identified a set of 12 indicators of clinical importance considered relevant to polypharmacy appropriateness. Use of these indicators in clinical practice and informatics systems is dependent on their operationalisation and their utility (e.g. risk stratification, targeting and monitoring polypharmacy interventions) requires subsequent evaluation. TRIAL REGISTRATION Registration number: PROSPERO ( CRD42016049176 ).
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Mossakowska TJ, Saunders CL, Corbett J, MacLure C, Winpenny EM, Dujso E, Payne RA. Current and future cardiovascular disease risk assessment in the European Union: an international comparative study. Eur J Public Health 2018; 28:748-754. [DOI: 10.1093/eurpub/ckx216] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
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Usher-Smith JA, Winther LR, Shefer GS, Silarova B, Payne RA, Griffin SJ. Factors Associated With Engagement With a Web-Based Lifestyle Intervention Following Provision of Coronary Heart Disease Risk: Mixed Methods Study. J Med Internet Res 2017; 19:e351. [PMID: 29038095 PMCID: PMC5662793 DOI: 10.2196/jmir.7697] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 07/21/2017] [Accepted: 08/20/2017] [Indexed: 12/05/2022] Open
Abstract
Background Web-based interventions provide the opportunity to combine the tailored approach of face-to-face interventions with the scalability and cost-effectiveness of public health interventions. This potential is often limited by low engagement. A number of studies have described the characteristics of individuals who engage more in Web-based interventions but few have explored the reasons for these variations. Objective We aimed to explore individual-level factors associated with different degrees of engagement with a Web-based behavior change intervention following provision of coronary heart disease (CHD) risk information, and the barriers and facilitators to engagement. Methods This study involved the secondary analysis of data from the Information and Risk Modification Trial, a randomized controlled trial of a Web-based lifestyle intervention alone, or alongside information on estimated CHD risk. The intervention consisted of three interactive sessions, each lasting up to 60 minutes, delivered at monthly intervals. Participants were characterized as high engagers if they completed all three sessions. Thematic analysis of qualitative data from interviews with 37 participants was combined with quantitative data on usage of the Web-based intervention using a mixed-methods matrix, and data on the views of the intervention itself were analyzed across all participants. Results Thirteen participants were characterized as low engagers and 24 as high engagers. There was no difference in age (P=.75), gender (P=.95), or level of risk (P=.65) between the groups. Low engagement was more often associated with: (1) reporting a negative emotional reaction in response to the risk score (P=.029), (2) perceiving that the intervention did not provide any new lifestyle information (P=.011), and (3) being less likely to have reported feeling an obligation to complete the intervention as part of the study (P=.019). The mixed-methods matrix suggested that there was also an association between low engagement and less success with previous behavior change attempts, but the statistical evidence for this association was weak (P=.16). No associations were seen between engagement and barriers or facilitators to health behavior change, or comments about the design of the intervention itself. The most commonly cited barriers related to issues with access to the intervention itself: either difficulties remembering the link to the site or passwords, a perceived lack of flexibility within the website, or lack of time. Facilitators included the nonjudgmental presentation of lifestyle information, the use of simple language, and the personalized nature of the intervention. Conclusions This study shows that the level of engagement with a Web-based intervention following provision of CHD risk information is not influenced by the level of risk but by the individual’s response to the risk information, their past experiences of behavior change, the extent to which they consider the lifestyle information helpful, and whether they felt obliged to complete the intervention as part of a research study. A number of facilitators and barriers to Web-based interventions were also identified, which should inform future interventions.
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Wilson CL, Rhodes KM, Payne RA. Financial incentives improve recognition but not treatment of cardiovascular risk factors in severe mental illness. PLoS One 2017; 12:e0179392. [PMID: 28598998 PMCID: PMC5466340 DOI: 10.1371/journal.pone.0179392] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Accepted: 05/30/2017] [Indexed: 11/18/2022] Open
Abstract
Objectives Severe mental illness (SMI) is associated with premature cardiovascular disease, prompting the UK primary care payment-for-performance system (Quality and Outcomes Framework, QOF) to incentivise annual physical health reviews. This study aimed to assess the QOF’s impact on detection and treatment of cardiovascular risk factors in people with SMI. Methods A retrospective open cohort study of UK general practice was conducted between 1996 and 2014, using segmented logistic regression with 2004 and 2011 as break points, reflecting the introduction of relevant QOF incentives in these years. 67239 SMI cases and 359951 randomly-selected unmatched controls were extracted from the Clinical Practice Research Datalink (CPRD). Results There was strong evidence (p≤0.015) the 2004 QOF indicator (general health) resulted in an immediate increase in recording of elevated cholesterol (odds ratio 1.37 (95% confidence interval 1.24 to 1.51)); obesity (OR 1.21 (1.06 to 1.38)); and hypertension (OR 1.19 (1.04 to 1.38)) in the SMI group compared with the control group, which was sustained in subsequent years. Similar findings were found for diabetes, although the evidence was weaker (p = 0.059; OR 1.21 (0.99 to 1.49)). There was evidence (p<0.001) of a further, but unsustained, increase in recording of elevated cholesterol and obesity in the SMI group following the 2011 QOF indicator (cardiovascular specific). There was no clear evidence that the QOF indicators affected the prescribing of lipid modifying medications or anti-diabetic medications. Conclusion Incentivising general physical health review for SMI improves identification of cardiovascular risk factors, although the additional value of specifically incentivising cardiovascular risk factor assessment is unclear. However, incentives do not affect pharmacological management of these risks.
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Browne J, Edwards DA, Rhodes KM, Brimicombe DJ, Payne RA. Association of comorbidity and health service usage among patients with dementia in the UK: a population-based study. BMJ Open 2017; 7:e012546. [PMID: 28279992 PMCID: PMC5353300 DOI: 10.1136/bmjopen-2016-012546] [Citation(s) in RCA: 83] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Revised: 10/19/2016] [Accepted: 01/09/2017] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND The majority of people with dementia have other long-term diseases, the presence of which may affect the progression and management of dementia. This study aimed to identify subgroups with higher healthcare needs, by analysing how primary care consultations, number of prescriptions and hospital admissions by people with dementia varies with having additional long-term diseases (comorbidity). METHODS A retrospective cohort study based on health data from the Clinical Practice Research Datalink (CPRD) was conducted. Incident cases of dementia diagnosed in the year starting 1/3/2008 were selected and followed for up to 5 years. The number of comorbidities was obtained from a set of 34 chronic health conditions. Service usage (primary care consultations, hospitalisations and prescriptions) and time-to-death were determined during follow-up. Multilevel negative binomial regression and Cox regression, adjusted for age and gender, were used to model differences in service usage and death between differing numbers of comorbidities. RESULTS Data from 4999 people (14 866 person-years of follow-up) were analysed. Overall, 91.7% of people had 1 or more additional comorbidities. Compared with those with 2 or 3 comorbidities, people with ≥6 comorbidities had higher rates of primary care consultations (rate ratio (RR) 1.31, 95% CI 1.25 to 1.36), prescriptions (RR 1.68, 95% CI 1.57 to 1.81), and hospitalisation (RR 1.62, 95% CI 1.44 to 1.83), and higher risk of death (HR 1.56, 95% CI 1.37 to 1.78). DISCUSSION In the UK, people with dementia with higher numbers of comorbidities die earlier and have considerably higher health service usage in terms of primary care consultations, hospital admissions and prescribing. This study provides strong evidence that comorbidity is a key factor that should be considered when allocating resources and planning care for people with dementia.
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Duncan P, Duerden M, Payne RA. Deprescribing: a primary care perspective. Eur J Hosp Pharm 2017; 24:37-42. [PMID: 31156896 PMCID: PMC6451545 DOI: 10.1136/ejhpharm-2016-000967] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Revised: 09/02/2016] [Accepted: 09/08/2016] [Indexed: 12/20/2022] Open
Abstract
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.
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Abel GA, Barclay ME, Payne RA. Adjusted indices of multiple deprivation to enable comparisons within and between constituent countries of the UK including an illustration using mortality rates. BMJ Open 2016; 6:e012750. [PMID: 27852716 PMCID: PMC5128942 DOI: 10.1136/bmjopen-2016-012750] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVES Social determinants can have a major impact on health and as a consequence substantial inequalities are seen between and within countries. The study of inequalities between countries relies on having accurate and consistent measures of deprivation across the country borders. However, in the UK most socioeconomic deprivation measures are not comparable between countries. We give a method of adjusting the Indices of Multiple Deprivation (IMD) for use across the UK, describe the deprivation of each UK country, and show the problems introduced by naïvely using country-specific deprivation measures in a UK-wide analysis of mortality rates. SETTING/PARTICIPANTS 42 148 geographic areas covering the population of the UK. OUTCOME MEASURES Adjusted IMD scores based on the income and employment domains of country-specific IMD scores, adjusting for the contribution of other domains. The mortality rate among people aged under 75 years standardised to the UK age structure was compared between country-specific and UK-adjusted IMD quintiles. RESULTS Of the constituent countries of the UK, Northern Ireland was the most deprived with 37% of the population living in areas in the most deprived fifth of the UK, followed by Wales with 22% of the population living in the most deprived fifth of the UK. England and Scotland had similar levels of deprivation. Deprivation-specific mortality rates were similar in England and Wales. Northern Ireland had lower mortality rates than England for each deprivation group, with similar differences for each group. Scotland had higher mortality rates than England for each deprivation group, with larger differences for more deprived groups. CONCLUSIONS Analyses of between-country and within-country inequalities by socioeconomic position should use consistent measures; failing to use consistent measures may give misleading results. The published adjusted IMD scores we describe allow consistent analysis across the UK.
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Abstract
Polypharmacy describes, in simplistic terms, the use of multiple medications in an individual. It has become a normal aspect of modern medicine, driven by an ageing, multimorbid population, the increasing availability of preventative medications and an increasing use of single-disease guidelines and adherence to evidence-based practice. However, polypharmacy is also associated with a range of adverse outcomes, and is considered an important and increasing challenge for clinical practice. Here, we consider the definitions of polypharmacy, the extent and nature of medication use in different settings, and the type of problems encountered as a consequence of polypharmacy.
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Sinnott C, Mercer SW, Payne RA, Duerden M, Bradley CP, Byrne M. Improving medication management in multimorbidity: development of the MultimorbiditY COllaborative Medication Review And DEcision Making (MY COMRADE) intervention using the Behaviour Change Wheel. Implement Sci 2015; 10:132. [PMID: 26404642 PMCID: PMC4582886 DOI: 10.1186/s13012-015-0322-1] [Citation(s) in RCA: 84] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 09/09/2015] [Indexed: 11/21/2022] Open
Abstract
Background Multimorbidity, the presence of two or more chronic conditions, affects over 60 % of patients in primary care. Due to its association with polypharmacy, the development of interventions to optimise medication management in patients with multimorbidity is a priority. The Behaviour Change Wheel is a new approach for applying behavioural theory to intervention development. Here, we describe how we have used results from a review of previous research, original research of our own and the Behaviour Change Wheel to develop an intervention to improve medication management in multimorbidity by general practitioners (GPs), within the overarching UK Medical Research Council guidance on complex interventions. Methods Following the steps of the Behaviour Change Wheel, we sought behaviours associated with medication management in multimorbidity by conducting a systematic review and qualitative study with GPs. From the modifiable GP behaviours identified, we selected one and conducted a focused behavioural analysis to explain why GPs were or were not engaging in this behaviour. We used the behavioural analysis to determine the intervention functions, behavioural change techniques and implementation plan most likely to effect behavioural change. Results We identified numerous modifiable GP behaviours in the systematic review and qualitative study, from which active medication review (rather than passive maintaining the status quo) was chosen as the target behaviour. Behavioural analysis revealed GPs’ capabilities, opportunities and motivations relating to active medication review. We combined the three intervention functions deemed most likely to effect behavioural change (enablement, environmental restructuring and incentivisation) to form the MultimorbiditY COllaborative Medication Review And DEcision Making (MY COMRADE) intervention. MY COMRADE primarily involves the technique of social support: two GPs review the medications prescribed to a complex multimorbid patient together. Four other behavioural change techniques are incorporated: restructuring the social environment, prompts/cues, action planning and self-incentives. Conclusions This study is the first to use the Behaviour Change Wheel to develop an intervention targeting multimorbidity and confirms the usability and usefulness of the approach in a complex area of clinical care. The systematic development of the MY COMRADE intervention will facilitate a thorough evaluation of its effectiveness in the next phase of this work. Electronic supplementary material The online version of this article (doi:10.1186/s13012-015-0322-1) contains supplementary material, which is available to authorized users.
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Silarova B, Lucas J, Butterworth AS, Di Angelantonio E, Girling C, Lawrence K, Mackintosh S, Moore C, Payne RA, Sharp SJ, Shefer G, Tolkien Z, Usher-Smith J, Walker M, Danesh J, Griffin S. Information and Risk Modification Trial (INFORM): design of a randomised controlled trial of communicating different types of information about coronary heart disease risk, alongside lifestyle advice, to achieve change in health-related behaviour. BMC Public Health 2015; 15:868. [PMID: 26345710 PMCID: PMC4562192 DOI: 10.1186/s12889-015-2192-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 08/26/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cardiovascular disease (CVD) remains the leading cause of death globally. Primary prevention of CVD requires cost-effective strategies to identify individuals at high risk in order to help target preventive interventions. An integral part of this approach is the use of CVD risk scores. Limitations in previous studies have prevented reliable inference about the potential advantages and the potential harms of using CVD risk scores as part of preventive strategies. We aim to evaluate short-term effects of providing different types of information about coronary heart disease (CHD) risk, alongside lifestyle advice, on health-related behaviours. METHODS/DESIGN In a parallel-group, open randomised trial, we are allocating 932 male and female blood donors with no previous history of CVD aged 40-84 years in England to either no intervention (control group) or to one of three active intervention groups: i) lifestyle advice only; ii) lifestyle advice plus information on estimated 10-year CHD risk based on phenotypic characteristics; and iii) lifestyle advice plus information on estimated 10-year CHD risk based on phenotypic and genetic characteristics. The primary outcome is change in objectively measured physical activity. Secondary outcomes include: objectively measured dietary behaviours; cardiovascular risk factors; current medication and healthcare usage; perceived risk; cognitive evaluation of provision of CHD risk scores; and psychological outcomes. The follow-up assessment takes place 12 weeks after randomisation. The experiences, attitudes and concerns of a subset of participants will be also studied using individual interviews and focus groups. DISCUSSION The INFORM study has been designed to provide robust findings about the short-term effects of providing different types of information on estimated 10-year CHD risk and lifestyle advice on health-related behaviours. TRIAL REGISTRATION Current Controlled Trials ISRCTN17721237 . Registered 12 January 2015.
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Mercer SW, Payne RA, Nicholl BI, Morrison J. Authors' reply to Lewis and Bray. BMJ 2015; 351:h4446. [PMID: 26286087 DOI: 10.1136/bmj.h4446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Mercer SW, Payne RA, Nicholl BI, Morrison J. Risk of intracranial haemorrhage linked to co-treatment with antidepressants and NSAIDs. BMJ 2015; 351:h3745. [PMID: 26173949 DOI: 10.1136/bmj.h3745] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Paddison CAM, Saunders CL, Abel GA, Payne RA, Campbell JL, Roland M. Why do patients with multimorbidity in England report worse experiences in primary care? Evidence from the General Practice Patient Survey. BMJ Open 2015; 5:e006172. [PMID: 25805528 PMCID: PMC4386239 DOI: 10.1136/bmjopen-2014-006172] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVES To describe and explain the primary care experiences of people with multiple long-term conditions in England. DESIGN AND METHODS Using questionnaire data from 906,578 responders to the English 2012 General Practice Patient Survey, we describe the primary care experiences of patients with long-term conditions, including 583,143 patients who reported one or more long-term conditions. We employed mixed effect logistic regressions to analyse data on six items covering three care domains (access, continuity and communication) and a single item on overall primary care experience. We controlled for sociodemographic characteristics, and for general practice using a random effect, and further, controlled for, and explored the importance of, health-related quality of life measured using the EuroQoL (EQ-5D) scale. RESULTS Most patients with long-term conditions report a positive experience of care at their general practice (after adjusting for sociodemographic characteristics and general practice, range 74.0-93.1% reporting positive experience of care across seven questions) with only modest variation by type of condition. For all three domains of patient experience, an increasing number of comorbid conditions is associated with a reducing percentage of patients reporting a positive experience of care. For example, compared with respondents with no long-term condition, the OR for reporting a positive experience is 0.83 (95% CI 0.80 to 0.87) for respondents with four or more long-term conditions. However, this relationship is no longer observed after adjusting for health-related quality of life (OR (95% CI) single condition=1.23 (1.21 to 1.26); four or more conditions=1.31 (1.25 to 1.37)), with pain making the greatest difference among five quality of life variables included in the analysis. CONCLUSIONS Patients with multiple long-term conditions more frequently report worse experiences in primary care. However, patient-centred measures of health-related quality of life, especially pain, are more important than the number of conditions in explaining why patients with multiple long-term conditions report worse experiences of care.
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Payne RA, Abel GA, Avery AJ, Mercer SW, Roland MO. Is polypharmacy always hazardous? A retrospective cohort analysis using linked electronic health records from primary and secondary care. Br J Clin Pharmacol 2015; 77:1073-82. [PMID: 24428591 DOI: 10.1111/bcp.12292] [Citation(s) in RCA: 130] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2013] [Accepted: 06/14/2013] [Indexed: 01/04/2023] Open
Abstract
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.
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Paddison CAM, Saunders CL, Abel GA, Payne RA, Adler AI, Graffy JP, Roland MO. How do people with diabetes describe their experiences in primary care? Evidence from 85,760 patients with self-reported diabetes from the English General Practice Patient Survey. Diabetes Care 2015; 38:469-75. [PMID: 25271208 DOI: 10.2337/dc14-1095] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
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.
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Payne RA, Abel GA, Avery AJ, Mercer SW, Roland MO. Response to: Assessing the harms of polypharmacy requires careful interpretation and consistent definitions. Br J Clin Pharmacol 2014; 78:672-3. [DOI: 10.1111/bcp.12358] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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Appleton SC, Abel GA, Payne RA. Cardiovascular polypharmacy is not associated with unplanned hospitalisation: evidence from a retrospective cohort study. BMC FAMILY PRACTICE 2014; 15:58. [PMID: 24684851 PMCID: PMC3997839 DOI: 10.1186/1471-2296-15-58] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2013] [Accepted: 03/25/2014] [Indexed: 11/10/2022]
Abstract
Background Polypharmacy is often considered suggestive of suboptimal prescribing, and is associated with adverse outcomes. It is particularly common in the context of cardiovascular disease, but it is unclear whether prescribing of multiple cardiovascular medicines, which may be entirely appropriate and consistent with clinical guidance, is associated with adverse outcome. The aim of this study was to assess the relationship between number of prescribed cardiovascular medicines and unplanned non-cardiovascular hospital admissions. Methods A retrospective cohort analysis of 180,815 adult patients was conducted using Scottish primary care data linked to hospital discharge data. Patients were followed up for one year for the outcome of unplanned non-cardiovascular hospital admission. The association between number of prescribed cardiovascular medicines and hospitalisation was modelled using logistic regression, adjusting for key confounding factors including cardiovascular and non-cardiovascular morbidity and non-cardiovascular prescribing. Results 25.4% patients were prescribed ≥1 cardiovascular medicine, and 5.7% were prescribed ≥5. At least one unplanned non-cardiovascular admission was experienced by 4.2% of patients. Admissions were more common in patients receiving multiple cardiovascular medicines (6.4% of patients prescribed 5 or 6 cardiovascular medicines) compared with those prescribed none (3.5%). However, after adjusting for key confounders, cardiovascular prescribing was associated with fewer non-cardiovascular admissions (OR 0.66 for 5 or 6 vs. no cardiovascular medicines, 95% CI 0.57-0.75). Conclusions We found no evidence that increasing numbers of cardiovascular medicines were associated with an increased risk of unplanned non-cardiovascular hospitalisation, following adjustment for confounding. Assumptions that polypharmacy is hazardous and represents poor care should be moderated in the context of cardiovascular disease.
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Payne RA, Avery AJ, Duerden M, Saunders CL, Simpson CR, Abel GA. Prevalence of polypharmacy in a Scottish primary care population. Eur J Clin Pharmacol 2014; 70:575-81. [PMID: 24487416 DOI: 10.1007/s00228-013-1639-9] [Citation(s) in RCA: 126] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2013] [Accepted: 12/29/2013] [Indexed: 10/25/2022]
Abstract
PURPOSE Polypharmacy-the use of multiple medications by a single patient-is an important issue associated with various adverse clinical outcomes and rising costs. It is also a topic rarely addressed by clinical guidelines. We used routine Scottish health records to address the lack of data on the prevalence of polypharmacy in the broader, adult primary care population, particularly in relation to long-term conditions. METHODS We conducted a cross-sectional analysis of adult electronic primary healthcare records and used linear regression models to examine the association between the number of medicines prescribed regularly and both multimorbidity and specific clinical conditions, adjusting for age, gender and socioeconomic deprivation. RESULTS Overall, 16.9 % of the adults assessed were receiving four to nine medications, and 4.6 % were receiving ten or more medications, increasing with age (28.6 and 7.4 %, respectively, in those aged 60-69 years; 51.8 and 18.6 %, respectively, in those aged ≥ 80 years), but relatively unaffected by gender or deprivation. Of those patients with two clinical conditions, 20.8 % were receiving four to nine medications, and 1.1 % were receiving ten or more medications; in those patients with six or more comorbidities, these values were 47.7 and 41.7 %, respectively. The number of medications varied considerably between clinical conditions, with cardiovascular conditions associated with the greatest number of additional medications. The accumulation of additional medicines was less with concordant conditions. CONCLUSIONS Polypharmacy is common in UK primary care. The main factor associated with this is multimorbidity, although considerable variation exists between different conditions. The impact of clinical conditions on the number of medicines is generally less in the presence of co-existing concordant conditions.
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