Showing papers by "Mark Ashworth published in 2015"
TL;DR: Higher reported achievement of activities incentivised under a major, nationwide pay-for-performance programme did not seem to result in reduced incidence of premature death in the population.
Abstract: Objectives To quantify the relationship between a national primary care pay-for-performance programme, the UK’s Quality and Outcomes Framework (QOF), and all-cause and cause-specific premature mortality linked closely with conditions included in the framework. Design Longitudinal spatial study, at the level of the “lower layer super output area” (LSOA). Setting 32482 LSOAs (neighbourhoods of 1500 people on average), covering the whole population of England (approximately 53.5 million), from 2007 to 2012. Participants 8647 English general practices participating in the QOF for at least one year of the study period, including over 99% of patients registered with primary care. Intervention National pay-for-performance programme incentivising performance on over 100 quality-of-care indicators. Main outcome measures All-cause and cause-specific mortality rates for six chronic conditions: diabetes, heart failure, hypertension, ischaemic heart disease, stroke, and chronic kidney disease. We used multiple linear regressions to investigate the relationship between spatially estimated recorded quality of care and mortality. Results All-cause and cause-specific mortality rates declined over the study period. Higher mortality was associated with greater area deprivation, urban location, and higher proportion of a non-white population. In general, there was no significant relationship between practice performance on quality indicators included in the QOF and all-cause or cause-specific mortality rates in the practice locality. Conclusions Higher reported achievement of activities incentivised under a major, nationwide pay-for-performance programme did not seem to result in reduced incidence of premature death in the population.
92 citations
TL;DR: It is suggested that closer attention is paid to ‘young older’ male drinkers, as well as to older drinkers born outside the UK and those with lower levels of socioeconomic deprivation who are drinking above safe limits.
Abstract: Objectives This study explores the relationship between alcohol consumption, health, ethnicity and socioeconomic deprivation. Participants 27 991 people aged 65 and over from an inner-city population, using a primary care database. Primary and Secondary Outcome Measures Primary outcome measures were alcohol use and misuse (>21 units per week for men and >14 for units per week women). Results Older people of black and minority ethnic (BME) origin from four distinct ethnic groups comprised 29% of the sample. A total of 9248 older drinkers were identified, of whom 1980 (21.4%) drank above safe limits. Compared with older drinkers, older unsafe drinkers contained a higher proportion of males, white and Irish ethnic groups and a lower proportion of Caribbean, African and Asian groups. For older drinkers, the strongest independent predictors of higher alcohol consumption were younger age, male gender and Irish ethnicity. Independent predictors of lower alcohol consumption were Asian, black Caribbean and black African ethnicity. Socioeconomic deprivation and comorbidity were not significant predictors of alcohol consumption in older drinkers. For older unsafe drinkers, the strongest predictor variables were younger age, male gender and Irish ethnicity; comorbidity was not a significant predictor. Lower socioeconomic deprivation was a significant predictor of unsafe consumption whereas African, Caribbean and Asian ethnicity were not. Conclusions Although under-reporting in high-alcohol consumption groups and poor health in older people who have stopped or controlled their drinking may have limited the interpretation of our results, we suggest that closer attention is paid to ‘young older’ male drinkers, as well as to older drinkers born outside the UK and those with lower levels of socioeconomic deprivation who are drinking above safe limits.
38 citations
TL;DR: Demographic characteristics were the strongest predictors of A&E attendance rates, and primary care variables that may be amenable to change only made a small contribution to higher A&e attendance rates.
Abstract: Background Demand for England’s accident and emergency (A&E) services is increasing and is particularly concentrated in areas of high deprivation. The extent to which primary care services, relative to population characteristics, can impact on A&E is not fully understood. Aim To conduct a detailed analysis to identify population and primary care characteristics associated with A&E attendance rates, particularly those that may be amenable to change by primary care services. Design and setting This study used a cross-sectional population-based design. The setting was general practices in England, in the year 2011–2012. Method Multivariate linear regression analysis was used to create a model to explain the variability in practice A&E attendance rates. Predictor variables included population demographics, practice characteristics, and measures of patient experiences of primary care. Results The strongest predictor of general practice A&E attendance rates was social deprivation: the Index of Multiple Deprivation (IMD-2010) (β = 0.3. B = 1.4 [95% CI =1.3 to 1.6]), followed by population morbidity (GPPS responders reporting a long-standing health condition) (β = 0.2, B = 231.5 [95% CI = 202.1 to 260.8]), and knowledge of how to contact an out-of-hours GP (GPPS question 36) (β = −0.2, B = −128.7 [95% CI =149.3 to −108.2]). Other significant predictors included the practice list size (β = −0.1, B = −0.002 [95% CI = −0.003 to −0.002]) and the proportion of patients aged 0–4 years (β = 0.1, B = 547.3 [95% CI = 418.6 to 676.0]). The final model explained 34.4% of the variation in A&E attendance rates, mostly due to factors that could not be modified by primary care services. Conclusion Demographic characteristics were the strongest predictors of A&E attendance rates. Primary care variables that may be amenable to change only made a small contribution to higher A&E attendance rates.
37 citations
TL;DR: Examination of challenges faced by PCPs as they implemented pandemic policies in Australia, Israel and England before the 2009/A/H1N1 pandemic vaccine became available highlighted the centrality of primary care in the pandemic response.
Abstract: During the 2009/A/H1N1 pandemic, the main burden of the patient management fell on primary care physicians (PCPs), and they were the principal implementers of pandemic policies. Broad involvement of PCPs in the pandemic response offered an excellent opportunity to investigate the challenges that they encountered. To examine challenges faced by PCPs as they implemented pandemic policies in Australia, Israel and England before the 2009/A/H1N1 pandemic vaccine became available. This is a qualitative descriptive study that employed in-depth semi-structured interviews with 65 PCPs from Australia, Israel and England. The data were analysed thematically to provide a detailed account of the themes. Challenges in three fields of the pandemic response were identified. (i) Consultation of patients was challenged by the high flow of patients, sick and worried-well, the necessity to provide personalised information about the disease during consultations, and unfamiliar antiviral treatment. (ii) Performance of public health responsibilities was complicated in regards to patient segregation and introduction of personal protection measures. (iii) Communication with the health authorities was inefficient, with no established route to provide feedback about the pandemic policies. The experience of the 2009/A/H1N1 pandemic highlighted the centrality of primary care in the pandemic response. Despite intensive pre-pandemic planning, numerous barriers for implementation of the pandemic policies in primary care were identified. Investigation of three different approaches for involvement of PCPs in the pandemic management showed that none of these approaches worked smoothly.
25 citations
TL;DR: Practices that primarily use GPs to deliver diabetes care could release significant resources with no adverse effect by switching their services towards nurse-led care.
Abstract: Background Diabetes affects around 3.6 million people in the UK. Previous research found that general practices employing more nurses delivered better diabetes care, but did not include data on individual patient characteristics or consultations received.
24 citations
TL;DR: A randomised controlled trial to examine whether specific behaviour change techniques integrating MI and CBT result in favourable changes in weight and physical activity in those at high risk of CVD and whether this intervention offers the potential to support maintenance of a healthy lifestyle.
Abstract: Interventions targeting multiple risk factors for cardiovascular disease (CVD), including poor diet and physical inactivity, are more effective than interventions targeting a single risk factor. A motivational interviewing (MI) intervention can provide modest dietary improvements and physical activity increases, while adding cognitive behaviour therapy (CBT) skills may enhance the effects of MI. We designed a randomised controlled trial (RCT) to examine whether specific behaviour change techniques integrating MI and CBT result in favourable changes in weight and physical activity in those at high risk of CVD. A group and individual intervention will be compared to usual care. A group intervention offers potential benefits from social support and may be more cost effective. Individuals aged between 40 and 74 years in 11 South London Clinical Commissioning Groups who are at high risk of developing CVD (≥20%) in the next 10 years will be recruited. A sample of 1,704 participants will be randomised to receive the enhanced MI intervention, delivered by trained healthy lifestyle facilitators (HLFs), in group or individual formats, in 10 sessions (plus an introductory session) over one year, or usual care. Randomisation will be conducted by King’s College London Clinical Trials Unit and researchers collecting outcome data will be blinded to treatment allocation. At 12-month and 24-month follow-up assessments, primary outcomes will be change in weight and physical activity (average steps per day). Secondary outcomes include changes in low-density lipoprotein cholesterol and CVD risk score. Incidence of CVD events since baseline will be recorded. A process evaluation will be conducted to evaluate factors which impact on delivery, adherence and outcome. An economic evaluation will estimate relative cost-effectiveness of each type of intervention delivery. This RCT assesses the effectiveness of a healthy lifestyle intervention for people at high risk of CVD. Benefits of the study include the ethnic and socioeconomic diversity of the study population and that, via social support within the group setting and long-term follow-up period, the intervention offers the potential to support maintenance of a healthy lifestyle. This trial is registered with the ISRCTN registry (identifier: ISRCTN84864870, registered 15 May 2012).
19 citations
TL;DR: Hypertensive patients with MM had lower SBP than those with hypertension alone and those with one or more co-morbidities and the greater the number of MM, the lower the SBP.
Abstract: Hypertension is the most prevalent cardiovascular long-term condition in the UK and is associated with a high rate of multimorbidity (MM). Multimorbidity increases with age, ethnicity and social deprivation. Previous studies have yielded conflicting findings about the relationship between MM and blood pressure (BP) control. Our aim was to investigate the relationship between multimorbidity and systolic blood pressure (SBP) in patients with hypertension. A cross-sectional analysis of anonymised primary care data was performed for a total of 299,180 adult patients of whom 31,676 (10.6 %) had a diagnosis of hypertension. We compared mean SBP in patients with hypertension alone and those with one or more co-morbidities and analysed the effect of type of comorbidity on SBP. We constructed a regression model to identify the determinants of SBP control. The strongest predictor of mean SBP was the number of comorbidities, β −0.13 (p < 0.05). Other predictors included Afro-Caribbean ethnicity, β 0.05 (p < 0.05), South Asian ethnicity, β −0.03 (p < 0.05), age, β 0.05 (p < 0.05), male gender, β 0.05 (p < 0.05) and number of hypotensive drugs β 0.06 (p < 0.05). SBP was lower by a mean of 2.03 mmHg (−2.22, −1.85) for each additional comorbidity and was lower in MM regardless of the type of morbidity. Hypertensive patients with MM had lower SBP than those with hypertension alone; the greater the number of MM, the lower the SBP. We found no evidence that BP control was related to BP targets, medication category or specific co-morbidity. Further research is needed to determine whether consultation rate, “white-coat hypertension” or medication adherence influence BP control in MM.
17 citations
TL;DR: Patient involvement in healthcare, in general, and in substance misuse treatment in particular, is becoming a topic of paramount imporance and patient involvement can be conceptualised as listening to the patients’ erspective and encouraging patients to take an active role in the treatment they are receiving.
13 citations
TL;DR: A decade after its introduction QOF has become embedded as part of the identity of primary care in the UK, and is now being replaced by new incentive schemes, which again beg an answer to Mangin and Toop’s provocative question about professionalism.
Abstract: In 2007, writing about the Quality and Outcomes Framework (QOF), Mangin and Toop drew attention to the risk of using financial incentives to drive clinical behaviour.1 Asking plaintively, ‘What have you done to yourselves?’, the authors expressed concerns that a combination of chasing financial reward, prioritising population health over individual patient care, and a reduction of clinical autonomy were all contributing to an erosion of professional values. QOF was transforming the landscape in general practice, enabling practices to demonstrate levels of achievement that were higher than many had predicted2 and yet, like most quality improvement interventions, the unintended consequences could not be ignored.
Early versions of QOF were criticised in particular for the large number of indicators that were not based on rigorous research evidence. Subsequent refinements have started to take this criticism on board. The National Institute for Health and Care Excellence now plays a central role in assessing the scientific properties of the indicators, drawing more explicitly on the science of improvement to link practice and evidence. Critics continue to voice concerns about the principle of incentivising clinical behaviours, the preoccupation with economic drivers for change over educational ones, and the disproportionate size of the financial incentives in comparison with other elements of practice income, but a decade after its introduction QOF has become embedded as part of the identity of primary care in the UK.
As the design and implementation of QOF adapts to take into account some of the legitimate criticisms, it is now being replaced by new incentive schemes, which again beg an answer to Mangin and Toop’s provocative question about professionalism. In 2014–2015, there were six national so-called ‘direct enhanced services’ (DESs), which incentivised specific clinical behaviours and were available to all practices in England: unplanned …
3 citations
TL;DR: This work aimed to investigate the association between overall Quality and Outcomes Framework (QOF) performance and mortality, and found no association with mortality.
Abstract: We agree with Honeyford and colleagues that investigation of specific pathways of care is warranted, but we aimed to investigate the association between overall Quality and Outcomes Framework (QOF) performance and mortality.1 2 We did, however, assess outcomes indicators related to deaths from specific conditions, but found no association with mortality. We omitted recorded prevalence from our models because register sizes also depend on “true” community prevalence, which partly depends on survival. …