A Self-Management Programme of Activity Coping and Education - SPACE for COPD(C) - in primary care: The protocol for a pragmatic trial.

INTRODUCTION: National guidance for chronic obstructive pulmonary disease (COPD) suggests that self-management support be provided for patients. Our institution has developed a standardised, manual-based, supported self-management programme: Self-Management Programme of Activity Coping and Education (SPACE for COPD(C)). SPACE was previously piloted on a 1-2-1 basis, delivered by researchers, to individuals with COPD. Discussions with stakeholders highlighted considerable interest in delivering the SPACE for COPD(C) intervention as a group-based self-management programme facilitated by healthcare professionals (HCPs) in primary care settings. The study aims are to explore the feasibility, acceptability and efficacy for the intervention to be delivered and supported by HCPs and to examine whether group-based delivery of SPACE for COPD(C), with sustained support, improves patient outcomes following the SPACE for COPD(C) intervention. METHODS AND ANALYSIS: A prospective, multi-site, single-blinded randomised controlled trial (RCT) will be conducted, with follow-up at 6 and 9 months. Participants will be randomly assigned to either the control group (usual care) or intervention group (a six-session, group-based SPACE for COPD(C)self-management programme delivered over 5 months). The primary outcome is change in COPD assessment test at 6 months.A discussion session will be conducted with HCPs who deliver the intervention to discuss and gain insight into any potential facilitators/barriers to implementing the intervention in practice. Furthermore, we will conduct semi-structured focus groups with intervention participants to understand feasibility and acceptability. All qualitative data will be analysed thematically. ETHICS AND DISSEMINATION: The project has received a favourable opinion from South Hampshire B Research Ethics Committee, REC reference: 14/SC/1169 and full R&D approval from the University Hospitals of Leicester NHS Trust: 152408.Study results will be disseminated through appropriate peer-reviewed journals, national and international respiratory/physiotherapy conferences, via the Collaboration and Leadership in Applied Health Research and Care and through social media. TRIAL REGISTRATION: ISRCTN17942821; pre-results.

Population health needs as predictors of variations in NHS practice payments: a cross-sectional study of English general practices in 2013-2014 and 2014-2015.

BACKGROUND: NHS general practice payments in England include pay for performance elements and a weighted component designed to compensate for workload, but without measures of specific deprivation or ethnic groups. AIM: To determine whether population factors related to health needs predicted variations in NHS payments to individual general practices in England. DESIGN AND SETTING: Cross-sectional study of all practices in England, in financial years 2013-2014 and 2014-2015. METHOD: Descriptive statistics, univariable analyses (examining correlations between payment and predictors), and multivariable analyses (undertaking multivariable linear regressions for each year, with logarithms of payments as the dependent variables, and with population, practice, and performance factors as independent variables) were undertaken. RESULTS: Several population variables predicted variations in adjusted total payments, but inconsistently. Higher payments were associated with increases in deprivation, patients of older age, African Caribbean ethnic group, and asthma prevalence. Lower payments were associated with an increase in smoking prevalence. Long-term health conditions, South Asian ethnic group, and diabetes prevalence were not predictive. The adjusted R2 values were 0.359 (2013-2014) and 0.374 (2014-2015). A slightly different set of variables predicted variations in the payment component designed to compensate for workload. Lower payments were associated with increases in deprivation, patients of older age, and diabetes prevalence. Smoking prevalence was not predictive. There was a geographical differential. CONCLUSION: Population factors related to health needs were, overall, poor predictors of variations in adjusted total practice payments and in the payment component designed to compensate for workload. Revising the weighting formula and extending weighting to other payment components might better support practices to address these needs.

Estimating smoking prevalence in general practice using data from the Quality and Outcomes Framework (QOF).

OBJECTIVES: To determine to what extent underlying data published as part of Quality and Outcomes Framework (QOF) can be used to estimate smoking prevalence within practice populations and local areas and to explore the usefulness of these estimates. DESIGN: Cross-sectional, observational study of QOF smoking data. Smoking prevalence in general practice populations and among patients with chronic conditions was estimated by simple manipulation of QOF indicator data. Agreement between estimates from the integrated household survey (IHS) and aggregated QOF-based estimates was calculated. The impact of including smoking estimates in negative binomial regression models of counts of premature coronary heart disease (CHD) deaths was assessed. SETTING: Primary care in the East Midlands. PARTICIPANTS: All general practices in the area of study were eligible for inclusion (230). 14 practices were excluded due to incomplete QOF data for the period of study (2006/2007-2012/2013). One practice was excluded as it served a restricted practice list. MEASUREMENTS: Estimates of smoking prevalence in general practice populations and among patients with chronic conditions. RESULTS: Median smoking prevalence in the practice populations for 2012/2013 was 19.2% (range 5.8-43.0%). There was good agreement (mean difference: 0.39%; 95% limits of agreement (-3.77, 4.55)) between IHS estimates for local authority districts and aggregated QOF register estimates. Smoking prevalence estimates in those with chronic conditions were lower than for the general population (mean difference -3.05%), but strongly correlated (Rp=0.74, p<0.0001). An important positive association between premature CHD mortality and smoking prevalence was shown when smoking prevalence was added to other population and service characteristics. CONCLUSIONS: Published QOF data allow useful estimation of smoking prevalence within practice populations and in those with chronic conditions; the latter estimates may sometimes be useful in place of the former. It may also provide useful estimates of smoking prevalence in local areas by aggregating practice based data.

Modelling factors in primary care quality improvement: a cross-sectional study of premature CHD mortality.

OBJECTIVES: To identify features of primary care quality improvement associated with improved health outcomes using premature coronary heart disease (CHD) mortality as an example, and to determine impacts of different modelling approaches. DESIGN: Cross-sectional study of mortality rates in 229 general practices. SETTING: General practices from three East Midlands primary care trusts. PARTICIPANTS: Patients registered to the practices above between April 2006 and March 2009. MAIN OUTCOME MEASURES: Numbers of CHD deaths in those aged under 75 (premature mortality) and at all ages in each practice. RESULTS: Population characteristics and markers of quality of primary care were associated with variations in premature CHD mortality. Increasing levels of deprivation, percentages of practice populations on practice diabetes registers, white, over 65 and male were all associated with increasing levels of premature CHD mortality. Control of serum cholesterol levels in those with CHD and the percentage of patients recalling access to their preferred general practitioner were both associated with decreased levels of premature CHD mortality. Similar results were found for all-age mortality. A combined measure of quality of primary care for CHD comprising 12 quality outcomes framework indicators was associated with decreases in both all-age and premature CHD mortality. The selected models suggest that practices in less deprived areas may have up to 20% lower premature CHD mortality than those with median deprivation and that improvement in the CHD care quality from 83% (lower quartile) to 86% (median) could reduce premature CHD mortality by 3.6%. Different modelling approaches yielded qualitatively similar results. CONCLUSIONS: High-quality primary care, including aspects of access to and continuity of care, detection and management, appears to be associated with reducing CHD mortality. The impact on premature CHD mortality is greater than on all-age CHD mortality. Determining the most useful measures of quality of primary care needs further consideration.

Association of features of primary health care with coronary heart disease mortality.

CONTEXT: The goal of US health care reform is to extend access. In England, with a universal access health system, coronary heart disease (CHD) mortality rates have decreased by more than two-fifths in the last decade, but variations in rates between local populations persist. OBJECTIVE: To identify which features of populations and primary health care explain variations in CHD mortality rates between the 152 primary care trust populations in England. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional study in England of all 152 primary care trusts (total registered population, 54.3 million in 2008) using a hierarchical regression model with age-standardized CHD mortality rate as the dependent variable, and population characteristics (index of multiple deprivation, smoking, ethnicity, and registers of individuals with diabetes) and service characteristics (level of provision of primary care services, levels of detected hypertension, pay for performance data) as candidate explanatory variables. MAIN OUTCOME MEASURES: Age-standardized CHD mortality rates in 2006, 2007, and 2008. RESULTS: The mean age-standardized CHD mortality rates per 100,000 European Standard Population were 97.9 (95% confidence interval [CI], 94.9-100.9) in 2006, 93.5 (95% CI, 90.4-96.5) in 2007, and 88.4 (95% CI, 85.7-91.1) in 2008. In all 3 years, 4 population characteristics were significantly positively associated with CHD mortality (index of multiple deprivation, smoking, white ethnicity, and registers of individuals with diabetes), and 1 service characteristic (levels of detected hypertension) was significantly negatively associated with CHD mortality (adjusted r(2) = 0.66 in 2006, adjusted r(2) = 0.68 in 2007, and adjusted r(2) = 0.67 in 2008). Other service characteristics did not contribute significantly to the model. CONCLUSION: In England, variations in CHD mortality are predominantly explained by population characteristics; however, greater detection of hypertension is associated with lower CHD mortality.