Louis S Levene

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.

Association of primary care characteristics with variations in mortality rates in England: an observational study.

Background Wide variations in mortality rates persist between different areas in England, despite an overall steady decline. To evaluate a conceptual model that might explain how population and service characteristics influence population mortality variations, an overall null hypothesis was tested: variations in primary healthcare service do not predict variations in mortality at population level, after adjusting for population characteristics. Methodology/Principal Findings In an observational study of all 152 English primary care trusts (geographical groupings of population and primary care services, total population 52 million), routinely available published data from 2008 and 2009 were modelled using negative binomial regression. Counts for all-cause, coronary heart disease, all cancers, stroke, and chronic obstructive pulmonary disease mortality were analyzed using explanatory variables of relevant population and service-related characteristics, including an age-correction factor. The main predictors of mortality variations were population characteristics, especially age and socio-economic deprivation. For the service characteristics, a 1% increase in the percentage of patients on a primary care hypertension register was associated with decreases in coronary heart disease mortality of 3% (95% CI 1–4%, p = 0.006) and in stroke mortality of 6% (CI 3–9%, p<0.0001); a 1% increase in the percentage of patients recalling being better able to see their preferred doctor was associated with decreases in chronic obstructive pulmonary disease mortality of 0.7% (CI 0.2–2.0%, p = 0.02) and in all cancer mortality of 0.3% (CI 0.1–0.5%, p = 0.009) (continuity of care). The study found no evidence of an association at primary care trust population level between variations in achievement of pay for performance and mortality. Conclusions/Significance Some primary healthcare service characteristics were also associated with variations in mortality at population level, supporting the conceptual model. Health care system reforms should strengthen these characteristics by delivering cost-effective evidence-based interventions to whole populations, and fostering sustained patient-provider partnerships.

Population characteristics, mechanisms of primary care and premature mortality in England: a cross-sectional study.

Objectives Health systems with strong primary care tend to have better population outcomes, but in many countries demand for care is growing. We sought to identify mechanisms of primary care that influence premature mortality. Design We developed a conceptual model of the mechanisms by which primary care influences premature mortality, and undertook a cross-sectional study in which population and primary care variables reflecting the model were used to explain variations in mortality of those aged under 75 years. The premature standardised mortality ratios (SMRs) for each practice, available from the Department of Health, had been calculated from numbers of deaths in the 5 years from 2006 to 2010. A regression model was undertaken with explanatory variables for the year 2009/2010, and repeated to check stability using data for 2008/2009 and 2010/2011. Setting All general practices in England were eligible for inclusion and, of the total of 8290, complete data were available for 7858. Results Population variables, particularly deprivation, were the most powerful predictors of premature mortality, but the mechanisms of primary care depicted in our model also affected mortality. The number of GPs/1000 population and detection of hypertension were negatively associated with mortality. In less deprived practices, continuity of care was also negatively associated with mortality. Conclusions Greater supply of primary care is associated with lower premature mortality even in a health system that has strong primary care (England). Health systems need to sustain the capacity of primary care to deliver effective care, and should assist primary care providers in identifying and meeting the needs of socioeconomically deprived groups.

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.

Predicting declines in perceived relationship continuity using practice deprivation scores: a longitudinal study in primary care

BACKGROUND Increased relationship continuity in primary care is associated with better health outcomes, greater patient satisfaction, and fewer hospital admissions. Greater socioeconomic deprivation is associated with lower levels of continuity, as well as poorer health outcomes. AIM To investigate whether deprivation scores predicted variations in the decline over time of patient-perceived relationship continuity of care, after adjustment for practice organisational and population factors. DESIGN AND SETTING An observational study in 6243 primary care practices with more than one GP, in England, using a longitudinal multilevel linear model, 2012-2017 inclusive. METHOD Patient-perceived relationship continuity was calculated using two questions from the GP Patient Survey. The effect of deprivation on the linear slope of continuity over time was modelled, adjusting for nine confounding variables (practice population and organisational factors). Clustering of measurements within general practices was adjusted for by using a random intercepts and random slopes model. Descriptive statistics and univariable analyses were also undertaken. RESULTS Relationship continuity declined by 27.5% between 2012 and 2017, and at all deprivation levels. Deprivation scores from 2012 did not predict variations in the decline of relationship continuity at practice level, after accounting for the effects of organisational and population confounding variables, which themselves did not predict, or weakly predicted with very small effect sizes, the decline of continuity. Cross-sectionally, continuity and deprivation were negatively correlated within each year. CONCLUSION The decline in relationship continuity of care has been marked and widespread. Measures to maximise continuity will need to be feasible for individual practices with diverse population and organisational characteristics.

Variations in coronary mortality rates between English primary care trusts: observational study 1993-2010.

Abstract Background In England, coronary heart disease (CHD) mortality has declined, but variations remain. Methods This study aimed to describe under 75-year CHD mortality variations across geographically defined populations. Regression slopes for mortality data as a function of time were calculated for all 151 English primary care trusts (PCTs), giving the change in the expected age adjusted rate for each extra year. Results Between 1993 and 2010, the mean age-standardized CHD mortality rate decreased from 107.76 to 35.12 per 100 000, but the coefficient of variation increased from 0.21 to 0.27. The slope of decline was significantly less after 2004 (β −4.91 for 1993–2003, −3.04 for 2004–2010). The proportion of smokers decreased by 24.6%. The estimated proportion of the population with controlled hypertension increased by 74.4% (2003–2010), but diabetes increased by 138% (1994–2010) and the proportion of obese people increased by 74.3% (1993–2010). There was a greater decline in CHD mortality in PCTs with greater deprivation and smoking (2006–2010). Conclusions Since 2004, there has not been a relative reduction of variations in CHD mortality. Appropriate strategies to improve early detection and effective management of risk factors are needed to lower overall CHD mortality further and to reduce persistent variations across England.

Study may not be the best approach to assessing link between QOF and premature death

Although Kontopantelis and colleagues found no association between recorded practice performance under the Quality and Outcomes Framework (QOF) and premature death rates, we are not convinced that improvements in healthcare, as measured through QOF, have no impact on population health.1 Our cross sectional studies of premature death from coronary heart disease in a sample of …

Rationalising Data Use for General Practice: A Missed Opportunity?

Practices and practitioners are required to produce bespoke reports using data for an ever-increasing range of purposes, including, among others, appraisals, contractual monitoring, quality assurance, and performance management by several bodies, without regard to unnecessary duplication of effort. Examples include producing numerous individual patient care plans for clinical commissioning groups (CCGs), a minimum of one completed audit cycle every 5 years for each GP as part of General Medical Council revalidation, and responses to the 130 questions of a Care Quality Commission (CQC) inspection. This huge non-clinical workload adds stress to practices and may be contributing to the current GP recruitment and retention crisis. The priorities of data use cannot solely be monitoring and performance management; to improve population outcomes (for example, premature mortality, morbidity, hospital admissions, time lost from work), we argue that general practice must also use data to strengthen its essential public health role. Local populations’ characteristics should be examined to better understand both health needs and the effect of interventions on outcomes, beyond the limited scope of the Quality and Outcomes Framework (QOF).1 This requires: Although this article considers mainly data extraction, interpretation, and presentation, a distinction needs to be made between these processes and the processes of data collection and entry. The designers of information systems need to support users …