A multi-level system quality improvement intervention to reduce racial disparities in hypertension care and control: study protocol

BACKGROUND: Racial disparities in blood pressure control have been well documented in the United States. Research suggests that many factors contribute to this disparity, including barriers to care at patient, clinician, healthcare system, and community levels. To date, few interventions aimed at reducing hypertension disparities have addressed factors at all of these levels. This paper describes the design of Project ReD CHiP (Reducing Disparities and Controlling Hypertension in Primary Care), a multi-level system quality improvement project. By intervening on multiple levels, this project aims to reduce disparities in blood pressure control and improve guideline concordant hypertension care. METHODS: Using a pragmatic trial design, we are implementing three complementary multi-level interventions designed to improve blood pressure measurement, provide patient care management services and offer expanded provider education resources in six primary care clinics in Baltimore, Maryland. We are staggering the introduction of the interventions and will use Statistical Process Control (SPC) charting to determine if there are changes in outcomes at each clinic after implementation of each intervention. The main hypothesis is that each intervention will have an additive effect on improvements in guideline concordant care and reductions in hypertension disparities, but the combination of all three interventions will result in the greatest impact, followed by blood pressure measurement with care management support, blood pressure measurement with provider education, and blood pressure measurement only. This study also examines how organizational functioning and cultural competence affect the success of the interventions. DISCUSSION: As a quality improvement project, Project ReD CHiP employs a novel study design that specifically targets multi-level factors known to contribute to hypertension disparities. To facilitate its implementation and improve its sustainability, we have incorporated stakeholder input and tailored components of the interventions to meet the specific needs of the involved clinics and communities. Results from this study will provide knowledge about how integrated multi-level interventions can improve hypertension care and reduce disparities. TRIAL REGISTRATION: ClinicalTrials.gov NCT0156686

Practical utility of general practice data capture and spatial analysis for understanding COPD and asthma

Abstract Background General practice-based (GP) healthcare data have promise, when systematically collected, to support estimating local rates of chronic obstructive pulmonary disease (COPD) and asthma, variations in burden of disease, risk factors and comorbid conditions, and disease management and quality of care. The use of GP information systems for health improvement has been limited, however, in the scope and quality of data. This study assessed the practical utility of de-identified clinical databases for estimating local rates of COPD and asthma. We compared COPD and asthma rates to national benchmarks, examined health related risk factors and co-morbidities as correlates of COPD and asthma, and assessed spatial patterns in prevalence estimates at the small-area level. Methods Data were extracted from five GP databases in western Adelaide, South Australia, for active patients residing in the region between 2012 and 2014. Prevalence estimates were computed at the statistical area 1 (SA1) spatial unit level using the empirical Bayes estimation approach. Descriptive analyses included summary statistics, spatial indices and mapping of geographic patterns. Bivariate associations were assessed, and disease profiles investigated to ascertain multi-morbidities. Multilevel logistic regression models were fitted, accounting for individual covariates including the number of comorbid conditions to assess the influence of area-level socio-economic status (SES). Results For 33,725 active patients, prevalence estimates were 3.4% for COPD and 10.3% for asthma, 0.8% higher and 0.5% lower for COPD and asthma, respectively, against 2014–15 National Health Survey (NHS) benchmarks. Age-specific comparisons showed discrepancies for COPD in the ‘64 years or less’ and ‘age 65 and up’ age groups, and for asthma in the ‘15–25 years’ and ‘75 years and up’ age groups. Analyses confirmed associations with individual-level factors, co-morbid conditions, and area-level SES. Geographic aggregation was seen for COPD and asthma, with clustering around GP clinics and health care centres. Spatial patterns were inversely related to area-level SES. Conclusion GP-based data capture and analysis has a clear potential to support research for improved patient outcomes for COPD and asthma via knowledge of geographic variability and its correlates, and how local prevalence estimates differ from NHS benchmarks for vulnerable age-groups

Fast-food exposure around schools in urban Adelaide

Objective To assess whether exposure to fast-food outlets around schools differed depending on socio-economic status (SES). Design Binary logistic regression was used to investigate the presence and zero-inflated Poisson regression was used for the count (due to the excess of zeroes) of fast food within 1000 m and 15000 m road network buffers around schools. The low and middle SES tertiles were combined due to a lack of significant variation as the 'disadvantaged' group and compared with the high SES tertile as the 'advantaged' group. School SES was expressed using the 2011 Australian Bureau of Statistics, socio-economic indices for areas, index of relative socio-economic disadvantage. Fast-food data included independent takeaway food outlets and major fast-food chains. Setting Metropolitan Adelaide, South Australia. Subjects A total of 459 schools were geocoded to the street address and 1000 m and 1500 m road network distance buffers calculated. Results There was a 1·6 times greater risk of exposure to fast food within 1000 m (OR=1·634; 95 % 1·017, 2·625) and a 9·5 times greater risk of exposure to a fast food within 1500 m (OR=9·524; 95 % CI 3·497, 25·641) around disadvantaged schools compared with advantaged schools. Conclusions Disadvantaged schools were exposed to more fast food, with more than twice the number of disadvantaged schools exposed to fast food. The higher exposure to fast food near more disadvantaged schools may reflect lower commercial land cost in low-SES areas, potentially creating more financially desirable investments for fast-food developers.</p