Factors Associated With the Provision of Coronary Heart Disease Preventive CareServices

The Anderson and Aday access framework (1974) is utilized to investigate the association of individual and community level, predisposing, socio-demographic, and enabling factors, on potential and realized access to coronary heart disease (CHD) preventive care. The cross-sectional study is based on a sample of adults age 18-85 from the Medical Expenditure Panel Survey (MEPS) who were identified with CHD risk or who had a CHD diagnosis.Variables from the MEPS and the Area Resource File (ARF) are used to test logistic regression models for dependent variables measuring primary and secondary CHD preventive care services. The primary preventive care measures include blood cholesterol testing, blood pressure checks, and, diet, exercise and smoking cessation counseling. The secondary preventive measures include beta-blocker reciept after myocardial infarction (MI) and statin drug use for the treatment of high blood cholesterol.Being uninsured is associated with a reduced likelihood of receiving primary CHD preventive care. Overall study results indicated gender and race are more consistent predictors of the receipt of CHD preventive care services than individual enabling or community characteristics. Women had a greater likelihood of receiving primaryCHD preventive care services than men. Hispanics are less likely than Caucasians to receive primary CHD preventive care services, except for blood cholesterol testing for which they are more likely to receive. Blacks are more likely than Caucasians to have blood cholesterol testing, but are no less likely to receive the other primary CHD preventive care measures. Blacks demonstrate a lower likelihood of receiving secondary CHD preventive care than Caucasians, specifically beta-blocker post myocardial infarction indicating that disparities in secondary CHD preventive care persist for segments of the study population. Persons over 75 years of age are less likely to receive primary CHD preventive care services as well as the secondary preventive measure ofstatin use for high blood cholesterol.Community level factors did not improve the logistic regression model for the receipt of CHD preventive care, yet, when predicting potential access for preventive services, persons from a higher percent Hispanic or black community were less likely to have a usual source of care

Day 3 - Creative Collaborations III: Community-Academic Collaborations

A community-engaged approach to research has been recognized as a powerful vehicle for strengthening the links between research and practice. Because of its potential benefits, many leading funding sources (NIH, NSF, & RWJ to name a few!) increasingly encourage researchers to utilize a community-engaged approach. However, community-engaged research requires partnership development, cooperation and negotiation, collaboration with non-academic partners and a commitment to address stakeholders’ issues—each warranting special attention in the proposal development and grant-writing process. This session is aimed at developing strategies for writing community-academic collaborations into successful grant proposals. Presenters will discuss their success strategies, as well as tips for finding community partners for research

Assessing community perspectives of the community based education and service model at Makerere University, Uganda: a qualitative evaluation

<p>Abstract</p> <p>Background</p> <p>Community partnerships are defined as groups working together with shared goals, responsibilities, and power to improve the community. There is growing evidence that these partnerships contribute to the success and sustainability of community-based education and service programs (COBES), facilitating change in community actions and attitudes. Makerere University College of Health Sciences (MakCHS) is forging itself as a transformational institution in Uganda and the region. The College is motivated to improve the health of Ugandans through innovative responsive teaching, provision of service, and community partnerships. Evaluating the COBES program from the community perspective can assist the College in refining an innovative and useful model that has potential to improve the health of Ugandans.</p> <p>Methods</p> <p>A stratified random sample of 11 COBES sites was selected to examine the community’s perception of the program. Key Informant Interviews of 11 site tutors and 33 community members were completed. The data was manually analyzed and themes developed.</p> <p>Results</p> <p>Communities stated the students consistently engaged with them with culturally appropriate behaviour. They rated the student’s communication as very good even though translators were frequently needed. Half the community stated they received some feedback from the students, but some communities interpreted any contact after the initial visit as feedback. Communities confirmed and appreciated that the students provided a number of interventions and saw positive changes in health and health seeking behaviours. The community reflected that some programs were more sustainable than others; the projects that needed money to implement were least sustainable. The major challenges from the community included community fatigue, and poor motivation of community leaders to continue to take students without compensation.</p> <p>Conclusions</p> <p>Communities hosting Makerere students valued the students’ interventions and the COBES model. They reported witnessing health benefits of fewer cases of disease, increased health seeking behavior and sustainable healthcare programs. The evidence suggests that efforts to standardize objectives, implement structural adjustments, and invest in development of the program would yield even more productive community interactions and a healthcare workforce with public health skills needed to work in rural communities.</p

Conducting High-Value Secondary Dataset Analysis: An Introductory Guide and Resources

Secondary analyses of large datasets provide a mechanism for researchers to address high impact questions that would otherwise be prohibitively expensive and time-consuming to study. This paper presents a guide to assist investigators interested in conducting secondary data analysis, including advice on the process of successful secondary data analysis as well as a brief summary of high-value datasets and online resources for researchers, including the SGIM dataset compendium (www.sgim.org/go/datasets). The same basic research principles that apply to primary data analysis apply to secondary data analysis, including the development of a clear and clinically relevant research question, study sample, appropriate measures, and a thoughtful analytic approach. A real-world case description illustrates key steps: (1) define your research topic and question; (2) select a dataset; (3) get to know your dataset; and (4) structure your analysis and presentation of findings in a way that is clinically meaningful. Secondary dataset analysis is a well-established methodology. Secondary analysis is particularly valuable for junior investigators, who have limited time and resources to demonstrate expertise and productivity

Racial/Ethnic Disparities in Exercise and Dietary Behaviors of Middle-Aged and Older Adults

BackgroundDifferences in health behaviors may be important contributors to racial/ethnic disparities in the health status of adults. Studies to date have not compared whether there are health behavior differences in exercise and dietary behaviors among middle-age and older adults in the four largest racial/ethnic categories.ObjectiveTo investigate racial/ethnic differences in exercise and dietary behaviors of middle-aged and older adults.DesignWe used data from the 2007 California Health Interview Survey. Multivariable logistic regression was used to examine interactions between age and race/ethnicity in predicting two categories of health behaviors. Analyses were conducted adjusting for sociodemographic characteristics, health insurance status, and healthcare utilization.ParticipantsA population-based sample of 33,189 California adults 45 years old and older: 26,522 non-Hispanic whites, 1,686 African American/blacks, 2,565 Asian/Pacific Islanders (1,741 English-proficient; 824 limited English-proficient), and 2,416 Latinos (1,538 English-proficient; 878 limited English-proficient).Main measuresSelf-report leisure-time physical activity (moderate and vigorous) and daily consumption of fruits and vegetables.Key resultsRacial/ethnic minorities generally engaged in less healthy exercise and dietary behaviors than whites, with differences more pronounced in middle adulthood. The disparities were the greatest among English-proficient minorities. Specifically, among middle-aged respondents, all racial/ethnic minorities engaged in less vigorous physical activity than whites (ORs range = 0.28 to 0.73; 95% CI range = 0.16-1.00). Additionally, middle-aged, English-proficient minorities engaged in less moderate physical activity compared to whites (ORs range =0.57 to 0.67; 95% CI range = 0.45-0.79). Furthermore, middle-aged, English-proficient Latinos had a poorer diet than whites (OR = 0.54; 0.39-0.75). Few significant racial/ethnic differences emerged in the exercise and dietary behaviors of older adults.ConclusionsRacial/ethnic disparities in exercise and dietary behaviors are most notable among middle-aged, acculturated minorities. Results highlight the need to promote positive exercise and dietary behaviors during critical preventive ages, when racial/ethnic disparities are large and the potential to prevent chronic disease is great

Automated telephone communication systems for preventive healthcare and management of long-term conditions

Background Automated telephone communication systems (ATCS) can deliver voice messages and collect health-related information from patients using either their telephone’s touch-tone keypad or voice recognition software. ATCS can supplement or replace telephone contact between health professionals and patients. There are four different types of ATCS: unidirectional (one-way, non-interactive voice communication), interactive voice response (IVR) systems, ATCS with additional functions such as access to an expert to request advice (ATCS Plus) and multimodal ATCS, where the calls are delivered as part of a multicomponent intervention. Objectives To assess the effects of ATCS for preventing disease and managing long-term conditions on behavioural change, clinical, process, cognitive, patient-centred and adverse outcomes. Search methods We searched 10 electronic databases (the Cochrane Central Register of Controlled Trials; MEDLINE; Embase; PsycINFO; CINAHL; Global Health; WHOLIS; LILACS; Web of Science; and ASSIA); three grey literature sources (Dissertation Abstracts, Index to Theses, Australasian Digital Theses); and two trial registries (www.controlled-trials.com; www.clinicaltrials.gov) for papers published between 1980 and June 2015. Selection criteria Randomised, cluster- and quasi-randomised trials, interrupted time series and controlled before-and-after studies comparing ATCS interventions, with any control or another ATCS type were eligible for inclusion. Studies in all settings, for all consumers/carers, in any preventive healthcare or long term condition management role were eligible. Data collection and analysis We used standard Cochrane methods to select and extract data and to appraise eligible studies. Main results We included 132 trials (N = 4,669,689). Studies spanned across several clinical areas, assessing many comparisons based on evaluation of different ATCS types and variable comparison groups. Forty-one studies evaluated ATCS for delivering preventive healthcare, 84 for managing long-term conditions, and seven studies for appointment reminders. We downgraded our certainty in the evidence primarily because of the risk of bias for many outcomes. We judged the risk of bias arising from allocation processes to be low for just over half the studies and unclear for the remainder. We considered most studies to be at unclear risk of performance or detection bias due to blinding, while only 16% of studies were at low risk. We generally judged the risk of bias due to missing data and selective outcome reporting to be unclear. For preventive healthcare, ATCS (ATCS Plus, IVR, unidirectional) probably increase immunisation uptake in children (risk ratio (RR) 1.25, 95% confidence interval (CI) 1.18 to 1.32; 5 studies, N = 10,454; moderate certainty) and to a lesser extent in adolescents (RR 1.06, 95% CI 1.02 to 1.11; 2 studies, N = 5725; moderate certainty). The effects of ATCS in adults are unclear (RR 2.18, 95% CI 0.53 to 9.02; 2 studies, N = 1743; very low certainty). For screening, multimodal ATCS increase uptake of screening for breast cancer (RR 2.17, 95% CI 1.55 to 3.04; 2 studies, N = 462; high certainty) and colorectal cancer (CRC) (RR 2.19, 95% CI 1.88 to 2.55; 3 studies, N = 1013; high certainty) versus usual care. It may also increase osteoporosis screening. ATCS Plus interventions probably slightly increase cervical cancer screening (moderate certainty), but effects on osteoporosis screening are uncertain. IVR systems probably increase CRC screening at 6 months (RR 1.36, 95% CI 1.25 to 1.48; 2 studies, N = 16,915; moderate certainty) but not at 9 to 12 months, with probably little or no effect of IVR (RR 1.05, 95% CI 0.99, 1.11; 2 studies, 2599 participants; moderate certainty) or unidirectional ATCS on breast cancer screening. Appointment reminders delivered through IVR or unidirectional ATCS may improve attendance rates compared with no calls (low certainty). For long-term management, medication or laboratory test adherence provided the most general evidence across conditions (25 studies, data not combined). Multimodal ATCS versus usual care showed conflicting effects (positive and uncertain) on medication adherence. ATCS Plus probably slightly (versus control; moderate certainty) or probably (versus usual care; moderate certainty) improves medication adherence but may have little effect on adherence to tests (versus control). IVR probably slightly improves medication adherence versus control (moderate certainty). Compared with usual care, IVR probably improves test adherence and slightly increases medication adherence up to six months but has little or no effect at longer time points (moderate certainty). Unidirectional ATCS, compared with control, may have little effect or slightly improve medication adherence (low certainty). The evidence suggested little or no consistent effect of any ATCS type on clinical outcomes (blood pressure control, blood lipids, asthma control, therapeutic coverage) related to adherence, but only a small number of studies contributed clinical outcome data. The above results focus on areas with the most general findings across conditions. In condition-specific areas, the effects of ATCS varied, including by the type of ATCS intervention in use. Multimodal ATCS probably decrease both cancer pain and chronic pain as well as depression (moderate certainty), but other ATCS types were less effective. Depending on the type of intervention, ATCS may have small effects on outcomes for physical activity, weight management, alcohol consumption, and diabetes mellitus. ATCS have little or no effect on outcomes related to heart failure, hypertension, mental health or smoking cessation, and there is insufficient evidence to determine their effects for preventing alcohol/ substance misuse or managing illicit drug addiction, asthma, chronic obstructive pulmonary disease, HIV/AIDS, hypercholesterolaemia, obstructive sleep apnoea, spinal cord dysfunction or psychological stress in carers. Only four trials (3%) reported adverse events, and it was unclear whether these were related to the intervention

Differences in Response to a Dietary Intervention Between the General Population and First-Degree Relatives of Colorectal Cancer Patients

Photograph of a scene on Sardis Lake