Exploring Models for Youth Engagement in Community Health Planning: The Youth-led Community Health Learning Initiative.

BACKGROUND: Community health assessment and improvement planning processes (CHA/CHIP) are often challenged with developing health actions that reach across a large community, city or county and that incorporate locally informed issues and place-specific strategies. In co-learning about approaches for enhancing CHA/CHIP processes through youth stakeholder input, a partnership of academic and community leaders came together to create The Youth-Led Community Health Learning Initiative (YLCHLI), a 1-year pilot initiative aimed at identifying health needs and assets in partnership with youth leaders and two central Texas communities. OBJECTIVE: To describe our approach, key findings, and lessons learned in implementing the YLCHLI in two different organizational settings: a high school-based setting and a community-based organization setting. METHODS: Guided by a community advisory board and the Mobilizing for Action through Planning and Partnerships framework, the YLCHLI incorporated a mixed methods design consisting of quantitative community health indicator analysis for topics identified in the Austin/Travis County CHA followed by a youth-led qualitative assessment of selected health issues via methods that included participatory mapping, data walks, and photovoice. RESULTS: Youth-informed findings provided rich insights and context for understanding disparities in selected health issues, including identification of social and environmental barriers to physical activity, healthy eating, health services, and mental health, and locally informed recommendations for community health improvement. CONCLUSION: High school health science tracks and community- based organizations represent promising settings for fostering community partnerships and youth engagement in identifying local health needs and opportunities that can enhance community health improvement planning and contribute to positive youth development.

What Characteristics Influence Whether Rural Beneficiaries Receiving Care From Urban Hospitals Return Home for Skilled Nursing Care?

PURPOSE: Skilled nursing care (SNC) provides Medicare beneficiaries short-term rehabilitation from an acute event. The purpose of this study is to assess beneficiary, market, and hospital factors associated with beneficiaries receiving care near home. METHODS: The population includes Medicare beneficiaries who live in a rural area and received acute care from an urban facility in 2013. "Near home" was defined 3 different ways based on distances from the beneficiary's home to the nearest source of SNC. Results include unadjusted means and odds ratios from logistic regression. FINDINGS: About 69% of rural beneficiaries receiving acute care in an urban location returned near home for SNC. Beneficiaries returning home were white (odds ratio [OR] black: 0.69; other race: 0.79); male (OR: 1.07); older (OR age 85+ [vs 65-69]: 1.14); farther from SNC (OR: 1.01 per mile); closer to acute care (OR: 0.28, logged miles); and received acute care from hospitals that did not own a skilled nursing facility (owned OR: 0.77) and hospitals with: no swing bed (swing bed OR: 0.47), high case mix (OR: 3.04), and nonprofit status (for-profit OR: 0.85). Results varied somewhat across definitions of "near home." CONCLUSIONS: Rural Medicare beneficiaries who received acute care far from home were more likely to receive SNC far from home. Because Medicare beneficiaries have the choice of where to receive SNC, policy makers may consider ensuring that new payment models do not incentivize provision of SNC away from home.

Associations of educational attainment, occupation, and community poverty with hip osteoarthritis.

OBJECTIVE: To examine cross-sectional baseline data from the Johnston County Osteoarthritis Project for the association between individual and community socioeconomic status (SES) measures with hip osteoarthritis (OA) outcomes. METHODS: We analyzed data on 3,087 individuals (68% white and 32% African American). Educational attainment and occupation were used as individual measures of SES. Census block group household poverty rate was used as a measure of community SES. Hip OA outcomes included radiographic OA and symptomatic OA in one or both hip joints. Multivariable logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for the association of each hip OA outcome with each SES variable separately, and then with all SES measures simultaneously. Associations between hip OA outcomes and SES variables were evaluated for effect modification by race and sex. RESULTS: Living in a community of high household poverty rate showed independent associations with hip radiographic OA in one or both hips (OR 1.50, 95% CI 1.18-1.92) and bilateral (both hips) radiographic OA (OR 1.87, 95% CI 1.32-2.66). Similar independent associations were found between low educational attainment among those with symptomatic OA in one or both hips (OR 1.44, 95% CI 1.09-1.91) or bilateral symptomatic OA (OR 1.91, 95% CI 1.08-3.39), after adjusting for all SES measures simultaneously. No significant associations were observed between occupation and hip OA outcomes, nor did race or sex modify the associations. CONCLUSION: Our data provide evidence that hip OA outcomes are associated with both education and community SES measures, associations that remained after adjustment for covariates and all SES measures.

Associations of educational attainment, occupation and community poverty with knee osteoarthritis in the Johnston County (North Carolina) osteoarthritis project.

INTRODUCTION: The purpose of this study was to examine data from the Johnston County Osteoarthritis (OA) Project for independent associations of educational attainment, occupation and community poverty with tibiofemoral knee OA. METHODS: A cross-sectional analysis was conducted on 3,591 individuals (66% Caucasian and 34% African American). Educational attainment (< 12 years or ≥12 years), occupation (non-managerial or not), and census block group household poverty rate (< 12%, 12 to 25%, > 25%) were examined separately and together in logistic models adjusting for covariates of age, gender, race, body mass index (BMI), smoking, knee injury and occupational activity score. Outcomes were presence of radiographic knee OA (rOA), symptomatic knee OA (sxOA), bilateral rOA and bilateral sxOA. RESULTS: When all three socioeconomic status (SES) variables were analyzed simultaneously, low educational attainment was significantly associated with rOA (odds ratio (OR) = 1.44, 95% confidence interval (CI) 1.20, 1.73), bilateral rOA (OR = 1.43, 95% CI 1.13, 1.81), and sxOA (OR = 1.66, 95% CI 1.34, 2.06), after adjusting for covariates. Independently, living in a community of high household poverty rate was associated with rOA (OR = 1.83, 95% CI 1.43, 2.36), bilateral rOA (OR = 1.56, 95% CI 1.12, 2.16), and sxOA (OR = 1.36, 95% CI 1.00, 1.83). Occupation had no significant independent association beyond educational attainment and community poverty. CONCLUSIONS: Both educational attainment and community SES were independently associated with knee OA after adjusting for primary risk factors for knee OA.

Health-related quality of life in adults from 17 family practice clinics in North Carolina.

INTRODUCTION: We examined health-related quality of life (HRQOL) in white and African American patients based on their own and their community's socioeconomic status. METHODS: Participants were 4,565 adults recruited from 17 family physician practices in urban and rural areas of North Carolina. Education was used as a proxy for individual socioeconomic status, and the census block-group poverty level was used as a proxy for community socioeconomic status. HRQOL measures were the 12-Item Short Form Survey Instrument, physical component summary (PCS) and mental component summary (MCS), and 3 Centers for Disease Control and Prevention HRQOL healthy days measures. Multilevel analyses examined independent associations of individual and community poverty level with HRQOL, adjusting for demographics and clustering by family practice. Analyses were stratified by race and were conducted on subgroups of arthritis and cardiovascular disease patients. RESULTS: Among whites, all 5 HRQOL measures were significantly associated with the lowest individual socioeconomic status, and 4 HRQOL measures were associated with the lowest community socioeconomic status (MCS being the exception). Among African Americans, 4 HRQOL measures were significantly associated with the lowest individual socioeconomic status and the lowest community socioeconomic status (PCS being the exception). Arthritis and cardiovascular disease subgroup analyses showed generally analogous findings. CONCLUSION: Better HRQOL measures generally were associated with low levels of community poverty and high levels of education, emphasizing the need for further exploration of factors that influence health.

Arthritis in the family practice setting: associations with education and community poverty.

OBJECTIVE: To examine associations of self-reported arthritis in 25 urban and rural family practice clinics with education (individual socioeconomic status) and community poverty (community socioeconomic status). METHODS: A total of 7,770 patients at 25 family practice sites across North Carolina self-reported whether they had arthritis. Education was measured as less than a high school (HS) degree, a HS degree, and more than a HS degree. The US Census 2000 block group poverty rate (percentage of households in poverty in that block group) was grouped into low, middle, and high tertiles. We assumed heterogeneity by race (non-Hispanic white and African American) for the effects of these sociodemographic variables, and therefore stratified by race. Multilevel analyses were performed using a 2-level mixed logistic model to examine the independent associations and joint effects of education and poverty with self-reported arthritis as the outcome, adjusting for age, sex, and body mass index. RESULTS: White participants with less than a HS degree living in block groups with high poverty had 1.55 times the odds (95% confidence interval [95% CI] 1.10-2.17) of reporting arthritis compared with white participants with more than a HS degree and low poverty rates. African American participants with less than a HS degree and high poverty rates had 2.06 times the odds (95% CI 1.16-3.66) of reporting arthritis compared with African American participants with more than a HS degree and low poverty rates. CONCLUSION: In the family practice setting, both disadvantaged white and African American participants showed increased odds of self-reported arthritis, with stronger associations in African Americans.

Designating places and populations as medically underserved: a proposal for a new approach.

This article describes the development of a theory-based, data-driven replacement for the Health Professional Shortage Area (HPSA) and Medically Underserved Area (MUA) designation systems. Data describing utilization of primary medical care and the distribution of practitioners were used to develop estimates of the effects of demographic and community characteristics on use of primary medical care. A scoring system was developed that estimates each community's effective access to primary care. This approach was reviewed and contributed to by stakeholder groups. The proposed formula would designate over 90% of current geographic and low-income population HPSA designations. The scalability of the method allows for adjustment for local variations in need and was considered acceptable by stakeholder groups. A data-driven, theory-based metric to calculate relative need for geographic areas and geographically-bounded special populations can be developed and used. Its use, however, requires careful explanation to and support from affected groups.

The effect of rural hospital closures on community economic health.

OBJECTIVE: To examine the effect of rural hospital closures on the local economy. DATA SOURCES: U.S. Census Bureau, OSCAR, Medicare Cost Reports, and surveys of individuals knowledgeable about local hospital closures. STUDY DESIGN: Economic data at the county level for 1990-2000 were combined with information on hospital closures. The study sample was restricted to rural counties experiencing a closure during the sample period. Longitudinal regression methods were used to estimate the effect of hospital closure on per-capita income, unemployment rate, and other community economic measures. Models included both leading and lagged closure terms allowing a preclosure economic downturn as well as time for the closure to be fully realized by the community. DATA COLLECTION: Information on closures was collected by contacting every state hospital association, reconciling information gathered with that contained in the American Hospital Association file and OIG reports. PRINCIPAL FINDINGS: Results indicate that the closure of the sole hospital in the community reduces per-capita income by 703 dollars (p<0.05) or 4 percent (p<0.05) and increases the unemployment rate by 1.6 percentage points (p<0.01). Closures in communities with alternative sources of hospital care had no long-term economic impact, although income decreased for 2 years following the closure. CONCLUSIONS: The local economic effects of a hospital closure should be considered when regulations that affect hospitals' financial well-being are designed or changed.

How might the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 affect the financial viability of rural pharmacies? An analysis of preimplementation prescription volume and payment sources in rural and urban areas.

CONTEXT: Passage of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA) has created interest in how the legislation will affect access to prescription drugs among rural beneficiaries. Policy attention has focused to a much lesser degree on the implications of the MMA for the financial viability of rural pharmacies. PURPOSE: This article presents descriptive information on mail-order prescriptions, volume, and payer type of retail prescriptions in rural vs urban areas. Together, these data provide a baseline for evaluating how implementation of the MMA may affect the financial viability of rural independent pharmacies. METHODS: Projections of prescriptions dispensed from retail and mail-order pharmacies in 2002 for the total US and a sample of 17 states were obtained from IMS Health. FINDINGS: The volume of mail-order prescriptions is small. Rural providers prescribed fewer retail and mail-order prescriptions per person, but more units per person. Rural areas have a higher percentage of prescriptions paid for by cash (18% vs 13%) and Medicaid (16% vs 10%) and a lower percentage of third-party payers than urban areas. Significant variation in volume and payer type exists between states. CONCLUSIONS: Rural, independent pharmacies may be negatively affected by MMA implementation as business shifts from cash to third-party reimbursement. The high degree of variation between states also has potentially important implications for the implementation of Prescription Drug Plan regions under MMA.