Population Health Innovations and Payment to Address Social Needs Among Patients and Communities With Diabetes.

Policy Points Population health efforts to improve diabetes care and outcomes should identify social needs, support social needs referrals and coordination, and partner health care organizations with community social service agencies and resources. Current payment mechanisms for health care services do not adequately support critical up-front investments in infrastructure to address medical and social needs, nor provide sufficient incentives to make addressing social needs a priority. Alternative payment models and value-based payment should provide up-front funding for personnel and infrastructure to address social needs and should incentivize care that addresses social needs and outcomes sensitive to social risk. CONTEXT: Increasingly, health care organizations are implementing interventions to improve outcomes for patients with complex health and social needs, including diabetes, through cross-sector partnerships with nonmedical organizations. However, fee-for-service and many value-based payment systems constrain options to implement models of care that address social and medical needs in an integrated fashion. We present experiences of eight grantee organizations from the Bridging the Gap: Reducing Disparities in Diabetes Care initiative to improve diabetes outcomes by transforming primary care and addressing social needs within evolving payment models. METHODS: Analysis of eight grantees through site visits, technical assistance calls, grant applications, and publicly available data from US census data (2017) and from Health Resources and Services Administration Uniform Data System Resources data (2018). Organizations represent a range of payment models, health care settings, market factors, geographies, populations, and community resources. FINDINGS: Grantees are implementing strategies to address medical and social needs through augmented staffing models to support high-risk patients with diabetes (e.g., community health workers, behavioral health specialists), information technology innovations (e.g., software for social needs referrals), and system-wide protocols to identify high-risk populations with gaps in care. Sites identify and address social needs (e.g., food insecurity, housing), invest in human capital to support social needs referrals and coordination (e.g., embedding social service employees in clinics), and work with organizations to connect to community resources. Sites encounter challenges accessing flexible up-front funding to support infrastructure for interventions. Value-based payment mechanisms usually reward clinical performance metrics rather than measures of population health or social needs interventions. CONCLUSIONS: Federal, state, and private payers should support critical infrastructure to address social needs and incentivize care that addresses social needs and outcomes sensitive to social risk. Population health strategies that address medical and social needs for populations living with diabetes will need to be tailored to a range of health care organizations, geographies, populations, community partners, and market factors. Payment models should support and incentivize these strategies for sustainability.

An Emerging Model for Community Health Worker-Based Chronic Care Management for Patients With High Health Care Costs in Rural Appalachia.

Community health workers (CHWs) can improve patients' health by providing them with ongoing behavioral support during the health care experience, and they help decrease health care costs, especially among patients whose starting costs are high and among underserved and minority populations. We developed a CHW-based care model with the aim of improving outcomes and lowering costs for high-risk diabetes patients in rural Appalachia. Enrolled patients experienced a mean decrease in HbA1c of 2.4 percentage points, and 60% or more of patients with diabetes lowered their blood glucose between baseline and 6 to 12 months after enrollment. As health care providers and patients became familiar with this model of care management, enrollment in the program accelerated.

Age at diagnosis of diabetes in Appalachia.

BACKGROUND: Appalachia is a region of the United States noted for the poverty and poor health outcomes of its residents. Residents of the poorest Appalachian counties have a high prevalence of diabetes and risk factors (obesity, low income, low education, etc.) for type 2 diabetes. However, diabetes prevalence exceeds what these risk factors alone explain. Based on this, the history of poor health outcomes in Appalachia, and personally observed high rates of childhood obesity and lack of concern about prediabetes, we speculated that people in Appalachia with diagnosed diabetes might tend to be diagnosed younger than their non-Appalachian counterparts. METHODS: We used data from the Behavioral Risk Factor Surveillance System (2006-2008). We compared age at diagnosis among counties by Appalachian Regional Commission-defined level of economic development. To account for risk differences, we constructed a model for average age at diagnosis of diabetes, adjusting for county economic development, obesity, income, sedentary lifestyle, and other covariates. FINDINGS: After adjustment for risk factors for diabetes, people in distressed or at-risk counties (the least economically developed) had their diabetes diagnosed two to three years younger than comparable people in non-Appalachian counties. No significant differences between non-Appalachian counties and Appalachian counties at higher levels of economic development remained after adjusting. CONCLUSIONS: People in distressed and at-risk counties have poor access to care, and are unlikely to develop diabetes at the same age as their non-Appalachian counterparts but be diagnosed sooner. Therefore, people in distressed and at-risk counties are likely developing diabetes at younger ages. We recommend that steps to reduce health disparities between the poorest Appalachian counties and non-Appalachian counties be considered.

Appalachian regional model for organizing and sustaining county-level diabetes coalitions.

This article describes a model for developing diabetes coalitions in rural Appalachian counties and presents evidence of their sustainability. The rural Appalachian coalition model was developed through a partnership between two federal agencies and a regional university. Coalitions go through a competitive application process to apply for one-time $10,000 grants. The project has funded 7 to 9 coalitions annually since 2001, reaching 66 total coalitions in 2008. Sustainability of the coalitions is defined by the number of coalitions that voluntarily report on their programs and services. In 2008, 58 of 66 (87%) coalitions in the Appalachian region continue to function and voluntarily submit reports even after their grant funds have been depleted. The factors that may contribute to sustainability are discussed in the article. This model for organizing coalitions has demonstrated that it is possible for coalitions to be maintained over time in rural underserved areas in Appalachia.

Residence in a distressed county in Appalachia as a risk factor for diabetes, Behavioral Risk Factor Surveillance System, 2006-2007.

INTRODUCTION: We compared the risk of diabetes for residents of Appalachian counties to that of residents of non-Appalachian counties after controlling for selected risk factors in states containing at least 1 Appalachian county. METHODS: We combined Behavioral Risk Factor Surveillance System data from 2006 and 2007 and conducted a logistic regression analysis, with self-reported diabetes as the dependent variable. We considered county of residence (5 classifications for Appalachian counties, based on economic development, and 1 for non-Appalachian counties), age, sex, race/ethnicity, education, household income, smoking status, physical activity level, and obesity to be independent variables. The classification "distressed" refers to counties in the worst 10%, compared with the nation as a whole, in terms of 3-year unemployment rate, per capita income, and poverty. RESULTS: Controlling for covariates, residents in distressed Appalachian counties had 33% higher odds (95% confidence interval, 1.10-1.60) of reporting diabetes than residents of non-Appalachian counties. We found no significant differences between other classifications of Appalachian counties and non-Appalachian counties. CONCLUSION: Residents of distressed Appalachian counties are at higher risk of diabetes than are residents of other counties. States with distressed Appalachian counties should implement culturally sensitive programs to prevent diabetes.

Factors associated with integrating self-management support into primary care.

PURPOSE: The purpose of this article is to expand the understanding of self-management support by describing factors that contribute to implementing a comprehensive self-management program in primary care. METHODS: Four rural health centers in medically underserved areas participated in a study to document the implementation of a self-management program. This program consisted of a social marketing plan and decision-making tools to guide patients in making self-management behavior changes. The stages of change constructs of the transtheoretical model were used to design the social marketing plan. Key informant interviews were conducted at 6-month and 9-month intervals to document the implementation process. A standardized set of questions was used in the interviews. The data from the interviews were analyzed using content analysis techniques. RESULTS: One of the principle findings is that self-management support requires putting a system in place, not just adding a new component to primary care. The health centers that fully implemented the self-management program made an organizational commitment to keep self-management on the agenda in management meetings, clinical staff set the example by adopting self-management behaviors, and patient self-management support was implemented in multiple patient care venues. CONCLUSION: Primary care centers with limited financial resources are able to integrate self-management support into their system of chronic illness care.

A quality improvement tool to assess self-management support in primary care.

BACKGROUND: Self management is an essential, central component of effective care for diabetes and other chronic illnesses, yet very few instruments exist to assess delivery or consistency of self-management support. The Assessment of Primary Care Resources and Supports for Chronic Disease Self-Management (PCRS) tool assesses both organizational infrastructure and delivery of self-management support services. METHODS: The PCRS was developed by the Robert Wood Johnson Foundation Diabetes Initiative and underwent several stages of development, including three pilot tests, review by experts, and implementation by a national quality improvement (QI) program. RESULTS: The development and testing of the instrument resulted in the current 16-item measure. Use of the PCRS in a QI collaborative with 20 diverse health care teams across the United States demonstrated that the instrument is helpful in assessing areas for improvement. DISCUSSION: Initial experience suggests that the PCRS is a user-friendly self-assessment tool that primary care teams can use to assess their current capacity to support and implement consistent patient-centered self management. The initial evaluation indicates that the PCRS has acceptable psychometric properties and is applicable across different types of primary care teams and chronic illness conditions.

The accelerated residency program: the Marshall University family practice 9-year experience.

BACKGROUND: In 1989, the American Board of Family Practice (ABFP) approved the first of 12 accelerated residency programs in family practice. These experimental programs provide a 1-year experience for select medical students that combines the requirements of the fourth year of medical school with those of the first year of residency, reducing the total training time by 1 year. This paper reports on the achievements and limitations of the Marshall University accelerated residency program over a 9-year period that began in 1992. METHODS: Several parameters have been monitored since the inception of the accelerated program and provide the basis for comparison of accelerated and traditional residents. These include initial resident characteristics, performance outcomes, and practice choices. RESULTS: A total of 16 students were accepted into the accelerated track from 1992 through 1998. During the same time period, 44 residents entered the traditional residency program. Accelerated resident tended to be older and had more career experience than their traditional counterparts. As a group, the accelerated residents scored an average of 30 points higher on the final in-training exams provided by the ABFP. All residents in both groups remained at Marshall to complete the full residency training experience, and all those who have taken the ABFP certifying exam have passed. Accelerated residents were more likely to practice in West Virginia, consistent with one of the initial goals for the program. In addition, accelerated residents were more likely to be elected chief resident and choose an academic career than those in the traditional group. Both groups opted for small town or rural practice equally. CONCLUSIONS: The Marshall University family practice 9-year experience with the accelerated residency track demonstrates that for carefully selected candidates, the program can provide an overall shortened path to board certification and attract students who excel academically and have high leadership potential. Reports from other accelerated programs are needed to fully assess the outcomes of this experiment in postgraduate medical education.

Health and school outcomes during children's transition into adolescence.

PURPOSE: Normative biopsychosocial stressors that occur during entry into adolescence can affect school performance.As a set of resources for adapting to life's challenges, good health may buffer a child from these potentially harmful stressors. This study examined the associations between health (measured as well-being, functioning, symptoms, and chronic conditions) and school outcomes among children aged 9-13 years in 4th-8th grades. METHODS: We conducted a prospective cohort study of 1,479 children from 34 schools followed from 2006 to 2008. Survey data were obtained from children and their parents, and school records were abstracted. Measures of child self-reported health were dichotomized to indicate presence of a health asset. Outcomes included attendance, grade point average, state achievement test scores, and child-reported school engagement and teacher connectedness. RESULTS: Both the transition into middle school and puberty had independent negative influences on school outcomes. Chronic health conditions that affected children's functional status were associated with poorer academic achievement. The number of health assets that a child possessed was positively associated with school outcomes. Low levels of negative stress experiences and high physical comfort had positive effects on teacher connectedness, school engagement, and academic achievement, whereas bullying and bully victimization negatively affected these outcomes. Children with high life satisfaction were more connected with teachers, more engaged in schoolwork, and earned higher grades than those who were less satisfied. CONCLUSIONS: As children enter adolescence, good health may buffer them from the potentially negative effects of school and pubertal transitions on academic success.

School outcomes of children with special health care needs.

OBJECTIVE: To examine the associations between having a special health care need and school outcomes measured as attendance, student engagement, behavioral threats to achievement, and academic achievement. PARTICIPANTS AND METHODS: A total of 1457 children in the fourth through sixth grades from 34 schools in 3 school districts and their parents provided survey data; parents completed the Children With Special Health Care Needs Screener. School records were abstracted for attendance, grades, and standardized achievement test scores. RESULTS: Across 34 schools, 33% of children screened positive for special health care needs. After adjusting for sociodemographic and school effects, children with special health care needs had lower motivation to do well in school, more disruptive behaviors, and more frequent experiences as a bully victim. They experienced significantly lower academic achievement, as measured by grades, standardized testing, and parental-assessed academic performance. These findings were observed for children who qualified as having a special health care need because they had functional limitations attributed to a chronic illness or a behavioral health problem but not for those who qualified only because they took prescription medications. CONCLUSIONS: Specific subgroups of children with special health care needs are at increased risk for poor school outcomes. Health and school professionals will need to collaborate to identify these children early, intervene with appropriate medical and educational services, and monitor long-term outcomes.