Building Statewide Quality Improvement Capacity to Improve Cardiovascular Care and Health Equity: Lessons from the Tennessee Heart Health Network.

DRIVING FORCES: Many states with high rates of cardiovascular disease (CVD) lack statewide quality improvement (QI) infrastructure (for example, resources, leadership, community) to address relevant health needs of the population. Academic health centers are well positioned to play a central role in addressing this deficiency. This article describes early experience and lessons learned in building statewide QI infrastructure through the Tennessee Heart Health Network (Network). APPROACH: A statewide, multistakeholder network composed of primary care practices (PCPs), health systems, health plans, QI organizations, patients, and academic institutions was led by the University of Tennessee Health Science Center (UTHSC), an academic health center, to improve cardiovascular health by supporting dissemination and implementation of patient-centered outcomes research (PCOR) evidence-based interventions in primary care. PCPs were required to select and implement at least one of three interventions (health coaching, tailored health-related text messaging, and pharmacist-physician collaboration). OUTCOMES AND KEY INSIGHTS: Thirty statewide organizational partners joined the Network in year one, including 18 health systems representing 77 PCPs (30.0% of 257 potentially eligible PCPs identified) with approximately 300,000 patients. The organizational partners share EHRs for the ongoing tracking and reporting of key health metrics, including hypertension control and delivery of tobacco cessation counseling. Of the 77 PCPs, 62 continue participation after year two (80.5% retention). Main barriers to participation and reasons for discontinuing participation included reluctance to share data and changes in leadership at the health system level. These 62 PCPs selected the following interventions to implement: health coaching (41.9%), tailored health-related text messages (48.4%), and pharmacist-physician collaboration (40.3%). CONCLUSION AND WHAT'S NEXT: Academic health centers have broad reach and high acceptability by diverse stakeholders. Tennessee's experience illustrates how academic health centers can serve as platforms for building a statewide infrastructure for disseminating, implementing, and sustaining QI interventions at the practice level. Assessment of Network impact is ongoing.

Racial differences in healthcare expenditures for prevalent multimorbidity combinations in the USA: a cross-sectional study.

BACKGROUND: We aimed to model total charges for the most prevalent multimorbidity combinations in the USA and assess model accuracy across Asian/Pacific Islander, African American, Biracial, Caucasian, Hispanic, and Native American populations. METHODS: We used Cerner HealthFacts data from 2016 to 2017 to model the cost of previously identified prevalent multimorbidity combinations among 38 major diagnostic categories for cohorts stratified by age (45-64 and 65 +). Examples of prevalent multimorbidity combinations include lipedema with hypertension or hypertension with diabetes. We applied generalized linear models (GLM) with gamma distribution and log link function to total charges for all cohorts and assessed model accuracy using residual analysis. In addition to 38 major diagnostic categories, our adjusted model incorporated demographic, BMI, hospital, and census division information. RESULTS: The mean ages were 55 (45-64 cohort, N = 333,094) and 75 (65 + cohort, N = 327,260), respectively. We found actual total charges to be highest for African Americans (means $78,544 [45-64], $176,274 [65 +]) and lowest for Hispanics (means $29,597 [45-64], $66,911 [65 +]). African American race was strongly predictive of higher costs (p < 0.05 [45-64]; p < 0.05 [65 +]). Each total charge model had a good fit. With African American as the index race, only Asian/Pacific Islander and Biracial were non-significant in the 45-64 cohort and Biracial in the 65 + cohort. Mean residuals were lowest for Hispanics in both cohorts, highest in African Americans for the 45-64 cohort, and highest in Caucasians for the 65 + cohort. Model accuracy varied substantially by race when multimorbidity grouping was considered. For example, costs were markedly overestimated for 65 + Caucasians with multimorbidity combinations that included heart disease (e.g., hypertension + heart disease and lipidemia + hypertension + heart disease). Additionally, model residuals varied by age/obesity status. For instance, model estimates for Hispanic patients were highly underestimated for most multimorbidity combinations in the 65 + with obesity cohort compared with other age/obesity status groupings. CONCLUSIONS: Our finding demonstrates the need for more robust models to ensure the healthcare system can better serve all populations. Future cost modeling efforts will likely benefit from factoring in multimorbidity type stratified by race/ethnicity and age/obesity status.

Age-related differences in risks and outcomes of 30-day readmission in adults with sickle cell disease.

BACKGROUND: Literature on 30-day readmission in adults with sickle cell disease (SCD) is limited. This study examined the overall and age-stratified rates, risk factors, and healthcare resource utilization associated with 30-day readmission in this population. METHODS: Using the Nationwide Readmissions Database, a retrospective cohort study was conducted to identify adult patients (aged ≥ 18) with SCD in 2016. Patients were stratified by age and followed for 30 days to assess readmission following an index discharge. The primary outcome was 30-day unplanned all-cause readmission. Secondary outcomes included index hospitalization costs and readmission outcomes (e.g., time to readmission, readmission costs, and readmission lengths of stay). Separate generalized linear mixed models estimated the adjusted odds ratios (aORs) for associations of readmission with patient and hospital characteristics, overall and by age. RESULTS: Of 15,167 adults with SCD, 2,863 (18.9%) experienced readmission. Both the rates and odds of readmission decreased with increasing age. The SCD complications vaso-occlusive crisis and end-stage renal disease (ESRD) were significantly associated with increased likelihood of readmission (p < 0.05). Age-stratified analyses demonstrated that diagnosis of depression significantly increased risk of readmission among patients aged 18-to-29 years (aOR = 1.537, 95%CI: 1.215-1.945) but not among patients of other ages. All secondary outcomes significantly differed by age (p < 0.05). CONCLUSION: This study demonstrates that patients with SCD are at very high risk of 30-day readmission and that younger adults and those with vaso-occlusive crisis and ESRD are among those at highest risk. Multifaceted, age-specific interventions targeting individuals with SCD on disease management are needed to prevent readmissions.

Comorbidities and neighborhood factors associated with prescription of sodium-glucose cotransporter protein-2 inhibitors and glucagon-like peptide-1 receptor agonists among medically underserved populations.

BACKGROUND: Evidence from clinical trials shows that newer second-line diabetes medications-glucagon-like peptide 1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter 2 inhibitors (SGLT2is)-have cardio-renal protective effects in addition to their glucose-lowering properties. Despite strong evidence of benefits, there is limited evidence regarding prescribing patterns for these medications, especially among populations at high risk for disparities. OBJECTIVE: To examine the associations of cardio-renal and obesity comorbidities and neighborhood factors with the prescribing of GLP-1RAs or SGLT2is in comparison with dipeptidyl peptidase 4 inhibitors (DPP-4is) or sulfonylureas (SFUs) and for each of the newer second-line diabetes medications (GLP-1RA vs DPP-4i, SGLT2i vs DPP-4i, GLP-1RA vs SFU, and SGLT2i vs SFU) in medically underserved populations. METHODS: A retrospective cohort study was conducted using electronic medical records from a health care delivery system that serves medically underserved populations in the Mid-South region of the United States. Metformin-treated adult patients with type 2 diabetes, and at least 1 prescription for GLP-1RA, SGLT2i, DPP-4i, or SFU class medications, were identified between April 2016 and August 2021. Neighborhood factors were assessed at the census tract level by geocoding and linking patient addresses to neighborhood-level risk factors. Using multilevel logistic regression models, we examined the associations of comorbidities and neighborhood factors with the prescription of newer second-line diabetes medications. RESULTS: 7,723 patients received newer second-line diabetes medications, with 16% prescribed GLP-1RAs, 11% prescribed SGLT2is, 28% prescribed DPP-4is, and 45% prescribed SFUs. Patients with cerebrovascular disease were significantly less likely to receive newer second-line diabetes medications (odds ratio [OR] = 0.65, 95% CI = 0.52-0.80). Patients with obesity were more likely to receive newer second-line diabetes medications (OR = 1.68, 95% CI = 1.48-1.90). Living in neighborhoods with higher proportions of college graduates was associated with a higher likelihood of receiving newer second-line diabetes medications (quartile 3 vs 1: OR = 1.30, 95% CI = 1.06-1.59; and quartile 4 vs 1: OR = 1.46, 95% CI = 1.13-1.88). CONCLUSIONS: Our findings demonstrate substantial underprescribing and significant clinical and neighborhood variations in the use of newer second-line diabetes medications. We found lower use of newer second-line diabetes medications among patients with cerebrovascular disease and higher use in those with obesity. Our findings also suggest that newer second-line diabetes medications are first adopted by those in higher socioeconomic groups, thus increasing disparities in care. DISCLOSURES: Dr Surbhi reports grants or contracts from the Tennessee Department of Health, Agency for Healthcare Research and Quality, and PhRMA Foundation. Dr Bailey reports honoraria from the SouthEast Texas Chapter of the American College of Healthcare Executives, leadership or fiduciary role in the Coalition for Better Health and The Healthy City, Inc., and stock or stock options in Proctor and Gamble, Walmart, and Apple. Dr Kovesdy reports personal fees from Bayer, Abbott, AstraZeneca, Takeda, Tricida, Akebia, Cara Therapeutics, Vifor, Rockwell, CSL Behring, Boehringer Ingelheim, and GSK, outside the submitted work. The other authors report no conflicts of interest.

Longitudinal Associations of Staff Shortages and Staff Levels with Health Outcomes in Nursing Homes.

OBJECTIVES: To examine whether facility-reported staff shortages and total staff levels were independently associated with changes in nursing home (NH) outcomes in 2020. DESIGN: Longitudinal cohort study. SETTING AND PARTICIPANTS: A total of 8466 NHs with staffing and outcome data. METHODS: This study used NH COVID-19 Public File (2020), Nursing Home Compare (2019-2020), and Payroll-Based Journal data (2019-2020). Outcome measures included the percentage of long-stay residents in a facility with declines in activities in daily living (ADLs), decreases in mobility, weight loss, and pressure ulcers in 2020 Q2, 2020 Q3, and 2020 Q4. Independent variables were whether NHs reported any shortage of aides or licensed nurses and total staff hours per resident day (HPRD). Separate 2-level (NH, state) Hierarchical Generalized Linear Mixed models examined the association of facility-reported shortages and staff hours with key NH resident outcomes, controlling for NH characteristics and COVID-19 infections. RESULTS: The weekly percentage of NHs reporting any staff shortage averaged 20%. Total staff HPRD increased slightly from 3.7 in 2019 to 3.8 in 2020. Health outcomes were stable during 2019 and 2020 Q1 but worsened substantially starting in 2020 Q2. For example, the percentage of residents with mobility loss increased from 16.2% in 2020 Q1 to 27.9% in 2020 Q4. Facility-reported staff shortages were associated with an increase in the proportion of residents with an ADL decline (0.54 percentage points), mobility loss (0.80 percentage points), weight loss (0.22 percentage points), and pressure ulcers (0.22 percentage points) (all P < .01). Total staff HPRD was not associated with changes in any outcomes (all P > .05). CONCLUSIONS AND IMPLICATIONS: NHs reported worsened health outcomes among long-stay residents in 2020, with worse outcomes found among facilities that reported staff shortages but not among those with lower total staff levels. Facility-reported shortages provide important quality information during the COVID-19 pandemic.

Effect of continuity of care on emergency department and hospital visits for obesity-associated chronic conditions: A federated cohort meta-analysis.

BACKGROUND: Obesity-associated chronic conditions (OCC) are prevalent in medically underserved areas of the Southern US. Continuity of care with a primary care provider is associated with reduced preventable healthcare utilization, yet little is known regarding the impact of continuity of care among populations with OCC. This study aimed to examine whether continuity of care protects patients living with OCC and the subgroup with type 2 diabetes (OCC+T2D) from emergency department (ED) and hospitalizations, and whether these effects are modified by race and patient residence in health professional shortage areas (HPSA) METHODS: We conducted a retrospective federated cohort meta-analysis of 2015-2018 data from four large practice-based research networks in the Southern U.S. among adult patients with obesity and one more more additional diagnosed OCC. The outcomes included overall and preventable ED visits and hospitalizations. Continuity of care was assessed at the clinic-level using the Bice-Boxerman Continuity of Care Index RESULTS: A total of 111,437 patients with OCC and 47,071 patients with OCC+T2D from the four large practice-based research networks in the South were included in the meta-analysis. Continuity of Care index varied among sites from a mean (SD) of 0.6 (0.4) to 0.9 (0.2). Meta-analysis demonstrated that, regardless of race or residence in HPSA, continuity of care significantly protected OCC patients from preventable ED visits (IRR:0.95; CI:0.92-0.98) and protected OCC+T2D patients from overall ED visits (IRR:0.92; CI:0.85-0.99), preventable ED visits (IRR:0.95; CI:0.91-0.99), and overall hospitalizations (IRR:0.96; CI:0.93-0.98) CONCLUSION: Improving continuity of care may reduce ED and hospital use for patients with OCC and particularly those with OCC+T2D.

Integrating Lay Health Coaches Into Primary Care: Acceptability, Credibility, and Effectiveness From the Provider Perspective.

The purpose of this mixed-methods, cross-sectional study was to assess the acceptability, effectiveness, and credibility of lay health coaches from the perspective of primary care personnel during coach integration into primary care teams through the Management of Diabetes in Everyday Life (MODEL) study. Surveys of 46 primary care clinic personnel were conducted in June 2017 and July 2017 to assess the acceptability, effectiveness, and credibility of lay health coaches in the clinics. Clinic personnel rated coach acceptability, impact, and credibility on a five-point Likert scale as 3.78, 3.76-4.04, and 3.71-3.95, respectively. Additionally, interviews revealed support for a team-based approach and recognition of the potential of coaches to enhance care. In the interviews clinic personnel also reported a lack of provider time to counsel patients as well as a need for improved provider-coach communication.

Feasibility of a Brief Intervention to Increase Rapid Primary Care Follow-Up Among African American Patients With Uncontrolled Diabetes.

The management of diabetes, like many other chronic conditions, depends on effective primary care engagement. Patients with diabetes without a usual source of care have a higher risk of uncontrolled disease, hospitalizations, and early death. Our objective was to study the effect of a brief intervention to help patients in medically underserved areas obtain rapid primary care follow-up appointments following hospitalization. We performed a pilot pragmatic randomized controlled trial of adult patients with uncontrolled diabetes who had been admitted to one of three hospitals in the Memphis, TN, area. The enhanced usual care arm received a list of primary care clinics, whereas the intervention group had an appointment made for them preceding their index discharge. Patients in both groups were evaluated for primary care appointment attendance within seven and fourteen days of index discharge. In addition, we examined barriers patients encounter to receiving rapid primary care follow-up using a secret shopper approach to assess wait times when calling primary care offices. Twelve patients were enrolled with six in each trial arm. Baseline demographics, access to medical care, and health literacy were similar across the groups. Primary care follow-up was also similar across the groups; no improvements in follow-up rates were seen in the group receiving assistance with making appointments. Identified barriers to making primary care follow-up appointments included inability to schedule an urgent appointment, long hold times when calling doctor's offices and lack of transportation. Additionally, hold times when calling primary care offices were found to be excessively long in the medically underserved areas studied. The study demonstrates the feasibility of providing patient assistance with scheduling rapid primary care follow-up appointments at the time of discharge and the potential to improve care transitions and access to primary care among patients living in medically underserved areas. Larger pragmatic trials are needed to further test alternative approaches for insuring rapid primary care follow-up in vulnerable patients with ambulatory care-sensitive chronic conditions.

Association of Weight Loss With Type 2 Diabetes Remission Among Adults in Medically Underserved Areas: A Retrospective Cohort Study.

PURPOSE: To examine the association between weight loss and type 2 diabetes remission among vulnerable populations living in medically underserved areas of the Mid-Southern United States. DESIGN: Quantitative, retrospective cohort study. SETTING: 114 ambulatory sites and 5 adults' hospitals in the Mid-South participating in a regional diabetes registry. PARTICIPANTS: 9,900 adult patients with type 2 diabetes, stratified by remission status, with 1 year of baseline electronic medical record data, and 1 year of follow-up data for the 2015-2018 study period. MEASURES: The outcomes were diabetes remissions, categorized as any remission, partial remission, and complete remission based on the guidelines of the American Diabetes Association. The exposure was weight loss, calculated by the change in the Body Mass Index (BMI) as a proxy measure. ANALYSIS: χ2 tests, Fisher's exact tests, and the Mann-Whitney U-test were used to examine the differences in patient characteristics by remission status across the 3 remission categories, as appropriate. Multiple multivariable logistic regressions adjusting for confounders were performed to estimate the adjusted odds ratios (aORs) for the associations between weight loss and diabetes remission. RESULTS: Among 9,900 patients identified, a reduction of 0.3 kg/m2 (standard deviation: 2.5) in the average BMI from the baseline to the follow-up was observed. 10.8% achieved any type of remission, with 9.8% for partial and 1.0% for complete remissions. Greater weight loss was significantly associated with an increased likelihood of any (aOR = 1.07, 95% confidence interval (CI), 1.06-1.08), partial (aOR 1.06, 95% CI, 1.04-1.07), and complete diabetes remission (aOR 1.10, 95% CI, 1.07-1.13). CONCLUSIONS: Weight loss is significantly associated with diabetes remission among patients living in medically underserved areas, but complete remission is rare.

Democracy and case fatality rate of COVID-19 at early stage of pandemic: a multicountry study.

Many studies have evaluated factors that influence the course of the COVID-19 pandemic in different countries. This multicountry study assessed the influence of democracy and other factors on the case fatality rate of COVID-19 during the early stage of the pandemic. We accessed the World Health Organization, World Bank, and the Democracy Index 2019 databases for data from the 148 countries. Multiple analyses were conducted to examine the association between the Democracy Index and case fatality rate of COVID-19. Within 148 countries, the percentage of the population aged 65 years and above (p = 0.0193), and health expenditure as a percentage of GDP (p = 0.0237) were positively associated with countries' case fatality rates. By contrast, hospital beds per capita helped to reduce the case fatality rates. In particular, the Democracy Index was positively associated with case fatality rates in a subgroup of 47 high-income countries. This study suggests that enhancing the health system with increased hospital beds and healthcare workforce per capita should reduce case fatality rate. The findings suggest that a higher Democracy Index is associated with more deaths from COVID-19 at the early stage of the pandemic, possibly due to the decreased ability of the government.

Early Patient-Centered Outcomes Research Experience With the Use of Telehealth to Address Disparities: Scoping Review.

BACKGROUND: Health systems and providers across America are increasingly employing telehealth technologies to better serve medically underserved low-income, minority, and rural populations at the highest risk for health disparities. The Patient-Centered Outcomes Research Institute (PCORI) has invested US $386 million in comparative effectiveness research in telehealth, yet little is known about the key early lessons garnered from this research regarding the best practices in using telehealth to address disparities. OBJECTIVE: This paper describes preliminary lessons from the body of research using study findings and case studies drawn from PCORI seminal patient-centered outcomes research (PCOR) initiatives. The primary purpose was to identify common barriers and facilitators to implementing telehealth technologies in populations at risk for disparities. METHODS: A systematic scoping review of telehealth studies addressing disparities was performed. It was guided by the Arksey and O'Malley Scoping Review Framework and focused on PCORI's active portfolio of telehealth studies and key PCOR identified by study investigators. We drew on this broad literature using illustrative examples from early PCOR experience and published literature to assess barriers and facilitators to implementing telehealth in populations at risk for disparities, using the active implementation framework to extract data. Major themes regarding how telehealth interventions can overcome barriers to telehealth adoption and implementation were identified through this review using an iterative Delphi process to achieve consensus among the PCORI investigators participating in the study. RESULTS: PCORI has funded 89 comparative effectiveness studies in telehealth, of which 41 assessed the use of telehealth to improve outcomes for populations at risk for health disparities. These 41 studies employed various overlapping modalities including mobile devices (29/41, 71%), web-based interventions (30/41, 73%), real-time videoconferencing (15/41, 37%), remote patient monitoring (8/41, 20%), and store-and-forward (ie, asynchronous electronic transmission) interventions (4/41, 10%). The studies targeted one or more of PCORI's priority populations, including racial and ethnic minorities (31/41, 41%), people living in rural areas, and those with low income/low socioeconomic status, low health literacy, or disabilities. Major themes identified across these studies included the importance of patient-centered design, cultural tailoring of telehealth solutions, delivering telehealth through trusted intermediaries, partnering with payers to expand telehealth reimbursement, and ensuring confidential sharing of private information. CONCLUSIONS: Early PCOR evidence suggests that the most effective health system- and provider-level telehealth implementation solutions to address disparities employ patient-centered and culturally tailored telehealth solutions whose development is actively guided by the patients themselves to meet the needs of specific communities and populations. Further, this evidence shows that the best practices in telehealth implementation include delivery of telehealth through trusted intermediaries, close partnership with payers to facilitate reimbursement and sustainability, and safeguards to ensure patient-guided confidential sharing of personal health information.

Refining a traditional urban-rural classification approach to better assess heterogeneity of treatment effects in patient-centered outcomes research.

This article describes a rationale and approach for modifying the traditional rural-urban commuting area (RUCA) coding scheme used to classify U.S. ZIP codes to enable suburban/rural vs. urban core comparisons in health outcomes research that better reflect current geographic differences in access to care in U.S. populations at risk for health disparities. The proposed method customization is being employed in the Patient-Centered Outcomes Research Institute-funded Management Of Diabetes in Everyday Life (MODEL) study to assess heterogeneity of treatment effect for patient-centered diabetes self-care interventions across the rural-urban spectrum. The proposed suburban/rural vs. urban core classification scheme modification is based on research showing that increasing suburban poverty and rapid conversion of many rural areas into suburban areas in the U.S. has resulted in similar health care access problems in areas designated as rural or suburban.•The RUCA coding scheme was developed when a much higher percentage of U.S. individuals resided in areas with very low population density.•Using the MODEL study example, this study demonstrates that the RUCA classification scheme using ZIP codes does not reflect real differences in health care access experienced by medically underserved study participants.•Both internal and external validation data suggest that the proposed suburban/rural vs. urban core customization of the RUCA geographic coding scheme better reflects real differences in healthcare access and is better able to assess the differential impact of clinical interventions designed to address geographic differences in access among vulnerable populations.

Using a Personal Health Library-Enabled mHealth Recommender System for Self-Management of Diabetes Among Underserved Populations: Use Case for Knowledge Graphs and Linked Data.

BACKGROUND: Traditionally, digital health data management has been based on electronic health record (EHR) systems and has been handled primarily by centralized health providers. New mechanisms are needed to give patients more control over their digital health data. Personal health libraries (PHLs) provide a single point of secure access to patients' digital health data and enable the integration of knowledge stored in their digital health profiles with other sources of global knowledge. PHLs can help empower caregivers and health care providers to make informed decisions about patients' health by understanding medical events in the context of their lives. OBJECTIVE: This paper reports the implementation of a mobile health digital intervention that incorporates both digital health data stored in patients' PHLs and other sources of contextual knowledge to deliver tailored recommendations for improving self-care behaviors in diabetic adults. METHODS: We conducted a thematic assessment of patient functional and nonfunctional requirements that are missing from current EHRs based on evidence from the literature. We used the results to identify the technologies needed to address those requirements. We describe the technological infrastructures used to construct, manage, and integrate the types of knowledge stored in the PHL. We leverage the Social Linked Data (Solid) platform to design a fully decentralized and privacy-aware platform that supports interoperability and care integration. We provided an initial prototype design of a PHL and drafted a use case scenario that involves four actors to demonstrate how the proposed prototype can be used to address user requirements, including the construction and management of the PHL and its utilization for developing a mobile app that queries the knowledge stored and integrated into the PHL in a private and fully decentralized manner to provide better recommendations. RESULTS: To showcase the main features of the mobile health app and the PHL, we mapped those features onto a framework comprising the user requirements identified in a use case scenario that features a preventive intervention from the diabetes self-management domain. Ongoing development of the app requires a formative evaluation study and a clinical trial to assess the impact of the digital intervention on patient-users. We provide synopses of both study protocols. CONCLUSIONS: The proposed PHL helps patients and their caregivers take a central role in making decisions regarding their health and equips their health care providers with informatics tools that support the collection and interpretation of the collected knowledge. By exposing the PHL functionality as an open service, we foster the development of third-party applications or services and provide motivational technological support in several projects crossing different domains of interest.

Increases in multimorbidity with weight class in the United States.

Little is known regarding how multimorbidity combinations associated with obesity change with increase in body weight. This study employed data from the national Cerner HealthFacts Data Warehouse to identify changes in multimorbidity patterns by weight class using network analysis. Networks were generated for 154 528 middle-aged patients in the following categories: normal weight, overweight, and classes 1, 2, and 3 obesity. The results show significant differences (P-value<0.05) in prevalence by weight class for all but three of 82 diseases considered. The percentage of patients with multimorbidity (excluding obesity) increases from in 55.1% in patients with normal weight, to 57.88% with overweight, 70.39% with Class 1 obesity, 73.99% with Class 2 obesity, and 71.68% in Class 3 obesity, increasing most substantially with the progression from overweight to class 1 obesity. Most prevalent disease clusters expand from only hypertension and dorsalgia in normal weight, to add joint disorders in overweight, lipidemias in class 1 obesity, diabetes in class 2 obesity, and sleep disorders and chronic kidney disease in class 3 obesity. Recognition of multimorbidity patterns associated with weight increase is essential for true precision care of obesity-associated chronic conditions and can help clinicians identify and address preclinical disease before additional complications arise.

Using preliminary data and prospective power analyses for mid-stream revision of projected group and subgroup sizes in pragmatic patient-centered outcomes research.

Pragmatic clinical trials are commonly used in patient-centered outcomes research to assess heterogeneity of treatment effects. Patient-Centered Outcomes Research Institute (PCORI) methodology standards for assessing heterogeneity of treatment effects are extremely rigorous, but their implementation in real-world settings can be difficult. Predicting recruitment effectiveness and subgroup characteristics is often challenging and may require mid-stream revision of projected group and subgroup sizes. Yet, little real-world data are available to demonstrate methodologically valid approaches to address situations where such revisions are necessary. These data were used for mid-stream revision of group and subgroup sizes in the Management of Diabetes in Everyday Life (MODEL) clinical trial. The planned number of randomized participants retained over the one-year study period was reduced from 800 to 581 due to recruitment difficulties among potential participants residing in rural areas. Prospective power analyses are based on the revised target of 581 participants retained and the proportions of 167 participants with various key baseline characteristics, who had been randomized in MODEL by January 2018, as reported to the Patient Center Outcomes Research Institute (PCORI) and the MODEL Data Safety and Monitoring Committee. Power calculations are based on two-sided t-tests with type-I error rates of 0.05 and the assumption that effect sizes will range from small (standardized difference = 0.36) to medium (= 0.50). The primary outcome variables are how many days in the previous week participants 1) ate healthy meals, 2) participated in at least 30 minutes of physical activity, and 3) took medications as prescribed. The POWER procedure of SAS 9.4 was used for all analyses. These data, along with the approach, can assist statisticians as they plan future pragmatic clinical trials evaluating heterogeneity of treatment effects. These data can help inform investigators, conducting patient-centered outcomes research, as they define subgroups for either confirmatory analyses for testing heterogeneity of treatment effects or for exploratory analyses where estimation of confidence bounds may be useful for generating future hypotheses. (This work was supported through a Patient-Centered Outcomes Research Institute (PCORI) Project Program Award (SC15-1503-28336), www.ClinicalTrials.gov and Identifier: NCT02957513 [1].).

Continuity of Care for Patients with Obesity-Associated Chronic Conditions: Protocol for a Multisite Retrospective Cohort Study.

BACKGROUND: Obesity affects nearly half of adults in the United States and is contributing substantially to a pandemic of obesity-associated chronic conditions such as type 2 diabetes, hypertension, and arthritis. The obesity-associated chronic condition pandemic is particularly severe in low-income, medically underserved, predominantly African-American areas in the southern United States. Little is known regarding the impact of geographic, income, and racial disparities in continuity of care on major health outcomes for patients with obesity-associated chronic conditions. OBJECTIVE: The aim of this study is to assess, among patients with obesity-associated chronic conditions, and within this group, patients with type 2 diabetes, (1) whether continuity of care is associated with lower overall and potentially preventable emergency department and hospital utilization, (2) the effect of geographic, income, and racial disparities on continuity of care and on health care utilization, (3) whether continuity of care particularly protects individuals at risk for disparities from adverse health outcomes, and (4) whether characteristics of health systems are associated with higher continuity of care and better outcomes. METHODS: Using 2015-2018 data from 4 practice-based research networks participating in the Southern Obesity and Diabetes Coalition, we will conduct a retrospective cohort analysis and distributed meta-analysis. Patients with obesity-associated chronic conditions and with type 2 diabetes will be assessed within each health system, following a standardized study protocol. The primary study outcomes are overall and preventable emergency department visits and hospitalizations. Continuity of care will be calculated at the facility level using a modified version of the Bice-Boxerman continuity of care index. Race will be assessed using electronic medical record data. Residence in a low-income area or a health professional shortage area respectively will be assessed by linking patient residence ZIP codes to the Centers for Medicare & Medicaid Services database. RESULTS: In 4 regional health systems across Tennessee, Mississippi, Louisiana, and Arkansas, a total of 53 adult hospitals were included in the study. A total of 147,889 patients with obesity-associated chronic conditions who met study criteria were identified in these health systems, of which 45,453 patients met the type 2 diabetes criteria for inclusion. Results are expected by the end of 2020. CONCLUSIONS: This study should reveal whether health system efforts to increase continuity of care for patients with obesity and diabetes have potential to improve outcomes and reduce costs. Analyzing disparities in continuity of care and their effect on major health outcomes can help demonstrate how to improve care and use of health care resources for vulnerable patients with obesity-associated chronic conditions, and within this group, patients with type 2 diabetes. Better understanding of the association between continuity and health care utilization for these vulnerable populations will contribute to the development of higher-value health systems in the southern United States. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/20788.

A mid-South chronic disease registry and practice-based research network to address disparities.

OBJECTIVES: To describe an innovative health information technology (HIT) model for supporting community-wide health improvement through multiprovider collaboration in a regional population health registry and practice-based research network (PBRN). STUDY DESIGN: Case study. METHODS: We describe the HIT data structure and governance of the Diabetes Wellness and Prevention Coalition (DWPC) Registry and PBRN based in Memphis, Tennessee. The population served and their characteristics were assessed for all adult patients with at least 1 encounter in a participating health care delivery system from January 1, 2013, to March 31, 2019. Disparities in access and health care utilization were assessed by residential zip code. RESULTS: The DWPC Registry is a chronic disease and population health data warehouse designed to facilitate chronic disease surveillance and tracking of processes and outcomes of care in medically underserved areas of the mid-South. The Registry primarily focuses on obesity-associated chronic conditions such as diabetes, hypertension, hyperlipidemia, and chronic kidney disease. It combines patient data from 7 regional health systems, which include 6 adult hospitals and more than 50 outpatient practices, covering 462,223 adults with 2,032,425 clinic visits and 602,679 hospitalizations and/or emergency department visits from January 1, 2013, to March 31, 2019. The most prevalent chronic conditions include obesity (37.2%), hypertension (34.4%), overweight (26.4%), hyperlipidemia (18.0%), and type 2 diabetes (14.0%). The Registry provides quarterly practice improvement reports to participating clinics, facilitates surveillance of and outreach to patients with unmet health needs, and supports a pragmatic clinical trial and multiple cohort studies. CONCLUSIONS: Regional registries and PBRNs are powerful tools that can support real-world quality improvement and population health efforts to reduce disparities and improve equity in chronic disease care in medically underserved communities across the United States.

The management of diabetes in everyday life study: Design and methods for a pragmatic randomized controlled trial comparing the effectiveness of text messaging versus health coaching.

Background African American patients with uncontrolled diabetes living in medically underserved areas need effective clinic-based interventions to improve self-care behaviors. Text messaging (TM) and health coaching (HC) are among the most promising low-cost population-based approaches, but little is known about their comparative effectiveness in real-world clinical settings. Objective Use a pragmatic randomized controlled trial design to determine the comparative effectiveness of TM and HC with enhanced usual care (EC) in African American adults with uncontrolled diabetes and multiple chronic health conditions. Methods/design The Management of Diabetes in Everyday Life (MODEL) study is randomizing 646 patients (n = 581with anticipated 90% retention) to 3 intervention arms: TM, HC, and EC. Participants are African American adults living in medically underserved areas of the Mid-South, age ≥ 18, with uncontrolled diabetes (A1c ≥ 8), one or more additional chronic conditions, and who have a phone with texting and voicemail capability. Primary outcome measures: the general diet, exercise, and medication adherence subscales of the revised Summary of Diabetes Self-Care Activities questionnaire assessed at one year. Secondary outcomes: diabetes-specific quality of life, primary care engagement, and average blood sugar (A1c). The study will also assess heterogeneity of treatment effects by six key baseline participant characteristics. Conclusions We describe the design and methods of the MODEL study along with design revisions required during implementation in a pragmatic setting. This trial, upon its conclusion, will allow us to compare the effectiveness of two promising low-cost primary care-based strategies for supporting self-care behaviors among African Americans individuals with uncontrolled diabetes. ClinicalTrials.gov registration number: NCT02957513.

The Personal Health Library: A Single Point of Secure Access to Patient Digital Health Information.

Traditionally, health data management has been EMR-based and mostly handled by health care providers. Mechanisms are needed to give patients more control over their health conditions. Personal Health Libraries (PHLs) provide a single point of secure access to patients' digital health information that can help empower patients to make better-informed decisions about their health care. This paper reports a work-in-progress on leveraging tools and methods from artificial intelligence and knowledge representation to build a private, decentralized PHL that supports interoperability and, ultimately, true care integration. We demonstrate how a social application querying such a decentralized PHL can deliver a tailored push notification intervention focused on improving self-care behaviors in diabetic adults from medically underserved communities.

Medication nonadherence, mental health, opioid use, and inpatient and emergency department use in super-utilizers.

OBJECTIVES: To examine whether mental health conditions, opioid use, and medication nonadherence are associated with inpatient and emergency department (ED) use among Medicare super-utilizers from medically underserved areas. STUDY DESIGN: Retrospective panel study. METHODS: The study included Medicare super-utilizers (≥3 hospitalizations or ≥2 hospitalizations with ≥2 ED visits in 6 months) served by a health system in a medically underserved area in the South from February 2013 to December 2014 with at least 1 filled prescription for hypertension, type 2 diabetes, cardiovascular, and/or chronic obstructive pulmonary disease/asthma medications. We used random effects negative binomial models to assess whether mental health diagnosis, opioid use, and medication nonadherence were associated with preventable and overall hospitalizations and ED visits stratified by age (18-64 vs ≥65 years). RESULTS: Overall chronic disease medication nonadherence was associated with more frequent hospitalizations and ED visits for both younger (hospitalizations: incidence rate ratio [IRR], 1.31; 95% CI, 1.16-1.47; ED visits: IRR, 1.33; 95% CI, 1.14-1.55) and older (hospitalizations: IRR, 1.34; 95% CI, 1.20-1.49; ED visits: IRR, 1.18; 95% CI, 1.02-1.38) beneficiaries. Mental health diagnosis was significantly associated with higher hospitalizations and ED visits among both age groups. Although associations between opioid medication use and inpatient and ED use were inconsistent and not significant in most cases, we found that 7 or more days' supply of opioids was associated with lower preventable hospitalizations in Medicare beneficiaries 65 years or older. CONCLUSIONS: The study findings highlight the importance of improving medication adherence and addressing behavioral health needs in Medicare super-utilizers.