Cost-utility analysis of community-based interventions for hypertension control in Vietnam.

Between 2010 and 2011, stakeholders implemented a multi-faceted community-based intervention in response to the escalating issue of uncontrolled hypertension in Hung Yen province, Vietnam. This initiative integrated expanded community health worker services, home blood pressure self-monitoring, and a unique "storytelling intervention" into routine clinical care. From the limited societal perspective, our study evaluates the cost-effectiveness of this intervention using a Markov model with a one-year cycle over a lifetime horizon. The analysis, based on a cohort of 671 patients, reveals a lifetime incremental cost of approximately VND 90.37 million (USD 3,930) per quality-adjusted life year (QALY) gained. With a willingness to pay at three times GDP (VND 259.2 million per QALY), the intervention proves cost-effective 80% of the time. This research underscores the potential of the community-based approach to effectively control hypertension, offering valuable insights into its broader implications for public health.

Examining racial/ethnic inequities in treatment participation among perinatal individuals with depression.

OBJECTIVE: A cluster randomized controlled trial (RCT) of two interventions for addressing perinatal depression treatment in obstetric settings was conducted. This secondary analysis compared treatment referral and participation among Minoritized perinatal individuals compared to their non-Hispanic white counterparts. METHODS: Among perinatal individuals with depression symptoms, we examined rates of treatment 1) referral (i.e., offered medications or referred to mental health clinician), 2) initiation (i.e., attended ≥1 mental health visit or reported prescribed antidepressant medication), and 3) sustainment (i.e., attended >1 mental health visit per study month or prescribed antidepressant medication at time of study interviews). We compared non-Hispanic white (NHW) (n = 149) vs. Minoritized perinatal individuals (Black, Asian, Hispanic/Latina, Pacific Islander, Native American, Multiracial, and white Hispanic/Latina n = 157). We calculated adjusted odds ratios (aOR) for each outcome. RESULTS: Minoritized perinatal individuals across both interventions had significantly lower odds of treatment referral (aOR = 0.48;95% CI = 0.27-0.88) than their NHW counterparts. There were no statistically significant differences in the odds of treatment initiation (aOR = 0.64 95% CI:0.36-1.2) or sustainment (aOR = 0.54;95% CI = 0.28-1.1) by race/ethnicity. CONCLUSIONS: Perinatal mental healthcare inequities are associated with disparities in treatment referrals. Interventions focusing on referral disparities across race and ethnicity are needed.

Examining Race-Based and Gender-Based Discrimination, Trust in Providers, and Mental Well-Being Among Black Women.

OBJECTIVES: To examine experiences of discrimination among Black women, and to determine if experiencing race- and gender-based discrimination is associated with mental well-being and trust. METHODS: Data from the TRUST study were used to examine experiences of discrimination among 559 Black women with hypertension receiving healthcare at a safety-net hospital in Birmingham, Alabama. A three-level variable was constructed to combine the race-based and gender-based measures of the Experiences of Discrimination scale. Linear regression was used to examine the association between experiences of discrimination with mental well-being and trust. RESULTS: Women who reported no experiences of race- or gender-based discrimination were older and reported higher mental well-being scores and greater trust. Fifty-three percent of study participants reported experiencing discrimination. Compared to participants who did not experience race- or gender-based discrimination, participants reporting experiences of race- or gender-based discrimination and those reporting experiencing both race- and gender-based discrimination were more likely to report poorer mental health. CONCLUSION: Reported experiences of gender- and/or race-based discrimination in this study were associated with lower mental health scores and less trust in health care providers. Our findings highlight the importance of examining experiences of discrimination among Black women, and the role of discrimination as a stressor and in reducing trust for providers. Incorporating an understanding and acknowledgement of experiences of discrimination into interventions, programs, and during clinical encounters may foster more trusting relationships between providers and patients.

Strengthening Quality Measurement to Predict Success for Total Knee Arthroplasty: Results from a Nationally Representative Total Knee Arthroplasty Cohort.

BACKGROUND: When performed well on appropriate patients, total knee arthroplasty (TKA) can dramatically improve quality of life. Patient-reported outcome measures (PROMs) are increasingly used to measure outcome following TKA. Accurate prediction of improvement in PROMs after TKA potentially plays an important role in judging the surgical quality of the health-care institutions as well as informing preoperative shared decision-making. Starting in 2027, the U.S. Centers for Medicare & Medicaid Services (CMS) will begin mandating PROM reporting to assess the quality of TKAs. METHODS: Using data from a national cohort of patients undergoing primary unilateral TKA, we developed an original model that closely followed a CMS-proposed measure to predict success, defined as achieving substantial clinical benefit, specifically at least a 20-point improvement on the Knee injury and Osteoarthritis Outcome Score, Joint Arthroplasty (KOOS, JR) at 1 year, and an enhanced model with just 1 additional predictor: the baseline KOOS, JR. We evaluated each model's performance using the area under the receiver operator characteristic curve (AUC) and the ratio of observed to expected (model-predicted) outcomes (O:E ratio). RESULTS: We studied 5,958 patients with a mean age of 67 years; 63% were women, 93% were White, and 87% were overweight or obese. Adding the baseline KOOS, JR improved the AUC from 0.58 to 0.73. Ninety-four percent of those in the top decile of predicted probability of success under the enhanced model achieved success, compared with 34% in its bottom decile. Analogous numbers for the original model were less discriminating: 77% compared with 57%. Only the enhanced model predicted success accurately across the spectrum of baseline scores. The findings were virtually identical when we replicated these analyses on only patients ≥65 years of age. CONCLUSIONS: Adding a baseline knee-specific PROM score to a quality measurement model in a nationally representative cohort dramatically improved its predictive power, eliminating ceiling and floor effects and mispredictions for readily identifiable patient subgroups. The enhanced model neither favors nor discourages care for those with greater knee dysfunction and requires no new data collection. LEVEL OF EVIDENCE: Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.

Paying for Medical and Social Complexity in Massachusetts Medicaid.

Importance: The first MassHealth Social Determinants of Health payment model boosted payments for groups with unstable housing and those living in socioeconomically stressed neighborhoods. Improvements were designed to address previously mispriced subgroups and promote equitable payments to MassHealth accountable care organizations (ACOs). Objective: To develop a model that ensures payments largely follow observed costs for members with complex health and/or social risks. Design, Setting, and Participants: This cross sectional study used administrative data for members of the Massachusetts Medicaid program MassHealth in 2016 or 2017. Participants included members who were eligible for MassHealth's managed care, aged 0 to 64 years, and enrolled for at least 183 days in 2017. A new total cost of care model was developed and its performance compared with 2 earlier models. All models were fit to 2017 data (most recent available) and validated on 2016 data. Analyses were begun in February 2019 and completed in January 2023. Exposures: Model 1 used age-sex categories, a diagnosis-based morbidity relative risk score (RRS), disability, serious mental illness, substance use disorder, housing problems, and neighborhood stress. Model 2 added an interaction for unstable housing with RRS. Model 3 added rurality and updated diagnosis-based RRS, medication-based RRS, and interactions between sociodemographic characteristics and morbidity. Main Outcome and Measures: Total 2017 annual cost was modeled and overall model performance (R2) and fair pricing of subgroups evaluated using observed-to-expected (O:E) ratios. Results: Among 1 323 424 members, mean (SD) age was 26.4 (17.9) years, 53.4% were female (46.6% male), and mean (SD) 2017 cost was $5862 ($15 417). The R2 for models 1, 2, and 3 was 52.1%, 51.5%, and 60.3%, respectively. Earlier models overestimated costs for members without behavioral health conditions (O:E ratios 0.94 and 0.93 for models 1 and 2, respectively) and underestimated costs for those with behavioral health conditions (O:E ratio >1.10); model 3 O:E ratios were near 1.00. Model 3 was better calibrated for members with housing problems, those with children, and those with high morbidity scores. It reduced underpayments to ACOs whose members had high medical and social complexity. Absolute and relative model performance were similar in 2016 data. Conclusions and Relevance: In this cross-sectional study of data from Massachusetts Medicaid, careful modeling of social and medical risk improved model performance and mitigated underpayments to safety-net systems.

Development of a multi-component intervention to promote participation of Black and Latinx individuals in biomedical research.

INTRODUCTION: Barriers to research participation by racial and ethnic minority group members are multi-factorial, stem from historical social injustices and occur at participant, research team, and research process levels. The informed consent procedure is a key component of the research process and represents an opportunity to address these barriers. This manuscript describes the development of the Strengthening Translational Research in Diverse Enrollment (STRIDE) intervention, which aims to improve research participation by individuals from underrepresented groups. METHODS: We used a community-engaged approach to develop an integrated, culturally, and literacy-sensitive, multi-component intervention that addresses barriers to research participation during the informed consent process. This approach involved having Community Investigators participate in intervention development activities and using community engagement studios and other methods to get feedback from community members on intervention components. RESULTS: The STRIDE intervention has three components: a simulation-based training program directed toward clinical study research assistants that emphasizes cultural competency and communication skills for assisting in the informed consent process, an electronic consent (eConsent) framework designed to improve health-related research material comprehension and relevance, and a "storytelling" intervention in which prior research participants from diverse backgrounds share their experiences delivered via video vignettes during the consent process. CONCLUSIONS: The community engaged development approach resulted in a multi-component intervention that addresses known barriers to research participation and can be integrated into the consent process of research studies. Results of an ongoing study will determine its effectiveness at increasing diversity among research participants.

Development of the Practice Readiness to Evaluate and address Perinatal Depression (PREPD) assessment.

OBJECTIVE: Perinatal depression is a common pregnancy complication and universal screening is recommended. The Practice Readiness to Evaluate and address Perinatal Depression (PREPD) was developed to measure obstetric practice readiness to integrate depression care into workflows. Objectives were to describe: (1) the PREPD; (2) associated characteristics by readiness level; and (3) use of the assessment to measure change. METHOD: The PREPD has four components, each scored to a 16-point maximum: (1) Environmental Scan (10% of PREPD); (2) Depression Detection, Assessment, and Treatment Questionnaire (30%); (3) Depression-related Policies Questionnaire (10%); and (4) Chart Abstraction (50%). Components were weighted and summed for an overall score. Summary and component scores were calculated by patient, practice, and provider. RESULTS: Average overall PREPD score was 7.3/16 (range: 4.8-9.9); scores varied between practices. The Environmental Scan averaged 2.0/16 (range: 0-5.2); Detection, Assessment, and Treatment averaged 8.3/16 (range: 3.0-11.5); Chart Abstraction averaged 7.2/16 (range: 5.1-9.6); and Depression-related Policies averaged 10.4/16 (range: 7.5-15). CONCLUSION: We found wide variation in obstetric practices' readiness to implement interventions for depression; most were minimally prepared. These data may be used to tailor practice intervention goals and as benchmarks with which to measure changes in integration of depression care over time.

Complex Patients Have More Emergency Visits: Don't Punish the Systems That Serve Them.

IMPORTANCE: Better patient management can reduce emergency department (ED) use. Performance measures should reward plans for reducing utilization by predictably high-use patients, rather than rewarding plans that shun them. OBJECTIVE: The objective of this study was to develop a quality measure for ED use for people diagnosed with serious mental illness or substance use disorder, accounting for both medical and social determinants of health (SDH) risks. DESIGN: Regression modeling to predict ED use rates using diagnosis-based and SDH-augmented models, to compare accuracy overall and for vulnerable populations. SETTING: MassHealth, Massachusetts' Medicaid and Children's Health Insurance Program. PARTICIPANTS: MassHealth members ages 18-64, continuously enrolled for the calendar year 2016, with a diagnosis of serious mental illness or substance use disorder. EXPOSURES: Diagnosis-based model predictors are diagnoses from medical encounters, age, and sex. Additional SDH predictors describe housing problems, behavioral health issues, disability, and neighborhood-level stress. MAIN OUTCOME AND MEASURES: We predicted ED use rates: (1) using age/sex and distinguishing between single or dual diagnoses; (2) adding summarized medical risk (DxCG); and (3) further adding social risk (SDH). RESULTS: Among 144,981 study subjects, 57% were women, 25% dually diagnosed, 67% White/non-Hispanic, 18% unstably housed, and 37% disabled. Utilization was higher by 77% for those dually diagnosed, 50% for members with housing problems, and 18% for members living in the highest-stress neighborhoods. SDH modeling predicted best for these high-use populations and was most accurate for plans with complex patients. CONCLUSION: To set appropriate benchmarks for comparing health plans, quality measures for ED visits should be adjusted for both medical and social risks.

COmmuNity-engaged SimULation Training for Blood Pressure Control (CONSULT-BP): A study protocol.

BACKGROUND: Healthcare professionals have negative implicit biases toward minority and poor patients. Few communication skills interventions target implicit bias as a factor contributing to disparities in health outcomes. We report the protocol from the COmmuNity-engaged SimULation Training for Blood Pressure Control (CONSULT-BP), a trial evaluating a novel educational and training intervention targeting graduate medical and nursing trainees that is designed to mitigate the effects of implicit bias in clinical encounters. The CONSULT-BP intervention combines knowledge acquisition, bias awareness, and practice of bias mitigating skills in simulation-based communication encounters with racially/ethnically diverse standardized patients. The trial evaluates the effect of this 3-part program on patient BP outcomes, self-reported patient medication adherence, patient-reported quality of provider communication, and trainee bias awareness. METHODS: We are conducting a cluster randomized trial of the intervention among cohorts of internal medicine (IM), family medicine (FM), and nurse practitioner (NP) trainees at a single academic medical center. We are enrolling entire specialty cohorts of IM, FM, and NP trainees over a 3-year period, with each academic year constituting an intervention cycle. There are 3 cycles of implementation corresponding to 3 sequential academic years. Within each academic year, we randomize training times to 1 of 5 start dates using a stepped wedge design. The stepped wedge design compares outcomes within training clusters before and after the intervention, as well as across exposed and unexposed clusters. Primary outcome of blood pressure control is measured at the patient-level for patients clustered within trainees. Eligible patients for outcomes analysis are: English-speaking; non-White racial/ethnic minority; Medicaid recipient (regardless of race/ethnicity); hypertension; not have pregnancy, dementia, schizophrenia, bipolar illness, or other serious comorbidities that would interfere with hypertension self-control; not enrolled in hospice. Secondary outcomes include trainee bias awareness. A unique feature of this trial is the engagement of academic and community stakeholders to design, pilot test and implement a training program addressing healthcare. DISCUSSION: Equipping clinicians with skills to mitigate implicit bias in clinical encounters is crucial to addressing persistent disparities in healthcare outcomes. Our novel, integrated approach may improve patient outcomes. TRIAL REGISTRATION: NCT03375918. PROTOCOL VERSION: 1.0 (November 10, 2020).

SUPPORT-AF IV: Supporting use of AC through provider prompting about oral anticoagulation therapy for AF clinical trial study protocol.

Background: Six million Americans suffer from atrial fibrillation (AF), a heart rhythm abnormality that significantly increases the risk of stroke. AF is responsible for 15% of ischemic strokes, which lead to permanent disability in 60% of cases and death in up to 20%. Anticoagulation (AC) is the mainstay for stroke prevention in patients with AF. Despite guidelines recommending AC for patients, up to half of eligible patients are not on AC. Clinical decision support tools in the electronic health record (EHR) can help bridge the disparity in AC prescription for patients with AF. Objective: To enhance and assess the effectiveness of our previous rule-based alert on AC initiation and persistence in a diverse patient population from UMass-Memorial Medical Center and University of Florida at Jacksonville. Methods/Results: Using the EHR, we will track AC initiation and persistence. We will interview both patients and providers to determine a measure of satisfaction with AC management. We will track digital crumbs to better understand the alert's mechanism of effect and further add enhancements. These enhancements will be used to refine the alert and aid in developing an implementation toolkit to facilitate use of the alert at other health systems. Conclusion: If the number of AC starts, the likelihood of persisting on AC, and the frequency alert use are found to be higher among intervention vs control providers, we believe such findings will confirm our hypothesis on the effectiveness of our alert.

Predicting the 10-year risk of death from other causes in men with localized prostate cancer using patient-reported factors: Development of a tool.

OBJECTIVE: To develop a tool for estimating the 10-year risk of death from other causes in men with localized prostate cancer. SUBJECTS AND METHODS: We identified 2,425 patients from the Surveillance Epidemiology and End Results-Medicare Health Outcomes Survey database, age <80, newly diagnosed with clinical stage T1-T3a prostate cancer from 1/1/1998-12/31/2009, with follow-up through 2/28/2013. We developed a Fine and Gray competing-risks model for 10-year other cause mortality considering age, patient-reported comorbid medical conditions, component scores and items of the SF-36 Health Survey, activities of daily living, and sociodemographic characteristics. Model discrimination and calibration were compared to predictions from Social Security life table mortality risk estimates. RESULTS: Over a median follow-up of 7.7 years, 76 men died of prostate-specific causes and 465 died of other causes. The strongest predictors of 10-year other cause mortality risk included increasing age at diagnosis, higher approximated Charlson Comorbidity Index score, worse patient-reported general health (fair or poor vs. excellent-good), smoking at diagnosis, and marital status (all other vs. married) (all p<0.05). Model discrimination improved over Social Security life tables (c-index of 0.70 vs. 0.59, respectively). Predictions were more accurate than predictions from the Social Security life tables, which overestimated risk in our population. CONCLUSIONS: We provide a tool for estimating the 10-year risk of dying from other causes when making decisions about treating prostate cancer using pre-treatment patient-reported characteristics.

Conquering hypertension in Vietnam-solutions at grassroots level: study protocol of a cluster randomized controlled trial.

BACKGROUND: Vietnam has been experiencing an epidemiologic transition to that of a lower-middle income country with an increasing prevalence of non-communicable diseases. The key risk factors for cardiovascular disease (CVD) are either on the rise or at alarming levels in Vietnam, particularly hypertension (HTN). Inasmuch, the burden of CVD will continue to increase in the Vietnamese population unless effective prevention and control measures are put in place. The objectives of the proposed project are to evaluate the implementation and effectiveness of two multi-faceted community and clinic-based strategies on the control of elevated blood pressure (BP) among adults in Vietnam via a cluster randomized trial design. METHODS: Sixteen communities will be randomized to either an intervention (8 communities) or a comparison group (8 communities). Eligible and consenting adult study participants with HTN (n = 680) will be assigned to intervention/comparison status based on the community in which they reside. Both comparison and intervention groups will receive a multi-level intervention modeled after the Vietnam National Hypertension Program including education and practice change modules for health care providers, accessible reading materials for patients, and a multi-media community awareness program. In addition, the intervention group only will receive three carefully selected enhancements integrated into routine clinical care: (1) expanded community health worker services, (2) home BP self-monitoring, and (3) a "storytelling intervention," which consists of interactive, literacy-appropriate, and culturally sensitive multi-media storytelling modules for motivating behavior change through the power of patients speaking in their own voices. The storytelling intervention will be delivered by DVDs with serial installments at baseline and at 3, 6, and 9 months after trial enrollment. Changes in BP will be assessed in both groups at several follow-up time points. Implementation outcomes will be assessed as well. DISCUSSION: Results from this full-scale trial will provide health policymakers with practical evidence on how to combat a key risk factor for CVD using a feasible, sustainable, and cost-effective intervention that could be used as a national program for controlling HTN in Vietnam. TRIAL REGISTRATION: ClinicalTrials.gov NCT03590691 . Registered on July 17, 2018. Protocol version: 6. Date: August 15, 2019.

Comparison of a Collective Intelligence Tailored Messaging System on Smoking Cessation Between African American and White People Who Smoke: Quasi-Experimental Design.

BACKGROUND: The Patient Experience Recommender System for Persuasive Communication Tailoring (PERSPeCT) is a machine learning recommender system with a database of messages to motivate smoking cessation. PERSPeCT uses the collective intelligence of users (ie, preferences and feedback) and demographic and smoking profiles to select motivating messages. PERSPeCT may be more beneficial for tailoring content to minority groups influenced by complex, personally relevant factors. OBJECTIVE: The objective of this study was to describe and evaluate the use of PERSPeCT in African American people who smoke compared with white people who smoke. METHODS: Using a quasi-experimental design, we compared African American people who smoke with a historical cohort of white people who smoke, who both received up to 30 emailed tailored messages over 65 days. People who smoke rated the daily message in terms of perceived influence on quitting smoking for 30 days. Our primary analysis compared daily message ratings between the two groups using a t test. We used a logistic model to compare 30-day cessation between the two groups and adjusted for covariates. RESULTS: The study included 119 people who smoke (African Americans, 55/119; whites, 64/119). At baseline, African American people who smoke were significantly more likely to report allowing smoking in the home (P=.002); all other characteristics were not significantly different between groups. Daily mean ratings were higher for African American than white people who smoke on 26 of the 30 days (P<.001). Odds of quitting as measured by 30-day cessation were significantly higher for African Americans (odds ratio 2.3, 95% CI 1.04-5.53; P=.03) and did not change after adjusting for allowing smoking at home. CONCLUSIONS: Our study highlighted the potential of using a recommender system to personalize for African American people who smoke. TRIAL REGISTRATION: ClinicalTrials.gov NCT02200432; https://clinicaltrials.gov/ct2/show/NCT02200432. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/jmir.6465.

A collection of marginalized two-part random-effects models for analyzing medical expenditure panel data: Impact of the New Cooperative Medical Scheme on healthcare expenditures in China.

Marginalized two-part random-effects generalized Gamma models have been proposed for analyzing medical expenditure panel data with excessive zeros. While these models provide marginal inference on expected healthcare expenditures, the usual unilateral specification of heteroscedastic variance on one of the two shape parameters for the generalized Gamma distribution in these models fails to encompass important special cases within the generalized gamma modeling framework. In this article, we construct marginalized two-part random-effects models that employ the log-normal, log-skew-normal, generalized Gamma, Weibull, Gamma, and inverse Gamma distributions to delineate the spectrum of nonzero healthcare expenditures in the second part of the models. These marginalized models supply additional choices for analyzing healthcare expenditure panel data with excessive zeros. We review the concepts of marginal effect and incremental effect, and summarize how these effects are estimated. For studies whose primary goal is to make inference on marginal effect or incremental effect of an independent variable with respect to healthcare expenditures, we advocate empirical mean square error criterion and information criteria to choose among candidate models. Then, we use the proposed models in an empirical analysis to examine the impact of the New Cooperative Medical Scheme on healthcare expenditures among older adults in rural China.

An Innovative Simulation-based Community-engaged Intervention for Training Research Assistants in Culturally Appropriate Informed Consent.

BACKGROUND: Enrolling under-represented groups in biomedical research remains challenging owing to limited health literacy, historic medical abuses, and mistrust. Addressing such barriers requires scrutiny of informed consent processes and training of research assistants (RAs). Applying simulation methods that are well-established in medical education, Simulation-based Community-engaged Research Intervention for Informed Consent Protocol Testing and Training (SCRIIPTT) engages community members as community advisors (CAs) to train RAs in implementing culturally appropriate approaches, such as addressing difficult issues related to race and power dynamics, into the informed consent training process. OBJECTIVES: To present SCRIIPTT's development, implementation, and preliminary findings. METHODS: Over 12 months, our community-academic partnership 1) introduced SCRIIPTT to the greater community using the Truth & Reconciliation Model, which acknowledges the wrongs of research and offers an apology; 2) deepened understanding of community concerns; 3) developed the intervention; 4) conducted a pilot; and 5) disseminated findings. RESULTS: SCRIIPTT included a comprehensive training manual, scenarios for simulated informed consent encounters, and a 37-item checklist to measure performance. Outcomes include CA and RA satisfaction surveys, and RA performance rating. The checklist adequately measured observable behaviors. RAs reported important gains in knowledge, self-confidence, and cultural competence in conducting informed consent. CAs reported positive experiences, being fully engaged and valued as members of the research team and participants during simulation encounters. CONCLUSIONS: This pilot study demonstrated the feasibility of SCRIIPTT, with preliminary evidence of effectiveness and acceptability. SCRIIPTT offers an innovative approach for community engagement in research training and advancing the skills of RAs in culturally appropriate informed consent.

African American women perceptions of physician trustworthiness: A factorial survey analysis of physician race, gender and age.

BACKGROUND/OBJECTIVE: Physical concordance between physicians and patients is advocated as a solution to improve trust and health outcomes for racial/ethnic minorities, but the empirical evidence is mixed. We assessed women's perceptions of physician trustworthiness based on physician physical characteristics and context of medical visit. METHODS: A factorial survey design was used in which a community-based sample of 313 African American (AA) women aged 45+ years responded to vignettes of contrived medical visits (routine versus serious medical concern visit) where the physician's race/ethnicity, gender, and age were randomly manipulated. Eight physician profiles were generated. General linear mixed modeling was used to assess separately and as an index, trust items of fidelity, honesty, competence, confidentiality, and global trust. Trust scores were based on a scale of 1 to 5, with higher scores indicating higher trust. Mean scores and effect sizes (ES) were used to assess magnitude of trust ratings. RESULTS: No significant differences were observed on the index of trust by physician profile characteristics or by medical visit context. However, the white-older-male was rated higher than the AA-older-female on fidelity (4.23 vs. 4.02; ES = 0.215, 95% CI: 0.001-0.431), competence (4.23 vs. 3.95; ES = 0.278, 95% CI: 0.062-0.494) and honesty (4.39 vs. 4.19, ES = 0.215, 95% CI: 0.001-0.431). The AA-older male was rated higher than the AA-older-female on competence (4.20 vs. 3.95; ES = 0.243, 95% CI: 0.022-0.464) and honesty (4.44 vs. 4.19; ES = 0.243, 95% CI: 0.022-0.464). The AA-young male was rated higher than AA-older-female on competence (4.16 vs. 3.95; ES = 0.205, 95% CI: 0.013-0.423). CONCLUSIONS: Concordance may hold no salience for some groups of older AA women with regards to perceived trustworthiness of a physician. Policies and programs that promote diversity in the healthcare workforce in order to reduce racial/ethnic disparities should emphasize cultural competency training for all physicians, which is important in understanding patients and to improving health outcomes.

Spirituality and Willingness to Participate in Health-Related Research Among African Americans.

African Americans remain underrepresented in health-related research. We examined the association between spirituality using the Self-Rating Spirituality Scale (range 6-24) and self-reported willingness to participate in health-related research studies among African Americans. Covariates included gender, education level, employment status, and previous research experience. Adjusted associations were calculated with logistic regression models, with multiple imputation to account for missing data. Results from the logistic regression model show that each one-point increase in the Self-Rating Spirituality Scale was associated with a 24% increase in the odds of being very likely to participate in research (OR: 1.24, 95% CI: 1.07-1.44). Those with less than a college degree (OR: 3.59, 95% CI: 1.51-8.54), who were unemployed (OR: 2.34, 95% CI: 1.03-5.33), and had previous research experience (OR: 2.92, 95% CI: 1.22-6.99) reported increased willingness to participate. This work offers new insight for developing recruitment initiatives within African American spiritual communities.

Caste matters: perceived discrimination among women in rural India.

The aim of this study is to examine the relationship of caste and class with perceived discrimination among pregnant women from rural western India. A cross-sectional survey was administered to 170 pregnant women in rural Gujarat, India, who were enrolled in a longitudinal cohort study. The Everyday Discrimination Scale and the Experiences of Discrimination questionnaires were used to assess perceived discrimination and response to discrimination. Based on self-report caste, women were classified into three categories with increasing historical disadvantage: General, Other Backward Castes (OBC), and Scheduled Caste or Tribes (SC/ST). Socioeconomic class was determined using the standardized Kuppuswamy scale. Regression models for count and binomial data were used to examine association of caste and class with experience of discrimination and response to discrimination. Sixty-eight percent of women experienced discrimination. After adjusting for confounders, there was a consistent trend and association of discrimination with caste but not class. In comparison to General Caste, lower caste (OBC, SC/ST) women were more likely to (1) experience discrimination (OBC OR: 2.2, SC/ST: 4.1; p trend: 0.01); (2) have a greater perceived discrimination score (OBC IRR: 1.3, SC/ST: 1.5; p trend: 0.07); (3) accept discrimination (OBC OR: 6.4, SC/ST: 7.6; p trend: < 0.01); and (4) keep to herself about discrimination (OBC OR: 2.7, SC/ST: 3.6; p trend: 0.04). The differential experience of discrimination by lower caste pregnant women in comparison to upper caste pregnant women and their response to such experiences highlight the importance of studying discrimination to understand the root causes of existing caste-based disparities.

Social Determinants of Health in Managed Care Payment Formulas.

Importance: Managed care payment formulas commonly allocate more money for medically complex populations, but ignore most social determinants of health (SDH). Objective: To add SDH variables to a diagnosis-based payment formula that allocates funds to managed care plans and accountable care organizations. Design, Setting, and Participants: Using data from MassHealth, the Massachusetts Medicaid and Children's Health Insurance Program, we estimated regression models predicting Medicaid spending using a diagnosis-based and SDH-expanded model, and compared the accuracy of their cost predictions overall and for vulnerable populations. MassHealth members enrolled for at least 6 months in 2013 in fee-for-service (FFS) programs (n = 357 660) or managed care organizations (MCOs) (n = 524 607). Exposures: We built cost prediction models from a fee-for-service program. Predictors in the diagnosis-based model are age, sex, and diagnoses from claims. The SDH model adds predictors describing housing instability, behavioral health issues, disability, and neighborhood-level stressors. Main Outcomes and Measures: Overall model explanatory power and overpayments and underpayments for subgroups of interest for all Medicaid-reimbursable expenditures excepting long-term support services (mean annual cost = $5590 per member). Results: We studied 357 660 people who were FFS participants and 524 607 enrolled in MCOs with a combined 806 889 person-years of experience. The FFS program experience included more men (49.6% vs 43.6%), older patients (mean age of 26.1 years vs 21.6 years), and sicker patients (mean morbidity score of 1.16 vs 0.89) than MCOs. Overall, the SDH model performed well, but only slightly better than the diagnosis-based model, explaining most of the spending variation in the managed care population (validated R2 = 62.4) and reducing underpayments for several vulnerable populations. For example, raw costs for the quintile of people living in the most stressed neighborhoods were 9.6% ($537 per member per year) higher than average. Since greater medical morbidity accounts for much of this difference, the diagnosis-based model underpredicts costs for the most stressed quintile by about 2.1% ($130 per member per year). The expanded model eliminates the neighborhood-based underpayment, as well as underpayments of 72% for clients of the Department of Mental Health (observed costs of about $30 000 per year) and of 7% for those with serious mental illness (observed costs of about $16 000 per year). Conclusions and Relevance: Since October 2016, MassHealth has used an expanded model to allocate payments from a prespecified total budget to managed care organizations according to their enrollees' social and medical risk. Extra payments for socially vulnerable individuals could fund activities, such as housing assistance, that could improve health equity.

RAHI-SATHI Indo-U.S. Collaboration: The Evolution of a Trainee-Led Twinning Model in Global Health Into a Multidisciplinary Collaborative Program.

BACKGROUND: In recent years there has been a surge in the number of global health programs operated by academic institutions. However, most of the existing programs describe partnerships that are primarily faculty-driven and supported by extramural funding. PROGRAM DESCRIPTION: Research and Advocacy for Health in India (RAHI, or "pathfinder" in Hindi) and Support and Action Towards Health-Equity in India (SATHI, or "partnership" in Hindi) are 2 interconnected, collaborative efforts between the University of Massachusetts Medical School (UMMS) and Charutar Arogya Mandal (CAM), a medical college and a tertiary care center in rural western India. The RAHI-SATHI program is the culmination of a series of student/trainee-led research and capacity strengthening initiatives that received institutional support in the form of faculty mentorship and seed funding. RAHI-SATHI's trainee-led twinning approach overcomes traditional barriers faced by global health programs. Trainees help mitigate geographical barriers by acting as a bridge between members from different institutions, garner cultural insight through their ability to immerse themselves in a community, and overcome expertise limitations through pre-planned structured mentorship from faculty of both institutions. Trainees play a central role in cultivating trust among the team members and, in the process, they acquire personal leadership skills that may benefit them in their future careers. CONCLUSION: This paradigm of trainee-led twinning partnership promotes sustainability in an uncertain funding climate and provides a roadmap for conducting foundational work that is essential for the development of a broad, university-wide global health program.