The role of primary care providers in testing for sexually transmitted infections in the MassHealth Medicaid program.

The objective of this study was to determine the prevalence and predictors of testing for sexually transmitted infections (STIs) under an accountable care model of health care delivery. Data sources were claims and encounter records from the Massachusetts Medicaid and Children's Health Insurance Program (MassHealth) for enrollees aged 13 to 64 years in 2019. This cross-sectional study examines the one-year prevalence of STI testing and evaluates social determinants of health and other patient characteristics as predictors of such testing in both primary care and other settings. We identified visits with STI testing using procedure codes and primary care settings from provider code types. Among 740,417 members, 55% were female, 11% were homeless or unstably housed, and 15% had some level of disability. While the prevalence of testing in any setting was 20% (N = 151,428), only 57,215 members had testing performed in a primary care setting, resulting in an 8% prevalence of testing by primary care clinicians (PCCs). Members enrolled in a managed care organization (MCO) were significantly less likely to be tested by a primary care provider than those enrolled in accountable care organization (ACO) plans that have specific incentives for primary care practices to coordinate care. Enrollees in a Primary Care ACO had the highest rates of STI testing, both overall and by primary care providers. Massachusetts' ACO delivery systems may be able to help practices increase STI screening with explicit incentives for STI testing in primary care settings.

Changes in Health Care Utilization During the First 2 Years of Massachusetts Medicaid Accountable Care Organizations.

On March 1, 2018, the Massachusetts Medicaid and Children's Health Insurance Program (MassHealth) launched an ambitious accountable care organization (ACO) program that sought to integrate care across the physical, behavioral, functional, and social services continuum while holding ACOs accountable for cost and quality. The study objective was to describe changes in health care utilization among MassHealth members during the pre-ACO baseline (2015-2017) and post-implementation periods (2018 and 2019). Using MassHealth administrative data, the authors conducted a repeated cross-sectional study of MassHealth members enrolled in ACOs during 2015-2019. Rates of primary care visits, all-cause and primary-care sensitive emergency department (ED) visits, ED boarding, hospitalizations, acute unplanned admissions, and readmissions were reported during the baseline period (2015-2017) and year 1 (2018) and year 2 (2019). Primary care visit rates increased for adult members throughout the study period from a baseline mean of 7.2-9.2 per member per year (observed-to-expected [O:E]: 1.16) in 2019. Observed all-cause hospitalization rates fell below expected values with O:E ratios of 0.96 among adults and 0.79 among children in 2018, and 0.96 and 0.92 among adults and children, respectively, in 2019. All-cause ED visit rates increased slightly, and rates of pediatric asthma-related admissions, unplanned admissions for adults with ambulatory care sensitive conditions, and unplanned admissions and ED boarding for adults with substance use disorder and serious mental illness all declined for the study period. These findings are suggestive of utilization shifts to higher-value, lower-cost care under Massachusetts's innovative and comprehensive ACO model.

Measuring The Enduring Imprint Of Structural Racism On American Neighborhoods.

A long history of discriminatory policies in the United States has created disparities in neighborhood resources that shape ethnoracial health inequities today. To quantify these differences, we organized publicly available data on forty-two variables at the census tract level within nine domains affected by structural racism: built environment, criminal justice, education, employment, housing, income and poverty, social cohesion, transportation, and wealth. Using data from multiple sources at several levels of geography, we developed scores in each domain, as well as a summary score that we call the Structural Racism Effect Index. We examined correlations with life expectancy and other measures of health for this index and other commonly used area-based indices. The Structural Racism Effect Index was more strongly associated with each health outcome than were the other indices. Its domain and summary scores can be used to describe differences in social risk factors, and they provide powerful new tools to guide policies and investments to advance health equity.

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.

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.

The Prevalence and Factors Associated with Antiepileptic Drug Use in US Nursing Home Residents.

BACKGROUND: Antiepileptic drugs (AEDs) are commonly used by nursing home residents, both on- and off-label. The landscape of AED use has changed over the past two decades; however, despite this, contemporaneous research on AED use in US nursing home residents is scant. OBJECTIVE: The aim of this study was to estimate the prevalence of AED use, describe prescribing patterns, identify factors associated with AED use, and assess whether these factors differ among AEDs with expanded indications in older adults (i.e. gabapentin, pregabalin, topiramate, and lamotrigine). METHODS: We conducted a cross-sectional study among 549,240 long-stay older residents who enrolled in fee-for-service Medicare and lived in 15,111 US nursing homes on 1 September 2016. Demographics and conditions associated with AED indications, epilepsy comorbidities, and safety data came from the Minimum Data Set Version 3.0 (MDS 3.0). Medicare Part D claims were used to identify AED use. Robust Poisson models and multinomial logistic models for clustered data estimated adjusted prevalence ratios (aPR), adjusted odds ratios (aOR), and 95% confidence intervals (CIs). RESULTS: Overall, 24.0% used AEDs (gabapentin [13.3%], levetiracetam [4.7%], phenytoin [1.9%], pregabalin [1.8%], and lamotrigine [1.2%]). AED use was associated with epilepsy (aPR 3.73, 95% CI 3.69-3.77), bipolar disorder (aPR 1.20, 95% CI 1.18-1.22), pain (aPRmoderate/severe vs. no pain 1.42, 95% CI 1.40-1.44), diabetes (aPR 1.27, 95% CI 1.26-1.28), anxiety (aPR 1.12, 95% CI 1.11-1.13), depression (aPR 1.17, 95% CI 1.15-1.18), or stroke (aPR 1.08, 95% CI 1.06-1.09). Residents with advancing age (aPR85+ vs. 65-74 years 0.73, 95% CI 0.73-0.74), Alzheimer's disease/dementia (aPR 0.87, 95% CI 0.86-0.88), or cognitive impairment (aPRsevere vs. no impairment 0.62, 95% CI 0.61-0.63) had decreased AED use. Gabapentinoid use was highly associated with pain (aORmoderate/severe vs. no pain 2.07, 95% CI 2.01-2.12) and diabetes (aOR 1.79, 95% CI 1.76-1.82), but not with an epilepsy indication. CONCLUSIONS: AED use was common in nursing homes, with gabapentin most commonly used (presumably for pain). That multiple comorbidities were associated with AED use underscores the need for future studies to investigate the safety and effectiveness of AED use in nursing home residents.

Adherence to Guidelines for Hepatitis B, Pneumococcal, and Influenza Vaccination in Patients With Diabetes.

IN BRIEF This single-center, cross-sectional study was designed to assess adherence to national guidelines for the immunization of patients with diabetes and to evaluate predictors of vaccination with the hepatitis B, influenza, and 23-valent pneumococcal polysaccharide vaccines. In patients considered to be at increased risk for infection and infectious disease complications because of their history of diabetes, extensive nonadherence to immunization recommendations for all three vaccines was found. Nonadherence to the 2011 Advisory Committee on Immunization Practices' recommendation for hepatitis B vaccination was ubiquitous. Allocation of health care resources to increase vaccine coverage should remain a priority, with a focus on spreading awareness of the hepatitis B vaccine recommendation for people with diabetes.