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.

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.

Allele-Specific Knockdown of Mutant Huntingtin Protein via Editing at Coding Region Single Nucleotide Polymorphism Heterozygosities.

Huntington's disease (HD) is a devastating, autosomal dominant neurodegenerative disease caused by a trinucleotide repeat expansion in the huntingtin (HTT) gene. Inactivation of the mutant allele by clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 based gene editing offers a possible therapeutic approach for this disease, but permanent disruption of normal HTT function might compromise adult neuronal function. Here, we use a novel HD mouse model to examine allele-specific editing of mutant HTT (mHTT), with a BAC97 transgene expressing mHTT and a YAC18 transgene expressing normal HTT. We achieve allele-specific inactivation of HTT by targeting a protein coding sequence containing a common, heterozygous single nucleotide polymorphism (SNP). The outcome is a marked and allele-selective reduction of mHTT protein in a mouse model of HD. Expression of a single CRISPR-Cas9 nuclease in neurons generated a high frequency of mutations in the targeted HD allele that included both small insertion/deletion (InDel) mutations and viral vector insertions. Thus, allele-specific targeting of InDel and insertion mutations to heterozygous coding region SNPs provides a feasible approach to inactivate autosomal dominant mutations that cause genetic disease.

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.

Calibrating Medicaid payment to need for long-term services and supports.

OBJECTIVES: The Massachusetts Medicaid and Children's Health Insurance Program, MassHealth, offers comprehensive Senior Care Options (SCO) plans to its Medicare-eligible members 65 years and older. Historically, MassHealth has paid a fixed per-person capitation rate for any "nursing home-certifiable" SCO member despite considerable heterogeneity of need. Our objective was to develop a model to predict long-term services and supports (LTSS) costs for community-dwelling SCO members. STUDY DESIGN: Concurrent predictive modeling. METHODS: We studied nursing home-certifiable SCO members who were enrolled for at least 183 days during 2016-2017 and used linear models to predict annual cost of community-based LTSS from demographic, medical, social determinants of health, and functional characteristics. We evaluated model performance using predictive performance (R2) and predictive ratios (observed costs divided by predicted costs) for various vulnerable subgroups. RESULTS: The modeling population included 35,259 enrollees. Mean (SD) annualized LTSS cost was $14,071 ($13,174). Functional status (ie, activities of daily living [ADLs] and instrumental ADLs) accounted for most of the variability in community LTSS cost (R2 = 18.4%) explainable by available variables. The Massachusetts SCO (MA-SCO) model (R2 = 21.6%) predicts accurately for several high-cost, vulnerable subgroups. Compared with fixed per-member capitation payments for all, the MA-SCO model reduces, for example, the payment to one plan by 28% and increases that to another by 35%. CONCLUSIONS: Predictive models using administrative data and functional status information can appropriately allocate payments for subgroups of members with LTSS needs that differ substantially from average. Calibrating payment to need mitigates incentives for population skimming and promotes the sustainability of mission-oriented organizations.

Emergency Department and Primary Care Use in Massachusetts 5 Years After Health Reform.

OBJECTIVE: Conceptually, access to primary care (through insurance) should reduce emergency department (ED) visits for primary care sensitive (PCS) conditions. We sought to identify characteristics of insured Massachusetts residents associated with PCS ED use, and compare such use for public versus private insurees. POPULATION AND SETTING: People under age 65 in the Massachusetts All-Payer Claims Data, 2011-2012. STUDY DESIGN: Retrospective, observational analysis of PCS ED use with nonurgent, urgent/primary care treatable, and urgent/potentially avoidable visits being considered PCS. We predicted utilization in 2012 using multivariable regression models and data available in 2011 administrative records. PRINCIPAL FINDINGS: Among 2,269,475 nonelderly Massachusetts residents, 40% had public insurance. Among public insurees, PCS ED use was higher than for private (mean, 36.5 vs. 9.0 per 100 persons; adjusted risk ratio, 2.53; 95% confidence limits, 2.49-2.56), while having any primary care visit was less common (70% vs. 83%), as was having any visit to one's own (attributed) primary care provider (38% vs. 44%). CONCLUSIONS: Public insurance was associated with less access to primary care and more PCS ED use; statewide labor shortages and low reimbursement rates from public insurance may have provided inadequate access to care that might otherwise have helped reduce PCS ED use.

Allostatic Load Biomarker Associations with Depressive Symptoms Vary among US Black and White Women and Men.

The prevalence and severity of depression differ in women and men and across racial groups. Psychosocial factors such as chronic stress have been proposed as contributors, but causes of this variation are not fully understood. Allostatic load, a measure of the physiological burden of chronic stress, is known to be associated with depression. Using data from the National Health and Nutrition Examination Survey 2005⁻2010, we examined the associations of nine allostatic load biomarkers with depression among US black and white adults aged 18⁻64 years (n = 6431). Depressive symptoms were assessed using the Patient Health Questionaire-9; logistic models estimated adjusted odds of depression based on allostatic load biomarkers. High-risk levels of c-reactive protein were significantly associated with increased odds of depression among white women (adjusted odds ratio (aOR) = 1.7, 95% CI: 1.1⁻2.5) and men (aOR = 1.8, 95% CI: 1.1⁻2.8) but not black women (aOR = 0.8, 95% CI: 0.6⁻1.1) or men (aOR = 0.9, 95% CI: 0.5⁻1.5). Among black men, hypertension (aOR = 1.7, 95% CI: 1.1⁻2.7) and adverse serum albumin levels (aOR = 1.7, 95% CI: 1.0⁻2.9) predicted depression, while high total cholesterol was associated with depression among black women (aOR = 1.6, 95% CI: 1.0⁻2.7). The associations between allostatic load biomarkers and depression varies with gendered race, suggesting that, despite consistent symptomatology, underlying disease mechanisms may differ between these groups.

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.

Prenatal Triptan Exposure and Internalising and Externalising Behaviour Problems in 3-Year-Old Children: Results from the Norwegian Mother and Child Cohort Study.

BACKGROUND: Triptans are commonly prescribed for migraine, a pain condition that is highly prevalent in women of childbearing age. No prior studies have investigated associations between exposure to triptans during fetal life and risk of externalising and internalising behaviours in children. METHODS: This study was set in the Norwegian Mother and Child Cohort study, a prospective birth cohort. A total of 41,173 live, singleton births without major malformations present at 36-month post-partum follow-up were included in this study; 396 used a triptan during pregnancy, 798 used a triptan prior to pregnancy only, 3291 reported migraine without triptan use, and 36,688 reported no history of migraine or triptan use. Marginal structural models were used to analyse the association between timing of triptan exposure and neurodevelopmental outcome. RESULTS: Children exposed to triptans during pregnancy had a 1.39-fold increased risk of externalising behaviours compared with those whose mothers used triptans prior to pregnancy only (95% CI 0.97, 1.97), a 1.36-fold increased risk compared with the unmedicated migraine group (95% CI 1.02, 1.81), and a 1.41-fold increased risk compared with the population comparison group (95% CI 1.08, 1.85). The greatest risk was associated with first trimester exposure (RR 1.77, 95% CI 0.98, 3.14). Risk differences were small, ranging from 3-6%. CONCLUSIONS: This study found an increased risk of clinically relevant externalising behaviours in children with prenatal exposure to triptans, and this risk was highest for first trimester exposure. Absolute risks were small, and the results may be due to confounding by underlying migraine severity.

Genome-wide copy number variation study associates metabotropic glutamate receptor gene networks with attention deficit hyperactivity disorder.

Attention deficit hyperactivity disorder (ADHD) is a common, heritable neuropsychiatric disorder of unknown etiology. We performed a whole-genome copy number variation (CNV) study on 1,013 cases with ADHD and 4,105 healthy children of European ancestry using 550,000 SNPs. We evaluated statistically significant findings in multiple independent cohorts, with a total of 2,493 cases with ADHD and 9,222 controls of European ancestry, using matched platforms. CNVs affecting metabotropic glutamate receptor genes were enriched across all cohorts (P = 2.1 × 10(-9)). We saw GRM5 (encoding glutamate receptor, metabotropic 5) deletions in ten cases and one control (P = 1.36 × 10(-6)). We saw GRM7 deletions in six cases, and we saw GRM8 deletions in eight cases and no controls. GRM1 was duplicated in eight cases. We experimentally validated the observed variants using quantitative RT-PCR. A gene network analysis showed that genes interacting with the genes in the GRM family are enriched for CNVs in ∼10% of the cases (P = 4.38 × 10(-10)) after correction for occurrence in the controls. We identified rare recurrent CNVs affecting glutamatergic neurotransmission genes that were overrepresented in multiple ADHD cohorts.

Comparative acute efficacy and tolerability of OROS and immediate release formulations of methylphenidate in the treatment of adults with attention-deficit/hyperactivity disorder.

BACKGROUND: The main aim of this study was to compare the safety and efficacy of IR MPH administered three times daily to those of once daily OROS-MPH. METHODS: Subjects were outpatient adults satisfying full diagnostic criteria for DSM-IV ADHD between 19 and 60 years of age. Data from two independently conducted 6-week placebo controlled, randomized clinical trials of IR-MPH (tid) and of OROS-MPH were pooled to create three study groups: Placebo (N = 116), IR-MPH (tid) (N = 102) and OROS-MPH (N = 67). RESULTS: Eight-five percent (N = 99) of placebo treated subjects, 77% (N = 79) of the IR-MPH (tid) treated subjects, and 82% (N = 55) of the OROS-MPH treated subjects completed the 6-week trial. Total daily doses at endpoint were 80.9 +/- 31.9 mg, 74.8 +/- 26.2 mg, and 95.4 +/- 26.3 mg in the OROS-MPH, IR-MPH (tid), and placebo groups, respectively. At endpoint, 66% (N = 44) of subjects receiving OROS-MPH and 70% (N = 71) of subjects receiving IR-MPH (tid) were considered responders compared with 31% (N = 36) on placebo. CONCLUSION: Comparison of data from two similarly designed, large, randomized, placebo-controlled, trials, showed that equipotent daily doses of once daily OROS-MPH had similar efficacy to that of TID administered IR MPH.