Search

Background: Implementation research generally assumes established evidence-based practices and prior piloting of implementation strategies, which may not be feasible during a public health emergency. We describe the use of a simulation model of the effectiveness of COVID-19 mitigation strategies to inform a stakeholder-engaged process of rapidly designing a tailored intervention and implementation strategy for individuals with serious mental illness (SMI) and intellectual/developmental disabilities (ID/DD) in group homes in a hybrid effectiveness-implementation randomized trial. Methods: We used a validated dynamic microsimulation model of COVID-19 transmission and disease in late 2020/early 2021 to determine the most effective strategies to mitigate infections among Massachusetts group home staff and residents. Model inputs were informed by data from stakeholders, public records, and published literature. We assessed different prevention strategies, iterated over time with input from multidisciplinary stakeholders and pandemic evolution, including varying symptom screening, testing frequency, isolation, contact-time, use of personal protective equipment, and vaccination. Model outcomes included new infections in group home residents, new infections in group home staff, and resident hospital days. Sensitivity analyses were performed to account for parameter uncertainty. Results of the simulations informed a stakeholder-engaged process to select components of a tailored best practice intervention and implementation strategy. Results: The largest projected decrease in infections was with initial vaccination, with minimal benefit for additional routine testing. The initial level of actual vaccination in the group homes was estimated to reduce resident infections by 72.4% and staff infections by 55.9% over the 90-day time horizon. Increasing resident and staff vaccination uptake to a target goal of 90% further decreased resident infections by 45.2% and staff infections by 51.3%. Subsequent simulated removal of masking led to a 6.5% increase in infections among residents and 3.2% among staff. The simulation model results were presented to multidisciplinary stakeholders and policymakers to inform the "Tailored Best Practice" package for the hybrid effectiveness-implementation trial. Conclusions: Vaccination and decreasing vaccine hesitancy among staff were predicted to have the greatest impact in mitigating COVID-19 risk in vulnerable populations of group home residents and staff. Simulation modeling was effective in rapidly informing the selection of the prevention and implementation strategy in a hybrid effectiveness-implementation trial. Future implementation may benefit from this approach when rapid deployment is necessary in the absence of data on tailored interventions. Trial registration: ClinicalTrials.gov NCT04726371 [ABSTRACT FROM AUTHOR]

Background Individuals with psychotic symptoms experience substantial morbidity and have shortened life expectancies; early treatment may mitigate the worst effects. Understanding care preceding a first psychotic disorder diagnosis is critical to inform early detection and intervention. Study Design In this observational cohort study using comprehensive information from the Massachusetts All-Payer Claims Database, we identified the first psychotic disorder diagnosis in 2016, excluding those with historical psychotic disorder diagnoses in the prior 48 months among those continuous enrollment data. We reviewed visits, medications, and hospitalizations 2012–2016. We used logistic regression to examine characteristics associated with pre-diagnosis antipsychotic use. Study Results There were 2505 individuals aged 15–35 years (146 per 100 000 similarly aged individuals in the database) with a new psychotic disorder diagnosis in 2016. Most (97%) had at least one outpatient visit in the preceding 48 months; 89% had a prior mental health diagnosis unrelated to psychosis (eg, anxiety [60%], depression [60%]). Many received psychotropic medications (77%), including antipsychotic medications (46%), and 68% had a visit for injury or trauma during the preceding 48 months. Characteristics associated with filling an antipsychotic medication before the psychotic disorder diagnosis included male sex and Medicaid insurance at psychosis diagnosis. Conclusions In this insured population of Massachusetts residents with a new psychotic disorder diagnosis, nearly all had some healthcare utilization, visits for injury or trauma were common, and nearly half filled an antipsychotic medication in the preceding 48 months. These patterns of care could represent either pre-disease signals, delays, or both in receiving a formal diagnosis. [ABSTRACT FROM AUTHOR]

This study examined COVID-19 infection and hospitalizations among people with serious mental illness who resided in residential care group homes in Massachusetts during the first year of the COVID-19 pandemic. The authors analyzed data on 2261 group home residents and COVID-19 data from the Massachusetts Department of Public Health. Outcomes included positive COVID-19 tests and COVID-19 hospitalizations March 1, 2020–June 30, 2020 (wave 1) and July 1, 2020–March 31, 2021 (wave 2). Associations between hazard of outcomes and resident and group home characteristics were estimated using multi-level Cox frailty models including home- and city-level frailties. Between March 2020 and March 2021, 182 (8%) residents tested positive for COVID-19, and 51 (2%) had a COVID-19 hospitalization. Compared with the Massachusetts population, group home residents had age-adjusted rate ratios of 3.0 (4.86 vs. 1.60 per 100) for COVID infection and 13.5 (1.99 vs. 0.15 per 100) for COVID hospitalizations during wave 1; during wave 2, the rate ratios were 0.5 (4.55 vs. 8.48 per 100) and 1.7 (0.69 vs. 0.40 per 100). In Cox models, residents in homes with more beds, higher staff-to-resident ratios, recent infections among staff and other residents, and in cities with high community transmission risk had greater hazard of COVID-19 infection. Policies and interventions that target group home-specific risks are needed to mitigate adverse communicable disease outcomes in this population. Clinical Trial Registration Number This study provides baseline (i.e., pre-randomization) data from a clinical trial study NCT04726371. [ABSTRACT FROM AUTHOR]

Smoke-free policies (SFP) in multi-unit housing are a promising tool for reducing exposure to tobacco smoke among residents. Concerns about increased housing instability due to voluntary or involuntary transitions induced by SFPs have been a primary barrier to greater widespread adoption. The impact of SFP implementation on transitions out of public housing in federally funded public housing authorities in Massachusetts was evaluated. Tenancy data from the Department of Housing and Urban Development were used to determine the time from admission to transitioning out of public housing based on a cohort study design. Periods of exposure to SFPs were defined based on dates of SFP implementation at each PHA. Multi-level Cox regression models were fit to estimate the effects of SFPs on the hazard of transitioning, adjusting for household- and PHA-level characteristics. Analyses were conducted in 2021‒2022. There were 44,705 households with a record of residence in Massachusetts PHAs over 2009‒2018. Over this period, despite increasing adoption of SFPs among the PHAs, rates of transition remained steady at around 5‒8 transitions per 1,000 household-months. There was no overall association between exposure to SFPs and transitions among the full sample (adjusted HR=0.99, 95% CI=0.95, 1.04, p =0.794). However, the association varied significantly by age group, race/ethnicity, timing of SFP adoption, and era of admission. Adoption of SFPs in public housing had a minimal overall impact on turnover for households in Massachusetts, though disparities in the impact were observed between different demographic and PHA-level subgroups. [ABSTRACT FROM AUTHOR]

Importance: Federally qualified health centers (FQHCs) receive federal funding to serve medically underserved areas and provide a range of services including comprehensive primary care, enabling services, and behavioral health care. Greater funding for FQHCs could increase the local availability of clinic-based care and help reduce more costly resource use, such as emergency department visits (ED). Objective: To examine the impact of funding increases for FQHCs after the ACA on the use of FQHCs and EDs. Methods: Retrospective study using the Massachusetts All Payer Claims Database (APCD) 2010–2013 that included APCD enrollees in 559 Massachusetts ZIP codes (N = 6,173,563 in 2010). We calculated shift-share predictions of changes in FQHC funding at the ZIP code-level for FQHCs that received Community Health Center funds in any year, 2010–13 (N = 31). Outcomes were the number of ZIP code enrollees with visits to FQHCs and EDs, overall and for emergent and non-emergent diagnoses. Results: In 2010, 4% of study subjects visited a FQHC, and they were more likely to be younger, have Medicaid, and live in low-income areas. We found that a standard deviation increase in prior year FQHC funding (+31 percentage point (pp)) at the ZIP code level was associated with a 2.3pp (95% CI 0.7pp to 3.8pp) increase in enrollees with FQHC visits and a 1.3pp (95% CI -2.3pp to -0.3pp) decrease in enrollees with non-emergent ED visits, but no significant change in emergent ED visits (0.3pp, 95% CI -0.8pp to 1.4pp). Conclusions: We found that areas exposed to greater FQHC funding increases had more growth in the number of enrollees seen by FQHCs and greater reductions in ED visits for non-emergent conditions. Investment in FQHCs could be a promising approach to increase access to care for underserved populations and reduce costly ED visits, especially for primary care treatable or non-emergent conditions. [ABSTRACT FROM AUTHOR]

Objective: Access to specialty mental health care may be poor because many psychiatrists do not accept health insurance reimbursement, whereas many patients rely on insurance to help pay for care. The objective of this study was to examine the extent of participation in private insurance by licensed psychiatrists.Methods: Using 2013 Massachusetts licensing data and the All-Payer Claims Database (APCD), the authors performed a cross-sectional analysis of licensed psychiatrists in Massachusetts. The fraction of psychiatrists who filed insurance claims, number of unique patients with insurance claims per psychiatrist, and physician characteristics associated with insurance participation were evaluated.Results: In 2013, Massachusetts had 2,348 licensed psychiatrists. Overall, 79% (N=1,843) had at least one paid claim for an outpatient visit in the APCD, but only 6% (N=151) had claims for at least 300 patients per year (a full caseload). Psychiatrists had a median of 18 patients with claims (mean=73). Compared with psychiatrists 30-39 years since medical school graduation, those within 19 years since graduation were less likely to bill for an outpatient (7-19 years, odds ratio [OR]=0.67, 95% confidence interval [CI]=0.47-0.94) and less likely to have claims for ≥300 patients per year (7-19 years, OR=0.49, 95% CI=0.29-0.83). Participation varied across insurance types (93% for group commercial plans versus 33% for Medicaid managed care plans).Conclusions: Among Massachusetts psychiatrists, participation in the private insurance market appears to be limited. Older psychiatrists are more likely to participate, and patients' access to psychiatrists who accept insurance could worsen as these psychiatrists retire. [ABSTRACT FROM AUTHOR]

Research Objective: The Affordable Care Act (ACA) expanded coverage for young adults by allowing them to remain dependents on their parents' plans until age 26 (in 2010) and expanding Medicaid to childless adults with incomes <138% of the federal poverty level (FPL) (in 2014). However, even post‐ACA, uninsured rates by age group were highest among young adults. In 2014, Massachusetts also expanded Medicaid eligibility for children to 19‐20‐year‐olds with incomes up to 150% FPL, which could reduce potential gaps in coverage for those who would otherwise age out of eligibility for Medicaid as children after age 18. We used the Massachusetts All Payer Claims Database to examine changes in coverage for Medicaid enrollees who turned 19 years old before and after the policy change. Study Design: We used data from the Massachusetts All Payer Claims Database (MA‐APCD) from 2012–2016 to examine two cohorts: Medicaid enrollees age 18 as of January 2012 and as of January 2014, who turned 19 years old prior to vs. after Medicaid expansion (pre‐ and post‐expansion cohorts, respectively). Monthly coverage changes for each cohort were examined for 2 years until they turned 21 years old (2012–2014 or 2014–2016). We classified months without insurance enrollment records as uninsured. We used logistic regression models to compare the likelihood of being uninsured for 3 or more months at age 19–20 and 20–21 for the pre‐ vs. post‐expansion cohorts, adjusting for gender, diagnoses of asthma, autism, obesity, mental illness, and intellectual and development disabilities, and ZIP code socioeconomic status (SES). Population Studied: Medicaid enrollees age 18 in January 2012 (N = 32,832) and January 2014 (N = 31,894) in the MA‐APCD. Principal Findings: In both cohorts, 49% were female and 29% lived in low SES ZIP codes; those who turned 19 prior to vs. after Medicaid expansion were less likely to have a baseline diagnosis of asthma (12.1% vs. 12.9%, p < 0.05), obesity (7.6% vs. 8.7%, p < 0.05), and mental illness (17.4% vs. 18.8%, p < 0.05). Enrollees who turned 19 prior to vs. after Medicaid expansion were more likely to have ≥3 months of commercial insurance at age 19–20 (8.5% vs. 3.6%; OR = 1.85, 95% CI 1.7, 2.0) and ≥ 3 months without insurance (17.0% vs. 1.2%; OR = 20.3, 95% CI 17.4, 23.6). Differences persisted at age 20–21, although both cohorts had access to Medicaid expansion for low‐income adults in these years (7.6% vs. 4.9%, OR = 1.4, 95% CI 1.3,1.6 for ≥3 months of commercial insurance; 11.5% vs. 0.9%, OR = 16.4, 95% CI 13.7, 19.5 for ≥3 months without insurance). Conclusions: Disruptions in insurance coverage for young adults aging out of Medicaid were substantially reduced in Massachusetts after the state expanded Medicaid for children to cover 19–20‐year‐olds and expanded coverage for low‐income adults. Commercial insurance coverage was also less likely for young adults after Medicaid expansion. Medicaid enrollees that entered adulthood prior to vs. after Medicaid expansion were more likely to be uninsured in years after Medicaid expansion. Implications for Policy or Practice: Expanding Medicaid eligibility for children to those ages 19–20 could substantially reduce the risk of becoming uninsured for low‐income children entering young adulthood. Primary Funding Source: Agency for Healthcare Research and Quality. [ABSTRACT FROM AUTHOR]