Faculty Bibliography

INTRODUCTION/BACKGROUND:High tobacco smoking prevalence in people with low SES or serious psychological distress (SPD) in the U.S. may increase cardiovascular disease (CVD) risk among these marginalized subpopulations. We estimate how smoking disparities contribute to CVD disparities. METHODS:Using the Simulation of Tobacco and Nicotine Outcomes and Policy model, a validated microsimulation model of tobacco use and clinical outcomes, we used 2004-2019 data from the National Health Interview Survey to first compare 20-year cumulative CVD incidence for 40-year-olds by sex, smoking status, and marginalized subpopulation membership. Second, we simulated the marginalized subpopulations with representative age, sex, and smoking status distributions to estimate 20-year cumulative CVD incidence under status quo and counterfactual scenarios. In the counterfactual scenario, smoking prevalence and trends in the low SES and SPD subpopulations match those in the higher SES and non-SPD subpopulations, respectively. RESULTS:The model-projected impact of smoking on 20-year cumulative CVD incidence is considerably larger than the impact of low SES or SPD; for example, among 40-year-old males, cumulative CVD incidence is 28.3% for low SES people who currently smoke, 13.0% for low SES people who never smoke, and 26.2% for higher SES people who currently smoke. In the second analysis, in the status quo scenario, model-projected 20-year cumulative CVD incidence is 19.3% for low SES and 22.1% for SPD; in the counterfactual scenario, it is 18.1% for low SES and 19.6% for SPD. CONCLUSIONS:Interventions focused on reducing smoking disparities could substantially reduce CVD in marginalized subpopulations.

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/BACKGROUND:ClinicalTrials.gov NCT04726371.

BACKGROUND:More than seven million people with intellectual and/or developmental disabilities (ID/DD) live in the US and may face an elevated risk for COVID-19. OBJECTIVE:To identify correlates of COVID-19 and related hospitalizations among people with ID/DD in group homes in Massachusetts. METHODS:We collected data during March 1, 2020-June 30, 2020 (wave 1) and July 1, 2020-March 31, 2021 (wave 2) from the Massachusetts Department of Public Health and six organizations administering 206 group homes for 1035 residents with ID/DD. The main outcomes were COVID-19 infections and related hospitalizations. We fit multilevel Cox proportional hazards models to estimate associations with observed predictors and assess contextual home- and organizational-level effects. RESULTS:Compared with Massachusetts residents, group home residents had a higher age-adjusted rate of COVID-19 in wave 1 (incidence rate ratio [IRR], 12.06; 95 % confidence interval [CI], 10.51-13.84) and wave 2 (IRR, 2.47; 95 % CI, 2.12-2.88) and a higher age-adjusted rate of COVID-19 hospitalizations in wave 1 (IRR, 17.64; 95 % CI, 12.59-24.70) and wave 2 (IRR, 4.95; 95 % CI, 3.23-7.60). COVID-19 infections and hospitalizations were more likely among residents aged 65+ and in group homes with 6+ resident beds and recent infection among staff and residents. CONCLUSIONS:Aggressive efforts to decrease resident density, staff-to-resident ratios, and staff infections through efforts such as vaccination, in addition to ongoing access to personal protective equipment and COVID-19 testing, may reduce COVID-19 and related hospitalizations in people with ID/DD living in group homes.

OBJECTIVE:Autoimmune encephalitis (AE) is a highly treatable neurologic condition that can cause psychosis. Screening for AE is not currently recommended in routine workup for first-episode psychosis (FEP), owing partly to the high cost of testing for AE-associated neuronal autoantibodies. METHODS:This study used a decision-analytic model to estimate the cost-effectiveness of routine serum screening for AE compared with clinically targeted screening in patients with FEP. Model parameters drawn from prior published literature included the prevalence of neuronal autoantibodies in FEP (4.5%), serum autoantibody panel cost (US $291), remission probability with antipsychotics (0.58), and remission probability with immunotherapy for patients diagnosed with AE (0.85). Outcomes included quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs), assessed over a 5-year horizon from the US health care sector and societal perspectives. ICER thresholds of $50,000/QALY to $150,000/QALY were used to define cost-effectiveness. The analysis was conducted between June 2018 and January 2020. RESULTS:Routine screening led to mean QALY gains of 0.008 among all patients and 0.174 among the subgroup of patients with neuronal autoantibodies. Mean costs increased by $780 from a societal perspective and $1,150 from a health care sector perspective, resulting in ICERs of $99,330/QALY and $147,460/QALY, respectively. Incorporating joint input data uncertainty, the likelihood routine screening has an ICER ≤ $150,000/QALY was 55% from a societal perspective and 37% from a health care sector perspective. The model parameter with the greatest contribution to overall uncertainty was the effectiveness of immunotherapy relative to antipsychotics. CONCLUSIONS:Routine screening for AE in patients with FEP may be cost-effective in the United States. As further immunotherapy effectiveness data become available, a more definitive recommendation to perform routine screening could be warranted.

Background:In recent years, there has been an increasing burden of child and adolescent mental illness recognized in the United States, and the need for pediatric mental health care is growing. Pediatric consultation-liaison (C-L) psychiatrists are increasingly playing a role in the management of medical and psychiatric disease for pediatric patients. The field is a fast-moving one, with understanding of new neuropsychiatric disease entities; reformulation of prior disease entities; and new interdisciplinary treatments and models of care. Methods:In this study, we aim to review recent advances in the field of pediatric C-L psychiatry, including new diagnostic entities, updated management of frequently encountered clinical presentations, and developments in systems of care. Conclusion:The advances in pediatric C-L psychiatry are broad and serve to promote more streamlined, evidence-based care for the vulnerable population of psychiatrically ill pediatric medical patients. More work remains to determine the most effective interventions for the wide array of presentations seen by pediatric C-L psychiatrists.

BACKGROUND:Mandatory trial registration, and later results reporting, were proposed to mitigate selective clinical trial publication and outcome reporting. The Food and Drug Administration (FDA) Amendments Act (FDAAA) was enacted by Congress on September 27, 2007, requiring the registration of all non-phase I clinical trials involving FDA-regulated medical interventions and results reporting for approved drugs. The association between FDAAA enactment and the registration, results reporting, and publication bias of neuropsychiatric trials has not been studied. METHODS:We conducted a retrospective cohort study of all efficacy trials supporting FDA new drug approvals between 2005 to 2014 for neuropsychiatric indications. Trials were categorized as pre- or post-FDAAA based on initiation and/or completion dates. The main outcomes were the proportions of trials registered and reporting results in ClinicalTrials.gov, and the degree of publication bias, estimated using the relative risks pre- and post-FDAAA of both the publication of positive vs non-positive trials, as well as of publication of positive vs non-positive trials without misleading interpretations. Registration and results reporting proportions were compared pre- and post-FDAAA using the two-tailed Fisher exact test, and the degrees of publication bias were compared by calculating the ratio of relative risks (RRR) for each period. RESULTS:The FDA approved 37 new drugs for neuropsychiatric indications between 2005 and 2014 on the basis of 142 efficacy trials, of which 101 were pre-FDAAA and 41 post-FDAAA. Post-FDAAA trials were significantly more likely to be registered (100% vs 64%; p < 0.001) and report results (100% vs 10%; p < 0.001) than pre-FDAAA trials. Pre-FDAAA, positive trials were more likely to be published (relative risk [RR] = 1.52; 95% confidence interval [CI] = 1.17-1.99; p = 0.002) and published without misleading interpretations (RR = 2.47; CI = 1.57-3.73; p < 0.001) than those with non-positive results. In contrast, post-FDAAA positive trials were equally likely to have been published (RR = 1; CI = 1-1, p = NA) and published without misleading interpretations (RR = 1.20; CI = 0.84-1.72; p = 0.30). The likelihood of publication bias pre-FDAAA vs post-FDAAA was greater for positive vs non-positive trials (RRR = 1.52; CI = 1.16-1.99; p = 0.002) and for publication without misleading interpretations (RRR = 2.06, CI = 1.17-3.61, p = 0.01). CONCLUSIONS:The enactment of FDAAA was followed by significantly higher proportions of trials that were registered and reporting results on ClinicalTrials.gov and significantly lower degrees of publication bias among trials supporting recent FDA approval of drugs for neuropsychiatric indications.

Off-label prescribing of psychiatric drugs is common, despite lacking strong scientific evidence of efficacy and potentially increasing risk for adverse events. The goal of this study was to characterize prevalence of off-label prescriptions of psychiatric drugs and examine patient and clinician predictors of off-label use. This manuscript presents a retrospective, cross-sectional study using data from the 2012 and 2013 National Ambulatory Medical Care Surveys (NAMCS). The study examined all adult outpatient visits to psychiatric practices for chronic care management with a single listed visit diagnosis in which at least one psychiatric drug was prescribed. The main outcome measure was off-label prescribing of at least one psychiatric drug, defined as prescription for a condition for which it has not been approved for use by the FDA. Among our sample representative of 1.85 billion outpatient visits, 18.5 million (1.3%) visits were to psychiatrists for chronic care management in which at least one psychiatric drug was prescribed. Overall, the rate of off-label use was 12.9% (95% CI: 12.2-15.7). The most common off-label uses were for manic-depressive psychosis treated with citalopram and primary insomnia treated with trazodone. Several patient and clinician characteristics were positively associated with off-label prescribing, including seeing a psychiatrist (OR: 1.06, 95% CI, 1.01-1.12; p = 0.03) instead of another type of clinician, the office visit taking place in the Western region of the country (OR: 1.09, 95% CI, 1.01-1.17; p = 0.02), and the patient having 3 or more chronic conditions (OR: 1.12, 95% CI, 1.02-1.14; p = 0.003). In contrast, having Medicare coverage (OR: 0.93, 95% CI, 0.84-0.97; p = 0.04) and receiving payment assistance from a medical charity (OR: 0.91, 95% CI, 0.88-0.96; p = 0.03) instead of private insurance were negatively associated with off-label prescribing. These results suggest that certain classes of psychiatric medications are being commonly prescribed to treat conditions for which they have not been determined by the FDA to be clinically efficacious and/or safe.

OBJECTIVE:Enhanced HIV prevention interventions, such as preexposure prophylaxis for high-risk individuals, require substantial investments. We sought to estimate the medical cost saved by averting 1 HIV infection in the United States. METHODS:We estimated lifetime medical costs in persons with and without HIV to determine the cost saved by preventing 1 HIV infection. We used a computer simulation model of HIV disease and treatment (CEPAC) to project CD4 cell count, antiretroviral treatment status, and mortality after HIV infection. Annual medical cost estimates for HIV-infected persons, adjusted for age, sex, race/ethnicity, and transmission risk group, were from the HIV Research Network (range, $1854-$4545/mo) and for HIV-uninfected persons were from the Medical Expenditure Panel Survey (range, $73-$628/mo). Results are reported as lifetime medical costs from the US health system perspective discounted at 3% (2012 USD). RESULTS:The estimated discounted lifetime cost for persons who become HIV infected at age 35 is $326,500 (60% for antiretroviral medications, 15% for other medications, 25% nondrug costs). For individuals who remain uninfected but at high risk for infection, the discounted lifetime cost estimate is $96,700. The medical cost saved by avoiding 1 HIV infection is $229,800. The cost saved would reach $338,400 if all HIV-infected individuals presented early and remained in care. Cost savings are higher taking into account secondary infections avoided and lower if HIV infections are temporarily delayed rather than permanently avoided. CONCLUSIONS:The economic value of HIV prevention in the United States is substantial given the high cost of HIV disease treatment.