Primary Care Physician Network Overlap Between Medicaid and the Patient Protection and Affordable Care Act Marketplace.

This cross-sectional study quantifies Medicaid and the Patient Protection and Affordable Care Act (ACA) Marketplace overlap among primary care physicians.

Equity Implications of the Affordable Care Act Among People With Past-Year Criminal Legal Interactions.

OBJECTIVE: This study examined whether expansions of Affordable Care Act (ACA) coverage led to changes in insurance coverage and behavioral health treatment use among adults with past-year criminal legal interactions. METHODS: National Survey on Drug Use and Health data and a difference-in-differences design were used to compare changes in insurance coverage and behavioral health treatment use among respondents with a mental or substance use disorder, by past-year criminal legal involvement (N=103,818). RESULTS: Prior to ACA expansions, respondents with past-year criminal legal involvement (vs. without) were less likely to have insurance (61.5% vs. 79.3%) or to receive mental health treatment (34.7% vs. 36.3%). The ACA coverage expansions reduced insurance disparities for people with criminal legal involvement by almost 5 percentage points. No changes in behavioral health treatment use were found. CONCLUSIONS: Future policies that help people with criminal legal involvement get connected to coverage and treatment are warranted to address persistent disparities in coverage and treatment receipt.

Use of residential opioid use disorder treatment among Medicaid enrollees in nine states.

INTRODUCTION: Residential treatment is a key component of the opioid use disorder care continuum, but research has not measured well the differences in its use across states at the enrollee level. METHODS: This cross-sectional observational study used Medicaid claims data from nine states to document the prevalence of residential treatment for opioid use disorder and to describe the characteristics of patients receiving care. For each patient characteristic, chi-square and t-tests tested for differences in the distribution between individuals who did and did not receive residential care. RESULTS: Among 491,071 Medicaid enrollees with opioid use disorder, 7.5 % were treated in residential facilities in 2019, though this number ranged widely (0.3-14.6 %) across states. Residential patients were more likely to be younger, non-Hispanic White, male, and living in an urban area. Although residential patients were less likely than those without residential care to be eligible for Medicaid through disability, diagnoses for comorbid conditions were more frequently observed among residential patients. CONCLUSIONS: Results from this large, multi-state study add context to the ongoing national conversation around opioid use disorder treatment and policy, providing a baseline for future work.

Outpatient follow-up and use of medications for opioid use disorder after residential treatment among Medicaid enrollees in 10 states.

BACKGROUND: Follow-up after residential treatment is considered best practice in supporting patients with opioid use disorder (OUD) in their recovery. Yet, little is known about rates of follow-up after discharge. The objective of this analysis was to measure rates of follow-up and use of medications for OUD (MOUD) after residential treatment among Medicaid enrollees in 10 states, and to understand the enrollee and episode characteristics that are associated with both outcomes. METHODS: Using a distributed research network to analyze Medicaid claims data, we estimated the likelihood of 4 outcomes occurring within 7 and 30 days post-discharge from residential treatment for OUD using multinomial logit regression: no follow-up or MOUD, follow-up visit only, MOUD only, or both follow-up and MOUD. We used meta-analysis techniques to pool state-specific estimates into global estimates. RESULTS: We identified 90,639 episodes of residential treatment for OUD for 69,017 enrollees from 2018 to 2019. We found that 62.5% and 46.9% of episodes did not receive any follow-up or MOUD at 7 days and 30 days, respectively. In adjusted analyses, co-occurring mental health conditions, longer lengths of stay, prior receipt of MOUD or behavioral health counseling, and a recent ED visit for OUD were associated with a greater likelihood of receiving follow-up treatment including MOUD after discharge. CONCLUSIONS: Forty-seven percent of residential treatment episodes for Medicaid enrollees are not followed by an outpatient visit or MOUD, and thus are not following best practices.

Difference-in-differences for categorical outcomes.

OBJECTIVE: To discuss and develop difference-in-difference estimators for categorical outcomes and apply them to estimate the effect of the Affordable Care Act's Medicaid expansion on insurance coverage. DATA SOURCES: Secondary analysis of Survey on Income and Program Participation (SIPP) data on health insurance coverage types before (January 2013) and after (December 2015) Medicaid expansion in 39 US states (19 expansion and 20 non-expansion). STUDY DESIGN: We develop difference-in-difference methods for repeated measures (panel data) of categorical outcomes. We discuss scale-dependence of DID assumptions for marginal and transition effect estimates and specify a new target estimand: the difference between outcome category transitions under treatment versus no treatment. We establish causal assumptions about transitions that are sufficient to identify this and a marginal target estimand. We contrast the marginal estimands identified by the transition approach versus an additive assumption only about marginal evolution. We apply both the marginal and transition approaches to estimate the effects of Medicaid expansion on health insurance coverage types (employer-sponsored; other private, non-group; public; and uninsured). DATA EXTRACTION: We analyzed 16,027 individual survey responses from people aged 18-62 years in the 2014 SIPP panel. PRINCIPAL FINDINGS: We show that the two identifying assumptions are equivalent (on the scale of the marginals) if either the baseline marginal distributions are identical or the marginals are constant in both groups. Applying our transitions approach to the SIPP data, we estimate a differential increase in transitions from uninsured to public coverage and differential decreases in transitions from uninsured to private, non-group coverage and in remaining uninsured. CONCLUSIONS: By comparing the assumption that marginals are evolving in parallel to an assumption about transitions across outcome values, we illustrate the scale-dependence of difference-in-differences. Our application shows that studying transitions can illuminate nuances obscured by changes in the marginals.

Problems with evidence assessment in COVID-19 health policy impact evaluation: a systematic review of study design and evidence strength.

INTRODUCTION: Assessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. METHODS: We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on 26 November 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation. RESULTS: After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-sectional), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes. DISCUSSION: The reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigour to be actionable by policy-makers. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.

Ensemble learning to predict opioid-related overdose using statewide prescription drug monitoring program and hospital discharge data in the state of Tennessee.

OBJECTIVE: To develop and validate algorithms for predicting 30-day fatal and nonfatal opioid-related overdose using statewide data sources including prescription drug monitoring program data, Hospital Discharge Data System data, and Tennessee (TN) vital records. Current overdose prevention efforts in TN rely on descriptive and retrospective analyses without prognostication. MATERIALS AND METHODS: Study data included 3 041 668 TN patients with 71 479 191 controlled substance prescriptions from 2012 to 2017. Statewide data and socioeconomic indicators were used to train, ensemble, and calibrate 10 nonparametric "weak learner" models. Validation was performed using area under the receiver operating curve (AUROC), area under the precision recall curve, risk concentration, and Spiegelhalter z-test statistic. RESULTS: Within 30 days, 2574 fatal overdoses occurred after 4912 prescriptions (0.0069%) and 8455 nonfatal overdoses occurred after 19 460 prescriptions (0.027%). Discrimination and calibration improved after ensembling (AUROC: 0.79-0.83; Spiegelhalter P value: 0-.12). Risk concentration captured 47-52% of cases in the top quantiles of predicted probabilities. DISCUSSION: Partitioning and ensembling enabled all study data to be used given computational limits and helped mediate case imbalance. Predicting risk at the prescription level can aggregate risk to the patient, provider, pharmacy, county, and regional levels. Implementing these models into Tennessee Department of Health systems might enable more granular risk quantification. Prospective validation with more recent data is needed. CONCLUSION: Predicting opioid-related overdose risk at statewide scales remains difficult and models like these, which required a partnership between an academic institution and state health agency to develop, may complement traditional epidemiological methods of risk identification and inform public health decisions.

Trends in suicidal ideation in an emergency department during COVID-19.

OBJECTIVE: This study aims to detail changes in presentations at a United States Emergency Department for suicidality before and after the outbreak of COVID-19. METHODS: A retrospective chart review was conducted of all adult patients who presented to an ED with suicidality and underwent psychiatric consultation during the study period. The cohorts consisted of patients who presented between December 2018 - May 2019 and December 2019 - May 2020. Information was collected on demographics, characteristics of suicidality, reasons for suicidality and disposition. The first wave from March - May 2020 was examined, using a difference-in-differences design to control for factors other than COVID-19 that may have influenced the outcomes' trend. RESULTS: Immediately following the pandemic outbreak there was a statistically significant increase in the proportion of undomiciled patients represented in visits for suicidality (40.7% vs. 57.4%; p-value <0.001). In addition, the proportion of patient visits attributed to social (18.0% vs. 29.2%; p-value 0.003) and structural (14.2% vs. 26.4%; p value <0.001) reasons for suicidality increased. Conversely, the proportion of visits due to psychiatric symptoms (70.5% vs 50.0%; p-value <0.001) decreased. Furthermore, patient visits were more likely to result in a medical admission (2.1% vs. 8.3%; p-value 0.002) and less likely to result in a psychiatric admission (68.4% vs 48.6%; p-value <0.001) during the initial phase of the pandemic. CONCLUSIONS: COVID-19 was associated with increased ED presentations for suicidality among undomiciled patients, as well as greater likelihood of social and structural reasons driving suicidality among all visits.

Urine Lipoarabinomannan Testing in Adults With Advanced Human Immunodeficiency Virus in a Trial of Empiric Tuberculosis Therapy.

BACKGROUND: The urine lipoarabinomannan (LAM) antigen test is a tuberculosis (TB) diagnostic test with highest sensitivity in individuals with advanced human immunodeficiency virus (HIV). Its role in TB diagnostic algorithms for HIV-positive outpatients remains unclear. METHODS: The AIDS Clinical Trials Group (ACTG) A5274 trial demonstrated that empiric TB therapy did not improve 24-week survival compared to isoniazid preventive therapy (IPT) in TB screen-negative HIV-positive adults initiating antiretroviral therapy with CD4 counts <50 cells/µL. Retrospective LAM testing was performed on stored urine obtained at baseline. We determined the proportion of LAM-positive participants and conducted modified intent-to-treat analysis excluding LAM-positive participants to determine the effect on 24-week survival, TB incidence, and time to TB using Kaplan-Meier method. RESULTS: A5274 enrolled 850 participants; 53% were male and the median CD4 count was 18 (interquartile range, 9-32) cells/µL. Of the 850, 566 (67%) had LAM testing (283 per arm); 28 (5%) were positive (21 [7%] and 7 [2%] in the empiric and IPT arms, respectively). Of those LAM-positive, 1 participant in each arm died and 5 of 21 and 0 of 7 in empiric and IPT arms, respectively, developed TB. After excluding these 28 cases, there were 19 and 21 deaths in the empiric and IPT arms, respectively (P = .88). TB incidence remained higher (4.6% vs 2%, P = .04) and time to TB remained faster in the empiric arm (P = .04). CONCLUSIONS: Among outpatients with advanced HIV who screened negative for TB by clinical symptoms, microscopy, and Xpert testing, LAM testing identified an additional 5% of individuals with TB. Positive LAM results did not change mortality or TB incidence.

Birds of a feather flock together: Comparing controlled pre-post designs.

OBJECTIVE: To formalize comparative interrupted time series (CITS) using the potential outcomes framework; compare two version of CITS-a standard linear version and one that adds postperiod group-by-time parameters-to two versions of difference-in-differences (DID)-a standard version with time fixed effects and one that adds group-specific pretrends; and reanalyze three previously published papers using these models. DATA SOURCES: Outcome data for reanalyses come from two counties' jail booking and release data, Medicaid prescription drug rebate data from the Centers for Medicare and Medicaid Services (CMS), and acute hepatitis C incidence from the Centers for Disease Control and Prevention. STUDY DESIGN: DID and CITS were compared using potential outcomes, and reanalyses were conducted using the four described pre-post study designs. DATA COLLECTION/EXTRACTION METHODS: Data from county jails were provided by sheriffs. Data from CMS are publicly available. Data for the third reanalysis were provided by the authors of the original study. PRINCIPAL FINDINGS: Though written differently and preferred by different research communities, the general version of CITS and DID with group-specific pretrends are the same: they yield the same counterfactuals and identify the same treatment effects. In a reanalysis with evidence of divergent preperiod trends, failing to account for this in standard DID led to an 84% smaller effect estimate than the more flexible models. In a second reanalysis with evidence of nonlinear outcome trends, failing to account for this in linear CITS led to a 28% smaller effect estimate than the more flexible models. CONCLUSION: We recommend detailing a causal model for treatment selection and outcome generation and the required counterfactuals before choosing an analytical approach. The more flexible versions of DID and CITS can accommodate features often found in real data, namely, nonlinearities and divergent preperiod outcome trends.

Medicaid Waivers and Access to Behavioral Health Services: What Is Known and What Can Be Expected.

In the past 5 years, Medicaid programs have implemented administrative barriers to enrollment. The impact of these provisions on access to mental health and substance use disorder treatment has been largely unstudied. This column reviews the literature on the previous changes to Medicaid enrollment and treatment use, current policy landscape, and steps that states or localities may take to offset these administrative burdens. Redirecting savings to other safety-net programs may increase access to care, but these programs lack the comprehensive benefits provided by Medicaid. Without another backstop, the implementation of these barriers will likely exacerbate the United States' behavioral health crises.

Evaluating the association between COVID-19 and psychiatric presentations, suicidal ideation in an emergency department.

OBJECTIVE: To estimate the association between COVID-19 and Emergency Department (ED) psychiatric presentations, including suicidal ideation. METHODS: Using an interrupted time series design, we analyzed psychiatric presentations using electronic health record data in an academic medical center ED between 2018 and 2020. We used regression models to assess the association between the onset of the COVID-19 outbreak and certain psychiatric presentations. The period February 26-March 6, 2020 was used to define patterns in psychiatric presentations before and after the coronavirus outbreak. RESULTS: We found a 36.2% decrease (unadjusted) in ED psychiatric consults following the coronavirus outbreak, as compared to the previous year. After accounting for underlying trends, our results estimate significant differential change associated with suicidal ideation and substance use disorder (SUD) presentations following the outbreak. Specifically, we noted a significant differential increase in presentations with suicidal ideation six weeks after the outbreak (36.4 percentage points change; 95% CI: 5.3, 67.6). For presentations with SUD, we found a differential increase in the COVID-19 time series relative to the comparison time series at all post-outbreak time points and this differential increase was significant three weeks (32.8 percentage points; 95% CI: 4.0, 61.6) following the outbreak. Our results estimate no differential changes significant at the P value < 0.05 level associated with affective disorder or psychotic disorder presentations in the COVID-19 time series relative to the comparator time series. CONCLUSIONS: The COVID-19 outbreak in Boston was associated with significant differential increases in ED presentations with suicidal ideation and SUD.

Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation: A systematic review of study design and evidence strength.

INTRODUCTION: Assessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature. METHODS: We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating. RESULTS: After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes. DISCUSSION: The reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policymakers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.

Medicaid Expansion's Spillover to the Criminal Justice System: Evidence from Six Urban Counties.

Spillovers from the Affordable Care Act Medicaid expansion to other social-sector outcomes have received little attention. One that may be especially salient for public policy is the impact of expanded eligibility on jail-related outcomes. This study compares recidivism outcomes in three non-expansion counties to nearby expansion counties before and after Medicaid expansion. Using forty-eight months of arrest data from six urban county jails, we conduct comparative interrupted time series analyses to describe changes in the probability of rearrest and the number of arrests before and after Medicaid expansion. Consistent with previous literature, we find mixed results. In two case studies, Medicaid expansion is associated with decreased rates of recidivism. In the other, we find differential increases in jail-based recidivism after Medicaid expansion. We use contextual information from site visits and stakeholder interviews to understand the factors that may mediate and moderate the relationship between Medicaid expansion and return to jail.

Development of a Tobacco Control Prescription in a Southern US City.

THE PROBLEM: Nationwide efforts to reduce smoking in the United States have been successful. Yet, there is unequal geographic progress in reducing rates of smoking and smoking-related illnesses. Located in a tobacco-producing state with weak tobacco laws, Nashville, Tennessee, has an adult smoking rate of 22.0%, requiring 45,000 smokers to quit to meet the Healthy People 2020 goal of 12%. PURPOSE: The purpose of this article was to detail the development a community-academic partnership (CAP) and its process for devising a local implementation strategy for tobacco control. KEY POINTS: Nashville's CAP developed with a community-based organization (CBOs) seeking out an academic partner. This unique approach addressed many of the challenges CAPs face, helped identify priorities and potential barriers to success and led to early wins. CONCLUSION: The success of Nashville's efforts suggests that CAPs should clearly delineate roles for members of the CAP, engage diverse stakeholders, be responsive to the community, and allow adequate time for planning and prioritizing.

The impact of expanded Medicaid eligibility on access to naloxone.

BACKGROUND AND AIMS: Federal, state and local US governments have sought interventions to reduce deaths due to opioid overdoses by increasing the availability of naloxone. The Affordable Care Act (ACA) expanded Medicaid coverage to low-income, childless adults, potentially giving this group financial access to naloxone. The aims of this paper are: (1) to describe the changes in the amount of Medicaid-covered naloxone used between 2009 and 2016 and (2) to quantify the differential change in the amount of dispensed naloxone between states that expanded their Medicaid programs and states that did not. DESIGN: A quasi-experimental approach based on states' ongoing choice to expand their Medicaid program to all adults with incomes between 100 and 138% of the federal poverty line (FPL), starting in 2014. As of 2018, 37 states had expanded and 14 states had not. Estimation of the policy impact relies on a difference-in-difference method. SETTING: US state Medicaid programs. PARTICIPANTS AND MEASUREMENTS: Data are from the Medicaid Drug Rebate Program and include all dispensed prescriptions of naloxone through the Medicaid program. State/quarters with fewer than 10 prescriptions are suppressed; n = 1632. FINDINGS: Prior to Medicaid expansion, the number of Medicaid-covered naloxone prescriptions was very similar in expansion and non-expansion states. On average, states that expanded Medicaid had 78.2 (95% confidence interval = 16.0-140.3, P = 0.02) more prescriptions per year for naloxone compared with states that did not expand Medicaid coverage, a nearly 10 increase over the pre-expansion years. Medicaid expansion contributed to this growth in Medicaid-covered naloxone more than other state-level naloxone policies. CONCLUSIONS: Medicaid accounts for approximately a quarter of naloxone sales. Medicaid expansion generated 8.3% of the growth in naloxone units from 2009 to 2016, holding other factors constant.

State laws and policies to reduce opioid-related harm: A qualitative assessment of PDMPs and naloxone programs in ten U.S. States.

As the magnitude of the opioid epidemic grew in recent years, individual states across the United States of America enacted myriad policies to address its complications. We conducted a qualitative examination of the structure, successes, and challenges of enacted state laws and policies aimed at the opioid epidemic, with an in-depth focus on prescription drug monitoring programs (PDMPs) and naloxone access efforts. A set of 10 states (Florida, Kentucky, Massachusetts, Michigan, Missouri, New York, North Carolina, Tennessee, Washington, and West Virginia) was chosen a priori to achieve a varied sample of state policies and timing, as well as population opioid complications. Archival research was conducted to identify state-level policies aimed at the opioid epidemic and semi-structured interviews were conducted with 31 key stakeholders between March and September 2016. The most frequently mentioned key to success was an identifiable champion instrumental in leading the passage of these policies. The lack of a unified legislature and physician pushback were challenges many states faced in implementing policies. Champion-led task forces, stakeholders' personal stories garnering buy-in, ongoing education and feedback to PDMP users, and inclusive stakeholder engagement are critical aspects of passing and implementing state policies aimed at combating the opioid epidemic. Engaging all interested stakeholders and providing continuing feedback are ongoing challenges in all states. Leveraging stakeholders' personal stories of how opioids affected their lives helped propel state efforts.

Effect of Medicaid Expansion on Health Insurance Coverage and Access to Care Among Adults With Depression.

OBJECTIVE: Multiple studies have detailed the relationship between Medicaid expansion under the Affordable Care Act and various health and financial outcomes. However, fewer studies have examined Medicaid expansion's effects on individuals with psychiatric diagnoses. This study sought to determine the relationship between Medicaid expansion and various health and financial outcomes among low-income adults with depression. METHODS: This quasi-experimental study used a random-digit-dial survey of U.S. citizens ages 19-64 with incomes below 138% of the federal poverty level. Surveys were conducted in three southern states (two expansion states, Arkansas and Kentucky, and one nonexpansion state, Texas) between 2013 and 2016. The study sample consisted of those with a positive screen for depression-score of ≥2 on the two-item Patient Health Questionnaire (N=4,853). Survey-weighted difference-in-differences regressions were conducted with insurance status, health care access and utilization, and affordability of care as outcomes of interest. Subgroup analyses stratified the sample on the basis of the respondent's residence in a health professional shortage area (HPSA) in mental health and severity of depression. RESULTS: Medicaid expansion was associated with a significant reduction in the proportion of adults with depression who lacked health insurance (-23 percentage points, 95% confidence interval=-32 to -14, p<.001). Medicaid expansion was also associated with significant reductions in delaying care and medications because of cost. These changes were similar regardless of residence in a mental health HPSA and severity of depression. CONCLUSIONS: Medicaid expansion was associated with improved access to care and medication among persons with depression, even in areas with relative shortages of mental health professionals.