Roberts, Eric T, Alexandra Glynn, Julie M Donohue, and Lindsay M Sabik. (2021) 2021. “The Relationship Between Take-up of Prescription Drug Subsidies and Medicaid Among Low-Income Medicare Beneficiaries.”. Journal of General Internal Medicine 36 (9): 2873-76. https://doi.org/10.1007/s11606-020-06241-y.
Publications
2021
Donohue, Julie M. (2021) 2021. “Learning From Novel Approaches to Paying for Hepatitis C Virus Medications in State Medicaid Programs.”. JAMA Health Forum 2 (8): e212412. https://doi.org/10.1001/jamahealthforum.2021.2412.
Marin, Jennifer R, Mara A G Hollander, Kristin N Ray, Julie M Donohue, and Evan S Cole. (2021) 2021. “Low-Value Diagnostic Imaging in Children With Medicaid.”. The Journal of Pediatrics 235: 253-263.e14. https://doi.org/10.1016/j.jpeds.2021.02.003.
OBJECTIVES: To estimate rates and settings of low-value imaging among pediatric Medicaid beneficiaries and estimate the associated expenditures.
STUDY DESIGN: Retrospective longitudinal cohort study from 2014 to 2016 of children <18 years enrolled in Pennsylvania Medicaid. Outcomes were rates of low-value imaging for 5 conditions identified by diagnosis codes, healthcare settings of imaging performance, and cost based on paid amounts.
RESULTS: Of the 645 767 encounters for the 5 conditions, there were 37 525 (5.8%) low-value imaging services. Per 1000 encounters, there were 246.0 radiographs for bronchiolitis, 174.0 head computed tomography (CT) studies for minor head trauma, 155.0 and 33.3 neuroimaging studies for headache and simple febrile seizure, respectively, and 19.5 abdominal CT scans (without prior ultrasound examination) for abdominal pain. Rates of low-value imaging were highest in non-Hispanic White children and those in rural areas. In adjusted analysis, non-Hispanic White children were more likely to receive a CT scan for abdominal pain, and Black children were more likely to have imaging for bronchiolitis and minor head trauma. For individual conditions, up to 87.9% of low-value imaging (CT scan for minor head trauma) was in the emergency department (ED), with most imaging across all conditions occurring in nonpediatric EDs, up to 42.2% was in the outpatient setting (neuroimaging for headache), and up to 20.7% was during inpatient encounters (neuroimaging for febrile seizure). Outpatient and ED low-value imaging resulted in more than $7 million in Medicaid expenditures.
CONCLUSIONS: Among the studied conditions, more than 1 in 20 encounters included low-value imaging, mostly in nonpediatric EDs and for bronchiolitis, head trauma, and headache. Interventions are needed to decrease the future performance of these low-value services.
Hollander, Mara A G, Evan S Cole, Julie M Donohue, and Eric T Roberts. (2021) 2021. “Changes in Medicaid Utilization and Spending Associated With Homeless Adults’ Entry into Permanent Supportive Housing.”. Journal of General Internal Medicine 36 (8): 2353-60. https://doi.org/10.1007/s11606-020-06465-y.
BACKGROUND: There is growing interest in financing housing and supportive services for homeless individuals through Medicaid. Permanent Supportive Housing (PSH), which integrates non-time-limited housing with supportive services for people who are disabled and chronically homeless, has seen rapid growth in the last decade, but clear evidence on the long-term impacts of PSH, needed to guide state efforts to finance some PSH services through Medicaid, is lacking.
OBJECTIVE: Assess changes in Medicaid expenditures and utilization associated with receiving PSH.
DESIGN: Cohort study using a difference-in-differences approach.
PARTICIPANTS: A total of 1226 PA Medicaid enrollees who entered PSH 2011-2016 and remained in PSH for 180 days or more, and a matched comparison cohort of 970 enrollees experiencing housing instability who did not receive PSH.
MAIN MEASURES: Medicaid spending in aggregate, and on behavioral and physical health services; emergency department (ED) visits and inpatient hospital stays.
KEY RESULTS: Three years after PSH entry, spending decreased by an average of $145/month in the PSH cohort relative to changes in the comparison cohort (p = 0.046), with the greatest relative spending reductions occurring for residential behavioral health ($64, p < 0.001) and inpatient non-behavioral health services ($89, p = 0.001). We also found relative reductions in ED use (4.7 visits/100 person-months, p = 0.010) and inpatient hospital stays (1.6 visits/100 person-months, p < 0.001).
CONCLUSIONS: These results can inform emerging state efforts to finance PSH services through Medicaid. Additional state expenditures to expand financing for PSH services could be partially offset by reductions in Medicaid spending, in part by facilitating a shift in treatment to outpatient from acute care settings.
Sachs, Rachel E, Kyle A Gavulic, Julie M Donohue, and Stacie B Dusetzina. (2021) 2021. “Recent Trends in Medicaid Spending and Use of Drugs With US Food and Drug Administration Accelerated Approval.”. JAMA Health Forum 2 (10): e213177. https://doi.org/10.1001/jamahealthforum.2021.3177.
IMPORTANCE: State Medicaid programs have reported concerns about rising drug prices and spending, particularly regarding drugs entering the market through the accelerated approval program under the US Food and Drug Administration (FDA). The accelerated approval program enables the FDA to approve drugs on the basis of unverified surrogate end points, meaning that clinical benefits for these products are uncertain at the time of approval. However, state Medicaid programs are legally required to cover these drugs. Little is known about the set of products with accelerated approval over time, their use among Medicaid beneficiaries, or the magnitude of their financial influence on state Medicaid programs.
OBJECTIVE: To identify the number and class of drugs approved through the FDA's accelerated approval pathway and analyze state Medicaid programs' use and spending on these drugs from 2015 through 2019.
DESIGN SETTING AND PARTICIPANTS: In this cross-sectional study, biannual FDA reports were used to identify products granted accelerated approval and their associated indications approved between December 1992 and December 2020. State Medicaid Drug Utilization Data files available for 1992 through 2019 were used to estimate national totals for spending and use of outpatient drugs.
MAIN OUTCOMES AND MEASURES: National Medicaid use and gross and net spending on drugs with accelerated approval from 2015 through 2019.
RESULTS: Since the inception of the FDA's accelerated approval pathway in 1992 through 2020, 216 product-indication pairs granted accelerated approval were identified, comprising 149 unique products. The composition of drugs approved through the pathway has changed over time, with 28 of 30 (93.3%) product-indication pairs receiving accelerated approval in 2020 being indicated for cancer. Relative to all outpatient prescription drugs paid for by Medicaid, products with accelerated approval ranged from 0.2% to 0.4% of use (1.3-2.4 million prescriptions annually). Despite their infrequent use, drugs with accelerated approval represented a minimum annual net spending on all drugs covered by Medicaid of 6.4% ($2.2 billion of $34.6 billion) in 2015 and a maximum of 9.1% ($2.5 billion of $27.6 billion) in 2018. Estimated annual gross spending on drugs with accelerated approval ranged from $4.2 billion to $4.9 billion over 2015 through 2019, and estimated net spending from $2.2 billion to $2.6 billion.
CONCLUSIONS AND RELEVANCE: In this cross-sectional study of 216 drugs granted accelerated approval, state spending on drugs approved through the FDA's growing accelerated approval program represented an outsized amount of spending relative to use. Because drugs with accelerated approval have come to market on the basis of trials using surrogate end points, considerable amounts of this spending may have been attributable to products with unproven clinical benefits.
Hollander, Mara A G, Chung-Chou H Chang, Antoine B Douaihy, Eric Hulsey, and Julie M Donohue. (2021) 2021. “Racial Inequity in Medication Treatment for Opioid Use Disorder: Exploring Potential Facilitators and Barriers to Use.”. Drug and Alcohol Dependence 227: 108927. https://doi.org/10.1016/j.drugalcdep.2021.108927.
BACKGROUND: Despite evidence that individuals with opioid use disorder (OUD) have a lower risk of mortality when using evidence-based medications for OUD (MOUD), only 20 % of people with OUD receive MOUD. Black patients are significantly less likely than White patients to initiate MOUD. We measured the association between various facilitators and barriers to initiation, including criminal justice, human services, and health care factors, and variation in initiation of MOUD by race.
METHODS: We used data from a comprehensive, linked data set of health care, human services, and criminal justice programs from Allegheny County in Western Pennsylvania to measure disparities in MOUD initiation by race in the first 180 days after an OUD diagnosis, as well as mediation by potential facilitators and barriers to treatment, among Medicaid enrollees. This is a cross-sectional analysis.
RESULTS: Among 6374 Medicaid enrollees who met study criteria, Black enrollees were 18.2 percentage points less likely than White enrollees to start MOUD after controlling for gender, age, and Medicaid eligibility (95 % CI: -21.5 % - -14.8 %). Each day in the emergency department or county jail was associated with a decrease in the likelihood of initiation, as was the presence of a non-OUD substance use disorder diagnosis or participation in intensive non-MOUD treatment. Mediators accounted for approximately one-fifth of the variation in initiation related to race.
CONCLUSIONS: Acute care facilities and settings in which people with OUD are incarcerated may have an opportunity to increase the use of MOUD overall and close the racial gap in initiation.
Horvitz-Lennon, Marcela, Rita Volya, Simon Hollands, Katya Zelevinsky, Andrew Mulcahy, Julie M Donohue, and Sharon-Lise T Normand. (2021) 2021. “Factors Associated With Off-Label Utilization of Second-Generation Antipsychotics Among Publicly Insured Adults.”. Psychiatric Services (Washington, D.C.) 72 (9): 1031-39. https://doi.org/10.1176/appi.ps.202000381.
OBJECTIVE: Off-label utilization of second-generation antipsychotic medications may expose patients to significant risks. The authors examined the prevalence, temporal trends, and factors associated with off-label utilization of second-generation antipsychotics among publicly insured adults.
METHODS: A retrospective repeated panel was used to examine monthly off-label utilization of second-generation antipsychotics among fee-for-service Medicare, Medicaid, and dually eligible White, Black, and Latino adult beneficiaries filling prescriptions for second-generation antipsychotics in California, Georgia, Mississippi, and Oklahoma from July 2008 through June 2013.
RESULTS: Among 301,367 users of second-generation antipsychotics, between 36.5% and 41.9% had utilization that was always off-label. Payer did not modify effects of race-ethnicity on off-label utilization. Compared with Whites, Blacks had lower monthly odds of off-label utilization in all four states, and Latinos had lower odds of utilization in California and Georgia. Payer was associated with off-label utilization in California, Mississippi, and Oklahoma. California Medicaid beneficiaries were 1.12 (95% confidence interval=1.10-1.13) times as likely as dually eligible beneficiaries to have off-label utilization. Off-label utilization increased relative to the baseline year in all states, but a downward trend followed in three states.
CONCLUSIONS: Off-label utilization of second-generation antipsychotics was prevalent despite the drugs' cardiometabolic risks and little evidence of their effectiveness. The lower likelihood of off-label utilization among patients from racial-ethnic minority groups might stem from prescribers' efforts to minimize risks, given a higher baseline risk for these groups, or from disparities-associated factors. Variation among payers suggests that payer policies can affect off-label utilization.
Jarlenski, Marian, Joo Yeon Kim, Katherine A Ahrens, Lindsay Allen, Anna Austin, Andrew J Barnes, Dushka Crane, et al. (2021) 2021. “Healthcare Patterns of Pregnant Women and Children Affected by OUD in 9 State Medicaid Populations.”. Journal of Addiction Medicine 15 (5): 406-13. https://doi.org/10.1097/ADM.0000000000000780.
OBJECTIVES: State Medicaid programs are the largest single provider of healthcare for pregnant persons with opioid use disorder (OUD). Our objective was to provide comparable, multistate measures estimating the burden of OUD in pregnancy, medication for OUD (MOUD) in pregnancy, and related neonatal and child outcomes.
METHODS: Drawing on the Medicaid Outcomes Distributed Research Network (MODRN), we accessed administrative healthcare data for 1.6 million pregnancies and 1.3 million live births in 9 state Medicaid populations from 2014 to 2017. We analyzed within- and between-state prevalences and time trends in the following outcomes: diagnosis of OUD in pregnancy, initiation, and continuity of MOUD in pregnancy, Neonatal Opioid Withdrawal Syndrome (NOWS), and well-child visit utilization among children with NOWS.
RESULTS: OUD diagnosis increased from 49.6 per 1000 to 54.1 per 1000 pregnancies, and the percentage of those with any MOUD in pregnancy increased from 53.4% to 57.9%, during our study time period. State-specific percentages of 180-day continuity of MOUD ranged from 41.2% to 84.5%. The rate of neonates diagnosed with NOWS increased from 32.7 to 37.0 per 1000 live births. State-specific percentages of children diagnosed with NOWS who had the recommended well-child visits in the first 15 months ranged from 39.3% to 62.5%.
CONCLUSIONS: Medicaid data, which allow for longitudinal surveillance of care across different settings, can be used to monitor OUD and related pregnancy and child health outcomes. Findings highlight the need for public health efforts to improve care for pregnant persons and children affected by OUD.
Xue, Lingshu, Robert M Boudreau, Julie M Donohue, Janice C Zgibor, Zachary A Marcum, Tina Costacou, Anne B Newman, Teresa M Waters, and Elsa S Strotmeyer. (2021) 2021. “Persistent Polypharmacy and Fall Injury Risk: The Health, Aging and Body Composition Study.”. BMC Geriatrics 21 (1): 710. https://doi.org/10.1186/s12877-021-02695-9.
BACKGROUND: Older adults receive treatment for fall injuries in both inpatient and outpatient settings. The effect of persistent polypharmacy (i.e. using multiple medications over a long period) on fall injuries is understudied, particularly for outpatient injuries. We examined the association between persistent polypharmacy and treated fall injury risk from inpatient and outpatient settings in community-dwelling older adults.
METHODS: The Health, Aging and Body Composition Study included 1764 community-dwelling adults (age 73.6 ± 2.9 years; 52% women; 38% black) with Medicare Fee-For-Service (FFS) claims at or within 6 months after 1998/99 clinic visit. Incident fall injuries (N = 545 in 4.6 ± 2.9 years) were defined as the initial claim with an ICD-9 fall E-code and non-fracture injury, or fracture code with/without a fall code from 1998/99 clinic visit to 12/31/08. Those without fall injury (N = 1219) were followed for 8.1 ± 2.6 years. Stepwise Cox models of fall injury risk with a time-varying variable for persistent polypharmacy (defined as ≥6 prescription medications at the two most recent consecutive clinic visits) were adjusted for demographics, lifestyle characteristics, chronic conditions, and functional ability. Sensitivity analyses explored if persistent polypharmacy both with and without fall risk increasing drugs (FRID) use were similarly associated with fall injury risk.
RESULTS: Among 1764 participants, 636 (36%) had persistent polypharmacy over the follow-up period, and 1128 (64%) did not. Fall injury incidence was 38 per 1000 person-years. Persistent polypharmacy increased fall injury risk (hazard ratio [HR]: 1.31 [1.06, 1.63]) after adjusting for covariates. Persistent polypharmacy with FRID use was associated with a 48% increase in fall injury risk (95%CI: 1.10, 2.00) vs. those who had non-persistent polypharmacy without FRID use. Risks for persistent polypharmacy without FRID use (HR: 1.22 [0.93, 1.60]) and non-persistent polypharmacy with FRID use (HR: 1.08 [0.77, 1.51]) did not significantly increase compared to non-persistent polypharmacy without FRID use.
CONCLUSIONS: Persistent polypharmacy, particularly combined with FRID use, was associated with increased risk for treated fall injuries from inpatient and outpatient settings. Clinicians may need to consider medication management for FRID and other fall prevention strategies in community-dwelling older adults with persistent polypharmacy to reduce fall injury risk.
Lo-Ciganic, Wei-Hsuan, Julie M Donohue, Eric G Hulsey, Susan Barnes, Yuan Li, Courtney C Kuza, Qingnan Yang, et al. (2021) 2021. “Integrating Human Services and Criminal Justice Data With Claims Data to Predict Risk of Opioid Overdose Among Medicaid Beneficiaries: A Machine-Learning Approach.”. PloS One 16 (3): e0248360. https://doi.org/10.1371/journal.pone.0248360.
Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algorithm to predict opioid overdose risk by integrating human services and criminal justice data with health claims data to capture the social determinants of overdose risk. This prognostic study included Medicaid beneficiaries (n = 237,259) in Allegheny County, Pennsylvania enrolled between 2015 and 2018, randomly divided into training, testing, and validation samples. We measured 290 potential predictors (239 derived from Medicaid claims data) in 30-day periods, beginning with the first observed Medicaid enrollment date during the study period. Using a gradient boosting machine, we predicted a composite outcome (i.e., fatal or nonfatal opioid overdose constructed using medical examiner and claims data) in the subsequent month. We compared prediction performance between a Medicaid claims only model to one integrating human services and criminal justice data with Medicaid claims (i.e., integrated model) using several metrics (e.g., C-statistic, number needed to evaluate [NNE] to identify one overdose). Beneficiaries were stratified into risk-score decile subgroups. The samples (training = 79,087, testing = 79,086, validation = 79,086) had similar characteristics (age = 38±18 years, female = 56%, white = 48%, having at least one overdose = 1.7% during study period). Using the validation sample, the integrated model slightly improved on the Medicaid claims only model (C-statistic = 0.885; 95%CI = 0.877-0.892 vs. C-statistic = 0.871; 95%CI = 0.863-0.878), with small corresponding improvements in the NNE and positive predictive value. Nine of the top 30 most important predictors in the integrated model were human services and criminal justice variables. Using the integrated model, approximately 70% of individuals with overdoses were members of the top risk decile (overdose rates in the subsequent month = 47/10,000 beneficiaries). Few individuals in the bottom 9 deciles had overdose episodes (0-12/10,000). Machine-learning algorithms integrating claims and social service and criminal justice data modestly improved opioid overdose prediction among Medicaid beneficiaries for a large U.S. county heavily affected by the opioid crisis.