Project description:ImportanceCOVID-19 relief legislation created a temporary moratorium on Medicaid disenrollment, but when the public health emergency ends, states will begin to "unwind" Medicaid enrollment. Prepandemic data shed light on factors that can affect Medicaid coverage stability.ObjectiveTo assess factors associated with the duration and continuity of Medicaid enrollment.Design, setting, and participantsIn this cross-sectional analyses of a Medicaid data set for 2016 that was released by the Agency for Healthcare Research and Quality in June of 2022, we analyze a nationally representative data set of 5.7 million persons, weighted to represent 70 million Medicaid beneficiaries in 2016. We focus on 22 million nondisabled, nonelderly adults for this analysis. The data were analyzed between July and September of 2022.Main outcomes and measuresThe main outcomes were the average months of Medicaid enrollment in 2016 and the probability of churning, defined as a break in coverage between 2 periods of enrollment during the calendar year. We compared these outcomes by eligibility category, state, demographic characteristics, and key Medicaid policies, including whether the state expanded Medicaid and whether it used ex parte reviews (automated reviews of other administrative data to reduce renewal paperwork burdens).ResultsIn this cross-sectional analysis, we analyze a nationally representative Medicaid data set of 5.7 million persons, weighted to represent 70 million Medicaid beneficiaries in 2016, released by the Agency for Healthcare Research and Quality in June of 2022. The analysis focused on nonelderly, nondisabled adults (aged 18-64 years) with a weighted population size of 22.7 million, of which 18.4% were Black, 19.2% were Latino, 39.5% were White, 7.3% were other/Asian/Native American, and 15.5% had unknown race. Multivariable regression analysis indicated that those living in states that expanded Medicaid but did not use ex parte reviews had longer average duration (0.31 months longer; 95% CI, 0.03-0.59) and lower risk of churning(odds ratio [OR], .40; 95% CI, 0.39-0.40), whereas those living in nonexpansion states that used ex parte reviews had lower odds of churning (OR, .68; 95% CI, 0.66-0.70) but also had shorter average duration (3.1 months shorter; 95% CI, -3.4 to -2.8). Those living in expansion states that used ex parte reviews also had reduced churning (OR, .83; 95% CI, 0.82-0.85). The average duration varied widely by state, even after adjustments for demographic and state policy factors.Conclusions and relevanceIf state Medicaid programs revert to prepandemic policies after the temporary moratorium ends, Medicaid coverage, particularly for nondisabled, nonelderly adults, is likely to become less stable again. Medicaid expansions are associated with improved continuity, but ex parte review may have a more complex role.

Project description:ImportanceAfter the federal public health emergency was declared in March 2020, states could qualify for increased federal Medicaid funding if they agreed to maintenance of eligibility (MOE) provisions, including a continuous coverage provision. The implications of MOE provisions for total Medicaid enrollment are unknown.ObjectiveTo examine observed increases in Medicaid enrollment and identify the underlying roots of that growth during the first 7 months of the COVID-19 public health emergency in Wisconsin.Design setting and participantsThis population-based cohort study compared changes in Wisconsin Medicaid enrollment from March through September 2020 with predicted changes based on previous enrollment patterns (January 2015-September 2019) and early pandemic employment shocks. The participants included enrollees in full-benefit Medicaid programs for nonelderly, nondisabled beneficiaries in Wisconsin from March through September 2020. Individuals were followed up monthly as they enrolled in, continued in, and disenrolled from Medicaid. Participants were considered to be newly enrolled if they enrolled in the program after being not enrolled for at least 1 month, and they were considered disenrolled if they left and were not reenrolled within the next month.ExposuresContinuous coverage provision beginning in March 2020; economic disruption from pandemic between first and second quarters of 2020.Main outcomes and measuresActual vs predicted Medicaid enrollment, new enrollment, disenrollment, and reenrollment. Three models were created (Medicaid enrollment with no pandemic, Medicaid enrollment with pandemic economic circumstances, and longer Medicaid enrollment with a pandemic-induced recession), and a 95% prediction interval was used to express uncertainty in enrollment predictions.ResultsThe study estimated ongoing Medicaid enrollment in March 2020 for 792 777 enrollees (mean [SD] age, 20.6 [16.5] years; 431 054 [54.4%] women; 213 904 [27.0%] experiencing an employment shock) and compared that estimate with actual enrollment totals. Compared with a model of enrollment based on past data and incorporating the role of recent employment shocks, most ongoing excess enrollment was associated with MOE provisions rather than enrollment of newly eligible beneficiaries owing to employment shocks. After 7 months, overall enrollment had increased to 894 619, 11.1% higher than predicted (predicted enrollment 805 130; 95% prediction interval 767 991-843 086). Decomposing higher-than-predicted retention, most enrollment was among beneficiaries who, before the pandemic, likely would have disenrolled within 6 months, although a substantial fraction (30.4%) was from reduced short-term disenrollment.Conclusions and relevanceIn this cohort study, observed increases in Medicaid enrollment were largely associated with MOE rather than new enrollment after employment shocks. Expiration of MOE may leave many beneficiaries without insurance coverage.

Project description:The COVID-19 pandemic has caused tremendous disruptions to non-COVID-19 clinical research. However, there has been little investigation on how patients themselves have responded to clinical trial recruitment during the COVID-19 pandemic. To investigate the effect of the COVID-19 pandemic on rates of patient consent to enrollment into non-COVID-19 clinical trials, we carried out a cross-sectional study using data from the Nitric Oxide/Acute Kidney Injury (NO/AKI) and Minimizing ICU Neurological Dysfunction with Dexmedetomidine-Induced Sleep (MINDDS) trials. All patients eligible for the NO/AKI or MINDDS trials who came to the hospital for cardiac surgery and were approached to gain consent to enrollment were included in the current study. We defined "Before COVID-19" as the time between the start of the relevant clinical trial and the date when efforts toward that clinical trial were deescalated by the hospital due to COVID-19. We defined "During COVID-19" as the time between trial de-escalation and trial completion. 5,015 patients were screened for eligibility. 3,851 were excluded, and 1,434 were approached to gain consent to enrollment. The rate of consent to enrollment was 64% in the "Before COVID-19" group and 45% in the "During COVID-19" group (n = 1,334, P<0.001) (RR = 0.70, 95% CI 0.62 to 0.80, P<0.001). Thus, we found that rates of consent to enrollment into the NO/AKI and MINDDS trials dropped significantly with the onset of the COVID-19 pandemic. Patient demographic and socioeconomic status data collected from electronic medical records and patient survey data did not shed light on possible explanations for this observed drop, indicating that there were likely other factors at play that were not directly measured in the current study. Increased patient hesitancy to enroll in clinical trials can have detrimental effects on clinical science, patient health, and patient healthcare experience, so understanding and addressing this issue during the COVID-19 pandemic is crucial.

Project description:ImportanceThe COVID-19 pandemic has been associated with increased unemployment rates and long periods when individuals were without health insurance. Little is known about how Medicaid expansion facilitates Medicaid enrollment as a buffer to coverage loss owing to unemployment.ObjectiveTo compare changes in health insurance coverage status associated with pandemic-related unemployment among previously employed adults in states that have vs have not expanded Medicaid eligibility.Design setting and participantsThis cohort study included US adults aged 27 to 64 years who were employed at baseline in the 2020 to 2021 Current Population Survey's Annual Social and Economic Supplement, which included calendar years 2019 to 2020 (32 462 person-years). Data analyses were conducted between November 2021 and April 2022.ExposuresJob loss (ie, new unemployment) experienced during 2020.Main outcomes and measuresPrimary outcomes were coverage status (ie, uninsured status) and source of coverage (ie, employer sponsored, marketplace, and Medicaid). Using 2-way person-by-year fixed-effects regression models, changes in coverage status associated with unemployment in states that expanded Medicaid were compared with states that did not expand Medicaid. Additional analyses were performed based on prepandemic coverage status.ResultsThe cohort included 16 231 adults (mean age, 46.8 [95% CI, 46.6-47.0] years; 51.6% women). New unemployment was associated with an increase of 2.9 (95% CI, 1.1-4.6) percentage points (P = .002) in the proportion of uninsured adults in Medicaid expansion states and an increase of 10.7 (95% CI, 2.4-18.9) percentage points (P = .01) in nonexpansion states. Workers were 5.4 (95% CI, 1.9-8.9) percentage points (P = .003) more likely to enroll in Medicaid after a job loss if they lived in a Medicaid expansion state compared with workers experiencing job loss in nonexpansion states.Conclusions and relevanceIn this cohort study of US adults, unemployment-related Medicaid enrollment was more frequent in Medicaid expansion states during the COVID-19 pandemic. Medicaid expansion led to a smaller increase in uninsured adults because those who lost private insurance coverage (eg, employer sponsored) appeared more able to transition to Medicaid after job loss.

Project description:BackgroundPatient-level predictors of enrollment in pediatric biorepositories are poorly described. Especially in pandemic settings, understanding who is likely to enroll in a biorepository is critical to interpreting analyses conducted on biospecimens. We describe predictors of pediatric COVID-19 biorepository enrollment and biospecimen donation to identify gaps in COVID-19 research on pediatric biospecimens.MethodsWe compared data from enrollees and non-enrollees aged 0-25 years with suspected or confirmed COVID-19 infection who were approached for enrollment in the Massachusetts General Hospital pediatric COVID-19 biorepository between April 12, 2020, and May 28, 2020, from community or academic outpatient or inpatient settings. Demographic and clinical data at presentation to care were from automatic and manual chart extractions. Predictors of enrollment and biospecimen donation were assessed with Poisson regression models.ResultsAmong 457 individuals approached, 214 (47%) enrolled in the biorepository. A COVID-19 epidemiologic risk factor was recorded for 53%, and 15% lived in a US Centers for Disease Control and Prevention-defined COVID-19 hotspot. Individuals living in a COVID-19 hotspot (relative risk (RR) 2.4 [95% confidence interval (CI): 1.8-3.2]), with symptoms at presentation (RR 1.8 [95% CI: 1.2-2.7]), or admitted to hospital (RR 1.8 [95% CI: 1.2-2.8]) were more likely to enroll. Seventy-nine percent of enrollees donated any biospecimen, including 97 nasopharyngeal swabs, 119 oropharyngeal swabs, and 105 blood, 16 urine, and 16 stool specimens, respectively. Age, sex, race, ethnicity, and neighborhood-level socioeconomic status based on zip code did not predict enrollment or biospecimen donation.ConclusionsWhile fewer than half of individuals approached consented to participate in the pediatric biorepository, enrollment appeared to be representative of children affected by the pandemic. Living in a COVID-19 hotspot, symptoms at presentation to care and hospital admission predicted biorepository enrollment. Once enrolled, most individuals donated a biospecimen.

Dataset Information

Changes in US Medicaid Enrollment During the COVID-19 Pandemic.

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