smdi: an R package to perform structural missing data investigations on partially observed confounders in real-world evidence studies.

Objectives: Partially observed confounder data pose a major challenge in statistical analyses aimed to inform causal inference using electronic health records (EHRs). While analytic approaches such as imputation are available, assumptions on underlying missingness patterns and mechanisms must be verified. We aimed to develop a toolkit to streamline missing data diagnostics to guide choice of analytic approaches based on meeting necessary assumptions. Materials and methods: We developed the smdi (structural missing data investigations) R package based on results of a previous simulation study which considered structural assumptions of common missing data mechanisms in EHR. Results: smdi enables users to run principled missing data investigations on partially observed confounders and implement functions to visualize, describe, and infer potential missingness patterns and mechanisms based on observed data. Conclusions: The smdi R package is freely available on CRAN and can provide valuable insights into underlying missingness patterns and mechanisms and thereby help improve the robustness of real-world evidence studies.

Variations in antibiotic prescribing among children enrolled in North Carolina Medicaid, 2013-2019.

PURPOSE: The majority of pediatric antibiotic prescribing occurs in the outpatient setting and inappropriate use contributes to antimicrobial resistance. There are regional variations in outpatient antibiotic use with the highest rates occurring in the Southern states, including in Appalachia. The purpose of this study was to describe the rates and risk factors for inappropriate antibiotic prescription among pediatric patients enrolled in North Carolina (NC) Medicaid. METHODS: We used Medicaid prescription claims data from 2013 to 2019 to describe patterns of pediatric antibiotic prescription in NC. We assessed patient and provider factors to identify variations in prescribing. FINDINGS: Children who were less than 2 years of age, non-Hispanic White, and living in a rural area had the highest overall rates of antibiotic prescription. Compared to pediatricians, the risk of inappropriate antibiotic prescription was highest among other specialists and general practioners and lowest among nurse practitioners. Rural areas of NC had the highest rates of inappropriate antibiotic prescribing, and the risk for non-Hispanic Black children compared to children of other races/ethnicities was compounded by rurality. CONCLUSIONS: Prescribing practices in NC differ compared to neighboring states with a lower overall risk of inappropriate prescription in Appalachian regions; however, disparities by race and rurality exist. Outpatient stewardship efforts in NC should focus on ensuring health equity by appreciating racial and geographic variations in prescribing patterns and providing education to all health care providers.

Genomic classifiers and prognosis of localized prostate cancer: a systematic review.

BACKGROUND: Refinement of the risk classification for localized prostate cancer is warranted to aid in clinical decision making. A systematic analysis was undertaken to evaluate the prognostic ability of three genomic classifiers, Decipher, GPS, and Prolaris, for biochemical recurrence, development of metastases and prostate cancer-specific mortality in patients with localized prostate cancer. METHODS: Data sources: MEDLINE, Embase, and Web of Science were queried for reports published from January 2010 to April 2022. STUDY SELECTION: prospective or retrospective studies reporting prognosis for patients with localized prostate cancer. DATA EXTRACTION: relevant data were extracted into a customized database by one researcher with a second overreading. Risk of bias was assessed using a validated tool for prognostic studies, Quality in Prognosis Studies (QUIPS). Disagreements were resolved by consensus or by input from a third reviewer. We assessed the certainty of evidence by GRADE incorporating adaptation for prognostic studies. RESULTS: Data synthesis: a total of 39 studies (37 retrospective) involving over 10,000 patients were identified. Twenty-two assessed Decipher, 5 GPS, and 14 Prolaris. Thirty-four studies included patients who underwent prostatectomy. Based on very low to low certainty of evidence, each of the three genomic classifiers modestly improved upon the prognostic ability for biochemical recurrence, development of metastases, and prostate cancer-specific mortality compared to standard clinical risk-classification schemes. LIMITATIONS: downgrading of confidence in the evidence stemmed largely from bias due to the retrospective nature of the studies, heterogeneity in treatment received, and era in which patients were treated (i.e., prior to the 2000s). CONCLUSIONS: Genomic classifiers provide a small but consistent improvement upon the prognostic ability of clinical classification schemes, which may be helpful when treatment decisions are uncertain. However, evidence from current management-era data and of the predictive ability of these tests is needed.

Overview of global real-world data sources for pediatric pharmacoepidemiologic research.

PURPOSE: Given limited information available on real-world data (RWD) sources with pediatric populations, this study describes features of globally available RWD sources for pediatric pharmacoepidemiologic research. METHODS: An online questionnaire about pediatric RWD sources and their attributes and capabilities was completed by members and affiliates of the International Society for Pharmacoepidemiology and representatives of nominated databases. All responses were verified by database representatives and summarized. RESULTS: Of 93 RWD sources identified, 55 unique pediatric RWD sources were verified, including data from Europe (47%), United States (38%), multiregion (7%), Asia-Pacific (5%), and South America (2%). Most databases had nationwide coverage (82%), contained electronic health/medical records (47%) and/or administrative claims data (42%) and were linkable to other databases (65%). Most (71%) had limited outside access (e.g., by approval or through local collaborators); only 10 (18%) databases were publicly available. Six databases (11%) reported having >20 million pediatric observations. Most (91%) included children of all ages (birth until 18th birthday) and contained outpatient medication data (93%), while half (49%) contained inpatient medication data. Many databases captured vaccine information for children (71%), and one-third had regularly updated data on pediatric height (31%) and weight (33%). Other pediatric data attributes captured include diagnoses and comorbidities (89%), lab results (58%), vital signs (55%), devices (55%), imaging results (42%), narrative patient histories (35%), and genetic/biomarker data (22%). CONCLUSIONS: This study provides an overview with key details about diverse databases that allow researchers to identify fit-for-purpose RWD sources suitable for pediatric pharmacoepidemiologic research.

Underimmunization of very low birth weight infants at discharge from the neonatal intensive care unit.

OBJECTIVE: To quantify immunization status among premature infants discharged from neonatal intensive care units (NICUs), and identify risk factors for underimmunization. STUDY DESIGN: We performed a cohort study of infants <33 weeks gestation discharged home between 2011 and 2020 from 241 NICUs. Using multivariable logistic regression, we examined the association between risk factors and underimmunization at discharge, defined as <1 dose of 5 vaccine types when discharged at 60-119 days of age and <2 doses when discharged at 120-179 days of age. RESULTS: Of 30,766 infants discharged at 60-119 days of age, 14% were underimmunized. Among 4358 infants discharged at 120-179 days of age, 53% were underimmunized. For infants discharged at 60-119 days of age, ventilator support within 30 days of discharge was associated with underimmunization. Having a surgical procedure was associated with underimmunization in both groups. CONCLUSION: A large proportion of premature infants discharged from the NICU are underimmunized.

Optimizing data integration in trials that use EHR data: lessons learned from a multi-center randomized clinical trial.

BACKGROUND: Despite great promise, trials that ascertain patient clinical data from electronic health records (EHR), referred to here as "EHR-sourced" trials, are limited by uncertainty about how existing trial sites and infrastructure can be best used to operationalize study goals. Evidence is needed to support the practical use of EHRs in contemporary clinical trial settings. MAIN TEXT: We describe a demonstration project that used EHR data to complement data collected for a contemporary multi-center pharmaceutical industry outcomes trial, and how a central coordinating center supported participating sites through the technical, governance, and operational aspects of this type of activity. We discuss operational considerations related to site selection, data extraction, site performance, and data transfer and quality review, and we outline challenges and lessons learned. We surveyed potential sites and used their responses to assess feasibility, determine the potential capabilities of sites and choose an appropriate data extraction strategy. We designed a flexible, multimodal approach for data extraction, enabling each site to either leverage an existing data source, create a new research datamart, or send all data to the central coordinating center to produce the requisite data elements. We evaluated site performance, as reflected by the speed of contracting and IRB approval, total patients enrolled, enrollment yield, data quality, and compared performance by data collection strategy. CONCLUSION: While broadening the type of sites able to participate in EHR-sourced trials may lead to greater generalizability and improved enrollment, sites with fewer technical resources may require additional support to participate. Central coordinating center support is essential to facilitate the execution of operational processes. Future work should focus on sharing lessons learned and creating reusable tools to facilitate participation of heterogeneous trial sites.

Vaccine patterns among patients diagnosed with Guillain-Barré Syndrome and matched counterparts in a Medicare supplemental population, 2000-2020.

Some vaccines have a small risk of Guillain-Barré Syndrome (GBS), a rare autoimmune disorder characterized by paralysis if untreated. The CDC's Advisory Committee on Immunization Practices (ACIP) guidelines do not consider GBS a precaution for future vaccines unless GBS developed within six weeks after a tetanus-toxoid-containing vaccine or influenza vaccine. Our goal was to describe vaccine patterns before and after GBS diagnosis. We matched each of 709 patients diagnosed with GBS from 2002 to 2020 with Medicare supplemental insurance to 10 counterparts without GBS (1:10) on age and sex. Propensity score-based weighting balanced covariates between groups, and we estimated weighted mean cumulative counts (wMCC) of vaccines/person before and after GBS diagnosis. Among patients with GBS, 7% were diagnosed within 42 days after a vaccine. Prior to GBS diagnosis, the wMCC of vaccines per person was similar between GBS cases and matched counterparts, but after two years of follow-up, GBS patients received 21 fewer vaccines/100 people than counterparts (wMCC difference -0.21 vaccines/person, 95% CI -0.24 to -0.18); GBS patients received 16 vaccines/100 people while matched counterparts received 36/100. Vaccine use was reduced following GBS diagnosis despite no ACIP precaution for most (93%) patients in this study. The observed drop in vaccines after GBS diagnosis indicates a disconnect between clinical practice and current recommendations.

Non-overdose acute care hospitalizations for opioid use disorder among commercially-insured adults: a retrospective cohort study.

BACKGROUND: Acute care inpatient admissions outside of psychiatric facilities have been increasingly identified as a critical touchpoint for opioid use disorder (OUD) treatment. We sought to describe non-opioid overdose hospitalizations with documented OUD and examine receipt of post-discharge outpatient buprenorphine. METHODS: We examined acute care hospitalizations with an OUD diagnosis in any position within US commercially-insured adults age 18-64 years (IBM MarketScan claims, 2013-2017), excluding opioid overdose diagnoses. We included individuals with ≥ 6 months of continuous enrollment prior to the index hospitalization and ≥ 10 days following discharge. We described demographic and hospitalization characteristics, including outpatient buprenorphine receipt within 10 days of discharge. RESULTS: Most (87%) hospitalizations with documented OUD did not include opioid overdose. Of 56,717 hospitalizations (49,959 individuals), 56.8% had a primary diagnosis other than OUD, 37.0% had documentation of an alcohol-related diagnosis code, and 5.8% end in a self-directed discharge. Where opioid use disorder was not the primary diagnosis, 36.5% were due to other substance use disorders, and 23.1% were due to psychiatric disorders. Of all non-overdose hospitalizations who had prescription medication insurance coverage and who were discharged to an outpatient setting (n = 49, 237), 8.8% filled an outpatient buprenorphine prescription within 10 days of discharge. CONCLUSIONS: Non-overdose OUD hospitalizations often occur with substance use disorders and psychiatric disorders, and very few are followed by timely outpatient buprenorphine. Addressing the OUD treatment gap during hospitalization may include implementing medication for OUD for inpatients with a broad range of diagnoses.

Impact of state legislation and institutional protocols on opioid prescribing practices following pediatric tonsillectomy.

Objectives: Tonsillectomy is a common pediatric surgery, and pain is an important consideration in recovery. Due to the opioid epidemic, individual states, medical societies, and institutions have all taken steps to limit postoperative opioids, yet few studies have examined the effect of these interventions on pediatric otolaryngology practices. The primary aim of this study was to characterize opioid prescribing practices following North Carolina state opioid legislation and targeted institutional changes. Methods: This single center retrospective cohort study included 1552 pediatric tonsillectomy patient records from 2014 to 2021. The primary outcome was number of oxycodone doses per prescription. This outcome was assessed over three time periods: (1) Before 2018 North Carolina opioid legislation. (2) Following legislation, before institutional changes. (3) After institutional opioid-specific protocols. Results: The mean (± standard deviation) number of doses per prescription in Periods 1, 2, and 3 was: 58 ± 53, range 4-493; 28 ± 36, range 3-488; and 23 ± 17, range 1-139, respectively. In the adjusted model, Periods 2 and 3 had lower doses by -41% (95% CI -49%, -32%) and -40% (95% CI -55%, -19%) compared to Period 1. After 2018 North Carolina legislation, dosage decreased by -9% (95% CI -13%, -5%) per year. Despite interventions, ongoing variability in prescription regimens remained in all periods. Conclusion: Legislative and institution specific opioid interventions was associated with a 40% decrease in oxycodone doses per prescription following pediatric tonsillectomy. While variability in opioid practices decreased post-interventions, it was not eliminated. Level of evidence: 3.

Geographic Trends in Pediatric Psychotropic Medication Dispensing Before and After the Start of the COVID-19 Pandemic.

OBJECTIVE: This study examined trends and geographic variability in dispensing of prescription psychotropic medications to U.S. youths before and after the start of the COVID-19 pandemic. METHODS: Using national data on prescription medication dispensing, the authors performed a cross-sectional study examining the monthly percent change in psychotropic medications dispensed (total N=95,639,975) to youths (ages 5-18 years) in 2020 versus 2019, across medication classes and geographic regions. RESULTS: For many medications, more were dispensed in March 2020 than in March 2019 and fewer in April-May 2020 versus April-May 2019. Stimulants had the largest decline: -26.4% in May 2020 versus May 2019. The magnitude of the monthly percent change varied by region. CONCLUSIONS: Fewer psychotropic medications were dispensed to U.S. youths after the start of the COVID-19 pandemic compared with 2019. Although some medication classes rebounded to prepandemic dispensing levels by September 2020, dispensing varied by class and region.

Healthcare Utilization for Medicaid-Insured Children with Medical Complexity: Differences by Sociodemographic Characteristics.

OBJECTIVE: To compare differences in healthcare utilization and costs for Medicaid-insured children with medical complexity (CMC) by race/ethnicity and rurality. METHODS: Retrospective cohort of North Carolina (NC) Medicaid claims for children 3-20 years old with 3 years continuous Medicaid coverage (10/1/2015-9/30/2018). Exposures were medical complexity, race/ethnicity, and rurality. Three medical complexity levels were: without chronic disease, non-complex chronic disease, and complex chronic disease; the latter were defined as CMC. Race/ethnicity was self-reported in claims; we defined rurality by home residence ZIP codes. Utilization and costs were summarized for 1 year (10/1/2018-9/30/2019) by complexity level classification and categorized as acute care (hospitalization, emergency [ED]), outpatient care (primary, specialty, allied health), and pharmacy. Per-complexity group utilization rates (per 1000 person-years) by race/ethnicity and rurality were compared using adjusted rate ratios (ARR). RESULTS: Among 859,166 Medicaid-insured children, 118,210 (13.8%) were CMC. Among CMC, 36% were categorized as Black non-Hispanic, 42.7% White non-Hispanic, 14.3% Hispanic, and 35% rural. Compared to White non-Hispanic CMC, Black non-Hispanic CMC had higher hospitalization (ARR = 1.12; confidence interval, CI 1.08-1.17) and ED visit (ARR = 1.17; CI 1.16-1.19) rates; Hispanic CMC had lower ED visit (ARR = 0.77; CI 0.75-0.78) and hospitalization rates (ARR = 0.79; CI 0.73-0.84). Black non-Hispanic and Hispanic CMC had lower outpatient visit rates than White non-Hispanic CMC. Rural CMC had higher ED (ARR = 1.13; CI 1.11-1.15) and lower primary care utilization rates (ARR = 0.87; CI 0.86-0.88) than urban CMC. DISCUSSION: Healthcare utilization varied by race/ethnicity and rurality for Medicaid-insured CMC. Further studies should investigate mechanisms for these variations and expand higher value, equitable care delivery for CMC.

Fitness of real-world data for clinical trial data collection: Results and lessons from a HARMONY Outcomes ancillary study.

BACKGROUND: Despite the extensive use of real-world data for retrospective, observational clinical research, our understanding of how real-world data might increase the efficiency of data collection in patient-level randomized clinical trials is largely unknown. The structure of real-world data is inherently heterogeneous, with each source electronic health record and claims database different from the next. Their fitness-for-use as data sources for multisite trials in the United States has not been established. METHODS: For a subset of participants in the HARMONY Outcomes Trial, we obtained electronic health record data from recruiting sites or Medicare claims data from the Centers for Medicare & Medicaid Services. For baseline characteristics and follow-up events, we assessed the level of agreement between these real-world data and data documented in the trial database. RESULTS: Real-world data-derived demographic information tended to agree with trial-reported demographic information, although real-world data were less accurate in identifying medical history. The ability of real-world data to identify baseline medication usage differed by real-world data source, with claims data demonstrating substantially better performance than electronic health record data. The limited number of lab results in the collected electronic health record data matched closely with values in the trial database. There were not enough follow-up events in the ancillary study population to draw meaningful conclusions about the performance of real-world data for identification of events. Based on the conduct of this ancillary study, the challenges and opportunities of using real-world data within clinical trials are discussed. CONCLUSION: Based on a subset of participants from the HARMONY Outcomes Trial, our results suggest that electronic health record or claims data, as currently available, are unlikely to be a complete substitute for trial data collection of medical history or baseline lab results, but that Medicare claims were able to identify most medications. The limited size of the study population prevents us from drawing strong conclusions based on these results, and other studies are clearly needed to confirm or refute these findings.

Implementation of a comprehensive hospitalist-led initiative to improve care for patients with opioid use disorder.

BACKGROUND: As opioid-related hospitalizations rise, hospitals must be prepared to evaluate and treat patients with opioid use disorder (OUD). We implemented a hospitalist-led program, Project Caring for patients with Opioid Misuse through Evidence-based Treatment (COMET) to address gaps in care for hospitalized patients with OUD. OBJECTIVE: Implement evidence-based treatment for inpatients with OUD and refer to postdischarge care. DESIGN, SETTING, AND PARTICIPANTS: Project COMET launched in July 2019 at Duke University Hospital (DUH), an academic medical center in Durham, NC. INTERVENTION, MAIN OUTCOMES, AND MEASURES: We engaged key stakeholders, performed a needs assessment, and secured health system funding. We developed protocols to standardize OUD treatment and employed a social worker to facilitate postdischarge care. Electronic health records were utilized for data analysis. RESULTS: COMET evaluated 512 patients for OUD during their index hospitalization from July 1, 2019 through June 30, 2021. Seventy-one percent of patients received medication for OUD (MOUD) during admission. Of those who received buprenorphine during admission, 64% received a discharge prescription. Of those who received methadone during admission, 83% of eligible patients were connected to a methadone clinic. Among all patients at DUH with OUD, MOUD use during hospitalization and at discharge increased in the post-COMET period compared to the pre-COMET period (p < .001 for both). CONCLUSION: Our program is one of the first to demonstrate successful implementation of a hospitalist-led, comprehensive approach to caring for hospitalized patients with OUD and can serve as an example to other institutions seeking to implement life-saving, evidence-based treatment in this population.

Evaluating fitness-for-use of electronic health records in pragmatic clinical trials: reported practices and recommendations.

OBJECTIVE: To empirically explore how pragmatic clinical trials (PCTs) that used real-world data (RWD) assessed study-specific fitness-for-use. METHODS: We conducted interviews and surveys with PCT teams who used electronic health record (EHR) data to ascertain endpoints. The survey cataloged key concerns about RWD, activities used to assess data fitness-for-use, and related barriers encountered by study teams. Patterns and commonalities across trials were used to develop recommendations for study-specific fitness-for-use assessments. RESULTS: Of 15 invited trial teams, 7 interviews were conducted. Of 31 invited trials, 15 responded to the survey. Most respondents had prior experience using RWD (93%). Major concerns about EHR data were data reliability, missingness or incompleteness of EHR elements, variation in data quality across study sites, and presence of implausible or incorrect values. Although many PCTs conducted fitness-for-use activities (eg, data quality assessments, 11/14, 79%), less than a quarter did so before choosing a data source. Fitness-for-use activities, findings, and resulting study design changes were not often publically documented. Overall costs and personnel costs were barriers to fitness-for-use assessments. DISCUSSION: These results support three recommendations for PCTs that use EHR data for endpoint ascertainment. Trials should detail the rationale and plan for study-specific fitness-for-use activities, conduct study-specific fitness-for-use assessments early in the prestudy phase to inform study design changes before the trial begins, and share results of fitness-for-use assessments and description of relevant challenges and facilitators. CONCLUSION: These recommendations can help researchers and end-users of real-world evidence improve characterization of RWD reliability and relevance in the PCT-specific context.

The use of electronic health records for recruitment in clinical trials: a mixed methods analysis of the Harmony Outcomes Electronic Health Record Ancillary Study.

BACKGROUND: The electronic health record (EHR) contains a wealth of clinical data that may be used to streamline the identification of potential clinical trial participants. However, there is little empirical information on site-level facilitators of and barriers to optimal use of EHR systems with respect to trial recruitment. METHODS: We conducted qualitative focus groups and quantitative surveys as part of the EHR Ancillary Study, which is being conducted alongside the multicenter, global, Harmony Outcomes Trial comparing albiglutide to standard care for the prevention of cardiovascular events in type 2 diabetes. Subject matter experts used findings from focus groups to draft a 20-question survey examining the use of the EHR for participant identification, common site recruitment strategies, and variation in perceived barriers to optimal use of the EHR. The final survey was fielded with 446 site investigators actively enrolling participants in the main trial. RESULTS: Nearly two-thirds of respondents were study coordinators (63.2%), 23.1% were principal investigators, and 13.7% held other research roles. Approximately half of the respondents reported using the EHR to find potential trial participants. Of these, 79.4% reported using EHR searches in conjunction with other recruitment methods, including reviewing of upcoming clinic schedules (75.3%) and contacting past trial participants (71.2%). Important barriers to optimal use of the EHR included the lack of availability of certain research-focused EHR modules and limitations on the ability to contact patients cared for by other providers. Of survey respondents who did not use the EHR to find potential participants, one-quarter reported that the EHR was not accessible in their country; this finding varied from 2.6% of respondents in North America to 50% of respondents in the Asia Pacific. CONCLUSIONS: While EHR screening was commonly used for recruitment in a cardiovascular outcomes trial, important technical, governance, and regulatory barriers persist. Multifaceted, scalable, and customizable strategies are needed to support the optimal use of the EHR for trial participant identification. TRIAL REGISTRATION: ClinicalTrials.gov NCT02465515. Registered on 8 June 2015.

Real-World Data for Planning Eligibility Criteria and Enhancing Recruitment: Recommendations from the Clinical Trials Transformation Initiative.

The growing availability of real-world data (RWD) creates opportunities for new evidence generation and improved efficiency across the research enterprise. To varying degrees, sponsors now regularly use RWD to make data-driven decisions about trial feasibility, based on assessment of eligibility criteria for planned clinical trials. Increasingly, RWD are being used to support targeted, timely, and personalized outreach to potential trial participants that may improve the efficiency and effectiveness of the recruitment process. This paper highlights recommendations and resources, including specific case studies, developed by the Clinical Trials Transformation Initiative (CTTI) for applying RWD to planning eligibility criteria and recruiting for clinical trials. Developed through a multi-stakeholder, consensus- and evidence-driven process, these actionable tools support researchers in (1) determining whether RWD are fit for purpose with respect to study planning and recruitment, (2) engaging cross-functional teams in the use of RWD for study planning and recruitment, and (3) understanding patient and site needs to develop successful and patient-centric approaches to RWD-supported recruitment. Future considerations for the use of RWD are explored, including ensuring full patient understanding of data use and developing global datasets.

Medicaid Coverage Disruptions Among Children Enrolled in North Carolina Medicaid From 2016 to 2018.

Importance: Brief disruptions in insurance coverage among eligible participants are associated with poorer health outcomes for children. Objective: To describe factors associated with coverage disruptions among children enrolled in North Carolina Medicaid from 2016 to 2018 and estimate the outcome of preventing such disruptions on medical expenditures. Design Setting and Participants: This was a retrospective cohort study using North Carolina Medicaid claims data. All enrolled individuals were aged 1 to 20 years on January 1, 2016, and with 30 days of prior continuous enrollment. Children were observed from January 1, 2016, until December 31, 2018. Analyses were conducted from June 2020 through December 2020. Main Outcomes and Measures: Risk of Medicaid coverage disruptions of 1 to less than 12 months was assessed. Among children who disenrolled from Medicaid for 30 or more days, the risk of reenrollment within 1 to 6 months and 7 to 11 months was assessed. An inverse probability of censoring weights method was then used to estimate the outcome of an intervention to reduce coverage disruptions through preventing disenrollment on per member per month (PMPM) cost. Results: The study population included 831 173 Medicaid beneficiaries aged 1 to 5 years (23%), 6 to 17 years (68%), and 18 to 20 years (9%); 35% were Black, 44% were White, and 14% were Hispanic/Latinx. Among those with a first disenrollment (n = 214 401, 26%), the risk of reenrollment within 6 months and 7 to 11 months was 19% and 7%, respectively. Risk of coverage disruption was higher for Black children (hazard ratio [HR], 1.21; 95% CI, 1.18-1.24), children of other races (Asian, American Indian, Hawaiian or Pacific Islander, multiple races, or unreported; HR, 1.37; 95% CI, 1.33-1.40), and Latinx children (HR, 1.65; 95% CI, 1.60-1.70) compared with White children. Risk of coverage disruption was also higher for children with higher medical complexity (HR, 1.15; 95% CI, 1.12-1.19). The risk of coverage disruption was lower for children living in counties with the highest unemployment rates (HR, 0.89; 95% CI, 0.85-0.94), and comparisons between county-level measures of child poverty and graduation rates showed little or no difference. The estimated PMPM cost for the full population under a scenario in which all medical costs were included was $125.73. Estimated PMPM cost for the full cohort in a counterfactual scenario in which disenrollment was prevented was slightly lower ($122.14). Across all subgroups, estimated PMPM costs were modestly lower ($2-$8) in the scenario in which disenrollment was prevented. Conclusions and Relevance: In this cohort study, the risk of Medicaid coverage disruption was high, with many eligible children in historically marginalized communities continuing to experience unstable enrollment. In addition to improving health outcomes, preventing coverage gaps through policies that decrease disenrollment may also reduce Medicaid costs.