Prevalence, adherence, and health care resource utilization in schizophrenia: A national and state-level analysis of US Medicaid Beneficiaries.

Prevalence, adherence, and health care resource utilization in schizophrenia: A national and state-level analysis of US Medicaid Beneficiaries - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice J Manag Care Spec Pharm . 2026 Jun;32(6):691–703. doi: 10.18553/jmcp.2026.32.6.691 Prevalence, adherence, and health care resource utilization in schizophrenia: A national and state-level analysis of US Medicaid Beneficiaries Joseph Parks 1 , Pin Xiang 2 , Ravi Patel 2 , Kaitlyn McBride 3 , Halley Costantino 3 , Sana Mirza 3, ✉ , Kinga Borsos 2 Author information Copyright and License information 1 National Council for Behavioral Wellbeing, Washington, DC 2 Boehringer Ingelheim Pharmaceuticals Inc, Ridgefield, CT 3 BluePath Solutions, Los Angeles, CA ✉ AUTHOR CORRESPONDENCE: Sana Mirza, 1.818.324.5965; smirza@bluepathsolutions.com Copyright © 2026, Academy of Managed Care Pharmacy. All rights reserved. PMC Copyright notice PMCID: PMC13193317  PMID: 42166304 Abstract BACKGROUND: Schizophrenia is a chronic and debilitating mental disorder that imposes substantial health care challenges, particularly among Medicaid beneficiaries. Despite the vulnerability of this population, a comprehensive understanding of national and state-level prevalence, adherence, and health care resource utilization (HCRU) remains limited. OBJECTIVE: To estimate the prevalence of schizophrenia among Medicaid beneficiaries at national and state levels and to characterize their sociodemographic profiles, medication adherence, and HCRU across care settings. METHODS: This retrospective cohort study used the Transformed Medicaid Statistical Information System Analytic Files from 2016 to 2022. Adults aged 18 years and older with at least 2 schizophrenia claims on separate dates were included. National and state-level prevalence analyses were conducted among all Medicaid beneficiaries, including Medicaid-only (beneficiaries enrolled exclusively in Medicaid) and dual-eligible beneficiaries (those enrolled in both Medicaid and Medicare). Descriptive analyses were conducted among Medicaid-only beneficiaries in the most recent study period (2022) to assess sociodemographic characteristics, adherence to antipsychotics (measured using the proportion of days covered [PDC], with adherence defined as PDC≥80%), and HCRU across settings, including inpatient and outpatient services, emergency department visits, and home health. RESULTS: From 2016 to 2022, the national prevalence of schizophrenia among all Medicaid beneficiaries decreased from 2.6% to 1.7%; however, the absolute number of affected individuals increased from 834,920 to 956,023, with California and New York reporting the largest patient populations. In 2022, a total of 143,970 Medicaid-only beneficiaries with schizophrenia were identified. The mean age was 41.9 years, with the largest proportion being male (56.4%) and non-Hispanic White (41.8%). Medication adherence was low, with fewer than 30% of patients with any antipsychotic prescription achieving a PDC greater than or equal to 80%. During the 12-month follow-up period, 44.9% of patients had at least 1 inpatient admission, and 54.6% of those hospitalized had at least 1 mental health–related admission. During the same 12-month period, 68.8% of patients had at least 1 mental health outpatient visit, with a mean of 30.6 visits among those with any mental health outpatient care. CONCLUSIONS: Schizophrenia remains highly prevalent in the Medicaid population at both national and state levels and continues to place substantial demands on the health care system. Low medication adherence and high HCRU among this population highlight ongoing unmet needs. These findings emphasize the need for targeted, system-level strategies to improve access, adherence, and coordinated care for individuals with schizophrenia within Medicaid programs. Plain language summary Schizophrenia remains highly prevalent among Medicaid beneficiaries and continues to impose substantial demands on the health care system. Individuals rely on outpatient mental health services and have frequent emergency department encounters. Expanding access to integrated, community-based services may help improve outcomes and manage system-level demand for care. Continued evaluation of Medicaid mental health services and coordinated care delivery models will be critical to ensure these services are meeting the complex needs of this population. Implications for managed care pharmacy Pharmacy-driven strategies, including proactive medication management, adherence support programs, and improved access to community-based treatment, may help reduce health care resource burden and enhance outcomes for Medicaid beneficiaries living with schizophrenia. Schizophrenia is a debilitating chronic psychiatric condition that impacts individuals’ cognitive and emotional functioning. Globally, schizophrenia affects approximately 1% of the population and ranks among the top 10 causes of disability worldwide 1 . In the United States, schizophrenia affects less than 1% of adults. 2 , 3 Medicaid beneficiaries are disproportionately affected, with prevalence estimates exceeding those observed in the commercially insured and general population. 4 , 5 This elevated prevalence likely reflects the social and health challenges faced by Medicaid populations, who experience higher rates of comorbidities and greater complexity in treatment and disease management. 6 Individuals with schizophrenia also face substantial economic disadvantages: unemployment rates are higher, and they are more likely to have low income, rely on public assistance, and experience housing instability compared with the general population. 7 , 8 Stigma and discrimination related to mental illness and disability can further reinforce these disadvantages by limiting opportunities for employment and housing and by contributing to undertreatment and poorer-quality care within health systems. 9 , 10 The socioeconomic disadvantages faced by individuals with schizophrenia further complicate disease management and access to care. These challenges are linked to treatment adherence, particularly to antipsychotic medication, which is an important determinant of clinical outcomes. Poor medication adherence is associated with worsening symptoms, relapse, and higher health care costs. 11 Patients with schizophrenia also use health care services more frequently than the general population, including hospitalizations, emergency department (ED) visits, outpatient (OP) care, and mental health services. 12 , 13 Prior research has documented substantial variability in utilization and medication adherence among Medicaid populations, influenced by demographic factors, comorbidity profiles, and state-level differences in Medicaid coverage and mental health service availability. 5 , 6 , 14 , 15 However, many studies are limited by narrow geographic coverage and populations, and few have examined both national and state-level patterns across multiple outcomes, including prevalence and mental health service utilization. Since the Medicaid expansion under the Affordable Care Act in 2014, enrollment in the program has grown substantially in many states, improving access to services for previously uninsured populations. For example, prior studies have shown that prescription drug utilization and reimbursement increased significantly after expansion, suggesting improved medication access among newly eligible beneficiaries. 16 , 17 State-level Medicaid programs vary in eligibility criteria, coverage policies, and the availability of mental health services, which can influence utilization patterns among enrollees. Understanding recent, real-world prevalence following Medicaid expansion is important to capture state-level variation and to contextualize the ongoing role of Medicaid in delivering care to this high-need population. Using national Medicaid claims data, this study provides a comprehensive assessment of adults with schizophrenia. Our objectives are to estimate national and state-level schizophrenia prevalence among Medicaid beneficiaries, describe antipsychotic use and adherence, and assess health care resource utilization (HCRU) across care settings, including mental health visits. By characterizing these patterns across the US Medicaid population, this study aims to inform policies and interventions that improve care delivery and outcomes for this vulnerable population. Methods DATA SOURCE AND STUDY DESIGN This retrospective, observational cohort study used the Transformed Medicaid Statistical Information System Analytic Files from 2016 to 2022. The Transformed Medicaid Statistical Information System is a national dataset developed by the Centers for Medicare & Medicaid Services (CMS) that provides comprehensive administrative claims and enrollment data for Medicaid beneficiaries across all US states, including individuals who are dually eligible for both Medicare and Medicaid (commonly referred to as dual eligibles), as well as those covered solely by Medicaid (hereinafter “Medicaid-only”). The data capture beneficiaries in both fee-for-service and managed care programs. Inpatient (IP), other services, and pharmacy claims were used to assess comorbidities, HCRU, medication use, and adherence. Nonprevalence analyses were restricted to Medicaid-only beneficiaries to maximize completeness of outcome capture and minimize underestimation of comorbidities, HCRU, and medication use/adherence. Claims for dual-eligible beneficiaries were not fully represented because a substantial portion of their care is covered by Medicare, particularly Medicare Advantage, and were missing/incomplete at the time of analysis. ELIGIBILITY CRITERIA For national and state-level prevalence, adult Medicaid beneficiaries aged 18 years and older were eligible if they had at least 2 medical claims for schizophrenia ( International Classification of Diseases, Tenth Revision, Clinical Modification F20.xx, F21, or F25.x) on separate dates in calendar year 2022 and continuous enrollment for the full calendar year; beneficiaries with missing age or residence data were excluded. Prevalence estimates included Medicaid-only and dual-eligible beneficiaries; the denominator comprised all adult Medicaid beneficiaries with continuous enrollment in 2022. For all other outcomes (sociodemographic/clinical characteristics, medication adherence, and HCRU), a Medicaid-only cohort was defined using at least 2 schizophrenia claims on separate dates, with the most recent claim in 2021 serving as the index date. Patients were required to have 12 months of continuous Medicaid-only enrollment before and after the index date; dual-eligible beneficiaries were excluded (see Supplementary Figure 1 (608.8KB, pdf) , available in online article, for a detailed patient attrition table). OUTCOMES: PREVALENCE, SOCIODEMOGRAPHIC CHARACTERISTICS, MEDICATION ADHERENCE, AND HCRU Annual estimates from 2016 to 2022 were calculated to examine trends in schizophrenia prevalence among all Medicaid beneficiaries, and state-specific counts for 2022 were analyzed to assess geographic variation. Within the Medicaid-only cohort, descriptive analyses included sociodemographic characteristics, geographic factors (region; urban/rural residence), and comorbidity profiles (Charlson Comorbidity Index [CCI]). Behavioral health comorbidities evaluated included bipolar disorder, depression, anxiety disorder, attention-deficit/hyperactivity disorder, substance use disorder, alcohol use disorder, suicidal ideation, borderline personality disorder, and posttraumatic stress disorder. Prescription claim counts reflect the number of all-cause pharmacy claims observed during the follow-up period and were not standardized by days supply or dispensing interval. Medication adherence was evaluated using the proportion of days covered (PDC) for commonly prescribed oral and long-acting injectable antipsychotic medications over the 12-month follow-up period. PDC is the number of days supply for all relevant prescriptions, divided by the number of days in the 12-month follow-up period. PDC considers the timing of all prescriptions, so if a patient refills the prescription prior to using the last supply of medication, the timing of the new prescription is shifted to begin once the last dispensed quality has been used. Patients with PDC greater than or equal to 80% were classified as adherent, consistent with thresholds commonly used in prior studies. 18 , 19 Only pharmacy claims with a recorded days supply were included in the adherence calculations, consistent with prior studies. 20 , 21 Medical claims for clinician-administered drugs (eg, J-codes) generally do not include days supply and therefore cannot be used to calculate PDC without imputing coverage intervals and dosing assumptions. To avoid introducing untestable assumptions into adherence measurement, we limited PDC to pharmacy claims with recorded days supply. As a result, this approach may not capture antipsychotics administered in physician offices or hospital settings and may underestimate total antipsychotic use, particularly for long-acting injectables. Accordingly, PDC results reflect adherence among beneficiaries who filled at least 1 antipsychotic prescription during the 12-month follow-up period. HCRU was assessed across inpatient admissions, ED visits, outpatient visits, and home health services. Mental health–related IP admissions were identified using setting-of-care indicators (eg, behavioral health facility type and/or revenue codes) to characterize utilization within behavioral health care settings. ED visits captured any emergency encounter (all-cause), including low-complexity visits. Selected measures (inpatient admissions, ED visits, outpatient visits) were also examined at the state level. DATA SOURCES AND MANAGEMENT All data were accessed through the CMS Virtual Research Data Center under strict compliance with HIPAA and Federal Information Security Management Act standards. 22 Raw data were cleaned and processed using SAS version 9.4. Variables with excessive missingness were excluded using standard rules when appropriate. Data quality checks were implemented to ensure reliability prior to analysis. All results were reported in accordance with the CMS cell size suppression policy, which prohibits reporting or derivation of any cell sizes between 1 and 10 to protect beneficiary confidentiality. 22 STATISTICAL ANALYSIS Prevalence was estimated as the proportion of beneficiaries meeting schizophrenia criteria relative to all adult Medicaid beneficiaries with continuous enrollment in the year of interest. Descriptive statistics summarized characteristics, medication use/adherence, and HCRU among Medicaid-only beneficiaries. State-level stratifications were performed across all 50 states and the District of Columbia. Results ANNUAL PREVALENCE Between 2016 and 2022, the average annual prevalence of schizophrenia among all Medicaid enrollees (including both Medicaid-only and dual-eligible beneficiaries) was 2.3%. The at-risk Medicaid population grew substantially over this period, increasing from 34.6 million beneficiaries in 2016 to 55.7 million in 2022, a 61% increase. The number of Medicaid beneficiaries with schizophrenia increased more modestly, from 834,920 in 2018 to 956,023 in 2022, representing a 14.5% increase. Prevalence declined steadily over time, from 2.6% in 2016 to 1.7% in 2022, reflecting the expansion of the at-risk Medicaid population (Table 1). TABLE 1. Annual Prevalence of Schizophrenia by Year (2016-2022) Stratification 2016 2017 2018 2019 2020 2021 2022 At-risk population, N a 34,569,777 35,208,719 35,310,411 34,887,980 41,229,412 50,079,457 55,707,045 Schizophrenia population, n b 891,285 915,696 834,920 868,201 907,523 943,713 956,023 Prevalence, % c 2.6 2.6 2.4 2.5 2.2 1.9 1.7 Open in a new tab Data derived from the Transformed Medicaid Statistical Information System Analytic Files (2022). a The at-risk population refers to the total number of adults aged 18 years and older at risk of developing schizophrenia and with continuous enrollment in Medicaid within the specified year. b The schizophrenia count includes 2 or more claims with a diagnosis of schizophrenia (International Classification of Diseases, Tenth Revision, Clinical Modification: F20.xx, F21, F25.x), on different days, and continuous enrollment in Medicaid during each year of interest. c Prevalence calculated as number of schizophrenia cases (n) divided by the at-risk population (N), multiplied by 100. In 2022, the schizophrenia prevalence in state Medicaid across the United States ranged from 1.1% to 3.6%, with the majority of states (n = 36) reporting estimates between 1.2% and 2.0%, including those with large Medicaid population such as California (1.5%) and New York (1.7%). The highest prevalence was observed in Missouri (3.6%), the District of Columbia (3.2%), Kansas (2.9%), and Minnesota (2.7%), whereas lower prevalence was seen in Iowa (2.3%), Ohio (2.4%), and Nebraska (2.5%). In terms of absolute numbers of Medicaid enrollees with schizophrenia, the largest burdens were concentrated in California (130,182), New York (85,047), and Ohio (48,893) and the lowest in Wyoming (656), South Dakota (1,369) and Vermont (1,435) ( Table 2 ). TABLE 2. Annual Prevalence of Schizophrenia by State (2022) Stratification 2022 State At-risk, N a Schizophrenia, n b Prevalence, % c Alabama 629,409 11,691 1.9 Alaska 157,200 2,102 1.3 Arizona 1,467,008 27,211 1.9 Arkansas 623,876 8,660 1.4 California 8,602,555 130,182 1.5 Colorado 971,057 11,242 1.2 Connecticut 790,514 14,619 1.8 Delaware 182,294 2,548 1.4 District of Columbia 202,193 6,455 3.2 Florida 2,829,932 37,346 1.3 Georgia 1,126,712 22,061 2.0 Hawaii 280,260 4,530 1.6 Idaho 236,557 4,688 2.0 Illinois 2,104,597 41,425 2.0 Indiana 1,206,649 18,609 1.5 Iowa 456,926 10,411 2.3 Kansas 193,679 5,593 2.9 Kentucky 1,081,739 12,435 1.1 Louisiana 1,189,916 21,878 1.8 Maine 297,346 4,932 1.7 Maryland 1,013,259 19,323 1.9 Massachusetts 1,474,825 27,215 1.8 Michigan 1,928,637 38,185 2.0 Minnesota 758,954 20,170 2.7 Mississippi 410,703 7,143 1.7 Missouri 668,076 23,943 3.6 Montana 184,797 2,738 1.5 Nebraska 173,682 4,285 2.5 Nevada 485,546 9,005 1.9 New Hampshire 157,760 2,651 1.7 New Jersey 1,230,423 26,518 2.2 New Mexico 611,475 6,488 1.1 New York 4,997,861 85,047 1.7 North Carolina 1,463,438 25,997 1.8 North Dakota 66,561 1,453 2.2 Ohio 2,047,738 48,893 2.4 Oklahoma 555,448 10,910 2.0 Oregon 884,414 10,910 1.2 Pennsylvania 2,082,256 36,925 1.8 Puerto Rico 1,182,946 4,407 0.4 Rhode Island 241,452 3,855 1.6 South Carolina 801,908 9,674 1.2 South Dakota 58,358 1,369 2.3 Tennessee 916,426 15,520 1.7 Texas 2,526,856 44,620 1.8 U.S. Virgin Islands 22,704 182 0.8 Utah 244,518 5,683 2.3 Vermont 119,340 1,435 1.2 Virginia 1,185,261 23,161 2.0 Washington 1,246,842 18,205 1.5 West Virginia 416,275 5,296 1.3 Wisconsin 883,884 15,543 1.8 Wyoming 33,990 656 1.9 Open in a new tab Data derived from the Transformed Medicaid Statistical Information System Analytic Files (2022). a The at-risk population refers to the total number of adults aged 18 years and older. b The schizophrenia count includes 2 or more claims with a diagnosis of schizophrenia (International Classification of Diseases, Tenth Revision, Clinical Modification: F20.xx, F21, F25.x), on different days, and continuous enrollment in Medicaid during each year of interest. c Prevalence calculated as number of schizophrenia cases (n) divided by the at-risk population (N), multiplied by 100. PATIENT DEMOGRAPHIC AND CLINICAL CHARACTERISTICS In 2022, 143,970 Medicaid-only beneficiaries with schizophrenia were identified. The mean age among patients was 41.9 years, with 39% aged 18 to 34 years. Male patients made up 56.4% of the cohort. By race and ethnicity, 41.8% identified as non-Hispanic White, 26.1% as non-Hispanic Black, and 14.5% as Hispanic (all races). Most beneficiaries (85.6%) resided in metropolitan areas, and the largest share lived in the South (30.6%) ( Table 3 ). TABLE 3. Patient Demographic Characteristics Characteristic Medicaid-only beneficiaries (n = 143,970) Age Mean (SD) 41.9 (16.0) Median (minimum-maximum) 39 (18-107) Age group, n (%) 18-24 21,235 (14.7) 25-34 35,525 (24.7) 35-44 29,295 (20.3) 45-54 22,877 (15.9) 55-64 21,948 (15.2) 65+ 13,090 (9.1) Sex, n (%) Female 62,828 (43.6) Male 81,142 (56.4) Race and ethnicity, n (%) White, non-Hispanic 60,187 (41.8) Black, non-Hispanic 37,522 (26.1) Asian, non-Hispanic 3,223 (2.2) American Indian and Alaska Native, non-Hispanic 2,154 (1.5) Hawaiian/Pacific Islander 723 (0.5) Multiracial, non-Hispanic 765 (0.5) Hispanic, all races 20,862 (14.5) Other, non-Hispanic 750 (0.5) Unknown 17,784 (12.4) Rural-urban continuum Metropolitan 123,193 (85.6) Nonmetropolitan 19,861 (13.8) Unknown 916 (0.6) Region of residence, n (%) Northeast 26,703 (18.5) Midwest 32,075 (22.3) South 44,009 (30.6) West 39,633 (27.5) US territories 1,550 (1.1) Primary language spoken at home, n (%) English 112,542 (78.2) Spanish 5,605 (3.9) Other 1,223 (0.8) Unknown 24,600 (17.1) US citizenship, n (%) US citizen 125,751 (87.3) Non-citizen 3,547 (2.5) Unknown 14,672 (10.2) Enrollment plan, n (%) Any managed care 118,608 (82.4) Exclusively fee-for-service 25,362 (17.6) Behavioral health–related comorbidity, n (%) Yes 545 (0.4) No 143,425 (99.6) Charlson Comorbidity Index Mean (SD) 0.5 (0.9) Median (minimum-maximum) 0 (0-8) Charlson Comorbidity Index, n (%) 0 97,950 (68.0) 1 23,779 (16.5) 2 14,863 (10.3) 3 5,154 (3.6) ≥4 2,224 (1.5) Open in a new tab MEDICATION USE ADHERENCE Among the Medicaid-only cohort, 66,497 beneficiaries (46.2%) had at least 1 pharmacy claim for an antipsychotic medication. The mean PDC among therapy users was 50.4%, and 29.3% achieved a PDC greater than or equal to 80%. A total of 17.4% of patients demonstrated very low adherence, with PDC values under 10% ( Table 4 ). TABLE 4. Medication Adherence Resource 12-Month adherence to prescription antipsychotics Medicaid-only cohort (n = 143,970) N Mean Median % SD (min-max) PDC 66,497 (46.2%) PDC (%) Mean (SD) 50.4 (34.2) Median (min-max) 47.8 (2.0-100.0) PDC≥80%, n (%) Yes 19,472 (29.3) No 47,025 (70.7) PDC, n (%) 0% to <10% 11,598 (17.4) 10% to <20% 7,560 (11.4) 20% to <30% 5,691 (8.6) 30% to <40% 4,903 (7.4) 40% to <50% 4,812 (7.2) 50% to <60% 3,902 (5.9) 60% to <70% 4,219 (6.3) 70% to <80% 4,340 (6.5) 80% to <90% 5,818 (8.7) 90% to <100% 9,096 (13.7) 100% 4,558 (6.9) Open in a new tab PDC = proportion of days covered. HEALTH CARE RESOURCE UTILIZATION Health care resource use, including both acute care and mental health services, was extensive across IP and OP settings among the Medicaid-only cohort during the 12-month post-index follow-up period. ED services were used by 91.6% of beneficiaries; among those with any ED visit, the mean number of visits was 9.0. Among beneficiaries with at least 1 IP admission, the mean number of admissions was 3.8 and the mean total length of stay was 20.2 days. Mental health–related IP utilization was also high: 24.6% of all beneficiaries had at least 1 mental health–related admission, and among those with any mental health–related admission, the mean number of admissions was 5.1 with a mean length of stay of 5.2 days per admission. Nearly all beneficiaries (95.8%) had at least 1 OP visit; among those with any OP care, the mean number of visits was 38.2. Mental health OP service use was substantial, with 68.8% of beneficiaries having at least 1 mental health OP visit and a mean of 30.6 visits among those with any mental health OP care. Prescription medication use was also high: 80.0% of beneficiaries had at least 1 prescription claim for any medication (antipsychotic or nonantipsychotic), and among those with at least 1 claim, the mean number of prescription claims was 42.1 during follow-up. Home health services were used by 34.7% of beneficiaries; among those with any home health use, the mean number of services was 65.5 ( Table 5 ). TABLE 5. Health Care Resource Utilization Use (Index Year = 2021) Resource 12-Month resource use Medicaid-only cohort (n = 143,970) N Mean (SD) % Median (min-max) Inpatient admission Any inpatient admission 64,713 44.9% Number of inpatient admissions, among all patients 1.7 (5.0) 0 (0-107) Number of inpatient admissions, among patients with ≥1 3.8 (6.9) 2 (1-107) Average length of stay (days), among patients with ≥1 8.1 (16.0) 5.0 (1.0-366.0) Total length of stay (days), among patients with ≥1 20.2 (31.7) 10 (1-366) MH inpatient admissions Any MH inpatient admission 35,373 24.6% Number of MH inpatient admissions, among all patients 1.4 (5.0) 0 (0-107) Number of MH inpatient admissions, among patients with ≥1 5.1 (8.9) 2 (1-106) Average length of stay (days), among patients with ≥1 5.2 (13.0) 2.3 (1.0-366.0) Total length of stay (days), among patients with ≥1 15.6 (29.0) 7 (1-366) Non-MH inpatient admissions Any non-MH inpatient admission 47,249 32.8% Number of non-MH inpatient admissions, among all patients 1.0 (3.5) 0 (0-107) Number of non-MH inpatient admissions, among patients with ≥1 1.9 (1.7) 1 (1-38) Average length of stay (days), among patients with ≥1 9.6 (15.8) 6.4 (1.0-366.0) Total length of stay (days), among patients with ≥1 17.4 (26.0) 9 (1-366) Emergency department visit Any emergency department visit 131,816 91.6% Number of emergency department visits, among all patients 8.2 (8.0) 6 (0-139) Number of emergency department visits, among patients with ≥1 9.0 (8.0) 7 (1-139) Home health service Any home health service 49,981 34.7% Number of home health services, among all patients 22.8 (72.5) 0 (0-366) Number of home health services, among patients with ≥1 65.5 (111.1) 10 (1-366) Outpatient visits Any outpatient visit 137,975 95.8% Number of outpatient visits, among all patients 36.6 (59.1) 16 (0-366) Number of outpatient visits, among patients with ≥1 38.2 (59.8) 17 (1-366) MH outpatient visits Any MH outpatient visit 98,993 68.8% Number of MH outpatient visits, among all patients 21.0 (49.6) 4 (0-366) Number of MH outpatient visits, among patients with ≥1 30.6 (57.3) 10 (1-366) Non-MH outpatient visits Any non-MH outpatient visit 125,243 87.0% Number of non-MH outpatient visits, among all patients 16.3 (35.5) 6 (0-366) Number of non-MH outpatient visits, among patients with ≥1 18.7 (37.4) 8 (1-366) Prescription claims Any prescription claim 115,158 80.0% Number of prescription claims, among all patients 33.7 (46.1) 16 (0-915) Number of prescription claims, among patients with ≥1 42.1 (48.0) 26 (1-915) Open in a new tab MH = mental health. STATE-LEVEL OUTCOMES: MEDICATION ADHERENCE AND HCRU State-level adherence (defined as PDC≥80) among Medicaid-only beneficiaries varied widely, ranging from 18.1% in the District of Columbia and 18.8% in North Carolina to 56.2% in Vermont. Several states reported adherence above 40%, including Utah (43.8%), Rhode Island (43.4%), and Oregon (40.7%), whereas many others clustered near the national average of 29.3%, such as California (25.6%), New York (33.4%), and Texas (28.3%). Similarly, health service utilization among this population varied across states and by care setting. ED use differed across states, with a national mean of 8.2 visits per patient and state-level averages ranging from 5.2 in Florida and 5.7 in the District of Columbia to more than 11 visits in Kentucky (11.3) and West Virginia (11.7). Across most states (more than 80%), mental health–related OP visit rates ranged from 32% to 81%, indicating substantial variability. In contrast, mental health–related IP hospitalization rates were more concentrated, with most states reporting rates between 10% and 30%. Full state-level outcomes are provided in Supplementary Tables 2-5 (608.8KB, pdf) . Discussion This study highlights the substantial burden of schizophrenia among Medicaid beneficiaries, a population disproportionately affected by socioeconomic disadvantage, unstable housing, food insecurity, and limited mental health care coverage. 23 These factors complicate disease management and contribute to poorer outcomes and higher health care utilization. The average annual prevalence of schizophrenia observed here aligns with prior estimates of 1% to 3% in similar populations. 4 , 5 Although prevalence declined from 2.6% in 2016 to 1.7% in 2022, the absolute number of individuals with schizophrenia increased, likely reflecting enrollment growth following Medicaid expansion, 24 and continuous enrollment policies under the Families First Coronavirus Response Act during the COVID-19 public health emergency, which may have contributed to the lower observed prevalence estimates in recent years. In 2022, state-level prevalence varied from 1.1% to 3.6%, with most states reporting rates between 1.2% and 2.0%, suggesting generally similar prevalence nationwide. The largest numbers of individuals with schizophrenia were observed in states with the highest overall Medicaid enrollment, including California, New York, and Texas. These patterns align with prior literature indicating that states with larger Medicaid programs tend to report higher numbers of beneficiaries with serious mental illness. 25 The demographic characteristics of our study population are in line with prior studies of individuals with schizophrenia. 5 , 21 , 26 , 27 However, our analyses captured relatively few behavioral health and clinical comorbidities, which may reflect under-capture related to coding practices and fewer diagnosis code positions in Medicaid claims, potentially reducing documentation of secondary conditions when schizophrenia is the primary diagnosis. As a result, behavioral health comorbidities in particular may be underestimated. Previous research has similarly reported low CCI scores among individuals with schizophrenia. 27 Medication adherence was low, with fewer than 30% achieving a PDC greater than or equal to 80%, consistent with recent real-world studies showing suboptimal adherence and frequent discontinuation of oral antipsychotics among adults with schizophrenia. 28 These low adherence rates may reflect a combination of system-level barriers, such as restrictive formularies, fragmented care, and a shortage of mental health providers, as well as individual-level challenges, including cognitive difficulties. 29 , 30 Recent US estimates also suggest persistent gaps in treatment engagement, with approximately 30% of adults with schizophrenia spectrum disorders receiving no mental health treatment in the prior year and only about one-quarter receiving minimally adequate treatment. 31 Additionally, nearly half of the US population lives in areas defined as mental health professional shortage areas, resulting in limited access to care. 32 Nonadherence and nonpersistence are associated with poorer outcomes, including relapse and higher acute-care utilization (eg, ED visits and hospitalizations), 33 – 35 making adherence improvement a central focus that will likely require both system-level reforms and patient-centered interventions. Study findings also highlight the substantial HCRU among Medicaid beneficiaries with schizophrenia and the complexity of managing this high-need population. The burden on both individuals and the Medicaid system is considerable, with more than 90% of patients experiencing at least 1 ED visit over the 12-month period, a pattern observed across many states. This rate is significantly higher than prior estimates of 20% to 30%, 26 , 36 likely owing to the inclusion of all ED encounters in our claims data, including visits not directly related to schizophrenia and low-complexity encounters. Consistent with this approach, the ED measure reflects all-cause utilization and does not distinguish encounters driven by mental health crises vs other medical presentations or potentially preventable visits related to limited access to primary care. Additionally, the focus on Medicaid enrollees, who often have greater medical and social complexity, may contribute to the higher observed rate compared with analyses among commercial populations. 24 , 32 Additionally, nearly half of patients in our study experienced IP hospitalization, rates that far exceed those in the general population. 13 , 37 These patterns may reflect poor access to primary care and routine health care services, further contributing to high acute service utilization. Rates of mental health service use were also high among our study population. Among patients with at least 1 IP admission (44.9%), more than half (54.6%) had a mental health–related admission, representing 24.6% of all patients. OP use was also substantial, with 68.8% of patients having at least 1 mental health OP visit, averaging 30.6 visits during follow-up. Similar to our reporting of ED encounters, the claims data in this analysis capture all OP encounters and acute events, including visits unrelated to schizophrenia, which may contribute to the high counts observed. These high levels of both mental health and non–mental health utilization contrast with the relatively low prevalence of comorbidities we reported for this population. This discrepancy may reflect both the underreporting of comorbid conditions in claims data and the frequent use of health care services for management of schizophrenia-related complications and acute events even in the absence of comorbid diagnoses. Care beyond OP and IP settings also played an important role, with nearly 35% of patients receiving home health services, which offer assistance with daily activities, medication management, and nursing care. Broadening access to these services could improve treatment adherence and potentially reduce the need for IP and emergency care. State-level analyses revealed substantial variation in HCRU, particularly for mental health services, with less variation observed for ED and IP utilization. The high level of variation for mental health service use across states was not surprising, as state-level differences in Medicaid program design, coverage of mental health services, care coordination models, and funding streams, including Medicaid expansion decisions and reimbursement rates, are known to contribute to variability in access and service utilization. 38 Importantly, these state-level comparisons are descriptive and were not adjusted for differences in state Medicaid policy and program design (eg, formularies and utilization management, managed care arrangements, and Medicaid expansion decisions). Observed variation may reflect both differences in patient case-mix and system-level administrative barriers, and future work should examine the extent to which state policy features explain the disparities observed. OP visits were universal nationally, with 95.6% of individuals having at least 1 visit. In contrast, regular mental health–related OP use varied widely across the majority of states, ranging from 32.3% in Pennsylvania to 81.1% in Massachusetts and New Hampshire. These differences may reflect variation in access to OP mental health services across states. Although our descriptive analyses do not establish whether lower OP use leads to greater reliance on IP or other high-intensity care, prior work suggests that timely OP follow-up after psychiatric hospitalization is associated with a lower risk of readmission among adults with schizophrenia or bipolar disorder. 39 Additionally, evaluations of integrated primary and mental health care delivered in community mental health settings have reported reductions in ED use and IP utilization, supporting the potential value of proactive, integrated models for reducing reliance on acute care. 40 Future research should examine the extent to which differences in Medicaid program design, provider capacity, and care models explain the observed state-level variation. Addressing these multifaceted challenges will require targeted interventions. Community-based care models, such as integrated specialty care, can improve continuity, reduce hospitalizations, and enhance patient engagement. 41 Expanding care coordination, reducing medication access barriers, and increasing access to psychosocial interventions, including cognitive behavioral therapy, supported employment, and housing support, are also critical for promoting adherence, recovery, and quality of life. 20 , 42 Evidence-based digital options, including prescription digital therapeutics, may serve as scalable aides to improve access and engagement and help reduce acute-care use and costs. They have demonstrated benefits across conditions, for opioid use disorder, 43 , 44 chronic insomnia, 45 depression/anxiety, 46 and serious mental illness where blended and mobile interventions show small to moderate improvements and good feasibility. 47 , 48 Integrated care models that bridge behavioral and primary care are especially important given the high burden of comorbid physical conditions and premature mortality in this population. 1 , 49 Limitations This study provides one of the most comprehensive assessments of schizophrenia-related burden among Medicaid beneficiaries, leveraging a large, nationally representative claims dataset covering all 50 states and the District of Columbia. The inclusion of state-level analyses offers valuable insight into regional variation and disparities in service utilization and adherence outcomes. Prior studies have examined Medicaid populations in only a limited number of states, which may not fully capture the national landscape of schizophrenia care. 5 , 13 , 20 Despite these strengths, the study has several important limitations. First, as with all claims-based studies, the data may not capture health care services delivered outside of the claims system. Additionally, HCRU and prescription utilization measures were assessed on an all-cause basis rather than restricted to schizophrenia-related claims, so they may reflect care for comorbid behavioral health and chronic medical conditions in addition to schizophrenia. We intentionally assessed HCRU and prescription utilization on an all-cause basis to reflect the total health care burden experienced by Medicaid beneficiaries with schizophrenia, recognizing that comorbid medical and behavioral conditions substantially contribute to overall system use. Mental health–related IP admissions were classified using setting-of-care indicators; therefore, this measure reflects utilization within behavioral health care settings and may include some medical encounters occurring in those settings. Higher prescription claim counts may reflect shorter dispensing intervals (eg, weekly dispensing) and/or frequent refills of the same medication rather than a larger number of distinct medications. Second, medication utilization was assessed using pharmacy fill data, which may not capture antipsychotics administered in physician offices or hospital settings. As a result, total antipsychotic use, particularly for long-acting injectables, may be underestimated. Third, we required 12 months of continuous Medicaid enrollment to support complete patient-level capture of HCRU and to avoid bias from partial enrollment periods that may not reflect a full year of observable utilization. However, this convention may preferentially include beneficiaries with more stable coverage and potentially lower social risk, thereby underrepresenting transient or homeless individuals. Further, claims data lack psychosocial determinants and patient-reported outcomes, which may underestimate the overall clinical and functional burden of schizophrenia. Finally, patient characteristics, adherence, and HCRU may not be generalizable to dual-eligible individuals, who represent a significant portion of adults with schizophrenia in the United States and have been shown to exhibit higher utilization across both Medicaid and Medicare programs. Because Medicare Advantage claims were not comprehensively available at the time of analysis, we restricted these outcomes to the Medicaid-only cohort to maximize completeness of outcome capture. This restriction may limit generalizability and likely yields conservative estimates of antipsychotic use and HCRU by excluding a clinically complex, higher-need subgroup. Additionally, all descriptive analyses required 12 months of continuous Medicaid enrollment before and after the index date. Because Medicaid eligibility can change as a result of state policies or administrative factors, this requirement may have introduced selection bias, particularly from 2016 to March 2020, by favoring beneficiaries with more stable health care coverage. However, this concern is lessened for patients observed after March 2020, as continuous enrollment policies were implemented under the Families First Coronavirus Response Act, which remained in effect through the end of the study period. Despite these limitations, the breadth and detail of this dataset allowed for a robust, real-world assessment, presenting recent estimates of the prevalence and burden of schizophrenia among Medicaid enrollees at both national and state levels. National initiatives, such as the CMS Rural Health Transformation Program, which is investing $50 billion over 5 years to enhance rural health care delivery, are fostering innovative approaches to reduce disparities and strengthen mental health infrastructure. Moving forward, policy and clinical interventions must target both medical and social determinants of health to meaningfully improve outcomes for Medicaid beneficiaries with schizophrenia. Conclusions Schizophrenia places a disproportionate burden on Medicaid enrollees, evidenced by the high prevalence at both national and state levels, as well as the frequent use of mental health services, IP hospital, and ED visits. These findings highlight the need for national and state-level interventions that address both service delivery gaps and broader social determinants of health. Expanding access to community-based services and supporting broader treatment options could help improve outcomes and reduce system demand and disparities in this vulnerable population. Future research should explore the impact of Medicaid mental health services and expansion on clinical outcomes and its potential to reduce the health care burden among patients with schizophrenia. Disclosures Kinga Borsos, Pin Xiang, and Ravi Patel were employed by the study sponsor. Sana Mirza, Halley Costantino, and Kaitlyn McBride were employees of BluePath Solutions LLC., which received funding from Boehringer Ingelheim Pharmaceuticals, Inc., to conduct the analyses for the study at the time of this study. This study was funded by Boehringer Ingelheim Pharmaceuticals, Inc. (Ridgefield, CT). 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