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. 2025 Sep 11;17:100379. doi: 10.1016/j.dadr.2025.100379

Identifying Opioid Treatment Programs in Medicaid claims data to support quality improvement

Barrett Wallace Montgomery 1, Tami L Mark 1,⁎, William Dowd 1, Chelsea Katz 1, Dylan DeLisle 1, Thanh Lu 1, Minglu Sun 1, Gary A Zarkin 1
PMCID: PMC12481129  PMID: 41035433

Abstract

In the United States, opioid treatment programs (OTPS) are the only provider type licensed to dispense methadone. Recently, U.S. regulators revised OTPs regulations with the aim of making OTP treatment more patient-centered and improving retention in treatment. Creating OTPs retention measures across all OTPs in the U.S. would give OTPs an important window into their retention rates relative to benchmarks and help identify which policies and procedures are most effective in improving retention. In the United States, insurance claims data are one of the few data sources available to create these metrics. Claims data include national provider identifiers; however, the Federal agency that regulates OTPs does not make public which national provider identifiers are associated with OTPs. This study investigated whether other variables captured in Medicaid claims could be used to identify OTPs. We identified two variables: methadone dispensing procedure codes and methadone clinic taxonomy codes, which identified 80 % and 66.8 % of the count of Medicaid-participating OTPs.Place of service and bill type codes were recently added to claims data and may be useful in the future. Methadone can reduce overdose deaths by 50 % but only if patients are maintained on methadone long enough. OTP metrics created with insurance claims data would facilitate efforts to improve retention and outcomes. This study identifies a practical way to identify OTPs in claims data to support such measures in the absence of a Federal list of OTPs and their national provider identifiers.

Keywords: Opioid Treatment Programs, Opioid Use Disorder, Medicaid Claims Data, Healthcare Quality Metrics, Methadone Treatment

Highlights

  • •

    First evaluation of methods to identify opioid treatment programs in Medicaid.

  • •

    Methadone-related procedure codes were the strongest identification method.

  • •

    Including provider NPIs from SAMHSA lists would improve Medicaid program tracking.

1. Introduction

There is an urgent need to improve the quality of treatment in opioid treatment programs (OTPs). Methadone, which can only be dispensed through OTPs, has been shown to reduce opioid overdoses and deaths by 50 % (Ma et al., 2019, Santo et al., 2021). In 2023, 2 % (or 5.7 million people) of the US population had an opioid use disorder (OUD), and 18 % (or 1.0 million people) received medications in the past year for their opioid use (Substance Abuse and Mental Health Services Administration, 2024). However, large portions of individuals leave methadone treatment prematurely before gaining this benefit (Soyka et al., 2008, Timko et al., 2016). Unlike other areas of healthcare, there are no metrics to help OTPs know how well they are doing in retaining patients on methadone or on other opioid medications (e.g., buprenorphine or naltrexone). Creating such metrics could help motivate OTPs to implement quality improvement strategies and help determine the most effective practices. Beyond individual quality measurement, reliable methods to identify OTPs in claims data would provide critical infrastructure for health services research, enabling consistent identification across studies and supporting policy decisions on resource allocation and treatment access. Such standardized identification could also inform value-based payment models and help identify high-performing programs whose practices could be disseminated more broadly.

Medicaid and Medicare insurance claims are two of the most common data sources used to develop provider-level quality metrics in the United States (Dowd et al., 2022, Jencks et al., 2000, Zhou et al., 2020). Claims-based data provide information on healthcare utilization and outcomes across care settings and time for millions of individuals. Medicaid claims are particularly relevant for OTPs: of the 2152 OTPs listed by the Substance Abuse and Mental Health Services Administration (SAMHSA) as of June 2022, 85 % of OTPs accept Medicaid (Substance Abuse and Mental Health Services Administration, 2023); 81 % of OTP patients in California in 2022 reported Medicaid as their primary payer (Department of Health Care Services and State of California, nd) and BayMark Health, which owns 120 OTPs across 23 states, reports that approximately 75 % of their patients are Medicaid beneficiaries (Van Dyke, 2025). The Centers for Medicare and Medicaid Services (CMS) collates Medicaid claims from all US states (including D.C.) into standard formats in a data set called the Transformed Medicaid Statistical Information System Analytic Files (TAF). Most variables in the TAF data are high quality (Centers for Medicare & Medicaid Services (CMS), 2024).

The federal government and states use Medicaid claims to create state-level Medicaid program substance use disorder quality metrics such as the percentage of Medicaid beneficiaries with an OUD initiating addiction treatment and the percentage of Medicaid beneficiaries with an OUD obtaining OUD medications (Kaye and Wilkniss, 2023, Medicaid & CHIP Health Care Quality Measures, 2024). These state-level quality indicators provide a birds-eye view of OUD treatment quality. Variation in quality metrics among states may highlight potential policies that can improve access and quality, such as Medicaid expansion and Medicaid reimbursement rates (Crable et al., 2022). However, state-level quality metrics are not useful guideposts for individual providers that want to track their own improvement. OUD providers have levers to improve the quality of OUD treatment that are not available to states, such as ensuring rapid access to treatment, adequate methadone dosing, and a welcoming treatment environment. To date, we know of no federal or state efforts to create quality measures at the individual OTP level.

In the United States, OTPs can dispense methadone only after they are certified by SAMHSA. SAMHSA maintains an inventory of every certified OTP in the country (the “gold standard” list of OTPs). Ideally, every OTP on the SAMHSA list would report their organizational National Provider Identifier (NPI) to provide a common identifier in the SAMHSA OTP list and the Medicaid claims data that could be used to identify OTPs in Medicaid claims. However, only 42 % of OTPs report their NPI to SAMHSA because this field is optional, and this information is not made publicly available without a Freedom of Information Act (FOIA) request (SAMHSA, nd).

To identify OTPs in the 2022 Medicaid and Medicare claims data, the Department of Health and Human Services Office of the Inspector General (OIG) matched data elements in the National Plan and Provider Enumeration System (NPPES) to corresponding elements in SAMHSA’s OTP list (Maxwell, 2024). Using a multi-step process, the OIG matched on a combination of geographic coordinates, phone number, and organization name (including algorithms for fuzzy matching) (Schoggen, 2024). For OTPs that they were unable to match, they conducted a manual review to attempt to determine the NPI (Schoggen, 2024). Ultimately, the OIG was able to identify NPIs for 87 % of the OTPs in the list, or 1732 out of the total 1995 in SAMHSA’s OTP directory as of January 12, 2023 (Maxwell, 2024).

The OIG employed complex algorithms and judgement calls (e.g., “manual review”) to link OTPs on SAMHSA’s OTP list to NPIs, a process that will be hard to replicate consistently (Schoggen, 2024). This study explores the potential of a simpler approach using data elements within the Medicaid claims themselves to identify OTPs, removing the need for external data linkage. Once OTPs have been identified, claims data can be attributed to them and thus quality metrics specific to those OTPs can be created.

2. Methods

For this research, we examined whether there are variables on CMS’ TAF (2017–2022) that could be used to identify OTPs within Medicaid claims. For this determination, we relied on the CMS documentation in the TAF data and the CMS DQ Atlas (which reports on the level of completeness of the variables in the TAF data). Of the variables identified through this process, we determined a subset that have a value, or set of values, associated with OTPs. We then analyzed CMS’ TAF files (2017–2022) to create counts of the number of unique NPIs per year that used the OTP-associated code(s) and compared them with the best available estimates from SAMHSA in each year. Though we conduct this comparison using NPIs only, it is important to note that this method allows for identification of the OTP by name, address, and other key characteristics through matching NPIs with the NPPES files which may be needed when using this approach as a strategy to measure and improve quality at the OTP level.

To obtain the best available counts of OTPs certified by SAMHSA by year, we identified the number of facilities that indicated that they were a “federally-certified Opioid Treatment Program (OTP)” using the SAMHSA National Survey of Substance Abuse Treatment Services (N-SSATS) (2017–2020) and National Substance Use and Mental Health Services Survey (N-SUMHSS) (2021–2022). To obtain counts of OTPs that served Medicaid beneficiaries, we applied an additional condition to our counts to capture only facilities that reported accepting Medicaid. We note that these counts based on N-SSATS and N-SUMHSS may underestimate the total number of OTPs because of non-response.

3. Results

3.1. Variables in Medicaid claims that may identify OTPs (2017–2022)

The variables available in Medicaid claims data, specifically the TAF, that might be used to identify OTPs include (1) Provider Type, (2) Provider Specialty, (3) Revenue Center Code, (4) Bill Type, (5) Place of Service, (6) Provider Taxonomy, and (7) Procedure Codes. We describe the usefulness for each of these variables below starting with what we consider the least useful and moving to the most promising variables. Table 1 succinctly summarizes the qualitative results of our assessment.

Table 1.

Evaluation of Medicaid variables to identify OTPs.

Claims Data Variable (Variable Name in TAF) Value Identifying OTPs (Short Descriptor) Conclusion of Analysis
Provider Type (BLG_PRVDR_TYPE_CD) None Not useful. No field specific to OTPs.
Provider Specialty (BLG_PRVDR_SPCLTY_CD) None Not useful. No field specific to OTPs.
Revenue Center Codes (REV_CNTR_CD) 090–091x (Behavioral Health Treatment/Services), 0949 (Other therapeutic services — other), and 0953 (Chemical dependency — drug and alcohol) Not useful. No field specific to OTPs. The new values that became effective 1/1/2021 include OTPs but are too general.
Bill Type (BILL_TYPE_CD) 087x (Freestanding Nonresidential Opioid Treatment Program) Not useful. No OTP-specific code prior to 1/1/2021 and code use is extremely sparse in 2021 and 2022.
Place of Service Code (POS_CD) 58 (Non-residential Opioid Treatment Facility) Potentially useful in the future. OTP value only became effective 1/1/2020. Identified 45.4 % of the expected number of NPIs in 2022 (up from 23.2 % in 2020).
Provider (Billing and Servicing) Taxonomy (BLG_PRVDR_TXNMY_CD and
SRVC_PRVDR_TXNMY_CD)		 261QM2800X (Methadone Clinic) Somewhat useful. Identified 66.8 % of the expected number of NPIs in 2022.
Procedure Codes (LINE_PRCDR_CD) H0020 (HCPCS code for methadone administration and/or service), G2067 (Medication-assisted treatment, methadone), G2078 (Take-home supply of methadone) Useful. Identified 80.0 % of the expected number of NPIs in 2022.
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3.1.1. Provider type and provider specialty

Neither of these variables have values specific to OTPs and therefore are not useful for identifying OTPs in Medicaid claims data.

3.1.2. Revenue center codes

In late 2020, as part of CMS’ coverage of OTPs, CMS gave guidance to OTPs on how to bill for their services, stating that 090–091x, 0949, and 0953 would be considered “Valid OTP service Revenue Codes” (Centers for Medicare & Medicaid Services (CMS), 2020b). Codes 090x cover 0900–0907, which indicate the use of general behavioral health treatments and services, several therapy types (electroshock, milieu, play, and activity), intensive outpatient services for psychiatry, a general chemical dependency code, and day treatment through a community behavioral health program. Codes 091x cover 0911–0919, which indicate the use of rehabilitation, less intensive or intensive partial hospitalizations, individual, group, and family therapy, biofeedback, testing, and behavioral health treatments. Code 0949 is for “Other Therapeutic Services – Other” whereas 0953 is for “Chemical dependency (drug and alcohol).” Though the quality of the revenue center codes field is likely high as payment for services by CMS depends heavily on their correct usage, none of the codes are specific enough to OTPs to be useful for the purpose of identifying OTPs.

3.1.3. Bill Type

On January 1, 2021, CMS added specific OTP bill type codes 087x for “Freestanding Nonresidential Opioid Treatment Program” (Centers for Medicare & Medicaid Services (CMS), 2020b). Before January 1, 2021, there was no OTP-specific bill type code. DQ Atlas determined bill type data for every state to be of “low concern,” except for New Jersey, which was determined to be of “high concern” based on how often unexpected or invalid values appear (Centers for Medicare & Medicaid Services (CMS), 2024). In 2022, the new bill type code identified less than 1 % of the number of SAMHSA-reported Medicaid-participating OTPs (13/1829).

3.1.4. Place of service

The place of service code for OTPs is 58 (Non-residential Opioid Treatment Facility). It was not effective until 2020, making it unsuitable for analyses predating this period (U.S. Department of Health and Human Services, 2024). All states in 2023 met the criteria for “low concern” with over 80 % of records having an expected combination of the bill type and place of service codes (Centers for Medicare & Medicaid Services (CMS), 2024). In our analysis of the TAF, we found that 388 OTPs submitted claims with place of service code 58 in 2020 (the year of adoption), 638 in 2021, and 830 in 2022 (Table 2). Therefore, in 2022, place of service code identified approximately 45 % of the number of SAMHSA-reported Medicaid-participating OTPs (830/1829).

Table 2.

Number of OTPs identified by SAMHSA compared to number identified using Medicaid codes.

Source 2017 2018 2019 2020 2021 2022
Number of OTPs according to SAMHSA surveys 1317 1519 1691 1754 1978* 2152*
Number of OTPs according to SAMHSA surveys that also participate in Medicaid 917 1114 1322 1454 1679* 1829*
Place of Service Code a a a 338 638 830
Provider Taxonomy Code 457 662 946 952 1089 1222
Procedure Codes 958 963 1183 1311 1440 1463
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Notes.

*

Indicates years in which a different method had to be used to calculate the number of OTPs because of the transitions from N-SSATS to N-SUMHSS.

a

Code not available until 2020.

3.1.5. Provider taxonomy

The provider taxonomy code that can identify OTPs is 261QM2800X (Methadone Clinic). Before 2020, taxonomy fields were invalid in more than 50 % of records in 15 states and invalid for between 20 % and 50 % of records in 26 other states (Centers for Medicare & Medicaid Services (CMS), 2020a). In the most recent year of data (2023), the validity is much improved; however, the records are still invalid between 20 % and 50 % of the time in five states (Centers for Medicare & Medicaid Services (CMS), 2024). Using the TAF, we calculated the unique number of OTPs that used this taxonomy code in each year. In 2022, the percentage of unique OTPs that used the methadone clinic taxonomy at least once was 66.8 % (1222/1829) of the number of SAMHSA-reported Medicaid-participating OTPs (see Table 2).

3.1.6. Procedure codes

Methadone can only be dispensed for OUD by licensed OTPs and can be identified by the procedure codes H0020, G2067, and G2078. Of these codes, G2067 and G2078 were only added in January 2020 when OUD treatment in OTPs became a covered benefit under Medicare. H0020 is an alcohol and drug services code used to bill for methadone administration. This code can be billed with modifiers to indicate bundling of medication administration depending on state billing policy. G2067 is a weekly bundle code for medication-assisted treatment using methadone, which includes medication administration, substance use counseling, individual and group therapy, and toxicology testing. G2078 is a take-home supply of methadone, up to 7 additional days’ supply used as an add-on code to a primary procedure code. Under CMS guidance, only OTPs may be reimbursed for these codes, meaning any provider filing a claim for these codes should be a licensed OTP. However, an exception to this rule is that hospitals can dispense methadone as long as they do not dispense it for more than 72 h (the 72-h rule). Procedure codes S0109 and J1230 were considered but ruled out as prior research found that S0109 “… was rarely used in non-outpatient settings” and J1230, an injectable, is primarily used during inpatient stays not associated with OUD (Busch et al., 2023). According to DQ Atlas, procedure codes in the 2023 TAF are of low concern for data quality in all 50 states and two-thirds of US territories (Centers for Medicare & Medicaid Services (CMS), 2024).

Using the TAF, we calculated the unique number of OTPs that billed one of the three Methadone procedure codes (H0020, G2067, and G2078) in each year. In 2022, the percentage of unique OTPs that billed at least one methadone procedure code in each year was 80.0 % (1463/1829) of the number of SAMHSA-reported Medicaid-participating OTPs (see Table 2).

Table 2 compares the most useful Medicaid codes to identify OTPs and the number of OTPs identified with those codes. We compare these numbers against the best available counts from SAMHSA in each year relying on the SAMHSA surveys of OTPs and the subset that participate in Medicaid. Because the TAF is a Medicaid-only data source, comparisons are made to the subset that participates in Medicaid. We provide the full number of OTPs in the top row for reference (Table 2).

4. Discussion

The ability to easily identify certified OTPs in Medicaid claims data would enable the creation of OTP-level quality metrics, which would greatly facilitate transparency in monitoring outcomes and research on real-world effectiveness of interventions. This foundational capability would support diverse applications, from creating consistent research methodologies across studies to informing evidence-based policy decisions about treatment funding and accessibility. Furthermore, reliable OTP identification could facilitate the implementation of outcomes-based reimbursement strategies and enable the systematic identification and replication of effective treatment practices. Unlike other sources of data for clinical reporting, claims-based quality measures do not require additional burden on providers and as we have noted, these data sources typically cover around 80 % of OTP patients (Department of Health Care Services, nd; Van Dyke, 2025). Our research highlights the complex challenges of identifying OTPs in Medicaid claims data, which creates barriers to monitoring treatment outcomes for these critical healthcare providers. The easiest and best solution to this problem would be for SAMHSA to add the organizational NPIs of each OTP on the official listings of OTPs they maintain. We believe this approach is feasible as NPIs are not considered private health information that would identify individuals under the Health Insurance Portability and Accountability Act rules for sharing claims data; in fact, CMS already provides them for Medicare-participating OTPs, and they are also publicly available on NPPES.

In the absence of having these NPIs publicly available on SAMHSA’s OTP list, we demonstrated that the methadone-specific procedure codes and methadone provider taxonomy code available in Medicaid data are promising options for OTP identification. The methadone procedure codes yielded 80 % of the number of OTPs reported by SAMHSA in 2022, while the provider taxonomy method yielded 66.8 %. The proportion identified by the taxonomy method generally increased between 2017 and 2022 whereas the proportion identified by the procedure codes decreased in the same period, indicating that the taxonomy may be more useful in the future.

Our analysis revealed that the number of OTPs that submit claims using the Non-residential Opioid Treatment Facility place of service code was low, although it increased substantially between 2020 (n = 388) and 2022 (n = 830), indicating that this code may be more useful over time. However, the place of service code only became effective in January 2020, so analyses prior to 2020 would be unable to use this code to identify OTPs. The case may be similar for the bill type codes, which were only added in 2021 but so far have seen little use. Meanwhile, the provider type, provider specialty, and revenue codes lack the specificity to be useful to identify OTPs within claims data.

The strengths of identifying OTPs using procedure or taxonomy codes in Medicaid claims include the strong underlying logic and assumptions, the ease and associated replicability of applying these methods, and the relatively high number of OTPs identified. A limitation of this method is that without the ability to confirm that the identified OTPs are the same as on SAMHSA’s OTP list, researchers are not able to validate the OTPs against the official list. Another related limitation is the 72-hour rule, which allows non-OTP providers, such as hospitals, to bill using the methadone procedure code. Although the number of methadone administrations under this exception is likely to be relatively small at this time, given the recent efforts and innovations in increasing access to medications for OUD, the 72-hour rule may be increasingly used (Liu et al., 2024, Taylor et al., 2022).

In this study, we used the counts of OTPs from SAMHSA’s N-SSATS and N-SUMHSS survey as an indicator of whether the methadone procedure or taxonomy codes were accurately identifying OTPs. However, it should be noted that these surveys may somewhat underestimate the number of OTPs. Response rates to the N-SSATS and N-SUMHSS surveys were generally about 90 %. For example, in 2022 the N-SUMHSS response rate was 88 % (Substance Abuse and Mental Health Services Administration, 2023). Although SAMHSA did not report the OTP-specific N-SSATS or N-SUMHSS survey response rates, we estimate that the non-response rate is about 6 % by triangulating between SAMHSA data sources.

The data linkage approach used by the DHS OIG was able to find matches for 87 % of the OTPs in the SAMHSA OTP Directory. The strengths of this approach include the higher number of OTPs identified, as well as the ability to use other information (e.g., provider name and address) to validate the OTPs identified against the SAMHSA list. However, there are many limitations to this method as well, including the difficulty and irreplicability of the matching itself, requiring multiple algorithms that use judgement call thresholds (e.g., fuzzy name matching, GIS mapping) and a manual review process. Efforts by different research teams would almost certainly yield different results.

Our findings have significant implications for healthcare policy and research. Most importantly, SAMHSA should share the NPIs of each OTP on the official lists they provide to facilitate this work. Without this resource, our research highlights variables that could be used directly from Medicaid claims to identify most, but not all, OTPs that deliver to Medicaid beneficiaries.

CRediT authorship contribution statement

William Dowd: Writing – review & editing, Validation, Methodology, Investigation, Formal analysis, Data curation. Mark Tami L: Writing – review & editing, Supervision, Software, Resources, Project administration, Methodology, Funding acquisition, Formal analysis, Conceptualization. Dylan DeLisle: Writing – review & editing, Validation, Supervision, Investigation, Data curation. Chelsea Katz: Writing – review & editing, Validation, Supervision, Project administration, Investigation, Formal analysis. Minglu Sun: Writing – review & editing, Validation, Investigation. Thanh Lu: Writing – review & editing, Validation, Supervision, Investigation, Formal analysis. Zarkin Gary: Writing – review & editing, Validation, Supervision, Project administration, Methodology, Investigation, Formal analysis. Barrett Wallace Montgomery: Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Methodology, Investigation, Formal analysis, Data curation.

Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Tami L. Mark reports financial support was provided by National Institute on Drug Abuse. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was funded by NIDA grant # 5RM1DA059375.

References

  1. Busch A.B., Kennedy-Hendricks A., Schilling C., Stuart E.A., Hollander M., Meiselbach M.K., Barry C.L., Huskamp H.A., Eisenberg M.D. Measurement approaches to estimating methadone continuity in opioid use disorder care. Med. Care. 2023;61(5):314–320. doi: 10.1097/MLR.0000000000001838. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Centers for Medicare & Medicaid Services (CMS), 2020. Data quality atlas: billing provider type, specialty, and taxonomy—OT professional. 〈https://wwwmedicaid.gov/dq-atlas/landing/topics/single/map?topic=g6m104&tafVersionId=23〉.〈https://www.medicaid.gov/dq-atlas/landing/topics/single/map?topic=g6m104&tafVersionId=23〉..
  3. Centers for Medicare & Medicaid Services (CMS) New Medicare National Uniform Billing Committee (NUBC) Type of Bill (TOB), Condition Code and Implementing Billing Codes for Opioid Treatment Programs CMS Manual System. U.S. Department of Health & Human Services; 2020. 〈https://www.cms.gov/files/document/r10521fm.pdf〉 [Google Scholar]
  4. Centers for Medicare & Medicaid Services (CMS), 2024. Data quality atlas: billing provider NPI—OT. 〈https://www.medicaid.gov/dq-atlas/landing/topics/single/map?topic=g6m35&tafVersionId=43〉.
  5. Crable E.L., Benintendi A., Jones D.K., Walley A.Y., Hicks J.M., Drainoni M.-L. Translating medicaid policy into practice: policy implementation strategies from three US states’ experiences enhancing substance use disorder treatment. Implement. Sci. 2022;17(1):3. doi: 10.1186/s13012-021-01182-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Department of Health Care Services, nd. State of California, n.d. California Outcomes Measurement System Treatment. 〈https://www.dhcs.ca.gov/provgovpart/Pages/caloms-treatment.aspx〉.
  7. Dowd W.N., Barch D.H., Seibert J.H., Mark T.L. Development and validation of a claim-based provider-level measurement of use of medications to treat opioid use disorder. J. Subst. Abus. Treat. 2022;140 doi: 10.1016/j.jsat.2022.108824. [DOI] [PubMed] [Google Scholar]
  8. Jencks S.F., Cuerdon T., Burwen D.R., Fleming B., Houck P.M., Kussmaul A.E., Nilasena D.S., Ordin D.L., Arday D.R. Quality of medical care delivered to medicare beneficiaries: a profile at state and national levels. Jama. 2000;284(13):1670–1676. doi: 10.1001/jama.284.13.1670. [DOI] [PubMed] [Google Scholar]
  9. Kaye N., Wilkniss S. State Approaches to Behavioral Health Measures in Medicaid Managed Care. National Academy for State Health Policy; 2023. 〈https://www.medicaid.gov/medicaid/quality-of-care/downloads/factsheet-sud-adult-core-set.pdf〉 [Google Scholar]
  10. Liu P., Chan B., Sokolski E., Patten A., Englander H. Piloting a Hospital-Based Rapid Methadone Initiation Protocol for Fentanyl. J Addict Med. 2024;18(4):458–462. doi: 10.1097/ADM.0000000000001324. https://www.ncbi.nlm.nih.gov/pubmed/38832695 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Ma J., Bao Y.-P., Wang R.-J., Su M.-F., Liu M.-X., Li J.-Q., Degenhardt L., Farrell M., Blow F.C., Ilgen M. Effects of medication-assisted treatment on mortality among opioids users: a systematic review and meta-analysis. Mol. Psychiatry. 2019;24(12):1868–1883. doi: 10.1038/s41380-018-0094-5. [DOI] [PubMed] [Google Scholar]
  12. Maxwell A. Department of Health and Human Services, Office of Inspector General; 2024. Medicare and Medicaid Enrollees in Many High-need Areas May Lack Access to Medications for Opioid Use Disorder.〈https://oig.hhs.gov/documents/evaluation/9999/OEI-BL-23-00160.pdf〉 [Google Scholar]
  13. Medicaid & CHIP Health Care Quality Measures, Centers for Medicare & Medicaid Services, 2024. Overview of substance use disorder measures in the 2024 child, adult, and health home core sets.〈https://www.medicaid.gov/medicaid/quality-of-care/downloads/factsheet-sud-adult-core-set.pdf〉
  14. SAMHSA, nd. FOIA Request Case Number 11202025S040. In: (SAMHSA), S.A.a.M.H.S.A. (Ed.).
  15. Santo T., Clark B., Hickman M., Grebely J., Campbell G., Sordo L., Chen A., Tran L.T., Bharat C., Padmanathan P. Association of opioid agonist treatment with all-cause mortality and specific causes of death among people with opioid dependence: a systematic review and meta-analysis. JAMA Psychiatry. 2021;78(9):979–993. doi: 10.1001/jamapsychiatry.2021.0976. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Schoggen L. In: Personal Communication from the HHS Office of Inspector General. Mark T., editor. 2024. [Google Scholar]
  17. Soyka M., Zingg C., Koller G., Kuefner H. Retention rate and substance use in methadone and buprenorphine maintenance therapy and predictors of outcome: results from a randomized study. Int. J. Neuropsychopharmacol. 2008;11(5):641–653. doi: 10.1017/S146114570700836X. 〈https://www.ncbi.nlm.nih.gov/pubmed/18205978〉 [DOI] [PubMed] [Google Scholar]
  18. Substance Abuse and Mental Health Services Administration . National Substance Use and Mental Health Services Survey (N-SUMHSS) 2022: Data on Substance Use and Mental Health Treatment Facilities, SAMHSA. Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality; 2023. 〈https://www.samhsa.gov/data/sites/default/files/reports/rpt42711/2022-nsumhss-annual-report.pdf〉 [Google Scholar]
  19. Substance Abuse and Mental Health Services Administration . Key Substance Use and Mental Health Indicators in the United States: Results from the 2023 National Survey on Drug Use and Health, SAMHSA. Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality; 2024. 〈https://www.samhsa.gov/data/report/2023-nsduh-annual-national-report〉 [Google Scholar]
  20. Taylor J.L., Laks J., Christine P.J., Kehoe J., Evans J., Kim T.W., Farrell N.M., White C.S., Weinstein Z.M., Walley A.Y. Bridge clinic implementation of "72-hour rule" methadone for opioid withdrawal management: Impact on opioid treatment program linkage and retention in care. Drug Alcohol Depend. 2022;236 doi: 10.1016/j.drugalcdep.2022.109497. https://www.ncbi.nlm.nih.gov/pubmed/35607834 [DOI] [PubMed] [Google Scholar]
  21. Timko C., Schultz N.R., Cucciare M.A., Vittorio L., Garrison-Diehn C. Retention in medication-assisted treatment for opiate dependence: a systematic review. J. Addict. Dis. 2016;35(1):22–35. doi: 10.1080/10550887.2016.1100960. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. U.S. Department of Health and Human Services, 2024. CMS place of service code set. 〈https://www.hhs.gov/guidance/document/cms-place-service-code-set〉.
  23. Van Dyke N. In: Question for BayMark Regarding Proportion of Patients that are Medicaid Beneficiaries. Mark T., editor. 2025. [Google Scholar]
  24. Zhou R.A., Beaulieu N.D., Cutler D. Primary care quality and cost for privately insured patients in and out of US health systems: evidence from four states. Health Serv. Res. 2020;55:1098–1106. doi: 10.1111/1475-6773.13590. [DOI] [PMC free article] [PubMed] [Google Scholar]

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