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Freibott CE, Jalali A, Murphy SM, Walley AY, Linas BP, Jeng PJ, Bratberg J, Marshall BDL, Zang X, Green TC, Morgan JR. The association between naloxone claims and proportion of independent vs. chain pharmacies: A longitudinal analysis of naloxone claims in the US. J Am Pharm Assoc (2003) 2024:102093. [PMID: 38604474 DOI: 10.1016/j.japh.2024.102093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/27/2024] [Accepted: 04/07/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Expanding access to naloxone through pharmacies is an important policy goal. Our objective was to characterize national county-level naloxone dispensing of chain versus independent pharmacies. METHODS The primary exposure in our longitudinal analysis was the proportion of chain pharmacies in a county, identified through the US Department of Homeland Security 2010 Infrastructure Foundation-Level Data. We defined counties as having "higher proportion" of chain pharmacies if at least 50% of pharmacies were large national chains. The primary outcome was quarter-year (2016Q1-2019Q2) rate of pharmacy naloxone claims per 100,000 persons from Symphony Health at the county-level. We compared the naloxone dispensing rate between county types using two-sample t-tests. We estimated the association between county-level chain pharmacy proportion and rate of naloxone claims using a linear model with year-quarter fixed effects. RESULTS Nearly one third of counties (n=946) were higher proportion. Higher proportion counties had a significantly higher rate of naloxone claims across the study period, in 4 of 6 urban-rural classifications, and in counties with and without naloxone access laws. The linear model confirmed that higher proportion counties had a significantly higher rate of naloxone claims, adjusting for urban/rural designation, income, population characteristics, opioid mortality rate, co-prescribing laws and naloxone access laws. CONCLUSION In this national study, we found an association between naloxone dispensing rates and the county-level proportion of chain (versus independent) pharmacies. Incentivizing naloxone dispensing through educational, regulatory, or legal efforts may improve naloxone availability and dispensing rates - particularly in counties with proportionately high numbers of independent pharmacies.
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Affiliation(s)
- Christina E Freibott
- Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston, MA, USA.
| | - Ali Jalali
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, USA
| | - Sean M Murphy
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, USA
| | - Alexander Y Walley
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA, USA
| | - Benjamin P Linas
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA, USA
| | - Philip J Jeng
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, USA
| | - Jeffrey Bratberg
- The University of Rhode Island, College of Pharmacy, Kingston, RI, USA
| | - Brandon D L Marshall
- Brown University School of Public Health, Department of Epidemiology, Providence, RI, USA; COBRE on Opioids and Overdose, Rhode Island Hospital, Providence, RI, USA
| | - Xiao Zang
- University of Minnesota, School of Public Health, Division of Health Policy and Management, Minneapolis, MN, USA
| | - Traci C Green
- Brown University School of Public Health, Department of Epidemiology, Providence, RI, USA; COBRE on Opioids and Overdose, Rhode Island Hospital, Providence, RI, USA; Brandeis University Heller School for Social Policy and Management; Rhode Island Hospital, RI, USA
| | - Jake R Morgan
- Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston, MA, USA
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Cherian T, Lim S, Katyal M, Goldfeld KS, McDonald R, Wiewel E, Khan M, Krawczyk N, Braunstein S, Murphy SM, Jalali A, Jeng PJ, Rosner Z, MacDonald R, Lee JD. Impact of jail-based methadone or buprenorphine treatment on non-fatal opioid overdose after incarceration. Drug Alcohol Depend 2024; 259:111274. [PMID: 38643529 DOI: 10.1016/j.drugalcdep.2024.111274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/13/2024] [Accepted: 03/18/2024] [Indexed: 04/23/2024]
Abstract
BACKGROUND Non-fatal overdose is a leading predictor of subsequent fatal overdose. For individuals who are incarcerated, the risk of experiencing an overdose is highest when transitioning from a correctional setting to the community. We assessed if enrollment in jail-based medications for opioid use disorder (MOUD) is associated with lower risk of non-fatal opioid overdoses after jail release among individuals with opioid use disorder (OUD). METHODS This was a retrospective, observational cohort study of adults with OUD who were incarcerated in New York City jails and received MOUD or did not receive any MOUD (out-of-treatment) within the last three days before release to the community in 2011-2017. The outcome was the first non-fatal opioid overdose emergency department (ED) visit within 1 year of jail release during 2011-2017. Covariates included demographic, clinical, incarceration-related, and other characteristics. We performed multivariable cause-specific Cox proportional hazards regression analysis to compare the risk of non-fatal opioid overdose ED visits within 1 year after jail release between groups. RESULTS MOUD group included 8660 individuals with 17,119 incarcerations; out-of-treatment group included 10,163 individuals with 14,263 incarcerations. Controlling for covariates and accounting for competing risks, in-jail MOUD was associated with lower non-fatal opioid overdose risk within 14 days after jail release (adjusted HR=0.49, 95% confidence interval=0.33-0.74). We found no significant differences 15-28, 29-56, or 57-365 days post-release. CONCLUSION MOUD group had lower risk of non-fatal opioid overdose immediately after jail release. Wider implementation of MOUD in US jails could potentially reduce post-release overdoses, ED utilization, and associated healthcare costs.
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Affiliation(s)
- Teena Cherian
- New York City Department of Health and Mental Hygiene, 42-09 28th Street, Queens, NY 11101, USA.
| | - Sungwoo Lim
- New York City Department of Health and Mental Hygiene, 42-09 28th Street, Queens, NY 11101, USA
| | - Monica Katyal
- New York City Health + Hospitals/Correctional Health Service, 55 Water Street, New York, NY 10041, USA
| | - Keith S Goldfeld
- New York University Grossman School of Medicine, 180 Madison Ave, New York, NY 10010, USA
| | - Ryan McDonald
- New York University Grossman School of Medicine, 180 Madison Ave, New York, NY 10010, USA
| | - Ellen Wiewel
- New York City Department of Health and Mental Hygiene, 42-09 28th Street, Queens, NY 11101, USA
| | - Maria Khan
- New York University Grossman School of Medicine, 180 Madison Ave, New York, NY 10010, USA
| | - Noa Krawczyk
- New York University Grossman School of Medicine, 180 Madison Ave, New York, NY 10010, USA
| | - Sarah Braunstein
- New York City Department of Health and Mental Hygiene, 42-09 28th Street, Queens, NY 11101, USA
| | - Sean M Murphy
- Weill Cornell Medical College, 425 East 61st Street, New York, NY 10065, USA
| | - Ali Jalali
- Weill Cornell Medical College, 425 East 61st Street, New York, NY 10065, USA
| | - Philip J Jeng
- Weill Cornell Medical College, 425 East 61st Street, New York, NY 10065, USA
| | - Zachary Rosner
- New York City Health + Hospitals/Correctional Health Service, 55 Water Street, New York, NY 10041, USA
| | - Ross MacDonald
- New York University Grossman School of Medicine, 180 Madison Ave, New York, NY 10010, USA
| | - Joshua D Lee
- New York University Grossman School of Medicine, 180 Madison Ave, New York, NY 10010, USA
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Lim S, Cherian T, Katyal M, Goldfeld KS, McDonald R, Wiewel E, Khan M, Krawczyk N, Braunstein S, Murphy SM, Jalali A, Jeng PJ, Rosner Z, MacDonald R, Lee JD. Jail-based medication for opioid use disorder and patterns of reincarceration and acute care use after release: A sequence analysis. J Subst Use Addict Treat 2024; 158:209254. [PMID: 38072387 PMCID: PMC10947890 DOI: 10.1016/j.josat.2023.209254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/25/2023] [Accepted: 12/04/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Treatment with methadone and buprenorphine medications for opioid use disorder (MOUD) during incarceration may lead to better community re-entry, but evidence on these relationships have been mixed. We aimed to identify community re-entry patterns and examine the association between in-jail MOUD and a pattern of successful reentry defined by rare occurrence of reincarceration and preventable healthcare utilization. METHODS Data came from a retrospective, observational cohort study of 6066 adults with opioid use disorder who were incarcerated in New York City jails and released to the community during 2011-14. An outcome was community re-entry patterns identified by sequence analysis of 3-year post-release reincarceration, emergency department visits, and hospitalizations. An exposure was receipt of in-jail MOUD versus out-of-treatment (42 % vs. 58 %) for the last 3 days before discharge. The study accounted for differences in baseline demographic, clinical, behavioral, housing, and criminal legal characteristics between in-jail MOUD and out-of-treatment groups via propensity score matching. RESULTS This study identified five re-entry patterns: stability (64 %), hospitalization (23 %), delayed reincarceration (7 %), immediate reincarceration (4 %), and continuous incarceration (2 %). After addressing confounding, 64 % and 57 % followed the stability pattern among MOUD and out-of-treatment groups who were released from jail in 2011, respectively. In 2012-14, the prevalence of following the stability pattern increased year-by-year while a consistently higher prevalence was observed among those with in-jail MOUD. CONCLUSIONS Sequence analysis helped define post-release stability based on health and criminal legal system involvement. Receipt of in-jail MOUD was associated with a marker of successful community re-entry.
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Affiliation(s)
- Sungwoo Lim
- New York City Department of Health and Mental Hygiene, Queens, NY, United States of America.
| | - Teena Cherian
- New York City Department of Health and Mental Hygiene, Queens, NY, United States of America
| | - Monica Katyal
- NYC Health and Hospitals/Correctional Health Services, New York, NY, United States of America
| | - Keith S Goldfeld
- New York University Grossman School of Medicine, New York, NY, United States of America
| | - Ryan McDonald
- New York University Grossman School of Medicine, New York, NY, United States of America
| | - Ellen Wiewel
- New York City Department of Health and Mental Hygiene, Queens, NY, United States of America
| | - Maria Khan
- New York University Grossman School of Medicine, New York, NY, United States of America
| | - Noa Krawczyk
- New York University Grossman School of Medicine, New York, NY, United States of America
| | - Sarah Braunstein
- New York City Department of Health and Mental Hygiene, Queens, NY, United States of America
| | - Sean M Murphy
- Weill Cornell Medical College, New York, NY, United States of America
| | - Ali Jalali
- Weill Cornell Medical College, New York, NY, United States of America
| | - Philip J Jeng
- Weill Cornell Medical College, New York, NY, United States of America
| | - Zachary Rosner
- NYC Health and Hospitals/Correctional Health Services, New York, NY, United States of America
| | - Ross MacDonald
- New York University Grossman School of Medicine, New York, NY, United States of America
| | - Joshua D Lee
- New York University Grossman School of Medicine, New York, NY, United States of America
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Chatterjee A, Yan S, Lambert A, Morgan JR, Green TC, Jeng PJ, Jalali A, Xuan Z, Krieger M, Marshall BDL, Walley AY, Murphy SM. Comparison of a national commercial pharmacy naloxone data source to state and city pharmacy naloxone data sources-Rhode Island, Massachusetts, and New York City, 2013-2019. Health Serv Res 2023; 58:1141-1150. [PMID: 37408299 PMCID: PMC10480090 DOI: 10.1111/1475-6773.14200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2023] Open
Abstract
OBJECTIVE Accurate naloxone distribution data are critical for planning and prevention purposes, yet sources of naloxone dispensing data vary by location, and completeness of local datasets is unknown. We sought to compare available datasets in Massachusetts, Rhode Island, and New York City (NYC) to a commercially available pharmacy national claims dataset (Symphony Health Solutions). DATA SOURCES AND STUDY SETTING We utilized retail pharmacy naloxone dispensing data from NYC (2018-2019), Rhode Island (2013-2019), and Massachusetts (2014-2018), and pharmaceutical claims data from Symphony Health Solutions (2013-2019). STUDY DESIGN We conducted a descriptive, retrospective, and secondary analysis comparing naloxone dispensing events (NDEs) captured via Symphony to NDEs captured by local datasets from the three jurisdictions between 2013 and 2019, when data were available from both sources, using descriptive statistics, regressions, and heat maps. DATA COLLECTION/EXTRACTION METHODS We defined an NDE as a dispensing event documented by the pharmacy and assumed that each dispensing event represented one naloxone kit (i.e., two doses). We extracted NDEs from local datasets and the Symphony claims dataset. The unit of analysis was the ZIP Code annual quarter. PRINCIPAL FINDINGS NDEs captured by Symphony exceeded those in local datasets for each time period and location, except in RI following legislation requiring NDEs to be reported to the PDMP. In regression analysis, absolute differences in NDEs between datasets increased substantially over time, except in RI before the PDMP. Heat maps of NDEs by ZIP code quarter showed important variations reflecting where pharmacies may not be reporting NDEs to Symphony or local datasets. CONCLUSIONS Policymakers must be able to monitor the quantity and location of NDEs in order to combat the opioid crisis. In regions where NDEs are not required to be reported to PDMPs, proprietary pharmaceutical claims datasets may be useful alternatives, with a need for local expertise to assess dataset-specific variability.
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Affiliation(s)
- Avik Chatterjee
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal MedicineBoston Medical Center/Boston University School of MedicineBostonMassachusettsUSA
| | - Shapei Yan
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal MedicineBoston Medical Center/Boston University School of MedicineBostonMassachusettsUSA
| | - Audrey Lambert
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal MedicineBoston Medical Center/Boston University School of MedicineBostonMassachusettsUSA
| | - Jake R. Morgan
- Boston University School of Public HealthBostonMassachusettsUSA
| | - Traci C. Green
- The Heller School for Social Policy and ManagementBrandeis UniversityWalthamMassachusettsUSA
| | - Philip J. Jeng
- Department of Population Health SciencesWeill Cornell Medical CollegeNew York CityNew YorkUSA
| | - Ali Jalali
- Department of Population Health SciencesWeill Cornell Medical CollegeNew York CityNew YorkUSA
| | - Ziming Xuan
- Boston University School of Public HealthBostonMassachusettsUSA
| | - Maxwell Krieger
- Department of EpidemiologyBrown University School of Public HealthProvidenceRhode IslandUSA
| | - Brandon D. L. Marshall
- Department of EpidemiologyBrown University School of Public HealthProvidenceRhode IslandUSA
| | - Alexander Y. Walley
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal MedicineBoston Medical Center/Boston University School of MedicineBostonMassachusettsUSA
| | - Sean M. Murphy
- Department of Population Health SciencesWeill Cornell Medical CollegeNew York CityNew YorkUSA
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Cadet T, Jalali A, Jeng PJ, Poole S, Woody G, Murphy SM. Determinants of health-related quality of life among individuals with opioid use disorder, recently released from incarceration. Addict Sci Clin Pract 2023; 18:34. [PMID: 37231479 DOI: 10.1186/s13722-023-00375-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 03/15/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND\OBJECTIVES: Concomitant with low rates of pharmacotherapy for incarcerated individuals with OUD, there is a high rate of opioid overdose following re-entry into the community. Our research objective was to develop a better understanding of the factors that influence health-related quality-of-life (HRQoL) among this population during the high-risk transition period from incarceration to community. Few studies have assessed health-related quality-of-life (HRQoL) among individuals with OUD who are involved with the criminal-legal system, let alone over the period directly surrounding release from incarceration. METHODS Secondary longitudinal analysis of data from a clinical trial where participants were randomized 1:1 to pre-release extended-release naltrexone (XR-NTX) + referral to community XR-NTX, vs. referral only. We conducted individual, multivariable regressions of EQ-5D domains (mobility, pain/discomfort, anxiety/depression; usual activities and self-care were excluded due to insufficient variation in scores), and the overall preference/utility score. HRQoL data were subset to timepoints immediately before release (baseline) and 12 weeks post-release; treatment groups were collapsed across condition. Multiple imputation by chained equations was conducted to handle missing 3-month data in the dependent variables and covariates, ad hoc. RESULTS Greater severity in the psychiatric composite score was associated with substantially lower HRQoL, across all measures, following release from incarceration. Greater severity in the medical composite score was associated with lower pain/discomfort-related HRQoL. CONCLUSIONS Our findings highlight the importance of ensuring individuals with OUD are linked not only to MOUD, but also treatment for their comorbid conditions upon release from incarceration.
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Affiliation(s)
- Techna Cadet
- Department of Population Health Sciences, Weill Cornell Medical College, 425 East 61St Street, Suite 301, New York, NY, 10065, USA.
| | - Ali Jalali
- Department of Population Health Sciences, Weill Cornell Medical College, 425 East 61St Street, Suite 301, New York, NY, 10065, USA
| | - Philip J Jeng
- Department of Population Health Sciences, Weill Cornell Medical College, 425 East 61St Street, Suite 301, New York, NY, 10065, USA
| | - Sabrina Poole
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - George Woody
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sean M Murphy
- Department of Population Health Sciences, Weill Cornell Medical College, 425 East 61St Street, Suite 301, New York, NY, 10065, USA
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Lim S, Cherian T, Katyal M, Goldfeld KS, McDonald R, Wiewel E, Khan M, Krawczyk N, Braunstein S, Murphy SM, Jalali A, Jeng PJ, MacDonald R, Lee JD. Association between jail-based methadone or buprenorphine treatment for opioid use disorder and overdose mortality after release from New York City jails 2011-17. Addiction 2023; 118:459-467. [PMID: 36305669 PMCID: PMC9898114 DOI: 10.1111/add.16071] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 09/27/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND AND AIMS Opioid overdose is a leading cause of death during the immediate time after release from jail or prison. Most jails in the United States do not provide methadone and buprenorphine treatment for opioid use disorder (MOUD), and research in estimating its impact in jail settings is limited. We aimed to test the hypothesis that in-jail MOUD is associated with lower overdose mortality risk post-release. DESIGN, SETTING AND PARTICIPANTS Retrospective, observational cohort study of 15 797 adults with opioid use disorder who were released from New York City jails to the community in 2011-2017. They experienced 31 382 incarcerations and were followed up to 1 year. MEASUREMENTS The primary outcomes were death caused by accidental drug poisoning and all-cause death. The exposure was receipt of MOUD (17 119 events) versus out-of-treatment (14 263 events) during the last 3 days before community re-entry. Covariates included demographic, clinical, behavioral, housing, health-care utilization and legal characteristics variables. We performed a multivariable, mixed-effect Cox regression analysis to test association between in-jail MOUD and deaths. FINDINGS The majority were male (82%) and their average age was 42 years. Receiving MOUD was associated with misdemeanor charges, being female, injection drug use and homelessness. During 1 year post-release, 111 overdose deaths occurred and crude death rates were 0.49 and 0.83 per 100 person-years for in-jail MOUD and out-of-treatment groups, respectively. Accounting for confounding and random effects, in-jail MOUD was associated with lower overdose mortality risk [adjusted hazard ratio (aHR) = 0.20, 95% confidence interval (CI) = 0.08-0.46] and all-cause mortality risk (aHR = 0.22, 95% CI = 0.11-0.42) for the first month post-release. CONCLUSIONS Methadone and buprenorphine treatment for opioid use disorder during incarceration was associated with an 80% reduction in overdose mortality risk for the first month post-release.
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Affiliation(s)
- Sungwoo Lim
- New York City Department of Health and Mental Hygiene, Queens, NY
| | - Teena Cherian
- New York City Department of Health and Mental Hygiene, Queens, NY
| | - Monica Katyal
- Health and Hospital Correctional Health Services, New York, NY
| | | | - Ryan McDonald
- New York University Grossman School of Medicine, New York, NY
| | - Ellen Wiewel
- New York City Department of Health and Mental Hygiene, Queens, NY
| | - Maria Khan
- New York University Grossman School of Medicine, New York, NY
| | - Noa Krawczyk
- New York University Grossman School of Medicine, New York, NY
| | - Sarah Braunstein
- New York City Department of Health and Mental Hygiene, Queens, NY
| | | | - Ali Jalali
- Weill Cornell Medical School, New York, NY
| | | | - Ross MacDonald
- Health and Hospital Correctional Health Services, New York, NY
| | - Joshua D. Lee
- New York University Grossman School of Medicine, New York, NY
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Ryan DA, Montoya ID, Koutoujian PJ, Siddiqi K, Hayes E, Jeng PJ, Cadet T, McCollister KE, Murphy SM. Budget impact tool for the incorporation of medications for opioid use disorder into jail/prison facilities. J Subst Use Addict Treat 2023; 146:208943. [PMID: 36880906 PMCID: PMC10084043 DOI: 10.1016/j.josat.2022.208943] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 09/02/2022] [Accepted: 12/30/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Given the personal and public consequences of untreated/undertreated OUD among persons involved in the justice system, an increasing number of jails and prisons are incorporating medication for opioid use disorder (MOUD) into their system. Estimating the costs of implementing and sustaining a particular MOUD program is vital to detention facilities, which typically face modest, fixed health care budgets. We developed a customizable budget impact tool to estimate the implementation and sustainment costs of numerous MOUD delivery models for detention facilities. METHODS The aim is to describe the tool and present an application of a hypothetical MOUD model. The tool is populated with resources required to implement and sustain various MOUD models in detention facilities. We identified resources via micro-costing techniques alongside randomized clinical trials. The resource-costing method is used to assign values to resources. Resources/costs are categorized as (a) fixed, (b) time-dependent, and (c) variable. Implementation costs include (a), (b), and (c) over a specified timeframe. Sustainment costs include (b) and (c). The MOUD model example entails offering all three FDA-approved medications, with methadone and buprenorphine provided by vendors, and naltrexone by the jail/prison facility. RESULTS Fixed resources/costs are incurred only once, including accreditation fees and trainings. Time-dependent resources/costs are recurring, but fixed over a given time-period; e.g., medication delivery and staff meetings. Variable resources/costs are those that are a direct function of the number of persons treated, such as the medication provided to each patient. Using nationally representative prices, we estimated fixed/sustainment costs to be $2919/patient, over 1 year. This article estimates annual sustainment costs to be $2885/patient. CONCLUSION The tool will serve as a valuable asset to jail/prison leadership, policymakers, and other stakeholders interested in identifying/estimating the resources and costs associated with alternative MOUD delivery models, from the planning stages through sustainment.
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Affiliation(s)
- Danielle A Ryan
- Weill Cornell Medical College, Department of Population Health Sciences, 425 East 61(st) Street, Suite 301, New York, NY 10065, United States of America.
| | - Iván D Montoya
- University of Miami Miller School of Medicine, Department of Public Health Sciences, 1120 N.W. 14(th) Street, Suite 1024, Miami, FL 33136, United States of America
| | - Peter J Koutoujian
- Middlesex House of Corrections and Jail, 269 Treble Cove Rd., North Billerica, MA 01862, United States of America
| | - Kashif Siddiqi
- Middlesex House of Corrections and Jail, 269 Treble Cove Rd., North Billerica, MA 01862, United States of America
| | - Edmond Hayes
- Franklin County Jail, 160 Elm St., Greenfield, MA 01301, United States of America
| | - Philip J Jeng
- Weill Cornell Medical College, Department of Population Health Sciences, 425 East 61(st) Street, Suite 301, New York, NY 10065, United States of America
| | - Techna Cadet
- Weill Cornell Medical College, Department of Population Health Sciences, 425 East 61(st) Street, Suite 301, New York, NY 10065, United States of America
| | - Kathryn E McCollister
- University of Miami Miller School of Medicine, Department of Public Health Sciences, 1120 N.W. 14(th) Street, Suite 1024, Miami, FL 33136, United States of America
| | - Sean M Murphy
- Weill Cornell Medical College, Department of Population Health Sciences, 425 East 61(st) Street, Suite 301, New York, NY 10065, United States of America
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Jalali A, Jeng PJ, Polsky D, Poole S, Ku YC, Woody GE, Murphy SM. Cost-effectiveness of extended-release injectable naltrexone among incarcerated persons with opioid use disorder before release from prison versus after release. J Subst Abuse Treat 2022; 141:108835. [PMID: 35933942 PMCID: PMC9508988 DOI: 10.1016/j.jsat.2022.108835] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 05/06/2022] [Accepted: 06/23/2022] [Indexed: 10/17/2022]
Abstract
INTRODUCTION Opioid use disorder (OUD) is highly prevalent among incarcerated populations, and the risk of fatal overdose following release from prison is substantial. Despite efficacy, few correctional facilities provide evidence-based addiction treatment. Extended-release injectable naltrexone (XR-NTX) administered prior to release from incarceration may improve health and economic outcomes. METHODS We conducted an economic evaluation alongside a randomized controlled trial testing the effectiveness of XR-NTX before release from prison (n = 38) vs. XR-NTX referral after release (n = 48) of incarcerated participants with OUD, both groups continuing treatment at a community addiction treatment center. The incremental cost-effectiveness ratio (ICER) assessed the cost-effectiveness of XR-NTX before release compared to referral after release for three stakeholder perspectives at 12- and 24-week periods: state policymaker, health care sector, and societal. Effectiveness measures included quality-adjusted life-years (QALYs) and abstinent years from opioids. In addition, we categorized resources as OUD-related and non-OUD-related medical care, state transfer payments, and other societal costs (productivity, criminal justice resources, etc.). RESULTS Results showed an association between XR-NTX and greater OUD-related costs and total costs from the state policymaker perspective. QALYs gained were positive but statistically insignificant between arms; however, results showed XR-NTX had an estimated 15.5 more days of opioid abstinence over 24 weeks and statistically significant at a 95 % confidence level based on the distribution of bootstrapped samples. We found that estimated ICERs to be > $500,000 per QALY for all stakeholder perspectives. For the abstinent-year effectiveness measure, we found XR-NTX before release to be cost-effective at a 95 % confidence level for willingness-to-pay values >$49,000 per abstinent-year, across all perspectives. CONCLUSIONS XR-NTX administered to persons who are incarcerated with OUD before release may provide value for stakeholders and bridge a well-known treatment gap for this vulnerable population. Lower than expected participant engagement and missing data limit our results, and study outcomes may be sensitive to methods that address missing data if replicated.
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Affiliation(s)
- Ali Jalali
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, USA.
| | - Philip J Jeng
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, USA
| | - Daniel Polsky
- Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Sabrina Poole
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yi-Chien Ku
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Academy for the Judiciary, Ministry of Justice, Taiwan
| | - George E Woody
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sean M Murphy
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, USA
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9
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Morgan JR, Freibott CE, Jalali A, Jeng PJ, Walley AY, Chatterjee A, Green TC, Nolan ML, Linas BP, Marshall BD, Murphy SM. The role of increasing pharmacy and community distributed naloxone in the opioid overdose epidemic in Massachusetts, Rhode Island, and New York City. Drug Alcohol Depend Rep 2022; 4:100083. [PMID: 36337350 PMCID: PMC9631422 DOI: 10.1016/j.dadr.2022.100083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Background Naloxone distributed to people at risk for opioid overdose has been associated with reduced overdose death rates; however, associations of retail pharmacy-distributed naloxone with overdose mortality have not been evaluated. Methods Our analytic cohort uses retail pharmacy claims data; three health departments' community distribution data; federal opioid overdose data; and American Community Survey data. Data were analyzed by 3-digit ZIP Code and calendar quarter-year (2016Q1-2018Q4), and weighted by population. We regressed opioid-related overdose mortality on retail-pharmacy and community naloxone distribution, and community-level demographics using a linear model, hypothesizing that areas with high overdose rates would have higher current levels of naloxone distribution but that increasing naloxone distribution from one quarter to the next would be associated with lower overdose. Results From Q1-2016 to Q4-2018, the unadjusted naloxone distribution rate increased from 97 to 257 kits per 100,000 persons, while the unadjusted opioid overdose mortality rate fell from 8.1 to 7.2 per 100,000 persons. The concurrent level of naloxone distribution (both pharmacy and community) was positively and significantly associated with fatal opioid overdose rates. We did not detect associations between change in naloxone distribution rates and overdose mortality. Conclusion Naloxone distribution volumes were correlated with fatal opioid overdose, suggesting medication was getting to communities where it was needed most. Amid high rates of overdose driven by fentanyl in the drug supply, our findings suggest additional prevention, treatment, and harm reduction interventions are required-and dramatically higher naloxone volumes needed-to reverse the opioid overdose crisis in the US.
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Affiliation(s)
- Jake R. Morgan
- Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston, MA, United States of America
- Corresponding author.
| | - Christina E. Freibott
- Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston, MA, United States of America
| | - Ali Jalali
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, United States of America
| | - Philip J. Jeng
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, United States of America
| | - Alexander Y. Walley
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA, United States of America
| | - Avik Chatterjee
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA, United States of America
| | - Traci C. Green
- Brandeis University Heller School for Social Policy and Management, Rhode Island Hospital, RI, United States of America
- Brown University School of Public Health, Department of Epidemiology, RI, United States of America
- COBRE on Opioids and Overdose, Rhode Island Hospital, RI, United States of America
| | - Michelle L. Nolan
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America
| | - Benjamin P. Linas
- Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA, United States of America
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States of America
| | - Brandon D.L. Marshall
- Brown University School of Public Health, Department of Epidemiology, RI, United States of America
- COBRE on Opioids and Overdose, Rhode Island Hospital, RI, United States of America
| | - Sean M. Murphy
- Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, United States of America
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10
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Murphy SM, Jeng PJ, McCollister KE, Leff JA, Jalali A, Shulman M, Lee JD, Nunes EV, Novo P, Rotrosen J, Schackman BR. Cost-effectiveness implications of increasing the efficiency of the extended-release naltrexone induction process for the treatment of opioid use disorder: a secondary analysis. Addiction 2021; 116:3444-3453. [PMID: 33950535 PMCID: PMC8568741 DOI: 10.1111/add.15531] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 07/13/2020] [Accepted: 04/21/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND AIMS In a US randomized-effectiveness trial comparing extended-release naltrexone (XR-NTX) with buprenorphine-naloxone (BUP-NX) for the prevention of opioid relapse among participants recruited during inpatient detoxification (CTN-0051), the requirement to complete opioid detoxification prior to initiating XR-NTX resulted in lower rates of initiation of XR-NTX (72% XR-NTX versus 94% BUP-NX). DESIGN This was a retrospective secondary analysis of CTN-0051 trial data, including follow-up data over 24-36 weeks. SETTING Eight community-based, inpatient-detoxification and follow-up outpatient treatment facilities in the United States. PARTICIPANTS A total of 283 participants randomized to receive XR-NTX. MEASUREMENTS Efficiency was estimated using a multivariable generalized structural equation model to explore simultaneous determinants of XR-NTX induction and induction duration (detoxification + residential days). Cost-effectiveness was estimated from the health-care sector perspective and included expected costs and quality-adjusted life-years (QALYs). FINDINGS Treatment site was the only modifiable factor that simultaneously increased the likelihood of XR-NTX induction and decreased induction duration. Incorporating the higher predicted probability of XR-NTX induction, and fewer predicted days of detoxification and subsequent residential treatment into the cost-effectiveness framework, reduced the incremental average 24-week total cost of XR-NTX treatment from $5317 more than that of BUP-NX (P = 0.01) to a non-statistically-significant difference of $1016 (P = 0.63). QALYs gained remained similar across arms. CONCLUSION Adopting an efficient model of extended-release naltrexone initiation could result in extended-release naltrexone and buprenorphine-naloxone being of comparable economic value from the health-care sector perspective over 24-36 weeks for patients seeking treatment for opioid use disorder at an inpatient detoxification facility.
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Affiliation(s)
- Sean M. Murphy
- Department of Population Health Sciences, Weill Cornell
Medical College, New York, NY, USA
| | - Philip J. Jeng
- Department of Population Health Sciences, Weill Cornell
Medical College, New York, NY, USA
| | - Kathryn E. McCollister
- Department of Public Health Sciences, University of Miami
Miller School of Medicine, Miami, FL USA
| | - Jared A. Leff
- Department of Population Health Sciences, Weill Cornell
Medical College, New York, NY, USA
| | - Ali Jalali
- Department of Population Health Sciences, Weill Cornell
Medical College, New York, NY, USA
| | - Matisyahu Shulman
- New York State Psychiatric Institute, Columbia University
Medical Center, New York, NY USA
| | - Joshua D. Lee
- Department of Population Health, New York University School
of Medicine, New York, NY USA
| | - Edward V. Nunes
- New York State Psychiatric Institute, Columbia University
Medical Center, New York, NY USA
| | - Patricia Novo
- Department of Psychiatry, New York University School of
Medicine, New York, NY USA
| | - John Rotrosen
- Department of Psychiatry, New York University School of
Medicine, New York, NY USA
| | - Bruce R. Schackman
- Department of Population Health Sciences, Weill Cornell
Medical College, New York, NY, USA
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11
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Bao Y, Zhang H, Wen K, Johnson P, Jeng PJ, Witkin LR, Nicholson S, Reid MC, Schackman BR. Robust Prescription Monitoring Programs and Abrupt Discontinuation of Long-term Opioid Use. Am J Prev Med 2021; 61:537-544. [PMID: 34233856 PMCID: PMC8455444 DOI: 10.1016/j.amepre.2021.04.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 03/12/2021] [Accepted: 04/09/2021] [Indexed: 11/26/2022]
Abstract
INTRODUCTION This study assesses the associations between the recent implementation of robust features of state Prescription Drug Monitoring Programs and the abrupt discontinuation of long-term opioid therapies. METHODS Data were from a national commercial insurance database and included privately insured adults aged 18-64 years and Medicare Advantage enrollees aged ≥65 years who initiated a long-term opioid therapy episode between Quarter 2 of 2011 and Quarter 2 of 2017. State Prescription Drug Monitoring Programs were characterized as nonrobust, robust, and strongly robust. Abrupt discontinuation was measured on the basis of high daily morphine milligram equivalents over the last 30 days of a long-term opioid therapy episode or no sign of tapering before discontinuation. Difference-in-differences models were estimated in 2019‒2020 to assess the association between robust Prescription Drug Monitoring Programs and abrupt discontinuation. RESULTS Among nonelderly privately insured adults, robust Prescription Drug Monitoring Programs were associated with an increase from 14.8% to 15.4% (4% relative increase, p=0.02) in the rate of ending long-term opioid therapy with ≥60 daily morphine milligram equivalents. For older Medicare Advantage enrollees, strongly robust Prescription Drug Monitoring Programs were associated with a reduction from 4.8% to 4.3% (10.4%, p=0.01) and from 3.0% to 2.4% (17.3%, p=0.001) in the rate of ending long-term opioid therapy with ≥90 and 120 daily morphine milligram equivalents, respectively. Prescription Drug Monitoring Programs robustness was not associated with clinically meaningful changes in the rate of discontinuing long-term opioid therapy without tapering. CONCLUSIONS Discontinuation without tapering was the norm for long-term opioid therapies in the samples throughout the study years. Findings do not support the notion that policies aimed at enhancing Prescription Drug Monitoring Program use were associated with substantial increases in abrupt long-term opioid therapy discontinuation.
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Affiliation(s)
- Yuhua Bao
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York; Department of Psychiatry, Weill Cornell Medicine, New York, New York.
| | - Hao Zhang
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
| | - Katherine Wen
- Department of Policy Analysis and Management, College of Human Ecology, Cornell University, Ithaca, New York
| | - Phyllis Johnson
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
| | - Philip J Jeng
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
| | - Lisa R Witkin
- Department of Anesthesiology, Weill Cornell Medicine, New York, New York; Division of Pain Medicine, NewYork-Presbyterian Lower Manhattan Hospital, NewYork-Presbyterian, New York, New York
| | - Sean Nicholson
- Department of Policy Analysis and Management, College of Human Ecology, Cornell University, Ithaca, New York
| | | | - Bruce R Schackman
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York; Department of Psychiatry, Weill Cornell Medicine, New York, New York; Department of Medicine, Weill Cornell Medicine, New York, New York
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12
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Rosen T, Wen K, Makaroun LK, Elman A, Zhang Y, Jeng PJ, LoFaso VM, Lachs MS, Clark S, Bao Y. Diagnostic Coding of Elder Mistreatment: Results From a National Database of Medicare Advantage and Private Insurance Patients, 2011-2017. J Appl Gerontol 2021; 41:918-927. [PMID: 34075830 PMCID: PMC8636549 DOI: 10.1177/07334648211018530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Health care providers may play an important role in detection of elder mistreatment, which is common but underrecognized. We used the Health Care Cost Institute insurance claims database to describe elder mistreatment diagnosis among Medicare Advantage (MA) and private insurance patients in the United States from 2011 to 2017. We used International Classification of Diseases (ICD) coding to identify cases, examining the impact of transition from ICD-9 (Ninth Revision) to ICD-10 (Tenth Revision), which occurred in October 2015 and added 14 new codes for "suspected" mistreatment. 8,127 patients (0.051% of all aged ≥ 65), including 6,304 with MA (0.058%) and 1,823 with private insurance (0.026%) received elder mistreatment diagnosis. Transition from ICD-9 to ICD-10 was associated with a small increase in diagnosis rate, with "suspected" codes used in 45.3% of ICD-10 versus 9.7% of ICD-9 cases. Overall rates remained low. Rates, settings, and types of diagnosis differed between MA and private insurance patients.
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Affiliation(s)
- Tony Rosen
- Department of Emergency Medicine, Weill Cornell Medicine / NewYork-Presbyterian Hospital, 525 East 68 Street, New York, NY 10065
| | - Katherine Wen
- Department of Policy Analysis and Management, Cornell University, 2301 Martha Van Rensselaer Hall, Ithaca, NY 14853
| | - Lena K. Makaroun
- Center for Health Equity Research and Promotion, Veterans Affairs (VA) Pittsburgh Healthcare System, Pittsburgh, PA
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Alyssa Elman
- Department of Emergency Medicine, Weill Cornell Medicine / NewYork-Presbyterian Hospital, 525 East 68 Street, New York, NY 10065
| | - Yiye Zhang
- Department of Health Policy & Research, Weill Cornell Medicine, 402 East 67 Street New York, NY 10065
| | - Philip J. Jeng
- Department of Health Policy & Research, Weill Cornell Medicine, 402 East 67 Street New York, NY 10065
| | - Veronica M. LoFaso
- Division of Geriatrics and Palliative Medicine, Weill Cornell Medicine / NewYork-Presbyterian Hospital, 525 East 68 Street, New York, NY 10065
| | - Mark S. Lachs
- Division of Geriatrics and Palliative Medicine, Weill Cornell Medicine / NewYork-Presbyterian Hospital, 525 East 68 Street, New York, NY 10065
| | - Sunday Clark
- Department of Surgery, Boston University School of Medicine, Boston, MA
| | - Yuhua Bao
- Department of Health Policy & Research, Weill Cornell Medicine, 402 East 67 Street New York, NY 10065
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13
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Bao Y, Li Y, Jeng PJ, Scodes J, Papp MA, Humensky JL, Wall M, Lee R, Ancker JS, Pincus HA, Smith TE, Dixon LB. Design of a Payment Decision-Support Tool for Coordinated Specialty Care for Early Psychosis. Psychiatr Serv 2021; 72:180-185. [PMID: 33267653 PMCID: PMC8317229 DOI: 10.1176/appi.ps.202000129] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
A strengthened evidence base and earmarked federal funding have spurred the implementation of coordinated specialty care (CSC) for people experiencing early psychosis. However, existing funding mechanisms are insufficient and unsustainable to support population-wide deployment of CSC. This article describes the design framework of an innovative payment model for CSC that includes a bundled case rate payment and an optional outcome-based payment. To assist CSC payer and provider organizations in designing payment systems tailored to local preferences and circumstances, the research team is developing a decision-support tool that allows users to define design choices and provide input. The authors document the analytical algorithms underlying the tool and discuss how it could be further developed or expanded for CSC and other behavioral health interventions that feature an interdisciplinary team of clinicians and nonclinical professionals, public education and outreach, patient centeredness, and a recovery orientation.
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Affiliation(s)
- Yuhua Bao
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Yan Li
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Philip J Jeng
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Jennifer Scodes
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Michelle A Papp
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Jennifer L Humensky
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Melanie Wall
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Rufina Lee
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Jessica S Ancker
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Harold Alan Pincus
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Thomas E Smith
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
| | - Lisa B Dixon
- Department of Population Health Sciences (Bao, Jeng, Papp, Ancker) and Department of Psychiatry (Bao), Weill Cornell Medicine, New York City; Department of Population Health Science and Policy and Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City (Li); New York State Psychiatric Institute, New York City (Scodes, Humensky, Wall, Pincus, Smith, Dixon); Department of Psychiatry, Irving Medical Center (Scodes, Humensky, Wall, Pincus, Smith, Dixon), and Department of Biostatistics, Mailman School of Public Health (Wall), Columbia University, New York City; Silberman School of Social Work at Hunter College, City University of New York, New York City (Lee)
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14
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Wen H, Hockenberry JM, Jeng PJ, Bao Y. Prescription Drug Monitoring Program Mandates: Impact On Opioid Prescribing And Related Hospital Use. Health Aff (Millwood) 2020; 38:1550-1556. [PMID: 31479368 DOI: 10.1377/hlthaff.2019.00103] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Comprehensive mandates for prescription drug monitoring programs (PDMPs) require state-licensed prescribers and dispensers both to register with and to use the programs in most clinical circumstances. Such mandates have the potential to improve providers' participation and reduce opioid-related adverse events. Using Medicaid prescription data and hospital utilization data across the US in the period 2011-16, we found that state implementation of comprehensive PDMP mandates was associated with a reduction in the opioid prescription rate from 161.47 to 147.07 per 1,000 enrollees per quarter, a reduction in the opioid-related inpatient stay rate from 97.50 to 93.34 per 100,000 enrollees per quarter, and a reduction in the opioid-related emergency department (ED) visit rate from 74.60 to 61.36 per 100,000 enrollees per quarter. Our estimated annual reductions of approximately 12,000 inpatient stays and 39,000 ED visits could save over $155 million in Medicaid spending, a fact that deserves policy attention when states attempt to strengthen and refine PDMPs to better tackle the opioid crisis.
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Affiliation(s)
- Hefei Wen
- Hefei Wen ( ) is an assistant professor in the Department of Health Management and Policy at the University of Kentucky College of Public Health, in Lexington
| | - Jason M Hockenberry
- Jason M. Hockenberry is an associate professor in the Department of Health Policy and Management, Rollins School of Public Health, Emory University, in Atlanta, Georgia
| | - Philip J Jeng
- Philip J. Jeng is a research coordinator in the Department of Healthcare Policy and Research, Weill Cornell Medical College, in New York City
| | - Yuhua Bao
- Yuhua Bao is an associate professor of healthcare policy and research at Weill Cornell Medical College
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15
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Murphy SM, Jeng PJ, Poole SA, Jalali A, Vocci FJ, Gordon MS, Woody GE, Polsky D. Health and economic outcomes of treatment with extended-release naltrexone among pre-release prisoners with opioid use disorder (HOPPER): protocol for an evaluation of two randomized effectiveness trials. Addict Sci Clin Pract 2020; 15:15. [PMID: 32321570 PMCID: PMC7178627 DOI: 10.1186/s13722-020-00188-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 04/08/2020] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Persons with an opioid use disorder (OUD) who were incarcerated face many challenges to remaining abstinent; concomitantly, opioid-overdose is the leading cause of death among this population, with the initial weeks following release proving especially fatal. Extended-release naltrexone (XR-NTX) is the most widely-accepted, evidence-based OUD pharmacotherapy in criminal justice settings, and ensures approximately 30 days of protection from opioid overdose. The high cost of XR-NTX serves as a barrier to uptake by many prison/jail systems; however, the cost of the medication should not be viewed in isolation. Prison/jail healthcare budgets are ultimately determined by policymakers, and the benefits/cost-offsets associated with effective OUD treatment will directly and indirectly affect their overall budgets, and society as a whole. METHODS This protocol describes a study funded by the National Institute of Drug Abuse (NIDA) to: evaluate changes in healthcare utilization, health-related quality-of-life, and other resources associated with different strategies of XR-NTX delivery to persons with OUD being released from incarceration; and estimate the relative "value" of each strategy. Data from two ongoing, publicly-funded, randomized-controlled trials will be used to evaluate these questions. In Study A, (XR-NTX Before vs. After Reentry), participants are randomized to receive their first XR-NTX dose before release, or at a nearby program post-release. In Study B, (enhanced XR-NTX vs. XR-NTX), both arms receive XR-NTX prior to release; the enhanced arm receives mobile medical (place of residence) XR-NTX treatment post-release, and the XR-NTX arm receives referral to a community treatment program post-release. The economic data collection instruments required to evaluate outcomes of interest were incorporated into both studies from baseline. Moreover, because the same instruments are being used in both trials on comparable populations, we have the opportunity to not only assess differences in outcomes between study arms within each trial, but also to merge the data sets and test for differences across trials. DISCUSSION Initiating XR-NTX for OUD prior to release from incarceration may improve patient health and well-being, while also producing downstream cost-offsets. This study offers the unique opportunity to assess the effectiveness and cost-effectiveness of multiple strategies, according to different stakeholder perspectives.
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Affiliation(s)
- Sean M Murphy
- Department of Population Health Sciences, Weill Cornell Medical College, 425 East 61st Street, Suite 301, New York, NY, 10065, USA.
| | - Philip J Jeng
- Department of Population Health Sciences, Weill Cornell Medical College, 425 East 61st Street, Suite 301, New York, NY, 10065, USA
| | - Sabrina A Poole
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ali Jalali
- Department of Population Health Sciences, Weill Cornell Medical College, 425 East 61st Street, Suite 301, New York, NY, 10065, USA
| | | | | | - George E Woody
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel Polsky
- Department of Health Policy and Management, Bloomberg School of Public Health, Carey Business School, Johns Hopkins University, Baltimore, MD, USA
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16
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Flash MJE, Garland WH, Martey EB, Schackman BR, Oksuzyan S, Scott JA, Jeng PJ, Rubio M, Losina E, Freedberg KA, Kulkarni SP, Hyle EP. Cost-effectiveness of a Medical Care Coordination Program for People With HIV in Los Angeles County. Open Forum Infect Dis 2019; 6:ofz537. [PMID: 31909083 PMCID: PMC6935680 DOI: 10.1093/ofid/ofz537] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 12/13/2019] [Indexed: 11/12/2022] Open
Abstract
Background The Los Angeles County (LAC) Division of HIV and STD Programs implemented a medical care coordination (MCC) program to address the medical and psychosocial service needs of people with HIV (PWH) at risk for poor health outcomes. Methods Our objective was to evaluate the impact and cost-effectiveness of the MCC program. Using the CEPAC-US model populated with clinical characteristics and costs observed from the MCC program, we projected lifetime clinical and economic outcomes for a cohort of high-risk PWH under 2 strategies: (1) No MCC and (2) a 2-year MCC program. The cohort was stratified by acuity using social and clinical characteristics. Baseline viral suppression was 33% in both strategies; 2-year suppression was 33% with No MCC and 57% with MCC. The program cost $2700/person/year. Model outcomes included quality-adjusted life expectancy, lifetime medical costs, and cost-effectiveness. The cost-effectiveness threshold for the incremental cost-effectiveness ratio (ICER) was $100 000/quality-adjusted life-year (QALY). Results With MCC, life expectancy increased from 10.07 to 10.94 QALYs, and costs increased from $311 300 to $335 100 compared with No MCC (ICER, $27 400/QALY). ICERs for high/severe, moderate, and low acuity were $30 500/QALY, $25 200/QALY, and $77 400/QALY. In sensitivity analysis, MCC remained cost-effective if 2-year viral suppression was ≥39% even if MCC costs increased 3-fold. Conclusions The LAC MCC program improved survival and was cost-effective. Similar programs should be considered in other settings to improve outcomes for high-risk PWH.
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Affiliation(s)
- Moses J E Flash
- Divisions of General Internal Medicine and Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Medical Practice Evaluation Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Wendy H Garland
- Division of HIV and STD Programs, Los Angeles County Department of Public Health, Los Angeles, California, USA
| | - Emily B Martey
- Divisions of General Internal Medicine and Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Medical Practice Evaluation Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Bruce R Schackman
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, New York, USA
| | - Sona Oksuzyan
- Division of HIV and STD Programs, Los Angeles County Department of Public Health, Los Angeles, California, USA
| | - Justine A Scott
- Divisions of General Internal Medicine and Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Medical Practice Evaluation Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Philip J Jeng
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, New York, USA
| | - Marisol Rubio
- Division of HIV and STD Programs, Los Angeles County Department of Public Health, Los Angeles, California, USA
| | - Elena Losina
- Medical Practice Evaluation Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Harvard University Center for AIDS Research, Harvard University, Boston, Massachusetts, USA.,Department of Orthopedic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Kenneth A Freedberg
- Divisions of General Internal Medicine and Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Medical Practice Evaluation Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Harvard University Center for AIDS Research, Harvard University, Boston, Massachusetts, USA.,Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Sonali P Kulkarni
- Division of HIV and STD Programs, Los Angeles County Department of Public Health, Los Angeles, California, USA
| | - Emily P Hyle
- Divisions of General Internal Medicine and Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Medical Practice Evaluation Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Harvard University Center for AIDS Research, Harvard University, Boston, Massachusetts, USA
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17
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Behrends CN, Paone D, Nolan ML, Tuazon E, Murphy SM, Kapadia SN, Jeng PJ, Bayoumi AM, Kunins HV, Schackman BR. Estimated impact of supervised injection facilities on overdose fatalities and healthcare costs in New York City. J Subst Abuse Treat 2019; 106:79-88. [DOI: 10.1016/j.jsat.2019.08.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 07/23/2019] [Accepted: 08/13/2019] [Indexed: 12/20/2022]
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18
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Kapadia SN, Jeng PJ, Schackman BR, Bao Y. State Medicaid Hepatitis C Treatment Eligibility Criteria and Use of Direct-Acting Antivirals. Clin Infect Dis 2019; 66:1618-1620. [PMID: 29206910 DOI: 10.1093/cid/cix1062] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Accepted: 11/29/2017] [Indexed: 01/29/2023] Open
Abstract
Medicaid program criteria for accessing hepatitis C treatment are changing. Medicaid drug utilization data from 2014 to 2016 show that programs that have relaxed their criteria have seen significant increases in treatment utilization, as have states with Medicaid expansions.
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Affiliation(s)
| | - Philip J Jeng
- Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, New York
| | - Bruce R Schackman
- Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, New York
| | - Yuhua Bao
- Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, New York
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19
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Bao Y, Wen K, Johnson P, Jeng PJ, Meisel ZF, Schackman BR. Assessing The Impact Of State Policies For Prescription Drug Monitoring Programs On High-Risk Opioid Prescriptions. Health Aff (Millwood) 2019; 37:1596-1604. [PMID: 30273045 DOI: 10.1377/hlthaff.2018.0512] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Policies and practices have proliferated to optimize prescribers' use of their states' prescription drug monitoring programs, which are statewide databases of controlled substances dispensed at retail pharmacies. Our study assessed the effectiveness of three such policies: comprehensive legislative mandates to use the program, laws that allow prescribers to delegate its use to office staff, and state participation in interstate data sharing. Our analysis of information from a large commercial insurance database indicated that comprehensive use mandates implemented during 2011-15 were associated with a 6-9 percent reduction in opioid prescriptions with high risk for misuse and overdose. We also found delegate laws to be associated with reductions of a similar magnitude for selected outcomes. In general, the effects of all three policies strengthened over time, especially beginning in the second year after implementation. Our findings support comprehensive use mandates and delegate laws to optimize prescribers' use of drug monitoring programs, but the results will need updates in the context of evolving state opioid policies-including the increasing integration of drug monitoring data with electronic health records.
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Affiliation(s)
- Yuhua Bao
- Yuhua Bao ( ) is an associate professor of healthcare policy and research at Weill Cornell Medical College, in New York City
| | - Katherine Wen
- Katherine Wen is a PhD student in the Department of Policy Analysis and Management, Cornell University, in Ithaca, New York
| | - Phyllis Johnson
- Phyllis Johnson is a programmer analyst in the Department of Healthcare Policy and Research, Weill Cornell Medical College
| | - Philip J Jeng
- Philip J. Jeng is a research coordinator in the Department of Healthcare Policy and Research, Weill Cornell Medical College
| | - Zachary F Meisel
- Zachary F. Meisel is the director of the Center for Emergency Care Policy and Research and an associate professor in the Department of Emergency Medicine, both at the Perelman School of Medicine, and a senior fellow at the Leonard Davis Institute of Health Economics, all at the University of Pennsylvania, in Philadelphia
| | - Bruce R Schackman
- Bruce R. Schackman is a professor of healthcare policy and research at Weill Cornell Medical College and director of the Center for Health Economics of Treatment Interventions for Substance Use Disorder, HCV, and HIV
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20
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Abstract
Objective To estimate the own‐price elasticity of demand for naloxone, a prescription medication that can counter the effects of an opioid overdose, and predict the change in pharmacy sales following a conversion to over‐the‐counter status. Data Sources/Study Setting The primary data source was a nationwide prescription claims dataset for 2010‐2017. The data cover 80 percent of US retail pharmacies and account for roughly 90 percent of prescriptions filled. Additional covariates were obtained from various secondary data sources. Study Design We estimated a longitudinal, simultaneous equation model of naloxone supply and demand. Our primary variables of interest were the quantity of naloxone sold, measured as total milligrams sold at pharmacies, and the out‐of‐pocket price paid per milligram, both measured per ZIP Code and quarter‐year. Data Collection/Extraction Methods Primary data came directly from payers and processors of prescription drug claims. Principal Findings We found that, on average, a 1 percent increase in the out‐of‐pocket price paid for naloxone would result in a 0.27 percent decrease in pharmacy sales. We predict that the total quantity of naloxone sold in pharmacies would increase 15 percent to 179 percent following conversion to over‐the‐counter status. Conclusions Naloxone is own‐price inelastic, and conversion to over‐the‐counter status is likely to lead to a substantial increase in total pharmacy sales.
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Affiliation(s)
- Sean M Murphy
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, New York
| | - Jake R Morgan
- Department of Health Law, Policy & Management, Boston University School of Public Health, Boston, Massachusetts
| | - Philip J Jeng
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, New York
| | - Bruce R Schackman
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, New York
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21
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Abstract
OBJECTIVE This study examined organizational variability of process-of-care and depression outcomes at eight community health centers (CHCs) in the years following implementation of collaborative care (CC) for depression. METHODS The authors used 8 years of observational data for 13,362 unique patients at eight CHCs that participated in Washington State's Mental Health Integration Program. Organization-level changes in depression and process-of-care outcomes over time were studied. RESULTS On average, depression outcomes improved for the first 2 years before improvement slowed, peaking at year 5. Significant organization-level variation was noted in outcomes. Improvements in depression outcomes tended to follow process-of-care measures. CONCLUSIONS Findings suggest that it may take 2 years after implementation of CC to fully observe depression outcome improvement at an organization level. Substantial variation between organizations in depression outcomes over time suggests that sustained attention to processes of care may be necessary to maintain initially achieved gains.
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Affiliation(s)
- Andrew D Carlo
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Carlo, Unützer); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York (Jeng, Bao)
| | - Philip J Jeng
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Carlo, Unützer); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York (Jeng, Bao)
| | - Yuhua Bao
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Carlo, Unützer); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York (Jeng, Bao)
| | - Jürgen Unützer
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Carlo, Unützer); Department of Healthcare Policy and Research, Weill Cornell Medical College, New York (Jeng, Bao)
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22
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Murphy SM, McCollister KE, Leff JA, Yang X, Jeng PJ, Lee JD, Nunes EV, Novo P, Rotrosen J, Schackman BR. Cost-Effectiveness of Buprenorphine-Naloxone Versus Extended-Release Naltrexone to Prevent Opioid Relapse. Ann Intern Med 2019; 170:90-98. [PMID: 30557443 PMCID: PMC6581635 DOI: 10.7326/m18-0227] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Not enough evidence exists to compare buprenorphine-naloxone with extended-release naltrexone for treating opioid use disorder. OBJECTIVE To evaluate the cost-effectiveness of buprenorphine-naloxone versus extended-release naltrexone. DESIGN Cost-effectiveness analysis alongside a previously reported randomized clinical trial of 570 adults in 8 U.S. inpatient or residential treatment programs. DATA SOURCES Study instruments. TARGET POPULATION Adults with opioid use disorder. TIME HORIZON 24-week intervention with an additional 12 weeks of observation. PERSPECTIVE Health care sector and societal. INTERVENTIONS Buprenorphine-naloxone and extended-release naltrexone. OUTCOME MEASURES Incremental costs combined with incremental quality-adjusted life-years (QALYs) and incremental time abstinent from opioids. RESULTS OF BASE-CASE ANALYSIS Use of the health care sector perspective and a willingness-to-pay threshold of $100 000 per QALY showed buprenorphine-naloxone to be preferable to extended-release naltrexone in 97% of bootstrap replications at 24 weeks and in 85% at 36 weeks. Similar results were obtained with incremental time abstinent from opioids as an outcome and with use of the societal perspective. RESULTS OF SENSITIVITY ANALYSIS The base-case results were sensitive to the cost of the 2 treatments and the success of randomized treatment initiation. LIMITATION Relatively short follow-up for a chronic condition, substantial missing data, no information on patient out-of-pocket and social service costs. CONCLUSION Buprenorphine-naloxone is preferred to extended-release naltrexone as first-line treatment when both options are clinically appropriate and patients require detoxification before initiating extended-release naltrexone. PRIMARY FUNDING SOURCE National Institute on Drug Abuse, National Institutes of Health.
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Affiliation(s)
- Sean M Murphy
- Weill Cornell Medical College, New York, New York (S.M.M., J.A.L., P.J.J., B.R.S.)
| | | | - Jared A Leff
- Weill Cornell Medical College, New York, New York (S.M.M., J.A.L., P.J.J., B.R.S.)
| | - Xuan Yang
- University of Miami Miller School of Medicine, Miami, Florida (K.E.M., X.Y.)
| | - Philip J Jeng
- Weill Cornell Medical College, New York, New York (S.M.M., J.A.L., P.J.J., B.R.S.)
| | - Joshua D Lee
- New York University School of Medicine, New York, New York (J.D.L., P.N., J.R.)
| | - Edward V Nunes
- Columbia University Medical Center, New York, New York (E.V.N.)
| | - Patricia Novo
- New York University School of Medicine, New York, New York (J.D.L., P.N., J.R.)
| | - John Rotrosen
- New York University School of Medicine, New York, New York (J.D.L., P.N., J.R.)
| | - Bruce R Schackman
- Weill Cornell Medical College, New York, New York (S.M.M., J.A.L., P.J.J., B.R.S.)
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23
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Zhang Y, Johnson P, Jeng PJ, Reid MC, Witkin LR, Schackman BR, Ancker JS, Bao Y. First Opioid Prescription and Subsequent High-Risk Opioid Use: a National Study of Privately Insured and Medicare Advantage Adults. J Gen Intern Med 2018; 33:2156-2162. [PMID: 30206790 PMCID: PMC6258623 DOI: 10.1007/s11606-018-4628-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Revised: 05/24/2018] [Accepted: 07/27/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND National guidelines make recommendations regarding the initial opioid prescriptions, but most of the supporting evidence is from the initial episode of care, not the first prescription. OBJECTIVE To examine associations between features of the first opioid prescription and high-risk opioid use in the 18 months following the first prescription. DESIGN Retrospective cohort study using data from a large commercial insurance claims database for 2011-2014 to identify individuals with no recent use of opioids and follow them for 18 months after the first opioid prescription. PARTICIPANTS Privately insured patients aged 18-64 and Medicare Advantage patients aged 65 or older who filled a first opioid prescription between 07/01/2011 and 06/30/2013. MAIN OUTCOMES AND MEASURES High-risk opioid use was measured by having (1) opioid prescriptions overlapping for 7 days or more, (2) opioid and benzodiazepine prescriptions overlapping for 7 days or more, (3) three or more prescribers of opioids, and (4) a daily dosage exceeding 120 morphine milligram equivalents, in each of the six quarters following the first prescription. KEY RESULTS All three features of the first prescription were strongly associated with high-risk use. For example, among privately insured patients, receiving a long- (vs. short-) acting first opioid was associated with a 16.9-percentage-point increase (95% CI, 14.3-19.5), a daily MME of 50 or more (vs. less than 30) was associated with a 12.5-percentage-point increase (95% CI, 12.1-12.9), and a supply exceeding 7 days (vs. 3 or fewer days) was associated with a 4.8-percentage-point increase (95% CI, 4.5-5.2), in the probability of having a daily dosage of 120 MMEs or more in the long term, compared to a sample mean of 4.2%. Results for the Medicare Advantage patients were similar. CONCLUSIONS Long-acting formulation, high daily dosage, and longer duration of the first opioid prescription were each associated with increased high-risk use of opioids in the long term.
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Affiliation(s)
- Yongkang Zhang
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, NY, USA
| | - Phyllis Johnson
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, NY, USA
| | - Philip J Jeng
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, NY, USA
| | - M Carrington Reid
- Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Lisa R Witkin
- Department of Anesthesiology, Weill Cornell Medical College, New York, NY, USA.,Division of Pain Medicine, New York-Presbyterian/Lower Manhattan Hospital, New York, NY, USA
| | - Bruce R Schackman
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, NY, USA.,Department of Medicine, Weill Cornell Medical College, New York, NY, USA.,Department of Psychiatry, Weill Cornell Medical College, New York, NY, USA
| | - Jessica S Ancker
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, NY, USA
| | - Yuhua Bao
- Department of Healthcare Policy & Research, Weill Cornell Medical College, New York, NY, USA. .,Department of Psychiatry, Weill Cornell Medical College, New York, NY, USA.
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