Faculty Bibliography

Aims/UNASSIGNED:We examined the effects of a statewide New York (NY) care management (CM) program for substance use disorder (SUD), Managed Addiction Treatment Services (MATS), on SUD treatment services' utilization and spending among patients with a recent history of high Medicaid spending and among those for whom a predictive algorithm indicates a higher probability of outlier spending in the following year. Methods/UNASSIGNED:We applied difference-in-difference analyses with propensity score matching using NY Medicaid claims data and a state registry of SUD-treatment episodes from 2006 to 2009. A total of 1263 CM enrollees with high SUD treatment spending (>$10K) in the prior year and a matched comparison group were included in the analysis. Crisis care utilization for SUD (detoxification and hospitalizations), outpatient SUD treatment, and Medicaid spending were examined over 12 months among both groups. CM effects among predicted high-future-spending patients (HFS) were also analyzed. Results/UNASSIGNED:CM increased outpatient SUD treatment visits by approximately 10.5 days (95% CI = 0.9, 20.0). CM crisis care and spending outcomes were not statistically different from comparison since both conditions had comparable pre-post declines. Conversely, CM significantly reduced SUD treatment spending by approximately $955 (95% CI = -1518, -391) and reduced days of detox utilization by about 1.0 days (95% CI = -1.9, -0.1) among HFS. Conclusion/UNASSIGNED:Findings suggest that CM can reduce SUD treatment spending and utilization when targeted at patients with a greater likelihood of high future spending, indicating the potential value of predictive models to select CM patients.

Unintentional overdose deaths, most involving opioids, have eclipsed all other causes of US deaths for individuals less than 50 years of age. An estimated 2.4 to 5 million individuals have opioid use disorder (OUD) yet a minority receive treatment in a given year. Medications for OUD (MOUD) are the gold standard treatment for OUD however early dropout remains a major challenge for improving clinical outcomes. A Cascade of Care (CoC) framework, first popularized as a public health accountability strategy to stem the spread of HIV, has been adapted specifically for OUD. The CoC framework has been promoted by the NIH and several states and jurisdictions for organizing quality improvement efforts through clinical, policy, and administrative levers to improve OUD treatment initiation and retention. This roadmap details CoC design domains based on available data and potential linkages as individual state agencies and health systems typically rely on limited datasets subject to diverse legal and regulatory requirements constraining options for evaluations. Both graphical decision trees and catalogued studies are provided to help guide efforts by state agencies and health systems to improve data collection and monitoring efforts under the OUD CoC framework.

BACKGROUND/UNASSIGNED:Integrated care programs that systematically and comprehensively address both behavioral and physical health may improve patient outcomes. However, there are few examples of such programs in addiction treatment settings. This article is a practical implementation report describing the implementation of an integrated care program into two opioid treatment programs (OTPs). METHOD/UNASSIGNED:Strategies used to implement integrated care into two OTPs included external facilitation, quality improvement (QI) processes, staff training, and an integrated organizational structure. Service, implementation, and client outcomes were examined using qualitative interviews with program staff (n  =  16), program enrollment data, and client outcome data (n  =  593) on mental health (MH), physical health, and functional indicators. RESULTS/UNASSIGNED:Staff found the program to generally be acceptable and appropriate, but also noted that the new services added to already busy workflows and more staffing were needed to fully reach the program's potential. The program had a high level of penetration (∼60%-70%), enrolling over 1,200 clients. Staff noted difficulties in connecting clients with some services. Client general functioning and MH symptoms improved, and heavy smoking decreased. The organizational structure and QI activities provided a strong foundation for interactive problem-solving and adaptations that were needed during implementation. CONCLUSIONS/UNASSIGNED:Providing medical and behavioral health treatment services in the same clinic using coordinated treatment teams, also known as integrated care, improves outcomes among those with chronic physical and behavioral health conditions. However, there are few practical examples of implementation of such programs in addiction treatment settings, which are promising, yet underutilized settings for integrated care programs. A multi-sectoral team used quality improvement (QI) and implementation strategies to implement integrated care into two opioid treatment programs (OTPs). The program enrolled over 1,200 clients and client general functioning and mental health (MH) symptoms improved, and heavy smoking decreased. Qualitative interviews provided important information about the barriers, facilitators, and context around implementation of this program. The OTP setting provided a strong foundation to build integrated care, but careful consideration of new workflows and changes in philosophy for staff, as well as ongoing training and supports for staff, are necessary. This project may help to advance the implementation of integrated care in OTPs by identifying barriers and facilitators to implementation, lessons learned, as well as providing a practical example of potentially useful QI and implementation strategies.

BACKGROUND:Individuals that have both diabetes and substance use disorder (SUD) are more likely to have adverse health outcomes and are less likely to receive high quality diabetes care, compared with patients without coexisting SUD. Care management programs for patients with chronic diseases, such as diabetes and SUD, have been associated with improvements in the process and outcomes of care. OBJECTIVE:The aim was to assess the impact of having coexisting SUD on diabetes process of care metrics. RESEARCH DESIGN/METHODS:Preintervention/postintervention triple difference analysis. SUBJECTS/METHODS:Participants in the New York State Medicaid Health Home (NYS-HH) care management program who have diabetes and a propensity-matched comparison group of nonparticipants (N=37,260). MEASURES/METHODS:Process of care metrics for patients with diabetes: an eye (retinal) exam, HbA1c test, medical attention (screening laboratory measurements) for nephropathy, and receiving all 3 in the past year. RESULTS:Before enrollment in NYS-HH, individuals with comorbid SUD had fewer claims for eye exams and HbA1c tests compared with those without comorbid SUD. Diabetes process of care improvements associated with NYS-HH enrollment were larger among those with comorbid SUD [eye exam: adjusted odds ratio (AOR)=1.08; 95% confidence interval (CI): 1.01-1.15]; HbA1c test: AOR=1.20 (95% CI: 1.11-1.29); medical attention for nephropathy: AOR=1.21 (95% CI: 1.12-1.31); all 3: AOR=1.09 (95% CI: 1.02-1.16). CONCLUSIONS:Individuals with both diabetes and SUD may benefit moderately more from care management than those without comorbid SUD. Individuals with both SUD and diabetes who are not enrolled in care management may be missing out on crucial diabetes care.

BACKGROUND:The New York State (NYS) Level of Care for Alcohol and Drug Treatment Referral (LOCADTR) was launched in 2015 to determine the most appropriate level of care for individuals seeking addiction treatment. However, research has not studied its predictive validity. We examined the predictive validity of the LOCADTR recommendation for outpatient treatment by determining whether those who entered a level of care (LOC) concordant with the LOCADTR recommendation differed in continuous engagement in treatment compared to those who entered a discordant LOC. METHODS:The study combined data from two NYS administrative sources, the LOCADTR database and a treatment registry. The study examined characteristics of the clients who entered concordant and discordant LOCs as well as tested for differences in continuous engagement of clients who entered discordant care compared to a propensity score-matched comparison group of clients who entered the concordant LOC. RESULTS:Among clients for whom the LOCADTR recommended the outpatient LOC, concordant clients who entered the outpatient LOC were more likely to be retained in care than discordant clients who entered the inpatient LOC (aOR = 0.53; 95% CI = 0.36, 0.77). We did not observe statistical differences in continuous engagement among clients who were recommended for outpatient and entered that LOC versus those who entered the outpatient rehabilitation LOC instead (aOR = 1.08; 95% CI = 0.90, 1.30). CONCLUSION/CONCLUSIONS:This study provides support for predictive validity of recommendations stemming from the LOCADTR. Clients, treatment providers, and payers benefited from a tool that provides clear guidance and predictively valid recommendations for treatment placement. The study found that clients were more likely to be retained in treatment for 6 months or longer if admitted to outpatient care, as recommended by the LOCADTR algorithm, rather than to inpatient treatment. One factor accounting for the longer engagement in outpatient care is the low level of continuity of care among patients being discharged from inpatient treatment.

INTRODUCTION/BACKGROUND:New York State implemented a Health Homes (HH) care management program to facilitate access to health services for Medicaid enrollees with multiple chronic conditions. This study assessed the impact of HH on health care utilization outcomes among enrollees who have substance use disorder (SUD). METHODS:Using HH enrollment data and Medicaid claims data 1 year before and after enrollment, this study compared HH enrollees who enrolled between 2012 and 2014 to a statistically matched comparison group created with propensity score methods. Analyses used generalized gamma models, logistic regression models, and difference-in-differences analyses to assess the impact of HH on general (all-cause) health care and SUD-related outpatient, emergency department (ED), hospitalization, and detoxification utilization as well as total Medicaid cost. RESULTS:The sample consisted of 41,229 HH enrollees and a comparison group of 39,471 matched patients. HH-enrolled patients who had SUD utilized less SUD-related ED services (average marginal effect (AME) = -1.85; 95% CI = -2.45, -1.24), SUD-related hospitalizations (AME = -1.28; 95% CI: -1.64, -0.93), and detoxification services (AME = -1.30; 95% CI = -1.64, -0.96), relative to the comparison group during the 1 year post-HH enrollment. SUD-related outpatient visits did not change significantly (AME = -0.28; 95% CI = -0.76, 0.19) for enrollees, but general health care outpatient visits increased (AME = 1.63; 95% CI = 1.33, 1.93). CONCLUSION/CONCLUSIONS:These findings provide preliminary evidence that care management programs can decrease ED visits and hospitalizations among people with SUD.

BACKGROUND:The misuse of and addiction to opioids is a national crisis that affects public health as well as social and economic welfare. There is an urgent need for strategies to improve opioid use disorder treatment quality (e.g., 6-month retention). Substance use disorder treatment programs are challenged by limited resources and a workforce that does not have the requisite experience or education in quality improvement methods. The purpose of this study is to test a multicomponent clinic-level intervention designed to aid substance use disorder treatment clinics in implementing quality improvement processes to improve high-priority indicators of treatment quality for opioid use disorder. METHODS:A stepped-wedge randomized controlled trial with 30 outpatient treatment clinics serving approximately 2000 clients with opioid use disorder each year will test whether a clinic-level measurement-driven, quality improvement intervention, called Coaching for Addiction Recovery Enhancement (CARE), improves (a) treatment process quality measures (use of medications for opioid use disorder, in-treatment symptom and therapeutic progress, treatment retention) and (b) recovery outcomes (substance use, health, and healthcare utilization). The CARE intervention will have the following components: (1) staff clinical training and tools, (2) quality improvement and change management training, (3) external facilitation to support implementation and sustainability of quality improvement processes, and (4) an electronic client-reported treatment progress tool to support data-driven decision making and clinic-level quality measurement. The study will utilize multiple sources of data to test study aims, including state administrative data, client-reported survey and treatment progress data, and staff interview and survey data. DISCUSSION/CONCLUSIONS:This study will provide the field with a strong test of a multicomponent intervention to improve providers' capacity to make systematic changes tied to quality metrics. The study will also result in training and materials that can be shared widely to increase quality improvement implementation and enhance clinical practice in the substance use disorder treatment system. TRIAL REGISTRATION/BACKGROUND:Trial # NCT04632238NCT04632238 registered at clinicaltrials.gov on 17 November 2020.

Objective: Although the rapid increase in opioid use disorders (OUD) and concurrent increase in Hepatitis C virus (HCV) in the United States is well-documented, little is known about HCV testing among high-risk populations. We examine patterns of HCV testing across OUD treatment settings for individuals with OUD in New York. Methods: Using 2014 New York Medicaid claims data, we identified OUD diagnosis, OUD treatment (methadone, buprenorphine, naltrexone, other treatment (inpatient or outpatient non-medication-based psychosocial treatment, such as psychotherapy) and no treatment) utilization and HCV-testing status among beneficiaries. We performed multivariable logistic regression to identify factors associated with HCV screening across OUD treatment settings. Results: 79,764 individuals with OUD diagnoses were identified in 2014. The prevalence of HCV screening was 32.4%, 16.2%, 20.6%, 16.8%, and 18.1% for those receiving methadone, buprenorphine, naltrexone, other treatment, and no treatment, respectively. In the adjusted logistic regression, those receiving any OUD treatment had greater odds of being screened, with the highest odds among methadone clients. Conclusions: Engagement in medication for OUD is associated with increased HCV testing. Findings indicate the importance of access to medication-based treatment for OUD and a need to further improve HCV screening rates.