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.

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.

Algorithms are regularly used to identify persons living with diagnosed HIV (PLWDH) in the Medicaid data. To the authors knowledge, there are no published reports of an HIV algorithm from claims codes that have been compared to an HIV surveillance system to assess its sensitivity, specificity, positive predictive value and negative predictive value in identifying PLWDH. The aims of this study were to: 1) develop an algorithm that could identify PLWDH in New York Medicaid data from 2006-2014; and 2) validate this algorithm using the New York HIV surveillance system. Classification and regression tree analysis identified 16 nodes that were combined to create a case-finding algorithm with five criteria. This algorithm identified 86,930 presumed PLWDH, of which 88.0% were verified by matching to the surveillance system. The algorithm yielded a sensitivity of 94.5%, a specificity of 94.5%, a positive predictive value of 88.0%, and a negative predictive value of 97.6%. This validated algorithm has the potential to improve the utility of the Medicaid data for assessing health outcomes and programmatic interventions.

BACKGROUND AND OBJECTIVES/OBJECTIVE:This paper investigates the prevalence and predictors for opioid use disorder (OUD) pharmacotherapy utilization for Medicaid-insured patients with human immunodeficiency virus (HIV) in New York. METHODS:We identified patients with HIV and OUD in 2014 in the New York State Medicaid claims data (n = 5621). The claims were used to identify individual client medication for addiction treatment (MAT) utilization, demographic information, and other medical and psychiatric health conditions. The logistic regression analyses were performed to explore the potential predictors of MAT service utilization among people with HIV and OUD. RESULTS:Of 5621 identified patients with HIV and OUD, 3647 (65%) received some type of MAT. Eighty-seven percent of treated patients received methadone while 10% received buprenorphine and 3% utilized both the therapies. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE/CONCLUSIONS:A substantial number of patients with HIV and OUD did not receive MAT. Findings suggest that there are opportunities to improve OUD care for patients with HIV and OUD, particularly among the younger generation, blacks, individuals living outside of New York City, and among those with serious psychiatric conditions. This initial study suggests that an additional research is needed to better understand how the gap in care affects this population. (Am J Addict 2020;29:151-154).