Multidisciplinary Medication Therapy Management and Hospital Readmission in Patients Undergoing Maintenance Dialysis: A Retrospective Cohort Study.

RATIONALE & OBJECTIVES: Dialysis patients frequently experience medication-related problems. We studied the association of a multidisciplinary medication therapy management (MTM) with 30-day readmission rates. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Maintenance dialysis patients discharged home from acute-care hospitals between May 2016 and April 2017 who returned to End-Stage Renal Disease Seamless Care Organization dialysis clinics after discharge were eligible. Patients who were readmitted within 3 days, died, or entered hospice within 30 days were excluded. EXPOSURE: MTM consisting of nurse medication reconciliation, pharmacist medication review, and nephrologist oversight was categorized into 3 levels of intensity: no MTM, partial MTM (defined as an incomplete MTM process), or full MTM (defined as a complete MTM process). OUTCOME: The primary outcome was 30-day readmission. ANALYTICAL APPROACH: Time-varying Prentice, Williams, and Peterson total time hazards models explored associations between MTM and time to readmission after adjusting for age, race, sex, diabetes comorbidity, albumin level, vascular access type, kidney failure cause, dialysis vintage and modality, marital status, home medications, frequent prior hospitalizations, length of stay, discharge diagnoses, hierarchical condition category, and facility standardized hospitalization rates. Propensity score matching was performed to examine the robustness of the associations in a comparison between the full- and no-MTM exposure groups on time to readmission. RESULTS: Among 1,452 discharges, 586 received no MTM, 704 received partial MTM, and 162 received full MTM; 30-day readmission rates were 29%, 19%, and 11%, respectively (P < 0.001). Compared with no MTM, discharges with full MTM had the lowest time-varying risk for readmission within 30 days (HR, 0.26; 95% CI, 0.15-0.45); discharges with partial MTM also had lower readmission risk (HR, 0.50; 95% CI, 0.37-0.68). In propensity score-matched sensitivity analysis, full MTM was associated with lower 30-day readmission risk (HR, 0.20; 95% CI, 0.06-0.69). LIMITATIONS: Reliance on observational data. Residual bias and confounding. CONCLUSIONS: MTM services following hospital discharge were associated with fewer 30-day readmissions in dialysis patients. Randomized controlled studies evaluating different MTM delivery models and cost-effectiveness in dialysis populations are warranted.

Behavioral Health Screening among Massachusetts Children Receiving Medicaid.

OBJECTIVE: To assess the impact of a Massachusetts Medicaid policy change (the Children's Behavioral Health Initiative; CBHI, which required and reimbursed behavioral health [BH] screening with standardized tools at well child visits and developed intensive home- and community-based BH services) on primary care practice examining the relationship of BH screening to subsequent BH service utilization. STUDY DESIGN: Using a repeated cross-sectional design, our 2010 and 2012 Medicaid study populations each included 2000 children/adolescents under the age of 21 years. For each year, the population was randomly selected and stratified into 4 age groups, with 500 members selected per group. Two data sources were used: medical records and Medicaid claims. RESULTS: The CBHI had a large impact on formal BH screening and treatment utilization among children/adolescents enrolled in Medicaid. Screening increased substantially (73%: 2010; 74%: 2012) since the baseline/premandate period (2007) when only 4% of well child visits included a formal screen. BH utilization increased among those formally screened but decreased among those with informal assessments. CONCLUSIONS: CBHI implementation transformed the relationship between primary care and BH services. Changes in regulation and payment resulted in widespread BH screening in Massachusetts primary care practices caring for children/adolescents on Medicaid.

Risk Factors for Relapse and Higher Costs Among Medicaid Members with Opioid Dependence or Abuse: Opioid Agonists, Comorbidities, and Treatment History.

Clinical trials show that opioid agonist therapy (OAT) with methadone or buprenorphine is more effective than behavioral treatments, but state policymakers remain ambivalent about covering OAT for long periods. We used Medicaid claims for 52,278 Massachusetts Medicaid beneficiaries with a diagnosis of opioid abuse or dependence between 2004 and 2010 to study associations between use of methadone, buprenorphine or other behavioral health treatment without OAT, and time to relapse and total healthcare expenditures. Cox Proportional Hazards ratios for patients treated with either methadone or buprenorphine showed approximately 50% lower risk of relapse than behavioral treatment without OAT. Expenditures per month were from $153 to $233 lower for OAT episodes compared to other behavioral treatment. Co-occurring alcohol abuse/dependence quadrupled the risk of relapse, other non-opioid abuse/dependence doubled the relapse risk and severe mental illness added 80% greater risk compared to those without each of those disorders. Longer current treatment episodes were associated with lower risk of relapse. Relapse risk increased as prior treatment exposure increased but prior treatment was associated with slightly lower total healthcare expenditures. These findings suggest that the effectiveness of OAT that has been demonstrated in clinical trials persists at the population level in a less controlled setting and that OAT is associated with lower total healthcare expenditures compared to other forms of behavioral treatment for patients with opioid addiction. Co-occurring other substance use and mental illness exert strong influences on cost and risk of relapse, suggesting that individuals with these conditions need more comprehensive treatment.

Adherence to Buprenorphine Treatment Guidelines in a Medicaid Program.

BACKGROUND: Buprenorphine is the most frequently prescribed medication for treating substance use disorders in the United States, but few studies have evaluated the structure of treatment delivered in real-world settings. The purpose of this study is to investigate adherence to current buprenorphine treatment guidelines using administrative data for Massachusetts Medicaid. METHODS: We identified buprenorphine treatment episodes beginning in 2009 through pharmacy claims. We then used service claims to identify treatment-related physician, behavioral, and laboratory services received in the induction, stabilization, and maintenance phases of these treatment episodes. Rates of service utilization were compared with those recommended in treatment guidelines. RESULTS: A total of 3674 treatment episodes met inclusion criteria, representing 3005 unique Medicaid beneficiaries. Liver enzymes were tested in 47.3% of episodes, but testing for hepatitis C (23.2%), hepatitis B (19.6%), and human immunodeficiency virus (HIV; 13.7%) was less frequent. Adherence to recommended physician visit frequency was 37.6% during induction, 39.7% during stabilization, and 51.2% during maintenance. For behavioral care, adherence rates were 40.0% during induction, 41.2% during stabilization, and 41.0% during maintenance. Rates of toxicology testing met or exceeded recommendations in just over 60% of episodes in the induction (61.1%), stabilization (62.1%), and maintenance (61.4%) phases. Although rates varied by treatment phase, substantial proportions of episodes showed no evidence of physician visits (27.2-42.8%), behavioral care (44.3-60.0%), and toxicology screening (25.3-39.0%). CONCLUSIONS: Our data suggest that there is significant variability in the structure of buprenorphine treatment provided to Massachusetts Medicaid beneficiaries, and that half or less of episodes include physician and behavioral visits at recommended frequencies. The use of administrative data for this type of analysis is limited by the potential for missing or inaccurate data. More research is needed to establish the levels of services most closely associated with positive outcomes to help guide providers in offering the highest-quality care.

The impact of prior authorization on buprenorphine dose, relapse rates, and cost for Massachusetts Medicaid beneficiaries with opioid dependence.

OBJECTIVE: To assess the impact of a 2008 dose-based prior authorization policy for Massachusetts Medicaid beneficiaries using buprenorphine + naloxone for opioid addiction treatment. Doses higher than 16 mg required progressively more frequent authorizations. DATA SOURCES: Mediciaid claims for 2007 and 2008 linked with Department of Public Health (DPH) service records. STUDY DESIGN: We conducted time series for all buprenorphine users and a longitudinal cohort analysis of 2,049 individuals who began buprenorphine treatment in 2007. Outcome measures included use of relapse-related services, health care expenditures per person, and buprenorphine expenditures. DATA COLLECTION/EXTRACTION METHODS: We used ICD-9 codes and National Drug Codes to identify individuals with opioid dependence who filled prescriptions for buprenorphine. Medicaid and DPH data were linked with individual identifiers. PRINCIPAL FINDINGS: Individuals using doses >24 mg decreased from 16.5 to 4.1 percent. Relapses increased temporarily for some users but returned to previous levels within 3 months. Buprenorphine expenditures decreased but total expenditures did not change significantly. CONCLUSION: Prior authorization policies strategically targeted by dose level appear to successfully reduce use of higher than recommended buprenorphine doses. Savings from these policies are modest and may be accompanied by brief increases in relapse rates. Lower doses may decrease diversion of buprenorphine.

Case selection for a Medicaid chronic care management program.

Medicaid agencies are beginning to turn to care management to reduce costs and improve health care quality. One challenge is selecting members at risk of costly, preventable service utilization. Using claims data from the State of Vermont, we compare the ability of three pre-existing health risk predictive models to predict the top 10 percent of members with chronic conditions: Chronic Illness and Disability Payment System (CDPS), Diagnostic Cost Groups (DCG), and Adjusted Clinical Groups Predictive Model (ACG-PM). We find that the ACG-PM model performs best. However, for predicting the very highest-cost members (e.g, the 99th percentile), the DCG model is preferred.