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The American Journal of Managed Care June 2017
Comparative Effectiveness and Costs of Insulin Pump Therapy for Diabetes
Ronald T. Ackermann, MD, MPH; Amisha Wallia, MD, MS; Raymond Kang, MA; Andrew Cooper, MPH; Theodore A. Prospect, FSA, MAAA; Lewis G. Sandy, MD, MBA; and Deneen Vojta, MD
Radical Prostatectomy Innovation and Outcomes at Military and Civilian Institutions
Jeffrey J. Leow, MBBS, MPH; Joel S. Weissman, PhD; Linda Kimsey, PhD; Andrew Hoburg, PhD; Lorens A. Helmchen, PhD; Wei Jiang, MS; Nathanael Hevelone, MPH; Stuart R. Lipsitz, ScD; Louis L. Nguyen, MD, MPH, MBA; and Steven L. Chang, MD, MS
Patients' Views of a Behavioral Intervention Including Financial Incentives
Judy A. Shea, PhD; Aderinola Adejare, BA; Kevin G. Volpp, MD, PhD; Andrea B. Troxel, ScD; Darra Finnerty, MPH; Karen Hoffer, BS; Thomas Isaac, MD, MPH, MBA; Meredith Rosenthal, PhD; Thomas D. Sequist, MD, MPH; and David A. Asch, MD, MBA
How Do Medicare Advantage Beneficiary Payments Vary With Tenure?
Paul D. Jacobs, PhD, and Eamon Molloy, PhD
Patient Ratings of Veterans Affairs and Affiliated Hospitals
Paul A. Heidenreich, MD, MS; Aimee Zapata, MS; Lisa Shieh, MD, PhD; Nancy Oliva, PhD, RN; and Anju Sahay, PhD
Using "Roll-up" Measures in Healthcare Quality Reports: Perspectives of Report Sponsors and National Alliances
Jennifer L. Cerully, PhD; Steven C. Martino, PhD; Lise Rybowski, MBA; Melissa L. Finucane, PhD; Rachel Grob, PhD; Andrew M. Parker, PhD; Mark Schlesinger, PhD; Dale Shaller, MPA; and Grant Martsolf, PhD, MPH, RN
Does the Offer of Free Prescriptions Increase Generic Prescribing?
Bruce Stuart, PhD; Franklin Hendrick, PhD; J. Samantha Dougherty, PhD; and Jing Xu, PhD
Patients' Views on Price Shopping and Price Transparency
Hannah L. Semigran, BA; Rebecca Gourevitch, MS; Anna D. Sinaiko, PhD; David Cowling, PhD; and Ateev Mehrotra, MD, MPH
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Heterogeneity of Nonadherent Buprenorphine Patients: Subgroup Characteristics and Outcomes
Charles Ruetsch, PhD; Joseph Tkacz, MS; Vijay R. Nadipelli, MS, BPharm; Brenna L. Brady, PhD; Naoko Ronquest, PhD; Hyong Un, MD; and Joseph Volpicelli, MD, PhD

Heterogeneity of Nonadherent Buprenorphine Patients: Subgroup Characteristics and Outcomes

Charles Ruetsch, PhD; Joseph Tkacz, MS; Vijay R. Nadipelli, MS, BPharm; Brenna L. Brady, PhD; Naoko Ronquest, PhD; Hyong Un, MD; and Joseph Volpicelli, MD, PhD
Patient and treatment heterogeneity were characterized within a sample of nonadherent buprenorphine members; an improved understanding of these factors may optimize patient—treatment matching and intervention efforts.
A total of 477 members qualified for the current study, with 172 (36%) categorized as adherent and the balance of 305 (64%) categorized as nonadherent. Results for costs, relapse, and MPR grouping analyses may be viewed in Table 2. Nonadherent members were significantly more likely than adherent members to evidence relapse by an OUD inpatient hospitalization or OUD ED visit (P <.05) and were significantly more likely to show any relapse (30.5% vs 15.7%; P <.001). Further, nonadherent members incurred significantly higher office, outpatient hospital, ED, inpatient, and total medical costs compared with adherent members (P <.05). 

Regarding specific levels of adherence within the nonadherent group, the MPR 0.00 to 0.19 subgroup (n = 92) was the largest, followed by the 0.20 to 0.39 group (n = 80). Although not presented in Table 2, the relapse rate among the nonadherent MPR subgroups revealed a steady decrease with increased adherence to B-MAT: the 0.00 to 0.19 group had the highest relapse rate at 46.7%, followed by the 0.20 to 0.39 (32.5%), 0.40 to 0.59 (27.9%), and 0.60 to 0.79 groups (15.4%). Furthermore, cost analyses using the MPR subgroups revealed significant linear trends for outpatient hospital, inpatient hospital, and ED costs, with decreased costs associated with greater MPR (P <.05). 

Clinical Subgroup Results

The ETDNC (n = 33) and IA (n = 30) subgroups were examined to further characterize the heterogeneity of adherent and nonadherent B-MAT members. Table 3 displays the relationship among the ETDNC, adherent, and balance of the nonadherent cases on healthcare expenditure, although no statistical testing was performed for lack of power. Relationships were in the expected direction, with the nonadherent cases having greater outpatient hospital, ED, inpatient hospital, and total medical costs compared with ETDNC members. Conversely, ETDNC members had similar or lower costs compared with adherent cases on the same measures. 

As expected, both the adherent and ETDNC groups had increased pharmacy costs compared with nonadherent cases. ETDNC cases were also significantly more likely than the balance of the adherence group to be aged 18 to 25 years (45.5% vs 26.7%) and appeared to be in better overall health (CCI score, 0.06 vs 0.33; P <.05; data not shown). The ETDNC group filled fewer prescriptions (11.6 ± 9.6) than all other groups, including both the adherent group (31.2 ± 20.4) and the balance of the nonadherent group (22.9 ± 23.1). 

A total of 30 nonadherent members qualified for the IA group, with the majority (53.3%) falling into the 0.60 to 0.79 MPR group. Compared with the balance of the nonadherence group, IA members had a significantly lower CCI score during the pre- (0.07 vs 0.23) and post periods (0.07 vs 0.33; P <.05) and were more likely to experience an OUD status change compared with the balance of the nonadherent group (13.3% vs 4.5%; P <.05). Based on these results, ETNDC members were placed into the overall adherent group for remaining analyses, while IA members remained in the nonadherent group.

Enhanced Adherence Results

Demographics. The inclusion of the ETDNC cases into the adherent group resulted in a final sample of 205 (43%) categorized as adherent, with the balance of 272 (57%) categorized as nonadherent. Demographic, service use, cost, and relapse results by the enhanced adherence grouping may be viewed in Table 4. Members were predominately males in their early 30s, with the adherent group being older (34.0 vs 31.6 years; P <.05). A greater proportion of nonadherent members were aged 18 to 25 years (47.8% vs 29.8%; P <.001). Adherent members were significantly more likely to be the primary plan subscriber compared with nonadherent members, who were more likely to be a dependent (P <.01). Within the nonadherent group, the MPR 0.00 to 0.19 subgroup (n = 92) was the largest of the MPR-based subgroups, followed by the 0.20 to 0.39 (n = 67), 0.60 to 0.79 (n = 58), and 0.40 to 0.59 MPR (n = 55) subgroups.

Relapse. The overall nonadherent group was more than 2.5 times more likely to relapse than the adherent group (34.2% vs 13.2%, P <.001). Nonadherent members were significantly more likely than adherent members to evidence 3 of the 4 relapse proxies (P <.05); the exception was OUD status change. The most commonly observed indicator of relapse in the nonadherent group was OUD inpatient hospitalization (25.0%).

Healthcare service use and cost. During the pre-period, healthcare service utilization and total pharmacy, medical, and overall healthcare costs were similar across adherent and nonadherent groups (P >.05). During the post period, adherent members had significantly more office visits, prescriptions, and accrued greater pharmacy costs, whereas the nonadherent group evidenced significantly greater outpatient hospital, ED, and inpatient visits and increased total medical costs (P <.05). Results of the multivariate models revealed that the nonadherent group incurred significantly decreased pharmacy costs (adjusted means $1930 vs $4818) but higher total medical costs ($8148 vs $3723) and total healthcare costs ($10,638 vs $7581; P <.01) compared with the adherent group.

MPR Grouping Results

Compared with the balance of the overall nonadherence group, the 0.00 to 0.19 group was significantly less likely to be the primary subscriber (30.4% vs 45.6%), whereas the 0.60 to 0.79 group was significantly more likely to be the primary subscriber (51.7% vs 37.4%) and was also less likely to be aged 18 to 25 years (34.5% vs 51.4%; P <.05). Those in the 0.00 to 0.19 MPR group were significantly more likely than other nonadherent members to relapse (46.7% vs 27.8%); specifically, they were more likely to evidence OUD hospitalizations (35.9% vs 19.4%) and OUD ED visits (15.2% vs 6.1%; P <.01). In contrast, those in the 0.60 to 0.79 MPR group were significantly less likely to relapse than other nonadherent members (13.8% vs 60.3%). Across the MPR groups, the results of 1-way analyses of variance of logged-transformed costs revealed statistically significant linear contrasts on 4 of 7 cost metrics: pharmacy, outpatient hospital, inpatient hospital, and total medical (P <.05) (Figure). Pharmacy costs increased with MPR, but the remaining cost indicators decreased with increasing amounts of medication on hand, with the MPR 0.60 to 0.79 group approximating the adherent group (MPR >0.80).  

Relapse Grouping Results

Compared with members who did not evidence a relapse (n = 357), members who experienced any type of relapse (n = 120) incurred significantly lower pharmacy costs ($2103 vs $3868) but more than 3 times the medical ($24,866 vs $7132) and twice the total healthcare costs ($26,969 vs $11,000; P <.001). Relapsing members were more likely to be nonadherent with B-MAT compared with those who had not relapsed (77.5% vs 50.1%; P <.001) and were also more likely to be in the MPR 0.00 to 0.19 subgroup (35.8% vs 13.7%; P <.001). By contrast, members who did not experience relapse were significantly more likely to be in the MPR 0.60 to 0.79 subgroup compared with relapsers (14.0% vs 6.7%; P <.001). 

DISCUSSION

Member demographics, relapse, healthcare service utilization, and costs associated with B-MAT nonadherence were examined in administrative claims from a commercially insured sample of OUD patients. Nonadherent members were younger and less likely to be employed, consistent with previously published predictors of nonadherence.19,21,22 Adherent members were more likely to use office- and pharmacy-based services compared with nonadherent members; the latter group incurred significantly greater high-cost healthcare services, consistent with the increased rate of relapse observed within this group. Overall, the nonadherent group demonstrated a 1.5-fold increase in total annual healthcare costs and significantly higher medical costs compared with adherent members. Although the relationship between B-MAT adherence and healthcare costs has previously been demonstrated,17 this study extended these findings by further stratifying the nonadherent group based on MPR and examining clinically meaningful subgroups. 

A significant linear trend demonstrating a negative relationship between adherence and outpatient, inpatient, and total medical costs was revealed, indicating that incremental increases in B-MAT adherence are associated with healthcare savings. The rate of relapse also decreased as adherence across the MPR subgroups increased. Differences in demographics among the MPR subgroups were also observed; nonadherent members within the 0.00 to 0.59 MPR groups were younger and more likely to be the dependent of the primary subscriber compared with adherent members. These characteristics are in notable contrast to those of the nonadherent 0.60 to 0.79 MPR group, who were older, more likely to be the primary subscriber, and significantly less likely to relapse. Conversely, the 0.00 to 0.19 MPR group was the most likely to evidence a relapse event and exhibited the highest medical and lowest pharmacy costs.

Treatment and demographic characteristics of the sample were also examined within 2 clinical subgroups of the larger adherent and nonadherent populations: the IA and ETDNC groups. Comparison of the demographic and treatment characteristics associated with these groups, as opposed to the MPR subgroups and larger adherence groups, highlighted the heterogeneity within the adherence groups and identified particular patterns of B-MAT utilization that may be associated with nonadherence. 

The IA group included members who evidenced multiple starts and stops with B-MAT, which clinically could be indicative of patients either taking drug holidays or forming the belief that they were no longer in need of B-MAT. Members in the IA group predominately fell into the 0.60 to 0.79 MPR group. Despite their relative high rate of adherence, their demographics, relapse rate, and cost of care diverged from the balance of the 0.60 to 0.79 MPR subgroup and more closely resembled the characteristics of members in the other nonadherent MPR subgroups. These results indicate that assessment of MPR alone is insufficient to estimate a patient’s risk of relapse and potential success with B-MAT. 

 
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