Inefficiencies in Osteoarthritis and Chronic Low Back Pain Management | Page 2
Published Online: October 23, 2013
Margaret K. Pasquale, PhD; Robert Dufour, PhD; Ashish V. Joshi, PhD; Andrew T. Reiners, MD; David Schaaf, MD; Jack Mardekian, PhD; George A. Andrews, MD, MBA, CPE; Nick C. Patel, PharmD, PhD, BCPP; and James Harnett, PharmD, MS
Pain-related costs were defined for all provider, facility, and pharmacy claims categories and summed over 365 days postindex for each of the 22 inefficiencies identified during the postindex period. For professional and facility claims, 100% of costs were counted if the OA or LBP diagnosis was documented in the primary position. For claims with OA or LBP in any secondary position, costs were apportioned based on number of listed diagnostic conditions that were consistent with the study by Goldberg and colleagues.8 For pharmacy claims, all postindex costs were summed for opioids, nonsteroidal anti-inflammatory drugs, antimigraine agents, antidepressants, antiepileptics/anticonvulsants, muscle relaxants, and steroids.
Once members with inefficiencies and associated costs were identified, the inefficiencies were rank-ordered from costliest to least costly. A member was allowed to have 1 or more inefficiencies; hence, mean costs of inefficiencies were not independent of each another. In order to determine whether the rankings were statistically significant, pairwise Wilcoxon signed rank tests were performed first within each inefficiency category and then for high-cost inefficiencies overall. The alpha value to achieve significance was adjusted via the Bonferroni method for the number of comparisons within each inefficiency category (15 comparisons for opioid use, 21 for miscellaneous drug use, and 28 for medical service use). In addition, members with and without inefficiencies were compared with respect to their postindex total pain-related healthcare costs. Generalized linear modeling of the log of the mean total 365-day postindex cost (adjusted to 2010 dollars) was performed on the following covariates: age, sex, geographic region, baseline RxRisk-V score, presence of an inefficiency, disease state (OA/CLBP and CLBP versus OA), presence of any of the top 10 medical comorbidities, and psychiatric comorbidity. The parameter estimates, Wald 95% confidence limits, exponentiated estimates, and Wald x2 test results were computed using the SAS PROC GENMOD procedure with log link function and gamma distribution (SAS Institute Inc, Cary, North Carolina). This approach to linear modeling is appropriate when modeling claim costs as both the gamma and claim costs distributions tend to approach a normal distribution.
Final sample sizes of 51,773 OA, 11,510 CLBP, and 5170 OA/CLBP members were available for analysis. We identified 46.9% of OA, 80.1% of CLBP, and 84.8% of OA/CLBP members as having at least 1 inefficiency measure postindex (Table 2). The mean number of inefficiencies per member with at least 1 inefficiency was highest for members with OA/ CLBP (2.65), followed by CLBP (2.23) and OA (1.73). Overall, 71% of the members with inefficiencies were identified as having an inefficiency from 1 category rather than multiple categories; only 4% of members with inefficiencies were identified with an inefficiency from all 3 categories.
Demographic and clinical characteristics of members with any of the inefficiencies versus members without inefficiencies are compared in Table 3. The mean age of members identified with inefficiencies was approximately 2 years less than the mean age of those without inefficiencies (P <.0001), and a lower percentage of these members lived in the South compared with members without inefficiencies (P <.0001). Members with inefficiencies had a significantly higher RxRisk-V score (P <.0001) and rates of psychiatric disorders than members without inefficiencies (in each case, P <.0001 except for alcohol abuse, for which there was no statistical difference between members). Among the top 10 comorbidities, rates of pain in joint (ICD-9-CM 719.4), as well as malaise and fatigue (ICD-9-CM 780.7) were higher among members with inefficiencies versus without (P <.0001).
The rank ordering by pain-related per member cost for the 7 highest cost inefficiency measures is reported in Table 4A. The highest cost inefficiency was repeated OA/LBP-related surgical procedures followed by OA/LBP-related inpatient admissions and excessive postsurgical opioid use. Per member costs for all 7 of the highest cost inefficiencies were significantly different than costs for members without inefficiencies (P <.0001 for all comparisons). Similar results were obtained when analyzing OA, CLBP, or OA/CLBP conditions separately (data not shown).
The rank ordering by total cost to the plan of inefficiency measures (Table 4B) resulted in a different set of high-cost measures driven by prevalence of inefficiencies in the population. Repeated diagnostic testing ($6215) and excessive OA/ LBP-related office visits ($4999) ranked in the top 2 positions, even though their per member costs were relatively low compared with the top 7 inefficiencies based on per member cost. Excessive postsurgical opioid use ($18,294) ranked high in terms of both per member cost and total plan cost.
Parameter estimates (including exponentiated for ease of interpretation) from generalized linear modeling for pain-related costs are reported in Table 5. The presence of any inefficiency was associated with adjusted costs that were more than 5-fold higher than costs associated with not having an inefficiency (P <.0001). Having OA/CLBP was associated with 16% higher pain-related costs than having OA (P <.0001), and CLBP was associated with 27% lower costs than OA (P <.0001). The presence of one of the top 10 comorbidities was associated with slightly lower costs (P <.0001), as was the presence of any one of the psychiatric comorbidities (P = .017).
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