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The American Journal of Managed Care October 2013
Dispensing Channel and Medication Adherence: Evidence Across 3 Therapy Classes
Reethi Iyengar, PhD, MBA, MHM; Rochelle Henderson, PhD, MPA; Jay Visaria, PhD, MPH; and Sharon Glave Frazee, PhD, MPH
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Zhannat Z. Nurgalieva, MD, PhD; Luisa Franzini, PhD; Robert O. Morgan, PhD; Sally W. Vernon, PhD; and Xianglin L. Du, MD, PhD
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Seth W. Glickman, MD, MBA; and Kevin A. Schulman, MD
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Inefficiencies in Osteoarthritis and Chronic Low Back Pain Management
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
Physician Capability to Electronically Exchange Clinical Information, 2011
Vaishali Patel, PhD, MPH; Matthew J. Swain, MPH; Jennifer King, PhD; and Michael F. Furukawa, PhD
Physician Assistants in American Medicine: The Half-Century Mark
James F. Cawley, MPH, PA-C; and Roderick S. Hooker, PhD, PA
How Do Providers Prioritize Prevention? A Qualitative Study
Jeffrey L. Solomon, PhD; Allen L. Gifford, MD; Steven M. Asch, MD; Nora Mueller, MAA; Colin M. Thomas, MD; John M. Stevens, MD; and Barbara G. Bokhour, PhD
Outcomes Among Chronically Ill Adults in a Medical Home Prototype
David T. Liss, PhD; Paul A. Fishman, PhD; Carolyn M. Rutter, PhD; David Grembowski, PhD; Tyler R. Ross, MA; Eric A. Johnson, MS; and Robert J. Reid, MD, PhD
Performance Measurement for People With Multiple Chronic Conditions: Conceptual Model
Erin R. Giovannetti, PhD; Sydney Dy, MD; Bruce Leff, MD; Christine Weston, PhD; Karen Adams, PhD, MT; Tom B. Valuck, MD, JD; Aisha T. Pittman, MPH; Caroline S. Blaum, MD; Barbara A. McCann, MSW; and Cynthia M. Boyd, MD, MPH

Inefficiencies in Osteoarthritis and Chronic Low Back Pain Management

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
This study identified inefficiencies in drug and medical service utilization related to pain management among Medicare members with osteoarthritis and chronic low back pain.
Objective: To identify inefficiencies in drug and medical service utilization related to pain management in patients with osteoarthritis and chronic low back pain.

Study Design: This retrospective cohort study applied revised measures of pain management inefficiencies to Humana Medicare members with osteoarthritis and/or chronic low back pain.

Methods: Subjects had either 2 or more claims for osteoarthritis on different days or 2 or more claims for low back pain 90 or more days apart, from January 1, 2008, to June 30, 2010, with the first occurrence assigned the index date. Inefficiencies were identified for 365 days postindex.Pain-related healthcare costs postindex were  compared between members with and without inefficiencies. A generalized linear model calculated adjusted costs per member controlling for age, sex, and comorbidities.

Results: Most members diagnosed with osteoarthritis, chronic low back pain, or both (N = 68,453) had at least 1 inefficiency measure (n = 37,863) during the postindex period. High per member costs were for repeated surgical procedures ($26,451) and  inpatient admissions ($19,372) compared with members without inefficiencies ($781; P <.0001). High total costs (prevalence times per member cost) were for repeated diagnostic testing and excessive office visits. Members with an inefficiency had adjusted  pain-related costs 5.42 times higher than those of members without an inefficiency (P <.0001).

Conclusions: Pain management inefficiencies are common and costly among Humana Medicare members with osteoarthritis and/or chronic low back pain. Further work by providers and payers is needed to determine benefits of member identification and early  intervention for these inefficiencies.

Am J Manag Care. 2013;19(10):816-823
This study demonstrates that most Medicare members with osteoarthritis or chronic low back pain experience inefficient pain management. High-cost inefficiencies need to be further explored to determine benefits of identifying members experiencing pain and providing early intervention.
  • High per member costs were observed with repeated surgical procedures and inpatient admissions related to osteoarthritis or low back pain. High total costs (prevalence multiplied by per member cost) were observed for repeated diagnostic testing and excessive office visits.
  • Members with 1 or more inefficiencies had adjusted pain-related healthcare costs that were 5.42 times those of members without inefficiencies (P <.0001).
Two forms of chronic pain, osteoarthritis (OA) and chronic low back pain (CLBP), have exceptionally high prevalence and associated healthcare costs in the United States. An estimated 13.9% of adults 25 years and older and 33.6% of adults 65 years and older are affected by OA1; and roughly a quarter of all adults in the United States suffer from CLBP during their lifetime.2 Associated healthcare costs for these diseases have been estimated at $48 billion for OA and $40 billion for back problems in 2005; collectively, musculoskeletal conditions ranked as the third-highest spending category among medical conditions in the United States.3 Given the high prevalence of and healthcare spending on musculoskeletal conditions, it is crucial for providers and payers to provide  appropriate and adequate pain management for these conditions. Exposure of potentially inefficient provider practices or patient behavior can aid providers and payers in providing appropriate care and reducing costs.

Sources of inefficiencies in pain management include underdiagnosis or inappropriate diagnosis, use of unnecessary procedures and tests,4-6 and improper use of medications.7 Although examples of such inefficiencies are numerous, very few studies have indicated how to identify patients experiencing suboptimal pain management and to quantify their associated healthcare costs. Goldberg and colleagues8 published measures of inefficiencies developed by an expert clinical panel (Patient Population Assessment to Identify Need [PAIN]) concerning pain management in patients with OA and/or low back pain (LBP). These indicators were then overlaid on a managed care database to identify members who were likely in need of better pain management.8 Additional analysis by Goldberg and colleagues9 demonstrated that total per member per month pain-related costs of members identified with any PAIN indicator of inefficiency ($843) were significantly higher than those for members not identified with an indicator of inefficiency ($121). 

The objective of the current study was to use Goldberg and colleagues’ PAIN indicators as a guide to develop inefficiency measures  applicable to a specific health insurance provider for Medicare members with OA and/or CLBP. With the information provided in this study, providers and payers will be able to focus on identified members to determine whether their painful conditions are being managed adequately and efficiently.


Study Data

This study utilized data from Humana’s SAS database, containing enrollment, medical, and pharmacy claims data for Humana’s Medicare membership. All data sources were merged using de-identified member identification. The finalized protocol was approved by an independent institutional review board.

Study Design

This was a retrospective cohort study using a claims database to evaluate OA and CLBP patients identified as having suboptimal management of pain based on inefficiency measures of prescription drug and medical service use (Table 1). Internal experts from Humana’s clinical and drug utilization review programs were consulted to review the Goldberg PAIN indicators8 and revise them based on clinical judgment. Patients with OA and/or CLBP were identified from January 1, 2008, to June 30, 2010. Each member’s date of first OA or LBP diagnosis was considered to be the index date, and members were required to have 365 days of continuous enrollment preindex and 365 days postindex.

Study Population

Members 18 years and older in Humana’s Medicare Advantage plans were included if they were identified with 2 or more claims for OA on different days and/or 2 or more claims for LBP in the primary diagnosis position that were 90 or more days apart to ensure the “chronic” nature of pain. The following International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code was used to identify OA: 715.xx. ICD-9-CM codes for LBP were 721.3, 721.42, 721.5-721.9x, 722.1x-722.2, 722.30, 722.32, 722.52, 722.6, 722.70, 722.73, 722.80, 722.83, 722.90, 722.93, 724.00, 724.02, 724.09, 724.2-724.6, 724.8, 724.9, 737.10-737.19, 737.2x, 737.3, 737.30, 738.4, 738.5, 793.3, 793.4, 756.10-756.19, 805.4, 805.6, 805.8, 846.x, 847.2, 847.3, 847.9, 739.3, 739.4, and 996.4. 

Members were excluded if they had pregnancy (ICD-9- CM 630.xx-679.xx, V22.xx, and V23.xx), cancer (ICD-9- CM 140.xx-172.xx and 174.xx-208.xx), organ transplant (ICD-9-CM V42.xx), rheumatoid arthritis (ICD-9-CM 714. xx), ankylosing spondylitis (ICD-9-CM 720.xx), human immunodeficiency virus infection (ICD-9-CM 042.xx), or sickle cell anemia (ICD-9-CM 282.6x) in the first or second diagnosis position. Members were also excluded if they resided in skilled nursing homes.

Statistical Analysis

Claims data of Humana Medicare members with OA, CLBP, or both conditions (hereafter OA/CLBP) were analyzed to identify individuals who met criteria for any inefficiency measures in Table 1. The count and percentage of members identified with each inefficiency measure during the postindex period were determined. Demographic and clinical characteristics ascertained during the preindex period were compared between members with and without inefficiencies identified postindex. Variables included age, sex, geographic region, top 10 comorbidities by 4-digit ICD-9-CM codes, psychiatric comorbidities, and the RxRisk-V comorbidity score.The RxRisk-V score10-14 is derived from drug claims data and thus can be applied to data from a narrow window of claims rather than the broader window typically necessary for medical–claims-based comorbidity scores.15 Accordingly, means were compared using 2-sample t tests, and count variables were compared using x2 tests.

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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