Economic Impact of Adherence to Pain Treatment Guidelines in Chronic Pain Patients.

OBJECTIVES: This research compared health care resource use (HCRU) and costs for pharmacotherapy prescribing that was adherent vs nonadherent to published pain management guidelines. Conditions included osteoarthritis (OA) and gout (GT) for nociceptive/inflammatory pain, painful diabetic peripheral neuropathy (pDPN) and post-herpetic neuralgia (PHN) for neuropathic pain, and fibromyalgia (FM) for sensory hypersensitivity pain. METHODS: This retrospective cohort study used claims from MarketScan Commercial and Medicare Databases identifying adults newly diagnosed with OA, GT, pDPN, PHN, or FM during July 1, 2006, to June 30, 2013, with 12-month continuous coverage before and after initial (index) diagnosis. Patients were grouped according to their pharmacotherapy pattern as adherent, nonadherent, or "unsure" according to published pain management guidelines using a claims-based algorithm. Adherent and nonadherent populations were compared descriptively and using multivariate statistical analyses for controlling bias. RESULTS: Final cohort sizes were 441,465 OA, 76,361 GT, 10,645 pDPN, 4,010 PHN, and 150,321 FM, with adherence to guidelines found in 51.1% of OA, 25% of GT, 59.5% of pDPN, 54.9% of PHN, and 33.5% of FM. Adherent cohorts had significantly (P < 0.05) fewer emergency department (ED) visits and lower proportions with hospitalizations or ED visits. Mean health care costs increased following diagnosis across all conditions; however, adherent cohorts had significantly lower increases in adjusted costs pre-index to postindex (OA $5,286 vs $9,532; GT $3,631 vs $7,873; pDPN $9,578 vs $16,337; PHN $2,975 vs $5,146; FM $2,911 vs $3,708; all P < 0.001; adherent vs nonadherent, respectively). CONCLUSIONS: Adherence to pain management guidelines was associated with significantly lower HCRU and costs compared with nonadherence to guidelines.

Development of a novel algorithm to determine adherence to chronic pain treatment guidelines using administrative claims.

OBJECTIVE: To develop a claims-based algorithm for identifying patients who are adherent versus nonadherent to published guidelines for chronic pain management. METHODS: Using medical and pharmacy health care claims from the MarketScan® Commercial and Medicare Supplemental Databases, patients were selected during July 1, 2010, to June 30, 2012, with the following chronic pain conditions: osteoarthritis (OA), gout (GT), painful diabetic peripheral neuropathy (pDPN), post-herpetic neuralgia (PHN), and fibromyalgia (FM). Patients newly diagnosed with 12 months of continuous medical and pharmacy benefits both before and after initial diagnosis (index date) were categorized as adherent, nonadherent, or unsure according to the guidelines-based algorithm using disease-specific pain medication classes grouped as first-line, later-line, or not recommended. Descriptive and multivariate analyses compared patient outcomes with algorithm-derived categorization endpoints. RESULTS: A total of 441,465 OA patients, 76,361 GT patients, 10,645 pDPN, 4,010 PHN patients, and 150,321 FM patients were included in the development of the algorithm. Patients found adherent to guidelines included 51.1% for OA, 25% for GT, 59.5% for pDPN, 54.9% for PHN, and 33.5% for FM. The majority (~90%) of patients adherent to the guidelines initiated therapy with prescriptions for first-line pain medications written for a minimum of 30 days. Patients found nonadherent to guidelines included 30.7% for OA, 6.8% for GT, 34.9% for pDPN, 23.1% for PHN, and 34.7% for FM. CONCLUSION: This novel algorithm used real-world pharmacotherapy treatment patterns to evaluate adherence to pain management guidelines in five chronic pain conditions. Findings suggest that one-third to one-half of patients are managed according to guidelines. This method may have valuable applications for health care payers and providers analyzing treatment guideline adherence.

Evaluating increased resource use in fibromyalgia using electronic health records.

OBJECTIVE: The management of fibromyalgia (FM), a chronic musculoskeletal disease, remains challenging, and patients with FM are often characterized by high health care resource utilization. This study sought to explore potential drivers of all-cause health care resource utilization and other factors associated with high resource use, using a large electronic health records (EHR) database to explore data from patients diagnosed with FM. METHODS: This was a retrospective analysis of de-identified EHR data from the Humedica database. Adults (≥18 years) with FM were identified based on ≥2 International Classification of Diseases, Ninth Revision codes for FM (729.1) ≥30 days apart between January 1, 2008 and December 31, 2012 and were required to have evidence of ≥12 months continuous care pre- and post-index; first FM diagnosis was the index event; 12-month pre- and post-index reporting periods. Multivariable analysis evaluated relationships between variables and resource utilization. RESULTS: Patients were predominantly female (81.4%), Caucasian (87.7%), with a mean (standard deviation) age of 54.4 (14.8) years. The highest health care resource utilization was observed for the categories of "medication orders" and "physician office visits," with 12-month post-index means of 21.2 (21.5) drug orders/patient and 15.1 (18.1) office visits/patient; the latter accounted for 73.3% of all health care visits. Opioids were the most common prescription medication, 44.3% of all patients. The chance of high resource use was significantly increased (P<0.001) 26% among African-Americans vs Caucasians and for patients with specific comorbid conditions ranging from 6% (musculoskeletal pain or depression/bipolar disorder) to 21% (congestive heart failure). Factors significantly associated with increased medications ordered included being female (P<0.001) and specific comorbid conditions (P<0.05). CONCLUSION: Physician office visits and pharmacotherapy orders were key drivers of all-cause health care utilization, with demographic factors, opioid use, and specific comorbidities associated with resource intensity. Health systems and providers may find their EHRs to be a useful tool for identifying and managing resource-intensive FM patients.