Development and validation of a one year predictive model for secondary fractures in osteoporosis.

The number of osteoporosis-related fractures in the United States is no longer declining. Existing risk-based assessment tools focus on long-term risk. Payers and prescribers need additional tools to identify patients at risk for imminent fracture. We developed and validated a predictive model for secondary osteoporosis fractures in the year following an index fracture using administrative medical and pharmacy claims from the Optum Research Database and Symphony Health, PatientSource. Patients ≥50 years with a case-qualifying fracture identified using a validated claims-based algorithm were included. Logistic regression models were created with binary outcome of a second fracture versus no second fracture within a year of index fracture, with the goal of predicting second fracture occurrence. In the Optum Research Database, 197,104 patients were identified with a case-qualifying fracture (43% commercial, 57% Medicare Advantage). Using Symphony data, 1,852,818 met the inclusion/exclusion criteria. Average patient age was 70.09 (SD = 11.09) and 71.28 (SD = 14.24) years in the Optum Research Database and Symphony data, respectively. With the exception of history of falls (41.26% vs 18.74%) and opioid use (62.80% vs 46.78%), which were both higher in the Optum Research Database, the two populations were mostly comparable. A history of falls and steroid use, which were previously associated with increased fracture risk, continue to play an important role in secondary fractures. Conditions associated with bone health (liver disease), or those requiring medications that impact bone health (respiratory disease), and cardiovascular disease and stroke-which may share etiology or risk factors with osteoporosis fractures-were also predictors of imminent fractures. The model highlights the importance of assessment of patient characteristics beyond bone density, including patient comorbidities and concomitant medications associated with increased fall and fracture risk, in alignment with recently issued clinical guidelines for osteoporosis treatment.

Medical chart validation of an algorithm for identifying multiple sclerosis relapse in healthcare claims.

OBJECTIVE: Relapse is a common measure of disease activity in relapsing-remitting multiple sclerosis (MS). The objective of this study was to test the content validity of an operational algorithm for detecting relapse in claims data. METHODS: A claims-based relapse detection algorithm was tested by comparing its detection rate over a 1-year period with relapses identified based on medical chart review. According to the algorithm, MS patients in a US healthcare claims database who had either (1) a primary claim for MS during hospitalization or (2) a corticosteroid claim following a MS-related outpatient visit were designated as having a relapse. Patient charts were examined for explicit indication of relapse or care suggestive of relapse. Positive and negative predictive values were calculated. RESULTS: Medical charts were reviewed for 300 MS patients, half of whom had a relapse according to the algorithm. The claims-based criteria correctly classified 67.3% of patients with relapses (positive predictive value) and 70.0% of patients without relapses (negative predictive value; kappa 0.373: p < 0.001). Alternative algorithms did not improve on the predictive value of the operational algorithm. Limitations of the algorithm include lack of differentiation between relapsing-remitting MS and other types, and that it does not incorporate measures of function and disability. CONCLUSIONS: The claims-based algorithm appeared to successfully detect moderate-to-severe MS relapse. This validated definition can be applied to future claims-based MS studies.

Health care costs among individuals with chronic obstructive pulmonary disease within several large, multi-state employers.

OBJECTIVE: To estimate chronic obstructive pulmonary disease (COPD)-attributable medical resource utilization and health care costs among employed individuals and their covered dependents with COPD. METHOD: Retrospective health care claims analysis. Employees and dependents 40 to 63 years old with a diagnosis of COPD between January 1, 2001 and December 31, 2002 were matched to two separate control cohorts. Medical resource utilization and health care costs were compared between cohorts. RESULTS: A total of 6445 individuals with COPD were matched to each control cohort. Mean age was 55.1 years, and cohorts were approximately 50% men. COPD subjects had significantly higher utilization and adjusted pharmacy, medical, and total health care costs than both control cohorts (P < 0.001). CONCLUSIONS: COPD subjects had significantly higher utilization and costs than individuals without COPD. Thus, the economic burden of COPD is present in younger, working individuals, as well as in the older, retired population.