Administrative data algorithms to identify diagnosis and treatment-related measures in patients with multiple myeloma A validation study

BACKGROUND: Analyses of secondary data (e.g., insurance claims) togenerate real-world evidence often entail use of algorithms to identify,define, and study key measures (e.g., diagnosis [dx] date; receipt oftherapy).OBJECTIVE: To systematically assess the validity of claims data-basedalgorithms used to identify multiple myeloma (MM) dx and treatmentrelatedmeasures.METHODS: A retrospective, observational study was conducted usingclaims data from Geisinger Health (GH), an integrated health caredelivery system in Pennsylvania. In a cohort of patients with MM fromJanuary 2004-November 2016, algorithms were used to identify anddefine measures related to dx and ensuing therapy. Measures fromclaims data were adjudicated against a medical record review (MRR)to evaluate the validity of the claims-based algorithms. Validity ofclaims-based study measures were evaluated by assessing positive predictivevalues (PPV) and proportions. PPV was calculated as the numberof true-positives divided by the sum of true- and false-positives.RESULTS: Of 352 patients with 2 MM dx claims 30 days apart, MRRwas conducted for 177 patients who met other selection criteria (e.g.,12-month pre-index period without MM dx). Most (68.9%) were 65years old and 54.8% were male. Of the patients reviewed, 131 hada confirmed MM dx, per the MRR, with a PPV of 74.0% (95% CI:67.680.5%). Among these, 84.7% (95% CI: 78.6-90.9%) of patientshad an initial MM dx date from claims within 30 days of the initialMM dx date ascertained from the MRR. From the MRR, 89.3% ofpatients were confirmed to receive first-line (1L) therapy versus 82.4%of patients identified using the claims-based algorithms. The resultingPPV was 94.4% (95% CI: 90.1-98.8%). Based on the claims-based algorithms,56.5%, 22.2%, and 21.3% of patients received doublet, steroidonly, and triplet regimens, respectively. The MRR showed that 63.3%,26.5%, and 6.8% received doublet, triplet, and steroid only regimens,respectively. The proportion having the same 1L regimens identifiedfrom claims and MRR was 66.7% (95% CI: 57.8-75.6%); those withthe same bortezomib- or lenalidomide-based 1L regimens was 77.8%(95% CI: 68.2-87.4%). Among patients receiving 1L therapy, 45.4%and 48.7% had evidence of progression from claims and MRR, respectively(resulting PPV: 63.3% [95% CI: 49.8-76.8%]).CONCLUSIONS: Using GH data, the claims-based algorithms hada PPV/proportion of >70% for identifying true MM dx, receipt of1L therapy, and 1L bortezomib- or lenalidomide-based regimens.Previous validation studies have reported similar PPVs.

Parikh, R., Clancy, Z., Candrilli, S., & Parikh, K. (2018). Administrative data algorithms to identify diagnosis and treatment-related measures in patients with multiple myeloma: A validation study. Journal of Managed Care and Specialty Pharmacy, 24(4-a), S29. [C21]. DOI: 10.18553/jmcp.2018.24.4-a.s1