Accuracy of Medicare Claim–based Algorithm to Detect Breast, Prostate, or Lung Cancer Bone Metastases. Issue 12 (December 2017)

• Record Type: Journal Article
• Authors: Sathiakumar, Nalini; Delzell, Elizabeth; Yun, Huifeng; Jooste, Rene; Godby, Kelly; Falkson, Carla; Yong, Mellissa; Kilgore, Meredith L.
• Is Part Of: Medical care. Volume 55:Issue 12(2017)
• Publication Date: 2017-12
• Subjects: bone metastases -- Medicare -- claim-based -- breast -- prostate -- lung -- cancer; Economics, Medical -- Periodicals; Insurance, Health -- Periodicals; Santé, Services de -- Administration -- Périodiques; Soins médicaux -- Périodiques; Medical economics -- Periodicals; Health insurance -- Periodicals; Medical economics -- United States -- Periodicals; Health insurance -- United States -- Periodicals; Comprehensive Health Care -- Periodicals; Personal Health Services -- Periodicals; Gezondheidszorg; Économie de la santé -- Périodiques; Santé, Services de -- Périodiques; Health insurance; Medical economics; United States; Periodicals; 362.10973
• DOI: 10.1097/MLR.0000000000000539
• Languages: English
• ISSNs: 0025-7079

Abstract

Abstract : Background: We had previously developed an algorithm for Medicare claims data to detect bone metastases associated with breast, prostate, or lung cancer. This study was conducted to examine whether this algorithm accurately documents bone metastases on the basis of diagnosis codes in Medicare claims data. Methods: We obtained data from Medicare claims and electronic medical records of patients 65 years or older with a breast, prostate, or lung cancer diagnosis at a teaching hospital and/or affiliated clinics during 2005 or 2006. We calculated the sensitivity and positive predictive value (PPV) of our algorithm using medical records as the "gold standard." The κ statistic was used to measure agreement between claims and medical record data. Results: The agreement between claims and medical record data for bone metastases among breast, prostate, and lung cancer patients was 0.93, 0.90, and 0.69, respectively. The sensitivities of our algorithm for bone metastasis in patients with breast, prostate, and lung were 96.8% [95% confidence interval (CI)=83.8% to 99.4%], 91.7% (95% CI=78.2% to 97.1%), and 74.1% (95% CI=55.3% to 86.8%), respectively; and the PPVs were 90.9% (95% CI=76.4% to 96.9%), 91.7% (95% CI=78.2% to 97.1%), and 71.4% (95% CI=52.9% to 84.8%), respectively. Conclusions: The algorithm for detecting bone metastases in claims data had high sensitivity and PPV for breast and prostate cancer patients. Sensitivity and PPV were lower but still moderate for lung cancer patients. Abstract : Supplemental Digital Content is available in the text.