{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T21:23:43Z","timestamp":1790717023745,"version":"4.1.0"},"reference-count":15,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2005,12,12]],"date-time":"2005-12-12T00:00:00Z","timestamp":1134345600000},"content-version":"vor","delay-in-days":3024,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Arthritis &amp; Rheumatism"],"published-print":{"date-parts":[[1997,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p><jats:italic>Objective<\/jats:italic>. To examine the sensitivity and positive predictive value of Medicare physician claims for select rheumatic conditions managed in rheumatology specialty practices.<\/jats:p><jats:p><jats:italic>Methods<\/jats:italic>. Eight rheumatologists in 3 states abstracted 378 patient office records to obtain information on diagnosis and office procedures. The Medicare Part B physician claims for these patient visits were obtained from the Health Care Financing Administration. The sensitivity of the claims data for a specific diagnosis was calculated as the proportion of all patients whose office records for a particular visit documented that diagnosis and who also had physician claims for that visit which identified that diagnosis. The positive predictive value was evaluated in a separate sample of 331 patient visits identified in Medicare physician claims. The positive predictive value of the claims data for a specific diagnosis was calculated as the proportion of patients with that diagnosis coded in the claims for a particular visit who also had the diagnosis documented in the medical record for that visit.<\/jats:p><jats:p><jats:italic>Results<\/jats:italic>. Ninety percent of abstracted office medical records were matched successfully with Medicare physician claims. The sensitivity of the Medicare physician claims was 0.90 (95% confidence interval [CI] 0.85\u20130.95) for rheumatoid arthritis (RA), 0.85 (95% CI 0.73\u20130.97) for systemic lupus erythematosus (SLE), and 0.85 (95% CI 0.78\u20131.0) for aspiration or injection procedures. The sensitivity for osteoarthritis (OA) of the hip or knee was \u22640.50 if 5\u2010digit codes specifying anatomic site were required. The sensitivity for fibromyalgia (FM) was 0.48 (95% Cl 0.28\u20130.68). The positive predictive values were at least 0.90 for RA, SLE, and aspiration or injection procedures. Positive predictive values for FM and the 5\u2010digit site\u2010specific codes for OA of the knee were 0.83 (95% CI 0.66\u20131.0) and 0.88 (95% CI 0.75\u20131.0), respectively, while the positive predictive value of the 5\u2010digit site\u2010specific codes for OA of the hip was zero (95% CI 0\u20130.26). The positive predictive value of OA at any site was 0.83 (95% CI 0.76\u20130.90).<\/jats:p><jats:p><jats:italic>Conclusion<\/jats:italic>. In specialty practice, Medicare physician claims had high sensitivity and positive predictive value for RA, SLE, OA without specification of anatomic site, and injection or aspiration procedures. The claims had lower sensitivity and predictive value for FM and for OA of the hip. The accuracy of Medicare physician claims for other conditions and in the primary care setting requires further investigation.<\/jats:p>","DOI":"10.1002\/art.1780400908","type":"journal-article","created":{"date-parts":[[2007,2,14]],"date-time":"2007-02-14T12:40:20Z","timestamp":1171456820000},"page":"1594-1600","source":"Crossref","is-referenced-by-count":122,"title":["Sensitivity and positive predictive value of medicare part B physician claims for rheumatologic diagnoses and procedures"],"prefix":"10.1002","volume":"40","author":[{"given":"Jeffrey N.","family":"Katz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jane","family":"Barrett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew H.","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aane M.","family":"Bacon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Herbert","family":"Kaplan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raphael I.","family":"Kieval","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen M.","family":"Lindsey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"W. Neal","family":"Roberts","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel M.","family":"Sheff","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert T.","family":"Spencer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arthur L.","family":"Weaver","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John A.","family":"Baron","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2005,12,12]]},"reference":[{"key":"e_1_2_1_2_2","unstructured":"RomanoPS LuftHS:Getting the Most Out of Messy Data: Problems and Approaches for Dealing with Large Administrative Data Sets. 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