Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 성윤경 | - |
dc.date.accessioned | 2019-11-04T01:48:56Z | - |
dc.date.available | 2019-11-04T01:48:56Z | - |
dc.date.issued | 2019-05 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF RHEUMATIC DISEASES, v. 22, NO 5, Page. 890-896 | en_US |
dc.identifier.issn | 1756-1841 | - |
dc.identifier.issn | 1756-185X | - |
dc.identifier.uri | https://onlinelibrary.wiley.com/doi/full/10.1111/1756-185X.13470 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/111785 | - |
dc.description.abstract | Background To identify knee osteoarthritis (OA) patients among OA patients in the claims database. Methods All patients with OA diagnostic codes for any sites (M15 to M19) in 2014 were recruited from a single academic referral hospital. After excluding patients who had inflammatory arthritis or were less than 50 years of age, we identified data for the overall OA population. Radiographic knee OA of Kellgren and Lawrence grades >= 2 is considered the gold standard for knee OA, and we evaluated the sensitivity, specificity, and positive predictive value (PPV) of three operational definitions using the diagnostic codes in the claims database. The operational definitions were: (1) gonarthrosis (M17); (2) any site of OA (M15 to M19) with knee X-ray; and (3) (1) or (2). Results A total of 7959 OA patients were included in this study of whom 74.5% were women. The PPV of gonarthrosis (M17) was 0.67 (95% CI 0.65-0.69), and sensitivity was 0.44 (95% CI 0.42-0.46). The PPV and sensitivity of any OA site (M15 to M19) with knee X-ray were 0.65 (95% CI 0.62-0.67), and 0.37 (95% CI 0.35-0.39), respectively. When knee OA was defined as satisfying either of the two above definitions, PPV was 0.63 (95% CI 0.62-0.65) and sensitivity 0.55 (95% CI 0.53-0.57). Conclusions Knee OA patients can be identified in a claims database using the algorithms of gonarthrosis (M17) or any site of OA (M15 to M19) with a performed knee X-ray. | en_US |
dc.description.sponsorship | This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant number: HC15C3388). | en_US |
dc.language.iso | en | en_US |
dc.publisher | WILEY | en_US |
dc.subject | claims data | en_US |
dc.subject | diagnostic codes | en_US |
dc.subject | osteoarthritis | en_US |
dc.subject | validation | en_US |
dc.title | Validation of algorithms to identify knee osteoarthritis patients in the claims database | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1111/1756-185X.13470 | - |
dc.relation.page | 890-896 | - |
dc.relation.journal | INTERNATIONAL JOURNAL OF RHEUMATIC DISEASES | - |
dc.contributor.googleauthor | Park, Ha-Rim | - |
dc.contributor.googleauthor | Im, SeulGi | - |
dc.contributor.googleauthor | Kim, Hyoungyoung | - |
dc.contributor.googleauthor | Jung, Sun-Young | - |
dc.contributor.googleauthor | Kim, Dalho | - |
dc.contributor.googleauthor | Jang, Eun Jin | - |
dc.contributor.googleauthor | Sung, Yoon-Kyoung | - |
dc.contributor.googleauthor | Cho, Soo-Kyung | - |
dc.relation.code | 2019045065 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF MEDICINE[S] | - |
dc.sector.department | DEPARTMENT OF MEDICINE | - |
dc.identifier.pid | sungyk | - |
dc.identifier.orcid | https://orcid.org/0000-0001-6691-8939 | - |
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