Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 조수경 | - |
dc.date.accessioned | 2021-11-02T00:22:25Z | - |
dc.date.available | 2021-11-02T00:22:25Z | - |
dc.date.issued | 2020-04 | - |
dc.identifier.citation | PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, v. 29, no. 4, page. 404-408 | en_US |
dc.identifier.issn | 1053-8569 | - |
dc.identifier.issn | 1099-1557 | - |
dc.identifier.uri | https://onlinelibrary.wiley.com/doi/10.1002/pds.4950 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/166103 | - |
dc.description.abstract | Purpose An increasing number of new medications are being developed and approved for psoriatic arthritis (PsA). To generate real-world evidence on comparative safety and effectiveness of these drugs, a claims-based algorithm that can accurately identify PsA is greatly needed. Methods To identify patients with PsA, we developed seven claims-based algorithms based on a combination of diagnosis codes and medication dispensing using the claims data from Medicare parts A/B/D linked to electronic medical records (2012-2014). Two physicians independently conducted a chart review using the treating physician's diagnosis of PsA as the gold standard. We calculated the positive predictive value (PPV) and 95% confidence intervals of each algorithm. Results Of the total 2157 records identified by the seven algorithms, 45% of the records had relevant clinical data to determine the presence of PsA. The PPV of the algorithms ranged from 75.2% (algorithm 1: >= 2 diagnosis codes for PsA and >= 1 diagnosis code for psoriasis) to 88.6% (algorithm 7: >= 2 diagnosis codes for PsA with >= 1 code by rheumatologist and >= 1 dispensing for PsA medication). Having >= 2 diagnosis codes and >= 1 dispensing for PsA medications (algorithm 6) also had PPV of 82.4%. Conclusions All seven claims-based algorithms demonstrated a moderately high PPV of 75% to 89% in identifying PsA. The use of >= 2 diagnosis codes plus >= 1 prescription claim for PsA appears to be a valid and efficient tool in identifying PsA patients in the claims data, while broader algorithms based on diagnoses without a prescription claim also have reasonably good PPVs. | en_US |
dc.description.sponsorship | Pfizer, Inc., Grant/Award Number: N/A | en_US |
dc.language.iso | en | en_US |
dc.publisher | WILEY | en_US |
dc.subject | claims database | en_US |
dc.subject | Medicare | en_US |
dc.subject | pharmacoepidemiology | en_US |
dc.subject | psoriasis | en_US |
dc.subject | psoriatic arthritis | en_US |
dc.title | Validation of claims-based algorithms for psoriatic arthritis | en_US |
dc.type | Article | en_US |
dc.relation.no | 4 | - |
dc.relation.volume | 29 | - |
dc.identifier.doi | 10.1002/pds.4950 | - |
dc.relation.page | 404-408 | - |
dc.relation.journal | PHARMACOEPIDEMIOLOGY AND DRUG SAFETY | - |
dc.contributor.googleauthor | Lee, Hemin | - |
dc.contributor.googleauthor | Ford, Julia A. | - |
dc.contributor.googleauthor | Jin, Yinzhu | - |
dc.contributor.googleauthor | Cho, Soo-Kyung | - |
dc.contributor.googleauthor | Santiago Ortiz, Adrian J. | - |
dc.contributor.googleauthor | Tong, Angela Y. | - |
dc.contributor.googleauthor | Kim, Seoyoung C. | - |
dc.relation.code | 2020049982 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF MEDICINE[S] | - |
dc.sector.department | DEPARTMENT OF MEDICINE | - |
dc.identifier.pid | skchomd | - |
dc.identifier.orcid | https://orcid.org/0000-0003-4493-8837 | - |
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