Validation of claims-based algorithms to identify patients with psoriasis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Hemin | - |
dc.contributor.author | He, Mengdong | - |
dc.contributor.author | Cho, Soo-Kyung | - |
dc.contributor.author | Bessette, Lily | - |
dc.contributor.author | Tong, Angela Y. | - |
dc.contributor.author | Merola, Joseph F. | - |
dc.contributor.author | Wegrzyn, Lani R. | - |
dc.contributor.author | Kilpatrick, Ryan D. | - |
dc.contributor.author | Kim, Seoyoung C. | - |
dc.date.accessioned | 2021-07-30T04:43:02Z | - |
dc.date.available | 2021-07-30T04:43:02Z | - |
dc.date.created | 2021-07-14 | - |
dc.date.issued | 2021-07 | - |
dc.identifier.issn | 1053-8569 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/991 | - |
dc.description.abstract | Purpose Accurately identifying patients with psoriasis (PsO) is crucial for generating real-world evidence on PsO disease course and treatment utilization. Methods We developed nine claims-based algorithms for PsO using a combination of the International Classification of Diseases (ICD)-9 codes, specialist visit, and medication dispensing using Medicare linked to electronic health records data (2013-2014) in two healthcare provider networks in Boston, Massachusetts. We calculated positive predictive value (PPV) and 95% confidence interval (CI) for each algorithm using the treating physician's diagnosis of PsO via chart review as the gold standard. Among the confirmed PsO cases, we assessed their PsO disease activity. Results The nine claims-based algorithms identified 990 unique patient records. Of those, 918 (92.7%) with adequate information were reviewed. The PPV of the algorithms ranged from 65.1 to 82.9%. An algorithm defined as >= 1 ICD-9 diagnosis code for PsO and >= 1 prescription claim for topical vitamin D agents showed the highest PPV (82.9%). The PPV of the algorithm requiring >= 2 ICD-9 diagnosis codes and >= 1 prescription claim for PsO treatment excluding topical steroids was 81.1% but higher (82.5%) when >= 1 diagnosis was from a dermatologist. Among 411 PsO patients with adequate information on PsO disease activity in EHRs, 1.5-5.8% had no disease activity, 31.3-36.8% mild, and 26.9-35.1% moderate-to-severe across the algorithms. Conclusions Claims-based algorithms based on a combination of PsO diagnosis codes and dispensing for PsO-specific treatments had a moderate-to-high PPV. These algorithms can serve as a useful tool to identify patients with PsO in future real-world data pharmacoepidemiologic studies. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.title | Validation of claims-based algorithms to identify patients with psoriasis | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Cho, Soo-Kyung | - |
dc.identifier.doi | 10.1002/pds.5229 | - |
dc.identifier.scopusid | 2-s2.0-85102869288 | - |
dc.identifier.wosid | 000631493400001 | - |
dc.identifier.bibliographicCitation | PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, v.30, no.7, pp.868 - 874 | - |
dc.relation.isPartOf | PHARMACOEPIDEMIOLOGY AND DRUG SAFETY | - |
dc.citation.title | PHARMACOEPIDEMIOLOGY AND DRUG SAFETY | - |
dc.citation.volume | 30 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 868 | - |
dc.citation.endPage | 874 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Public, Environmental & Occupational Health | - |
dc.relation.journalResearchArea | Pharmacology & Pharmacy | - |
dc.relation.journalWebOfScienceCategory | Public, Environmental & Occupational Health | - |
dc.relation.journalWebOfScienceCategory | Pharmacology & Pharmacy | - |
dc.subject.keywordPlus | antipsoriasis agent | - |
dc.subject.keywordPlus | biological product | - |
dc.subject.keywordPlus | steroid | - |
dc.subject.keywordPlus | tacrolimus | - |
dc.subject.keywordPlus | vitamin D derivative | - |
dc.subject.keywordPlus | aged | - |
dc.subject.keywordPlus | Article | - |
dc.subject.keywordPlus | claims based algorithm | - |
dc.subject.keywordPlus | confidence interval | - |
dc.subject.keywordPlus | dermatologist | - |
dc.subject.keywordPlus | disease activity | - |
dc.subject.keywordPlus | disease course | - |
dc.subject.keywordPlus | electronic health record | - |
dc.subject.keywordPlus | female | - |
dc.subject.keywordPlus | health care personnel | - |
dc.subject.keywordPlus | health care utilization | - |
dc.subject.keywordPlus | human | - |
dc.subject.keywordPlus | ICD-9 | - |
dc.subject.keywordPlus | major clinical study | - |
dc.subject.keywordPlus | male | - |
dc.subject.keywordPlus | medicare | - |
dc.subject.keywordPlus | patient identification | - |
dc.subject.keywordPlus | predictive value | - |
dc.subject.keywordPlus | prescription | - |
dc.subject.keywordPlus | priority journal | - |
dc.subject.keywordPlus | psoriasis | - |
dc.subject.keywordPlus | ultraviolet phototherapy | - |
dc.subject.keywordPlus | algorithm | - |
dc.subject.keywordPlus | factual database | - |
dc.subject.keywordPlus | International Classification of Diseases | - |
dc.subject.keywordPlus | medicare | - |
dc.subject.keywordPlus | United States | - |
dc.subject.keywordAuthor | administrative claims data | - |
dc.subject.keywordAuthor | claims& | - |
dc.subject.keywordAuthor | #8208 | - |
dc.subject.keywordAuthor | based algorithm | - |
dc.subject.keywordAuthor | PsO | - |
dc.subject.keywordAuthor | psoriasis | - |
dc.subject.keywordAuthor | validation | - |
dc.identifier.url | https://onlinelibrary.wiley.com/doi/10.1002/pds.5229 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.