Development of stroke identification algorithm for claims data using the multicenter stroke registry database.
BACKGROUND:Identifying acute ischemic stroke (AIS) among potential stroke cases is crucial for stroke research based on claims data. However, the accuracy of using the diagnostic codes of the International Classification of Diseases 10th revision was less than expected. METHODS:From the National Hea...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2020-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0228997 |
| _version_ | 1819029882362920960 |
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| author | Jun Yup Kim Keon-Joo Lee Jihoon Kang Beom Joon Kim Moon-Ku Han Seong-Eun Kim Heeyoung Lee Jong-Moo Park Kyusik Kang Soo Joo Lee Jae Guk Kim Jae-Kwan Cha Dae-Hyun Kim Tai Hwan Park Moo-Seok Park Sang-Soon Park Kyung Bok Lee Hong-Kyun Park Yong-Jin Cho Keun-Sik Hong Kang-Ho Choi Joon-Tae Kim Dong-Eog Kim Wi-Sun Ryu Jay Chol Choi Mi-Sun Oh Kyung-Ho Yu Byung-Chul Lee Kwang-Yeol Park Ji Sung Lee Sujung Jang Jae Eun Chae Juneyoung Lee Hee-Joon Bae CRCS-K investigators |
| author_facet | Jun Yup Kim Keon-Joo Lee Jihoon Kang Beom Joon Kim Moon-Ku Han Seong-Eun Kim Heeyoung Lee Jong-Moo Park Kyusik Kang Soo Joo Lee Jae Guk Kim Jae-Kwan Cha Dae-Hyun Kim Tai Hwan Park Moo-Seok Park Sang-Soon Park Kyung Bok Lee Hong-Kyun Park Yong-Jin Cho Keun-Sik Hong Kang-Ho Choi Joon-Tae Kim Dong-Eog Kim Wi-Sun Ryu Jay Chol Choi Mi-Sun Oh Kyung-Ho Yu Byung-Chul Lee Kwang-Yeol Park Ji Sung Lee Sujung Jang Jae Eun Chae Juneyoung Lee Hee-Joon Bae CRCS-K investigators |
| author_sort | Jun Yup Kim |
| collection | DOAJ |
| description | BACKGROUND:Identifying acute ischemic stroke (AIS) among potential stroke cases is crucial for stroke research based on claims data. However, the accuracy of using the diagnostic codes of the International Classification of Diseases 10th revision was less than expected. METHODS:From the National Health Insurance Service (NHIS) claims data, stroke cases admitted to the hospitals participating in the multicenter stroke registry (Clinical Research Collaboration for Stroke in Korea, CRCS-K) during the study period with principal or additional diagnosis codes of I60-I64 on the 10th revision of International Classification of Diseases were extracted. The datasets were randomly divided into development and validation sets with a ratio of 7:3. A stroke identification algorithm using the claims data was developed and validated through the linkage between the extracted datasets and the registry database. RESULTS:Altogether, 40,443 potential cases were extracted from the NHIS claims data, of which 31.7% were certified as AIS through linkage with the CRCS-K database. We selected 17 key identifiers from the claims data and developed 37 conditions through combinations of those key identifiers. The key identifiers comprised brain CT, MRI, use of tissue plasminogen activator, endovascular treatment, carotid endarterectomy or stenting, antithrombotics, anticoagulants, etc. The sensitivity, specificity, and diagnostic accuracy of the algorithm were 81.2%, 82.9%, and 82.4% in the development set, and 80.2%, 82.0%, and 81.4% in the validation set, respectively. CONCLUSIONS:Our stroke identification algorithm may be useful to grasp stroke burden in Korea. However, further efforts to refine the algorithm are necessary. |
| first_indexed | 2024-12-21T06:21:19Z |
| format | Article |
| id | doaj.art-d6542a959b5a4c61b7ac482c1c289d55 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-21T06:21:19Z |
| publishDate | 2020-01-01 |
| publisher | Public Library of Science (PLoS) |
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| spelling | doaj.art-d6542a959b5a4c61b7ac482c1c289d552022-12-21T19:13:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01152e022899710.1371/journal.pone.0228997Development of stroke identification algorithm for claims data using the multicenter stroke registry database.Jun Yup KimKeon-Joo LeeJihoon KangBeom Joon KimMoon-Ku HanSeong-Eun KimHeeyoung LeeJong-Moo ParkKyusik KangSoo Joo LeeJae Guk KimJae-Kwan ChaDae-Hyun KimTai Hwan ParkMoo-Seok ParkSang-Soon ParkKyung Bok LeeHong-Kyun ParkYong-Jin ChoKeun-Sik HongKang-Ho ChoiJoon-Tae KimDong-Eog KimWi-Sun RyuJay Chol ChoiMi-Sun OhKyung-Ho YuByung-Chul LeeKwang-Yeol ParkJi Sung LeeSujung JangJae Eun ChaeJuneyoung LeeHee-Joon BaeCRCS-K investigatorsBACKGROUND:Identifying acute ischemic stroke (AIS) among potential stroke cases is crucial for stroke research based on claims data. However, the accuracy of using the diagnostic codes of the International Classification of Diseases 10th revision was less than expected. METHODS:From the National Health Insurance Service (NHIS) claims data, stroke cases admitted to the hospitals participating in the multicenter stroke registry (Clinical Research Collaboration for Stroke in Korea, CRCS-K) during the study period with principal or additional diagnosis codes of I60-I64 on the 10th revision of International Classification of Diseases were extracted. The datasets were randomly divided into development and validation sets with a ratio of 7:3. A stroke identification algorithm using the claims data was developed and validated through the linkage between the extracted datasets and the registry database. RESULTS:Altogether, 40,443 potential cases were extracted from the NHIS claims data, of which 31.7% were certified as AIS through linkage with the CRCS-K database. We selected 17 key identifiers from the claims data and developed 37 conditions through combinations of those key identifiers. The key identifiers comprised brain CT, MRI, use of tissue plasminogen activator, endovascular treatment, carotid endarterectomy or stenting, antithrombotics, anticoagulants, etc. The sensitivity, specificity, and diagnostic accuracy of the algorithm were 81.2%, 82.9%, and 82.4% in the development set, and 80.2%, 82.0%, and 81.4% in the validation set, respectively. CONCLUSIONS:Our stroke identification algorithm may be useful to grasp stroke burden in Korea. However, further efforts to refine the algorithm are necessary.https://doi.org/10.1371/journal.pone.0228997 |
| spellingShingle | Jun Yup Kim Keon-Joo Lee Jihoon Kang Beom Joon Kim Moon-Ku Han Seong-Eun Kim Heeyoung Lee Jong-Moo Park Kyusik Kang Soo Joo Lee Jae Guk Kim Jae-Kwan Cha Dae-Hyun Kim Tai Hwan Park Moo-Seok Park Sang-Soon Park Kyung Bok Lee Hong-Kyun Park Yong-Jin Cho Keun-Sik Hong Kang-Ho Choi Joon-Tae Kim Dong-Eog Kim Wi-Sun Ryu Jay Chol Choi Mi-Sun Oh Kyung-Ho Yu Byung-Chul Lee Kwang-Yeol Park Ji Sung Lee Sujung Jang Jae Eun Chae Juneyoung Lee Hee-Joon Bae CRCS-K investigators Development of stroke identification algorithm for claims data using the multicenter stroke registry database. PLoS ONE |
| title | Development of stroke identification algorithm for claims data using the multicenter stroke registry database. |
| title_full | Development of stroke identification algorithm for claims data using the multicenter stroke registry database. |
| title_fullStr | Development of stroke identification algorithm for claims data using the multicenter stroke registry database. |
| title_full_unstemmed | Development of stroke identification algorithm for claims data using the multicenter stroke registry database. |
| title_short | Development of stroke identification algorithm for claims data using the multicenter stroke registry database. |
| title_sort | development of stroke identification algorithm for claims data using the multicenter stroke registry database |
| url | https://doi.org/10.1371/journal.pone.0228997 |
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