Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM
Healthcare data has economic value and is evaluated as such. Therefore, it attracted global attention from observational and clinical studies alike. Recently, the importance of data quality research emerged in healthcare data research. Various studies are being conducted on this topic. In this study...
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MDPI AG
2021-10-01
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| Online Access: | https://www.mdpi.com/2076-3417/11/19/9188 |
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| author | Ki-Hoon Kim Wona Choi Soo-Jeong Ko Dong-Jin Chang Yeon-Woog Chung Se-Hyun Chang Jae-Kwon Kim Dai-Jin Kim In-Young Choi |
| author_facet | Ki-Hoon Kim Wona Choi Soo-Jeong Ko Dong-Jin Chang Yeon-Woog Chung Se-Hyun Chang Jae-Kwon Kim Dai-Jin Kim In-Young Choi |
| author_sort | Ki-Hoon Kim |
| collection | DOAJ |
| description | Healthcare data has economic value and is evaluated as such. Therefore, it attracted global attention from observational and clinical studies alike. Recently, the importance of data quality research emerged in healthcare data research. Various studies are being conducted on this topic. In this study, we propose a DQ4HEALTH model that can be applied to healthcare when reviewing existing data quality literature. The model includes 5 dimensions and 415 validation rules. The four evaluation indicators include the net pass rate (NPR), weighted pass rate (WPR), net dimensional pass rate (NDPR), and weighted dimensional pass rate (WDPR). They were used to evaluate the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) at three medical institutions. These indicators identify differences in data quality between the institutions. The NPRs of the three institutions (A, B, and C) were 96.58%, 90.08%, and 90.87%, respectively, and the WPR was 98.52%, 94.26%, and 94.81%, respectively. In the quality evaluation of the dimensions, the consistency was 70.06% of the total error data. The WDPRs were 98.22%, 94.74%, and 95.05% for institutions A, B, and C, respectively. This study presented indices for comparing quality evaluation models and quality in the healthcare field. Using these indices, medical institutions can evaluate the quality of their data and suggest practical directions for decreasing errors. |
| first_indexed | 2024-03-10T07:06:10Z |
| format | Article |
| id | doaj.art-dfa7174460c244568dbe8038402759af |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T07:06:10Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-dfa7174460c244568dbe8038402759af2023-11-22T15:49:00ZengMDPI AGApplied Sciences2076-34172021-10-011119918810.3390/app11199188Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDMKi-Hoon Kim0Wona Choi1Soo-Jeong Ko2Dong-Jin Chang3Yeon-Woog Chung4Se-Hyun Chang5Jae-Kwon Kim6Dai-Jin Kim7In-Young Choi8Department of Biomedicine & Health Sciences, The Cathlic University of Korea, Seoul 06591, KoreaDepartment of Biomedicine & Health Sciences, The Cathlic University of Korea, Seoul 06591, KoreaDepartment of Biomedicine & Health Sciences, The Cathlic University of Korea, Seoul 06591, KoreaDepartment of Ophthalmology, Yeouido St. Mary’s Hospital, The Cathlic University of Korea, Seoul 06591, KoreaDepartment of Ophthalmology and Visual Science, St. Vincent’s Hospital, College of Medicine, The Cathlic University of Korea, Seoul 06591, KoreaDepartment of Medical Informatics, College of Medicine, The Cathlic University of Korea, Seoul 06591, KoreaDepartment of Medical Informatics, College of Medicine, The Cathlic University of Korea, Seoul 06591, KoreaDepartment of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Cathlic University of Korea, Seoul 06591, KoreaDepartment of Medical Informatics, College of Medicine, The Cathlic University of Korea, Seoul 06591, KoreaHealthcare data has economic value and is evaluated as such. Therefore, it attracted global attention from observational and clinical studies alike. Recently, the importance of data quality research emerged in healthcare data research. Various studies are being conducted on this topic. In this study, we propose a DQ4HEALTH model that can be applied to healthcare when reviewing existing data quality literature. The model includes 5 dimensions and 415 validation rules. The four evaluation indicators include the net pass rate (NPR), weighted pass rate (WPR), net dimensional pass rate (NDPR), and weighted dimensional pass rate (WDPR). They were used to evaluate the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) at three medical institutions. These indicators identify differences in data quality between the institutions. The NPRs of the three institutions (A, B, and C) were 96.58%, 90.08%, and 90.87%, respectively, and the WPR was 98.52%, 94.26%, and 94.81%, respectively. In the quality evaluation of the dimensions, the consistency was 70.06% of the total error data. The WDPRs were 98.22%, 94.74%, and 95.05% for institutions A, B, and C, respectively. This study presented indices for comparing quality evaluation models and quality in the healthcare field. Using these indices, medical institutions can evaluate the quality of their data and suggest practical directions for decreasing errors.https://www.mdpi.com/2076-3417/11/19/9188healthcare dataOMOP CDMmultisite studydata quality assessment |
| spellingShingle | Ki-Hoon Kim Wona Choi Soo-Jeong Ko Dong-Jin Chang Yeon-Woog Chung Se-Hyun Chang Jae-Kwon Kim Dai-Jin Kim In-Young Choi Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM Applied Sciences healthcare data OMOP CDM multisite study data quality assessment |
| title | Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM |
| title_full | Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM |
| title_fullStr | Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM |
| title_full_unstemmed | Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM |
| title_short | Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM |
| title_sort | multi center healthcare data quality measurement model and assessment using omop cdm |
| topic | healthcare data OMOP CDM multisite study data quality assessment |
| url | https://www.mdpi.com/2076-3417/11/19/9188 |
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