Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM
| Autor: | Daijin Kim, Se-Hyun Chang, Ki-Hoon Kim, In Young Choi, Dong-Jin Chang, Wona Choi, Yeon-Woog Chung, Soo-Jeong Ko, Jaekwon Kim |
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| Rok vydání: | 2021 |
| Předmět: |
Technology
QH301-705.5 Computer science QC1-999 media_common.quotation_subject OMOP CDM Field (computer science) Consistency (statistics) Health care Statistics General Materials Science Quality (business) Biology (General) Healthcare data QD1-999 Instrumentation multisite study media_common Fluid Flow and Transfer Processes data quality assessment business.industry Physics Process Chemistry and Technology General Engineering healthcare data Engineering (General). Civil engineering (General) Computer Science Applications Chemistry Validation rule Data quality Observational study TA1-2040 business |
| Zdroj: | Applied Sciences Volume 11 Issue 19 Applied Sciences, Vol 11, Iss 9188, p 9188 (2021) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app11199188 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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