| Autor: |
Sunyang Fu, Maria Vassilaki, Omar A. Ibrahim, Ronald C. Petersen, Sandeep Pagali, Jennifer St Sauver, Sungrim Moon, Liwei Wang, Jungwei W. Fan, Hongfang Liu, Sunghwan Sohn |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Digital Health, Vol 4 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2673-253X |
| DOI: |
10.3389/fdgth.2022.958539 |
| Popis: |
The secondary use of electronic health records (EHRs) faces challenges in the form of varying data quality-related issues. To address that, we retrospectively assessed the quality of functional status documentation in EHRs of persons participating in Mayo Clinic Study of Aging (MCSA). We used a convergent parallel design to collect quantitative and qualitative data and independently analyzed the findings. We discovered a heterogeneous documentation process, where the care practice teams, institutions, and EHR systems all play an important role in how text data is documented and organized. Four prevalent instrument-assisted documentation (iDoc) expressions were identified based on three distinct instruments: Epic smart form, questionnaire, and occupational therapy and physical therapy templates. We found strong differences in the usage, information quality (intrinsic and contextual), and naturality of language among different type of iDoc expressions. These variations can be caused by different source instruments, information providers, practice settings, care events and institutions. In addition, iDoc expressions are context specific and thus shall not be viewed and processed uniformly. We recommend conducting data quality assessment of unstructured EHR text prior to using the information. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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