Examining the impact of data quality and completeness of electronic health records on predictions of patients’ risks of cardiovascular disease
To assess the extent of variation of data quality and completeness of electronic health records and impact on the robustness of risk predictions of incident cardiovascular disease (CVD) using a risk prediction tool that is based on routinely collected data (QRISK3).
Gespeichert in:
| Autor*in: |
Li, Yan [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Encapsulation of EGCG and esterified EGCG derivatives in double emulsions containing Whey Protein Isolate, Bacterial Cellulose and salt - Evageliou, Vasiliki ELSEVIER, 2019, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:133 ; year:2020 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.ijmedinf.2019.104033 |
|---|
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ELV048717916 |
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| 650 | 7 | |a CVD risk prediction |2 Elsevier | |
| 650 | 7 | |a Electronic health records |2 Elsevier | |
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Examining the impact of data quality and completeness of electronic health records on predictions of patients’ risks of cardiovascular disease |
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To assess the extent of variation of data quality and completeness of electronic health records and impact on the robustness of risk predictions of incident cardiovascular disease (CVD) using a risk prediction tool that is based on routinely collected data (QRISK3). |
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To assess the extent of variation of data quality and completeness of electronic health records and impact on the robustness of risk predictions of incident cardiovascular disease (CVD) using a risk prediction tool that is based on routinely collected data (QRISK3). |
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To assess the extent of variation of data quality and completeness of electronic health records and impact on the robustness of risk predictions of incident cardiovascular disease (CVD) using a risk prediction tool that is based on routinely collected data (QRISK3). |
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