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A log analysis exploring the predictors of electronic health record access by clinicians for consumers aged ≥65 who present to the emergency department
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Mullins, Alexandra, Skouteris, Helen, Morris, Heather and Enticott, Joanne (2022) A log analysis exploring the predictors of electronic health record access by clinicians for consumers aged ≥65 who present to the emergency department. In: Challenges of Trustable AI and Added-Value on Health. Studies in Health Technology and Informatics, 294 . IOS Press, pp. 577-578.
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Official URL: https://doi.org/10.3233/shti220531
Abstract
Electronic health records are widely implemented, yet little is understood around adoption and use in the ED setting. Older patients (≥65) are a cohort likely to benefit from use. The primary outcome (MHR access) was explored using logistic regression of 9 independent variables. 28.33% of patients had their MHR accessed within 3 days of presenting. Access is more likely when patients arrive via urgent ambulance and/or are triaged as critical.
| Item Type: | Book Item | ||||
|---|---|---|---|---|---|
| Divisions: | Faculty of Social Sciences > Warwick Business School | ||||
| SWORD Depositor: | Library Publications Router | ||||
| Series Name: | Studies in Health Technology and Informatics | ||||
| Publisher: | IOS Press | ||||
| ISSN: | 1879-8365 | ||||
| Book Title: | Challenges of Trustable AI and Added-Value on Health | ||||
| Official Date: | 25 May 2022 | ||||
| Dates: |
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| Volume: | 294 | ||||
| Page Range: | pp. 577-578 | ||||
| DOI: | 10.3233/shti220531 | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Open Access (Creative Commons) |
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