Poulos, J;
Zhu, L;
Shah, AD;
(2021)
Data gaps in electronic health record (EHR) systems: An audit of problem list completeness during the COVID-19 pandemic.
International Journal of Medical Informatics
, 150
, Article 104452. 10.1016/j.ijmedinf.2021.104452.
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Abstract
OBJECTIVE: To evaluate the completeness of diagnosis recording in problem lists in a hospital electronic health record (EHR) system during the COVID-19 pandemic. DESIGN: Retrospective chart review with manual review of free text electronic case notes. SETTING: Major teaching hospital trust in London, one year after the launch of a comprehensive EHR system (Epic), during the first peak of the COVID-19 pandemic in the UK. PARTICIPANTS: 516 patients with suspected or confirmed COVID-19. MAIN OUTCOME MEASURES: Percentage of diagnoses already included in the structured problem list. RESULTS: Prior to review, these patients had a combined total of 2841 diagnoses recorded in their EHR problem lists. 1722 additional diagnoses were identified, increasing the mean number of recorded problems per patient from 5.51 to 8.84. The overall percentage of diagnoses originally included in the problem list was 62.3% (2841 / 4563, 95% confidence interval 60.8%, 63.7%). CONCLUSIONS: Diagnoses and other clinical information stored in a structured way in electronic health records is extremely useful for supporting clinical decisions, improving patient care and enabling better research. However, recording of medical diagnoses on the structured problem list for inpatients is incomplete, with almost 40% of important diagnoses mentioned only in the free text notes.
| Type: | Article |
|---|---|
| Title: | Data gaps in electronic health record (EHR) systems: An audit of problem list completeness during the COVID-19 pandemic |
| Location: | Ireland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ijmedinf.2021.104452 |
| Publisher version: | https://doi.org/10.1016/j.ijmedinf.2021.104452 |
| Language: | English |
| Additional information: | © 2021 The Authors. Published by Elsevier B.V. under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | COVID-19, Data completeness, EHR systems, Electronic health record, Health information technology, Problem lists |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10126754 |
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