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Data gaps in electronic health record (EHR) systems: An audit of problem list completeness during the COVID-19
Jordan Poulos1, Leilei Zhu2, Anoop D Shah3
1UCL Medical School, University College London, Gower Street, London, WC1E 6BT, UK; EHRS Directorate, University College London Hospitals NHS Foundation Trust, 250 Euston Rd, London, NW1 2PG, UK.
Insights
Diagnosis recording in hospital electronic health records (EHR) is incomplete. Nearly 40% of diagnoses were found only in free text notes, not the structured problem list, impacting patient care.
Area of Science:
- Health Informatics
- Clinical Documentation
- Pandemic Preparedness
Background:
- Electronic health record (EHR) systems are crucial for clinical decision-making and research.
- Accurate diagnosis recording in structured problem lists is essential for comprehensive patient data.
- The COVID-19 pandemic highlighted the need for efficient and complete health information management.
Purpose of the Study:
- To evaluate the completeness of diagnosis recording in hospital EHR problem lists.
- To assess the impact of the COVID-19 pandemic on diagnosis documentation accuracy.
- To identify discrepancies between structured problem lists and free text clinical notes.
Main Methods:
- Retrospective chart review of 516 patients with suspected or confirmed COVID-19.
- Manual review of free text electronic case notes within a major London teaching hospital EHR.
- Analysis of diagnosis recording in structured problem lists versus free text entries.
Main Results:
- A total of 4563 diagnoses were identified across 516 patients.
- Only 62.3% of diagnoses were initially present in the structured EHR problem list.
- An additional 1722 diagnoses were discovered in free text notes, increasing the mean problems per patient from 5.51 to 8.84.
Conclusions:
- Diagnosis recording on inpatient EHR problem lists is significantly incomplete.
- Approximately 40% of important diagnoses were only documented in free text notes.
- Improving structured data capture in EHRs is vital for patient care and research.
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.
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