Data gaps in electronic health record (EHR) systems: An audit of problem list completeness during the COVID-19 pandemic.

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.

SUBMITTER: Poulos J 

PROVIDER: S-EPMC9759969 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature