Open Access
Indicators of missing Electronic Medical Record (EMR) discharge summaries: A retrospective study on data from a large Canadian cohort
Author(s) -
Natalie Wiebe,
Yuan Xu,
Abdel Aziz Shaheen,
Catherine Eastwood,
Bastien Boussat,
Hude Quan
Publication year - 2020
Publication title -
international journal of population data science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.602
H-Index - 7
ISSN - 2399-4908
DOI - 10.23889/ijpds.v5i3.1352
Subject(s) - missing data , medicine , medical record , logistic regression , electronic medical record , comorbidity , cohort , electronic records , emergency medicine , retrospective cohort study , database , statistics , mathematics , computer science
Introduction and Objectives:
Electronic medical records (EMRs), specifically the discharge summary (DS), can improve secondary use data availability and interprofessional communication. We aimed to assess the completeness of our EMRs by assessing the presence of a DS in the EMR. Additionally, we assessed for indicators of a missing DS.
Methods:
A chart review was conducted on 3,011 inpatient charts in Calgary, Alberta. 893 charts were missing an electronic DS. A 10% sample was drawn to assess for presence of a paper DS. A Chi-square test, Fisher’s test and logistic regression assessed for associations between electronic DS absence and i) patient and hospital characteristics, and ii) patient comorbidities
Results:
The univariate analyses showed that age, being a surgical patient, a Charlson Comorbidity Index (CCI) of </1, as well as patients with myocardial infarctions, congestive heart failure, cerebrovascular disease, dementia, chronic pulmonary disease, diabetes, and renal disease were associated with a missing DS. Those that were middle aged, surgical patients, or had fewer comorbidities were more likely to have a missing DS. Within the 10% sample, approximately 50% of all patients were from a surgical department, all of which were missing both electronic and paper discharge summaries.
Conclusions: Our study is the first to describe indicators of missing electronic DS. The DS impacts interprofessional communication, patient outcomes, and data quality. Therefore, the implications of an incomplete DS are widespread. Our findings will caution future researchers using EMR data about the potential for incomplete data, particularly for patients who are surgical, middle aged, and have fewer comorbidities.