Corinne Hohl


Research Classification

Emergency Medicine
Health Information Systems
Health Care Organization
Decision Making

Research Interests

Patient Safety
Medication Safety
Adverse Drug Events
Drug safety and effectiveness
Health Information Technology
Clinical Decision Making
Health services research
Adverse Event Reporting

Research Methodology

Observational cohort studies
Administrative Database Studies
Randomized Controlled Trials
Systematic Reviews
Implementation Studies
Mixed methods
action research


Master's students
Doctoral students
Postdoctoral Fellows

My research group is working with Ministry to develop, implement and evaluate a new provincial medication safety information technology we have developed. This work will provide multiple opportunities for graduate students to be involved in. With the implementation of this technology more robust data will become available on adverse drug events experienced by patients. Future projects include the development of methods to conduct sentinel surveillance of adverse drug events, and studies in comparative drug safety and effectiveness.

I support public scholarship, e.g. through the Public Scholars Initiative, and am available to supervise students and Postdocs interested in collaborating with external partners as part of their research.
I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.

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Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

Investigating health outcomes and risk factors for adverse drug events to improve patient safety and identify strategies for health system improvements (2022)

Preliminary evidence suggests that 19-54% of patients diagnosed with adverse drug events (ADEs), unintended harm from medications, will be re-exposed to the culprit medication upon hospital discharge. The studies from which these estimates arise are small, descriptive, or rely solely on administrative data. Previous research reports an estimated 6-28% of adverse drug events can be identified using administrative data; these data are not well poised to examine adverse events. By triangulating multiple data sources (prospective, chart review, administrative claims data), we sought to: (1) Examine the proportion of re-exposure to culprit medication upon hospital or emergency department discharge, and identify any risk factors for culprit medication re-exposure using Cox regression models; (2) Investigate methods to identify medication non-adherence using claims data, and examine repeat medication non-adherence descriptively; and (3) Examine how administrative health data perform in identifying adverse drug events, including medication non-adherence, by calculating sensitivity and specificity, and conducting logistic regression. The results of our analyses indicated that re-exposure to culprit medication occurred for 45.2% of adverse drug events, though this was largely driven by necessary, irreplaceable medications. Re-exposure varied by type of ADE and duration of medication use. Analyses indicated that no method to identify medication non-adherence in administrative datasets performed well, but the proportion of days covered was the best measure. Finally, as expected, administrative claims data performed poorly in identifying adverse drug events. The administrative data source from which events were more readily detected was hospital data. Overall, the results of this dissertation suggest that while a large proportion of adverse drug events result in subsequent medication re-exposure, these may not be inappropriate re-exposures.ivFurther research is needed to draw this distinction. These results also demonstrate that adverse drug events, including medication non-adherence, are poorly identified in administrative claims data, and caution should be used when interpreting research that relies solely on their use. Previous work in the field has likely underestimated the burden of adverse drug events. Where possible, research on adverse drug events should include data that are prospectively collected at the point of care.

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Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Investigating patient-reported outcomes among COVID-19 survivors: a longitudinal cohort study (2022)

Background:Many Coronavirus Disease 2019 (COVID-19) survivors report long-term sequelae. However, few studies have measured patient-reported outcomes and compared them to those of patients who tested negative for severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). This study compares the long-term physical and mental health outcomes of patients presenting to emergency departments who tested positive for SARS-COV-2 with those who tested negative.Methods:This study enrolled consecutive eligible patients presenting to emergency departments participating in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) between March 1st 2020 and July 14th 2021. Patients tested for SARS-COV-2 were eligible. Consecutive SARS-COV-2 positive patients were consented for follow-up, and matched with test-negative controls from the same hospital and date. The outcome measures were the Veterans RAND physical health component score (PCS) and mental health component score (MCS). The PCS and MCS of propensity score matched patients were analyzed using linear mixed effects models. Risk factors for PCS and MCS were modelled using linear regression.Results:Our cohort included 1170 SARS-COV-2 positive patients and 3716 test-negative controls. Comparing the groups, the adjusted mean difference in PCS was 0.50 (95%CI: -0.36, 1.36) and -1.01 (95%CI: -1.91, -0.11) for MCS. A World Health Organization Ordinal Outcome Score of 6-7, representing severe SARS-COV-2 disease, was the strongest predictor of PCS (β=-7.4; 95%CI: -9.8, -5.1). Prior mental health illness was the strongest predictor of MCS (β=-5.4; 95%CI: -6.3, -4.5). Conclusion:The mean PCS was similar among SARS-COV-2 positive and negative participants tested under similar circumstances, while mean MCS was worse among SARS-COV-2 positive participants. The mental health sequelae of COVID-19 should be considered when developing long-term support programs for survivors.

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