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BMJ Qual Saf. 2019 Jul 3. pii: bmjqs-2018-008664. doi: 10.1136/bmjqs-2018-008664. [Epub ahead of print]

Study of a multisite prospective adverse event surveillance system.

Author information

1
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada aforster@ohri.ca.
2
Department of Medicine, University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada.
3
Geriatric Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada.
4
General Internal Medicine, McGill University Department of Medicine, Montréal, Québec, Canada.
5
Clinical Practice Assessment Unit, Department of Medicine, McGill University Health Centre, Montréal, Québec, Canada.
6
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
7
Internal Medicine & Critical Care, Queensway Carleton Hospital, Ottawa, Ontario, Canada.
8
Nursing, University of Ottawa Faculty of Health Sciences, Ottawa, Ontario, Canada.

Abstract

BACKGROUND:

We have designed a prospective adverse event (AE) surveillance method. We performed this study to evaluate this method's performance in several hospitals simultaneously.

OBJECTIVES:

To compare AE rates obtained by prospective AE surveillance in different hospitals and to evaluate measurement factors explaining observed variation.

METHODS:

We conducted a multicentre prospective observational study. Prospective AE surveillance was implemented for 8 weeks on the general medicine wards of five hospitals. To determine if population factors may have influenced results, we performed mixed-effects logistic regression. To determine if surveillance factors may have influenced results, we reassigned observers to different hospitals midway through surveillance period and reallocated a random sample of events to different expert review teams.

RESULTS:

During 3560 patient days of observation of 1159 patient encounters, we identified 356 AEs (AE risk per encounter=22%). AE risk varied between hospitals ranging from 9.9% of encounters in Hospital D to 35.8% of encounters in Hospital A. AE types and severity were similar between hospitals-the most common types were related to clinical procedures (45%), hospital-acquired infections (21%) and medications (19%). Adjusting for age and comorbid status, we observed an association between hospital and AE risk. We observed variation in observer behaviour and moderate agreement between clinical reviewers, which could have influenced the observed rate difference.

CONCLUSION:

This study demonstrated that it is possible to implement prospective surveillance in different settings. Such surveillance appears to be better suited to evaluating hospital safety concerns within rather than between hospitals as we could not definitively rule out whether the observed variation in AE risk was due to population or surveillance factors.

KEYWORDS:

adverse events, epidemiology and detection; patient safety; trigger tools

PMID:
31270254
DOI:
10.1136/bmjqs-2018-008664
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Conflict of interest statement

Competing interests: None declared.

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