Jennifer A Hutcheon1,2, Lily Lee3, K S Joseph3,4,5, Brooke Kinniburgh3, Geoffrey W Cundiff4. 1. Perinatal Services BC, Provincial Health Services Authority, Vancouver, BC, Canada. jhutcheon@cfri.ca. 2. Department of Obstetrics and Gynaecology, University of British Columbia (UBC), Shaughnessy Building C408A, 4500 Oak Street, Vancouver, BC, V6N 3N1, Canada. jhutcheon@cfri.ca. 3. Perinatal Services BC, Provincial Health Services Authority, Vancouver, BC, Canada. 4. Department of Obstetrics and Gynaecology, University of British Columbia (UBC), Shaughnessy Building C408A, 4500 Oak Street, Vancouver, BC, V6N 3N1, Canada. 5. School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada.
Abstract
OBJECTIVES: To establish the feasibility of implementing a previously-published clinical standardized performance indicator, the Adverse Outcome Index (AOI), using routinely-collected data in a population-based perinatal database and to examine variation in the indicator over time and between hospitals. METHODS: Maternal and newborn medical record data contained in the British Columbia Perinatal Data Registry, 2004-2013, were used to calculate an AOI (a composite of 10 maternal and newborn adverse events) and its severity-weighted scores, the Weighted Adverse Outcome Score and the Severity Index. Temporal trends in the indices were examined by plotting annual risks and weighted risks with 95% confidence intervals. Hospital-level risks were calculated with 95% confidence intervals, adjusting for patient case-mix. RESULTS: Among 410,054 singleton deliveries in British Columbia, the risk of AOI was 5.8 per 100, while the Weighted Adverse Outcome Score and Severity Index were 1.6 and 27.4, respectively. The risk of AOI did not change significantly over the study period, while the Severity Index decreased from 29.3 (95% CI 26.7-31.9) in 2004 to 23.9 (22.0-25.8) in 2013. Fifteen of 52 hospitals had risks of AOI significantly above the provincial median. The hospitals' risks of AOI were not correlated with their Severity Indices (r = 0.02). CONCLUSIONS: The AOI can successfully be estimated using data from a population-based database, and used to monitor trends in safety of labour and delivery over time and between hospitals. The low correlation between frequency and severity of adverse events confirms the importance of considering event severity in perinatal population health surveillance.
OBJECTIVES: To establish the feasibility of implementing a previously-published clinical standardized performance indicator, the Adverse Outcome Index (AOI), using routinely-collected data in a population-based perinatal database and to examine variation in the indicator over time and between hospitals. METHODS: Maternal and newborn medical record data contained in the British Columbia Perinatal Data Registry, 2004-2013, were used to calculate an AOI (a composite of 10 maternal and newborn adverse events) and its severity-weighted scores, the Weighted Adverse Outcome Score and the Severity Index. Temporal trends in the indices were examined by plotting annual risks and weighted risks with 95% confidence intervals. Hospital-level risks were calculated with 95% confidence intervals, adjusting for patient case-mix. RESULTS: Among 410,054 singleton deliveries in British Columbia, the risk of AOI was 5.8 per 100, while the Weighted Adverse Outcome Score and Severity Index were 1.6 and 27.4, respectively. The risk of AOI did not change significantly over the study period, while the Severity Index decreased from 29.3 (95% CI 26.7-31.9) in 2004 to 23.9 (22.0-25.8) in 2013. Fifteen of 52 hospitals had risks of AOI significantly above the provincial median. The hospitals' risks of AOI were not correlated with their Severity Indices (r = 0.02). CONCLUSIONS: The AOI can successfully be estimated using data from a population-based database, and used to monitor trends in safety of labour and delivery over time and between hospitals. The low correlation between frequency and severity of adverse events confirms the importance of considering event severity in perinatal population health surveillance.
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