Preventing critical failure. Can routinely collected data be repurposed to predict avoidable patient harm? A...

Area of Science:

• Health Services Research
• Patient Safety
• Maternal Health

Background:

• Routinely collected health service performance data can offer insights into service delivery.
• Predicting critical safety failures in healthcare settings is crucial for improving patient outcomes.
• Maternity services are complex environments where early detection of stress is vital.

Purpose of the Study:

• To investigate if sharing routinely collected health service performance data could have predicted a critical safety failure at an Australian maternity service.
• To assess the predictive value of various data sources for identifying health service stress and potential failure.

Main Methods:

• An observational, quantitative, descriptive study was conducted.
• Data from a public hospital maternity service in Victoria, Australia, between 2000 and 2014 were analyzed.
• Statistical analyses included independent samples t-tests and Pearson correlations to examine relationships between service activity, outcomes, and complaints.

Main Results:

• The maternity service experienced a significant increase in births without a corresponding increase in bed capacity, indicating increased workload.
• A weak but significant correlation was found between birth numbers per birth suite and perinatal mortality.
• Direct-to-service patient complaints increased prior to recognized excess perinatal mortality, suggesting a potential early warning.

Conclusions:

• Clinical activity data and direct-to-service patient complaints show potential as predictors of health service stress.
• Complaints to regulators and medicolegal activity were less effective predictors of system failure in this context.
• Significant improvements in data handling and integration are necessary to utilize such data for predicting health service failure effectively.