How to Use Data to Improve Patient Safety
Today, researchers estimate that one in three hospitalized patients experience preventable harm and over 400,000 individuals per year die from these injuries.
There is a gap in healthcare safety culture and the way health systems uses data (or think they use data) to understand patient harm and what to do about it. Much of the data collection is manual and not integrated with financial, operational, and other data, resulting in a fragmented approach to safety analytics that’s not actionable or predictive. Scores are recorded, and boxes are checked, but the real work to make patients safer—closing the loop between information and action—is incomplete.
The status of patient safety moving forward, however, stands to improve. Despite the discouraging statistics noted above, in today’s era of data-driven healthcare, machine learning, and predictive analytics, the industry can turnaround decades of lost ground in patient safety and finally make much needed improvements. This white paper describes the problems in safety culture and how healthcare analytics and new-generation tools will fix them.
- Key Weakness in Patient Safety Today
- Four Measures to Improve Patient Safety
- Three Key Capabilities of Machine Learning in Patient Safety
- Success Stories: Data at Work for Patient Safety
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