The Joint Commission Journal on Quality and Patient Safety
Innovation in Patient Safety and Quality at the National LevelThe American College of Surgeons National Surgical Quality Improvement Program: Achieving Better and Safer Surgery
Section snippets
Ways to Achieve Accurate Data Collection
Across the many ACS quality improvement programs,10 frontline providers are continually striving to find and use the most accurate data possible when evaluating, diagnosing, and treating their patients. Likewise, having accurate data is central to measuring and evaluating the quality of surgical care. Many factors contribute to the collection of accurate data in ACS NSQIP, including well-specified definitions for every data variable, training and annual testing of the data abstractors,
Feeding Back the Data
Regardless of which tailored module a hospital chooses, feeding back data is critical to achieving improvement—and this area is one in which many of the advances in the program have occurred. Similar to the VA program, ACS NSQIP initially fed back risk-adjusted reports semiannually to its hospitals. The program then increased the frequency of reports to quarterly. In 2011 we added real-time, risk-adjusted reports to the program, including real-time summary dashboards.
Individual-provider data
Developing a Collection of Surgical Improvement Tools
ACS NSQIP recognized early on that to achieve quality improvement (QI), having data is necessary but not sufficient. ACS NSQIP created several tools for hospitals to use to spur QI. A number of clinical guidelines were developed targeting the challenges that ACS NSQIP hospitals have faced (Sidebar 1, page 202). For example, some of the first guidelines addressed the most common occurrences in hospitals—SSI, urinary tract infection, pneumonia, and venous thromboembolism. Most of the hospitals
Summary
The improvements that have been accomplished by local hospitals and providers participating in ACS NSQIP have been possible because their efforts have been built on the foundation of high-quality data, which are essential to achieving and sustaining improvement. Importantly, data should be clinically meaningful and as accurate as possible without creating an infeasible burden. Without accurate data, not only is it difficult to know how good (or not good) the care is, it is difficult to gain
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