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Developing a Standardized Process to Visualize, Analyze, and Communicate NSQIP Data Using an Advanced Visual Data

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    A new surgical scorecard uses visual analytics to track surgical site infections (SSIs) and comorbidities monthly, improving data feedback for surgeons. This tool helps identify performance outliers and enhances quality improvement initiatives.

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    Area of Science:

    • Surgical Quality Improvement
    • Health Informatics
    • Data Analytics

    Background:

    • The American College of Surgeons National Quality Improvement Program (ACS NSQIP) provides high-level morbidity and mortality data.
    • Surgeons require monthly, interactive data visualization and comorbidity analysis for quality improvement.
    • Current reporting methods lack the desired granularity and timeliness for effective surgical feedback.

    Purpose of the Study:

    • To develop and test a surgical scorecard using advanced visual data analytics.
    • To provide surgeons with timely, interactive feedback on surgical outcomes and comorbidities.
    • To improve the analysis of surgical site infections (SSIs) and associated risk factors.

    Main Methods:

    • A proof-of-concept project tracked SSIs and comorbidities using a synthetic NSQIP database (5,000 patients).
    • Variables included diabetes, HgbA1c, immunosuppression, hypertension, BMI, and smoking.
    • Scorecards were generated to visualize SSIs by time, department, and comorbidity; statistical tests analyzed relationships.

    Main Results:

    • Visual data analytics accelerated NSQIP report timeliness from 6 months to 45 days.
    • The scorecard enabled visualization of data trends by time, specialty, and procedure.
    • Statistical testing identified surgeons with outlier SSI rates.

    Conclusions:

    • An on-demand scorecard facilitates real-time analysis of medical comorbidities and SSIs.
    • This tool aids in identifying performance outliers for targeted quality improvement.
    • Interactive data visualization enhances the understanding of factors influencing surgical outcomes.