Standardization of Data Collection and Reporting Methods for Infection Control (IC) Surveillance of Targeted, High Risk Procedures Via a Web Based Format in a 22 Hospital System Leads to the Development of a Model Process

ISSUE: IC reporting of surgical site infections (SSI) at the system level was revealing no useful prevention/interventional information for performance improvement. Rates were reported for all surgical sites, but were not stratified by procedure. A new system that promoted procedure specific reporting was needed to allow accurate representation of SSI rates and to facilitate detection and prevention opportunities. PROJECT: A national IC Practitioner (ICP) work group was deployed to revise the processes for surveillance. A review of historical data to identify high volume, problem prone, high risk, high cost and patient outcome related conditions was conducted. Three sub groups were formed to develop indicators for each of the conditions prioritized: spine fusion; skin grafts; and tissue expander procedures. Coded procedure data and patient demographics were pulled from the existing coding system. ICPʹs crossmatched patients who developed infections. A process manual was developed to ensure consistency in procedures and to support personnel. Demographic and surveillance data elements were defined and collected through chart abstraction. The data was entered into a web based program for aggregation and analysis. RESULTS: A network of informed ICPʹs resulted who now share best practices across the system. Using a standardized process for surveillance improved the comparability of data and helped identify opportunities to improve speed and effectiveness of corrective/preventative interventions. Use of a system driven process using coded data allowed for improved accuracy of reporting. Data analysis, risk stratification and predictive risk modeling are ongoing. LESSONS LEARNED: The development of consistently reported surveillance across a multi hospital system points out the challenges in using comparative data within the health care industry. Constant attention must be provided to data collection in order to ensure data integrity. The need for common surveillance programs becomes self evident when practice changes are shared and improved outcomes are realized for patients who are at risk for infections. In addition, prevention and risk prediction is possible when using common nomenclature and surveillance techniques.