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Braun B, Hafner J, Schweizer ML, Septimus E, Moody J, Richards C, Hickok J, Herwaldt L. Development and Implementation of a Consensus Algorithm to Optimize Pre-Operative Antimicrobial Prophylaxis and Decrease Gram Positive Surgical Site Infections for Cardiac and Orthopedic Procedures. Poster session presented at: AcademyHealth Annual Research Meeting; 2013 Jun 24; Baltimore, MD.
Research Objective: 1) To develop and evaluate the effectiveness of a pre-operative prophylaxis algorithm (bundle of practices) to reduce the risk of Gram-positive surgical site infections for cardiac and orthopedic surgical patients; 2) To identify factors that facilitate or impede implementation of the algorithm as a quality improvement (QI) initiative in 21 diverse community hospitals. Study Design: The algorithm was based on: 1) a systematic literature review (SLR) and meta-analysis of previous studies; 2) a review of existing preoperative prophylaxis guidelines; 3) a call for infection preventionists and organizations to submit current algorithms and 4) advice from a 12-member expert panel comprising cardiac and orthopedic surgeons, infectious disease experts, and anesthesiologists who addressed gaps in guidelines to ensure the final consensus algorithm was based on best available evidence. In year 2, a quasi-experimental (QE) observational study, which will use time series regression analysis techniques, was conducted to assess the algorithm's effectiveness. A large national healthcare system with centralized informatics systems, QI and infection prevention structures implemented the algorithm as a QI initiative in volunteer hospitals. Project liaisons received centralized, in-person protocol education and materials to facilitate hospital-specific implementation plans. Frequent coaching calls were conducted to answer questions and disseminate study updates. To minimize staff work load, the algorithm bundle was integrated into usual care processes to the greatest extent possible. Population Studied: The primary patient-level outcome is the rate of deep incisional and organ space surgical site infections among adult patients undergoing selected cardiac and orthopedic procedures. Hospital-level contextual factors of interest include equipment availability, staff turnover, physician leadership, outpatient and inpatient coordination etc. Principal Findings: The consensus algorithm reflects best practice given current knowledge and presents a bundle of practices: Staphylococcus aureus nasal screening, mupirocin decolonization, pre-surgical chlorohexidine gluconate (CHG) bathing, and cefazolin antimicrobial prophylaxis with vancomycin added depending on screening results. Algorithm implementation was a comprehensive process requiring patients to use mupirocin and CHG at home, and staff from multiple disciplines and settings - surgical departments, outpatient offices, inpatient peri-operative nursing, pre-operative surgical services, post-operative surgical unit, infection prevention, informationtechnology services, pharmacy, and laboratory - to collaborate. Major activities included modifying EMR screens, revising and reviewing physician pre-operative orders, acquiring essential equipment and supplies, educating staff, and modifying outpatient practices to ensure patients were screened and S. aureus carriers received appropriate decolonization and prophylaxis. Roll-out of the intervention took longer than the anticipated two months at most sites due to competing initiatives, staff turnover and local outbreaks (meningitis, influenza). Some physicians were reluctant to adopt the prophylaxis recommendations because they had strong opinions and because publication of a national consensus guideline was delayed. Analysis of the QE study to assess algorithm effectiveness is in process. Conclusions: Even within a centralized health system with strong infrastructure, ease of implementation varied across sites. Contextual factors substantially affect implementation of complex QI initiatives. Implications for Policy, Delivery, or Practice: Standardization of practice often improves the quality of care. Yet hospitals differed in their ability to implement the consensus algorithm and time needed to accomplish this goal. Participants expedited the adoption of new practices by quickly sharing their insights.
