Vaidehi Nayar1, Andrea Kennedy2, Janine Pappas2, Krista D Atchley3, Cynthia Field3, Sarah Smathers4, Eva E Teszner4, Julia S Sammons5, Susan E Coffin5, Jeffrey S Gerber5, Thomas L Spray6, James M Steven7, Louis M Bell5, Joan Forrer8, Fernando Gonzalez9, Albert Chi2, William J Nieczpiel9, John N Martin9, J William Gaynor6. 1. Office of Clinical Quality Improvement, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania. Electronic address: nayarv@email.chop.edu. 2. Office of Clinical Quality Improvement, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania. 3. Cardiac Nursing, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania. 4. Department of Infection Prevention and Control, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania. 5. Division of Infectious Diseases, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania. 6. Division of Cardiothoracic Surgery, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; The Cardiac Center at The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania. 7. Division of Pediatric Cardiac Anesthesia, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania. 8. Division of Cardiothoracic Surgery, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania. 9. Information Services, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Abstract
BACKGROUND: The use of administrative data for surgical site infection (SSI) surveillance leads to inaccurate reporting of SSI rates [1]. A quality improvement (QI) initiative was conducted linking clinical registry and administrative databases to improve reporting and reduce the incidence of SSI [2]. METHODS: At our institution, The Society of Thoracic Surgeons Congenital Heart Surgery Database (STS-CHSD) and infection surveillance database (ISD) were linked to the enterprise data warehouse containing electronic health record (EHR) billing data. A data visualization tool was created to (1) use the STS-CHSD for case ascertainment, (2) resolve discrepancies between the databases, and (3) assess impact of QI initiatives, including wound alert reports, bedside reviews, prevention bundles, and billing coder education. RESULTS: Over the 24-month study period, 1,715 surgical cases were ascertained according to the STS-CHSD clinical criteria, with 23 SSIs identified through the STS-CHSD, 20 SSIs identified through the ISD, and 32 SSIs identified through the billing database. The rolling 12-month STS-CHSD SSI rate decreased from 2.73% (21 of 769 as of January 2013) to 1.11% (9 of 813 as of December 2014). Thirty reporting discrepancies were reviewed to ensure accuracy. Workflow changes facilitated communication and improved adjudication of suspected SSIs. Billing coder education increased coding accuracy and narrowed variation between the 3 SSI sources. The data visualization tool demonstrated temporal relationships between QI initiatives and SSI rate reductions. CONCLUSIONS: Linkage of registry and infection control surveillance data with the EHR improves SSI surveillance. The visualization tool and workflow changes facilitated communication, SSI adjudication, and assessment of the QI initiatives. Implementation of these initiatives was associated with decreased SSI rates.
BACKGROUND: The use of administrative data for surgical site infection (SSI) surveillance leads to inaccurate reporting of SSI rates [1]. A quality improvement (QI) initiative was conducted linking clinical registry and administrative databases to improve reporting and reduce the incidence of SSI [2]. METHODS: At our institution, The Society of Thoracic Surgeons Congenital Heart Surgery Database (STS-CHSD) and infection surveillance database (ISD) were linked to the enterprise data warehouse containing electronic health record (EHR) billing data. A data visualization tool was created to (1) use the STS-CHSD for case ascertainment, (2) resolve discrepancies between the databases, and (3) assess impact of QI initiatives, including wound alert reports, bedside reviews, prevention bundles, and billing coder education. RESULTS: Over the 24-month study period, 1,715 surgical cases were ascertained according to the STS-CHSD clinical criteria, with 23 SSIs identified through the STS-CHSD, 20 SSIs identified through the ISD, and 32 SSIs identified through the billing database. The rolling 12-month STS-CHSD SSI rate decreased from 2.73% (21 of 769 as of January 2013) to 1.11% (9 of 813 as of December 2014). Thirty reporting discrepancies were reviewed to ensure accuracy. Workflow changes facilitated communication and improved adjudication of suspected SSIs. Billing coder education increased coding accuracy and narrowed variation between the 3 SSI sources. The data visualization tool demonstrated temporal relationships between QI initiatives and SSI rate reductions. CONCLUSIONS: Linkage of registry and infection control surveillance data with the EHR improves SSI surveillance. The visualization tool and workflow changes facilitated communication, SSI adjudication, and assessment of the QI initiatives. Implementation of these initiatives was associated with decreased SSI rates.