Components of Existing National Surgical Site Infection Surveillance Programs Based on a Case Series of Low- and Middle-Income Countries: Building Blocks for Success and Opportunities for Improvement

Abstract
Background: Surgical site infection (SSI) surveillance programs are recommended to be included in national infection prevention and control (IPC) programs, yet few exist in low- or middle-income countries (LMICs). Our goal was to identify components of surveillance in existing programs that could be replicated elsewhere and note opportunities for improvement to build awareness for other countries in the process of developing their own national surgical site infection surveillance (nSSIS) programs. Methods: We administered a survey built upon the U.S. Centers for Disease Control and Prevention's framework for surveillance system evaluation to systematically deconstruct logistical infrastructure of existing nSSIS programs in LMICs. Qualitative analyses of survey responses by thematic elements were used to identify successful surveillance system components and recognize opportunities for improvement. Results: Three respondents representing countries in Europe and Central Asia, sub-Saharan Africa, and South Asia designated as upper middle-income, lower middle-income, and low-income responded. Notable strengths described by respondents included use of local paper documentation, staggered data entry, and limited data entry fields. Opportunities for improvement included outpatient data capture, broader coverage of healthcare centers within a nation, improved audit processes, defining the denominator of number of surgical procedures, and presence of an easily accessible, free SSI surveillance training program for healthcare workers. Conclusions: Outpatient post-surgery surveillance, national coverage of healthcare facilities, and training on how to take local SSI surveillance data and integrate it within a broader nSSIS program at the national level remain areas of opportunities for countries looking to implement a nSSIS program.