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Objective Surgical site infections (SSIs) are a serious and costly post-op complication. Generating SSI rates often requires labor-intensive methods, but increasing numbers of publications reported SSI rates using administrative data. Methods Index laminectomy and spinal fusion procedures were identified using Canadian Classification of Health Interventions (CCI) procedure codes for inpatients and outpatients in the province of Alberta, Canada between 2008 and 2015. SSIs occurring in the year postsurgery were identified using the International Classification of Diseases, 10th Revision, Canada (ICD-10-CA) diagnosis and CCI procedure codes indicative of post-op infection. Rates of SSIs and case characteristics were reported. Results Over the 8-year study period, 21,222 index spinal procedures were identified of which 12,027 (56.7%) were laminectomy procedures, with 322 SSIs identified, an SSI rate of 2.7 per 100 procedures. Of the 9,195 (43.3%) fusion procedures, 298 were identified as an SSI, an SSI rate of 3.2 per 100 procedures. This study found SSI rates increased from 2008 and 2015, and rates were the highest in the 0-18 year age group. Conclusions The rates reported in this study were similar to published SSI rates using traditional surveillance methods, suggesting administrative data may be a viable method for reporting SSI rates following spinal procedures. Further work is needed to validate SSIs identified using administrative data by comparing to traditional surveillance.

Background Clostridioides difficile infection (CDI) is one of the most common health care-associated infections. This study assessed the validity of the Discharge Abstract Database (DAD) compared to a traditional clinical surveillance method for identifying CDI. Methods Retrospective analysis of all DAD records with International Statistical Classification of Diseases and Related Health Problems 10th Revision (ie, ICD-10) diagnostic code A04.7 (enterocolitis due to CDI) between April 2015 and March 2019 were compared to a clinical dataset of positive inpatient CDI for all acute care facilities in Alberta, Canada. Sensitivity and positive predictive values were calculated using R version 3.6.0. Results The DAD had a sensitivity of 85.0% (95% confidence interval: 84.1%-85.8%) and a positive predictive value of 80.0% (95% confidence interval: 79.2%-80.0%). The CDI rate per 1,000 admissions over the study period was 28% higher in the DAD compared to Infection Prevention and Control surveillance. Discussion The DAD does not distinguish symptomatic cases from asymptomatic cases and so indicators to identify symptomatic disease would need to be applied, potentially through a linkage to antibiotic treatment orders available in patient management systems. Conclusions The DAD is moderately sensitive for identifying symptomatic CDI cases in Alberta, Canada and caution should be applied when interpreting rates based on administrative data.

In a population-based, five-year retrospective cohort study of 5304 adult patients with hospital-acquired Clostridioides difficile infection across Alberta (N=101 hospitals), 30-day all-cause and attributable mortality were 12.2% and 4.5%, respectively. Patients >75 years of age had the highest odds of attributable mortality (odds ratio (OR) 9.34, 95% confidence interval (CI) 2.92-29.83) and largest difference in mean length of stay (11.7 days, 95% CI 8.2-15.2). A novel finding was that elevated white blood cell count at admission was associated with reduced attributable mortality (OR 0.67, 95% CI 0.50-0.90) which deserves further study. Advancing age was incrementally and significantly associated with all outcomes.

Co-morbid illnesses have a major influence on the epidemiology of infectious diseases. Although International Classification of Diseases (ICD) discharge codes are frequently used to evaluate the presence of co-morbidities in observational research, additional research is required about their validity. We reviewed the evidence supporting the use of routinely coded administrative data for ascertainment of co-morbid diseases with emphasis as it relates to the study of infectious diseases. A systematic Medline, Embase, and bibliographic review were conducted in order to identify and critically appraise published (1990–2008) studies comparing administrative databases with conventional chart review. Twenty-one co-morbidities commonly associated with infectious diseases risk were a priori selected for specific evaluation. Of the 21 co-morbid conditions chosen, only 19 had adequate data available for evaluation. Thirteen studies were included; only one focused on an infectious disease population. Eleven articles validated individual co-morbid conditions data in electronic administrative databases and reported a wide range of pooled sensitivity (13–82%) but overall high pooled specificity (>97%) when compared with medical chart review. Seven articles compared Charlson Co-morbidity Index scores derived from administrative data algorithms as compared with that calculated from medical record review and found that administrative data underscored the index in all articles with kappa agreement ranging from 0.30 to 0.56. The small body of literature published to date suggests that electronic administrative databases have limited validity for co-morbidity evaluation. Studies evaluating administrative database ascertainment of co-morbidities specifically in infectious diseases research are needed.

Electronic surveillance that utilises information held in databases is more efficient than conventional infection surveillance methods. Validity is not well-defined, however. We systematically reviewed studies comparing the utility of electronic and conventional surveillance methods. Publications were identified using Medline (1980-2007) and bibliographic review. The sensitivity and specificity of electronic compared with conventional surveillance was reported. Twenty-four studies were included. Six studies reported that nosocomial infections could be detected utilising microbiology data alone with good overall sensitivity (range: 63-91%) and excellent specificity (range: 87 to >99%). Two studies used three laboratory-based algorithms for the detection of infection outbreaks yielding variable utility measures (sensitivity, range: 43-91%; specificity, range: 67-86%). Seven studies using only administrative data including discharge coding (International Classification of Diseases, 9th edn, Clinical Modification) and pharmacy data claimed databases had good sensitivity (range: 59-96%) and excellent specificity (range: 95 to >99%) in detecting nosocomial infections. Six studies combined both laboratory and administrative data for a range of infections, and overall had higher sensitivity (range: 71-94%) but lower specificity (range: 47 to >99%) than with use of either alone. Three studies evaluated community-acquired infections with variable results. Electronic surveillance has moderate to excellent utility compared with conventional methods for nosocomial infections. Future studies are needed to refine electronic algorithms further, especially with community-onset infections.