Validation of administrative population-based data sets for the detection of cesarean delivery surgical site infection

Divergences between healthcare-associated infection administrative data and active surveillance data in Canada

BACKGROUND

Although Canada has both a national active surveillance system and administrative data for the passive surveillance of healthcare-associated infections (HAI), both have identified strengths and weaknesses in their data collection and reporting. Active and passive surveillance work independently, resulting in results that diverge at times. To understand the divergences between administrative health data and active surveillance data, a scoping review was performed.

METHOD

Medline, Embase and Cumulative Index to Nursing and Allied Health Literature along with grey literature were searched for studies in English and French that evaluated the use of administrative data, alone or in comparison with traditional surveillance, in Canada between 1995 and November 2, 2020. After extracting relevant information from selected articles, a descriptive summary of findings was provided with suggestions for the improvement of surveillance systems to optimize the overall data quality.

RESULTS

Sixteen articles met the inclusion criteria, including twelve observational studies and four systematic reviews. Studies showed that using a single source of administrative data was not accurate for HAI surveillance when compared with traditional active surveillance; however, combining different sources of data or combining administrative with active surveillance data improved accuracy. Electronic surveillance systems can also enhance surveillance by improving the ability to detect potential HAIs.

CONCLUSION

Although active surveillance of HAIs produced the most accurate results and remains the gold-standard, the integration between active and passive surveillance data can be optimized. Administrative data can be used to enhance traditional active surveillance. Future studies are needed to evaluate the feasibility and benefits of potential solutions presented for the use of administrative data for HAI surveillance and reporting in Canada.

Risk factors for surgical site infection following cesarean delivery: a retrospective cohort study

BACKGROUND

The rate of cesarean delivery is increasing in North America. Surgical site infection following this operation can make it difficult to recover, care for a baby and return home. We aimed to determine the incidence of surgical site infection to 30 days following cesarean delivery, associated risk factors and whether risk factors differed for predischarge versus postdischarge infection.

METHODS

We identified a retrospective cohort in Nova Scotia by linking the provincial perinatal database to hospital admissions and physician billings databases to follow women for 30 days after they had given birth by cesarean delivery between Jan. 1, 1997 and Dec. 31, 2012. Logistic regression with generalized estimating equations was used to determine risk factors for infection.

RESULTS

A total of 25 123 women had 33 991 cesarean deliveries over the study period. Of the 25 123, 923 had surgical site infections, giving an incidence rate of 2.7% (95% CI 2.54%-2.89%); the incidence decreased over time. Risk factors for infection (adjusted odds ratios ≥ 1.5) were prepregnancy weight 87.0 kg or more, gaining 30.0 kg or more during pregnancy, chorioamnionitis, maternal blood transfusion, anticoagulation therapy, alcohol or drug abuse, second stage of labour before surgery, delivery in 1997-2000 and delivery in a hospital performing 130-1249 cesarean deliveries annually. Women who gave birth earlier in the study period, those who gave birth in a hospital with 130-949 cesarean deliveries per year and those with more than 1 fetus were at a significantly higher risk for surgical site infection before discharge; women who smoked were at significantly higher risk for surgical site infection after discharge.

INTERPRETATION

Most risk factors are known before delivery, and some are potentially modifiable. Although the incidence of surgical site infection decreased over time, targeted clinical and infection prevention and control interventions could further reduce the burden of illness associated with this health-care-related infection.

The quality of denominator data in surgical site infection surveillance versus administrative data in Norway 2005-2010

Background

High quality of surveillance systems for surgical site infections (SSIs) is the key to their usefulness. The Norwegian Surveillance System for Antibiotic Consumption and Healthcare-Associated Infections (NOIS) was introduced by regulation in 2005, and is based largely on automated extraction of data from underlying systems in the hospitals.

Methods

This study investigates the quality of NOIS-SSI’s denominator data by evaluating completeness, representativeness and accuracy compared with de-identified administrative data for 2005–2010. Comparisons were made by region, hospital type and size, age and sex for 4 surgical procedures.

Results

The completeness of NOIS improved from 29.2 % in 2005 to 79.8 % in 2010. NOIS-SSI became representative over time for most procedures by hospital size and type, but not by region. It was representative by age and sex for all years and procedures. Accuracy was good for all years and procedures by all explanatory variables.

Conclusions

A flexible and incremental implementation strategy has encouraged the development of computer-based surveillance systems in the hospitals which gives good accuracy, but the same strategy has adversely affected the completeness and representativeness of the denominator data. For the purpose of evaluating risk factors and implementing prevention and precautionary measures in the individual hospitals, representativeness seems sufficient, but for benchmarking and/or public reporting it is not good enough.

Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review

OBJECTIVE

Measuring the incidence of healthcare-associated infections (HAI) is of increasing importance in current healthcare delivery systems. Administrative data algorithms, including (combinations of) diagnosis codes, are commonly used to determine the occurrence of HAI, either to support within-hospital surveillance programmes or as free-standing quality indicators. We conducted a systematic review evaluating the diagnostic accuracy of administrative data for the detection of HAI.

METHODS

Systematic search of Medline, Embase, CINAHL and Cochrane for relevant studies (1995-2013). Methodological quality assessment was performed using QUADAS-2 criteria; diagnostic accuracy estimates were stratified by HAI type and key study characteristics.

RESULTS

57 studies were included, the majority aiming to detect surgical site or bloodstream infections. Study designs were very diverse regarding the specification of their administrative data algorithm (code selections, follow-up) and definitions of HAI presence. One-third of studies had important methodological limitations including differential or incomplete HAI ascertainment or lack of blinding of assessors. Observed sensitivity and positive predictive values of administrative data algorithms for HAI detection were very heterogeneous and generally modest at best, both for within-hospital algorithms and for formal quality indicators; accuracy was particularly poor for the identification of device-associated HAI such as central line associated bloodstream infections. The large heterogeneity in study designs across the included studies precluded formal calculation of summary diagnostic accuracy estimates in most instances.

CONCLUSIONS

Administrative data had limited and highly variable accuracy for the detection of HAI, and their judicious use for internal surveillance efforts and external quality assessment is recommended. If hospitals and policymakers choose to rely on administrative data for HAI surveillance, continued improvements to existing algorithms and their robust validation are imperative.

Methodology of the Norwegian Surveillance System for Healthcare-Associated Infections: the value of a mandatory system, automated data collection, and active postdischarge surveillance

BACKGROUND

Surveillance is a primary component of systems for the prevention of health care-associated infections (HCAI). Feedback to surgeons from these surveillance systems may reduce rates of surgical site infections (SSIs) by approximately 20%.

OBJECTIVE

Our objective was to describe the Norwegian Surveillance System for Healthcare-Associated Infections' (NOIS) module for SSI (NOIS-SSI) and to evaluate the completeness of hospital participation, the effectiveness of automated data collection, and the added value of follow-up after hospital discharge during 2005 to 2009.

METHODS

NOIS was introduced by regulation in 2005. Hospital participation is described through adherence to the mandatory requirements and participation in the voluntary aspects of the system. Automated data collection is evaluated through the completeness of reporting of explanatory and administrative variables. The impact of active postdischarge surveillance is assessed through the completeness of follow-up and the proportion of infections detected after hospital discharge.

RESULTS

The system has achieved 95% (52/55) hospital participation, with 65% (34/52) of the hospitals submitting more data than the required minimum. The completeness of patient and procedure-related background data is satisfactory, with 23.3% (5,079/21,772) of the records having at least 1 missing value. The completeness of 30-day follow-up of patients is 90.7% (19,747/21,772), and 81% (765/948) of the infections were detected after discharge from hospital.

CONCLUSION

Implementation of a new surveillance system for SSI has been successful evaluated through hospital participation, the completeness of reporting of explanatory and administrative variables, and the completeness of postdischarge follow-up. Important success factors are a mandatory system, automated data-harvesting systems in hospitals, and active postdischarge surveillance.