Surveillance of selected post-caesarean infections based on electronic registries: validation study including post-discharge infections

Establishing semi-automated infection surveillance in obstetrics and gynaecology

BACKGROUND

Surveillance is an acknowledged method to decrease nosocomial infections, such as surgical site infections (SSIs). Electronic healthcare records create the opportunity for automated surveillance. While approaches for different types of surgeries and indicators already exist, there are very few for obstetrics and gynaecology.

AIM

To analyse the sensitivity and workload reduction of semi-automated surveillance in obstetrics and gynaecology.

METHODS

In this retrospective, single-centre study at a 1438-bed tertiary care hospital in Germany, semi-automated SSI surveillance using the indicators 'antibiotic prescription', 'microbiological data' and 'administrative data' (diagnosis codes, readmission, post-hospitalization care) was compared with manual analysis and categorization of all patient files. Breast surgeries (BSs) conducted in 2018 and caesarean sections (CSs) that met the inclusion criteria between May 2013 and December 2019 were included. Indicators were analysed for sensitivity, number of analysed procedures needed to identify one case, and potential workload reduction in detecting SSIs in comparison with the control group.

FINDINGS

The reference standard showed nine SSIs in 416 BSs (2.2%). Sensitivities for the indicators 'antibiotic prescription', 'diagnosis code', 'microbiological sample taken', and the combination 'diagnosis code or microbiological sample' were 100%, 88.9%, 66.7% and 100%, respectively. The reference standard showed 54 SSIs in 3438 CSs (1.6%). Sensitivities for the indicators 'collection of microbiological samples', 'diagnosis codes', 'readmission/post-hospitalization care', and the combination of all indicators were 38.9%, 27.8%, 85.2% and 94.4%, respectively.

CONCLUSIONS

Semi-automated surveillance systems may reduce workload by maintaining high sensitivity depending on the type of surgery, local circumstances and thorough digitalization.

Electronically assisted surveillance systems of healthcare-associated infections: a systematic review

Background

Surveillance of healthcare-associated infections (HAI) is the basis of each infection control programme and, in case of acute care hospitals, should ideally include all hospital wards, medical specialties as well as all types of HAI. Traditional surveillance is labour intensive and electronically assisted surveillance systems (EASS) hold the promise to increase efficiency.

Objectives

To give insight in the performance characteristics of different approaches to EASS and the quality of the studies designed to evaluate them.

Methods

In this systematic review, online databases were searched and studies that compared an EASS with a traditional surveillance method were included. Two different indicators were extracted from each study, one regarding the quality of design (including reporting efficiency) and one based on the performance (e.g. specificity and sensitivity) of the EASS presented.

Results

A total of 78 studies were included. The majority of EASS (n = 72) consisted of an algorithm-based selection step followed by confirmatory assessment. The algorithms used different sets of variables. Only a minority (n = 7) of EASS were hospital-wide and designed to detect all types of HAI. Sensitivity of EASS was generally high (> 0.8), but specificity varied (0.37–1). Less than 20% (n = 14) of the studies presented data on the efficiency gains achieved.

Conclusions

Electronically assisted surveillance of HAI has yet to reach a mature stage and to be used routinely in healthcare settings. We recommend that future studies on the development and implementation of EASS of HAI focus on thorough validation, reproducibility, standardised datasets and detailed information on efficiency.

Postpartum urinary tract infection by mode of delivery: a Danish nationwide cohort study

OBJECTIVES

To examine the association between postpartum urinary tract infection and intended mode of delivery as well as actual mode of delivery.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

All live births in Denmark between 2004 and 2010 (n=450 856). Births were classified by intended caesarean delivery (n=45 053) or intended vaginal delivery (n=405 803), and by actual mode of delivery: spontaneous vaginal delivery, operative vaginal delivery, emergency or planned caesarean delivery in labour or prelabour.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome measure was postpartum urinary tract infection (n=16 295) within 30 days post partum, defined as either a diagnosis of urinary tract infection in the National Patient Registry or redemption of urinary tract infection-specific antibiotics recorded in the Register of Medicinal Product Statistics.

RESULTS

We found that 4.6% of women with intended caesarean delivery and 3.5% of women with intended vaginal delivery were treated for postpartum urinary tract infection.Women with intended caesarean delivery had a significantly increased risk of postpartum urinary tract infection compared with women with intended vaginal delivery (OR 1.33, 95% CI 1.27 to 1.40), after adjustment for age at delivery, smoking, body mass index, educational level, gestational diabetes mellitus, infection during pregnancy, birth weight, preterm delivery, preterm prelabour rupture of membranes, pre-eclampsia, parity and previous caesarean delivery (adjusted OR 1.24, 95% CI 1.17 to 1.46).Using actual mode of delivery as exposure, all types of operative delivery had an equally increased risk of postpartum urinary tract infection compared with spontaneous vaginal delivery.

CONCLUSIONS

Compared with intended vaginal delivery, intended caesarean delivery was significantly associated with a higher risk of postpartum urinary tract infection. Future studies should focus on reducing routine catheterisation prior to operative vaginal delivery as well as improving procedures related to catheterisation.

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.

Risks and benefits of the skin-to-skin cesarean section - a retrospective cohort study

OBJECTIVE

Comparing maternal and neonatal outcomes after conventional cesarean section (CS) versus a "natural" or "skin-to-skin" cesarean section (SSCS).

METHODS

Retrospective cohort of women who underwent a SSCS (01-2013 until 12-2013) compared to conventional CS (08-2011 to 08-2012). CS before 37 weeks, under general anesthesia and in case of fetal distress were excluded. Main outcome measures were maternal blood loss, post-operative infection and admission; neonatal infection and admission; procedural outcomes.

RESULTS

We analyzed 285 (44%) women in the SSCS-group and 365 (56%) in the conventional CS-group. There were no significant differences in surgical site infection (2.1% versus 1.6%; RR 1.1; 95%CI 0.64-2.0), or other maternal outcomes. Fewer neonates born after SSCS were admitted to the pediatric ward (9.5% versus 18%; RR 0.58; 95%CI 0.41-0.80) and fewer neonates had a suspected neonatal infection (2.0% versus 7.3%; RR 0.40; 95%CI 0.19-0.83). No differences were observed for other outcomes. Mean operation time was 4m42s longer in the SSCS-group compared to the conventional CS-group (58m versus 53m; 95%CI 2m44s-6m40s). Mean recovery time was 14m46s shorter (114m versus 129m; 95%CI 3m20s-26m).

CONCLUSION

Adverse maternal and neonatal outcomes were not increased after skin-to-skin cesarean compared to conventional cesarean delivery.

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.

Data elements and validation methods used for electronic surveillance of health care-associated infections: a systematic review

BACKGROUND

We describe the primary data sources, data elements, and validation methods currently used in electronic surveillance systems (ESS) for identification and surveillance of health care-associated infections (HAIs), and compares these data elements and validation methods with recommended standards.

METHODS

Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a PubMed and manual search was conducted to identify research articles describing ESS for identification and surveillance of HAIs published January 1, 2009-August 31, 2014. Selected articles were evaluated to determine what data elements and validation methods were included.

RESULTS

Among the 509 articles identified in the original literature search, 30 met the inclusion criteria. Whereas the majority of studies (83%) used recommended data sources and validated the numerator (80%), only 10% of studies performed external and internal validation. In addition, there was variation in the ESS data formats used.

CONCLUSIONS

Our findings suggest that the majority of ESS for HAI surveillance use standard definitions, but the lack of widespread internal data, denominator, and external validation in these systems reduces the reliability of their findings. Additionally, advanced programming skills are required to create, implement, and maintain these systems and to reduce the variability in data formats.

Data use and effectiveness in electronic surveillance of healthcare associated infections in the 21st century: a systematic review

OBJECTIVE

As more electronic health records have become available during the last decade, we aimed to uncover recent trends in use of electronically available patient data by electronic surveillance systems for healthcare associated infections (HAIs) and identify consequences for system effectiveness.

METHODS

A systematic review of published literature evaluating electronic HAI surveillance systems was performed. The PubMed service was used to retrieve publications between January 2001 and December 2011. Studies were included in the review if they accurately described what electronic data were used and if system effectiveness was evaluated using sensitivity, specificity, positive predictive value, or negative predictive value. Trends were identified by analyzing changes in the number and types of electronic data sources used.

RESULTS

26 publications comprising discussions on 27 electronic systems met the eligibility criteria. Trend analysis showed that systems use an increasing number of data sources which are either medico-administrative or clinical and laboratory-based data. Trends on the use of individual types of electronic data confirmed the paramount role of microbiology data in HAI detection, but also showed increased use of biochemistry and pharmacy data, and the limited adoption of clinical data and physician narratives. System effectiveness assessments indicate that the use of heterogeneous data sources results in higher system sensitivity at the expense of specificity.

CONCLUSIONS

Driven by the increased availability of electronic patient data, electronic HAI surveillance systems use more data, making systems more sensitive yet less specific, but also allow systems to be tailored to the needs of healthcare institutes' surveillance programs.

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.

Automated surveillance for healthcare-associated infections: opportunities for improvement

Surveillance of healthcare-associated infections is a cornerstone of infection prevention programs, and reporting of infection rates is increasingly required. Traditionally, surveillance is based on manual medical records review; however, this is very labor intensive and vulnerable to misclassification. Existing electronic surveillance systems based on classification algorithms using microbiology results, antibiotic use data, and/or discharge codes have increased the efficiency and completeness of surveillance by preselecting high-risk patients for manual review. However, shifting to electronic surveillance using multivariable prediction models based on available clinical patient data will allow for even more efficient detection of infection. With ongoing developments in healthcare information technology, implementation of the latter surveillance systems will become increasingly feasible. As with current predominantly manual methods, several challenges remain, such as completeness of postdischarge surveillance and adequate adjustment for underlying patient characteristics, especially for comparison of healthcare-associated infection rates across institutions.

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

We validated population-based hospital, emergency room, and physician claim databases for the detection of surgical site infections against the reference standard of clinical surveillance. Although these data sets are highly specific and could be used to define research cohorts, their low sensitivity and positive predictive value make them inadequate for use as quality indicators.