Getting it right: automated surveillance of healthcare-associated infections

How effective are monthly departmental tracer surveys? A 5-year retrospective study of 138 surveys in 96 departments

BACKGROUND

Repeat department-wide surveys are commonly employed for infection control. There remains debate concerning their cost-effectivess. The aim of the study was to measure the impact of repeat department-wide surveys in major in-patient departments (IPDs) and ambulatory facilities (AFs) in a tertiary care hospital. This was a retrospective study of 138 surveys condcuted in 96 departments over a 5-year period.

METHODS

Two itemized questionnaires were designed to assess the most frequently inadequately adhered to infection control measures: one for IPD (with 21 items) and the other for AF (with 17 items).

RESULTS

A total of 72 surveys were conducted in 49 IPDs, of which 39 (54%) were repeat surveys, and 66 surveys in 47 AFs, of which 33 (50%) were repeat surveys. The baseline rate of adherence/department was 71% ± 14 for the IPD, with an increase from the first to the last survey to 82% ± 13 (P = .037). In 15/21 measured infection control items, adherence improved. Adherence to infection control items was lower at baseline in the AFs than in the IPDs (63 ± 27), with an increase to 76 ± 20 (non significant). Although adherence improved for 9 items, it deteriorated in another 8, producing an overall statistically unchanged outcome.

CONCLUSION

Repeat whole-department surveys contribute moderately to increased adherence to infection control guidelines. AFs demonstrate lower rates of adherence to infection control guidelines and are less receptive to educational measures.

Automated surveillance of non-ventilator-associated hospital-acquired pneumonia (nvHAP): a systematic literature review

BACKGROUND

Hospital-acquired pneumonia (HAP) and its specific subset, non-ventilator hospital-acquired pneumonia (nvHAP) are significant contributors to patient morbidity and mortality. Automated surveillance systems for these healthcare-associated infections have emerged as a potentially beneficial replacement for manual surveillance. This systematic review aims to synthesise the existing literature on the characteristics and performance of automated nvHAP and HAP surveillance systems.

METHODS

We conducted a systematic search of publications describing automated surveillance of nvHAP and HAP. Our inclusion criteria covered articles that described fully and semi-automated systems without limitations on patient demographics or healthcare settings. We detailed the algorithms in each study and reported the performance characteristics of automated systems that were validated against specific reference methods. Two published metrics were employed to assess the quality of the included studies.

RESULTS

Our review identified 12 eligible studies that collectively describe 24 distinct candidate definitions, 23 for fully automated systems and one for a semi-automated system. These systems were employed exclusively in high-income countries and the majority were published after 2018. The algorithms commonly included radiology, leukocyte counts, temperature, antibiotic administration, and microbiology results. Validated surveillance systems' performance varied, with sensitivities for fully automated systems ranging from 40 to 99%, specificities from 58 and 98%, and positive predictive values from 8 to 71%. Validation was often carried out on small, pre-selected patient populations.

CONCLUSIONS

Recent years have seen a steep increase in publications on automated surveillance systems for nvHAP and HAP, which increase efficiency and reduce manual workload. However, the performance of fully automated surveillance remains moderate when compared to manual surveillance. The considerable heterogeneity in candidate surveillance definitions and reference standards, as well as validation on small or pre-selected samples, limits the generalisability of the findings. Further research, involving larger and broader patient populations is required to better understand the performance and applicability of automated nvHAP surveillance.

Concerns and frustrations about the public reporting of device-related healthcare-associated infections: Perspectives of hospital leaders and staff

BACKGROUND

Public reporting of healthcare-associated infections (HAIs) aims to incentivize improvement in infection prevention. The motivation and mechanisms of public reporting have raised concerns about the reliability of this data, but little is known about the specific concerns of hospital leaders and staff. This study sought to better understand perspectives of individuals in these roles regarding the identification and public reporting of HAIs.

METHODS

We conducted interviews with 471 participants including hospitals leaders (eg, administrative and clinical leaders) and hospital staff (eg, physicians and nurses) between 2017 and 2019 across 18 US hospitals. A semistructured interview guide was used to explore perspectives about the use of HAI data within the context of management strategies used to support infection prevention.

RESULTS

Interviewees described concerns about public reporting of HAI data, including a lack of trust in the data and inadvertent consequences of its public reporting, as well as specific frustrations related to the identification and accountability for publicly-reported HAIs.

CONCLUSION

Concerns and frustrations related to public reporting of HAI data highlight the need for improved guidelines, transparency, and incentives. Efforts to build trust in publicly-reported HAI data can help ensure this information is used effectively to improve infection prevention practices.