Should International Classification of Diseases codes be used to survey hospital-acquired pneumonia?

Clinical challenge of diagnosing non-ventilator hospital-acquired pneumonia and identifying causative pathogens: a narrative review

Non-ventilated hospital-acquired pneumonia (NV-HAP) is associated with a significant healthcare burden, arising from high incidence and associated morbidity and mortality. However, accurate identification of cases remains challenging. At present, there is no gold-standard test for the diagnosis of NV-HAP, requiring instead the blending of non-specific signs and investigations. Causative organisms are only identified in a minority of cases. This has significant implications for surveillance, patient outcomes and antimicrobial stewardship. Much of the existing research in HAP has been conducted among ventilated patients. The paucity of dedicated NV-HAP research means that conclusions regarding diagnostic methods, pathology and interventions must largely be extrapolated from work in other settings. Progress is also limited by the lack of a widely agreed definition for NV-HAP. The diagnosis of NV-HAP has large scope for improvement. Consensus regarding a case definition will allow meaningful research to improve understanding of its aetiology and the heterogeneity of outcomes experienced by patients. There is potential to optimize the role of imaging and to incorporate novel techniques to identify likely causative pathogens. This would facilitate both antimicrobial stewardship and surveillance of an important healthcare-associated infection. This narrative review considers the utility of existing methods to diagnose NV-HAP, with a focus on the significance and challenge of identifying pathogens. It discusses the limitations in current techniques, and explores the potential of emergent molecular techniques to improve microbiological diagnosis and outcomes for patients.

Performance of ICD-10-AM codes for quality improvement monitoring of hospital-acquired pneumonia in a haematology-oncology casemix in Victoria, Australia

BACKGROUND

The Australian hospital-acquired complication (HAC) policy was introduced to facilitate negative funding adjustments in Australian hospitals using ICD-10-AM codes.

OBJECTIVE

The aim of this study was to determine the positive predictive value (PPV) of the ICD-10-AM codes in the HAC framework to detect hospital-acquired pneumonia in patients with cancer and to describe any change in PPV before and after implementation of an electronic medical record (EMR) at our centre.

METHOD

A retrospective case review of all coded pneumonia episodes at the Peter MacCallum Cancer Centre in Melbourne, Australia spanning two time periods (01 July 2015 to 30 June 2017 [pre-EMR period] and 01 September 2020 to 28 February 2021 [EMR period]) was performed to determine the proportion of events satisfying standardised surveillance definitions.

RESULTS

HAC-coded pneumonia occurred in 3.66% (n = 151) of 41,260 separations during the study period. Of the 151 coded pneumonia separations, 27 satisfied consensus surveillance criteria, corresponding to an overall PPV of 0.18 (95% CI: 0.12, 0.25). The PPV was approximately three times higher following EMR implementation (0.34 [95% CI: 0.19, 0.53] versus 0.13 [95% CI: 0.08, 0.21]; p = .013).

CONCLUSION

The current HAC definition is a poor-to-moderate classifier for hospital-acquired pneumonia in patients with cancer and, therefore, may not accurately reflect hospital-level quality improvement. Implementation of an EMR did enhance case detection, and future refinements to administratively coded data in support of robust monitoring frameworks should focus on EMR systems.

IMPLICATIONS

Although ICD-10-AM data are readily available in Australian healthcare settings, these data are not sufficient for monitoring and reporting of hospital-acquired pneumonia in haematology-oncology patients.

Best Practices for Identifying Hospitalized Lower Respiratory Tract Infections Using Administrative Data: A Systematic Literature Review of Validation Studies

INTRODUCTION

Estimating the burden of lower respiratory tract infections (LRTIs) increasingly relies on administrative databases using International Classification of Diseases (ICD) codes, but no standard methodology exists. We defined best practices for ICD-based algorithms that estimate LRTI incidence in adults.

METHODS

We conducted a systematic review of validation studies assessing the use of ICD code-based algorithms to identify hospitalized LRTIs in adults, published in Medline, EMBASE, and LILACS between January 1996 and January 2022, according to PRISMA guidelines. We assessed sensitivity, specificity, and other accuracy measures of different algorithms.

RESULTS

We included 26 publications that used a variety of ICD code-based algorithms and gold standard criteria, and 18 reported sensitivity and/or specificity. Sensitivity was below 80% in 72% (38/53) of algorithms and specificity exceeded 90% in 77% (37/48). Algorithms for all-cause LRTI (n = 18) that included only pneumonia codes in primary position (n = 3) had specificity greater than 90% but low sensitivity (55-72%). Sensitivity increased by 5-15%, with minimal loss in specificity, with the addition of primary codes for severe pneumonia (e.g. sepsis) while pneumonia codes were in secondary position, and by 13% with codes from LRTI-related infections (e.g. viral) or other respiratory diseases (e.g. empyema). Sensitivity increased by 8% when pneumonia codes were in any position, but specificity was not reported. In hospital-acquired pneumonia and pneumococcal-specific pneumonia, algorithms containing only nosocomial- or pathogen-specific ICD codes had poor sensitivity, which improved when broader pneumonia codes were added, in particular codes for unspecified organisms.

CONCLUSION

Our systematic review highlights that most ICD code-based algorithms are relatively specific, but miss a substantial number of hospitalized LRTI adult cases. Best practices to estimate LRTI incidence in this population include the use of all pneumonia ICD codes for any LRTI outcome and, to a lesser extent, those for other LRTI-related infections or respiratory diseases.

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.

VAP risk index: Early prediction and hospital phenotyping of ventilator-associated pneumonia using machine learning

BACKGROUND

Ventilator-associated pneumonia (VAP) is a leading cause of morbidity and mortality in intensive care units (ICUs). Early identification of patients at risk of VAP enables early intervention, which in turn improves patient outcomes. We developed a predictive model for individualized risk assessment utilizing machine learning to identify patients at risk of developing VAP.

METHODS

The Philips eRI dataset, a multi-institution electronic medical record (EMR), was used for model development. For adult (≥18y) patients, we propose a set of criteria using indications of the start of a new antibiotic treatment temporally contiguous to a microbiological test to mark suspected infection events, of which those with a positive culture are labeled as presumed VAP if 1) the event occurs at least 48 h after intubation, and 2) there are no indications of community-acquired pneumonia (CAP) or other hospital-acquired infections (HAI) in the patient charts. The resulting VAP and no-VAP (control) cases were then used to build an ensemble of decision trees to predict the risk of VAP in the next 24 h using data on patients' demographics, vitals, labs, and ventilator settings.

RESULTS

The resulting model predicts the development of VAP 24 h in advance with an AUC of 76 % and AUPRC of 75 %. Additionally, we group hospitals that are similar in healthcare processes into distinct clusters and characterize VAP prediction for the identified hospital clusters. We show inter-hospital (teaching status and healthcare processes) and cohort-specific (age groups, gender, early vs late VAP, ICU mortality status) differences in VAP prediction and associated symptomologies.

CONCLUSIONS

Our proposed VAP criteria use clinical actions to mark incidences of presumed VAP infection, which enables the development of models for early detection of these events. We curated a patient cohort using these criteria and used it to build a model for predicting impending VAP events prior to clinical suspicions. We present a clustering approach for tailoring the VAP prediction model for different hospital types based on their EMR data characteristics. The model provides an instantaneous risk score that allows early interventions and confirmatory diagnostic actions.

Association between hospital onset of infection and outcomes in sepsis patients - A propensity score matched cohort study based on health claims data in Germany

BACKGROUND

Hospital-acquired infections are a common source of sepsis. Hospital onset of sepsis was found to be associated with higher acute mortality and hospital costs, yet its impact on long-term patient-relevant outcomes and costs is unknown.

OBJECTIVE

We aimed to assess the association between sepsis origin and acute and long-term outcomes based on a nationwide population-based cohort of sepsis patients in Germany.

METHODS

This retrospective cohort study used nationwide health claims data from 23 million health insurance beneficiaries. Sepsis patients with hospital-acquired infections (HAI) were identified by ICD-10-codes in a cohort of adult patients with hospital-treated sepsis between 2013 and 2014. Cases without these ICD-10-codes were considered as sepsis cases with community-acquired infection (CAI) and were matched with HAI sepsis patients by propensity score matching. Outcomes included in-hospital/12-month mortality and costs, as well as readmissions and nursing care dependency until 12 months postsepsis.

RESULTS

We matched 33,110 HAI sepsis patients with 28,614 CAI sepsis patients and 22,234 HAI sepsis hospital survivors with 19,364 CAI sepsis hospital survivors. HAI sepsis patients had a higher hospital mortality than CAI sepsis patients (32.8% vs. 25.4%, RR 1.3, p < .001). Similarly, 12-months postacute mortality was higher (37.2% vs. 30.1%, RR=1.2, p < .001). Hospital and 12-month health care costs were 178% and 22% higher in HAI patients than in CAI patients, respectively. Twelve months postsepsis, HAI sepsis survivors were more often newly dependent on nursing care (33.4% vs. 24.0%, RR=1.4, p < .001) and experienced 5% more hospital readmissions (mean number of readmissions: 2.1 vs. 2.0, p < .001).

CONCLUSIONS

HAI sepsis patients face an increased risk of adverse outcomes both during the acute sepsis episode and in the long-term. Measures to prevent HAI and its progression into sepsis may be an opportunity to mitigate the burden of long-term impairments and costs of sepsis, e.g., by early detection of HAI progressing into sepsis, particularly in normal wards; adequate sepsis management and adherence to sepsis bundles in hospital-acquired sepsis; and an improved infection prevention and control.

Incidence and Outcomes of Non-Ventilator-Associated Hospital-Acquired Pneumonia in 284 US Hospitals Using Electronic Surveillance Criteria

Importance

Non-ventilator-associated hospital-acquired pneumonia (NV-HAP) is a common and deadly hospital-acquired infection. However, inconsistent surveillance methods and unclear estimates of attributable mortality challenge prevention.

Objective

To estimate the incidence, variability, outcomes, and population attributable mortality of NV-HAP.

Design, Setting, and Participants

This cohort study retrospectively applied clinical surveillance criteria for NV-HAP to electronic health record data from 284 US hospitals. Adult patients admitted to the Veterans Health Administration hospital from 2015 to 2020 and HCA Healthcare hospitals from 2018 to 2020 were included. The medical records of 250 patients who met the surveillance criteria were reviewed for accuracy.

Exposures

NV-HAP, defined as sustained deterioration in oxygenation for 2 or more days in a patient who was not ventilated concurrent with abnormal temperature or white blood cell count, performance of chest imaging, and 3 or more days of new antibiotics.

Main Outcomes and Measures

NV-HAP incidence, length-of-stay, and crude inpatient mortality. Attributable inpatient mortality by 60 days follow-up was estimated using inverse probability weighting, accounting for both baseline and time-varying confounding.

Results

Among 6 022 185 hospitalizations (median [IQR] age, 66 [54-75] years; 1 829 475 [26.1%] female), there were 32 797 NV-HAP events (0.55 per 100 admissions [95% CI, 0.54-0.55] per 100 admissions and 0.96 per 1000 patient-days [95% CI, 0.95-0.97] per 1000 patient-days). Patients with NV-HAP had multiple comorbidities (median [IQR], 6 [4-7]), including congestive heart failure (9680 [29.5%]), neurologic conditions (8255 [25.2%]), chronic lung disease (6439 [19.6%]), and cancer (5,467 [16.7%]); 24 568 cases (74.9%) occurred outside intensive care units. Crude inpatient mortality was 22.4% (7361 of 32 797) for NV-HAP vs 1.9% (115 530 of 6 022 185) for all hospitalizations; 12 449 (8.0%) were discharged to hospice. Median [IQR] length-of-stay was 16 (11-26) days vs 4 (3-6) days. On medical record review, pneumonia was confirmed by reviewers or bedside clinicians in 202 of 250 patients (81%). It was estimated that NV-HAP accounted for 7.3% (95% CI, 7.1%-7.5%) of all hospital deaths (total hospital population inpatient death risk of 1.87% with NV-HAP events included vs 1.73% with NV-HAP events excluded; risk ratio, 0.927; 95% CI, 0.925-0.929).

Conclusions and Relevance

In this cohort study, NV-HAP, which was defined using electronic surveillance criteria, was present in approximately 1 in 200 hospitalizations, of whom 1 in 5 died in the hospital. NV-HAP may account for up to 7% of all hospital deaths. These findings underscore the need to systematically monitor NV-HAP, define best practices for prevention, and track their impact.

Electronic surveillance criteria for non-ventilator-associated hospital-acquired pneumonia: Assessment of reliability and validity

OBJECTIVE

Surveillance of non-ventilator-associated hospital-acquired pneumonia (NV-HAP) is complicated by subjectivity and variability in diagnosing pneumonia. We compared a fully automatable surveillance definition using routine electronic health record data to manual determinations of NV-HAP according to surveillance criteria and clinical diagnoses.

METHODS

We retrospectively applied an electronic surveillance definition for NV-HAP to all adults admitted to Veterans' Affairs (VA) hospitals from January 1, 2015, to November 30, 2020. We randomly selected 250 hospitalizations meeting NV-HAP surveillance criteria for independent review by 2 clinicians and calculated the percent of hospitalizations with (1) clinical deterioration, (2) CDC National Healthcare Safety Network (CDC-NHSN) criteria, (3) NV-HAP according to a reviewer, (4) NV-HAP according to a treating clinician, (5) pneumonia diagnosis in discharge summary; and (6) discharge diagnosis codes for HAP. We assessed interrater reliability by calculating simple agreement and the Cohen κ (kappa).

RESULTS

Among 3.1 million hospitalizations, 14,023 met NV-HAP electronic surveillance criteria. Among reviewed cases, 98% had a confirmed clinical deterioration; 67% met CDC-NHSN criteria; 71% had NV-HAP according to a reviewer; 60% had NV-HAP according to a treating clinician; 49% had a discharge summary diagnosis of pneumonia; and 82% had NV-HAP according to any definition according to at least 1 reviewer. Only 8% had diagnosis codes for HAP. Interrater agreement was 75% (κ = 0.50) for CDC-NHSN criteria and 78% (κ = 0.55) for reviewer diagnosis of NV-HAP.

CONCLUSIONS

Electronic NV-HAP surveillance criteria correlated moderately with existing manual surveillance criteria. Reviewer variability for all manual assessments was high. Electronic surveillance using clinical data may therefore allow for more consistent and efficient surveillance with similar accuracy compared to manual assessments or diagnosis codes.

Nonventilator hospital-acquired pneumonia: A call to action

In 2020 a group of U.S. healthcare leaders formed the National Organization to Prevent Hospital-Acquired Pneumonia (NOHAP) to issue a call to action to address non-ventilator-associated hospital-acquired pneumonia (NVHAP). NVHAP is one of the most common and morbid healthcare-associated infections, but it is not tracked, reported, or actively prevented by most hospitals. This national call to action includes (1) launching a national healthcare conversation about NVHAP prevention; (2) adding NVHAP prevention measures to education for patients, healthcare professionals, and students; (3) challenging healthcare systems and insurers to implement and support NVHAP prevention; and (4) encouraging researchers to develop new strategies for NVHAP surveillance and prevention. The purpose of this document is to outline research needs to support the NVHAP call to action. Primary needs include the development of better models to estimate the economic cost of NVHAP, to elucidate the pathophysiology of NVHAP and identify the most promising pathways for prevention, to develop objective and efficient surveillance methods to track NVHAP, to rigorously test the impact of prevention strategies proposed to prevent NVHAP, and to identify the policy levers that will best engage hospitals in NVHAP surveillance and prevention. A joint task force developed this document including stakeholders from the Veterans' Health Administration (VHA), the U.S. Centers for Disease Control and Prevention (CDC), The Joint Commission, the American Dental Association, the Patient Safety Movement Foundation, Oral Health Nursing Education and Practice (OHNEP), Teaching Oral-Systemic Health (TOSH), industry partners and academia.

Gender differences in incidence and in-hospital outcomes of community-acquired, ventilator-associated and nonventilator hospital-acquired pneumonia in Spain

AIMS

We aim to compare the incidence and in-hospital outcomes of community-acquired pneumonia (CAP), ventilator-associated pneumonia (VAP) and nonventilator hospital-acquired pneumonia (NV-HAP) according to gender.

METHODS

This was a retrospective observational epidemiological study using the Spanish National Hospital Discharge Database for the years 2016 and 2017.

RESULTS

Of 277 785 hospital admissions, CAP was identified in 257 455 (41.04% females), VAP was identified in 3261 (30.42% females) and NV-HAP was identified in 17 069 (36.58% females). The incidence of all types of pneumonia was higher amongst males (CAP: incidence rate ratio [IRR] 1.05, 95% CI 1.03-1.06; VAP: IRR 1.36, 95% CI 1.26-1.46; and NV-HAP: IRR 1.16, 95% CI 1.14-1.18). The crude in-hospital mortality (IHM) rate for CAP was 11.44% in females and 11.80% in males (P = .005); for VAP IHM, the rate was approximately 35% in patients of both genders and for NV-HAP IHM, the rate was 23.97% for females and 26.40% for males (P < .001). After multivariable adjustment, in patients of both genders, older age and comorbidities were factors associated with IHM in the three types of pneumonia analysed. Female gender was a risk factor for IHM after VAP (OR 1.24; 95% CI 1.06-1.44), and no gender differences were found for CAP or NV-HAP.

CONCLUSIONS

Our findings show a difference between females and males, with females presenting a lower incidence of all types of pneumonia. However, female gender was a risk factor for IHM after VAP.

A successful program preventing nonventilator hospital-acquired pneumonia in a large hospital system

Objective:

To develop and evaluate a program to presvent hospital-acquired pneumonia (HAP).

Design:

Prospective, observational, surveillance program to identify HAP before and after 7 interventions. An order set automatically triggered in programmatically identified high-risk patients.

Setting:

All 21 hospitals of an integrated healthcare system with 4.4 million members.

Patients:

All hospitalized patients.

Interventions:

Interventions for high-risk patients included mobilization, upright feeding, swallowing evaluation, sedation restrictions, elevated head of bed, oral care and tube care.

Results:

HAP rates decreased between 2012 and 2018: from 5.92 to 1.79 per 1,000 admissions (P = .0031) and from 24.57 to 6.49 per 100,000 members (P = .0014). HAP mortality decreased from 1.05 to 0.34 per 1,000 admissions and from 4.37 to 1.24 per 100,000 members. Concomitant antibiotic utilization demonstrated reductions of broad-spectrum antibiotics. Antibiotic therapy per 100,000 members was measured as follows: carbapenem days (694 to 463; P = .0020), aminoglycoside days (154 to 61; P = .0165), vancomycin days (2,087 to 1,783; P = .002), and quinolone days (2,162 to 1,287; P < .0001). Only cephalosporin use increased, driven by ceftriaxone days (264 to 460; P = .0009). Benzodiazepine use decreased between 2014 to 2016: 10.4% to 8.8% of inpatient days. Mortality for patients with HAP was 18% in 2012% and 19% in 2016 (P = .439).

Conclusion:

HAP rates, mortality, and broad-spectrum antibiotic use were all reduced significantly following these interventions, despite the absence of strong supportive literature for guidance. Most interventions augmented basic nursing care. None had risks of adverse consequences. These results support the need to examine practices to improve care despite limited literature and the need to further study these difficult areas of care.

Accuracy and reliability of electronic versus CDC surveillance criteria for non-ventilator hospital-acquired pneumonia

Nonventilator hospital-acquired pneumonia (NV-HAP) is one of the most common healthcare-associated infections, but most hospitals do not track it. We created a pilot electronic definition for NV-HAP and compared its accuracy to Centers for Disease Control and Prevention (CDC) criteria. Kappa values for the electronic definition and CDC criteria versus "true" pneumonia were similar: 0.40 and 0.47, respectively.

Development and Assessment of Objective Surveillance Definitions for Nonventilator Hospital-Acquired Pneumonia

IMPORTANCE

Hospital-acquired pneumonia is the most common health care-associated infection in the United States. Most cases occur in nonventilated patients, but many hospitals track hospital-acquired pneumonia only in ventilated patients because of the complexity and subjectivity of conducting surveillance for large numbers of nonventilated patients.

OBJECTIVE

To propose and assess potentially objective, efficient, and reproducible surveillance definitions for nonventilator hospital-acquired pneumonia (NV-HAP) using routine clinical data stored in electronic health record systems.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted in 2 tertiary referral and 2 community hospitals in Massachusetts between May 31, 2015, and July 1, 2018. All nonventilated patients aged 18 years or older who were admitted to these hospitals were included (N = 310 651).

EXPOSURES

Ten candidate definitions for NV-HAP based on clinically meaningful combinations of 6 potential surveillance criteria were proposed: worsening oxygenation, temperature higher than 38 °C (fever), abnormal white blood cell count of less than 4000/μL or more than 12 000/μL, performance of chest imaging, submission of respiratory specimen for culture, and 3 or more days of new antibiotics.

MAIN OUTCOMES AND MEASURES

Incidence rates, lengths of stay, hospital mortality rates, and odds ratios (ORs) for time to discharge and mortality compared with those of matched controls were calculated for each candidate definition. The ORs were adjusted for demographics, clinical service, comorbidities, and severity of illness.

RESULTS

The study analyzed 310 651 patients with 489 519 admissions, including 205 054 patients with 311 484 admissions of 3 or more days. Among the patients with 311 484 admissions, the mean (SD) patient age was 58.3 (19.3) years and 176 936 (56.8%) were of women. Incidence rates for candidate definitions per 100 admissions ranged from 3.4 events for worsening oxygenation alone to 0.9 event for worsening oxygenation and at least 3 days of new antibiotics to 0.6 event for worsening oxygenation, at least 3 days of new antibiotics, fever, abnormal white blood cell count, and performance of chest imaging. Crude mortality rates ranged from 16.1% (n = 2643) for patients with worsening oxygen alone to 27.7% (n = 868) for patients with worsening oxygenation, at least 3 days of antibiotics, fever or abnormal white blood cell count, and chest imaging. Patients who met NV-HAP candidate definitions remained in the hospital for twice as long as their matched controls (adjusted ORs ranged from 1.8 [95% CI, 1.7-1.8] to 2.1 [95% CI, 2.0-2.1]) and were 4 to 6 times as likely to die in the hospital (adjusted ORs ranged from 3.8 [95% CI, 3.5-4.0] to 6.5 [95% CI, 5.2-8.2]). Agreement between candidate definitions and clinical diagnoses was fair (κ = 0.33).

CONCLUSIONS AND RELEVANCE

These findings suggest that objective surveillance for NV-HAP using electronically computable definitions that incorporate common clinical criteria is feasible and generates incidence, mortality, and adjusted ORs for hospital mortality similar to estimates from manual surveillance. These definitions have the potential to facilitate widespread, automated surveillance for NV-HAP and thus inform the development and evaluation of prevention programs.

Development and validation of a semi-automated surveillance system-lowering the fruit for non-ventilator-associated hospital-acquired pneumonia (nvHAP) prevention

Objectives

Conducting manual surveillance of non-ventilator-associated hospital-acquired pneumonia (nvHAP) using ECDC (European Centre for Disease Prevention and Control) surveillance criteria is very resource intensive. We developed and validated a semi-automated surveillance system for nvHAP, and describe nvHAP incidence and aetiology at our hospital.

Methods

We applied an automated classification algorithm mirroring ECDC definition criteria to distinguish patients ‘not at risk’ from patients ‘at risk’ for suffering from nvHAP. ‘At risk’-patients were manually screened for nvHAP. For validation, we applied the reference standard of full manual evaluation to three validation samples comprising 2091 patients.

Results

Among the 39 519 University Hospital Zurich inpatient discharges in 2017, the algorithm identified 2454 ‘at-risk’ patients, reducing the number of medical records to be manually screened by 93.8%. From this subset, nvHAP was identified in 251 patients (0.64%, 95%CI: 0.57–0.73). Sensitivity, negative predictive value, and accuracy of semi-automated surveillance versus full manual surveillance were lowest in the validation sample consisting of patients with HAP according to the International Classification of Diseases (ICD-10) discharge diagnostic codes, with 97.5% (CI: 93.7–99.3%), 99.2% (CI: 97.9–99.8%), and 99.4% (CI: 98.4–99.8%), respectively. The overall incidence rate of nvHAP was 0.83/1000 patient days (95%CI: 0.73–0.94), with highest rates in haematology/oncology, cardiac and thoracic surgery, and internal medicine including subspecialties.

Conclusions

The semi-automated surveillance demonstrated a very high sensitivity, negative predictive value, and accuracy. This approach significantly reduces manual surveillance workload, thus making continuous nvHAP surveillance feasible as a pivotal element for successful prevention efforts.

Co-outbreak of multidrug resistance and a novel ST3006 Klebsiella pneumoniae in a neonatal intensive care unit: A retrospective study

The outbreak of carbapenem-resistant Klebsiella pneumoniae is a serious public health problem, especially in the neonatal intensive care unit (NICU).Fifteen K. pneumoniae strains were isolated from 7 neonates during June 3 to 28, 2017 in an NICU. Antimicrobial susceptibility was determined by the Vitek 2 system and microbroth dilution method. Multilocus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE) were used to analyze the genetic relatedness of the isolates. Whole-genome sequencing and gene function analysis were performed to investigate pathogenicity and drug resistance and screen genomic islands.Three clones of K. pneumoniae were identified from 7 neonates: 7 strains of ST37, 7 of novel ST3006, and 1 of ST1224. Gene sequencing showed that the kpn1343 (ST37) strain harbored 12 resistance genes (OXA-33, TEM-1, SHV-11, AAC (6')-IId, AAC (3)-IIa, AAC (6')-Ib-cr, catB3, arr-3, sul1, oqxB, oqxA, CRP, and catB3) and included 15 genomic islands and 205 reduced virulence genes. The kpn1344 (ST3006) strain harbored 4 antibiotic-resistant genes (TEM-1, CTX-M-3, vgaC, and CRP) and included 19 genomic islands and 209 reduced virulence genes. MLST and PFGE showed that 15 strains of K. pneumoniae were divided into 3 groups with a high level of homology. ST1224 (kpn1362) was isolated on June 28, 2017, which was 10 days after the last isolate (kpn1359, June 18, 2017); thus, we speculated that ST1224 was not the clone that caused the outbreak.This co-outbreak of K. pneumoniae involved 2 clones: ST37 and ST3006. ST37 carried the multidrug-resistant genes, such as OXA-33, TEM-1, and SHV-11, and ST3006 was a novel K. pneumoniae ST typing. Whole-genome sequencing may be an effective method for screening bacterial-resistant genes and their functions.