Administrative Data Fail to Accurately Identify Cases of Healthcare-Associated Infection

Measuring the Direct Medical Costs of Hospital-Onset Infections Using an Analogy Costing Framework

BACKGROUND

The majority of recent estimates on the direct medical cost attributable to hospital-onset infections (HOIs) has focused on device- or procedure-associated HOIs. The attributable costs of HOIs that are not associated with device use or procedures have not been extensively studied.

OBJECTIVE

We developed simulation models of attributable cost for 16 HOIs and estimated the total direct medical cost, including nondevice-related HOIs in the USA for 2011 and 2015.

DATA AND METHODS

We used total discharge costs associated with HOI-related hospitalization from the National Inpatient Sample and applied an analogy costing methodology to develop simulation models of the costs attributable to HOIs. The mean attributable cost estimate from the simulation analysis was then multiplied by previously published estimates of the number of HOIs for 2011 and 2015 to generate national estimates of direct medical costs.

RESULTS

After adjusting all estimates to 2017 US dollars, attributable cost estimates for select nondevice-related infections attributable cost estimates ranged from $7661 for ear, eye, nose, throat, and mouth (EENTM) infections to $27,709 for cardiovascular system infections in 2011; and from $8394 for EENTM to $26,445 for central nervous system infections in 2016 (based on 2015 incidence data). The national direct medical costs for all HOIs were $14.6 billion in 2011 and $12.1 billion in 2016. Nondevice- and nonprocedure-associated HOIs comprise approximately 26-28% of total HOI costs.

CONCLUSION

Results suggest that nondevice- and nonprocedure-related HOIs result in considerable costs to the healthcare system.

Modernizing Surgical Quality: A Novel Approach to Improving Detection of Surgical Site Infections in the Veteran Population

Introduction: Surgical site infections (SSIs) are an important quality measure. Identifying SSIs often relies upon a time-intensive manual review of a sample of common surgical cases. In this study, we sought to develop a predictive model for SSI identification using antibiotic pharmacy data extracted from the electronic medical record (EMR). Methods: A retrospective analysis was performed on all surgeries at a Veteran Affair's Medical Center between January 9, 2020 and January 9, 2022. Patients receiving outpatient antibiotics within 30 days of their surgery were identified, and chart review was performed to detect instances of SSI as defined by VA Surgery Quality Improvement Program criteria. Binomial logistic regression was used to select variables to include in the model, which was trained using k-fold cross validation. Results: Of the 8,253 surgeries performed during the study period, patients in 793 (9.6%) cases were prescribed outpatient antibiotics within 30 days of their procedure; SSI was diagnosed in 128 (1.6%) patients. Logistic regression identified time from surgery to antibiotic prescription, ordering location of the prescription, length of prescription, type of antibiotic, and operating service as important variables to include in the model. On testing, the final model demonstrated good predictive value with c-statistic of 0.81 (confidence interval: 0.71-0.90). Hosmer-Lemeshow testing demonstrated good fit of the model with p value of 0.97. Conclusion: We propose a model that uses readily attainable data from the EMR to identify SSI occurrences. In conjunction with local case-by-case reporting, this tool can improve the accuracy and efficiency of SSI identification.

Strategies to prevent ventilator-associated pneumonia, ventilator-associated events, and nonventilator hospital-acquired pneumonia in acute-care hospitals: 2022 Update

The purpose of this document is to highlight practical recommendations to assist acute care hospitals to prioritize and implement strategies to prevent ventilator-associated pneumonia (VAP), ventilator-associated events (VAE), and non-ventilator hospital-acquired pneumonia (NV-HAP) in adults, children, and neonates. This document updates the Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals published in 2014. This expert guidance document is sponsored by the Society for Healthcare Epidemiology (SHEA), and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America, the American Hospital Association, the Association for Professionals in Infection Control and Epidemiology, and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise.

Advanced Practice Provider-inclusive Staffing Models and Patient Outcomes in Pediatric Critical Care

BACKGROUND

Pediatric intensive care units (PICUs) are increasingly staffed with advanced practice providers (APPs), supplementing traditional physician staffing models.

OBJECTIVES

We evaluate the effect of APP-inclusive staffing models on clinical outcomes and resource utilization in US PICUs.

RESEARCH DESIGN

Retrospective cohort study of children admitted to PICUs in 9 states in 2016 using the Healthcare Cost and Utilization Project's State Inpatient Databases. PICU staffing models were assessed using a contemporaneous staffing survey. We used multivariate regression to examine associations between staffing models with and without APPs and outcomes.

MEASURES

The primary outcome was in-hospital mortality. Secondary outcomes included odds of hospital acquired conditions and ICU and hospital lengths of stay.

RESULTS

The sample included 38,788 children in 40 PICUs. Patients admitted to PICUs with APP-inclusive staffing were younger (6.1±5.9 vs. 7.1±6.2 y) and more likely to have complex chronic conditions (64% vs. 43%) and organ failure on admission (25% vs. 22%), compared with patients in PICUs with physician-only staffing. There was no difference in mortality between PICU types [adjusted odds ratio (AOR): 1.23, 95% confidence interval (CI): 0.83-1.81, P=0.30]. Patients in PICUs with APP-inclusive staffing had lower odds of central line-associated blood stream infections (AOR: 0.76, 95% CI: 0.59-0.98, P=0.03) and catheter-associated urinary tract infections (AOR: 0.73, 95% CI: 0.61-0.86, P<0.001). There were no differences in lengths of stay.

CONCLUSIONS

Despite being younger and sicker, children admitted to PICUs with APP-inclusive staffing had no increased odds of mortality and lower odds of some hospital acquired conditions compared with those in PICUs with physician-only staffing. Further research can inform APP integration strategies which optimize outcomes.

Evaluating inpatient adverse outcomes under California's Delivery System Reform Incentive Payment Program

OBJECTIVE

The California Delivery System Reform Incentive Payment Program (DSRIP) provided incentive payments to Designated Public Hospitals (DPHs) to improve quality of care. We assessed the program's impact on reductions in sepsis mortality, central line-associated bloodstream infections (CLABSIs), venous thromboembolisms (VTEs), and hospital-acquired pressure ulcers (HAPUs).

DATA SOURCES

We used 2009-2014 discharge data from California hospitals.

STUDY DESIGN

We used a pre-post study design with a comparison group. We constructed propensity scores and used them to assign inverse probability weights according to their similarity to DPH discharges. Interaction term coefficients of time trends and treatment group provided significance testing.

DATA EXTRACTION

We used Patient Safety Indicators for CLABSI, HAPU, and VTE, and constructed a sepsis mortality measure.

PRINCIPAL FINDINGS

Discharges from DPHs and non-DPHs both saw decreases in the four outcomes over the DSRIP period (2010-2014). The difference-in-difference estimator (DD) for sepsis was only significant during two time periods, comparing 2010 with 2012 (DD: -2.90 percent, 95% CI: -5.08, -0.72 percent) and 2010 with 2014 (DD: -5.74, 95% CI: -8.76 percent, -2.72 percent); the DD estimator was not significant comparing 2010 with 2012 (DD: -1.30, 95% CI: -3.18 percent, 0.58 percent) or comparing 2010 with 2013 (DD: -3.05 percent, 95% CI: -6.50 percent, 0.40 percent). For CLABSI, we did not find any meaningful differences between DPHs and non-DPHs across the four time periods. For HAPU and VTE, the only significant DD estimator compared 2014 with 2010.

CONCLUSIONS

We did not find that DPHs participating in DSRIP outperformed non-DPHs during the DSRIP program. Our results were robust to multiple sensitivity analyses. Given multiple concurrent inpatient safety initiatives, it was challenging to assign improvements over time periods to DSRIP.

The association of burn patient volume with patient safety indicators and mortality in the US

INTRODUCTION

Clinical volume has been associated with rate of complications and mortality for various conditions and procedures. We aim to analyze the relationship between annual hospital burn admission, patient safety indicators (PSI), line infections, and inpatient mortality. We hypothesize that high facility volume will correlate with better outcomes.

METHODS

All burn admissions with complete data for total body surface area (TBSA) and depth were extracted from the Nationwide Inpatient Sample from 2002-2011. Predictor variables included age, gender, comorbidities, %TBSA, burn depth, and inhalation injury. Surgically relevant PSIs were drawn from the Healthcare Cost & Utilization Project and included: sepsis, venous thromboembolic disease, hemorrhage, pneumonia, and wound complications. Outcomes were analyzed with regression models.

RESULTS

Of the 57,468 encounters included, 3.1% died, 6.3% experienced >1 PSI event, and 0.3% experienced a catheter-associated urinary tract infections or central line associated blood stream infections. The most frequent PSI was pneumonia followed by sepsis and VTE. Annual hospital burn admission volume was independently associated with decreased odds of mortality (OR 0.99, 95% CI 0.99-0.99, p < 0.001) and PSIs (OR 0.99, 95% CI 0.99-0.99, p = 0.031). There was no significant correlation with line infections. In both mortality and PSI models, age, %TBSA, inhalation injuries, and Elixhauser comorbidity score were significantly associated with adverse outcomes (p < 0.05).

CONCLUSION

There was a significant association between higher hospital volume and decreased likelihood of patient safety indicators and mortality. There was no observed relationship with line infections. These findings could inform future verification policies of US burn centers.

Validity and Reliability of Administrative Coded Data for the Identification of Hospital-Acquired Infections: An Updated Systematic Review with Meta-Analysis and Meta-Regression Analysis

OBJECTIVE

To conduct an updated assessment of the validity and reliability of administrative coded data (ACD) in identifying hospital-acquired infections (HAIs).

METHODS

We systematically searched three libraries for studies on ACD detecting HAIs compared to manual chart review. Meta-analyses were conducted for prosthetic and nonprosthetic surgical site infections (SSIs), Clostridium difficile infections (CDIs), ventilator-associated pneumonias/events (VAPs/VAEs) and non-VAPs/VAEs, catheter-associated urinary tract infections (CAUTIs), and central venous catheter-related bloodstream infections (CLABSIs). A random-effects meta-regression model was constructed.

RESULTS

Of 1,906 references found, we retrieved 38 documents, of which 33 provided meta-analyzable data (N = 567,826 patients). ACD identified HAI incidence with high specificity (≥93 percent), prosthetic SSIs with high sensitivity (95 percent), and both CDIs and nonprosthetic SSIs with moderate sensitivity (65 percent). ACD exhibited substantial agreement with traditional surveillance methods for CDI (κ = 0.70) and provided strong diagnostic odds ratios (DORs) for the identification of CDIs (DOR = 772.07) and SSIs (DOR = 78.20). ACD performance in identifying nosocomial pneumonia depended on the ICD coding system (DORICD-10/ICD-9-CM  = 0.05; p = .036). Algorithmic coding improved ACD's sensitivity for SSIs up to 22 percent. Overall, high heterogeneity was observed, without significant publication bias.

CONCLUSIONS

Administrative coded data may not be sufficiently accurate or reliable for the majority of HAIs. Still, subgrouping and algorithmic coding as tools for improving ACD validity deserve further investigation, specifically for prosthetic SSIs. Analyzing a potential lower discriminative ability of ICD-10 coding system is also a pending issue.

Electronic Surveillance of Surgical Site Infections

BACKGROUND

Electronic health and administrative data are increasingly being used for identifying surgical site infections (SSI). We found an unexpectedly high number of patients who could not be classified definitively as having an infection or not. To further explore this, we present an electronic classification algorithm for conservative case finding and identify alterations that would adapt the method for other purposes.

METHODS

Two computer algorithms were created to identify SSI. One model used a strict National Healthcare Safety Network (NHSN) based SSI algorithm, which was applied to all discharges from 443,284 all discharges from four hospitals in Manhattan, NY, 2009 through 2012. The second model used discharges that only had NHSN-defined SSI procedures during the same period.

RESULTS

The strict SSI algorithm was able to classify SSI status for 27.3% of discharges; there was a high number of indeterminate cases. In contrast, the modified, less strict model, classified 97.2% of discharges with NHSN-approved SSI procedures.

CONCLUSION

Electronic records provide several options for aiding with the identification of infections in healthcare settings and can be tailored to suit specific uses. While algorithms for SSI classification should reflect the NHSN definition, our research emphasizes how variations of model building can affect the number of indeterminate cases that may necessitate manual review.

Potentially Preventable Hospitalizations and the Burden of Healthcare-Associated Infections

BACKGROUND

An estimated 4% of hospital admissions acquired healthcare-associated infections (HAIs) and accounted for $9.8 (USD) billion in direct cost during 2011. In 2010, nearly 140 000 of the 3.5 million potentially preventable hospitalizations (PPHs) may have acquired an HAI. There is a knowledge gap regarding the co-occurrence of these events.

AIMS

To estimate the period occurrences and likelihood of acquiring an HAI for the PPH population.

METHODS

Retrospective, cross-sectional study using logistic regression analysis of 2011 Texas Inpatient Discharge Public Use Data File including 2.6 million admissions from 576 acute care hospitals. Agency for Healthcare Research and Quality Prevention Quality Indicator software identified PPH, and existing administrative data identification methodologies were refined for Clostridium difficile infection, central line-associated bloodstream infection, catheter-associated urinary tract infection, and ventilator-associated pneumonia. Odds of acquiring HAIs when admitted with PPH were adjusted for demographic, health status, hospital, and community characteristics.

FINDINGS

We identified 272 923 PPH, 14 219 HAI, and 986 admissions with PPH and HAI. Odds of acquiring an HAI for diabetic patients admitted for lower extremity amputation demonstrated significantly increased odds ratio of 2.9 (95% confidence interval: 2.16-3.91) for Clostridium difficile infection. Other PPH patients had lower odds of acquiring HAI compared to non-PPH patients, and results were frequently significant.

CONCLUSIONS

Clinical implications include increased risk of HAI among diabetic patients admitted for lower extremity amputation. Methodological implications include identification of rare events for inpatient subpopulations and the need for improved codification of HAIs to improve cost and policy analyses regarding allocation of resources toward clinical improvements.

Burden of Six Healthcare-Associated Infections on European Population Health: Estimating Incidence-Based Disability-Adjusted Life Years through a Population Prevalence-Based Modelling Study

BACKGROUND

Estimating the burden of healthcare-associated infections (HAIs) compared to other communicable diseases is an ongoing challenge given the need for good quality data on the incidence of these infections and the involved comorbidities. Based on the methodology of the Burden of Communicable Diseases in Europe (BCoDE) project and 2011-2012 data from the European Centre for Disease Prevention and Control (ECDC) point prevalence survey (PPS) of HAIs and antimicrobial use in European acute care hospitals, we estimated the burden of six common HAIs.

METHODS AND FINDINGS

The included HAIs were healthcare-associated pneumonia (HAP), healthcare-associated urinary tract infection (HA UTI), surgical site infection (SSI), healthcare-associated Clostridium difficile infection (HA CDI), healthcare-associated neonatal sepsis, and healthcare-associated primary bloodstream infection (HA primary BSI). The burden of these HAIs was measured in disability-adjusted life years (DALYs). Evidence relating to the disease progression pathway of each type of HAI was collected through systematic literature reviews, in order to estimate the risks attributable to HAIs. For each of the six HAIs, gender and age group prevalence from the ECDC PPS was converted into incidence rates by applying the Rhame and Sudderth formula. We adjusted for reduced life expectancy within the hospital population using three severity groups based on McCabe score data from the ECDC PPS. We estimated that 2,609,911 new cases of HAI occur every year in the European Union and European Economic Area (EU/EEA). The cumulative burden of the six HAIs was estimated at 501 DALYs per 100,000 general population each year in EU/EEA. HAP and HA primary BSI were associated with the highest burden and represented more than 60% of the total burden, with 169 and 145 DALYs per 100,000 total population, respectively. HA UTI, SSI, HA CDI, and HA primary BSI ranked as the third to sixth syndromes in terms of burden of disease. HAP and HA primary BSI were associated with the highest burden because of their high severity. The cumulative burden of the six HAIs was higher than the total burden of all other 32 communicable diseases included in the BCoDE 2009-2013 study. The main limitations of the study are the variability in the parameter estimates, in particular the disease models' case fatalities, and the use of the Rhame and Sudderth formula for estimating incident number of cases from prevalence data.

CONCLUSIONS

We estimated the EU/EEA burden of HAIs in DALYs in 2011-2012 using a transparent and evidence-based approach that allows for combining estimates of morbidity and of mortality in order to compare with other diseases and to inform a comprehensive ranking suitable for prioritization. Our results highlight the high burden of HAIs and the need for increased efforts for their prevention and control. Furthermore, our model should allow for estimations of the potential benefit of preventive measures on the burden of HAIs in the EU/EEA.

Research Methods in Healthcare Epidemiology and Antimicrobial Stewardship: Use of Administrative and Surveillance Databases

Administrative and surveillance data are used frequently in healthcare epidemiology and antimicrobial stewardship (HE&AS) research because of their wide availability and efficiency. However, data quality issues exist, requiring careful consideration and potential validation of data. This methods paper presents key considerations for using administrative and surveillance data in HE&AS, including types of data available and potential use, data limitations, and the importance of validation. After discussing these issues, we review examples of HE&AS research using administrative data with a focus on scenarios when their use may be advantageous. A checklist is provided to help aid study development in HE&AS using administrative data.

Infect Control Hosp Epidemiol 2016;1–10

A Simple and Powerful Risk-Adjustment Tool for 30-day Mortality Among Inpatients

BACKGROUND

Risk adjustment for mortality is increasingly important in an era when hospitals and health care systems are being compared with respect to health outcomes and quality. A powerful predictive model has been developed to risk-adjust for 30-day mortality among inpatients, but it is complex and not widely used.

OBJECTIVE

To develop and validate a simpler model, with predictive power similar to more complex models.

RESEARCH DESIGN

This was a retrospective split-validation study. In a derivation cohort, a predictive model for 30-day mortality was developed using logistic regression with the Charlson comorbidity score, Laboratory-Based Acute Physiology Score, and age as the predictor variables. In the validation cohort, the performance and calibration of the model to predict 30-day mortality was examined.

SUBJECTS

All admissions to the medical service of 2 urban university-based teaching hospitals located in Bronx, New York, between July 1, 2002, and April 30, 2008.

MEASURES

All-cause mortality was taken from the social security death registry. Predictor variables were constructed from demographic characteristics, laboratory and billing data extracted from a clinical data repository.

RESULTS

The study sample included 147 991 admissions and overall 30-day mortality was 5.4%. The model had excellent discrimination, with a c-statistics of 0.8585 in the derivation cohort and 0.8484 in the validation cohort. The model accurately predicts 30-day mortality in all risk deciles.

CONCLUSIONS

This simple and powerful predictive model can be used by hospitals and health care systems as a risk-adjustment tool for quality and research purposes.

Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals: 2014 Update

Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format to assist acute care hospitals in implementing and prioritizing strategies to prevent ventilator-associated pneumonia (VAP) and other ventilator-associated events (VAEs) and to improve outcomes for mechanically ventilated adults, children, and neonates. This document updates "Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals," published in 2008. This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA) and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the American Hospital Association (AHA), the Association for Professionals in Infection Control and Epidemiology (APIC), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise. The list of endorsing and supporting organizations is presented in the introduction to the 2014 updates.

A cross-sectional survey of the acceptability of data collection processes for validation of a European point prevalence survey of healthcare-associated infections and antimicrobial use

BACKGROUND

Statistical measurements alone are insufficient to ensure robust data for point prevalence surveys (PPS) of healthcare-associated infections (HAI). Data quality is determined by the type of data, data collection methods and available resources. Data collectors' views regarding the acceptability of data collection process for validation studies are also important to consider.

AIM

To explore data collectors' views on the acceptability of data collection processes used for a European validation PPS of HAI and antimicrobial use (AMU).

METHODS

An anonymous online survey was conducted with 67 data collectors from 10 European countries involved in the study.

FINDINGS

Twenty-five (64.1%) participants viewed AMU data collection as easy/quite easy whereas only five (12.8%) thought HAI data collection was easy/quite easy. Six (17%) participants indicated that incentives and 21 (56.8%) that disincentives were possibly/definitely present for reporting cases of HAI. Engagement of staff was not thought to have adversely affected data collection as only one (2.6%) and five (15.4%) participants thought involvement of hospital PPS teams and administration was low/very low, respectively.

DISCUSSION

Participants believed the approaches used were appropriate but that more training was required prior to data collection, some case definitions should be reviewed and the number of variables reduced.

Measuring Surgical Site Infections in Children: Comparing Clinical, Electronic, and Administrative Data

BACKGROUND

Surgical site infections (SSIs) are an important end point and measure of quality of care. Surgical site infections can be identified using clinical registries, electronic surveillance, and administrative claims data. This study compared measurements of SSIs using these 3 different methods and estimated their implication for health care costs.

STUDY DESIGN

Data were obtained from 5,476 surgical patients treated at a single academic children's hospital (January 1, 2010 through August 31, 2014). Surgical site infections within 30 days were identified using a clinical registry in the NSQIP Pediatric, an electronic surveillance method (Nosocomial Infection Marker; MedMined), and billing claims. Infection rates, diagnostic characteristics, and attributable costs were estimated for each of the 3 measures of SSI.

RESULTS

Surgical site infections were observed in 2.24% of patients per NSQIP Pediatric definitions, 0.99% of patients per the Nosocomial Infection Marker, and 2.34% per billing claims definitions. Using NSQIP Pediatric as the clinical reference, Nosocomial Infection Marker had a sensitivity of 31.7% and positive predictive value of 72.2%, and billing claims had a sensitivity of 48.0% and positive predictive value of 46.1% for detection of an SSI. Nosocomial Infection Marker and billing claims overestimated the costs of SSIs by 108% and 41%, respectively.

CONCLUSIONS

There is poor correlation among SSIs measured using electronic surveillance, administrative claims, and clinically derived measures of SSI in the pediatric surgical population. Although these measures might be more convenient, clinically derived data, such as NSQIP Pediatric, may provide a more appropriate quality metric to estimate the postoperative burden of SSIs in children.

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.

Low Completeness of Bacteraemia Registration in the Danish National Patient Registry

Bacteraemia is associated with significant morbidity and mortality and timely access to relia-ble information is essential for health care administrators. Therefore, we investigated the complete-ness of bacteraemia registration in the Danish National Patient Registry (DNPR) containing hospital discharge diagnoses and surgical procedures for all non-psychiatric patients. As gold standard we identified bacteraemia patients in three defined areas of Denmark (~2.3 million inhabitants) from 2000 through 2011 by use of blood culture data retrieved from electronic microbiology databases. Diagnoses coded according to the International Classification of Diseases, version 10, and surgical procedure codes were retrieved from the DNPR. The codes were categorized into seven groups, ranked a priori according to the likelihood of bacteraemia. Completeness was analysed by contin-gency tables, for all patients and subgroups. We identified 58,139 bacteraemic episodes in 48,450 patients; 37,740 episodes (64.9%) were covered by one or more discharge diagnoses within the sev-en diagnosis/surgery groups and 18,786 episodes (32.3%) had a code within the highest priority group. Completeness varied substantially according to speciality (from 17.9% for surgical to 36.4% for medical), place of acquisition (from 26.0% for nosocomial to 36.2% for community), and mi-croorganism (from 19.5% for anaerobic Gram-negative bacteria to 36.8% for haemolytic strepto-cocci). The completeness increased from 25.1% in 2000 to 35.1% in 2011. In conclusion, one third of the bacteraemic episodes did not have a relevant diagnosis in the Danish administrative registry recording all non-psychiatric contacts. This source of information should be used cautiously to iden-tify patients with bacteraemia.

The Likelihood of Hospital Readmission Among Patients With Hospital-Onset Central Line-Associated Bloodstream Infections

OBJECTIVE

To determine whether central line-associated bloodstream infections (CLABSIs) increase the likelihood of readmission.

DESIGN

Retrospective matched cohort study for the years 2008-2009.

SETTING

Acute care hospitals.

PARTICIPANTS

Medicare recipients. CLABSI and readmission status were determined by linking National Healthcare Safety Network surveillance data to the Centers for Medicare and Medicaid Services' Medical Provider and Analysis Review in 8 states. Frequency matching was used on International Classification of Diseases, Ninth Revision, Clinical Modification procedure code category and intensive care unit status.

METHODS

We compared the rate of readmission among patients with and without CLABSI during an index hospitalization. Cox proportional hazard analysis was used to assess rate of readmission (the first hospitalization within 30 days after index discharge). Multivariate models included the following covariates: race, sex, length of index hospitalization stay, central line procedure code, Gagne comorbidity score, and individual chronic conditions.

RESULTS

Of the 8,097 patients, 2,260 were readmitted within 30 days (27.9%). The rate of first readmission was 7.1 events/person-year for CLABSI patients and 4.3 events/person-year for non-CLABSI patients (P<.001). The final model revealed a small but significant increase in the rate of 30-day readmissions for patients with a CLABSI compared with similar non-CLABSI patients. In the first readmission for CLABSI patients, we also observed an increase in diagnostic categories consistent with CLABSI, including septicemia and complications of a device.

CONCLUSIONS

Our analysis found a statistically significant association between CLABSI status and readmission, suggesting that CLABSI may have adverse health impact that extends beyond hospital discharge.

Burden of Clostridium difficile infection on hospital readmissions and its potential impact under the Hospital Readmission Reduction Program

BACKGROUND

Both Clostridium [corrected] difficile infection (CDI) rates in hospitals and interest in reducing 30-day readmission rates have increased dramatically in the United States. The objective of this study was to characterize the burden of CDI on 30-day hospital readmissions at a tertiary care health-system.

METHODS

A patient discharge database was used to identify patients with a CDI diagnosis (ICD-9 code 008.45) during their stay in 2012. Patients were classified as index admissions (CDI discharges) or 30-day readmissions (CDI readmissions). Readmission rates, length of stay (LOS), and time to readmission were assessed among CDI readmissions.

RESULTS

Among discharges from the health system (n = 51,353), 615 were diagnosed with CDI (1%). Thirty-day readmissions were more common among CDI discharges (30.1%) than non-CDI discharges (14.4%). Average LOS for CDI readmissions was 5-6 days longer than non-CDI readmissions. Time to readmission was shorter among CDI discharges diagnosed on admission than CDI discharges diagnosed later during their hospital stay (median, 7 days).

CONCLUSION

Reductions in hospital-onset CDI and readmission of patients with an index CDI can provide tremendous cost savings to hospitals. This calls for better infection control and antibiotic stewardship measures toward CDI management in the hospital and as patients transition to the next level of care.

Strategies to prevent ventilator-associated pneumonia in acute care hospitals: 2014 update

Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format to assist acute care hospitals in implementing and prioritizing strategies to prevent ventilator-associated pneumonia (VAP) and other ventilator-associated events (VAEs) and to improve outcomes for mechanically ventilated adults, children, and neonates. This document updates “Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals,” published in 2008. This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA) and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the American Hospital Association (AHA), the Association for Professionals in Infection Control and Epidemiology (APIC), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise. The list of endorsing and supporting organizations is presented in the introduction to the 2014 updates.

Comparison of the Use of Administrative Data and an Active System for Surveillance of Invasive Aspergillosis

Background.

Administrative data, such as International Classification of Diseases, Ninth Revision (ICD-9) codes, are readily available and are an attractive option for surveillance and quality assessment within a single institution or for interinstitutional comparisons. To understand the usefulness of administrative data for the surveillance of invasive aspergillosis, we compared information obtained from a system based on ICD-9 codes with information obtained from an active, prospective surveillance system, which used more extensive case-finding methods (Transplant Associated Infection Surveillance Network).

Methods.

Patients with suspected inyasive aspergillosis were identified by aspergillosis-related ICD-9 codes assigned to hematopoietic stem cell transplant recipients and solid organ transplant recipients at a single hospital from April 1, 2001, through January 31, 2005. Suspected cases were classified as proven or probable invasive aspergillosis by medical record review using standard definitions. We calculated the sensitivity and positive predictive value (PPV) of identifying invasive aspergillosis by individual ICD-9 codes and by combinations of codes.

Results.

The sensitivity of code 117.3 was modest (63% [95% confidence interval {CI}, 38%-84%]), as was the PPV (71% [95% CI, 44%-90%]); the sensitivity of code 117.9 was poor (32% [95% CI, 13%-57%]), as was the PPV (15% [95% CI, 6%-31%]). The sensitivity of codes 117.3 and 117.9 combined was 84% (95% CI, 60%-97%); the PPV of the combined codes was 30% (95% CI, 18%-44%). Overall, ICD-9 codes triggered a review of medical records for 64 medical patients, only 16 (25%) of whom had proven or probable invasive aspergillosis.

Conclusions.

A surveillance system that involved multiple ICD-9 codes was sufficiently sensitive to identify most cases of invasive aspergillosis; however, the poor PPV of ICD-9 codes means that this approach is not adequate as the sole tool used to classify cases. Screening ICD-9 codes to trigger a medical record review might be a useful method of surveillance for invasive aspergillosis and quality assessment, although more investigation is needed.

Evaluation of International Classification of Diseases, Ninth Revision, Clinical Modification Codes for Reporting Methicillin-Resistant Staphylococcus aureus Infections at a Hospital in Illinois

Background.

States, including Illinois, have passed legislation mandating the use of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes for reporting healthcare-associated infections, such as methicillin-resistant Staphylococcus aureus (MRSA).

Objective.

To evaluate the sensitivity of ICD-9-CM code combinations for detection of MRSA infection and to understand implications for reporting.

Methods.

We reviewed discharge and microbiology databases from July through August of 2005, 2006, and 2007 for ICD-9-CM codes or microbiology results suggesting MRSA infection at a tertiary care hospital near Chicago, Illinois. Medical records were reviewed to confirm MRSA infection. Time from admission to first positive MRSA culture result was evaluated to identify hospital-onset MRSA (HO-MRSA) infections. The sensitivity of MRSA code combinations for detecting confirmed MRSA infections was calculated using all codes present in the discharge record (up to 15); the effect of reviewing only 9 diagnosis codes, the number reported to the Centers for Medicare and Medicaid Services, was also evaluated. The sensitivity of the combination of diagnosis codes for detection of HO-MRSA infections was compared with that for community-onset MRSA (CO-MRSA) infections.

Results.

We identified 571 potential MRSA infections with the use of screening criteria; 403 (71%) were confirmed MRSA infections, of which 61 (15%) were classified as HO-MRSA. The sensitivity of MRSA code combinations was 59% for all confirmed MRSA infections when 15 diagnoses were reviewed compared with 31% if only 9 diagnoses were reviewed (P &lt; .001). The sensitivity of code combinations was 33% for HO-MRSA infections compared with 62% for CO-MRSA infections (P &lt; .001).

Conclusions.

Limiting analysis to 9 diagnosis codes resulted in low sensitivity. Furthermore, code combinations were better at revealing CO-MRSA infections than HO-MRSA infections. These limitations could compromise the validity of ICD-9-CM codes for interfacility comparisons and for reporting of healthcare-associated MRSA infections.

Underestimating the Impact of Ventilator-Associated Pneumonia by Use of Surveillance Data

We calculated rates of ventilator-associated pneumonia (VAP) by using surveillance data, clinical data, and coding data. Compared with the VAP rates calculated on the basis of surveillance data, the VAP rates calculated on the basis of coding data were significantly overestimated in 4 of 5 intensive, care units. Efforts to improve coding and clinical documentation will address much but not all of this discrepancy between surveillance and administrative data.

Long-term central venous catheter use and risk of infection in older adults with cancer

PURPOSE

Long-term central venous catheters (CVCs) are often used in patients with cancer to facilitate venous access to administer intravenous fluids and chemotherapy. CVCs can also be a source of bloodstream infections, although this risk is not well understood. We examined the impact of long-term CVC use on infection risk, independent of other risk factors such as chemotherapy, in a population-based cohort of patients with cancer.

PATIENTS AND METHODS

We conducted a retrospective analysis using SEER-Medicare data for patients age > 65 years diagnosed from 2005 to 2007 with invasive colorectal, head and neck, lung, or pancreatic cancer, non-Hodgkin lymphoma, or invasive or noninvasive breast cancer. Cox proportional hazards regression was used to examine the relationship between CVC use and infections, with CVC exposure as a time-dependent predictor. We used multivariable analysis and propensity score methods to control for patient characteristics.

RESULTS

CVC exposure was associated with a significantly elevated infection risk, adjusting for demographic and disease characteristics. For patients with pancreatic cancer, risk of infections during the exposure period was three-fold greater (adjusted hazard ratio [AHR], 2.93; 95% CI, 2.58 to 3.33); for those with breast cancer, it was six-fold greater (AHR, 6.19; 95% CI, 5.42 to 7.07). Findings were similar when we accounted for propensity to receive a CVC and limited the cohort to individuals at high risk of infections.

CONCLUSION

Long-term CVC use was associated with an increased risk of infections for older adults with cancer. Careful assessment of the need for long-term CVCs and targeted strategies for reducing infections are critical to improving cancer care quality.

Validity analysis of a unique infection surveillance system in the intensive care unit by analysis of a data warehouse built through a workflow-integrated software application

BACKGROUND

An electronic decision support programme was developed within the intensive care unit (ICU) that provides an overview of all infection-related patient data, and allows ICU physicians to add clinical information during patient rounds, resulting in prospective compilation of a database.

AIM

To assess the validity of computer-assisted surveillance (CAS) of ICU-acquired infection performed by analysis of this database.

METHODS

CAS was compared with prospective paper-based surveillance (PBS) for ICU-acquired respiratory tract infection (RTI), bloodstream infection (BSI) and urinary tract infection (UTI) over four months at a 36-bed medical and surgical ICU. An independent panel reviewed the data in the case of discrepancy between CAS and PBS.

FINDINGS

PBS identified 89 ICU-acquired infections (13 BSI, 18 UTI, 58 RTI) and CAS identified 90 ICU-acquired infections (14 BSI, 17 UTI, 59 RTI) in 876 ICU admissions. There was agreement between CAS and PBS on 13 BSI (100 %), 14 UTI (77.8 %) and 42 RTI (72.4 %). Overall, there was agreement on 69 infections (77.5%), resulting in a kappa score of 0.74. Discrepancy between PBS and CAS was the result of capture error in 11 and 14 infections, respectively. Interobserver disagreement on probability (13 RTI) and focus (two RTI, one UTI) occurred for 16 episodes. The time required to collect information using CAS is less than 30% of the time required when using PBS.

CONCLUSION

CAS for ICU-acquired infection by analysis of a database built through daily workflow is a feasible surveillance method and has good agreement with PBS. Discrepancy between CAS and PBS is largely due to interobserver variability.

Using electronic medical records to increase the efficiency of catheter-associated urinary tract infection surveillance for National Health and Safety Network reporting

BACKGROUND

Streamlining health care-associated infection surveillance is essential for health care facilities owing to the continuing increases in reporting requirements.

METHODS

Stanford Hospital, a 583-bed adult tertiary care center, used their electronic medical record (EMR) to develop an electronic algorithm to reduce the time required to conduct catheter-associated urinary tract infection (CAUTI) surveillance in adults. The algorithm provides inclusion and exclusion criteria, using the National Healthcare Safety Network definitions, for patients with a CAUTI. The algorithm was validated by trained infection preventionists through complete chart review for a random sample of cultures collected during the study period, September 1, 2012, to February 28, 2013.

RESULTS

During the study period, a total of 6,379 positive urine cultures were identified. The Stanford Hospital electronic CAUTI algorithm identified 6,101 of these positive cultures (95.64%) as not a CAUTI, 191 (2.99%) as a possible CAUTI requiring further validation, and 87 (1.36%) as a definite CAUTI. Overall, use of the algorithm reduced CAUTI surveillance requirements at Stanford Hospital by 97.01%.

CONCLUSIONS

The electronic algorithm proved effective in increasing the efficiency of CAUTI surveillance. The data suggest that CAUTI surveillance using the National Healthcare Safety Network definitions can be fully automated.

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.

Use of administrative data for surgical site infection surveillance after congenital cardiac surgery results in inaccurate reporting of surgical site infection rates

BACKGROUND

The National Healthcare Safety Network (NHSN) is a safety surveillance system managed by the Centers for Disease Control and Prevention that monitors procedure specific rates of surgical site infections (SSIs). At our institution, SSI data is collected and reported by three different methods: (1) the NHSN database with reporting to the Centers for Disease Control and Prevention; (2) the hospital billing database with reporting to payers; and (3) The Society of Thoracic Surgeons Congenital Heart Surgery Database. A quality improvement initiative was undertaken to better understand issues with SSI reporting and to evaluate the effect of different data sources on annual SSI rates.

METHODS

Annual cardiac surgery procedure volumes for all three data sources were compared. All episodes of SSI identified in any data source were reviewed and adjudicated using NHSN SSI criteria, and the effect on SSI rates was evaluated.

RESULTS

From January 1, 2008, to December 31, 2011, 2,474 cardiac procedures were performed and reported to The Society of Thoracic Surgeons Congenital Heart Surgery Database. Billing data identified 1,865 cardiac surgery procedures using the 63 CARD International Classification of Diseases-Ninth Revision codes from the NHSN inclusion criteria. Only 1,425 procedures were targeted for NHSN surveillance using the NHSN's CARD operative procedure group in the same period. Procedures identified for NHSN surveillance annually underestimated the number of cardiac operations performed by 17% to 71%. As a result, annual SSI rates potentially differed by 12% to 270%.

CONCLUSIONS

The NHSN CARD surveillance guidelines for SSI fail to identify all pediatric cardiac surgical procedures. Failure to target all at-risk procedures leads to inaccurate reporting of SSI rates largely based on identifying the denominator. Inaccurate recording of SSI data has implications for public reporting, benchmarking of outcomes, and denial of payment. Use of The Society of Thoracic Surgeons Congenital Heart Surgery Database as the gold standard to identify procedures for surveillance will lead to more accurate reporting of SSI rates.

Validity of ICD-9-CM codes for the identification of complications related to central venous catheterization

Two complications of central venous catheterization (CVC), iatrogenic pneumothorax and central line-associated bloodstream infection (CLABSI), have dedicated International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Despite increasing use of ICD-9-CM codes for research and pay-for-performance purposes, their validity for detecting complications of CVC has not been established. Complications of CVCs placed between July 2010 and December 2011 were identified by ICD-9-CM codes in discharge records from a single hospital and compared with those revealed by medical record abstraction. The ICD-9-CM code for iatrogenic pneumothorax had a sensitivity of 66.7%, specificity of 100%, positive predictive value (PPV) of 100%, and negative predictive value (NPV) of 99.5%. The ICD-9-CM codes for CLABSI had a sensitivity of 33.3%, specificity of 99.0%, PPV of 28.6%, and NPV of 99.2%. The low sensitivity and variable PPV of ICD-9-CM codes for detection of complications of CVC raise concerns about their use for research or pay-for-performance purposes.

Identification of device-associated infections utilizing administrative data

BACKGROUND

Health care-associated infections are a cause of significant morbidity and mortality in US hospitals. Recent changes have broadened the scope of health care-associated infections surveillance data to use in public reporting and of administrative data for determining Medicare reimbursement adjustments for hospital-acquired conditions.

METHODS

Infection surveillance results for catheter-associated urinary tract infections (CAUTI), central line-associated bloodstream infections (CLABSI), and ventilator-associated pneumonia were compared with infections identified by hospital administrative data. The sensitivity and specificity of administrative data were calculated, with surveillance data considered the gold standard.

RESULTS

The sensitivity of administrative data diagnosis codes for CAUTI, CLABSI, and ventilator-associated pneumonia were 0%, 21%, and 25%, respectively. The incorporation of additional diagnosis codes in definitions increased the sensitivity of administrative data somewhat with little decrease in specificity. Positive predictive values for definitions corresponding to Centers for Medicare and Medicaid services-defined hospital-acquired conditions were 0% for CAUTI and 41% for CLABSI.

CONCLUSIONS

Although infection surveillance methods and administrative data are widely used as tools to identify health care-associated infections, in our study administrative data failed to identify the same infections that were detected by surveillance. Hospitals, already incentivized by the use of performance measures to improve the quality of patient care, should also recognize the need for ongoing scrutiny of appropriate quality measures.

Accuracy of hospital administrative data in reporting central line-associated bloodstream infections in newborns

OBJECTIVES

Central line-associated bloodstream infections (CLABSIs) are a significant source of morbidity and mortality in the NICU. In 2010, Medicaid was mandated not to pay hospitals for treatment of CLABSI; however, the source of CLABSI data for this policy was not specified. Our objective was to evaluate the accuracy of hospital administrative data compared with CLABSI confirmed by an infection control service.

METHODS

We evaluated hospital administrative and infection control data for newborns admitted consecutively from January 1, 2008, to December 31, 2010. Clinical and demographic data were collected through chart review. We compared cases of CLABSI identified by administrative data (International Classification of Diseases, Ninth Revision, Clinical Modification 999.31) with infection control data that use national criteria from the Centers for Disease Control and Prevention as the gold standard. To ascertain the nature possible deficiencies in the administrative data, each patient's medical record was searched to determine if clinical phrases that commonly refer to CLABSI appeared.

RESULTS

Of 2920 infants admitted to the NICU during our study period, 52 were identified as having a CLABSI: 42 by infection control data only, 7 through hospital administrative data only, and 3 appearing in both. Against the gold standard, hospital administrative data were 6.7% sensitive and 99.7% specific, with a positive predictive value of 30.0% and a negative predictive value of 98.6%. Only 48% of medical records indicated a CLABSI.

CONCLUSIONS

Our findings from a major children's hospital NICU indicate that International Classification of Diseases, Ninth Revision, Clinical Modification code 993.31 is presently not accurate and cannot be used reliably to compare CLABSI rates in NICUs.

Central line-associated infections as defined by the Centers for Medicare and Medicaid Services' Hospital-acquired condition versus standard infection control surveillance: why hospital compare seems conflicted

OBJECTIVE

To evaluate the concordance of case-finding methods for central line-associated infection as defined by Centers for Medicare and Medicaid Services (CMS) hospital-acquired condition (HAC) compared with traditional infection control (IC) methods.

SETTING

One tertiary care and 2 community hospitals in North Carolina.

PATIENTS

Adult and pediatric hospitalized patients determined to have central line infection by either case-finding method.

METHODS

We performed a retrospective comparative analysis of infection detected using HAC versus standard IC central line-associated bloodstream infection surveillance from October 1, 2007, through December 31, 2009. One billing and 2 IC databases were queried and matched to determine the number and concordance of cases identified by each method. Manual review of 25 cases from each discordant category was performed. Sensitivity and positive predictive value (PPV) were calculated using IC as criterion standard.

RESULTS

A total of 1,505 cases were identified: 844 by International Classification of Diseases, Ninth Revision (ICD-9), and 798 by IC. A total of 204 cases (24%) identified by ICD-9 were deemed not present at hospital admission by coders. Only 112 cases (13%) were concordant. HAC sensitivity was 14% and PPV was 55% compared with IC. Concordance was low regardless of hospital type. Primary reasons for discordance included differences in surveillance and clinical definitions, clinical uncertainty, and poor documentation.

CONCLUSIONS

The case-finding method used by CMS HAC and the methods used for traditional IC surveillance frequently do not agree. This can lead to conflicting results when these 2 measures are used as hospital quality metrics.

Discord among performance measures for central line-associated bloodstream infection

BACKGROUND

Central line-associated bloodstream infection (CLABSI) is a national target for mandatory reporting and a Centers for Medicare and Medicaid Services target for value-based purchasing. Differences in chart review versus claims-based metrics used by national agencies and groups raise concerns about the validity of these measures.

OBJECTIVE

Evaluate consistency and reasons for discordance among chart review and claims-based CLABSI events.

METHODS

We conducted 2 multicenter retrospective cohort studies within 6 academic institutions. A total of 150 consecutive patients were identified with CLABSI on the basis of National Healthcare Safety Network (NHSN) criteria (NHSN cohort), and an additional 150 consecutive patients were identified with CLABSI on the basis of claims codes (claims cohort). All events had full-text medical record reviews and were identified as concordant or discordant with the other metric.

RESULTS

In the NHSN cohort, there were 152 CLABSIs among 150 patients, and 73.0% of these cases were discordant with claims data. Common reasons for the lack of associated claims codes included coding omission and lack of physician documentation of bacteremia cause. In the claims cohort, there were 150 CLABSIs among 150 patients, and 65.3% of these cases were discordant with NHSN criteria. Common reasons for the lack of NHSN reporting were identification of non-CLABSI with bacteremia meeting Centers for Disease Control and Prevention (CDC) criteria for an alternative infection source.

CONCLUSION

Substantial discordance between NHSN and claims-based CLABSI indicators persists. Compared with standardized CDC chart review criteria, claims data often had both coding omissions and misclassification of non-CLABSI infections as CLABSI. Additionally, claims did not identify any additional CLABSIs for CDC reporting. NHSN criteria are a more consistent interhospital standard for CLABSI reporting.

Lessons learned while implementing mandatory health care-associated infection reporting in New York State

New York State Public Health Law §2819, requiring the mandatory public reporting of health care-associated infections, was enacted in July 2005. This article describes key provisions in the legislation, New York State health care-associated infection program development, the rationale for selection of the National Healthcare Safety Network for reporting, and lessons learned.

Effect of nonpayment for preventable infections in U.S. hospitals

BACKGROUND

In October 2008, the Centers for Medicare and Medicaid Services (CMS) discontinued additional payments for certain hospital-acquired conditions that were deemed preventable. The effect of this policy on rates of health care-associated infections is unknown.

METHODS

Using a quasi-experimental design with interrupted time series with comparison series, we examined changes in trends of two health care-associated infections that were targeted by the CMS policy (central catheter-associated bloodstream infections and catheter-associated urinary tract infections) as compared with an outcome that was not targeted by the policy (ventilator-associated pneumonia). Hospitals participating in the National Healthcare Safety Network and reporting data on at least one health care-associated infection before the onset of the policy were eligible to participate. Data from January 2006 through March 2011 were included. We used regression models to measure the effect of the policy on changes in infection rates, adjusting for baseline trends.

RESULTS

A total of 398 hospitals or health systems contributed 14,817 to 28,339 hospital unit-months, depending on the type of infection. We observed decreasing secular trends for both targeted and nontargeted infections long before the policy was implemented. There were no significant changes in quarterly rates of central catheter-associated bloodstream infections (incidence-rate ratio in the postimplementation vs. preimplementation period, 1.00; P=0.97), catheter-associated urinary tract infections (incidence-rate ratio, 1.03; P=0.08), or ventilator-associated pneumonia (incidence-rate ratio, 0.99; P=0.52) after the policy implementation. Our findings did not differ for hospitals in states without mandatory reporting, nor did it differ according to the quartile of percentage of Medicare admissions or hospital size, type of ownership, or teaching status.

CONCLUSIONS

We found no evidence that the 2008 CMS policy to reduce payments for central catheter-associated bloodstream infections and catheter-associated urinary tract infections had any measurable effect on infection rates in U.S. hospitals. (Funded by the Agency for Healthcare Research and Quality.).

A comparison of 3 metrics to identify health care-associated infections

BACKGROUND

The best approach to measurement of health care-associated infection rates is controversial.

METHODS

We compared 3 metrics to identify catheter-associated bloodstream infection (CA-BSI), catheter-associated urinary tract infection (CA-UTI), and ventilator-associated pneumonia (VAP) in 8 intensive care units during 2009. We evaluated traditional surveillance using National Healthcare Safety Network methodology, data mining with MedMined Data Mining Surveillance (CareFusion Corporation, San Diego, CA), and administrative coding with ICD-9-CM.

RESULTS

A total of 65 CA-BSI, 28 CA-UTI, and 48 VAP was identified. Traditional surveillance detected 58 CA-BSI and no false positives; data mining identified 51 cases but 51 false positives; administrative coding documented 6 cases and 6 false positives. Traditional surveillance detected 27 CA-UTI and no false positives; data mining identified 17 cases but 19 false positives; administrative coding documented 3 cases and 1 false-positive. Traditional surveillance detected 41 VAP and no false positives; data mining identified 26 cases but also 79 false positives; administrative coding found 17 cases and 13 false positives. Overall sensitivities were as follows: traditional surveillance, 0.84; data mining, 0.67; administrative coding, 0.18. Positive predictive values were as follows: traditional surveillance, 1.0; data mining, 0.39; administrative coding, 0.57.

CONCLUSION

Traditional surveillance proved superior in terms of sensitivity, positive predictive value, and rate estimation.

Electronic measures of surgical site infection: implications for estimating risks and costs

OBJECTIVE

Electronic measures of surgical site infections (SSIs) are being used more frequently in place of labor-intensive measures. This study compares performance characteristics of 2 electronic measures of SSIs with a clinical measure and studies the implications of using electronic measures to estimate risk factors and costs of SSIs among surgery patients.

METHODS

Data included 1,066 general and vascular surgery patients at a single academic center between 2007 and 2008. Clinical data were from the National Surgical Quality Improvement Program (NSQIP) database, which includes a nurse-derived measure of SSI. We compared the NSQIP SSI measure with 2 electronic measures of SSI: MedMined Nosocomial Infection Marker (NIM) and International Classification of Diseases, Ninth Revision (ICD-9) coding for SSIs. We compared infection rates for each measure, estimated sensitivity and specificity of electronic measures, compared effects of SSI measures on risk factors for mortality using logistic regression, and compared estimated costs of SSIs for measures using linear regression.

RESULTS

SSIs were observed in 8.8% of patients according to the NSQIP definition, 2.6% of patients according to the NIM definition, and 5.8% according to the ICD-9 definition. Logistic regression for each SSI measure revealed large differences in estimated risk factors. NIM and ICD-9 measures overestimated the cost of SSIs by 134% and 33%, respectively.

CONCLUSIONS

Caution should be taken when relying on electronic measures for SSI surveillance and when estimating risk and costs attributable to SSIs. Electronic measures are convenient, but in this data set they did not correlate well with a clinical measure of infection.

Using electronically available inpatient hospital data for research

Despite a push to create electronic health records and a plethora of healthcare data from disparate sources, there are no data from a single electronic source that provide a full picture of a patient's hospital course. This paper describes a process to utilize electronically available inpatient hospital data for research. We linked several different sources of extracted data, including clinical, procedural, administrative, and accounting data, using patients' medical record numbers to compile a cohesive, comprehensive account of patient encounters. Challenges encountered included (1) interacting with distinct administrative units to locate data elements; (2) finding a secure, central location to house the data; (3) appropriately defining health measures of interest; (4) obtaining and linking these data to create a usable format for conducting research; and (5) dealing with missing data. Although the resulting data set is incredibly rich and likely to prove useful for a wide range of clinical and comparative effectiveness research questions, there are multiple challenges associated with linking hospital data to improve the quality of patient care.

Prevalence of major infections and adverse outcomes among hospitalized. ST-elevation myocardial infarction patients in Florida, 2006

Background

ST-elevation myocardial infarction (STEMI) patients have risk factors and co-morbidities and require procedures predisposing to healthcare acquired infections (HAIs). As few data exist on the extent and consequences of infections among these patients, the prevalence, predictors, and potential complications of major infections among hospitalized STEMI patients at all Florida acute care hospitals during 2006 were analyzed.

Methods

Sociodemographic characteristics, risk factors, co-morbidities, procedures, complications, and mortality were analyzed from hospital discharge data for 11, 879 STEMI patients age ≥18 years. We used multivariable logistic regression modeling to examine and adjust for multiple potential predictors of any infection, bloodstream infection (BSI), pneumonia, surgical site infection (SSI), and urinary tract infection (UTI).

Results

There were 2, 562 infections among 16.6% of STEMI patients; 6.2% of patients had ≥2 infections. The most prevalent HAIs were UTIs (6.0%), pneumonia (4.6%), SSIs (4.1%), and BSIs (2.6%). Women were at 29% greater risk, Blacks had 23% greater risk, and HAI risk increased 11% with each 5 year increase in age. PCI was the only protective major procedure (OR 0.81, 95% CI, 0.69-0.95, p < .05). HAI lengthened hospital stays. STEMI patients with a BSI were almost 5 times more likely (31.3% vs. 6.5%, p < .0001), and those with pneumonia were 3 times more likely (19.6% vs. 6.5%, p < .0001) to die before discharge.

Conclusions

The protective effect of PCI on risk of infection is likely mediated by its many benefits, including reduced length of hospitalizations.

Use of benchmarking and public reporting for infection control in four high-income countries

Benchmarking of surveillance data for health-care-associated infection (HCAI) has been used for more than three decades to inform prevention strategies and improve patients' safety. In recent years, public reporting of HCAI indicators has been mandated in several countries because of an increasing demand for transparency, although many methodological issues surrounding benchmarking remain unresolved and are highly debated. In this Review, we describe developments in benchmarking and public reporting of HCAI indicators in England, France, Germany, and the USA. Although benchmarking networks in these countries are derived from a common model and use similar methods, approaches to public reporting have been more diverse. The USA and England have predominantly focused on reporting of infection rates, whereas France has put emphasis on process and structure indicators. In Germany, HCAI indicators of individual institutions are treated confidentially and are not disseminated publicly. Although evidence for a direct effect of public reporting of indicators alone on incidence of HCAIs is weak at present, it has been associated with substantial organisational change. An opportunity now exists to learn from the different strategies that have been adopted.

Validity of ICD-9-CM coding for identifying incident methicillin-resistant Staphylococcus aureus (MRSA) infections: is MRSA infection coded as a chronic disease?

BACKGROUND AND OBJECTIVE

Investigators and medical decision makers frequently rely on administrative databases to assess methicillin-resistant Staphylococcus aureus (MRSA) infection rates and outcomes. The validity of this approach remains unclear. We sought to assess the validity of the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code for infection with drug-resistant microorganisms (V09) for identifying culture-proven MRSA infection.

DESIGN

Retrospective cohort study.

METHODS

All adults admitted to 3 geographically distinct hospitals between January 1, 2001, and December 31, 2007, were assessed for presence of incident MRSA infection, defined as an MRSA-positive clinical culture obtained during the index hospitalization, and presence of the V09 ICD-9-CM code. The κ statistic was calculated to measure the agreement between presence of MRSA infection and assignment of the V09 code. Sensitivities, specificities, positive predictive values, and negative predictive values were calculated.

RESULTS

There were 466,819 patients discharged during the study period. Of the 4,506 discharged patients (1.0%) who had the V09 code assigned, 31% had an incident MRSA infection, 20% had prior history of MRSA colonization or infection but did not have an incident MRSA infection, and 49% had no record of MRSA infection during the index hospitalization or the previous hospitalization. The V09 code identified MRSA infection with a sensitivity of 24% (range, 21%-34%) and positive predictive value of 31% (range, 22%-53%). The agreement between assignment of the V09 code and presence of MRSA infection had a κ coefficient of 0.26 (95% confidence interval, 0.25-0.27).

CONCLUSIONS

In its current state, the ICD-9-CM code V09 is not an accurate predictor of MRSA infection and should not be used to measure rates of MRSA infection.

The impact of statistical choices on neonatal intensive care unit quality ratings based on nosocomial infection rates

OBJECTIVE

To examine the extent to which performance assessment methods affect the percentage of neonatal intensive care units (NICUs) and very low-birth-weight (VLBW) infants included in performance assessments, the distribution of NICU performance ratings, and the level of agreement in those ratings.

DESIGN

Cross-sectional study based on risk-adjusted nosocomial infection rates.

SETTING

NICUs belonging to the California Perinatal Quality Care Collaborative 2007-2008.

PARTICIPANTS

One hundred twenty-six California NICUs and 10 487 VLBW infants.

MAIN EXPOSURES

Three performance assessment choices: (1) excluding "low-volume" NICUs (those caring for <30 VLBW infants per year) vs a criterion based on confidence intervals, (2) using Bayesian vs frequentist hierarchical models, and (3) pooling data across 1 vs 2 years.

MAIN OUTCOME MEASURES

Proportion of NICUs and patients included in quality assessment, distribution of ratings for NICUs, and agreement between methods using the κ statistic.

RESULTS

Depending on the methods applied, 51% to 85% of NICUs and 72% to 96% of VLBW infants were included in performance assessments, 76% to 87% of NICUs were considered "average," and the level of agreement between NICU ratings ranged from 0.23 to 0.89.

CONCLUSIONS

The percentage of NICUs included in performance assessments and their ratings can shift dramatically depending on performance measurement method. Physicians, payers, and policymakers should continue to closely examine which existing performance assessment methods are most appropriate for evaluating pediatric care quality.