To evaluate random effects of volume (patient days or device days) on healthcare-associated infections (HAIs) and the standardized infection ratio (SIR) used to compare hospitals.

A longitudinal comparison between publicly reported quarterly data (2014–2020) and volume-based random sampling using 4 HAI types: central-line–associated bloodstream infections, catheter-associated urinary tract infections, Clostridioides difficile infections, methicillin-resistant Staphylococcus aureus infections.

Using 4,268 hospitals with reported SIRs, we examined relationships of SIRs to volume and compared distributions of SIRs and numbers of reported HAIs to the outcomes of simulated random sampling. We included random expectations into SIR calculations to produce a standardized infection score (SIS).

Among hospitals with volumes less than the median, 20%–33% had SIRs of 0, compared to 0.3%–5% for hospitals with volumes higher than the median. Distributions of SIRs were 86%–92% similar to those based on random sampling. Random expectations explained 54%–84% of variation in numbers of HAIs. The use of SIRs led hundreds of hospitals with more infections than either expected at random or predicted by risk-adjusted models to rank better than other hospitals. The SIS mitigated this effect and allowed hospitals of disparate volumes to achieve better scores while decreasing the number of hospitals tied for the best score.

SIRs and numbers of HAIs are strongly influenced by random effects of volume. Mitigating these effects drastically alters rankings for HAI types and may further alter penalty assignments in programs that aim to reduce HAIs and improve quality of care.

To develop a probabilistic method for measuring central line–associated bloodstream infection (CLABSI) rates that reduces the variability associated with traditional, manual methods of applying CLABSI surveillance definitions.

Multicenter retrospective cohort study of bacteremia episodes among patients hospitalized in adult patient-care units; the study evaluated presence of CLABSI.

Hospitals that used SafetySurveillor software system (Premier) and who also reported to the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN).

Patients were identified from a stratified sample from all eligible blood culture isolates from all eligible hospital units to generate a final set with an equal distribution (ie, 20%) from each unit type. Units were divided a priori into 5 major groups: medical intensive care unit, surgical intensive care unit, medical-surgical intensive care unit, hematology unit, or general medical wards.

Episodes were reviewed by 2 experts, and a selection of discordant reviews were re-reviewed. Data were joined with NHSN data for hospitals for in-plan months. A predictive model was created; model performance was assessed using the c statistic in a validation set and comparison with NHSN reported rates for in-plan months.

A final model was created with predictors of CLABSI. The c statistic for the final model was 0.75 (0.68–0.80). Rates from regression modeling correlated better with expert review than NHSN-reported rates.

The use of a regression model based on the clinical characteristics of the bacteremia outperformed traditional infection preventionist surveillance compared with an expert-derived reference standard.

Infect. Control Hosp. Epidemiol. 2016;37(2):149–155

Methicillin-resistant Staphylococcus aureus (MRSA) infections due to USA300 have become widespread in community and healthcare settings. It is unclear whether risk factors for bloodstream infections (BSIs) differ by strain type.

To examine the epidemiology of S. aureus BSIs, including USA300 and non-USA300 MRSA strains.

Retrospective observational study with molecular analysis.

Large urban public hospital.

Individuals with S. aureus BSIs from January 1, 2007 through December 31, 2013.

We used electronic surveillance data to identify cases of S. aureus BSI. Available MRSA isolates were analyzed by pulsed-field gel electrophoresis. Poisson regression was used to evaluate changes in BSI incidence over time. Risk factor data were collected by medical chart review and logistic regression was used for multivariate analysis of risk factors.

A total of 1,015 cases of S. aureus BSIs were identified during the study period; 36% were due to MRSA. The incidence of hospital-onset (HO) MRSA BSIs decreased while that of community-onset (CO) MRSA BSIs remained stable. The rate of CO– and HO– methicillin-susceptible S. aureus infections both decreased over time. More than half of HO-MRSA BSIs were due to the USA300 strain type and for 4 years, the proportion of HO-MRSA BSIs due to USA300 exceeded 60%. On multivariate analysis, current or former drug use was the only epidemiologic risk factor for CO- or HO-MRSA BSIs due to USA300 strains.

USA300 MRSA is endemic in communities and hospitals and certain populations (eg, those who use illicit drugs) may benefit from enhanced prevention efforts in the community.

Infect. Control Hosp. Epidemiol. 2015;36(12):1417–1422

Central line–associated bloodstream infection (BSI) rates are a key quality metric for comparing hospital quality and safety. Traditional BSI surveillance may be limited by interrater variability. We assessed whether a computer-automated method of central line–associated BSI detection can improve the validity of surveillance.

Retrospective cohort study.

Eight medical and surgical intensive care units (ICUs) in 4 academic medical centers.

Traditional surveillance (by hospital staff) and computer algorithm surveillance were each compared against a retrospective audit review using a random sample of blood culture episodes during the period 2004–2007 from which an organism was recovered. Episode-level agreement with audit review was measured with κ statistics, and differences were assessed using the test of equal κ coefficients. Linear regression was used to assess the relationship between surveillance performance (κ) and surveillance-reported BSI rates (BSIs per 1,000 central line–days).

We evaluated 664 blood culture episodes. Agreement with audit review was significantly lower for traditional surveillance (κ [95% confidence interval (CI)] = 0.44 [0.37–0.51]) than computer algorithm surveillance (κ [95% CI] [0.52–0.64]; P = .001). Agreement between traditional surveillance and audit review was heterogeneous across ICUs (P = .001); furthermore, traditional surveillance performed worse among ICUs reporting lower (better) BSI rates (P = .001). In contrast, computer algorithm performance was consistent across ICUs and across the range of computer-reported central line–associated BSI rates.

Compared with traditional surveillance of bloodstream infections, computer automated surveillance improves accuracy and reliability, making interfacility performance comparisons more valid.

Infect Control Hosp Epidemiol 2014;35(12):1483–1490

Previous work has shown that daily skin cleansing with Chlorhexidine gluconate (CHG) is effective in preventing infection in the medical intensive care unit (MICU). A colorimetric, semiquantitative indicator was used to measure CHG concentration on skin (neck, antecubital fossae, and inguinal areas) of patients bathed daily with CHG during their MICU stay and after discharge from the MICU, when CHG bathing stopped.

MICU patients at Rush University Medical Center.

CHG concentration on skin was measured and skin sites were cultured quantitatively. The relationship between CHG concentration and microbial density on skin was explored in a mixed-effects model using gram-positive colony-forming unit (CFU) counts.

For 20 MICU patients studied (240 measurements), the lowest CHG concentrations (0–18.75 μg/mL) and the highest gram-positive CFU counts were on the neck (median, 1.07 log10 CFUs; P = .014). CHG concentration increased postbath and decreased over 24 hours (P < .001). In parallel, median log10 CFUs decreased pre- to postbath (0.78 to 0) and then increased over 24 hours to the baseline of 0.78 (P = .001). A CHG concentration above 18.75 μg/mL was associated with decreased gram-positive CFUs (P = .004). In all but 2 instances, CHG was detected on patient skin during the entire interbath (approximately 24-hour) period (18 [90%] of 20 patients). In 11 patients studied after MICU discharge (80 measurements), CHG skin concentrations fell below effective levels after 1–3 days.

In MICU patients bathed daily with CHG, CHG concentration was inversely associated with microbial density on skin; residual antimicrobial activity on skin persisted up to 24 hours. Determination of CHG concentration on the skin of patients may be useful in monitoring the adequacy of skin cleansing by healthcare workers.

To assess Clostridium difficile infection (CDI)-related colectomy rates by CDI surveillance definitions and over time at multiple healthcare facilities.

Five university-affiliated acute care hospitals in the United States.

Cases of CDI and patients who underwent colectomy from July 2000 through June 2006 were identified from 5 US tertiary care centers. Monthly CDI-related colectomy rates were calculated as the number of CDI-related colectomies per 1,000 CDI cases, and cases were categorized according to recommended surveillance definitions. Logistic regression was performed to evaluate risk factors for CDI-related colectomy.

In total, 8,569 cases of CDI were identified, and 75 patients underwent CDI-related colectomy. The overall colectomy rate was 8.7 per 1,000 CDI cases. The CDI-related colectomy rate ranged from 0 to 23 per 1,000 CDI episodes across hospitals. The colectomy rate for healthcare-facility-onset CDI was 4.3 per 1,000 CDI cases, and that for community-onset CDI was 16.5 per 1,000 CDI cases (P < .05). There were significantly more CDI-related colectomies at hospitals B and C (P < .05).

The overall CDI-related colectomy rate was low, and there was no significant change in the CDI-related colectomy rate over time. Onset of disease outside the study hospital was an independent risk factor for colectomy.

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.

Retrospective cohort study.

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 k 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.

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 k coefficient of 0.26 (95% confidence interval, 0.25–0.27).

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.

To compare incidence rates of Clostridium difficile infection (CDI) during a 6-year period among 5 geographically diverse academic medical centers across the United States by use of recommended standardized surveillance definitions of CDI that incorporate recent information on healthcare facility (HCF) exposure.

Data on C. difficile toxin assay results and dates of hospital admission and discharge were collected from electronic databases. Chart review was performed for patients with a positive C. difficile toxin assay result who were identified within 48 hours after hospital admission to determine whether they had any HCF exposure during the 90 days prior to their hospital admission. CDI cases, defined as any inpatient with a stool toxin assay positive for C. difficile, were categorized into 5 surveillance definitions based on recent HCF exposure. Annual CDI rates were calculated and evaluated by use of the χ2 test for trend and the χ2 summary test.

During the study period, there were significant increases in the overall incidence rates of HCF-onset, HCF-associated CDI (from 7.0 to 8.5 cases per 10,000 patient-days; P < .001); community-onset, HCF-associated CDI attributed to a study hospital (from 1.1 to 1.3 cases per 10,000 patient-days; P = .003); and community-onset, HCF-associated CDI not attributed to a study hospital (from 0.8 to 1.5 cases per 1,000 admissions overall; P < .001). For each surveillance definition of CDI, there were significant differences in the total incidence rate between HCFs.

The increasing incidence rates of CDI over time and across healthcare institutions and the correlation of CDI incidence in different surveillance categories suggest that CDI may be a regional problem and not isolated to a single HCF within a community.

To compare incidence of hospital-onset Clostridium difficile infection (CDI) measured by the use of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes with rates measured by the use of electronically available C. difficile toxin assay results.

Cases of hospital-onset CDI were identified at 5 US hospitals during the period from July 2000 through June 2006 with the use of 2 surveillance definitions: positive toxin assay results (gold standard) and secondary ICD-9-CM discharge diagnosis codes for CDI. The x2 test was used to compare incidence, linear regression models were used to analyze trends, and the test of equality was used to compare slopes.

Of 8,670 cases of hospital-onset CDI, 38% were identified by the use of both toxin assay results and the ICD-9-CM code, 16% by the use of toxin assay results alone, and 45% by the use of the ICD-9-CM code alone. Nearly half (47%) of cases of CDI identified by the use of a secondary diagnosis code alone were community-onset CDI according to the results of the toxin assay. The rate of hospital-onset CDI found by use of ICD-9-CM codes was significantly higher than the rate found by use of toxin assay results overall (P<.001), as well as individually at 3 of the 5 hospitals (P<.001 for all). The agreement between toxin assay results and the presence of a secondary ICD-9-CM diagnosis code for CDI was moderate, with an overall k value of 0.509 and hospital-specific k values of 0.489–0.570. Overall, the annual increase in CDI incidence was significantly greater for rates determined by the use of ICD-9-CM codes than for rates determined by the use of toxin assay results (P = .006).

Although the ICD-9-CM code for CDI seems to be adequate for measuring the overall CDI burden, use of the ICD-9-CM discharge diagnosis code for CDI, without present-on-admission code assignment, is not an acceptable surrogate for surveillance for hospital-onset CDI.

To develop prediction algorithms for the presence of a central vascular catheter in hospitalized patients with use of data present in an electronic health record. Such algorithms could be used for measurement of device utilization rates and for clinical decision support rules.

Criterion standard.

John H. Stroger, Jr, Hospital of Cook County, a 464-bed public hospital in Chicago, Illinois.

Patients admitted to the medical intensive care unit from May 31, 2005 through June 26, 2006 (derivation data set, May 31, 2005-September 28, 2005; validation data set, September 29, 2005-June 28, 2006).

Covariates were collected from the electronic medical record for each patient; the outcome variable was presence of a central vascular device. Multivariate models were developed using the derivation set and the generalized estimating equation. Three models, each with increasing database requirements, were validated using the validation set. Device utilization ratios and performance characteristics were calculated.

Although Charlson score and duration of intensive care unit stay were significant predictors in all models, factors that indicated use or presence of a central line were also important. Device utilization rates derived from the algorithmic models were as accurate as those obtained using manual sampling.

Automated calculation of central vascular catheter use is both feasible and accurate, providing estimates statistically similar to those obtained using manual surveillance. Prediction modeling of central vascular catheter use may enable automated surveillance of bloodstream infections and enhance important prevention interventions, such as timely removal of unnecessary central lines.

To evaluate the effect of bathing patients with 2% chlorhexidine on the rates of central vascular catheter (CVC)–associated bloodstream infection (BSI) at a long-term acute care hospital (LTACH).

Quasi-experimental study.

A 70-bed LTACH in the greater Chicago area.

All consecutive patients admitted to the LTACH during the period from February 2006 to February 2008.

For patients at the LTACH, daily 2% chlorhexidine baths were instituted during the period from September 2006 until May 2007 (ie, the intervention period). A preintervention period (in which patients were given daily soap-and-water baths) and a postintervention period (in which patients were given daily nonmedicated baths and weekly 2% chlorhexidine baths) were also observed. The rates of CVC-associated BSI and ventilator-associated pneumonia were analyzed for the intervention period and for the pre- and postintervention periods.

The rates of CVC-associated BSI were 9.5, 3.8, and 6.4 cases per 1,000 CVC-days during the preintervention, intervention, and postintervention periods, respectively. By the end of the intervention period, there was a net reduction of 99% in the CVC-associated BSI rate. No changes were seen in the rates of ventilator-associated pneumonia during the preintervention and intervention periods.

Daily chlorhexidine baths appeared to be an effective intervention to reduce rates of CVC-associated BSI in an LTACH.

Controlled studies that took place in medical intensive care units (MICUs) have demonstrated that bathing patients with Chlorhexidine gluconate (CHG) can reduce skin colonization with potential pathogens and can lessen the risk of central venous catheter (CVC)-associated bloodstream infection (BSI).

TO examine, without oversight of practice by research study staff, the effectiveness or real-world effect of patient cleansing with CHG on rates of CVC-associated BSI.

In the fall of 2005, the MICU at Rush University Medical Center discontinued bathing patients daily with soap and water and substituted skin cleansing with no-rinse, 2% CHG-impregnated cloths. This change was a clinical management decision without research input.

A 21-bed MICU at Rush University Medical Center.

Patients hospitalized in the MICU during the period from September 2004 through October 2006.

In a pre-post study design, we gathered data from administrative and laboratory databases, infection control practitioner logs, and patient medical charts to compare rates of CVC-associated BSI and blood culture contamination between the baseline soap-and-water bathing period (September 2004-October 2005) and the CHG bathing period (November 2005-October 2006). Rates of secondary BSI, Clostridium difficile infection (CDI), ventilator-associated pneumonia (VAP), and urinary tract infection (UTI) served as control variables that were not expected to be affected by CHG bathing.

Bathing with CHG was associated with a statistically significant decrease in the rate of CVC-associated BSI (from 5.31 to 0.69 cases per 1,000 CVC-days; P = .006) and in the rate of blood culture contamination (from 6.99 to 4.1 cases per 1,000 patient-days; P = .04). Rates of secondary BSI, CDI, VAP, and UTI did not change significantly.

In our analysis of real-world practice, daily bathing of MICU patients with CHG was effective at reducing rates of CVC-associated BSI and blood culture contamination. Controlled studies are needed to determine whether these beneficial effects extend outside the MICU.

To evaluate the impact of cases of community-onset, healthcare facility (HCF)-associated Clostridium difficile infection (CDI) on the incidence and outbreak detection of CDI.

A retrospective multicenter cohort study.

Five university-affiliated, acute care HCFs in the United States.

We collected data (including results of C. difficile toxin assays of stool samples) on all of the adult patients admitted to the 5 hospitals during the period from July I, 2000, through June 30, 2006. CDI cases were classified as HCF-onset if they were diagnosed more than 48 hours after admission or as community-onset, HCF-associated if they were diagnosed within 48 hours after admission and if the patient had recently been discharged from the HCF. Four surveillance definitions were compared: cases of HCF-onset CDI only (hereafter referred to as HCF-onset CDI) and cases of HCF-onset and community-onset, HCF-associated CDI diagnosed within 30, 60, and 90 days after the last discharge from the study hospital (hereafter referred to as 30-day, 60-day, and 90-day CDI, respectively). Monthly CDI rates were compared. Control charts were used to identify potential CDI outbreaks.

The rate of 30-day CDI was significantly higher than the rate of HCF-onset CDI at 2 HCFs (P < .01 ). The rates of 30-day CDI were not statistically significantly different from the rates of 60-day or 90-day CDI at any HCF. The correlations between each HCF's monthly rates of HCF-onset CDI and 30-day CDI were almost perfect (ρ range, 0.94-0.99; P < .001). Overall, 12 time points had a CDI rate that was more than 3 standard deviations above the mean, including 11 time points identified using the definition for HCF-onset CDI and 9 time points identified using the definition for 30-day CDI, with discordant results at 4 time points (k = 0.794; P < .001).

Tracking cases of both community-onset and HCF-onset, HCF-associated CDI captures significantly more CDI cases, but surveillance of HCF-onset, HCF-associated CDI alone is sufficient to detect an outbreak.

To describe and measure reliability of a computer-assisted method of case vignette assembly and expert review to assess the appropriateness of antimicrobial therapy for hospitalized adults.

Feasibility and reliability analysis of computer-assisted tool used to compare the effects of antimicrobial stewardship interventions.

Public teaching hospital.

Randomly selected adult antimicrobial recipients admitted to inpatient medicine services.

Clinical data abstracted from 504 paper medical records were merged with computerized laboratory and pharmacy data to assemble case vignettes that underwent expert review for appropriateness. We performed 3 validations, as follows: data for 35 vignettes abstracted independently by 2 research assistants were assessed for interrater agreement, expert review of 24 vignettes was compared with review of the corresponding paper medical records, and interrater reliability of antimicrobial appropriateness assessments by 2 experts was determined for 70 case vignettes.

Vignette assembly and expert review each required 10–12 minutes per case. Potentially important discrepancies occurred in 0%–32% of clinical findings abstracted independently by 2 research assistants. Expert review of 24 vignettes and the corresponding full paper medical records yielded fair agreement (kappa, 0.30). The 2 experts identified inappropriate initial antimicrobial therapy in 67% and 61% of case vignettes reviewed independently; interrater agreement was improved after sequential case discussion and stringent application of appropriateness criteria (kappa, 0.72).

Our case vignette assembly and expert review method is efficient, but improvements in both technical and human performance are needed to be able to yield valid estimates of the prevalence of inappropriate antimicrobial use. Assessments of antimicrobial appropriateness require validation.