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

To evaluate the use of inpatient pharmacy and administrative data to detect surgical site infections (SSIs) following hysterectomy and colorectal and vascular surgery.

Retrospective cohort study.

Five hospitals affiliated with academic medical centers.

Adults who underwent abdominal or vaginal hysterectomy, colorectal surgery, or vascular surgery procedures between July 1, 2003, and June 30, 2005.

We reviewed the medical records of weighted, random samples drawn from 3,079 abdominal and vaginal hysterectomy, 4,748 colorectal surgery, and 3,332 vascular surgery procedures. We compared routine surveillance with screening of inpatient pharmacy data and diagnosis codes and then performed medical record review to confirm SSI status.

Medical records from 823 hysterectomy, 736 colorectal surgery, and 680 vascular surgery procedures were reviewed. SSI rates determined by antimicrobial- and/or diagnosis code-based screening followed by medical record review (enhanced surveillance) were substantially higher than rates determined by routine surveillance (4.3% [95% confidence interval, 3.6%—5.1%] vs 2.7% for hysterectomies, 7.1% [95% confidence interval, 6.7%–8.2%] vs 2.0% for colorectal procedures, and 2.3% [95% confidence interval, 1.9%–2.9%] vs 1.4% for vascular procedures). Enhanced surveillance had substantially higher sensitivity than did routine surveillance to detect SSI (92% vs 59% for hysterectomies, 88% vs 22% for colorectal procedures, and 72% vs 43% for vascular procedures). A review of medical records confirmed SSI for 31% of hysterectomies, 20% of colorectal procedures, and 31% of vascular procedures that met the enhanced screening criteria.

Antimicrobial- and diagnosis code-based screening may be a useful method for enhancing and streamlining SSI surveillance for a variety of surgical procedures, including those procedures targeted by the Centers for Medicare and Medicaid Services.

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.

To evaluate the use of routinely collected electronic health data in Medicare claims to identify surgical site infections (SSIs) following hip arthroplasty, knee arthroplasty, and vascular surgery.

Retrospective cohort study.

Four academic hospitals that perform prospective SSI surveillance.

We developed lists of International Classification of Diseases, Ninth Revision, and Current Procedural Terminology diagnosis and procedure codes to identify potential SSIs. We then screened for these codes in Medicare claims submitted by each hospital on patients older than 65 years of age who had undergone 1 of the study procedures during 2007. Each site reviewed medical records of patients identified by either claims codes or traditional infection control surveillance to confirm SSI using Centers for Disease Control and Prevention/ National Healthcare Safety Network criteria. We assessed the performance of both methods against all chart-confirmed SSIs identified by either method.

Claims-based surveillance detected 1.8–4.7-fold more SSIs than traditional surveillance, including detection of all previously identified cases. For hip and vascular surgery, there was a 5-fold and 1.6-fold increase in detection of deep and organ/space infections, respectively, with no increased detection of deep and organ/space infections following knee surgery. Use of claims to trigger chart review led to confirmation of SSI in 1 out of 3 charts for hip arthroplasty, 1 out of 5 charts for knee arthroplasty, and 1 out of 2 charts for vascular surgery.

Claims-based SSI surveillance markedly increased the number of SSIs detected following hip arthroplasty, knee arthroplasty, and vascular surgery. It deserves consideration as a more effective approach to target chart reviews for identifying SSIs.

Infect Control Hosp Epidemiol 2012;33(1):40-49

To evaluate whether longitudinal insurer claims data allow reliable identification of elevated hospital surgical site infection (SSI) rates.

We conducted a retrospective cohort study of Medicare beneficiaries who underwent coronary artery bypass grafting (CABG) in US hospitals performing at least 80 procedures in 2005. Hospitals were assigned to deciles by using case mix–adjusted probabilities of having an SSI-related inpatient or outpatient claim code within 60 days of surgery. We then reviewed medical records of randomly selected patients to assess whether chart-confirmed SSI risk was higher in hospitals in the worst deciles compared with the best deciles.

Fee-for-service Medicare beneficiaries who underwent CABG in these hospitals in 2005.

We evaluated 114,673 patients who underwent CABG in 671 hospitals. In the best decile, 7.8% (958/12,307) of patients had an SSI-related code, compared with 24.8% (2,747/11,068) in the worst decile (P<.001). Medical record review confirmed SSI in 40% (388/980) of those with SSI-related codes. In the best decile, the chart-confirmed annual SSI rate was 3.2%, compared with 9.4% in the worst decile, with an adjusted odds ratio of SSI of 2.7 (confidence interval, 2.2–3.3; P<.001) for CABG performed in a worst-decile hospital compared with a best-decile hospital.

Claims data can identify groups of hospitals with unusually high or low post-CABG SSI rates. Assessment of claims is more reproducible and efficient than current surveillance methods. This example of secondary use of routinely recorded electronic health information to assess quality of care can identify hospitals that may benefit from prevention programs.

To outline methods for deriving and validating intensive care unit (ICU) antimicrobial utilization (AU) measures from computerized data and to describe programming problems that emerged.

Retrospective evaluation of computerized pharmacy and administrative data.

ICUs from 4 academic medical centers over 36 months.

Investigators separately developed and validated programming code to report AU measures in selected ICUs. Use of antibacterial and antifungal drugs for systemic administration was categorized and expressed as antimicrobial-days (each day that each antimicrobial drug was given to each patient) and patient-days receiving antimicrobials (each day that any antimicrobial drug was given to each patient). Monthly rates were compiled and analyzed centrally, with ICU patient-days as the denominator. Results were validated against data collected from manual review of medical records. Frequent discussion among investigators aided identification and correction of programming problems.

AU data were successfully programmed though a reiterative process of computer code revision. After identifying and resolving major programming errors, comparison of computerized patient-level data with data collected by manual review of medical records revealed discrepancies in antimicrobial-days and patient-days receiving antimicrobials that ranged from less than 1% to 17.7%. The hospital from which numerator data were derived from electronic records of medication administration had the least discrepant results.

Computerized AU measures can be derived feasibly, but threats to validity must be sought out and corrected. The magnitude of discrepancies between computerized AU data and a gold standard based on manual review of medical records varies, with electronic records of medication administration providing maximal accuracy.

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.

The incidence of surgical site infection (SSI) after hysterectomy ranges widely from 2% to 21%. A specific risk stratification index could help to predict more accurately the risk of incisional SSI following abdominal hysterectomy and would help determine the reasons for the wide range of reported SSI rates in individual studies. To increase our understanding of the risk factors needed to build a specific risk stratification index, we performed a retrospective multihospital analysis of risk factors for SSI after abdominal hysterectomy.

Retrospective case-control study of 545 abdominal and 275 vaginal hysterectomies from July 1, 2003, to June 30, 2005, at 4 institutions. SSIs were defined by using Centers for Disease Control and Prevention/National Nosocomial Infections Surveillance criteria. Independent risk factors for abdominal hysterectomy were identified by using logistic regression.

There were 13 deep incisional, 53 superficial incisional, and 18 organ-space SSIs after abdominal hysterectomy and 14 organ-space SSIs after vaginal hysterectomy. Because risk factors for organ-space SSI were different according to univariate analysis, we focused further analyses on incisional SSI after abdominal hysterectomy. The maximum serum glucose level within 5 days after operation was highest in patients with deep incisional SSI, lower in patients with superficial incisional SSI, and lowest in uninfected patients (median, 189, 156, and 141 mg/dL, respectively; P = .005). Independent risk factors for incisional SSI included blood transfusion (odds ratio [OR], 2.4) and morbid obesity (body mass index [BMI], >35; OR, 5.7). Duration of operation greater than the 75th percentile (OR, 1.7), obesity (BMI, 30–35; OR, 3.0), and lack of private health insurance (OR, 1.7) were marginally associated with increased odds of SSI.

Incisional SSI after abdominal hysterectomy was associated with increased BMI and blood transfusion. Longer duration of operation and lack of private health insurance were marginally associated with SSI.

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.