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To identify important risk factors for carbapenem-resistant Enterobacterales (CRE) infections among hospitalized patients.
We utilized a case–case–control design that compared patients with CRE infections to patients with carbapenem-susceptible Enterobacterales (CSE) infections and randomly selected controls during the period from January 2011 through December 2016.
The study population was selected from patients at a large metropolitan tertiary-care and instructional medical center.
Cases of CRE were defined as initial admission of adults diagnosed with a bacterial infection of an Enterobacterales species resistant clinically or through sensitivity testing to carbapenems 48 hours or more after admission. Cases of CSE were selected from the same patient population as the CRE cases within a 30-day window for admission, with diagnostic pathogens identified as susceptible to carbapenems. Controls were defined as adult patients admitted to any service within a 30-day window from a CRE case for >48 hours who did not meet either of the above case definitions during that admission.
Antibiotic exposure within 90 days prior to admission and length of hospital stay were both associated with increased odds of CRE and CSE infections compared to controls. Patients with CRE infections had >18 times greater odds of prior antibiotic exposure compared to patients with CSE infections.
Antibiotic exposure and increased length of hospital stay may result in increased patient risk of developing an infection resistant to carbapenems and other β-lactams.
Background: Antimicrobial resistance (AMR) is an increasingly critical global public health challenge. An initial step in prevention is the understanding of resistance patterns with accurate surveillance. To improve accurate surveillance and good clinical care, we developed training materials to improve the appropriate collection of clinical culture samples in Ethiopia. Methods: Specimen-collection training materials were initially developed by a team of infectious diseases physicians, a clinical microbiologist, and a monitoring and evaluation specialist using a training of trainers (ToT) platform. Revisions after each training session were provided by Ethiopian attendees including the addition of regional and culturally relevant material. The training format involved didactic presentations, interactive practice sessions with participants providing feedback and training to each other and the entire group as well as assessments of all training activities. Results: Overall, 4 rounds of training were conducted from August 2017 to September 2019. The first 2 rounds of training were conducted by The Ohio State University (OSU) staff, and Ethiopian trainers conducted the last 2 rounds. Initial training was primarily in lecture format outlining use of microbiology laboratory findings in clinical practice and steps for collecting specimens correctly. Appropriate specimen collection was demonstrated and practiced. Essential feedback from this early audience provided input for the final development of the training manual and visual aids. The ToT for master trainers took place in July 2018 and was conducted by OSU staff. In sessions held in February and August 2019, these master trainers provided training to facility trainers, who provide training to personnel directly responsible for specimen collection. In total, 144 healthcare personnel (including physicians, nurses, and laboratory staff), from 12 representative Ethiopian public and academic hospitals participated in the trainings. Participants were satisfied with the quality of the training (typically ranked >4.5 of 5.0) and strongly agreed that the objectives were clearly defined and that the information was relevant to their work. Posttraining scores increased by 23%. Conclusions: Training materials for clinical specimen collection have been developed for use in low- and middle-resource settings and with initial pilot testing and adoption in Ethiopia. The trainings were well accepted, and Ethiopian personnel were able to successfully lead the trainings and improve their knowledge and skills regarding specimen collection. The materials are being finalized in an online format for easier open access dissemination. Further studies are planned to determine the effectiveness of the trainings in improving the quality of clinical specimen submissions to the microbiology laboratory.
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
Infection surveillance definitions for long-term care facilities (ie, the McGeer Criteria) have not been updated since 1991. An expert consensus panel modified these definitions on the basis of a structured review of the literature. Significant changes were made to the criteria defining urinary tract and respiratory tract infections. New definitions were added for norovirus gastroenteritis and Clostridum difficile infections.
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.
Automated surveillance using electronically available data has been found to be accurate and save time. An automated Clostridium difficile infection (CDI) surveillance algorithm was validated at 4 Centers for Disease Control and Prevention Epicenter hospitals. Electronic surveillance was highly sensitive, specific, and showed good to excellent agreement for hospital-onset; community-onset, study facility-associated; indeterminate; and recurrent CDI.
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.
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 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 investigate a pseudo-outbreak of “Mycobacterium paraffinicum” (unofficial taxon) infection and/or colonization, using isolates recovered from clinical and environmental specimens.
University-affiliated, tertiary-care hospital.
M. paraffinicum, a slow-growing, nontuberculous species of mycobacteria, was recovered from 21 patients and an ice machine on a single patient care unit over a 2.5-year period. The clinical, epidemiological, and environmental investigation of this pseudo-outbreak is described.
Twenty-one patients with pulmonary symptoms and possible risk factors for tuberculosis were admitted to inpatient rooms that provided airborne isolation conditions in 2 adjacent hospital buildings. In addition, 1 outpatient had induced sputum cultured for mycobacteria in the pulmonary function laboratory. Of the samples obtained from these 21 patients, 26 isolates from respiratory samples and 1 isolate from a stool sample were identified as M. paraffinicum. Environmental isolates obtained from an ice machine in the patient care unit where the majority of the patients were admitted were also identified as M. paraffinicum.
An epidemiological investigation that used molecular tools confirmed the suspicion of a pseudo-outbreak of M. paraffinicum infection and/or colonization. The hospital water system was identified as the source of contamination.