Marc-Oliver Wright

Preliminary assessment of an automated surveillance system for infection control.

BACKGROUND AND OBJECTIVEnRapid identification and investigation of potential outbreaks is key to limiting transmission in the healthcare setting. Manual review of laboratory results remains a cumbersome, time-consuming task for infection control practitioners (ICPs). Computer-automated techniques have shown promise for improving the efficiency and accuracy of surveillance. We examined the use of automated control charts, provided by an automated surveillance system, for detection of potential outbreaks.nnnSETTINGnA 656-bed academic medical center.nnnMETHODSnWe retrospectively reviewed 13 months (November 2001 through November 2002) of laboratory-patient data, comparing an automated surveillance application with standard infection control practices. We evaluated positive predictive value, sensitivity, and time required to investigate the alerts. An ICP created 75 control charts. A standardized case investigation form was developed to evaluate each alert for the likelihood of nosocomial transmission based on temporal and spatial overlap and culture results.nnnRESULTSnThe 75 control charts were created in 75 minutes and 18 alerts fired above the 3-sigma level. These were independently reviewed by an ICP and associate hospital epidemiologist. The review process required an average of 20 minutes per alert and the kappa score between the reviewers was 0.82. Eleven of the 18 alerts were determined to be potential outbreaks, yielding a positive predictive value of 0.61. Routine surveillance identified 5 of these 11 alerts during this time period.nnnCONCLUSIONnAutomated surveillance with user-definable control charts for cluster identification was more sensitive than routine methods and is capable of operating with high specificity and positive predictive value in a time-efficient manner.

The electronic medical record as a tool for infection surveillance: successful automation of device-days.

BACKGROUNDnManual collection of central venous catheter, ventilator, and indwelling urinary catheter device-days is time-consuming, often restricted to intensive care units (ICU) and prone to error.nnnMETHODSnWe describe the use of an electronic medical record to extract existing clinical documentation of invasive devices. This allowed automated device-days calculations for device-associated infection surveillance in an acute care setting.nnnRESULTSnThe automated system had high sensitivity, specificity, and positive and negative predictive values (>0.90) compared with chart review. The system is not restricted to ICUs and reduces surveillance efforts by a conservative estimate of over 3.5 work-weeks per year in our setting. Eighty percent of urinary catheter days and 50% of central venous catheter-days occurred outside the ICU.nnnCONCLUSIONnDevice-days may be automatically extracted from an existing electronic medical record with a higher degree of accuracy than manual collection while saving valuable personnel resources.

Reporting catheter-associated urinary tract infections: denominator matters.

OBJECTIVEnTo evaluate two different methods of measuring catheter-associated urinary tract infection (CAUTI) rates in the setting of a quality improvement initiative aimed at reducing device utilization.nnnDESIGN, SETTING, AND PATIENTSnComparison of CAUTI measurements in the context of a before-after trial of acute care adult admissions to a multicentered healthcare system.nnnMETHODSnCAUTIs were identified with an automated surveillance system, and device-days were measured through an electronic health record. Traditional surveillance measures of CAUTI rates per 1,000 device-days (R1) were compared with CAUTI rates per 10,000 patient-days (R2) before (T1) and after (T2) an intervention aimed at reducing catheter utilization.nnnRESULTSnThe device-utilization ratio declined from 0.36 to 0.28 between T1 and T2 (P = .001), while infection rates were significantly lower when measured by R2 (28.2 vs 23.2, P = .02). When measured by R1, however, infection rates trended upward by 6% (7.79 vs. 8.28, P = .47), and at the nursing unit level, reduction in device utilization was significantly associated with increases in infection rate.nnnCONCLUSIONSnThe widely accepted practice of using device-days as a method of risk adjustment to calculate device-associated infection rates may mask the impact of a successful quality improvement program and reward programs not actively engaged in reducing device usage.

Electronic prediction rules for methicillin-resistant Staphylococcus aureus colonization.

BACKGROUNDnConsiderable hospital resources are dedicated to minimizing the number of methicillin-resistant Staphylococcus aureus (MRSA) infections. One tool that is commonly used to achieve this goal is surveillance for MRSA colonization. This process is costly, and false-positive test results lead to isolation of individuals who do not carry MRSA. The performance of this technique would improve if patients who are at high risk of colonization could be readily targeted.nnnMETHODSnFive MRSA colonization prediction rules of varying complexity were derived in a population of 23,314 patients who were consecutively admitted to a US hospital and tested for colonization. Rules incorporated only prospectively collected, structured electronic data found in a patients record within 1 day of hospital admission. These rules were tested in a validation cohort of 26,650 patients who were admitted to 2 other hospitals.nnnRESULTSnThe prevalence of MRSA at hospital admission was 2.2% and 4.0% in the derivation and validation cohorts, respectively. Multivariable modeling identified predictors of MRSA colonization among demographic, admission-related, pharmacologic, laboratory, physiologic, and historical variables. Five prediction rules varied in their performance, but each could be used to identify the 30% of patients who accounted for greater than 60% of all cases of MRSA colonization and approximately 70% of all MRSA-associated patient-days. Most rules could also identify the 20% of patients with a greater than 8% chance of colonization and the 40% of patients among whom colonization prevalence was 2% or less.nnnCONCLUSIONSnWe report electronic prediction rules that can fully automate triage of patients for MRSA-related hospital admission testing and that offer significant improvements on previously reported rules. The efficiencies introduced may result in savings to infection control programs with little sacrifice in effectiveness.

Value of performing active surveillance cultures on intensive care unit discharge for detection of methicillin-resistant Staphylococcus aureus.

OBJECTIVEnTo quantify the value of performing active surveillance cultures for detection of methicillin-resistant Staphylococcus aureus (MRSA) on intensive care unit (ICU) discharge.nnnDESIGNnProspective cohort study.nnnSETTINGnMedical ICU (MICU) and surgical ICU (SICU) of a tertiary care hospital.nnnPARTICIPANTSnWe analyzed data on adult patients who were admitted to the MICU or SICU between January 17, 2001, and December 31, 2004. All participants had a length of ICU stay of at least 48 hours and had surveillance cultures of anterior nares specimens performed on ICU admission and discharge. Patients who had MRSA-positive clinical cultures in the ICU were excluded.nnnRESULTSnOf 2,918 eligible patients, 178 (6%) were colonized with MRSA on ICU admission, and 65 (2%) acquired MRSA in the ICU and were identified by results of discharge surveillance cultures. Patients with MRSA colonization confirmed by results of discharge cultures spent 853 days in non-ICU wards after ICU discharge, which represented 27% of the total number of MRSA colonization-days during hospitalization in non-ICU wards for patients discharged from the ICU.nnnCONCLUSIONSnSurveillance cultures of nares specimens collected at ICU discharge identified a large percentage of MRSA-colonized patients who would not have been identified on the basis of results of clinical cultures or admission surveillance cultures alone. Furthermore, these patients were responsible for a large percentage of the total number of MRSA colonization-days during hospitalization in non-ICU wards for patients discharged from the ICU.

Aggressive Control measures for resistant Acinetobacter baumannii and the impact on acquisition of methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus in a medical intensive care unit

The medical ICU implemented aggressive control measures following an outbreak of multidrug-resistant, clonal Acinetobacter baumannii. Multivariable regression analyses comparing acquisition (6 months preceding to 6 months during or following the outbreak) revealed decreased VRE and MRSA acquisition. Aggressive control measures can reduce VRE, and perhaps MRSA, transmission.

Methicillin-resistant Staphylococcus aureus infection and colonization among hospitalized prisoners.

We assessed methicillin-resistant Staphylococcus aureus (MRSA) infection and colonization in hospitalized prisoners. Of 434 admission surveillance cultures, 58 (13%) were positive for MRSA. The sensitivity of admission surveillance cultures of samples from the anterior nares was 72% and increased to 84% when the calculation included cultures of wound samples. Hospitalized prisoners are at high risk for MRSA infection and colonization, and surveillance should include cultures of nares and wound samples.

Healthcare-associated Infections Studies Project: An American Journal of Infection Control and National Healthcare Safety Network Data Quality Collaboration

This is the first case study published in a series in the American Journal of Infection Control since the National Healthcare Safety Network (NHSN) of the Centers for Disease Control and Prevention surveillance definition update of 2016. These cases represent some of the complex patient scenarios infection preventionists have encountered in their daily surveillance of health care-associated infections using NHSN procedural approaches and definitions. Case study objectives have been previously published.1 With each case, a link to an online survey is provided, where you may enter answers to questions and receive immediate feedback in the form of correct answers and explanations. All individual participant answers will remain confidential, although it is the authors’ intention to share a summary of the survey responses at a later date. Cases, answers, and explanations have been reviewed and approved by NHSN. We hope that you will take advantage of this offering, and we look forward to your active participation. The online survey may be found at https://www.surveymonkey.com/r/ 2016Case1. We strongly recommend that you review/reference the NHSN Patient Safety Component Manual, Multidrug-Resistant Organism and Clostridium difficile Infection (MDRO/CDI) Module2 for information you may need to answer the case study questions and use the MDRO and CDI LabID event calculator3 as needed. The findings and conclusions in this case study are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. For each question, please select the most correct answer.

Survey of infection prevention informatics use and practitioner satisfaction in US hospitals.

We surveyed hospital epidemiologists and infection preventionists on their usage of and satisfaction with infection prevention-specific software supplementing their institutions electronic medical record. Respondents with supplemental software were more satisfied with their softwares infection prevention and antimicrobial stewardship capabilities than those without. Infection preventionists were more satisfied than hospital epidemiologists.

Clinical decision support systems and infection prevention: To know is not enough

Clinical decision support (CDS) systems are an increasingly used form of technology designed to guide health care providers toward established protocols and best practices with the intent of improving patient care. Utilization of CDS for infection prevention is not widespread and is particularly focused on antimicrobial stewardship. This article provides an overview of CDS systems and summarizes key attributes of successfully executed tools. A selection of published reports of CDS for infection prevention and antimicrobial stewardship are described. Finally, an individual organization describes its CDS infrastructure, process of prioritization, design, and development, with selected highlights of CDS tools specifically targeting common infection prevention quality improvement initiatives.