Integration of genomic and clinical data augments surveillance of healthcare-acquired infections

2019 ◽  
Vol 40 (6) ◽  
pp. 649-655 ◽  
Author(s):  
Doyle V. Ward ◽  
Andrew G. Hoss ◽  
Raivo Kolde ◽  
Helen C. van Aggelen ◽  
Joshua Loving ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Infection Control ◽  
Clinical Data ◽  
Medical Center ◽  
Academic Medical Center ◽  
Whole Genome Sequence ◽  
False Alarms ◽  
Whole Genome ◽  
Healthcare Settings ◽  
Cross Transmission

AbstractBackground:Determining infectious cross-transmission events in healthcare settings involves manual surveillance of case clusters by infection control personnel, followed by strain typing of clinical/environmental isolates suspected in said clusters. Recent advances in genomic sequencing and cloud computing now allow for the rapid molecular typing of infecting isolates.Objective:To facilitate rapid recognition of transmission clusters, we aimed to assess infection control surveillance using whole-genome sequencing (WGS) of microbial pathogens to identify cross-transmission events for epidemiologic review.Methods:Clinical isolates ofStaphylococcus aureus,Enterococcus faecium,Pseudomonas aeruginosa, andKlebsiella pneumoniaewere obtained prospectively at an academic medical center, from September 1, 2016, to September 30, 2017. Isolate genomes were sequenced, followed by single-nucleotide variant analysis; a cloud-computing platform was used for whole-genome sequence analysis and cluster identification.Results:Most strains of the 4 studied pathogens were unrelated, and 34 potential transmission clusters were present. The characteristics of the potential clusters were complex and likely not identifiable by traditional surveillance alone. Notably, only 1 cluster had been suspected by routine manual surveillance.Conclusions:Our work supports the assertion that integration of genomic and clinical epidemiologic data can augment infection control surveillance for both the identification of cross-transmission events and the inclusion of missed and exclusion of misidentified outbreaks (ie, false alarms). The integration of clinical data is essential to prioritize suspect clusters for investigation, and for existing infections, a timely review of both the clinical and WGS results can hold promise to reduce HAIs. A richer understanding of cross-transmission events within healthcare settings will require the expansion of current surveillance approaches.

scholarly journals Accuracy of Infection Control Surveillance in Identifying Genomically Confirmed Cross Transmission Clusters

2020 ◽  
Vol 41 (S1) ◽  
pp. s439-s440
Author(s):  
Kyle Hansen ◽  
Richard T. Ellison ◽  
Doyle V. Ward ◽  
Devon J. Holler ◽  
Judy L. Ashworth ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Clinical Data ◽  
Medical Center ◽  
Academic Medical Center ◽  
Automated Analysis ◽  
Sample Collection ◽  
Single Nucleotide Variants ◽  
Cross Transmission ◽  
Unique Strain ◽  
Genomic Relatedness

Background: Infection prevention surveillance for cross transmission is often performed by manual review of microbiologic culture results to identify geotemporally related clusters. However, the sensitivity and specificity of this approach remains uncertain. Whole-genome sequencing (WGS) analysis can help provide a gold-standard for identifying cross-transmission events. Objective: We employed a published WGS program, the Philips IntelliSpace Epidemiology platform, to compare accuracy of two surveillance methods: (i.) a virtual infection practitioner (VIP) with perfect recall and automated analysis of antibiotic susceptibility testing (AST), sample collection timing, and patient location data and (ii) a novel clinical matching (CM) algorithm that provides cluster suggestions based on a nuanced weighted analysis of AST data, timing of sample collection, and shared location stays between patients. Methods: WGS was performed routinely on inpatient and emergency department isolates of Enterobacter cloacae, Enterococcus faecium, Klebsiella pneumoniae, and Pseudomonas aeruginosa at an academic medical center. Single-nucleotide variants (SNVs) were compared within core genome regions on a per-species basis to determine cross-transmission clusters. Moreover, one unique strain per patient was included within each analysis, and duplicates were excluded from the final results. Results: Between May 2018 and April 2019, clinical data from 121 patients were paired with WGS data from 28 E. cloacae, 21 E. faecium, 61 K. pneumoniae, and 46 P. aeruginosa isolates. Previously published SNV relatedness thresholds were applied to define genomically related isolates. Mapping of genomic relatedness defined clusters as follows: 4 patients in 2 E. faecium clusters and 2 patients in 1 P. aeruginosa cluster. The VIP method identified 12 potential clusters involving 28 patients, all of which were “pseudoclusters.” Importantly, the CM method identified 7 clusters consisting of 27 patients, which included 1 true E. faecium cluster of 2 patients with genomically related isolates. Conclusions: In light of the WGS data, all of the potential clusters identified by the VIP were pseudoclusters, lacking sufficient genomic relatedness. In contrast, the CM method showed increased sensitivity and specificity: it decreased the percentage of pseudoclusters by 14% and it identified a related genomic cluster of E. faecium. These findings suggest that integrating clinical data analytics and WGS is likely to benefit institutions in limiting expenditure of resources on pseudoclusters. Therefore, WGS combined with more sophisticated surveillance approaches, over standard methods as modeled by the VIP, are needed to better identify and address true cross-transmission events.Funding: This study was supported by Philips Healthcare.Disclosures: None

scholarly journals Utility of Routine Genomic Sequencing for Infection Control Surveillance

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S35-S35
Author(s):  
Richard T Ellison ◽  
Andrew Hoss ◽  
Jomol Mathew ◽  
Jeff Halperin ◽  
Brian Gross ◽  
...  
Keyword(s):  
Infection Control ◽  
Medical Center ◽  
Academic Medical Center ◽  
Microbial Pathogens ◽  
Genomic Sequencing ◽  
Sequencing Analysis ◽  
Nucleotide Polymorphisms ◽  
Philips Healthcare ◽  
Recent Transmission ◽  
Research Grant

Abstract Background Recent work indicates that comprehensive genomic sequencing can be a highly effective tool in defining the transmission of microbial pathogens. We have studied the utility of the routine use of genomic sequencing for infection control surveillance in an academic medical center. Methods The genomes of inpatient and emergency department isolates of Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Enterococcus faecium were sequenced. Within each species, single-nucleotide polymorphisms (SNP) were identified in the core genome for all isolates using alignment-based methods. The number of SNP differences between isolate pairs was determined and used, in combination with the patient’s electronic medical records to identify potential transmission events. Results Between September 2016 and March 2017, 388 S. aureus, 66 P. aeruginosa, 48 K. pneumoniae, and 29 E. faecium isolates were sequenced from 373 patients. There was variation in the distribution of SNP differences between intrapatient isolates for the four pathogens; with the least variability for E. faecium and greatest for P. aeruginosa. The majority of the bacterial isolates from separate patients appeared to be genetically unique exhibiting marked SNP differences from other isolates. There were 19 sets of isolates where the SNP variation between interpatient isolates was either comparable to that of intrapatient variation (12) and suggestive of recent transmission events, or with SNP variation somewhat greater than the intrapatient SNP variation (7) suggesting relative relatedness. Only one of the highly related sets had been previously identified by standard infection control surveillance. Likely transmissions appeared to have occurred both in the inpatient and outpatient settings, and the transmission routes were not always apparent. Conclusion The routine use of genomic sequencing analysis identified previously unrecognized likely transmission events within the institution’s patient population that are of relevance to infection control surveillance. This capacity should significantly enhance our understanding of the epidemiology of hospital acquired infections, and assist in developing and implementing new prevention strategies. Disclosures R. T. Ellison III, Philips Healthcare: Consultant and Grant Investigator, Consulting fee and Research grant; A. Hoss, Philips: Employee, Salary; J. Mathew, Philips Healthcare: Investigator, Research grant; J. Halperin, Philips Healthcare: Employee and Shareholder, Salary; B. Gross, Philips: Employee and Shareholder, Salary; D. V. Ward, Philips Healthcare: Consultant, Investigator and Research Contractor, Consulting fee, Research support and Salary

Double Trouble: Patients With Both True and False Arrhythmia Alarms

2020 ◽  
Vol 40 (2) ◽  
pp. 14-23
Author(s):  
Stella Chiu Nguyen ◽  
Sukardi Suba ◽  
Xiao Hu ◽  
Michele M. Pelter
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Medical Center ◽  
Academic Medical Center ◽  
Secondary Analysis ◽  
Altered Mental Status ◽  
False Alarms ◽  
Number Of False Alarms ◽  
Academic Medical ◽  
Using Data

Background Patients with both true and false arrhythmia alarms pose a challenge because true alarms might be buried among a large number of false alarms, leading to missed true events. Objective To determine (1) the frequency of patients with both true and false arrhythmia alarms; (2) patient, clinical, and electrocardiographic characteristics associated with both true and false alarms; and (3) the frequency and types of true and false arrhythmia alarms. Methods This was a secondary analysis using data from an alarm study conducted at a tertiary academic medical center. Results Of 461 intensive care unit patients, 211 (46%) had no arrhythmia alarms, 12 (3%) had only true alarms, 167 (36%) had only false alarms, and 71 (15%) had both true and false alarms. Ventricular pacemaker, altered mental status, mechanical ventilation, and cardiac intensive care unit admission were present more often in patients with both true and false alarms than among other patients (P < .001). Intensive care unit stays were longer in patients with only false alarms (mean [SD], 106 [162] hours) and those with both true and false alarms (mean [SD], 208 [333] hours) than in other patients. Accelerated ventricular rhythm was the most common alarm type (37%). Conclusions An awareness of factors associated with arrhythmia alarms might aid in developing solutions to decrease alarm fatigue. To improve detection of true alarms, further research is needed to build and test electrocardiographic algorithms that adjust for clinical and electrocardiographic characteristics associated with false alarms.

scholarly journals Whole-Genome Sequencing for Investigation of Possible Hospital Transmission of Tuberculosis

2020 ◽  
Vol 41 (S1) ◽  
pp. s435-s435
Author(s):  
Jenna Rasmusson ◽  
Priya Sampathkumar ◽  
Nancy Wengenack
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Medical Center ◽  
Academic Medical Center ◽  
Clinical Information ◽  
The United States ◽  
Advanced Lung Cancer ◽  
Massive Hemoptysis ◽  
Whole Genome ◽  
Foreign Born

Background: Whole-genome sequencing (WGS) is increasingly used in epidemiological investigations of infectious diseases. We describe the use of WGS to identify drug-resistance variants of tuberculosis (TB) and to determine potential transmission between patients at an academic medical center. Methods: Chart review and interviews of patients and healthcare workers along with WGS of M. tuberculosis isolates from the patients. Clinical information: In June 2019, patient A, a 20-year-old college student born in the United States was admitted with massive hemoptysis. The patient was identified as having active, cavitary TB that was acid-fast smear positive, and the mycobacterial culture grew M. tuberculosis. Patient B, a 40-year-old foreign-born patient with advanced lung cancer was acid-fast smear negative, but mycobacterial cultures were positive for M. tuberculosis. The 2 patients had overlapping stays in the medical intensive care unit. There was concern that patient B had acquired TB during her stay in the hospital from patient A, who was highly infectious. WGS showed that the mycobacterial isolates from the 2 patients were unrelated. Patient A was a student at a college campus where the state health department had previously issued a health advisory concerning active pulmonary TB in a student; and 7 additional TB cases were subsequently identified through contact investigation. Patient A denied any contact with other persons who were part of the outbreak and had not been included in the contact investigations of any of the cases. Of the 8 outbreak cases, 6 had been seen at our institution and had isolates available for testing. WGS showed that these 6 isolates matched patient A, establishing that she was part of the college outbreak. Conclusions: WGS was useful in establishing the source of M. tuberculosis infection in a patient who did not have known exposure to TB and in demonstrating that transmission of TB did not occur in the hospital.Funding: NoneDisclosures: None

Application of a fluorescent marker with quantitative bioburden methods to assess cleanliness

2018 ◽  
Vol 39 (11) ◽  
pp. 1296-1300 ◽  
Author(s):  
I-Chen Hung ◽  
Hao-Yuan Chang ◽  
Aristine Cheng ◽  
An-Chi Chen ◽  
Ling Ting ◽  
...  
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Survey Study ◽  
Environmental Cleaning ◽  
Fluorescent Marker ◽  
Atp Assay ◽  
Atp Bioluminescence ◽  
Bioluminescence Assay ◽  
Cross Transmission ◽  
Atp Bioluminescence Assay

AbstractBackgroundImprovement of environmental cleaning in hospitals has been shown to decrease in-hospital cross transmission of pathogens. Several objective methods, including aerobic colony counts (ACCs), the adenosine triphosphate (ATP) bioluminescence assay, and the fluorescent marker method have been developed to assess cleanliness. However, the standard interpretation of cleanliness using the fluorescent marker method remains uncertain.ObjectiveTo assess the fluorescent marker method as a tool for determining the effectiveness of hospital cleaning.DesignA prospective survey study.SettingAn academic medical center.MethodsThe same 10 high-touch surfaces were tested after each terminal cleaning using (1) the fluorescent marker method, (2) the ATP assay, and (3) the ACC method. Using the fluorescent marker method under study, surfaces were classified as totally clean, partially clean, or not clean. The ACC method was used as the standard for comparison.ResultsAccording to the fluorescent marker method, of the 830 high-touch surfaces, 321 surfaces (38.7%) were totally clean (TC group), 84 surfaces (10.1%) were partially clean (PC group), and 425 surfaces (51.2%) were not clean (NC group). The TC group had significantly lower ATP and ACC values (mean ± SD, 428.7 ± 1,180.0 relative light units [RLU] and 15.6 ± 77.3 colony forming units [CFU]/100 cm2) than the PC group (1,386.8 ± 2,434.0 RLU and 34.9 ± 87.2 CFU/100 cm2) and the NC group (1,132.9 ± 2,976.1 RLU and 46.8 ± 119.2 CFU/100 cm2).ConclusionsThe fluorescent marker method provided a simple, reliable, and real-time assessment of environmental cleaning in hospitals. Our results indicate that only a surface determined to be totally clean using the fluorescent marker method could be considered clean.

Investigation of an Outbreak of Methicillin-ResistantStaphylococcus aureusin Patients With Skin Disease Using DNA Restriction Patterns

1992 ◽  
Vol 13 (8) ◽  
pp. 472-476 ◽  
Author(s):  
Richard A. Venezia ◽  
Valerie Harris ◽  
Cynthia Miller ◽  
Hilary Peck ◽  
Mara San Antonio
Keyword(s):  
Infection Control ◽  
Medical Center ◽  
Academic Medical Center ◽  
Tertiary Care ◽  
Restriction Pattern ◽  
Staff Members ◽  
Skin Ulcers ◽  
Academic Medical ◽  
Dna Restriction ◽  
Total Dna

AbstractObjective:To investigate an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) among patients using chromosomal typing of the isolates.Design:Comparison of epidemiological and clinical data to endonuclease restriction fragmentation analysis (RFA) of the MRSA isolates associated with an outbreak. Total DNA from the MRSA isolates was restricted with HINDIII and HAEIII for typing.Setting:Tertiary care academic medical center.Methods:An epidemiological investigation of an outbreak of MRSA among patients in private rooms was evaluated by routine infection control methods. The MRSA isolates from blood cultures of 7 patients and the nares of a nurse were collected during the outbreak. MRSA isolates from 23 patients not associated with the outbreak also were collected. The total DNA of the MRSA isolates were restricted with HINDIII and HAEIII and electrophoresed on 0.6% agarose gels.Results:MRSA from 4 of the 7 bacteremic patients and the nurse on the outbreak unit had the same endonuclease restriction pattern. The patients were linked in that they were compromised by severe psoriasis or skin ulcers, were on the unit during the same period, and had oatmeal baths in a common bathtub. Of 50 staff members screened, the nurse was the only person detected as colonized by the strain. The other 3 patients on the unit as well as the 23 patients in other locations not associated with the outbreak had MRSA isolates with different RFA patterns. The use of the bathtub was discontinued and further transmission of MRSA was stopped.Conclusions:A comparison of the relatedness of MRSA by RFA demonstrated the uniqueness of the epidemiologically linked isolates and the utility of the RFA technique in the performance of routine infection control investigations.

scholarly journals Access to Routinely Collected Clinical Data for Research: A Process Implemented at an Academic Medical Center

2019 ◽  
Vol 12 (3) ◽  
pp. 231-235
Author(s):  
Susan C. Guerrero ◽  
Sujatha Sridhar ◽  
Cynthia Edmonds ◽  
Christina F. Solis ◽  
Jiajie Zhang ◽  
...  
Keyword(s):  
Clinical Data ◽  
Medical Center ◽  
Academic Medical Center ◽  
Academic Medical

scholarly journals Identification of a Novel Clone, ST736, among Enterococcus faecium Clinical Isolates and Its Association with Daptomycin Nonsusceptibility

2014 ◽  
Vol 58 (8) ◽  
pp. 4848-4854 ◽  
Author(s):  
Guiqing Wang ◽  
Sitharthan Kamalakaran ◽  
Abhay Dhand ◽  
Weihua Huang ◽  
Caroline Ojaimi ◽  
...  
Keyword(s):  
Enterococcus Faecium ◽  
Medical Center ◽  
Tertiary Care ◽  
The United States ◽  
Clinical Isolates ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Content Type ◽  
Tertiary Care Medical Center

ABSTRACTResistance to daptomycin in enterococcal clinical isolates remains rare but is being increasingly reported in the United States and worldwide. There are limited data on the genetic relatedness and microbiological and clinical characteristics of daptomycin-nonsusceptible enterococcal clinical isolates. In this study, we assessed the population genetics of daptomycin-nonsusceptibleEnterococcus faecium(DNSE) clinical isolates by multilocus sequence typing (MLST) and whole-genome sequencing analysis. Forty-two nonduplicate DNSE isolates and 43 randomly selected daptomycin-susceptibleE. faeciumisolates were included in the analysis. AllE. faeciumisolates were recovered from patients at a tertiary care medical center in suburban New York City from May 2009 through December 2013. The daptomycin MICs of the DNSE isolates ranged from 6 to >256 μg/ml. Three major clones ofE. faecium(ST18, ST412, and ST736) were identified among these clinical isolates by MLST and whole-genome sequence-based analysis. A newly recognized clone, ST736, was seen in 32 of 42 (76.2%) DNSE isolates and in only 14 of 43 (32.6%) daptomycin-susceptibleE. faeciumisolates (P< 0.0001). This report provides evidence of the association betweenE. faeciumclone ST736 and daptomycin nonsusceptibility. The identification and potential spread of this novelE. faeciumclone and its association with daptomycin nonsusceptibility constitute a challenge for patient management and infection control at our medical center.

scholarly journals A new hat for librarians: providing REDCap support to establish the library as a central data hub

2018 ◽  
Vol 106 (1) ◽  
Author(s):  
Kevin Read ◽  
Fred Willie Zametkin LaPolla
Keyword(s):  
Data Management ◽  
Clinical Data ◽  
Medical Center ◽  
Academic Medical Center ◽  
Data Series ◽  
Management Support ◽  
Support Unit ◽  
Data Services ◽  
Service Gap ◽  
Central Data

Background: REDCap, an electronic data capture tool, supports good research data management, but many researchers lack familiarity with the tool. While a REDCap administrator provided technical support and a clinical data management support unit provided study design support, a service gap existed.Case Presentation: Librarians with REDCap expertise sought to increase and improve usage through outreach, workshops, and consultations. In collaboration with a REDCap administrator and the director of the clinical data management support unit, the role of the library was established in providing REDCap training and consultations. REDCap trainings were offered to the medical center during the library’s quarterly data series, which served as a springboard for offering tailored REDCap support to researchers and research groups.Conclusions: Providing REDCap support has proved to be an effective way to associate the library with data-related activities in an academic medical center and identify new opportunities for offering data services in the library. By offering REDCap services, the library established strong partnerships with the Information Technology Department, Clinical Data Support Department, and Compliance Office by filling in training gaps, while simultaneously referring users back to these departments when additional expertise was required. These new partnerships continue to grow and serve to position the library as a central data hub in the institution.

scholarly journals 68. Active Monitoring of a Healthcare Worker Cohort During the COVID-19 Epidemic

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S165-S165
Author(s):  
Rupak Datta ◽  
Melissa Campbell ◽  
Anne Wyllie ◽  
Arnau Casanovas-Massana ◽  
Ryan Handoko ◽  
...  
Keyword(s):  
Medical Center ◽  
Academic Medical Center ◽  
Significant Proportion ◽  
Healthcare Setting ◽  
Active Monitoring ◽  
Passive Monitoring ◽  
Self Monitoring ◽  
Healthcare Settings ◽  
Blood Specimens

Abstract Background Initial CDC recommendations for passive monitoring of COVID-19 related symptoms among staff may not be sufficient in preventing the introduction and transmission of SARS-CoV-2 in healthcare settings. We therefore implemented active monitoring for SARS-CoV-2 infection in healthcare workers (HCWs) at an academic medical center during the COVID-19 epidemic in northeast US. Methods We recruited a cohort of HCWs at Yale New Haven Hospital who worked in COVID-19 units and did not have COVID-19 related symptoms between March 28 and June 1, 2020. During follow-up, participants provided daily information on symptoms by responding to a web-based questionnaire, self-administered nasopharyngeal (NP) and saliva specimens every 3 days, and blood specimens every 14 days. We performed SARS-CoV-2 RT-PCR and an anti-spike protein IgM and IgG ELISA to identify virological and serological-confirmed infection, respectively. Results We enrolled 525 (13%) amongst 4,136 HCW of whom daily information on symptoms and NP, saliva, and blood specimens were obtained for 66% (of 13208), 42% (or 1977), 44% (of 2071) and 65% (of 1099), respectively, of the follow-up measurement points. We identified 16 (3.0% of 525) HCWs with PCR-confirmed SARS-CoV-2 infection and an additional 12 (2.3% of 525) who were not tested by PCR or had negative PCR results but had serological evidence of infection. The overall cumulative incidence of SARS-CoV-2 infection was 5.3% (28 of 525) amongst HCWs. Cases were not identified by hospital protocols for passive staff self-monitoring for symptoms. Amongst 16 PCR-confirmed cases, 9 (56%) of the 16 PCR-confirmed HCW had symptoms during or after the date of initial detection. We did not identify an epidemiological link between the 28 confirmed cases. Conclusion We found that a significant proportion (5.3%) of HCWs were infected with SARS-CoV-2 during the COVID-19 epidemic. In the setting of universal PPE use, infections were possibly acquired in the community rather than stemming from patient-HCW or HCW-HCW transmission. Passive monitoring of symptoms is inadequate in preventing introductions of SARS-CoV-2 into the healthcare setting due to asymptomatic and oligosymptomatic presentations. Disclosures All Authors: No reported disclosures

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