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

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.

Implementation of a pharmacist-provided pharmacogenomics service in an executive health program

2021 ◽  
Author(s):  
Ina Liko ◽  
Lisa Corbin ◽  
Eric Tobin ◽  
Christina L Aquilante ◽  
Yee Ming Lee
Keyword(s):  
Health Program ◽  
Medical Center ◽  
Academic Medical Center ◽  
Test Results ◽  
Sample Collection ◽  
Team Members ◽  
University Of Colorado ◽  
Academic Medical ◽  
Previous Medication ◽  
Selection Of

Abstract Disclaimer In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose We describe the implementation of a pharmacist-provided pharmacogenomics (PGx) service in an executive health program (EHP) at an academic medical center. Summary As interest in genomic testing grows, pharmacists have the opportunity to advance the use of PGx in EHPs, in collaboration with other healthcare professionals. In November 2018, a pharmacist-provided PGx service was established in the EHP at the University of Colorado Hospital. The team members included 3 physicians, a pharmacist trained in PGx, a registered dietitian/exercise physiologist, a nurse, and 2 medical assistants. We conducted 4 preimplementation steps: (1) assessment of the patient population, (2) selection of a PGx test, (3) establishment of a visit structure, and (4) selection of a billing model. The PGx consultations involved two 1-hour visits. The first visit encompassed pretest PGx education, review of the patient’s current medications and previous medication intolerances, and DNA sample collection for genotyping. After this visit, the pharmacist developed a therapeutic plan based on the PGx test results, discussed the results and plan with the physician, and created a personalized PGx report. At the second visit, the pharmacist reviewed the PGx test results, personalized the PGx report, and discussed the PGx-guided therapeutic plan with the patient. Overall, the strategy worked well; minor challenges included evaluation of gene-drug pairs with limited PGx evidence, communication of information to non-EHP providers, scheduling issues, and reimbursement. Conclusion The addition of a PGx service within an EHP was feasible and provided pharmacists the opportunity to lead PGx efforts and collaborate with physicians to expand the precision medicine footprint at an academic medical center.

scholarly journals Assessment of a Human Cadaver Model for Training Emergency Medicine Residents in the Ultrasound Diagnosis of Pneumothorax

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Srikar Adhikari ◽  
Wesley Zeger ◽  
Michael Wadman ◽  
Richard Walker ◽  
Carol Lomneth
Keyword(s):  
Emergency Medicine ◽  
Sensitivity And Specificity ◽  
Medical Center ◽  
Academic Medical Center ◽  
Ultrasound Diagnosis ◽  
Normal Lung ◽  
Human Cadaver ◽  
Academic Medical ◽  
Human Cadavers ◽  
Human Cadaver Model

Objectives. To assess a human cadaver model for training emergency medicine residents in the ultrasound diagnosis of pneumothorax.Methods. Single-blinded observational study using a human cadaveric model at an academic medical center. Three lightly embalmed cadavers were used to create three “normal lungs” and three lungs modeling a “pneumothorax.” The residents were blinded to the side and number of pneumothoraces, as well as to each other’s findings. Each resident performed an ultrasound examination on all six lung models during ventilation of cadavers. They were evaluated on their ability to identify the presence or absence of the sliding-lung sign and seashore sign.Results. A total of 84 ultrasound examinations (42-“normal lung,” 42-“pneumothorax”) were performed. A sliding-lung sign was accurately identified in 39 scans, and the seashore sign was accurately identified in 34 scans. The sensitivity and specificity for the sliding-lung sign were 93% (95% CI, 85–100%) and 90% (95% CI, 81–99%), respectively. The sensitivity and specificity for the seashore sign were 80% (95% CI, 68–92%) and 83% (95% CI, 72–94%), respectively.Conclusions. Lightly embalmed human cadavers may provide an excellent model for mimicking the sonographic appearance of pneumothorax.

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.

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 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 Giving Your EHR a Checkup after COVID-19: A Practical Framework for Reviewing Clinical Decision Support in Light of the Telemedicine Expansion (Preprint)

2020 ◽  
Author(s):  
Jonah Feldman ◽  
Adam Szerencsy ◽  
Devin Mann ◽  
Jonathan Austrian ◽  
Ulka Kothari ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Data ◽  
Chronic Care ◽  
Medical Center ◽  
Academic Medical Center ◽  
Clinical Decision ◽  
Rapid Expansion ◽  
Office Visits ◽  
Academic Medical

BACKGROUND The transformation of healthcare during COVID-19 with the rapid expansion of telemedicine visits presents new challenges to chronic care and preventive health providers. Clinical decision support (CDS) is critically important to chronic care providers, and CDS malfunction is common during times of change. It is essential to regularly re-assess an organization's ambulatory CDS program to maintain care quality. This is especially true after an immense change, like the COVID-19 telemedicine expansion. OBJECTIVE Our objective is to re-assess the ambulatory CDS program at a large academic medical center in light of telemedicine's expansion in response to COVID-19. METHODS Our clinical informatics team devised a practical framework for an intra-pandemic ambulatory CDS assessment focused on the impact of the telemedicine expansion. This assessment began with a quantitative analysis comparing CDS alert performance in the context of in-person and telemedicine visits. Board-certified physician informaticists then completed a formal workflow review of alerts with inferior performance in telemedicine visits. Informaticists then reported on themes and optimization opportunities through the existing CDS governance structure. RESULTS Our assessment revealed that 10 of our top 40 alerts by volume were not firing as expected in telemedicine visits. In 3 out of the top 5 alerts, providers were significantly less likely to take action in telemedicine when compared to office visits. Cumulatively, alerts in telemedicine encounters had an action taken rate of 5.3% (3,257/64,938) compared to 8.3% (19,427/233,636) for office visits. Observations from a clinical informaticist workflow review included: (1) Telemedicine visits have different workflows than office visits. Some alerts developed for the office were not appearing at the optimal time in the telemedicine workflow. (2) Missing clinical data is a common reason for decreased alert firing seen in telemedicine visits. (3) Remote patient monitoring and patient-reported clinical data entered through the portal could replace data collection usually completed in the office by an MA or RN. CONCLUSIONS Conclusions: In a large academic medical center at the pandemic epicenter, an intra-pandemic ambulatory CDS assessment revealed clinically significant CDS malfunctions that highlight the importance of re-assessing ambulatory CDS performance after the telemedicine expansion. CLINICALTRIAL

scholarly journals iCONCUR: informed consent for clinical data and bio-sample use for research

2016 ◽  
Vol 24 (2) ◽  
pp. 380-387 ◽  
Author(s):  
Hyeoneui Kim ◽  
Elizabeth Bell ◽  
Jihoon Kim ◽  
Amy Sitapati ◽  
Joe Ramsdell ◽  
...  
Keyword(s):  
Informed Consent ◽  
Clinical Data ◽  
Patient Preferences ◽  
Medical Center ◽  
Academic Medical Center ◽  
Electronic Health Record Data ◽  
Web Based ◽  
For Profit ◽  
Academic Medical ◽  
Electronic Health

Background: Implementation of patient preferences for use of electronic health records for research has been traditionally limited to identifiable data. Tiered e-consent for use of de-identified data has traditionally been deemed unnecessary or impractical for implementation in clinical settings. Methods: We developed a web-based tiered informed consent tool called informed consent for clinical data and bio-sample use for research (iCONCUR) that honors granular patient preferences for use of electronic health record data in research. We piloted this tool in 4 outpatient clinics of an academic medical center. Results: Of patients offered access to iCONCUR, 394 agreed to participate in this study, among whom 126 patients accessed the website to modify their records according to data category and data recipient. The majority consented to share most of their data and specimens with researchers. Willingness to share was greater among participants from an Human Immunodeficiency Virus (HIV) clinic than those from internal medicine clinics. The number of items declined was higher for for-profit institution recipients. Overall, participants were most willing to share demographics and body measurements and least willing to share family history and financial data. Participants indicated that having granular choices for data sharing was appropriate, and that they liked being informed about who was using their data for what purposes, as well as about outcomes of the research. Conclusion: This study suggests that a tiered electronic informed consent system is a workable solution that respects patient preferences, increases satisfaction, and does not significantly affect participation in research.

Gender differences in career progress and satisfaction in an academic medical center

2002 ◽  
Vol 2 (3) ◽  
pp. 95-104 ◽  
Author(s):  
JoAnn Manson ◽  
Beverly Rockhill ◽  
Margery Resnick ◽  
Eleanor Shore ◽  
Carol Nadelson ◽  
...  
Keyword(s):  
Gender Differences ◽  
Medical Center ◽  
Academic Medical Center ◽  
Academic Medical ◽  
Career Progress
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