scholarly journals Identification of Colonized Patients During an Outbreak of Candida auris Using a Regional Health Information Exchange

2020 ◽  
Vol 41 (S1) ◽  
pp. s255-s256
Author(s):  
Richard Brooks ◽  
Elisabeth Vaeth ◽  
Heather Saunders ◽  
Tim Blood ◽  
Brittany Grace ◽  
...  
Keyword(s):  
Health Information ◽  
Acute Care ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Acute Care Hospitals ◽  
Regional Health ◽  
Candida Auris ◽  
Notification System ◽  
Healthcare Facilities ◽  
Care Facilities

Background: In June 2019, the Maryland Department of Health (MDH) was notified of a hospitalized patient with Candida auris bloodstream infection. The MDH initiated a contact investigation to identify additional patients with C. auris colonization. Many of the contacts had been discharged home from the hospital and were therefore not available for screening. Healthcare facilities in Maryland, Virginia, and Washington, DC, submit patient data to a regional health information exchange (HIE) called the Chesapeake Regional Information System for our Patients (CRISP). CRISP includes a notification system that alerts providers when flagged patients have healthcare encounters. We aimed to use this system to identify discharged C. auris contacts on their next inpatient encounter to rapidly screen them and to detect new cases. Methods:C. auris contacts were defined as patients located on an inpatient unit on the same day, receiving wound care from the same team, or having a procedure in the same operating room on the same day as the index patient or any patients subsequently identified as having C. auris infection or colonization detected either during the normal course of clinical care or through screening. Contacts who remained hospitalized were screened during inpatient point prevalence surveys (PPSs). Contacts discharged to postacute-care facilities were screened by facility staff. Contacts who had been discharged home were flagged in CRISP, and MDH staff received CRISP encounter alerts when these patients were readmitted. MDH staff then contacted the admitting facilities to recommend screening for C. auris. Axilla and groin swabs were collected and tested by rt-PCR at the Mid-Atlantic Regional Antibiotic Resistance Laboratory Network laboratory. Results: As of October 8, 2019, 4,017 contacts were identified. Among these, 936 (23%) contacts at 56 healthcare facilities (33 acute-care hospitals and 23 postacute-care facilities) were screened for C. auris, and 10 patients with C. auris colonization were identified (1.1% of contacts who underwent C. auris screening). Of these, 6 (60%) were identified through CRISP notification and 4 (40%) were identified by PPSs conducted in acute-care hospitals. Conclusions: In this ongoing C. auris outbreak, a large proportion of colonized patients was identified using an electronic encounter notification system within a regional HIE. This approach was effective for identifying opportunities to screen contacts at their next healthcare encounter and can augment other means of case detection, like PPSs. HIEs should incorporate mechanisms to facilitate contact tracing for public health investigations.Funding: NoneDisclosures: None

scholarly journals Public Health Oversight of Interfacility Transfers During a Candida auris Outbreak—Orange County, California, 2019

2020 ◽  
Vol 41 (S1) ◽  
pp. s76-s77
Author(s):  
Kathleen O'Donnell ◽  
Ellora Karmarkar ◽  
Brendan R Jackson ◽  
Erin Epson ◽  
Matthew Zahn
Keyword(s):  
Public Health ◽  
Acute Care ◽  
Orange County ◽  
Acute Care Hospitals ◽  
Nursing Facilities ◽  
Candida Auris ◽  
Retrospective Case ◽  
California Department ◽  
Healthcare Facilities ◽  
Contact Precautions

Background: In February 2019, the Orange County Health Care Agency (OCHCA) identified an outbreak of Candida auris, an emerging fungus that spreads rapidly in healthcare facilities. Patients in long-term acute-care hospitals (LTACHs) and skilled nursing facilities that provide ventilator care (vSNFs) are at highest risk for C. auris colonization. With assistance from the California Department of Public Health and the Centers for Disease Control and Prevention, OCHCA instituted enhanced surveillance, communication, and screening processes for patients colonized with or exposed to C. auris. Method: OCHCA implemented enhanced surveillance by conducting point-prevalence surveys (PPSs) at all 3 LTACHs and all 14 vSNFs in the county. Colonized patients were identified through axilla/groin skin swabbing with C. auris detected by PCR and/or culture. In facilities where >1 C. auris colonized patient was found, PPSs were repeated every 2 weeks to identify ongoing transmission. Retrospective case finding was instituted at 2 LTACHs with a high burden of colonized patients; OCHCA contacted patients discharged after January 1, 2019, and offered C. auris screening. OCHCA tracked the admission or discharge of all colonized patients, and facilities with ongoing transmission were required to report transfers of any patient, regardless of colonization status. OCHCA tracked all patients discharged from facilities with ongoing transmission to ensure that accepting facilities conducted admission surveillance testing of exposed patients and implemented appropriate environmental and contact precautions. Result: From February–October 2019, 192 colonized patients were identified. All 3 LTACHs and 6 of 14 VSNFs had at least 1 C. auris–colonized patient identified on initial PPS, and 2 facilities had ongoing transmission identified on serial PPS. OCHCA followed 96 colonized patients transferred a total of 230 times (an average of 2.4 transfers per patient) (Fig. 1) and 677 exposed patients discharged from facilities with ongoing transmission (Fig. 2). Admission screening of 252 exposed patients on transfer identified 13 (5.2%) C. auris–colonized patients. As of November 1, 2019, these 13 patients were admitted 21 times to a total of 6 acute-care hospitals, 2 LTACHs, and 3 vSNFs. Transferring facilities did not consistently communicate the colonized patient’s status and the requirements for isolation and testing of exposed patients. Conclusion: OCHCA oversight of interfacility transfer, though labor-intensive, improved identification of patients colonized with C. auris and implementation of appropriate environmental and contact precautions, reducing the risk of transmission in receiving healthcare facilities.Funding: NoneDisclosures: None

Consumer Support for Health Information Exchange and Personal Health Records: A Regional Health Information Organization Survey

2010 ◽  
Vol 36 (3) ◽  
pp. 1043-1052 ◽  
Author(s):  
Vaishali N. Patel ◽  
Rina V. Dhopeshwarkar ◽  
Alison Edwards ◽  
Yolanda Barrón ◽  
Jeffrey Sparenborg ◽  
...  
Keyword(s):  
Health Information ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Personal Health Records ◽  
Information Organization ◽  
Personal Health ◽  
Regional Health ◽  
Health Records

scholarly journals 329Parsing Multi-Source Microbiology Culture Data in a Regional Health Information Exchange to Describe Patterns of Infection

2014 ◽  
Vol 1 (suppl_1) ◽  
pp. S133-S133
Author(s):  
Marc Rosenman ◽  
Kinga Szucs ◽  
S. Maria E. Finnell ◽  
Shahid Khokhar ◽  
Abel Kho
Keyword(s):  
Health Information ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Regional Health

scholarly journals Measuring the Degree of Unmatched Patient Records in a Health Information Exchange Using Exact Matching

2016 ◽  
Vol 07 (02) ◽  
pp. 330-340 ◽  
Author(s):  
John Zech ◽  
Gregg Husk ◽  
Thomas Moore ◽  
Jason Shapiro
Keyword(s):  
Social Security ◽  
Health Information ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Reference Value ◽  
P Value ◽  
Patient Records ◽  
Exact Matching ◽  
Healthcare Facilities ◽  
Significant Difference

SummaryHealth information exchange (HIE) facilitates the exchange of patient information across different healthcare organizations. To match patient records across sites, HIEs usually rely on a master patient index (MPI), a database responsible for determining which medical records at different healthcare facilities belong to the same patient. A single patient’s records may be improperly split across multiple profiles in the MPI.We investigated the how often two individuals shared the same first name, last name, and date of birth in the Social Security Death Master File (SSDMF), a US government database containing over 85 million individuals, to determine the feasibility of using exact matching as a split record detection tool. We demonstrated how a method based on exact record matching could be used to partially measure the degree of probable split patient records in the MPI of an HIE.We calculated the percentage of individuals who were uniquely identified in the SSDMF using first name, last name, and date of birth. We defined a measure consisting of the average number of unique identifiers associated with a given first name, last name, and date of birth. We calculated a reference value for this measure on a subsample of SSDMF data. We compared this measure value to data from a functioning HIE.We found that it was unlikely for two individuals to share the same first name, last name, and date of birth in a large US database including over 85 million individuals. 98.81% of individuals were uniquely identified in this dataset using only these three items. We compared the value of our measure on a subsample of Social Security data (1.00089) to that of HIE data (1.1238) and found a significant difference (t-test p-value < 0.001).This method may assist HIEs in detecting split patient records.

scholarly journals User perspectives on the usability of a regional health information exchange

2011 ◽  
Vol 18 (5) ◽  
pp. 711-716 ◽  
Author(s):  
Cynthia S Gadd ◽  
Yun-Xian Ho ◽  
Cather Marie Cala ◽  
Dana Blakemore ◽  
Qingxia Chen ◽  
...  
Keyword(s):  
Health Information ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Regional Health ◽  
User Perspectives

scholarly journals 174. Increase in Candida auris cases in New Jersey healthcare facilities during the COVID-19 pandemic — 2017–2020

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S106-S107
Author(s):  
Reed Magleby ◽  
Gabriel Innes ◽  
Diya Cherian ◽  
Jessica Arias ◽  
Jason Mehr ◽  
...  
Keyword(s):  
New Jersey ◽  
Acute Care ◽  
Acute Care Hospitals ◽  
Point Prevalence ◽  
Candida Auris ◽  
Healthcare Facilities ◽  
Clinical Specimens ◽  
Department Of Health ◽  
Percent Positivity

Abstract Background Candida auris is a fungal pathogen associated with multidrug resistance, high mortality, and healthcare transmission. Since its U.S. emergence in 2017, to March 19, 2021, 1708 clinical infections were reported nationwide, of which 235 (13.8%) were reported in New Jersey. The New Jersey Department of Health (NJDOH) maintains C. auris surveillance in healthcare facilities (HCF) such as acute care hospitals, long-term acute care hospitals (LTACHs), and skilled nursing facilities, to monitor clinical infections and patient colonization. We aimed to characterize the epidemiology of C. auris infection and colonization among HCF patients during 2017–2020. Methods HCFs report C. auris cases identified from clinical specimens and surveillance activities such as admission screenings and point prevalence surveys (PPS) to NJDOH. Cases are classified as either infection or colonization using National Notifiable Diseases Surveillance System case definitions. We analyzed cases reported during 2017–2020 to describe types of cases, facilities reporting cases, and demographics of affected patients. We analyzed PPS results to calculate percent positivity of tests from patients without previously identified infection and compared percent positivity between types of facilities. We examined quarterly trends for all variables before and after the COVID-19 pandemic peak in the second quarter of 2020. Results During 2017–2020, 614 C. auris cases identified from clinical specimens were reported to NJDOH [243 (39.6%) infection, 371 (60.4%) colonization]; of these, 139 (57.2%) and 301 (81.1%) , respectively, were identified at long-term acute care hospitals (LTACHs). PPS percent positivity was higher at LTACHs (mean 7.6%) compared with all other facility types (mean 3.6%) for 13 of 16 quarters during 2017–2020. Case reports increased 2.6-fold from the Q2 2020 peak of the COVID-19 pandemic to Q3 2020.From Q1 to Q4 2020, PPS percent positivity increased from 4.8% to 10.5%. Figure 1. Candida auris cases reported to New Jersey Department of Health, 2017–2020 Figure 2. Candida auris test percent positivity among healthcare facility patients sampled for point prevalence surveys* and total number of C. auris point prevalence tests performed, New Jersey, 2017–2020. *Excluding individuals already known to be cases Conclusion The COVID-19 pandemic may have exacerbated C. auris transmission in HCF and potential causes should be further explored. LTACHs carry a disproportionate burden of patients colonized with C. auris and should be prioritized for surveillance and containment efforts. Disclosures All Authors: No reported disclosures

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