infection control & hospital epidemiology october 2017, vol. 38, no. 10 original article
Utilization of Electronic Health Record Events to Conduct a Tuberculosis Contact Investigation in a High-Risk Oncology Unit
Shauna C. Usiak, MPH, CIC;1,a Fabian A. Romero, MD;1,a Patrice Schwegman, BS;2 Violet Fitzpatrick, RN, COHN;3 MaryAnn Connor, MSN, RN-BC, CPHIMS;4 Janet Eagan, RN, MPH, CIC;1 Arthur E. Brown, MD, MACP, FIDSA;3 Mini Kamboj, MD, FIDSA1
objective. To describe the utilization of electronic medical data resources, including health records and nursing scheduling resources, to conduct a tuberculosis (TB) exposure investigation in a high-risk oncology unit.
setting. A 42-bed inpatient unit with a mix of surgical and medical patients at a large tertiary-care cancer center in New York City. participants. High-risk subjects and coworkers exposed to a healthcare worker (HCW) with cavitary smear positive lung TB.
results. During the 3-month exposure period, 270 patients were admitted to the unit; 137 of these (50.7%) received direct care from the index case HCW. Host immune status and intensity of exposure were used to establish criteria for postexposure testing, and 63 patients (45%) met these criteria for first-tier postexposure testing. No cases of active TB occurred. Among coworkers, 146 had significant exposure (ie,>8 hours cumulative). In the 22-month follow-up period after the exposure, no purified protein derivative or interferon gamma release assay conversions or active cases of TB occurred among exposed HCWs or patients.
conclusions. Electronic medical records and employee scheduling systems are useful resources to conduct otherwise labor-intensive contact investigations. Despite the high-risk features of our index case, a highly vulnerable immunocompromised patient population, and extended proximity to coworkers, we did not find any evidence of transmission of active or latent tuberculosis infection among exposed individuals.
Infect Control Hosp Epidemiol 2017;38:1235–1239
Contact investigations for tuberculosis (TB) can be onerous and resource intensive. Most healthcare-associated investiga- tions involve tracking and evaluation of contacts with a source patient diagnosed with active infection.1,2 Although less com- mon, transmission of TB after exposure to a healthcare worker (HCW) with unrecognized TB has also been reported.3–5 The Centers for Disease Control and Prevention (CDC) recom- mend periodic testing of HCWs as part of TB control efforts for timely diagnosis and prevention of TB spread in healthcare settings.6 In 2014, 585 cases of TB were diagnosed in New York City
with an incidence rate of 7.2 cases per 100,000 persons. Among them, 24 individuals (4%) were healthcare workers.7 It is well established that the risk of TB among HCWs is higher than that of the general population.8 Transmission of Mycobacterium tuberculosis (MTB) between HCWs and from HCW to patients has been described previously, especially in neonatal intensive care units and newborn nurseries. In several of these
reports, exposure occurred in high-risk settings; secondary cases were observed after low-intensity exposure or short exposure times.9–11 Based on studies among contacts withHIV,12 and the higher-
than-average risk of TB reactivation with certain cancers,13–15 persons undergoing oncologic treatment are considered to be at a greater risk for progressing to active disease after exposure to a contagious case of MTB. Furthermore, investigations in these situations can be especially challenging due to the unreliable performance of the tuberculin skin test (TST) or newer- generation assays in detecting recent or past TB infection.16,17 In this report, we describe the utilization of electronic
medical data resources to conduct a TB contact investigation. The source case was an HCW, and the exposure setting was a high-risk oncology unit at a large tertiary-care cancer center. We summarize the strategy used to generate a contact list, risk stratification, and implementation of a differential testing approach among patients and HCWs.
Affiliations: 1. Department of Medicine, Division of Infection Control, Memorial Sloan Kettering Cancer Center, New York, New York; 2. Health Informatics Department, Memorial Sloan Kettering Cancer Center, New York, New York; 3. Employee Health & Wellness Services, Memorial Sloan Kettering Cancer Center,
New York, New York; 4. Department of Nursing, Nursing Informatics Division,Memorial Sloan Kettering Cancer Center, New York, New York. aAuthors with equal contribution. © 2017 by The Society for Healthcare Epidemiology of America. All rights reserved. 0899-823X/2017/3810-0014. DOI: 10.1017/ice.2017.165
Received March 2, 2017; accepted July 5, 2017; electronically published August 10, 2017
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