HAI Surveillance Enhancement within EpiCenter by Utilization of Triage Notes
AbstractObjectiveEvaluate the usage of triage note data from EpiCenter, a syndromicsurveillance system utilized by New Jersey Department of Health(NJDOH), to enhance Healthcare-Associated Infections (HAIs)surveillance for infections following a surgical procedure.IntroductionIn New Jersey, Health Monitoring Systems Inc.’s (HMS) EpiCentercollects chief complaint data for syndromic surveillance from 79 of80 emergency departments (ED). Using keyword algorithms, thesevisits are classified into syndrome categories for monitoring unusualhealth events.HAIs are infections that patients acquire while they are receivingtreatment for a health condition in a health care setting. Followingthe 2014 Ebola outbreak in West Africa, the New Jersey Departmentof Health (NJDOH) Communicable Disease Service (CDS) startedrecruiting EDs to include triage note data in addition to chiefcomplaint data to enhance surveillance capability for Ebola and otherHAIs. Research by the University of North Carolina suggests triagenote data improve the ability to detect illness of interest by fivefold1.Currently, there are three NJ EDs with triage note data in EpiCenteralong with ICD 10 codes which can be used for comparison.This pilot study will assess whether infections following a surgicalprocedure can be captured in triage note data along with ICD codes.Also, this evaluation will determine if triage note data can be usedto create HAI custom classifications for syndromic surveillance.These classifications can potentially be used by surveillanceand/or preparedness personnel and local health departments, as wellas hospitals, to better prepare for detecting and preventing HAIs thatare a significant cause of morbidity and mortality in the U.S.2MethodsThree NJ facilities with triage notes information sending toEpiCenter were included in this study. ED visits occurred from10/23/2015 to 10/29/2015 and from 2/2/2016 to 2/10/2016 in thesefacilities with available ICD 10 codes information in EpiCenter wereevaluated.This analysis focused on sepsis and post-surgery infections relatedICD 10 codes: A400, A401, A402, A403, A408, A409, A410, A411,A412, A414, A4150, A4151, A4152, A4158, A418, A419, R571,R578, R579, T811, T81.43. The keywords tested in triage notesare abdominal pain, redness, fev, fver, pyrexia, temp, elev temp,elevated temp, temp elev, hi temp, high temp, temp hi, temp10, temp10, feeling hot, feels hot, feel hot, fuo, febr, cloudy fluid, cfluid,drainage, abscess, wound, tenderness, swelling, erythema, red, pain,post surgery, fever.The sensitivity, specificity and positive predictive value (PPV)of selected keywords applied in the triage notes were evaluated bycomparing to patient’s ICD 10 codes.ResultsThere were 2757 ED visits with triage notes and ICD 10 codes from10/23/2015 to 10/29/2015 and from 2/2/2016 to 2/10/2016. Duringthese time frames, one ED visit matched with both selected keywordsand ICD codes, five matched with ICD 10 codes only, 59 matchedwith keywords only, and 2692 did not match with either keywordsor ICD 10 codes. In Table 1, it indicates that selected keywordshave a high specificity (97.9 %) but with a relatively low sensitivity(16.7 %) and PPV (1.7%).ConclusionsSelected keywords and ICD 10 codes from facilities sending triagenotes were used to evaluate the surveillance system on identifyinginfections following a surgical procedure through analysis of EDtriage note field. We also reviewed all NJ ED data during the samestudy period for other facilities not sending triage notes. It indicatedthat several key ICD codes, e.g. ICD code T81.4, infections followinga surgical procedure, have been included in many facilities. Thisanalysis will be repeated as more EDs participate in EpiCenterwith triage notes and other data fields to refine the keywords and toimprove the sensitivity and PPV.Table 1: Sensitivity, specificity and PPV calculations of selected keywordsapplied in triage notes based on the ICD 10 codes related to infectionsfollowing a surgical procedure.
How to Cite
Erdogdu, P., Tsai, S., & Hamby, T. (2017). HAI Surveillance Enhancement within EpiCenter by Utilization of Triage Notes. Online Journal of Public Health Informatics, 9(1). https://doi.org/10.5210/ojphi.v9i1.7618
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