Algorithm cuts time spent on COVID-19 patient contact tracing by 60%
Contact tracing has become a key strategy in combating the novel coronavirus – particularly with regard to asymptomatic people who may not know they've been exposed.
However, trying to track down those with whom a COVID-19-positive patient has been in contact can be both time- and labor-intensive. A new case report in the Journal of the American Medical Informatics Association shows how one hospital in Singapore used an algorithm to improve the efficiency of the contact-tracing process.
"Prior to the establishment of the algorithm, contact tracing teams comprising six members each would spend up to 10 hours to complete contact tracing for five new COVID-19 patients," wrote the researchers from Changi General Hospital.
"With the augmentation by the algorithm, we observed ≥60% savings in overall manhours needed for contact tracing when there were five and above daily new cases through a time-motion study and Monte-Carlo simulation," they continued.
WHY IT MATTERS
The hospital's contact tracing process, as described by the researchers, involved mapping all activities of the patient for the period from 14 days before the onset of their symptoms, as well as those of the healthcare workers who attended to the patient and other patients in close contact with them.
The hospital then shared that information with the Ministry of Health within 24 hours to ensure timely follow-up.
In order to identify exposed healthcare workers and neighboring patients more efficiently, the researchers developed an algorithm using data from five separate informatics systems used in the hospital's day-to-day operations.
Those systems were the clinical electronic health records system; the inpatient module recording patient movements from registration to inpatient admission to discharge; the real-time locating-system, tracking patient movements through a radio-frequency identification tag; the outpatient appointment system; and the radiology information system.
According to the researchers, these five systems are among those that feed into the enterprise analytic platform SingHealth-IHiS Electronic Health Intelligence System, or eHints.
"The algorithm was scripted to extract the information required in a sequential manner from the eHints repository data derived from these five source systems to meet the contact tracing requirement," they explained.
After the algorithm generated a customized contact-tracing report for each COVID-19 patient based on the patient's presence in the various areas and time period, the contact-tracing team would scope the contacts to be interviewed.
"The model demonstrated significant time savings as well as manpower to complete the contact tracing process, especially for days with higher volume of new COVID-19 patients detected," wrote the researchers.
THE LARGER TREND
In the United States, companies have developed contact-tracing software to try and augment the process of finding those who may have been exposed to novel coronavirus patients.
Apple and Google's contact tracing API went live in May. The technology was aimed at helping public health agencies deploy apps to notify individuals of potential COVID-19 exposure.
But privacy concerns and public doubt have slowed mass adoption of the software, with 71% of Americans in one survey saying they wouldn't use the apps.
ON THE RECORD
"In the COVID-19 pandemic, expedient identification of individuals with significant exposure to COVID-19 patients is a key strategy to break the chain of transmission and flatten the epidemiology curve," wrote the Changi Hospital researchers.
"With the increasing number of new cases diagnosed daily, the capacity for timely contact tracing would have to be met by increasing staff numbers to perform interviews of the COVID-19 patient and the contacts. The algorithm’s value-add was the rapid and comprehensive identification of the COVID-19 patient’s activity as well as individuals at risk – [healthcare workers] and other patients, to be interviewed. The contact tracing staff could then focus on the interviews and risk assessment of the contacts," they continued.
Kat Jercich is senior editor of Healthcare IT News.
Healthcare IT News is a HIMSS Media publication.