Managing an Exposure: Why the EMR Is Lacking
Saskia v. Popescu
Saskia v. Popescu, PhD, MPH, MA, CIC, is a hospital epidemiologist and infection preventionist. During her work as an infection preventionist, she performed surveillance for infectious diseases, preparedness, and Ebola-response practices. She holds a doctorate in Biodefense from George Mason University where her research focuses on the role of infection prevention in facilitating global health security efforts. She is certified in Infection Control and has worked in both pediatric and adult acute care facilities.
Insight into healthcare exposures gives us a new reason to invest in surveillance tools
There’s a moment for infection preventionist (IP) epidemiologists that makes us recoil, take in a big breath, and gear up for the inevitable misery of an exposure. Exposures are 1 of the more painful tasks in infection prevention and epidemiology and have the ability to stress out even the most seasoned of IPs. When a patient visits a health care facility and there is a delay in isolation, or when a health care worker works while infected, we’re often required to act if a communicable disease is involved. From measles to pertussis and even tuberculosis, an exposure to vulnerable patients/staff could mean illness, which often mean response efforts are up against the clock.
One of the most problematic aspects of an exposure is determining who is involved—both patients and staff alike. If the source case was a patient, the staff involved in their care must be identified, and if the source case is a health care worker, then the exposure list is usually longer as it involves both the individual’s patients and colleagues. For a disease like measles, which is highly contagious and infectious, we must also account for any patients exposed in waiting areas and other public areas where the patient went without the proper isolation (this includes considering patients on the same air-handling unit) Since the incubation period is usually 10-12 days, this often leaves little time for response efforts.
One of the tools we often use to identify those involved in an exposure (for both notification and even prophylaxis purposes) is the electronic medical record (EMR) system. The EMR allows us to rapidly pull a list of staff who were involved in the care of a patient (assuming the patient was the index case)…or at least it should.
In the years I have worked in infection prevention epidemiology, I have dealt with dozens of exposures, ranging from pertussis to tuberculosis, varicella, and even measles. In every event, the expectation was that the EMR system should help make the process of tracking exposures easier. Or so I’ve been told. Unfortunately, there are several gaps within this exposure-response that should be made easier by the creation of the EMR, and yet hospitals often struggle to truly use them. A 2017 study reviewing pertussis cases during an outbreak across Midwestern states used 2 different methods to try and identify exposed staff—the EMR and a real-time location system (RTLS) worn by staff. The authors mirrored the sentiments of many within infection prevention, noting that using the EMR is challenging and misses a number of potential exposures. Of the 9 cases of pertussis evaluated, the RTLS doubled the exposure list and proved itself as a valuable addition in contact tracing. The EMR review alone identified 45 possible contacts in the 9 pertussis cases (13 health care workers were identified in the EMR alone and not by the RTLS), while the RTLS alone identified 77 contacts (45 of whom were new contacts not identified within the EMR).
The truth is that there are a lot of exposed individuals that do not chart within the EMR, such as those in food services, environmental services, volunteers, anyone assisting with the care of another HCW, etc. Use of the EMR for identified exposed persons is inherently limited, in that the systems are not designed for such practices, meaning that there needs to be substantial efforts on the backend of the programs to create more effective and sensitive data pulls. Also, with plenty of employees not documenting in the chart, this leaves considerable gaps. Often, the charting aspect of using the EMR is limited and pulling from the billing side can be more helpful. If an employee is the index case, this also limits the utility of the EMR, as the data is patient derivative, and not capable of pulling information based off an employee (ie, more than often, I’ve had to depend on their supervisor to provide their schedule).
Overall, there are a lot of gaps within the exposure process of infection prevention and, more often, we rely on the EMR. Unfortunately, this process is clunky at best and error-prone at worst, leaving many staff and patients unidentified as potential exposures. Although this may not seem like a critical problem to fix, as measles cases continue to soar in the United States, we will need a more effective, efficient, and less time-consuming tool to aid in these efforts. For many exposures, time is in short supply and reliance on inefficient tools consume precious time and risk missing exposed patients and staff.