The tragic case of Thomas Eric Duncan represents a failure of communication with consequences that extend well beyond the current Ebola crisis. When Mr. Duncan first presented at Texas Health Presbyterian Hospital in Dallas, his recent travel history from Liberia was reportedly ascertained and entered into the hospital’s electronic health record (EHR) system. Somehow, this critical piece of information never registered with the physician who diagnosed Mr. Duncan, and in the absence of this vital contextual framework, the list of symptoms was misinterpreted and did not seem to warrant hospitalization. Mr. Duncan was then sent home in his highly contagious state, potentially sparking a chain of infections that could have been completely avoided.
The hospital initially blamed the EHR interface for this oversight, only to retract the statement. Yet, the role of EHRs in either exacerbating or helping to contain the spread of Ebola in the United States was formally recognized on Oct. 17 by an ONC/CDC initiative to use EHRs in Ebola screening. Regardless of how the key data point was missed in Dallas, what happened there was a high-stakes version of a common problem in the U.S. health care system: the failure to connect data and story. Mr. Duncan’s biomedical measurements, those nuggets of data elicited by and easily slotted into the drop-down menus of typical EHR interfaces, were captured and transmitted to the medical team. But his narrative, the story of helping to carry a young woman dying of Ebola before travelling to the United States, was left out. This kind of social information about the environmental, root causes of disease is often hard to quantify. It fits poorly into computational ontologies. And so, even when it is on a checklist, it can get left out.
Over a decade ago, Dr. Vimla Patel and her colleagues argued in the Journal of Biomedical Informatics that doctors and patients use different conceptual models to explain sickness and health. Doctors, they argued, are trained to see the patient through a disease model that emphasizes pathophysiology. In contrast, patients understand their experience through an illness model that attends to the ways that being sick disrupts their daily lives. Not surprisingly, disease-model data is privileged in most health care documentation, and consequently, in most health care delivery. With the growing use of EHRs in clinical settings, Patel argued, essential information gets left out of the medical record. Mr. Duncan’s case exemplifies the devastating consequences.
As the nation’s health systems move into phase 2 of health information technology reform, clinicians will be required to demonstrate “meaningful use” of their government-subsidized EHR systems. At the same time, the Affordable Care Act is moving medicine from a procedure-based reimbursement model to one that is outcome-based. Both of these policies aim to create more patient-centered care. One of the hallmarks of patient-centered care is shared decision-making, a process that deliberately creates space for the patient’s illness experience to dialogue with the clinician’s disease model. The missteps in Mr. Duncan’s treatment show what can happen in the absence of patient-centered care. The U.S. health care system is in the grips of big data fever, but Ebola in Dallas should serve as a grave reminder that data without context is not only meaningless, it can be deadly. It’s time to bring patient stories back into the medical record.
Kirsten Ostherr is a professor of English, Rice University, Houston, TX.
