Rx for Ebola: Protect the Perimeter with Decision Support and Surveillance

A man walks into an emergency room with a globally notorious febrile illness wanted for mass killings in other countries.  Instead of being diagnosed and treated, he is released back into the community, continuing to expose health workers and community members without warning.   While this may sound like the September 2014 Ebola virus fumble in Dallas, it was also the scenario that drove the SARS epidemic in 2002-3 when, as today in Africa, health care facilities were a major node of transmission.

Back then, a small cadre of techies and local public health workers developed a scalable process of perimeter screening at emergency departments that fed into a public health surveillance system (the SARS Surveillance Project).   Front line health care workers welcomed a simple decision tool to distinguish routine fevers from possible SARS, allowing them to initiate infection control to protect themselves and their patients.  Health departments received immediate notification of suspect cases and daily trends of respiratory febrile illness.   In a matter of days the system was operational in Milwaukee, and within a few weeks across parts of Ohio, Colorado and Texas too.

The system might be considered laughably simple today (yes, it involved paper, pencil and arithmetic).  It was slapped together with tools at hand and without federal funding.  Nevertheless it scaled far faster than the anticipated SARS epidemic.  (We never found a SARS case, nor were there cases to find in our jurisdictions.)  The Dallas experience proves that a similar approach is needed today.   I hope our old publication might prove useful to today’s Ebola virus fighters.

We failed to get CDC to pick up or even endorse the project.  It fell victim to the “not invented here” syndrome.  (Although we showed we could rapidly scale to EDs serving more than a quarter of the US population, the last conversation ended with “We already work with an emergency department in California, thank you very much” [emphasis mine]).*

A larger question is: are we better equipped to scale up such a system today after US$ billions of investment into health information technology?   The short-term answer is “No”, outside some local centers of excellence.    But there is little reason we couldn’t get there with a little strategic leadership and investment.

Imagine that CDC translates Ebola suspect case definitions (symptoms, signs, travel, sick contacts) into standardized HIT data elements.  Imagine these are loaded into a standards-compliant rules repository accessible to electronic health record systems (EHRs).   Imagine that EHR systems upload these rules to alert triage personnel to ask 4-6 brief questions of febrile patients.   Imagine that responses suggesting Ebola trigger immediate infection control and public health reporting.  Imagine that patients, healthcare workers and the community are protected pending definitive diagnosis.  Imagine that emergency response receives the gift of a head start on the possible emergence of a generation of new cases.

In recent years the pieces of this more automated solution have been largely completed but not assembled and applied: widespread certified EHR use; specifications for capturing most of the needed data elements; methods to distribute clinical decision support rules; specifications for electronic public health reporting.   With a focused vision and public health investment an adaptable system that combines “situational” EHR decision support with surveillance could be achieved fairly rapidly.  In the meantime, I’m told, paper, pencil and basic http are still available to replicate the 2002 approach.

 

*(In fairness it must be told I joined CDC 8 years later, and during my two years there agency budgets for the public health use of health information technology markedly shrank.  Thus I must share responsibility for the current state, despite efforts to the contrary.)