Maryland Electronic System Provides Early H1N1 Detection

Evan Sweeney, for HealthLeaders Media , November 4, 2009

When H1N1 outbreaks were first encountered in April, the Maryland Department of Health was one of the first to notice a trend in flu-like illnesses.

The state had been on a mission to achieve 100% hospital compliance by June 30, 2009, within the state-run Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE). In December 2008, 17 hospitals were on board, and by June 1, all 46 had joined, making Maryland the first state with 100% compliance.

So when alerts began showing up in the spring for outbreaks of flu-like illnesses, some employees at the state department thought the system was broken, says Fran Phillips, deputy secretary for public health at the Maryland Department of Health and Mental Hygiene in Baltimore.

"For a while, we honestly thought we had some kind of data interference or it was some sort of programming error, but then we linked that to some of the other data sources we had and we realized we were seeing people who were at the leading edge of what later came to be positive lab tests of H1N1," Phillips says.

By June, ESSENCE tracked the virus in all 46 hospitals throughout the state and has continued to track the H1N1 virus as flu season hit this fall.

"We're watching now for the first time how this virus is going to behave in a large population in a flu season," Phillips says. "That's why everyone is looking at how the emergency room volume rates relate to the severity of the individuals admitted to the hospital, either in regular medical beds or ICU beds. It's a really important way to determine how moderate or severe this illness will be."

ESSENCE delivers a very simple and very broad set of data to the state department of health because it only sorts cases based on the patient's chief complaint. Data from every hospital is collected every day and batched at midnight, which staff members at the health department receive each morning. Two dedicated epidemiologists comb through the data and look for correlations or irregularities.

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