EHRs boost vaccine efficiency

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Electronic health records can help fight vaccine-preventable diseases by automating immunization data, according to research recently published in the journal Applied Clinical Informatics.

Researchers from the Columbia University School of Nursing found that this data also could provide quicker and more cohesive community data to public health agencies. Automated reporting also reduced lag time, which has always been associated with immunization reporting.

The study analyzed 1.7 million records submitted by 217 primary care practices to the New York Citywide Immunizations Registry between January 2007 and June 2011, before and after EHR reporting was possible. It examined differences in records submitted by day, lag time and eligibility of getting the vaccine.

"The efficiency offered by automation has significant implications for managing public health, whether it is by informing a local physician on the health of an individual or informing policymakers on health trends within a whole community," lead researcher and CU Nursing professor Jacqueline Merrill, said in an announcement. "For example, EHRs greatly enhance our ability to help at-risk populations for whom up-to-date immunizations are critical, such as children, immunosuppressed individuals, or the chronically ill. 

"Before automated registries," she added, "reporting was less structured and data submittal was less consistent."

Tracking immunizations has been difficult, despite the fact that health officials in the U.S. recommend vaccinating against 17 vaccine-preventable diseases.

EHRs have recently also been shown to be able to slow increases in outpatient costs. A study from the University of Michigan showed that on average, outpatient care saved $5.14 per month compared to not using EHRs. It has been acknowledged that while EHRs have the potential to reduce healthcare costs and improve outcomes, the systems do not do so automatically.

To learn more:
- read the announcement from Columbia University
- read the study in Applied Clinical Informatics

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