Page 43 - Driving Public Health in the Fast Lane

Recommendation 2: INTEROPERABLE Data Systems

The public health data superhighway must be built on the foundation of interoperable data systems and
shared data standards. Many of the current challenges facing today’s public health surveillance system
are rooted in the discrepant public health data systems that cannot communicate with one another or
external, private sector health care providers. Interoperability will drive more, better, and faster public
health data.

More Data
Enhancing and improving public health surveillance requires better access to existing data sources.
Increased access can be accomplished in two ways. First, it is paramount to access the wealth of data in
EHRs. With the advancement and proliferation of EHRs, the public health and health care communities
have an opportunity to increase efficient data transfer and enhance the quality, accuracy, completeness,
and depth of the data contributed to public health surveillance. Seamless delivery of EHR data to public
health will result in high-value data to public health surveillance efforts and create several efficiencies by
reducing redundant manual request for clinical information.

Second, as the public health data superhighway is constructed, it should include electronic access to
non-traditional data sources such as medication-assisted treatment programs, pharmacies, social media,
disease registries, and prescription drug monitoring programs to supplement traditional data sources.
Automated access to non-traditional data sources combined with traditional data sources will bring
additional value and depth to public health activities.

Better Data
The paper-based methods of data collection and sharing are vulnerable to errors and mistakes.
Transcription and translation errors, duplicate entries, and incomplete information reduce the quality of
public health data. Reports can be entirely missed and never submitted, or there might be confusion about
what and how to report. Investments should be made to automate data collection from multiple sources
to reduce errors, remove the administrative burden of data collection, and increase data quality.

Additionally, efforts to standardize public health data are critical to harmonize data exchange from
multiple sources. Public health and health care data standards are a key component of the overall
interoperability of the public health data superhighway, because they allow individual data systems to
contribute compatible and comparable information to be used in the aggregate.

Faster Data
Public health surveillance is hindered by slow, manual data exchange mechanisms. As elucidated in
the case studies, paper reports stack up next to the fax machine waiting to be sent and received. Once
received, reports need to be efficiently, processed, organized, and analyzed to turn raw data into
information useful to policymakers and the public. Whether the public health department is operating
under normal conditions, or during response to a public health outbreak or emergency, paper-based
methods and manual data entry create a bottleneck in a timely public health response. To get data
faster, investments must be made to build the public health data superhighway to enable any type of
public health data to be electronically shared quickly and efficiently. By utilizing a core infrastructure,
public health can then apply enterprise-level advanced data analytics, predictive analytics, and artificial
intelligence to produce curated and precise real-time reporting from multiple data sources.

Changing from the Slow Lane to the Fast Lane 43