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Online J Public Health InformOnline J Public Health InformOJPHIOnline Journal of Public Health Informatics1947-2579University of Illinois at Chicago Library  ojphi-10-e6510.5210/ojphi.v10i1.8549ISDS 2018 Conference AbstractsUsing a One Health Approach to Build an Integrated Surveillance Data
System Clifford Wayne *Department of Health, Washington State, Olympia,
WA, USA* Wayne Clifford E-mail: wayne.clifford@doh.wa.gov30 5 2018 2018 10 1 e65ISDS Annual Conference Proceedings 2018. This is an Open Access
article distributed under the terms of the Creative Commons
Attribution-Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all
non-commercial use, distribution, and reproduction in any medium, provided the
original work is properly cited.Keywords 
One Healthsurveillance datainformaticsDatabase
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Objective
Integrate and streamline the collection and analysis of environmental, veterinary,
and vector zoonotic data using a One Health approach to data system development.

Introduction
Environmental Public Health Zoonotic Disease surveillance includes veternary,
environmental, and vector data. Surveillance systems within each sector may appear
disparate from each other, although they are actually complimentaly and closely
allied. Consolidating and integrating data in to one application can be challenging,
but there are commonalities shared by all. The goal of the One Health Integrated
Data System is to standardize data collection, streamline data entry, and integrate
these sectors in to one application.

Methods
Data Assessment. An assessment of each surveillance function was carried
out to evaluate data types and needs. Identify Commonalities. Common
data was identified across each of the surveillance areas. Identify Unique
Data. Data unique to specific surveillance efforts was identified.
Build Data Structure. A back-end data structure was developed that
reflected the data needs from each surveillance area. Build Data Entry
Interfaces. Data entry interfaces were developed to meet the needs of
each surveillance area. Build Data QC. Procedures were developed that
run several quality control checks on the data. Build Data Eports. To
allow users to carry out more extensive analysis of data, customized data exports
were built.

Results
This data integration project resulted in: 

Reduced time spent entering and
managing data 

 Improved data entry error rates


Increased visibility
through automated program metrics 

Improved access to data from data
users

Conclusions
Integrating data and building a data system that reflects the diversity of
environmental, veterinary, and vector surveillance data is doable using
off-the-shelf database tools. The process of integrating data and building the data
structure results in a more intimate understanding of the data revealing
opportunities for improving data quality.

Acknowledgments
Zoonotic Disease Program staff at the Washington State Department of Health.