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San Diego BMI surveillance: Lessons learned in developing new electronic surveillance using existing systems
Objective To highlight coordination of technical development with policies, agreements, and quality assurance (QA) required for implementation of a BMI surveillance system based on data collected in healthcare settings.
Methods This project required parallel development of technical infrastructure, policies, QA and analytic methods. A Health Officer Order was issued to facilitate data collection and data use agreements were established to address privacy concerns. Registry staff developed new QA tools to assess clinic policies as well as BMI measurement and data entry. New technical components included modifying direct interfaces and data uploads.
Results By July 2012, BMI data transfer capacity was in place for 12 sites. The sites included six community clinic networks, two large medical systems, and four private medical groups. By mid-2012, the SDIR contained 2.3 million patient records, with newly submitted BMI data on over 592,000 patients. The initial system overrepresented the low-income population, yet provided an early assessment of BMI differences among population groups.
Discussion Electronic disease surveillance has successfully modernized older paper-based reporting systems, but for these systems, state and local regulations and reporting requirements predated the development of new technical infrastructure. While existing systems provide an attractive solution for health departments to maximize infrastructure, rapid implementation can outpace development of regulations and policies to insure that data collection follows regulations and has sufficient rigor to be useful in community surveillance.
Learning Areas:
Communication and informaticsLearning Objectives:
Discuss the importance of coordinated development when modifying existing surveillance capabilities for new diseases or conditions.
Describe policies, agreements, QA tools, and analytic methods developed for BMI surveillance.
Identify key factors for implementation of BMI Surveillance.
Keyword(s): Obesity, Health Information Systems
Qualified on the content I am responsible for because: I am an epidemiologist and the lead evaluator for two large fedral grants on obesity prevention through plicy, systems, and environmental change. I worked in collaboration with the immunization registry manager to implement the BMI surveillance system described in this abstract.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.