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The Texas Children's Hospital immunization forecaster: conceptualization to implementation
Rachel M Cunningham1, Leila C Sahni, G Brady Kerr
1Rachel M. Cunningham, Leila C. Sahni, G. Brady Kerr, Laura L. King, and Julie A. Boom are with the Immunization Project, Texas Children's Hospital, Houston. Nathan A. Bunker is with Dandelion Software & Research, Inc., Toquerville, UT.
Insights
Texas Children's Hospital developed a novel immunization forecasting system to improve vaccine adherence. This system, the TCH Forecaster, is now used nationally to recommend timely vaccinations.
Area of Science:
- Medical Informatics
- Public Health
- Software Engineering
Background:
- Immunization forecasting systems are crucial for managing patient vaccination histories and recommending appropriate vaccines.
- Adherence to recommended vaccination schedules is vital for public health.
- A novel system was needed to effectively operationalize complex immunization guidelines.
Purpose of the Study:
- To describe the conceptualization, development, implementation, and distribution of the Texas Children's Hospital (TCH) Forecaster.
- To create a robust tool for evaluating and recommending patient vaccinations based on established guidelines.
Main Methods:
- An expert team at TCH, including pediatricians, nurses, and software engineers, developed the TCH Forecaster starting in 2007.
- A rule-based system was created, incorporating vaccine recommendations, age/interval minimums, and contraindications.
- The software was designed, coded, populated with data, integrated, and rigorously tested.
Main Results:
- Fifteen vaccine tables were created, covering 79 dose states and 84 vaccine types for the U.S. immunization schedule.
- The TCH Forecaster was successfully implemented within TCH, the Indian Health Service, and the Virginia Department of Health.
- The TCH Forecast Tester is now utilized nationwide.
Conclusions:
- Immunization forecasting systems have the potential to enhance adherence to vaccine recommendations.
- Further efforts are needed to promote healthcare provider adoption and evaluate the impact of these systems on patient care.
Objectives:
Immunization forecasting systems evaluate patient vaccination histories and recommend the dates and vaccines that should be administered. We described the conceptualization, development, implementation, and distribution of a novel immunization forecaster, the Texas Children's Hospital (TCH) Forecaster.
Methods:
In 2007, TCH convened an internal expert team that included a pediatrician, immunization nurse, software engineer, and immunization subject matter experts to develop the TCH Forecaster. Our team developed the design of the model, wrote the software, populated the Excel tables, integrated the software, and tested the Forecaster. We created a table of rules that contained each vaccine's recommendations, minimum ages and intervals, and contraindications, which served as the basis for the TCH Forecaster.
Results:
We created 15 vaccine tables that incorporated 79 unique dose states and 84 vaccine types to operationalize the entire United States recommended immunization schedule. The TCH Forecaster was implemented throughout the TCH system, the Indian Health Service, and the Virginia Department of Health. The TCH Forecast Tester is currently being used nationally.
Conclusions:
Immunization forecasting systems might positively affect adherence to vaccine recommendations. Efforts to support health care provider utilization of immunization forecasting systems and to evaluate their impact on patient care are needed.
