Rachel M Cunningham1, Leila C Sahni, G Brady Kerr, Laura L King, Nathan A Bunker, Julie A Boom. 1. Rachel 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.
Abstract
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.
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.
Authors: Jason M Glanz; Komal J Narwaney; Sophia R Newcomer; Matthew F Daley; Simon J Hambidge; Ali Rowhani-Rahbar; Grace M Lee; Jennifer C Nelson; Allison L Naleway; James D Nordin; Marlene M Lugg; Eric S Weintraub Journal: JAMA Pediatr Date: 2013-11 Impact factor: 16.193
Authors: Fangjun Zhou; Abigail Shefer; Jay Wenger; Mark Messonnier; Li Yan Wang; Adriana Lopez; Matthew Moore; Trudy V Murphy; Margaret Cortese; Lance Rodewald Journal: Pediatrics Date: 2014-03-03 Impact factor: 7.124