Surveillance of Spina Bifida Across the Lifespan - Component A The purpose of the proposed project is to develop population-based surveillance of individuals of all ages with spina bifida living in the fourteen counties in New York State with active birth defects surveillance programs to estimate prevalence, mortality, and survival for all age groups. The New York State Department of Health (NYSDOH) plans to develop a new spina bifida surveillance framework comprised of cases identified using state birth defects surveillance program (NYS Birth Defects Registry) information and linked to records from clinics, hospital inpatient and outpatient data, Medicaid data, immunization data, vital records data and National Death Index data. NYSDOH expects to achieve the following outcomes by the end of the project period: 1. An increased availability of SB data to inform clinical care and public health materials, programs, and interventions 2. An improved understanding among public health and clinical researchers and providers of SB prevalence, age-specific mortality, and cause of death 3. An improved understanding among public health and clinical researchers and providers of healthcare use and sources of care for individuals with SB 4. Improved accuracy or efficiency in SB case-finding, reporting, or outcome prediction 5. Improved SB data quality and availability of data for action Component B The purpose of the proposed project is to develop machine learning algorithms trained to differentiate true spina bifida (SB) cases from individuals with SB codes without SB in the New York Birth Defects Registry. We propose a collaboration between staff at the New York State Department of Health (NYSDOH) and staff at the University at Albany-State University of New York (UA) to train and validate the algorithms using 2019-2023 information from the Birth Defects Registry, active surveillance programs, vital records and the Statewide Planning and Research Cooperative System (SPARCS) for counties in New York State with active surveillance programs. We will then test the algorithms for cases identified in demographically similar counties adjacent to the active surveillance region for the same time period. The NYSDOH and UA expects to achieve the following outcomes by the end of the project period: 1. Improved accuracy or efficiency in SB case-finding, reporting, or outcome prediction 2. Improved SB data quality and availability of data for action
