Abstract

Abstract Background The prevalence of missed opportunities for immunization among children is estimated to be 32.2%. The introduction of new vaccines in EPI schedule and lack of training of frontline health workers (FHWs) on the guidelines for number and spacing of doses and manual construction of vaccine schedules based on a child's age deteriorates efficiencies of FHWs, especially in forecasting catch-up schedules. We have designed and tested the validity of an innovative Decision Support System Application Programming Interface (DSS-API) which will automatically generate an age-appropriate immunization schedule for a child. Methods Using a multi-country setting approach, DSS was deployed in six immunization facilities of Pakistan and Bangladesh between July 2019 to April 2020. Details of all visiting children were recorded in database. Information on date of birth and past immunization history was used by the DSS-API to determine an individualized age-appropriate immunization schedule. These schedules were compared to the gold standard's outputs calculated by an immunization expert. Results A total of 6,241 vaccination events were recorded from all the sites. Using area under the curve, the calculated sensitivity of DSS to determine age-appropriate immunization schedule was found between 99-100% for the individual EPI vaccines, while the specificity of the DSS algorithm was found between 98-100%. Conclusions DSS is a feasible feature that can be incorporated in Digital Immunization Registries to accurately schedule routine and catch-up immunizations and can effectively reduce Missed Opportunities for Immunizations by assisting FHWs through automatic construction of immunization schedules. Key messages DSS-API is a unique application that can improve process efficiencies of frontline health workers by automatic generation of accurate age-appropriate catch-up vaccine schedules. DSS has the potential to reduce missed opportunities for immunization (MOI) and improve immunization coverage and timeliness among children aged under 2 years.

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