Analyzing client denial trends in the NDI dataset: Patterns and predictive insights
Date
2024-05
Language
American English
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Abstract
This project analyzed denial patterns among clients in the HANDS in Autism® NDI Exploratory dataset. Using REDCap and Cerner data, a structured coding scheme was implemented for consistent data entry and scoring. Python was used to quantitatively analyze denial reasons across 2021–2023. The most frequent denial factors included unmet family/parent criteria and issues unrelated to autism. Statistical testing, including Chi-Square and Fisher’s exact tests, revealed no significant relationship between gender and denial reasons. The project also produced a user guide for REDCap data entry and proposed future directions, including expanding the dataset and improving data completeness through enhanced data collection practices.
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Cite As
Samala, V., Neal, T., Deodhar, A., Devarapalli, B. A., & Swiezy, N. (2024). Analyzing client denial trends in the NDI dataset: Patterns and predictive insights. Presented at the Spring 2024 Poster Session, HANDS in Autism® Interdisciplinary Training and Resource Center at Indiana University School of Medicine, Indiana University Indianapolis. †
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