Browsing by Subject "Behavioral Health Outcomes"

Now showing 1 - 2 of 2
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    Assessing Clinical Global Impressions Severity Scores in Adults with Autism Across Counties: A Coordinated Care Study from Preadmission to Post-Discharge
    (2023-08-04) Enugu, Hari Priya Reddy; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This practicum, conducted at HANDS in Autism® in collaboration with the Indiana NeuroDiagnostic Institute (NDI), aimed to examine changes in behavioral severity among adults with Autism Spectrum Disorder (ASD) using the Clinical Global Impressions (CGI) Severity Scale. Data were collected from REDCap across multiple stages of care, including preadmission, 7-day, 1-month, 3-month, 6-month, 9-month, and 12-month post-discharge intervals. Severity scores were categorized by county and visualized using Excel, Python, and Tableau to assess behavioral change trends. Results showed a clear reduction in severity from preadmission (primarily scores of 6–7) to post-discharge (with most scores at 5 or below), suggesting improved outcomes following inpatient intervention. This analysis supports the value of longitudinal tracking using standardized tools like CGI to inform treatment planning and promote recovery monitoring in adults with ASD.
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    Assessing Outcomes of Evidence-Based Practices Through Violence Risk Assessment and Clinical Global Impression (CGI) Analysis in Children with Autism Spectrum Disorder
    (2023-04-28) Darsanapu, Archana; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This practicum at HANDS in Autism®, in collaboration with the Indiana NeuroDiagnostic Institute (NDI), aimed to evaluate the effectiveness of an evidence-based coordinated care approach for youth with Autism Spectrum Disorder (ASD) receiving inpatient psychiatric services. The study compared pre-admission data collected via Cerner and post-discharge data collected through REDCap for 42 individuals. Using the Clinical Global Impression (CGI) scale and Violence Risk Assessment (VRA), the project measured behavioral outcomes following treatment. Data were coded, analyzed using Python and Excel, and visualized to assess changes in severity and improvement scores. Results showed that 31 of 42 patients demonstrated measurable improvement. The findings support the use of integrated data systems and standardized behavioral tools to monitor treatment impact and reduce risks associated with behavioral health crises. This project contributes to ongoing evaluation of treatment interventions and development of comprehensive, individualized care plans for youth with ASD.