Browsing by Subject "Electronic Health Records (EHR)"

Now showing 1 - 3 of 3
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    Assessing Patient Characteristics and Improving Data Accessibility in Autism Spectrum Disorder Inpatient Programs.
    (2023-12) Darsanapu, Archana; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This project focused on enhancing healthcare data visualization and accessibility for individuals with Autism Spectrum Disorder (ASD) receiving inpatient psychiatric services. Data review and quality assurance were conducted using REDCap, with a focus on accuracy and completeness of patient demographic and service data. An interactive Power BI dashboard was developed using REDCap-exported datasets to visualize trends in service characteristics, patient profiles, and healthcare utilization. Although dynamic integration through API was not available, the dashboard was built with scalable design features to support future real-time functionality. Additional responsibilities included coordinating evaluations, supporting subgroup communication, and organizing timelines to ensure consistent data workflows across projects. The effort demonstrates the practical value of integrating informatics tools in ASD clinical settings to support data-driven care, team collaboration, and strategic decision-making.
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    Stabilizing Behavioral Changes and Preventing Readmission in Individuals with Autism Spectrum Disorder Through Transitional Support Strategies
    (2022-08) Achanti, Sai Yashashwini; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    Youth with Autism Spectrum Disorder (ASD) often experience behavioral challenges requiring coordinated and sustained inpatient support. This practicum, conducted at the Neurodiagnostic Institute (NDI) in partnership with HANDS in Autism®, focused on evaluating stabilization outcomes and the effectiveness of post-discharge planning in preventing readmissions. Electronic health record data were extracted from Cerner and categorized using the Aberrant Behavior Checklist (ABC) and Clinical Global Impression (CGI) scales. The data were further aligned with moderator variables to examine behavioral outcomes across inpatient care and post-discharge periods. Tools including R, REDCap, and Excel were used to manage, code, and visualize the data. Findings revealed patterns in behavior change trajectories that may inform individualized care planning and system-wide improvements. This analysis supports the use of evidence-based behavioral classifications and quantitative tracking to enhance continuity of care, reduce readmissions, and improve long-term outcomes for individuals with ASD in psychiatric inpatient settings.
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    Use of Electronic Health Records to Support a Public Health Response to the COVID-19 Pandemic in the United States: A Perspective from Fifteen Academic Medical Centers
    (Oxford University Press, 2020-11-03) Madhavan, Subha; Bastarache, Lisa; Brown, Jeffrey S.; Dorr, David A.; Embi, Peter J.; Friedman, Charles P.; Johnson, Kevin B.; Moore, Jason H.; Kohane, Isaac S.; Payne, Philip R.O.; Tenenbaum, Jessica D.; Weiner, Mark G.; Wilcox, Adam B.; Ohno-Machado, Lucila; Butte, Atul J.; Medicine, School of Medicine
    Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result in unnecessary delays in understanding, predicting, preparing for, containing, and mitigating the COVID-19 pandemic in the US. Response efforts involve the collection and analysis of data corresponding to healthcare organizations, public health departments, socioeconomic indicators, as well as additional signals collected directly from individuals and communities. We focused on electronic health record (EHR) data, since EHRs can be leveraged and scaled to improve clinical care, research, and to inform public health decision-making. We outline the current challenges in the data ecosystem and the technology infrastructure that are relevant to COVID-19, as witnessed in our 15 institutions. The infrastructure includes registries and clinical data networks to support population-level analyses. We propose a specific set of strategic next steps to increase interoperability, overall organization, and efficiencies