HRSA Population Health Dashboard
Nguyen, C.
Show abstract
Project PurposeTo develop a quality dashboard tool for the Health Resources and Services Administration (HRSA) community health centers to examine health center characteristics associated with performance excellence and predict future healthcare cost. BackgroundHRSA is the primary federal agency for improving health care to people who are geographically isolated, economically or medically vulnerable. HRSA-funded health centers are required to upload to Uniform Data System (UDS). HRSA health data is rich; however, their website provides limited meaningful visualization and data-driven analysis. MethodThe project reviewed data from Uniform Data System between 2017 and 2019. The data was cleaned using Excel. Visualization was displayed on Tableau, and the cost prediction modeling was completed using Python Machine Learning libraries. All the findings are available for public view on Weebly-hosted website. OutcomesThe Tableau dashboard showcases the effectiveness of the preventive intervention and chronic disease management initiatives over the years. This tool focuses on comparison between outcomes in health care programs and cost benefits in all states. The dashboard also uses the most fit Machine Learning model and the most important variables to predict the cost per patient of a health center. DiscussionThe lack of similar performance comparison dashboards by HRSA suggests a need for HRSA Population Health Dashboard to understand the performances of HRSA-funded health centers or regions through times. It shows the ineffectiveness of the current healthcare programs in reducing disease growth and healthcare cost over the course of 3 years. Next Steps/OpportunitiesThe final dashboard will be available for public use and will continue to aggregate more real-time data using Application Programming Interface (API) to improve its accuracy of prediction model. The HRSA Population Health Dashboard will be beneficial to management at both HRSA federal- and health center-level to make valuable strategies.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- LinkR: an open source, low-code and collaborative data science platform for healthcare data analysis and visualization 93%
- Development and Evaluation of MADDIE: Method to Acquire Delivery Date Information from Electronic Health Records 92%
- Synthetic Data Generation in Healthcare: A Scoping Review of reviews on domains, motivations, and future applications 92%
Similar papers in this journal
- Development and preliminary testing of Health Equity Across the AI Lifecycle (HEAAL): A framework for healthcare delivery organizations to mitigate the risk of AI solutions worsening health inequities 93%
- From months to minutes: creating Hyperion, a novel data management system expediting data insights for oncology research and patient care 93%
- Impact of electronic medical records on healthcare delivery in Nigeria: A Review 92%
Similar papers in this journal
- Implicit bias in Critical Care Data: Factors affecting sampling frequencies and missingness patterns of clinical and biological variables in ICU Patients 92%
- Construction and application of a revised satisfaction index model for Chinese urban and rural residents basic medical insurance 92%
- On the predictability of postoperative complications for cancer patients: a Portuguese cohort study 91%
Similar papers in this journal
- Measure what matters: counts of hospitalized patients are a better metric for health system capacity planning for a reopening 92%
- Increasing Trust in Real-World Evidence Through Evaluation of Observational Data Quality 92%
- Gaps in Artificial Intelligence Research for Rural Health in the United States: A Scoping Review 91%
Similar papers in this journal
- De-novo FAIRification via an Electronic Data Capture system by automated transformation of filled electronic Case Report Forms into machine-readable data 91%
- Signal from the Noise: A Mixed Methods Process Mining Approach to Evaluate Care Pathways. 91%
- Demonstrating the Consequences of Learning Missingness Patterns in Early Warning Systems for Preventative Health Care: A Novel Simulation and Solution 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.