Data Simulation: Generate realistic healthcare QI data with various participant phenotypes, measurements, and outcomes.
Data Import: Upload your own healthcare quality improvement data in JSON format.
Data Summary: View comprehensive statistical summaries of your dataset.
Visualization: Explore data through tables and interactive charts.
Analytics: Perform statistical analyses, risk factor assessments, and quality improvement metrics calculations.
Reporting: Generate reports summarizing findings and export them for presentation.
Education: Teaching healthcare quality improvement methods and data analysis to students and practitioners.
Research: Exploring relationships between clinical variables and patient outcomes.
Healthcare Planning: Developing and testing quality improvement initiatives based on data analysis.
Clinical Practice: Monitoring and improving patient care quality metrics across different units.
Benchmarking: Comparing performance metrics across different clinical settings.
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To deploy this project open and click on Share and Publish.
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There are several ways of editing the QI application. Changes made via Lovable will be committed automatically to this repo. Any other IDE can also be used to work locally, clone this repo and push changes. Pushed changes will also be reflected in Lovable. Local editing an dtesting only requires having Node.js & npm installed - install with nvm. Follow these steps:
# Step 1: Clone the repository using the project's Git URL.
git clone <YOUR_GIT_URL>
# Step 2: Navigate to the project directory.
cd <YOUR_PROJECT_NAME>
# Step 3: Install the necessary dependencies.
npm i
# Step 4: Start the development server with auto-reloading and an instant preview.
npm run devAlternatively, the code can be edited directly in GitHub by navigating to the desired file(s), clicking the "Edit" button (pencil icon) at the top right of the file view, and ensuring that revisions are committed.
- This project is built with Vite, TypeScript, React, shadcn-ui, and Tailwind CSS.