The capstone project provides an opportunity for health organizations and learners to collaborate to identify and translate a real organizational health need into an analytics problem. The project can include elements of data collection & preparation, data modeling and analysis with the potential to include predictive modeling, machine learning implementation, constructing dashboards or spreadsheets, programming, statistical analysis, and a solution deployment plan. Capstone project results/recommendations will be communicated in a report document and a final presentation.

You should submit a high-level proposal/health-related problem statement including relevant data sets and definitions, a list of acceptable tools (if applicable), and expected deliverables. Health datasets could be provided based on a non-disclosure agreement or in an anonymized/synthetic data format that is relevant to your organization and business problem. The capstone course instructors will review the documents to confirm the scope and timing of the proposed problem and its alignment with the capstone course requirements.

Analytics solution may be applicable for (however they are not limited to) the following topics:

1. Demand for social services (healthcare, emergency services, infrastructure, etc.)
2. Identify gaps in healthcare
3. Non profit funding and research
4. Disease & Chronic Condition Identification
5. Cost & Utilization
6. Population Health Risk Adjustment
7. Evidence Based Care Tracking (EBCR)
8. Transition of Care

To ensure students’ learning objectives are achieved, we recommend that the datasets are at least 20,000+ rows in size. Data need not be ‘clean’; it is advantageous to the students’ learning experience to require hygiene prior to analysis. Similarly, if more than one database is provided, which must be conjoined, students will be required to integrate them. This supports the learning experience and minimizes partner data preparation.

Note: Students can sign a NDA, if required.