Michael has six years of experience in healthcare data analytics and analytic research. He has expertise in the full process of large and small data, including data ingestion, error correction, data normalization, analysis, visualization, and reporting. He has experience with inferential statistical methods, such as t-tests, weighted least squares, propensity score matching, and coarsened exact matching.
Michael’s professional experience includes:
- Preparing Quality Measures for the Colorado State Innovation Model using the Colorado APCD.
- Developing hospital utilization metrics and hospital needs-based assessment reports using the Texas Health Care Information Collective. This work involved measuring shortfalls in mental health services, hospital psychiatric utilization, and emergency department utilization.
- Designing metrics to analyze frequency and severity of substance use disorders and mental illness.
- Conducting primary care analyses using APCD data and development of easy-to-understand reporting tools for the Governor's task force on primary care in a large state.
- Aiding in the development of benchmarking solutions for inpatient, outpatient, and professional settings to measure national performance.
- Preparing a longitudinal diabetes, hypertension, and prediabetes study measuring costs and utilization changes over time.
- Conducting Stoploss Analysis using commercial PPO data.
- Employing specific skills in a variety of programming and query languages, including R, Python, SQL, Excel, and Power BI
