Data Analyst – Healthcare Facility Normalization & Predictive Modeling

PROJECT OVERVIEW We are seeking a detail-oriented Data Analyst for a multi-phase project involving the normalization of data for approximately 600 facilities. The goal is to create a "Single Source of Truth" by merging multiple datasets and building a predictive model to estimate potential capacity gains. This is a medium-range project; as we conduct more feasibility studies, we will feed that new data back into the model to improve accuracy over time. KEY RESPONSIBILITIES Database Normalization: Reconcile three disparate data sources into one master Google Sheet. You must "hard-tie" each facility using verified primary keys (Medicare CCN, Medicaid ID, and internal file numbers) to ensure 100% mapping accuracy. Primary Source Data Mining: Access and extract granular infrastructure data—specifically room configurations (1-bed, 2-bed, 3-bed, and 4-bed counts). Multiple Regression Analysis: Using an existing sample of validated feasibility studies (gains of 0-15 beds), perform a multiple linear regression to identify the relationship between square footage, facility age, and bed gain. Predictive Scaling: Apply the regression results across the full population of 600 facilities to rank and prioritize targets based on "Predicted Bed Gain." Iterative Model Refinement: As new data from onsite studies is collected, update the master sheet and retrain the model to improve accuracy (R-Squared). REQUIRED SKILLS Advanced Data Cleaning: Expertise in handling inconsistent text strings and performing complex lookups across large datasets. Statistical Proficiency: Solid understanding of regression analysis, including the ability to interpret p-values and identify outliers. CMS Data Fluency: Familiarity with the Provider Data Catalog (PDC) and the Healthcare Cost Report Information System (HCRIS). Secondary Research & Data Discovery: Proactively browse and identify additional publicly available datasets that could impact the model, such as state-level health inventory logs, regional planning reports, or building permit databases. Tooling: Expert-level Google Sheets or Excel skills. Apply tot his job