Dan Hopkins

Professional Services, VP

Dan Hopkins joined Health Catalyst in June of 2012; most recently, he worked for Frederick Memorial Hospital as a Senior Data Solutions Architect creating dashboards related to nursing sensitive indicators and patient satisfaction. His other career highlights include roles at the University of Utah as Senior Data Architect, Senior Data Analyst and Senior Business Analyst, Iomega as a Senior Oracle Applications Analyst, Hunt Oil in Dallas, Texas as an IS Project Manager and Senior HRIS Analyst and Mirage Resorts in Las Vegas as Compensation/HRIS Manager, Senior Financial Analyst and Assistant Executive Hotel Manager.

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Optimize Your Labor Management with Health Catalyst PowerLabor™

To cut costs, healthcare leaders are looking at their greatest operating expense—labor management. However, with outdated labor management systems, decision makers rely on retrospective, incomplete data to forecast staffing volumes and patient support needs. Limited workforce insight can result in misaligned staffing or worse, jeopardizing patient care due to lack of labor support. With the Health Catalyst PowerLabor™ application, part of the Financial Empowerment Suite™, decision makers have access to a comprehensive view of labor data by organization, department, team, and job role. Timely insight into current and future hospital needs allows leaders to staff to patient volume, control escalating labor expenses, and ensure optimal resources for excellent patient care.

Transforming Healthcare Analytics: Five Critical Steps

By committing to transforming healthcare analytics, organizations can eventually save hundreds of millions of dollars (depending on their size) and achieve comprehensive outcomes improvement. The transformation helps organizations achieve the analytics efficiency needed to navigate the complex healthcare landscape of technology, regulatory, and financial challenges and the challenges of value-based care.

To achieve analytics transformation and ROI within a short timeframe, organizations can follow five phases to become data driven:

1. Establish a data-driven culture.
2. Acquire and access data.
3. Establish data stewardship.
4. Establish data quality.
5. Spread data use.

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