Senior Vice President and General Manager, Financial Transformation Business
Dan Unger joined Health Catalyst in April 2014. He came to Health Catalyst after working at Accretive Health where he managed a team that worked with the Intermountain Medical Group to improve revenue cycle processes and reduce operational costs. Prior to Accretive, Dan worked as a consultant at Equation Consulting (a physician economics consulting firm) and as a pricing and profitability analyst at JP Morgan Chase. He graduated from the University of Arizona with degrees in Finance and Entrepreneurship and received his MBA in International Finance from the Thunderbird School of Global Management.
U.S. health systems will have a projected deficit of 200,000-450,000 RNs by 2025. Meanwhile, hospital labor costs have reached almost 50% of an organization’s overall expenses. Now more than ever, leaders need a data-driven labor management strategy that ensures the most cost-effective, high-quality care.
Regardless of COVID-19 vaccine efficacy and how long it takes risk levels to fall into less threatening ranges, many effects of the pandemic are here to stay. One area that will remain fundamentally altered is the business of delivering healthcare—the strategies and ins and outs of healthcare finance. COVID-19 has fueled new delivery models and new competition, as patients and clinicians are drawn to more convenient, less costly care (e.g., virtual care) and less stressful, more productive work environments.
So, how can traditional providers adapt and thrive in this new healthcare landscape? They must start by recognizing the impending challenge as a business problem, not a technology or care problem. This means leveraging their CFOs and financial leaders to play a more collaborative role in empowering clinicians to make better decisions and operationalizing health systems’ key differentiator—data.
Effectively financial management is an ongoing challenge for healthcare organizations, according to Dan Unger, General Manager and Senior Vice President of Financial Transformation Business at Health Catalyst. In this episode of Owning the Future of Healthcare, a Health Catalyst podcast, Unger discusses the criticality of an agile financial approach, competing with new innovative healthcare providers, […]
Uncompensated care can cost large health systems billions of dollars annually, making outstanding balances one of their biggest costs. Propensity-to-pay tools help organizations target unpaid accounts by using artificial intelligence (AI) to leverage external and internal financial and socioeconomic data and identify the likelihood that patients in a population will pay their balances (propensity to pay). With propensity-to-pay insight, financial teams can focus their efforts on patients most likely to pay, and connect patients who are unable to pay with charity care or government assistance. Both health systems and patients benefit, as patients can avoid bad debt and organizations receive compensation for care they’ve delivered.