Dan Unger

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.

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Resolving Uncompensated Care: Artificial Intelligence Takes on One of Healthcare’s Biggest Costs

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.

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