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.
Learn more about Dan Unger
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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When it comes to transitioning to value-based reimbursement, health systems consistently ask two questions:
Why should I invest in reducing utilization when 90+ percent of my business is still fee-for-service (FFS)?
Where do I start?
This value-based reimbursement road map can help systems transition from barely surviving to successfully arriving (while respecting both shared-risk and FFS worlds):
Stop #1: Surviving— If you don’t get paid for the risk you take on, then you can’t survive long term.
Stop #2: Sustaining—Numerous clinical interventions occur in hospitals that systems can focus on to help improve the bottom line.
Stop #3: Succeeding—Build out competencies on a smaller population with aligned incentives so you can negotiate deeper alignment with key payers.
Stop #4: Arriving— The ultimate destination, where the lines between traditional healthcare delivery and public health are blurred.
Although healthcare is far from arriving at the value-based reimbursement destination, it can use this road map’s pragmatic strategies for heading down the right road.
These past few years have seen a lot of coverage on healthcare costs. But a majority of these articles just confuse the issue. Some of the reasons healthcare costs are elusive do not include: 1. Hospitals are hiding something. Or 2. There isn’t enough data. Instead, the real reasons behind the difficulty are: 1. Healthcare is complex. 2. Fragmentation. And, most importantly and pervasively, 3. Data governance. Until data governance becomes a priority, healthcare organizations will not be able to get clear answers for their healthcare costs.