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UPMC’s Porter says very firmly, “First, you have to invest in the people—you need actual data scientists, who have a high technical capability,” he emphasizes. “But those people are difficult to get, and are expensive.”
Once the AI- and machine learning-based tools are implemented, Porter says, he and his colleagues will be engaged not only in predictive denials management but also in developing models to predict patient payment behavior. “We’re looking at our patient segmentation to understand patient payment patterns and behaviors—who pays and how, for example, on the first bill, the second bill, etc. We want to create a better patient experience around this.”
Clearly, there are challenges involved here; but, everyone agrees, this is one area in which the potential of technology to fuel a new kind of revenue cycle management is very real.
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An API-first approach supports low-code solutions, and that is of immense value to healthcare facilities right now. These solutions are lightweight and can be delivered to a device carried by a …
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