The presence of artificial intelligence has been increasing in the healthcare industry, and with the technology maturing and becoming more viable, the opportunities for it to make administrative and process improvements have been increasing – and revenue cycle management is one area in which this is especially manifest. The problem with many current revenue cycle processes is that it can result in a lot of friction and waste. In a HIMSS20 digital presentation, Mark Morsch, vice president of technology at Optum360, cited data indicating that there can be as much as $200 billion in administrative waste in the healthcare system due to inefficient revenue cycle practices. "That's waste in the system between providers and payers that's generated from a lot of inefficiency, from inaccurate documentation and coding, a lack of transparency, and both sides not being aware of the appropriate steps a lot of times," Morsch said. Hiring data provided by Optum360 illustrates the extent to which administrative spending has increased.

A study on artificial intelligence (AI) suggests the technology holds promise for detecting Medicare fraud within home health and hospice. However, leaders within the industry say a measured approach should be taken, given potential shortcomings and pitfalls related to AI. The research team at Florida Atlantic University programmed computers to predict, classify and flag potentially fraudulent Medicare Part B claims from 2012 to 2015. Fraudulent activities included patient abuse or neglect and billing for services that weren't delivered. The team applied algorithms to detect patterns of fraud in the Centers for Medicare & Medicaid Services (CMS) data because "patterns in the data are hidden from us" as humans, said Taghi Khoshgoftaar, Florida Atlantic University director of Data Mining and Machine Learning Lab in the Department of Computer and Electrical Engineering and Computer Science.