Healthcare finance leaders have got their hands full.
Billions of dollars have been invested in healthcare AI in recent years, and billions more will be invested in the years to come. Finance leaders, consequently, are scrambling as fast as they can to come up to speed on the rapidly developing set of technologies and how they might help their organizations.
To give them a bit of a hand, the Healthcare Financial Management Association (HFMA) recently published a short primer on what it views as the top “five realities” about AI in healthcare that financial leaders should be aware of as they sort through rapidly developing, and thus changing, opportunities.
1: Healthcare has a data quality problem
AI requires large data sets of accurate, clean data to be effective, so in addition to vetting particular technologies, financial leaders must be mindful of their organization’s data practices to ensure optimal data quality.
To that end, says the HFMA, “(d)ata governance work groups composed of financial, business and clinical data consumers can assist analytics and technical teams in clarifying how data is defined, captured, structured, transferred, cleaned and presented,” with the overall goal being effective improvements across the data quality landscape.
2: AI consists of multiple technologies and tools
It’s an easy mistake to make for newcomers, but AI is not a single technology. Rather, it’s an umbrella term that includes machine learning, natural language processing, robotics and algorithms.
Given the potential for confusion, then, it’s important for financial leaders to educate their colleagues about the differences, understand vendor terminology and ask for explanations with they don’t and work with business or clinical decision-makers to validate the results of the models within their own environment.
3: AI will require new skills and competencies
No, AI is probably not going to replace humans in the workplace on a large-scale level, but it will require humans to learn new skills. In addition to automating a range of mundane tasks, the innovation AI enables will force healthcare leaders to centralize AI skill development, as well as to create “data translator and business architect roles” to, among other things, collaborate with data professionals to design new algorithms, rearchitect business processes and decision-making practices and develop and implement new operating models.
4: New security, privacy and ethics concerns should be addressed
In addition to the myriad advantages AI will bring, it will also bring new challenges, including ensuring patient privacy, developing effective “data use agreements with vendors regarding data protection, intended use of data and compliance with standards,” and updating and understanding regulations impacting data, including the 21st Century Cures Act and emergency data transparency requirements.
5: AI is in a hype cycle
Finally, AI is still considered the new technological kid on the block, and as such there’s no small amount of hype associated with it. To ensure a sound investment, the HFMA says healthcare finance leaders “can leverage strengths in financial decision support to narrow the focus of appropriate use cases, convene collaborative, multidisciplinary teams, standardize and organize the data, define success measures and set the stage for better performance, service and outcomes.”
The bottom line, says the HFMA, is that as AI expands to help reduce costs, improve consumer engagement and further digitize the delivery of care, financial leaders don’t need to be risk takers to move forward with AI. They just need to understand what they’re getting their organizations into.