The Conversation on Diversity and Automation
The conversation regarding the incorporation of diversity when implementing artificial intelligence (AI) has recently focused on ensuring that machines have not been programmed to include biases in the decision-making. However, as we see more healthcare organizations implement AI, robotic process automation (RPA) and machine learning (ML) in the revenue cycle, we need to be careful to not systematically eliminate jobs held by protected classes.
I’ve had the honor of working in the revenue cycle for almost 30 years. It is difficult to find statistics on the percentage of revenue cycle staff that are minorities or in a protected class, but from my experience, many revenue cycle staff individuals fall into that category. As we begin to think about who will be making decisions about automation (an estimated 87 percent of healthcare boards are white, while only 13 percent are people of color[1]), I would guess that many sitting in the decision-making seats don’t represent the staff they manage.
There’s no question that we need to automate the revenue cycle. Mundane and repetitive tasks, like getting the status of a claim or checking on a prior authorization request, can and should be automated. However, we have an ethical obligation to evaluate how automating these tasks can impact our staff. Yes, we will be able to do more with less, and we can now use our staff to do work that only humans can do.
As your organization begins its automation journey, leaders must consider the impact on the diversity of its people. The first step is to acknowledge that discrimination in RPA and AI/ML implementation is a real risk. Organizations should identify potential risks associated with discrimination – like eliminating positions, staff turnover during implementation and even implementation failure – and then plan for the risk by implementing strategies to minimize or eliminate it. As organizations define use cases for automation, leaders should evaluate the roles that will be impacted by the automation and the demographics of the staff in those roles. In addition, leaders must understand the extent to which the jobs will change, meaning what percent of the current role will be automated.
Strategies to Address Diversity Risk
Once the organization has identified and understands any risk, there should be a collaboration between team members in the organization, including human resources and the office of diversity and inclusion, on which strategy to best address the risk.
- The avoidance strategy requires the organization to understand the consequences of adopting RPA or AI/ML, plan for the risk and then take steps to avoid it. For example, a revenue cycle leadership team may decide to evaluate the opportunity to implement RPA in claims status. Upon careful review, the organization determines that the need for staff will reduce by 40 percent. The organization may then determine that they will redeploy staff to other areas with vacancies or high turnover (e.g., patient access services).
- The controlling risk strategy works by understanding and accepting the risk in order to reduce or eliminate the impacts of the risk. For example, one identified risk could be that staff may decide to leave the organization proactively upon hearing about automation efforts, or the performance of staff may wane as individuals become concerned about future job loss. A controlling risk strategy in this situation would include proactive communication methods with staff about the automation journey, and even including them in the automation implementation.
An alternate controlling risk strategy may also include an investment to upskill staff. As tasks are automated, team members can absorb more advanced activities. For instance, as organizations automate the submission of prior authorizations for less intensive cases, staff can be redeployed to more complex cases. To help the staff succeed in these new roles, organizations can design educational programs to provide staff with the anatomy/physiology knowledge and coding skills required to succeed.
At Windham Brannon, we acknowledge that 2022 is the year of automation in the revenue cycle – but to ignore the impact on staff would be irresponsible. The good news is that organizations can incorporate diversity, equity, and inclusion into their overall automation strategy creating a stronger revenue cycle organization. You can find out more by contacting your Windham Brannon advisor or contacting Valerie Barckhoff.
[1] Haefner, Morgan. “‘We’ve made no progress’: Healthcare boards 87% white, Leverage Network study finds.” Becker’s Hospital Review. Feb. 23, 2021.