This is the fourth article in a series regarding process-based opportunities as the healthcare industry begins to emerge from the challenges of the pandemic. As noted in the introduction to this series, each of these articles will define an issue, consider the problem and its implications to healthcare, and then present potential solutions.

Earlier in this series, I wrote about the issue of clinician burnout, with the two top contributing factors being the great number of bureaucratic tasks people have to perform, and the excessive number of hours they have to spend at work just to get everything done.

That is not just true with clinicians – this story is the same with staff throughout healthcare organizations, whether they work in management, medical records, accounting, claims management or other departments.

Staff members universally have too many tasks to do in a limited amount of time because they are caught up in processes that comprise a host of wasteful, monotonous, manual activities. There are several process improvement solutions to this problem, but in this article, I want to explore how the application of robotic process automation can help.

And no, I am not going to recommend you replace your workforce with robots.

When people think of robots, what often comes to mind is a machine approximating the size and shape of a human and mimicking our motions and tasks, or a small vehicle motoring around and performing a singular task.

Robotic process automation is neither of those things. In fact, usually it is invisible, working inside of your computer systems and databases, but it has the potential to make significant positive effects on how efficiently and effectively your people and your organization work.

The challenge

Many of the tasks we perform in healthcare are tedious and repetitive, causing hours upon hours of data entry, with staff often re-entering data that exists and could be retrieved somewhere else in the system.

This is often the reason, for example, that the lag time between submitting a claim to a payer and receiving payment from them takes so long. Healthcare staff also spend a great deal of unnecessary time extracting information from medical databases and clinical documents for the purpose of public health reporting.

We also put our external customers through a version of this tedium by having them spend their valuable time in a call center scheduling appointments, requesting prescription refills or getting necessary medical or procedure information, and not streamlining this process also affects staff time.

Another problem is that humans performing repetitive, monotonous tasks are much more inclined to produce errors than a computer bot, and computer bots can work around the clock without requiring sleep, water, food or office space.

These are only a few of the myriad examples of wasted time and effort spent on mundane tasks, which negatively affect staff morale, external customer satisfaction, and the bottom lines of healthcare organizations.

Implications for healthcare

Significantly degrading the productivity of our human resources on monotonous tasks means we are also losing money and competitive advantage in the process. RPA can address many process challenges in healthcare across many areas, including billing and compliance, electronic health records, clinical documentation, financial systems, patient scheduling, and in many areas of internal and external customer engagement.

The rewards can be significant. According to a Deloitte global RPA survey, organizations saw a return on investment with RPA in less than 12 months, with robots averaging 20% of full-time equivalent capacity in those organizations. Respondents to the survey said RPA met or exceeded their expectations in multiple areas, including cost reduction, and improved compliance, quality/accuracy and productivity.

Solutions

While the “robot” aspect of robotic process automation gets much of the attention, successful implementation of RPA centers on the people and processes that will be impacted. Depending on the scale, the costs for creating and putting to work a complex network of bots can range into the millions of dollars, so failure and/or abandonment of the effort can be expensive. Because failure is most often caused by poor preparation, let’s look at a four-phase approach to integrating RPA.

• Planning. The processes to be automated and the logistical issues for implementing each are identified, with an eye toward compatibility with existing processes and systems.

• Preliminary development. Building on the planning phase, automation workflows are created to select automation candidates thoroughly, and possible risks are identified.

• Deployment and testing. This phase involves intensive monitoring with the goal of discovering outages and bugs in the product. Once this phase is completed, bots can then be scaled and deployed.

• Support and maintenance. In order to maintain its productivity, the fully deployed product is continuously updated across the database.

Successfully implementing RPA solutions means creating a diverse team of stakeholders that includes the people who are impacted by a process problem that seriously impedes their productivity, the leaders of those people, and those with the technological know-how to automate the processes.

Such a team, identifying a problem, finding an RPA solution and using a phased approach such as the one described above, can open up limitless possibilities for organizational improvement.

A final note: Just because bots can work around the clock effortlessly and without errors doesn’t mean employees should fear losing their jobs because of them. Computer bots are not capable of higher cognitive functions. They don’t have the powerful human abilities of logical and critical thinking.

What those bots do represent, however, is the opportunity to open up more time in the workplace for us humans to use our power to “think about thinking” and create time and space for doing the work that most matters in our organizations.

Sam Hanna is an executive-in-residence at American University. Prior roles include being a consulting practice leader, a chief strategy and innovations officer, and a digital strategist at global consulting firms such as PwC and Deloitte. He holds a PhD in Translational Health Sciences from the George Washington University and a MBA in Entrepreneurship from Babson College.