Minutes after my son’s high school baseball game ends, or after my daughter’s soccer team trots off the field, a brief news article about the game pops up on my phone. These articles typically have a punchy headline and include highlights from a game that ended minutes earlier. But these articles aren’t written by sports reporters sitting in the stands. They are generated by robotics process automation (RPA) combined with natural language creation (NLC). A parent or coach tracks balls, strikes, hits, and all of the plays through a smartphone app. The numerical data are then translated into a narrative through an NLC program. This technology is being incorporated across many industries—from banking to customer service—pretty much any business or activity that generates or processes large amounts of data.
RPA is the hard coding of activities that people manually perform on computers. This could include virtually any task that a person does on his or her keyboard. If he or she puts information into a spreadsheet and sends it off in an email, a data-bot can be written to extract that information and use it to complete a task. Given the vast amounts of data health care organizations generate, RPA could streamline processes and take over some of the mundane tasks employees now perform.
Clinicians typically manually type notes about a patient’s condition, prescription drug usage, vital statistics, and past medical history into the patient’s electronic health record (EHR). RPA robots could be programed to extract all of that information and translate it into a narrative using NLC. RPA robots, or data-bots, are software programs designed to perform repeatable tasks. Staff can monitor and record the tasks performed by these bots, producing valuable data.
While automation tools can do some things, they cannot do others. When some people hear the word “robotic,” they immediately conjure up images of metallic humanoids (with blinking red lights) methodically traversing the hallways. But data-bots aren’t anything more than hard-coded computer actions that can accomplish many tasks that are now performed manually. Data-bots operate around the clock with no coffee breaks or sick days, and they aren’t prone to accuracy errors that people can make due to late work hours, stress or not enough sleep.
ROI can go beyond the obvious
Many health care and life sciences companies are beginning to learn from industries that have already incorporated RPA into their workflows, but adoption is not yet widespread. Many health care employees continue to spend their days on highly repetitive, manual tasks. RPA holds the potential to dramatically improve the speed and efficiency of these activities by taking them out of human hands and putting them into the virtual hands of data-bots.
Such tools can lead to a return on investment (ROI) in reduced labor costs and improved productivity. But ROI can go beyond the obvious. When organizations implement automation tools such as RPA, they typically redesign processes around the new technology, making the entire process more efficient.
It can be useful for organizations to take a holistic view of the entire process in which RPA is being implemented to find these overall efficiencies. It can be challenging to find the budget dollars needed to build and implement automation tools. But organization leaders should recognize the strategic and competitive advantage this technology can offer. That should be included in the expected ROI when trying to justify the implementation cost.
ROI could lead to a more competitive workforce
If an organization has strategically determined that it needs to limit new hiring to remain competitive in the future, automation tools could help them get more work done with fewer people. Organizations can refocus their existing employees on more strategic activities. Such areas might include quality and safety, which can help the organization achieve a strategic advantage. Rather than spending thousands of hours on obtaining data, employees can focus on making strategic decisions based on the data that has been gathered by automation tools such as RPA.
What can be automated?
Health care organizations are governed by regulatory oversight and quality metrics. Determining whether quality goals have been met often depends on good analysis of patient care data.
Compliance, for example, can be a tremendously complicated process. Consider a hospital that serves Medicare beneficiaries and processes thousands of claims daily. Employees are typically tasked with ensuring accurate billing, and compliance activities are often designed to identify potential billing risk flags from among the millions of claims that a provider submits to payors. Automation can take over some of those monotonous and repetitive tasks. RPA can be used to pull and aggregate data from multiple and disparate sources, thereby improving the efficiency of regulatory, non-financial, and risk reporting because it reduces or eliminates time-consuming processes of collecting, compiling, cleansing, and summarizing large amounts of information. Additionally, RPA can enhance workflow management through its ability to designate, track, and manage monitoring and testing assignments.
Some life science organizations that are subject to payment transparency requirements have automated the activities that generate the related reporting. They also have used automation tools to improve compliance-monitoring analytics and many other activities that are good candidates for automation.
Rise of the machines
Many health care organizations use EHR systems to manage their medical record documentation and clinical workflow. These systems amalgamate tremendous amounts of data that could be useful for assuring patient care quality, compliance, and risk mitigation. However, many health care organizations struggle to harness the data contained in their EHR systems—even with the implementation of expensive data warehouses. However, automation tools such as RPA can collect data and translate it into a meaningful format. Employees might spend hundreds of hours each week extracting data, but if data-bots can take over these repetitive tasks, employees can dedicate more time to strategic analysis and decisions.
Some people refer to cognitive intelligence or artificial intelligence (AI) as the next wave, and see RPA as a near-term solution for automation. Combining RPA with AI in the future can allow health care organizations to create intelligent analyses culled from tremendous amounts of data. The productivity enhancements achievable through automation tools such as RPA can represent a tremendous opportunity and strategic advance for health care organizations that are willing to embrace the concept and step into the future.
For more on this technology trend and other trends impacting life sciences and health care organizations, check out our tech trends series