How a Digital Workforce Will Save Healthcare

How a Digital Workforce Will Save Healthcare

Enterprises have been digitizing data and processes furiously over the past few decades, and these efforts have unlocked a pantheon of capabilities to offer new products and better experiences, and healthcare is no exception. Partially driven by government mandates and subsidies, healthcare systematically bought large electronic medical record systems (EMRs and EHRs) and other systems to bring them into the digital era. Unfortunately, this tidal wave of adoption, although extraordinarily valuable, had negative side effects as well: 


The digitization of healthcare created silos. Database fortresses were built at every organization. They weren’t built to share. They weren’t built to interoperate – not between software systems and certainly not between organizations. No connection to insurers. No connection to other providers and until recently, almost no connection to patients. 

Instead, healthcare employees have taken on the job of the data router, shifting hours spent from being in front of patients, to being in front of computers, shepherding patient data into the right fields. This administrative burden is driving skyrocketing costs, rising attrition and a backlog of work in an industry already suffering from razor thin margins. Healthcare can’t continue to operate like this – there must be a solution to rescue nearly a trillion dollars of administrative costs and reallocate these precious resources to the delivery of care, the creation of new drugs and therapies, and the research to eradicate diseases.


The answer is an AI-powered digital workforce.

Today, most healthcare executives are familiar with robotic process automation, or RPA – it’s used to automate common workflows or business practices like patient scheduling, supply chain management, claims management, and more. That’s because many of the time-consuming, manual processes that make up healthcare administration are simple, rule-based and high volume – the perfect candidate processes for automation. But for many organizations looking to deploy artificial intelligence, RPA alone will not allow them to realize the full benefits of AI – a digital workforce is required.


A digital workforce goes beyond traditional RPA in 3 very important ways:
  1. A digital workforce has deep learning
  2. Gets smarter over time & adjusts work 
  3. Interacts with human management

Not all automations a digital employee does can be performed by a human – in many cases, a digital employee uses deep learning techniques to accomplish far more complex tasks

Although a digital employee depends on RPA as a building block of their capabilities, they leverage other advanced technologies to handle more complex tasks that RPA can’t accomplish alone. For instance, while RPA can quickly and accurately process large volumes of data, Olive, the first AI-powered digital employee built for healthcare, leverages some degree of artificial cognition on top of an automation, allowing her to make decisions or take action with cognitive “thinking” involved.

The processes involved in deep learning are similar to that of data mining and predictive modeling – this is how a digital employee gets smarter over time. Leveraging deep learning techniques provides better and faster information that improves efficiency, capacity, and reduces costs by providing insights into bottlenecks – and the reason behind these bottlenecks – identifying systemic, recurring issues and making adjustments or recommendations to solve them. 

A digital workforce can learn, adapt to change their work based on new intelligence.

Most of the value of a digital worker is created after a bot is deployed – that’s because, much like a human employee, if a bot is doing the same thing on day 100 of employment as it was on day 1, a huge opportunity is lost. Through predictive analytics, deep learning, and a continual stream of insights, a digital employee gets smarter over time, providing lasting value.

Olive turns insights into actionable intelligence, identifying potential problems from a mile away, so organizations are learning about solutions before they even learn about the problem. By consuming large amounts of historical data already in your system, Olive finds trends and data anomalies in your workflows and learns to respond the same way a human would – only smarter, faster, and more accurately – making continual improvements to provide better, more meaningful data and insight as she learns. And by pairing a digital employee with key hospital administrators, they can streamline and improve the management of data-heavy tasks like insurance eligibility checks or patient scheduling, using data to uncover and resolve recurring issues.


A digital employee interacts with managers to provide business intelligence and recommendations on improved ways to handle tasks, so they continue to generate value after deployment.
 

Olive works with human managers to determine the best way to communicate actionable insights, and that intelligence gives organizations a ‘Decision Advantage’ over where and how they apply their resources towards current workflow improvements or new candidate processes for automation. 

For instance, at one health system, Olive was hired to automate claim status checks. But unlike a traditional RPA bot, as soon as Olive was live she started collecting data that became actionable insights – like dollar amounts associated with denials – to communicate back to her manager for process improvement opportunities. Based on these learnings, her manager recommended that she focus on a specific subset of denials, which lead to another key discovery: millions of dollars of denials stemmed from a specific drug denial due to missing prior authorizations and medical necessity. This insight allowed the hospital to target a specific department in their organization where this recurring issue could be resolved. This “always on” analysis of information allows a digital employee to proactively offer new solutions for workflow improvements as she gets smarter over time.

A digital employee has Global Awareness and can connect disparate sets of information

Lastly, “global awareness” is another important concept that’s core to a digital employee – the understanding or awareness of information across multiple networks, systems, databases, or contexts. Interoperability is a consistent and growing challenge facing healthcare and the ability for our digital employees to transcend those silos opens up great opportunity. One example is quickly identifying a portal outage and alerting managers before a failure, as well as other organizations where Olives are employed. In the future, it could mean knowing a particular patient’s identity across multiple doctors’ offices or hospitals – even across different systems globally. This identification and matching of people is monumentally important to building the interoperability our industry so desperately needs.


That’s why we built Olive: to work side-by-side with healthcare employees with access to a limitless amount of data. 

As AI becomes more advanced – using applications humans have already developed to organize and interpret larger datasets than a human ever could – the opportunity to build and scale a digital workforce is greater than ever before. And at Olive, we think healthcare employees should handle the functions that are uniquely suited to humans, not the job of data entry clerk or data router. Olive can perform these tasks much more accurately and efficiently, working to resolve recurring issues over time and allowing human employees to focus on higher-value initiatives.

 

Working alongside healthcare employees, Olive is trained to think and make complex decisions that are driven by data. She never misses a day of work. She never makes unprogrammed mistakes. And every Olive learns collectively, like a network, so that healthcare organizations never have to solve the same problem twice. 

We’re making healthcare more efficient, more affordable, and more human with a growing digital workforce, so humans finally have the time, energy, and bandwidth to focus on what matters most: the patient experience. Just think of all the time digital employees will give back to our human employees – clinicians, providers, administrators, payers, and more. And with every organization that employs a digital employee, our ability to carve millions of dollars out of the cost of healthcare will become closer to reality.

If you want to learn more about Olive, contact us to schedule a demo.

 

“Will a Robot Take My Job?”: How to talk with your team about Artificial Intelligence

Artificial intelligence is one of the hottest trends in the healthcare industry (and, let’s face it, just about every other industry right now). People have touted it as the cornerstone of the Fourth Industrial Revolution, which might seem exciting to some of us––but to individuals working in repetitive, task-driven roles, this can take on more of an ominous tone. After all, the past Industrial Revolution completely reshaped the workforce and how humans approached their jobs and livelihoods. Can (and will) automation do the same thing, particularly in the healthcare industry?

In our last webinar with HFMA about optimizing the Revenue Cycle using Artificial Intelligence, several attendees asked us how artificial intelligence will impact their teams and if they should plan to downsize if they intend to introduce automation into their organizations. This is a common concern, and one that we hear time and time again at Olive. In order to help you better weather the storm and start a healthy dialogue about automation with your team, here are a few pointers to get you started. 

1. Frame automation as a solution, not a threat. When discussing the potential for automation within your organization, you can take a similar approach with your fellow leadership and with your own team: rather than taking a doomsday approach, start a brainstorm about how automation can free up your team’s bandwidth, and where those individuals can be leveraged in a way that’s more meaningful to the organization as a whole (and to them!). After spending so long stuck in the status quo, this can be a challenge. Be sure to give all stakeholders plenty of context in advance of your conversation; that way, everyone can come prepared and open-minded to engage on the future of the organization.

2. Make your human team feel….well, human. It’s scary and vulnerable to think of technology invalidating your job, so approach the topic with empathy and optimism when talking with your team. Genuinely listen and respond to your team’s apprehensions in a way that makes them feel supported and appreciated. If you treat your team with respect and openness during these initial conversations, they will be less likely to see automation as a threat to their livelihoods, and more as a tool to help them do their jobs even better than before.

3. Keep them involved. No one likes having a major change dropped on them at the last minute, let alone without their input. Once you start talking with automation vendors about potential workflow solutions, keep your team closely involved––after all, they’re your in-house experts! They are closest to the problem and, if involved in the process from the beginning, they can help your workflow automations truly shine. Make sure that they have a direct line to your workflow automation vendors and that they feel a sense of ownership over the automation project.

    1. Artificial intelligence and automation can have an exponential impact on healthcare organizations’ operational efficiency and care delivery. But the first step to achieving that benefit is to gain buy-in from other stakeholders and especially from your own team. By speaking openly, early, and often about the impact it will have––on your entire organization––you can foster a sense of collective ownership and excitement for, not fear of, the future.

    2. 4. Clarify your intentions and expectations for how artificial intelligence will impact your organization. Some leaders do turn to automation in order to downsize their teams–-and in some cases, it’s the ugly reality of what has to happen for their organization to stay in business. But other leaders look to automation as a way to scale and empower their existing workforce to achieve more than ever before. Having a clear stance on this––and understanding why, as a leader, you need to do this for your organization–will make subsequent conversations easier both for you and your team.

    If you’re starting to explore automating part of your healthcare organization, our team is always happy to help you structure these early-level conversations with your team or with other stakeholders. Reach out to us today to learn more.  Start here with us today.