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.

 

AI Will Make Healthcare More Human Than Ever. Here’s How.

AI Will Make Healthcare More Human Than Ever. Here’s How.

Originally published in Health:Further

With the rise of robotics and AI across virtually every industry, the fear of “will a robot take my job?” is more pressing than ever. In the healthcare world, at least, that future couldn’t come soon enough.

The U.S. healthcare system is advanced in so many ways, yet one of the most glaring problems that still plagues it is a lack of interoperability, or as we like to say, the lack of the “Internet of Healthcare (IoH).” In the literal sense, the Internet of Healthcare means connecting networks—connecting health systems, connecting data, connecting patient information and more. It means turning healthcare from a series of intranets connected by fax machines, to a true internet connected by AI as the “router.”

That’s a far cry from the healthcare experience we face now. Today, just getting into a hospital requires mountains of paperwork, faxes, and family medical histories that often take longer to fill out than the hospital visit itself. In one of the most vulnerable and human professions that exists, patients are left feeling like just a number.

The reason this exists is because our existing healthcare technologies were not built to share data. They were built as fortresses to protect the data of patients at each instance, and to make sure that data was available only within the walls of that system.

 

 

As a result, humans had to take on the job of the router, the data processor, the transmitter. This phenomenon has shifted the hours spent by humans from being in front of patients to being in front of computer screens, logged in to many user interfaces, shepherding patient data into the right fields. Licensed caregivers’ quality of life have been pummeled by this new role, and the consequence comes in the form of burnt-out employees, skyrocketing administrative costs, less human-to-human experiences, and most importantly, subsequent decreased quality of care.

It’s easy to throw stones at the software that exists and excoriate them for their lack of data sharing capabilities. However, they were just a product of the requirements they had to meet to become certified and meet a rather daunting set of standards imposed by the federal government. It’s not clear that data sharing should have been introduced into the requirements framework earlier or more aggressively, and it’s not clear if diagnosing that now does us any good. The reality that exists with healthcare technology is that we now have to figure out how to scale that technology to the next level.

We think AI is the solution to scaling that technology, to taking the robot out of the human and propelling human potential further than we’ve ever seen it.

So, what does the world look like when we “take the robot out of the human?” I won’t comment on what it will look like in other industries, but here’s how I see it playing out in the healthcare industry.

1. Insured patients no longer incur unexpected out-of-pocket costs because of registration issues or human error. Instead of filling out insurance information at intake, AI helps hospitals understand patients’ coverage before they even set foot through the door. The same people who spend their days inputting information into EMRs can focus on actually talking to, and understanding, the patients who are there to see them.

2. Patients’ identities are reconciled across multiple departments, even multiple hospitals. By knowing exactly who is coming through the door, and why, AI helps hospitals cut down on doctor-shopping and drastically reduce overdoses on prescription medications.

3. Ride-sharing vehicles are dispatched to the patients who need them the most. Instead of relying on patients to find their own way to the hospital, AI detects which patients have the greatest no-show risk, then dispatches a vehicle to get them the care they need, when they need it.

4. Patients are seamlessly matched to cutting-edge technologies and clinical trials. Finding clinical trial participants can be like finding a needle in a haystack, and it can be the difference between life and death for tens of thousands of people every year. AI gives us the framework not just to enrich those lives, but to save them altogether.

5. Clinicians no longer spend six hours a day entering data into an EMR. Instead, AI transcribes notes from each patient exam and submit them for approval. Burnout decreases, energy improves, and clinicians get to spend their time doing what they care about most.

What’s common about all of those experiences? Humans aren’t out of the picture. In fact, they’re more a part of the picture than they are today. With AI as the router, humans finally have the time, the energy, and the bandwidth to focus on what matters most: the patient.

The current zeitgeist around AI is trepidation about whether or not it will take human jobs, but I believe we will be able to achieve so much more as a humankind with the assistance of AI. It’s true, AI will certainly take parts of our jobs, reconfigure our jobs, but that’s exactly what we need in healthcare today.

We can use AI to take over the Button Olympics that humans are enduring in hospitals across the country. AI can transmit the data where it needs to go, and use global awareness to ensure the right data goes to the right place. AI can turn the human-powered Internet of Healthcare into a technology-powered internet, without having to overhaul the immense infrastructure that has already been put into place. With AI doing all of these things, humans can focus more on creativity and empathy, on the skills that no machine can recreate.

AI largely is not trying to replace humans, just trying to replace some of what humans do. Imagine what healthcare would be like if we could take the robot out of the human. Think about how much better off, and happier, and more fulfilled, the workforce would be. That’s the world I am dedicated to building.