Dispelling 10 Myths about AI in Healthcare

Dispelling 10 Myths about AI in Healthcare

Depending on whom you ask, artificial intelligence has the potential to transform our economy, take our jobs, overrun the human race, or maybe even a combination of the three. While AI holds a lot of promise, it has also turned into a buzzword that is frequently misunderstood and misapplied to both our lives and our businesses. This is especially true in healthcare, where the promise of better patient outcomes is often overshadowed by the threat of compromised jobs or regulatory red tape. To help set the record straight on the current state of AI in healthcare, we’ve put together a list of the top 10 myths we hear most frequently.

1. There is just one type of AI.

In fact, AI is a blanket term that comprises multiple types of technology, including optical character recognition, natural language processing, and machine intelligence. At its core, artificial intelligence refers to technology that mimics sophisticated human processes in a way that makes it indistinguishable from a human. In this way, our definition of AI comprises not just computer vision and machine intelligence, but also Robotic Process Automation, which automates repetitive, rule-based tasks.

2. Automation will take away more jobs than it creates.

In fact, industry experts speculate that the opposite will happen. The reason why is because AI adoption won’t happen overnight––and when it does happen, it will primarily replace repetitive, lower-skilled jobs that don’t require human traits such as creativity or empathy. This won’t invalidate the need for a human workforce; on the contrary, it will provide an opportunity for jobs to become less menial and more thoughtful.

3. AI is first and foremost a way to cut costs.

Some organizations may turn to AI as a way to cut costs, but that also can be a side-effect of so many other benefits that automation can bring. AI can help organizations improve their efficiency and KPIs, reduce risk, improve employee satisfaction and retention, and more…while also cutting the costs associated with them.

4. AI’s ROI is difficult to calculate.

Because AI is still a new business tool and ROI may not be as cut-and-dry as it is for other, more conventional business tools, many mistakenly think that AI’s ROI is difficult to ascertain and they choose to avoid the perceived risk. However, the key to assessing ROI is to be diligent in measuring your current-day spend––not only in terms of salary and benefits, but also in terms of risk, of extra days in A/R, and any other subsidiary metrics that might be positively influenced by AI. If you choose to work with an automation vendor, they will be able to help you think through the metrics to consider when evaluating AI’s ROI potential. Then, they will help you understand how AI will impact those metrics so that you can generate buy-in from your team––while also feeling confident yourself.

5. AI is a magic fix for your business.

Many organizations think that AI is the “secret sauce” that will help them improve efficiency, reduce costs, and make their employees happier. And while all of those things can and do happen when AI is executed properly, those effects don’t come quite as easily as some may believe. Many AI companies sell insights, not action, to their clients, which means that your organization still needs to do the work in order for AI to have a tangible impact on your business.*

6. AI requires large amounts of data.

It’s true that more data is always better when it comes to artificial intelligence––after all, the more historical data you have at your disposal, the more opportunities you have to “train” an algorithm to act a certain way based on similar data in the future. However, depending on the task that you intend to automate, certain AI frameworks are flexible enough to work with limited subsets of data.

7. Only large companies with in-house IT teams can benefit from AI.

Even as recently as a few years ago, organizations needed to employ a sophisticated internal IT team in order to build, customize, and implement an AI model for their organization. Not so today. At Olive, we’ve seen AI successfully implemented everywhere from the nation’s largest health systems down to 17-bed rural clinics. If your organization is on the smaller size but is still interested in implementing AI, you might consider contracting with a third party to build and manage your automations rather than bringing on extra in-house support.

8. You can’t build AI in-house.

With the advent of cloud technology, it’s easier than ever to create data-intensive automations and harness the power of AI for your organization. This, coupled with robotic process automation and AI platforms, provides organizations with more of a “do-it-yourself” option so that they can harness the benefits of AI without having to rely on external consultants. If you’re trying to determine whether building in-house or hiring an external consultant would be more beneficial for your organization, ask yourself whether AI is a part of your organization’s core competency (meaning, it directly aligns with the value proposition with which you face the market). If AI is a key component to your organization’s value statement, you might want to consider if you have the skills in-house to execute on your workflows. If that isn’t the case for your organization (which it likely is not for a provider), outsourcing your workflow to an automation vendor will help you harness the same impact without straining your internal resources.

9. AI inherently possesses the ability to learn from itself.

AI “learns” by analyzing test data and determining which inputs translated to a given output. It will make its best educated guess based on the data it has at its disposal, but just like humans, it needs additional support to help it differentiate “right” from “wrong.” Often, humans will re-train the algorithm to help it refine its predictions.

10. AI is still too risky to apply to healthcare.

There are too many applications of AI in healthcare––from diagnostics to imaging to revenue cycle management––for reservations to pervade the entire healthcare industry. It’s true that in a clinical setting, AI can pose a greater risk because the stakes of being “right” are much higher. However, administrative AI is a burgeoning subset of healthcare AI that focuses on improving operational efficiency by optimizing data transfers between healthcare tools and systems. In our experience, the impact potential is undeniable: one of our customers was able to reduce their Days in Accounts Receivable by 34% in the first 180 days of using AI to manage their organization’s insurance eligibility checks.



Even though healthcare AI still is a new concept and will continue to be defined over time, early signs indicate that the sky is the limit in terms of its potential to benefit an organization’s operational efficiency. If your organization is looking for ways to harness the power of automation and AI, reach out to us today to learn more.

*That said, Olive isn’t one of those “Brain in a Jar” companies (as we like to call them). Our AI solutions automate your repetitive and high-volume tasks so that you can reap the rewards of AI without having to sacrifice your team’s time and bandwidth.

Olive at Grace Hopper Celebration 2018

Olive at Grace Hopper Celebration 2018

I was fortunate that Olive sent me to attend the Grace Hopper Celebration (#GHC18)in Houston, TX, this year. It was an amazing and inspiring three-day event with 20,000 female technologists from across the globe. I was able to attend workshops and presentations on Artificial Intelligence (AI) and Machine Learning (ML), data and privacy, and career development presented by thought leaders from Google, Amazon, Deep Mind, and other industries.

Best of #GHC18? The best part of my GHC experience was:


A. Building a serverless scheduler web app in Amazon Web Services (AWS) by creating buckets on S3, setting up static website hosting, creating a DynamoDB table to store schedule information, creating and testing three Lambda AWS functions used to add, get, and update calendar sessions, and creating and deploying an Application Program Interface (API) to trigger the new functions.
Hearing a panel discussion on the future of Artificial Intelligence (AI) and General Intelligence (GI) where we discussed the likelihood of reaching GI in our lifetimes, what our ethical responsibilities are as individuals and corporations as we develop new AI technologies, and how to address reward hacking in AI.

B. Learning more about privacy and security in the IoT space, the lack of knowledge on how massive amounts of collected personal information are being shared, lack of consumer control over personal data, and examples of data being used in unexpected ways.
Meeting New People: There are people from all around the world from the heaviest hitting mega-companies to small startups with bold, new ideas. It’s a great opportunity to find out what people across other industries are working on, the challenges they’ve faced, and the technologies and strategies they employ.

C. Inspiration: Attending #GHC18 and hearing the success stories of women further ahead in their careers, learning about their businesses, and hearing how they’re changing the world left me with a huge boost of inspiration to bring back and share with my colleagues.



I’m lucky to be a part of a company that values diversity and encourages growth.
See you at #GHC19!

20,000 women attend the opening keynote address at #GHC18

Robotic Process Automation Vs Machine Learning: What’s the Difference?

Robotic Process Automation Vs Machine Learning: What’s the Difference?

The rapid advancements in automation are revolutionizing business operations for organizations in practically every industry.  As automation technology continues to evolve and uncover new opportunities to showcase its effectiveness, healthcare companies are one of the industries rapidly discovering the benefits of its methodologies.  While hospitals are projected to invest over $50 billion dollars towards artificial intelligence and robotic process automation solutions by 2020, some in the industry are only beginning to look into the potential of these solutions and their game-changing advantages.  After spending time with over 300 revenue cycle and IT executives at Becker’s 4th Annual Health & IT Revenue Cycle conference, our teams at Olive were able to garner some details behind executives’ findings and concerns.  The top 5 takeaways we found include a sense of hesitation regarding the ability to prove ROI, but also reveal that the most agreed upon application of AI will prove its worth most in repetitive high volume tasks like eligibility checks, authorizations, and claims.

Robotic process automation and machine learning are often the two technologies discussed the most when broaching this topic, but what is the difference between the two? Further, which of these two work the best for a given use case?  We’ll discuss the details of both methods and help you answer both of those questions in this piece.

What is robotic process automation?

It’s quite common for robotic process automation (RPA) to be thought of as actual robotic devices performing operations on an assembly line or robot constructs like The Iron Giant and Transformers.  However, robots exist in other forms as part of other technologies like soft-bots, AI, sensor networks, and data analytics. Fundamentally, the simplest way to describe RPA is that it’s a process by which a repeatable rule-based task is executed through an automation solution.

Operating within predefined rules and procedures, RPA solutions are able to complete an action through a machine that would normally require human interaction.  Whether the task is in a factory environment or office space, RPA can help with the construction of a component for a finished product or even help office productivity by brewing coffee through Wi-Fi enabled coffee makers.  Because RPA solutions require a thoroughly practiced, documented, and familiar procedure to fulfill its automation benefits, some believe it will eliminate the need for humans in some areas, however, that isn’t really the case.  RPA is designed to handle the tedious repetitive tasks humans currently must do, enabling enhanced human productivity by allowing humans to focus on the more complex and creative tasks they excel at.

Sometimes considered to be the most basic form of AI, robotic process automation is best utilized in business practices that require little skill and are performed under set parameters including how often a task needs to be executed and within specified timeframes.  In healthcare applications, RPA reaps loads of benefits by allowing skilled and/or specialized staff to focus their attention towards tasks that require human cognition and subjective decision making. There are often instances within hospitals where employees with clinical skills, such as nurses and aides, are tasked with additional tasks of insurance verification and data recording.  While these responsibilities are expected within their roles along with other staff members, these duties are ideal for an RPA solution to tackle. Having these non-clinical jobs being addressed through automation allows for staff to concentrate their attention on their principal tasks better suited for their skills of patient care and advocacy.

Studies have already shown that the increase of automation in processing medical records and documentation has led to a 15% decrease in the odds of in-hospital deaths and administrations that have adopted RPA have seen a 200% ROI within the first year of use (Olive AI white paper). As the U.S. nears a projected shortage of 250,000 nurses by 2025, identifying and implementing automation solutions within healthcare infrastructures has become a much more pressing need thus allowing clinical staff to dedicate their abilities towards tasks exhibiting their skillsets.

What is machine learning?

Similar to robotic process automation, the primary objective of machine learning (ML) is to also have computing technology mimic human operations.  However, where RPA is required to operate within a rule and process-based environment that limits decision making under unfamiliar situations, ML truly expresses its artificial intelligence as a learning resource exhibiting what most feel is the biggest characteristic of AI; adaptation.  Simply put, RPA acts more like a straightforward resource that executes actions based on its configuration, which places it in more of a grunt perspective with little freedom to “think” outside the box or exhibit any learning abilities. Machine learning, on the other hand, autonomously improves its performance over time, like humans, as the system is provided with observational data and real-world interaction.  Some have even made the comparison between the two as brains over brawn with ML being the former.

In the healthcare industry, ML also adds exponential benefits to administrations acting as the router between systems and data by automating repetitive high traffic tasks.  Serving as its own employee within an organization, an ML solution utilizes its own credentials to access system databases to record and report patient information or EHR (electronic health record).  By following the local credential structure, this allows for seamless integration into existing systems with little change to accommodate its inclusion and no additional workflows. For example, our Olive AI can be used to perform patient insurance eligibility checks.  After reviewing the patient record and history from their respective EHR, Olive can assist with checking against insurance eligibility portals. With a baseline of information gathered, the system can then proceed to offer approved solutions, compare previously approved authorizations, schedule future appointments and post-visit follow-ups, and payments.  Having this level of automation 24/7 365 days of the year empowers hospital and clinic staff to center attention towards their most critical role of patient care.

An article published in Healthcare IT News reported a prediction from IDC (International Data Corporation) that global investment towards AI solutions will jump 60% this year totaling $12.5 billion and then up to $46 billion by 2020.  As automation continues its seemingly endless upward trend and creates countless prospective breakthroughs in practically every industry, machine learning continues to be a key proponent towards technological advancement.


So which one is better?

To answer this question, decision-makers and executives must first determine their most critical business needs that can be best be improved through automation.  Overall, robotic process automation and machine learning are both invaluable solutions that are sure to drastically enhance business performance for any organization.  Some businesses may opt to incorporate an RPA option in order to automate their easier low skill functions as this will require little effort to integrate and in the smallest amount of time.  Other organizations have decided to use RPA as a starting point in their AI implementation with machine learning as their end goal for automation. Nonetheless, having discussed the capabilities of both RPA and ML, it seems the only one who can determine which is better for a business is the business itself based on their requirements and ultimately the option that will provide the highest ROI over time.

At Olive, we strive to build revolutionary artificial intelligence and robotic process automation solutions for the healthcare industry that layer in ML for a more robust robotic process automation solution. Our focus is on improving business productivity through automation of the error-prone and mundane tasks of healthcare administration so that staff can focus on patient care.  Our efficient cost-reducing options continue to deliver immediate positive results with Olive AI overseeing repetitious high traffic processes and workflows. These specialized tools empower our customers with the freedom to let their teams express the creativity and empathy that only a person is able to provide.  Please contact us to schedule a demo of our Olive AI and let us begin developing a solution that can address your automation demands and be your first step towards an AI environment.

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

“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.

    Navigating AI and RPA in Healthcare: Top 5 Takeaways from Becker’s HIT 2018

    Navigating AI and RPA in Healthcare: Top 5 Takeaways from Becker’s HIT 2018

    We’re back at Olive HQ after an invigorating week at Becker’s 4th Annual Health IT & Revenue Cycle Conference. We spent time with over 300 Rev Cycle and IT executives in Chicago. Through our conversations, one thing is clear – top hospital systems and executives are actively seeking to determine artificial intelligence and RPA’s (robotic process automation) place in their organizations.


    Hospitals are forecasted to spend over $50 billion dollars on AI related technologies by 2020, according to Healthcare IT News. Yet, many are only beginning their evaluation of AI. So what are these leaders saying about AI and automation in healthcare? Here are five key insights we identified from our conversations with them:


    1. 58% of revenue cycle and IT executives are simply trying to understand the hospital applications of AI and whether it makes sense for their organization

    2. Healthcare organizations are looking for AI to capture missing revenue, increase accuracy of patient information captured and help with new tasks & processes

    3. AI still doesn’t feel “easy” or “accessible” to healthcare executives.  There are lingering questions on reliability, ROI, and organizational fit

    4. Leaders in Healthcare believe the best applications of AI across the Revenue Cycle are eligibility checks, prior authorizations and claims processing

    5. AI and Automation is poised to provide the quickest ROI when matched with repetitive, high volume tasks across the Revenue Cycle

    Wondering how you can apply AI and RPA successfully in your organization? As a healthcare-exclusive AI and RPA company, Olive can help you identify the right approach to applying AI in your hospital.  Start here with us today.

    Customers Can’t Tell You What To Build

    Customers Can’t Tell You What To Build

    It’s Your Job To Figure That Out

    When you’re building a product for someone, the first thing you need to know is that your customer probably doesn’t care.

    They will care. Once you’ve finished the product, put it in their hands, and made their life better, then they will care.

    For about as long as it takes them to remember that lunch is in an hour. Then they’re back to not caring.

    Such is the life of a product creator. It’s your job to create something new for customers, but it’s not their job to care. This can seem disrespectful. You slaved away, building this product for them. You’ve sacrificed weeks, months, years of your life to make this — and they can’t be bothered to give you a little feedback?

    You might feel entitled to at least some attention. You are, after all, building a product for them. Surely they can take some time out of their day to tell you what you should make.

    But they won’t, for a couple of reasons:

    1. They don’t care enough to. They have a million other things going on in their life. Things more important than telling a programmer how to do their job.
    2. They’re too busy to. Chances are, they’re busy building something else for someone else. They don’t have time to sit down and go over the product with you.
    3. They don’t know how. They don’t have the skills to create the products they use, and they don’t have the bandwidth to sit around and come up with ways the product could be different. Studies have shown that the only feedback they can give you is feedback about what they’ve already used, not what’s possible. (Considering what’s possible is your job).

    They don’t because it isn’t worth their time. People value their own time. “The majority (66%) of adults feel that valuing their time is the most important thing a company can do to provide them with good online customer experience.”

    That doesn’t mean it isn’t worth your time, because it is. The reason customers won’t give you attention isn’t that your work doesn’t matter; it’s because they have delegated the work to you and trust you to get it done. The highest authority in any business isn’t the CEO or the board, but the customers. It’s their money that pays the bills.

    It’s your job to solve their problem, and to solve it with as little support as possible.

    To some people, that sounds harsh. ‘You expect me to solve your problem, without your help?’ It can even seem like a tautology; how do you solve a problem you know nothing about?

    In reality, it’s honorable work to have. And deep down inside, you know this. You’re in this position because you decided to make building products for other people your job. You made it your job (hopefully) not because you thought you’d get rich, or because it was easy, but because you find meaning in the work. Appealing to customers to tell you what to do not only produces a worse product; it takes the challenge and the honor out of doing it.

    That said, you want to stay receptive to any feedback they have without forcing them to give it. People may not be able to imagine what will make them happy, but they can tell you how they feel about what’s in front of them right now.

    Not getting in the customer’s way is almost as important as making the product in the first place. One study showed that 74% of customers are likely to switch brands if they find the buying experience difficult, no matter how awesome the product. This is a painful loss because it costs anywhere from 5 to 25 times as much to acquire a new customer as it does to keep a current one.

    If your customers could help you that much, you’d be out of a job.

    As it so happens, they can’t. By virtue of their position, they lack the objectivity they need to understand their problems. By virtue of their jobs, they lack the skills necessary to engineer a solution to their problems. And by virtue of their daily responsibilities, they lack the vision to consider other possibilities.

    “I think Henry Ford once said, ‘If I’d asked customers what they wanted, they would have told me, “A faster horse!”’ People don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.”
    Steve Jobs

    Your customers may not be able to actively help you, but they are still a valuable source of information. Their behavior is feedback in and of itself.

    • If they receive what you build with no comment, it communicates something. It could mean that your solution is so compelling that they don’t need to worry about it anymore. Or it could mean they’re not using your solution because their previous one is easier for them.
    • If they react positively, that doesn’t mean it’s time to pump the breaks. It means whatever you’re doing, you’re doing right. You should be doing more of it.
    • If they receive your product with reluctance (or outright complaints), it means you’ve taken a wrong turn. Don’t wait until they complain about the product or cancel their service. Make sure to identify what’s causing the friction and solve it before it becomes a more significant problem.

    “The best customer service is if the customer doesn’t need to call you, doesn’t need to talk to you. It just works.”
    Jeff Bezos

    It’s an honor to create products for people. Nothing matches the satisfaction you get when you see something you made changing the lives of countless other people. People are leaving it up to you to create something for them. And when they start using it, you know it isn’t because someone forced it on them, but because it makes their life better.

    At Olive, we make Artificial Intelligence for doctor’s offices and hospitals that handle administrative tasks, so healthcare employees can do what they do best — take care of their patients. Check out our website to learn more.

    Welcoming Olive to the Oak HC/FT Family!

    Welcoming Olive to the Oak HC/FT Family!

    Originally published on Oak HC/FT

    Today, we led the Series D financing in Olive (formerly known as CrossChx), the leading healthcare provider of robotic process automation (“RPA”) tools. Through its eponymous platform, the company streamlines repetitive, high-volume tasks by leveraging the systems and tools that its customers already have in place without complex integrations. Leveraging AI, Olive helps hospitals and health systems reduce costs, eliminate clerical error, boost efficiency, and improve satisfaction.

    Our investment in Olive is the result of our thematic pursuit for solutions that help drive efficiency and lower costs using automation technology. While Olive is not unique in providing RPA solutions, we have yet to come across another company with as much proven expertise in solving challenges unique to healthcare. Sean Lane, the CEO and founder of Olive, and his team have developed a platform that delivers an immense amount of value without needing to fundamentally change the way its customers do business.

    We spoke with many of Olive’s customers all of whom confirmed how integral the technology has become to their day-to-day operations. Many users referred to Olive as another member of their team, describing the work “she” did, stating they couldn’t imagine their workflow without “her.” This is the sort of thing that really underscores how Olive goes far beyond a typical software solution.

    The use cases for Olive within the healthcare ecosystem are seemingly endless and we see them as only continuing to grow as the company expands with next-generation technology like Pupil, the company’s process mining solution. We look forward to partnering with the company to support growth strategies and scale the business. Alongside Ascension Ventures, Drive Capital, SVB Capital, and the other existing investors participating in this round, we at Oak HC/FT could not be more excited to partner with Sean and his team on their journey.

    Olive (f/k/a CrossChx) Closes $32.8 Million Series D Financing

    Olive (f/k/a CrossChx) Closes $32.8 Million Series D Financing

    Funding led by Oak HC/FT and Ascension Ventures to enable company to accelerate product development and scale its technology to healthcare organizations nationwide

    CrossChx rebrands itself as Olive to reflect commitment to building meaningful AI-enabled robotic process automation solutions for healthcare

    COLUMBUS OH, July 30, 2018—Olive, the premier healthcare-focused robotic process automation and artificial intelligence company, announced today that it has raised a $32.8 million Series D round from Oak HC/FT and Ascension Ventures with participation from existing investors. The round will help the company scale its eponymous AI solution, Olive, throughout healthcare organizations nationwide and invest in new capabilities such as Pupil, its process mining tool, that will be launched at alpha sites this summer.

    “Hospital operations have grown unsustainably complex as providers must adopt new technologies, workflows, and regulations with increasing frequency in order to provide best-practice care,” added John Kuelper, Investment Director at Ascension Ventures. “Olive’s cutting-edge process mining and automation technologies are enabling our firm’s health system partners to continually optimize clinical and administrative operations so caregivers can spend more of their time on patient care.”

    “Olive arrives at a time when healthcare organizations are burdened with improving efficiency, reducing costs, and enhancing the patient experience,” said Sean Lane, Founder and CEO of Olive. “Olive handles repetitive, high-volume tasks, which allows employees to get back to patient care and presents healthcare organizations with value that could not otherwise be realized.”

    “As the first healthcare automation solution on the market using AI to streamline repetitive tasks and workflows by working with existing systems, Olive is uniquely positioned to counteract the ever-increasing cost of healthcare and humanize the cumbersome process,” said Billy Deitch, Principal at Oak HC/FT. “We are excited to partner with Olive to deploy its innovative technology at scale.”

    Billy Deitch, Principal at Oak HC/FT and John Kuelper, Investment Director at Ascension Ventures, will join the company’s board of directors.

    Earlier this year, Olive divested its legacy Connect platform and related products including Connect biometrics, Queue registration kiosk, and the CrossChx Connect mobile app to DHS Group.

    Olive is a healthcare-specific artificial intelligence and process automation company that empowers healthcare organizations to improve efficiency and patient care while reducing costly administrative errors. Its eponymous AI solution, Olive, acts as the intelligent router between systems and data by automating repetitive, high-volume tasks and workflows, providing true interoperability. Olive has helped healthcare organizations reduce data and billing errors, eliminate denials for no coverage, improve cash collections by reducing days in A/R, and more. To learn more and receive updates, visit www.oliveai.com.

    Founded in 2014, Oak HC/FT (http://oakhcft.com) is the premier venture growth-equity fund investing in Healthcare Information & Services (“HC”) and Financial Services Technology (“FT”). With $1.1 billion in assets under management, we are focused on driving transformation in these industries by providing entrepreneurs and companies with strategic counsel, board-level participation, business plan execution and access to our extensive network of industry leaders. Oak HC/FT is headquartered in Greenwich, CT with offices in Boston and San Francisco. Follow Oak HC/FT on Twitter, LinkedIn and Medium.

    Ascension Ventures is a strategic healthcare investment firm with four funds and more than $800 million in capital under management. The firm was launched in 2001 by Ascension, the nation’s largest Catholic and non-profit health system, and today invests on behalf of thirteen of the nation’s leading community health systems. These health system limited partners collectively operate 474 hospitals, have 578,000 employees and generate $88 billion in annual revenue. AV collaborates with these partners to identify, invest in, and support strategically aligned private companies that are transforming the healthcare industry and enhancing the experience for patients, their families, and caregivers.

    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.

    Why Optimism is Important

    Why Optimism is Important

    Throughout the life cycle of a product there will be ups and downs. Times when the hype is high, and times when the path forward is uncertain. These waves put pressure on the Product Manager to constantly lead, no matter the situation. What if you’re not sure that the company is moving in the right direction? Or you’re not confident in the performance of an upcoming release?

    If you feel this, you’re likely not alone, but as the leader of the product, you must project optimism in order to keep your team with you.

    Whether you like it or not, people are looking at you. They pick up on your expressions, your reactions, and your attitude. When you are bearish on a decision, that attitude has a way of permeating through the product team and other stakeholders. People will divest in the effort and become skeptical about the path. Projecting optimism will do just the opposite. Showing that you’re confident in a positive outcome will give the rest of your team something positive to look forward to. It will keep those around you calm in the face of uncertainty, and will give them a reason to follow you. It will even give your team confidence that a solution can be found in difficult situations.

    Successful PdMs will need to lead teams and products through thick and thin. Being optimistic about your future and confident in your decisions will keep you and your team feeling positive and focused on moving forward. Next time you notice confidence weaning on your team, try projecting optimism about the situation, because if you don’t—who will?