Category: Featured

Halfway Through 2018 – Where Is Healthcare Headed?

With the first half of the year behind us, we thought we’d share some of the current healthcare trends that are gaining traction in this week’s blog post.  We’ve outlined the top four to keep watch for over the remainder of 2018.

Revenue Cycle Management – Providers recognize the need for more efficient revenue cycle management (RCM) operations to collect payment for services. Implementing RCM technology can help organizations automate this process. In fact, Health Data Management recently named MedeAnalytics to its list of 20 leading revenue cycle management vendors.

In our blog post by Tom Schaal, director of product management, he outlines the need for healthcare organizations to prioritize and develop a RCM strategy that addresses cash collections, bad debt, denials, productivity and what providers should look for in an analytics partner.

Artificial Intelligence – AI is still top of mind and according to research from Accenture, healthcare’s AI market could increase to $6.6 billion by 2021. Many executives think it could take over some clinical tasks, leaving providers with more time to focus on patients. Google is dominating this space in healthcare by debuting its Google Duplex and developing ways for machines to diagnose patients – much like a physician would do.

But staying ahead of the of AI curve can be challenging. Our blog post from Tyler Downs, chief technology officer, offers advice for healthcare organizations to achieve success, like adopting security applications and making sure they have the right team to develop AI.

Prescriptions to Your Door – Amazon has been making headlines in the past few months, from choosing its new CEO for its mega-merger with JP Morgan and Berkshire Hathaway to announcing its plans to purchase PillPack which offers presorted medication and home delivery. Could PillPack soon be a part of the Amazon Prime membership? It’s possible that prescriptions will quickly be delivered in a cost-effective way right to your doorstep.

Doctors Embracing Consumer Membership Fees – Growing patient and physician frustrations around healthcare costs have led to the rise of doctors embracing their own membership fees. In lieu of working with payers under the traditional structure, physicians across the country are opting for a membership model where patients pay these monthly membership fees for their services.

According to a direct primary care physician, there could be as many as 800 direct primary care practices across the U.S., which could increase in the next few years if healthcare costs continue to rise.

Bottom line: the healthcare landscape is always changing, and organizations need to stay on top of trends. MedeAnalytics partners with clients to help them solve these ever-changing challenges. To learn more about how we can help you, contact us here.

California mandate to lower C-sections will impact population health – how can analytics help?

Following a surge of cesarean section (C-section) operations for expecting mothers, doctors in California must now reduce the number of C-sections performed to 23.9 percent for low-risk births. The state’s health insurance marketplace under the Affordable Care Act, Covered California, wants to curb this rate to improve patient safety and quality. Any hospital that doesn’t meet these metrics runs the risk of being removed from the state’s health insurance marketplace as an in-network provider. Currently, most hospitals in California deliver around 40 percent of their babies via C-section.

The medical rationale for reducing the rate of C-sections is strong. C-sections can expose a woman to unnecessary risks such as infection, hemorrhage or even death. Studies also show babies born by C-section have a higher risk of complications and spending more time in the neonatal intensive care unit. We talked to Bruce Carver, Associate Vice President of payer services at MedeAnalytics, about this new mandate and how data analytics can be leveraged to address it.

How could this approach impact hospitals in California?

There are some factors that would be beneficial for Covered California to keep in mind. Reaching the goal ultimately falls on the provider, who is giving patients that care. But hospitals should be examined on a case by case basis if they are not meeting the metric, because removing them from the insurance marketplace could have a huge impact on providers and members, especially in rural areas. 1.4 million people in California purchase their health insurance through 11 insurers on the state exchange. Additionally, there could be valid, uncontrollable reasons why a hospital might miss the metric. But, of the 243 maternity hospitals in the state, 40 percent have already met this target.

How can analytics play a role?

Analytics can ensure health plans are appropriately enforcing such utilization management requirements. For example, they can analyze if the problem exists with a certain market or provider. The real problem is not actually tracking these initiatives, but figuring out what action will illicit the desired outcome. Additionally, health plans are always at risk of losing member utilization through a third party contracting entity that could offer a lower price than the health plan itself. In this circumstance, the health plan does not have knowledge of such services or utilization.

How can Covered California achieve its goal?

To be successful, Covered California should allow data to drive the best decision to achieve the desired outcome, in this case, lowering the C-section rate to 23.9 percent. Over time, analytics can provide the retrospective insight to develop more predictive models that address cost and utilization issues before they have a significant impact on costs. Getting ahead of these issues early can often keep organizations from having to put out these mandates in the first place to correct the market.

MedeAnalytics can help your plan get control of its population health by using data analytics to communicate gaps in care to physicians and improve care coordination. Visit our Population Health page here to learn more, or contact us here.

How can Analytics Help Solve Healthcare’s Biggest RCM Issues?

Revenue cycle management (RCM) is a critical part of any healthcare operation and with rising healthcare costs it’s even more difficult to manage. However, to better handle costs and overall revenue, healthcare organizations need to prioritize and develop an RCM strategy. The strategy itself needs to address various revenue pain points, including: cash collections, bad debt, denials, productivity and overall business strategy. We recently connected with Tom Schaal, director of product management at MedeAnalytics, to better understand what’s holding healthcare organizations back from addressing these pain points and what to look for in an analytics partner.

RCM Challenges

  • The Need to Do More with Less – Margins are shrinking across the board and a lot is changing, especially with value-based reimbursement expected to represent 83 percent of provider revenue by 2020. Provider organizations are struggling to meet quality metrics, not to mention, the added reporting required under MACRA and MIPS. With physician burnout and overall healthcare costs at an all-time high, organizations are looking to cut back anywhere they can.
  • Disparate Solutions – According to a recent survey, almost 69 percent of healthcare organizations are using more than one vendor solution for revenue cycle management. This means different numbers, screens, reports, siloed data and inefficiencies.
  • Lack of Actionable Insights – Many solutions aim to consolidate data, but significant challenges still exist when it comes to sharing that data. Some providers are leveraging data visualization tools to bring information together, but issues arise when it comes time to draw actionable and timely insights from it and hinders organizations from understanding how to adjust their RCM operations.

What to Look for in an Analytics Partner

  • Strong Industry Knowledge – The most important step when finding an analytics partner is to select an organization that has a strong background in healthcare. A vendor who knows the industry top to bottom that can help your organization stay up to date on the latest trends, policies and technology. You want to also ensure you are selecting a partner that allows for unification and normalization across the board so there is complete transparency and a single source of truth.
  • Action, Action, Action – Having the right RCM data is one thing, but what good is data if you can’t do anything with it? An analytics partner can use your data to draw actionable insights that will not only make a difference in your organization’s bottom line, but also in its overall success.
  • More Time to Focus on What’s Most Important – At the end of the day, healthcare organizations have one overarching goal: provide patients with quality care. With a strong analytics partner, providers can spend less time worrying about issues or processes and spend more time focusing on quality care.

MedeAnalytics offers a suite of analytics solutions, including a business office platform that can help you get big-picture insight into your revenue cycle. With a background cemented in the healthcare industry, our team understands all the critical nuances that come with it. Our analytics tools and offerings draw critical and timely insights that can help your organization make even smarter decisions. To learn how we can help support your organization in addressing its RCM, check out more here. Contact us here.

Payer and Provider Collaboration Ensures the Industry is Tracking Towards Value

Collaboration between payers and providers is an important asset to improving quality of care across the healthcare ecosystem, while simultaneously keeping costs down. For example, payers have access to a significant number of claims data that creates a holistic view of patients’ information, while providers typically have discrete clinical data information. By working together to exchange this information, payers and providers can stay on top of patients and ensure they are getting quality care and avoiding high-cost events, such as visits to the emergency room. Also, with value-based care top of mind, payers and providers need to work together to leverage data and analytics to reach that end goal. We talked to Bruce Carver, Associate Vice President of payer services at MedeAnalytics, for his insight on the current challenges that prevent payer-provider collaboration, best practices to achieve it and why it’s useful.

Challenges that can arise within collaboration

When it comes to payers exchanging information with providers, storing clinical data received from an electronic medical record (EMR) is very expensive. There is no standard format across the U.S. for providers to implement that information simultaneously. Oftentimes, payers don’t want to add another system to store that information, instead integrating it through an EMR that can be sent out from a provider’s system and to a payer. In addition, providers have access to more timely data as well, enabling immediate outreach to patients. Ultimately, collaboration is needed so both the payer and provider are on the same page when it comes to treating patients. If either doesn’t have the complete information, it can result in gaps in care and ineffective treatment.

How analytics can help

Analytics can provide additional ways that a provider and payer can exchange that clinical information. In an EMR, there are hundreds of different measures and metrics that are collected within that provider’s system but oftentimes only a small portion of that is necessary to be able to collaborate effectively for the value-based programs that are in place. MedeAnalytics has enabled external use of its platform by a provider to be able to attach and upload that information straight into an analytic tool that is used to measure results of the program, which makes for a more cost-effective solution.

Additionally, focusing analytics on three areas can help save costs:

  • The individual market – Analyzing the market can allow payers to make strategic decisions on how to approach and cater to specific member populations.
  • Gaps in care – A prospective look at gaps in care ensures that patients are getting the care they need, both preventative and specific to any chronic conditions. The goal is keeping healthy patients healthy and managing those with chronic conditions to keep them from requiring high-cost services like emergency room visits or hospital admission.
  • High costs – If organizations can establish where they are spending the most, they can work to lower those expenses throughout the year.

How patients can be managed

With quality care for patients being top of mind for both payers and providers, exchanging valuable information to stay on top of at-risk and high-risk patients can also lower costs. For example, if a diabetic patient stopped attending physician visits, or stopped refilling prescriptions, payers can alert providers to get that patient back on track. That in turn could save individuals from future emergency room visits which are costly for the payer, and potentially catastrophic for the patient. And with a value-based care mindset, it is in a provider’s best interest to keep that patient well and on their health plan. Further, providers can alert payers to which patients are not being treated in preventative care appointments, and by remedying this, can prevent at-risk patients from becoming high-cost, by putting them on a long-term plan to keep them healthy, which saves money for the payer.

When done effectively, payer and provider collaboration can mean better care for the patient and a drive towards value-based care. It’s all about making the most of your analytics investment, building trust and effective communication, as Bruce outlines here. To learn how MedeAnalytics can help your organizations collaborate with payers and providers, visit our population health solution page here or our healthcare economics solution page here.

Managing high-cost members with analytics

As the health demands of patients expand, payers are increasingly focused on a small segment of their member population that is driving the largest share of healthcare spending: high-cost members. According to the American Health Policy Institute, these high-need, high-cost individuals can cost $100,000 every year, which accounts for one-third of total healthcare spending.

As a result, payers are looking for new ways to identify and engage with these individuals using analytic tools. We recently spoke with Diane Gerdes, payer product marketing manager at MedeAnalytics, for her input on the value of using data analytics to address high-cost members’ needs and costs.

What challenges are payers facing when it comes to understanding high-cost members?

For many organizations, the biggest challenge is identifying individuals before they become a high-cost member. These individuals are dealing with acute and chronic conditions and possibly taking expensive prescription medications. Typically, it isn’t until a costly event like a hospitalization that problems finally come to the surface. Adding to this challenge is predicting who will continue to be a high-cost member in the long-term. That’s where advanced analytics can help by targeting individuals who are high-cost or at-risk and giving payers the insight to design proactive solutions that keep members healthy and minimize costly adverse health events.

What pain points do payers face around integrating and analyzing large amounts of data?

General pain points center around the overall process for collecting, integrating and analyzing data. Because data is typically housed in various operational and clinical systems, it takes an extraordinary amount of time and effort to organize and mine the data. By the time the data is ready for analysis, it is no longer timely, and payers miss critical opportunities to intervene and engage with members. 

Can you share more on how analytics can help?

Analytics can help payers take a more proactive approach by uncovering opportunities to impact high-cost members earlier. An intelligent analytics platform that efficiently gathers data across all systems (e.g., medical, pharmacy, lab) helps payers more quickly target individuals who have chronic conditions or who are at-risk, as well as those who are not complying with evidence-based guidelines. Payers armed with this insight are better positioned to align programs (e.g., care management and preventive care) and intervene with individuals before their conditions progress into complex, high-cost conditions. Solutions like MedeAnalytics’ Healthcare Economics makes data accessible and approachable, and empowers payers to make faster, smarter decisions that lead to improved outcomes.

MedeAnalytics worked successfully with St. Joseph Hospital, a part of Covenant Health, to help them identify and target those at risk for high-cost care within their own workforce. St. Joseph Hospital leveraged data and analytics to improve care for their employees and families, while also designing benefit plans and cutting costs. The hospital’s data revealed just 9 percent of the highest risk employees were responsible for 40 percent of employee health plan costs. Analyzing their employee data allowed the organization to identify exactly where the money was being spent and make changes regarding pharmaceutical costs and benefit plans, which put them on track to spend $2.5 million less the following year.

The challenges facing payers are endless but with the investment and use of data analytics, organizations can make even smarter decisions about the members they serve. To learn more about St. Joseph Hospital’s success – click here. Interested in learning how we can help your organization achieve similar results and combat high-cost members? Visit our solutions page here.

As costs go up, how can the industry adapt?

Healthcare costs continue to rise across the industry. According to a study published in the Journal of the American Medical Association, money spent on healthcare in the U.S. is nearly twice as high as 10 high-income countries. Not only does the U.S. have the highest percentage of obese adults but it also has the lowest life expectancy and the highest infant mortality rates compared to 10 high-income counties. What’s driving these costs? According to Harvard researchers, prescription drug prices and administrative costs are the main culprits.

Prescription Drug Prices

Prescription drug costs are high, not only for payers, but also for the patients that need these life-saving drugs. Unfortunately, treatment for some diseases can cost nearly a million dollars as one Wall Street Journal article explores. The administration is looking to put policies in place to cut costs, but what can be done at the health system level to help these efforts?

St. Joseph Hospital, part of Covenant Health, leverages MedeAnalytics to analyze their pharmaceutical spend and identify cost saving opportunities. The health system found that an extremely high percentage of their pharma spend came from specialty drugs. They were able to identify $100,000 in potential savings, just from generic drug substitution in three therapeutic classes where generic equivalents were available. Additionally, pharmaceutical data revealed one patient with a single drug at a special dosage cost $700 for a 30-day supply. Using analytics, the organization confirmed the cost was correct but also found other patients who were taking the same drug in a smaller dosage two or three times a day, had a significantly lower cost. By simply changing the dosage, they reduced the cost from $700 to just $9 a month. Download our case study to learn more on how St. Joseph Hospital cut costs around their pharma spend.

Administrative Costs

Costs related to planning, regulating and managing a health system account for eight percent of total spend in the U.S. compared to one to three percent in other countries. Health plans are always looking to improve efficiency, grow revenue and reduce overall costs, especially at the operating level but frequently run into roadblocks.

Presbyterian Health System (PHS), an integrated delivery system with eight hospitals in New Mexico, understands the challenges of balancing costs, utilization and quality all too well, as the organization struggled to oversee its entire business from one integrated view. However, after they partnered with MedeAnalytics, PHS was able to achieve measurable ROI in their financial, clinical and operational areas while reducing redundancies. For more on their approach to cut administrative costs, view here.

Despite the high cost of care facing the country, the U.S. is spearheading critical research into drugs, treatment and approaches that will change the state of care for so many patients. Learn more about how our analytics solutions can help you uncover insights to support your organization during these changing times.  You can view our solutions here or contact us here.

Health IT Springs Into Action: What We Can Expect In Q2

Despite record-breaking snow storms covering parts of the country last week, spring is officially here! This winter was a busy one for the healthcare industry with another HIMSS conference, along with major news from companies including, CVS and Aetna to Amazon, JPM and Berkshire Hathaway. As the weather (hopefully) warms, the industry will continue to buzz with breaking announcements and happenings. We’ve outlined some of our predictions in the upcoming months.

Better Manage the High Costs of Healthcare  

Despite U.S. healthcare costs nearly twice as high as other high-income countries, all of the money spent on healthcare in the U.S. is not paying off. A Harvard University report found that costs are largely attributed to prescription drug prices, administration costs and physician pay. As we head into spring, we expect vendors to showcase new solutions/technologies to combat these costs and for thought leaders to continue to bring this issue to center stage.

Consumer Big Data Applications

Data has played a critical role in healthcare for years, but as a recent Fortune piece highlights that data, including medical images, genetic profiles, how you sleep and more, is now more valuable than ever as it is being analyzed to drive change. The article explains:

These massive storehouses of information have always been there. But now, thanks to a slew of novel technologies, sophisticated measuring devices, ubiquitous connectivity and the cloud, and yes, artificial intelligence, companies can harness and make sense of this data as never before. 

As data, especially patient specific data, comes top of mind, more data is being considered and granular details about an individual patient are making a difference when it comes to the care they receive. Over the next few months, we expect to see more of a focus on analyzing data to draw insights that can help improve outcomes and cut costs.

Bipartisan Efforts to Fix Healthcare

Back in February, a new nonpartisan group of politicians, policy makers, executives and other public figures, led by Andy Slavitt, joined forces to take politics out of health care and bring the U.S. health system together. The group, United States of Care, pledges to push for policy changes based on the idea that despite political divides, Americans want the same thing when it comes to their health. Due to disagreement on both sides of the aisle, healthcare policy has been a pain point for the Trump Administration. We presume more individuals will speak out and pledge to do their part to help the country focus on what’s most important: delivering cost effective, quality care.

As we look ahead to the spring, we anticipate unexpected companies to come into the space and new polices and ideas to emerge in the market. With healthcare changing on the daily, find out how your organization can stay relevant as we head into the new season. Learn more about our offerings here and contact us here.

HIMSS18 Series: The Top Payer Trends to Watch

We’re a little more than one week out from the annual HIMSS conference which begins on Monday, March 5 at the Sands Expo Center in Las Vegas, NV. The event brings together more than 40,000+ health IT professionals from various sectors of the industry. To help you better prepare for this whirlwind event, we connected with our very own Diane Gerdes, payer product marketing manager, to gather her predictions on what trends she believes will be top of mind for the payer industry and some major topics that will be discussed during the conference.

Here are Diane’s four predictions:

1. Increase in merger and acquisitions

The payer market continues to experience drastic change and game-changing mergers and acquisitions (like the CVS and Aetna merger) will continue to transform how the insurance market operates. Combining forces amongst major players will help bring a new perspective to the industry and allows for payers to differentiate themselves and remain competitive in a fast-moving space.

2. Rapid development of health apps and new data

Since the creation of smartphones and wearable technology – consumer-facing apps and data have boomed. In the United States, there are more than 200 million smartphone users with access to more than 4 million apps. In addition, a recent article in Managed Healthcare Executive reports that the wearable market is expected to grow from 101.9 million units sold in 2016 to 213 billion units in 2020. This is an incredibly large, untapped data pool that holds great promise for the healthcare industry – “smart” information that leads to smarter decisions. We can expect payers to employ more consumer-facing applications and devices to better understand and connect with their members across their healthcare journey.

3. Engaged healthcare consumers

Members are evolving and using various modalities to connect – not only with their friends or family but with their healthcare providers. While different age groups are adopting technology at varying rates, healthcare consumers overall are demanding more digital capabilities and greater access to information and services. According to a MobileSmith report, by 2020 millennials will make most of the healthcare decisions in the U.S. Given this shift, payers need to evolve their coverage plans to account for how these individuals receive care, including telehealth and remote monitoring (e.g., remote glucose monitors). These services not only offer convenient, affordable alternatives to traditional office visits but also deliver a constant stream of data. The ability to harness this information, along with other data, and transform it into meaningful, actionable insights will be key to delivering high-quality, patient-centric care.

4. New methods for data analysis

The volume of healthcare data is increasing at an exponential rate: 48 percent per year. To manage these growing data sets, sophisticated analytic tools and machine learning will become more important to identify patterns and predict outcomes. In fact, the role of machine learning in healthcare and clinical decision making are currently dominating news headlines. At MedeAnalytics, data discovery, data mapping, and statistical analysis (a key component of machine learning) helps us to show our customers what is needed for any given implementation. Our platform also uses linear regression models to learn trends based on our client’s trends. Transformative technologies, like AI and machine learning, will continue to play an increasingly important role in healthcare as they will help payer organizations to make more data-driven decisions.

2018 will be the year of the patient in healthcare and we can expect that theme to impact the way traditional healthcare payers operate.

If you’re interested in meeting with us at HIMSS, click here to schedule your appointment. Looking for more resources for the payer market? Check out our solutions page here.

The Association Health Plan Proposal is Making Big Waves – Here Are Our Predictions

Earlier this month, the Department of Labor (DoL) released a proposed rule that allows small business and employee groups to purchase association health plans (AHPs) instead of employee-sponsored or individual health insurance plans. This recent proposal was met with mixed views across the healthcare industry – some believing this would further complicate the insurance market or weaken consumer protections.

Our very own Bruce Carver, associate vice president of payer services at MedeAnalytics, offered his insight on the potential impact this proposal can have on the insurance market. His thoughts on benefits, risk and coverage are below.

What are the primary changes this rule would allow?

The Trump administration has proposed a new rule, based on an executive order by President Trump, that allows Association Health Plans (AHP’s) to expand the types of groups that can form an AHP. The two primary changes in the rule would allow AHP’s to be offered  membership without regard to state lines, and allow self-employed individuals to take part in a large-group AHP.

What does this mean for essential benefits?

This proposal could allow insurers to sell plans that do not cover certain essential health benefits, like mental health, substance abuse treatment, maternity care and prescription drugs. This may cause a lot of confusion with members when they are treated by providers and any limitations in coverage will need to be clearly communicated between members and providers, in an already confusing market. Members will also need to consider if the plan benefits them based upon pre-existing conditions. 

What about risk?

Any time you increase the number of people covered in a plan, you have the capability to diversify risk. The concept of “pooling” members in a region for covered benefits by putting small groups together into a single larger group is not new. Some states allow for this type of “pooling” under group rating programs for disability and workers’ compensation benefits. 

How will this impact network coverage?

As member coverage crosses state lines, regional health plans will need to consider if they have appropriate network coverage to meet access requirements. This may also increase competition in some markets that have few options. However, this may also have the potential to drive down costs.

What have been industry reactions around the plan?

There is a lot of initial criticism that health plans will “cherry pick” healthier members, leaving the sicker members in the traditional Obamacare plans. This has yet to be proven to be the case.  At the end of the day, health risk is just that…risk.  “Pooling” a lot of members into a single plan that has a balance of healthy and sicker individuals may improve costs vs. the current options offered today.

Looking for more details on AHPs? Bruce also shared his commentary in a recent article by Health Leaders Media. If you’re looking for a partner to help your organization manage the shifting healthcare landscape, contact us here.

Machine Learning: A Q&A with CTO Tyler Downs

We recently sat down with Tyler Downs, CTO of MedeAnalytics to discuss trends in machine learning in healthcare. He offered insights into how MedeAnalytics is using machine learning to power data analytics and what’s in store for the future of the technology.

Q: What exactly is machine learning?

A: In layman’s terms, machine learning is the application of artificial intelligence that enables computers to automatically learn and improve from experience without being explicitly programmed. It’s all about developing computer programs that can access data and learn from it themselves.

Machine learning is used every day in social networking, commuting apps, and online shopping. Think of Facebook. When you upload photos to Facebook, it automatically highlights faces and suggests friends to tag. Facebook also uses algorithms to personalize your newsfeed and ensure you’re seeing posts that interest you. Google Maps analyzes the speed of traffic at any given time. And on Amazon, you see recommendations for products you might be interested in, displaying “customers who bought this item also bought…”. These all use forms of machine learning.

Q: How is machine learning being used in healthcare?

A: Think about the huge volumes of data being generated in healthcare. Machine learning can be trained to look at structured and unstructured data (images, video, audio files), identify anomalies, and point to areas that need attention.

There are clinical, financial, and operational applications of machine learning in healthcare. In the clinical realm, Google has developed a machine learning algorithm to aid in tumor-detection on mammograms. Stanford is using algorithms to identify skin cancer.

In the revenue cycle, machine learning can be used to predict denials, improve point-of-service collections, and identify a patient’s propensity to pay their bills. This enables the health system to increase reimbursement, reduce the cost collect, reduce bad debt, and more.

For healthcare operations, machine learning enables providers to improve throughput in the OR and ED, assess the risk of no-shows, identify trends in patient volumes, determine the appropriate appointment length, and enable schedulers to allocate the right amount of time for procedures based on the individual patient and physician. These capabilities drive down costs, which is important considering the average cost of an OR can be as much as $60-80 per minute (Stanford).

Q: How is MedeAnalytics using machine learning?

A: A key component of machine learning is data discovery, data mapping, and statistical analysis. We do this today. It enables us to quickly and clearly see what data is needed for a given implementation.

Our platform also uses linear regression models to learn trends based on our clients’ trends. For example, one of our payer clients might always see new member enrollment spike at the end of the month. The system learns that such spikes aren’t anomalies but are expected patterns according to historical data.

And as I mentioned before, we can help providers predict a patient’s propensity to pay their bill. This is crucial as deductibles and cost-sharing are on the rise. Rather than having collections agents call patients in alphabetical order, they can start with those who are most likely to pay. This brings more money into the hospital and makes collections agents more efficient, reducing the cost to collect.

We have an active data science team with PhD-level data scientists who help us uncover the possibilities with machine learning for our clients’ specific use cases.

Q: What’s in store for the future of machine learning?

The healthcare industry has only scratched the surface of what’s possible with machine learning. Machine learning in healthcare will continue to improve, resulting in better clinical outcomes, more streamlined operations, and a reduced cost of care. And as machine learning becomes more deeply ingrained in our work (and in our daily lives), it has the potential to become the infrastructure that will power a second digital revolution.

To learn more about machine learning, please contact Mike Doeff at or ask your account manager.