NextHealth Technologies

Test and Learn Your Way to Medical Cost Savings

To be truly innovative you need to create a culture of experimentation.

Have you ever bought anything from Amazon zShops? Probably not.

How about Amazon Auctions? Not likely.

You are not alone because these two massive experiments were quickly scuttled by the retailing giant 15 years ago on the road to hitting their home run with Amazon Marketplace where nearly 50% of current units sold on are from third-party sellers. zShops and Auctions were not failures; rather, the company had to test these two concepts in order to learn how to successfully execute the Marketplace offering. A test and learn culture is critical for innovation not just in retail but in every industry, including healthcare.  

“To invent you have to experiment, and if you know in advance that it’s going to work, it’s not an experiment,” says Amazon’s CEO Jeff Bezos in his 2015 shareholder letter. “Most large organizations embrace the idea of invention, but are not willing to suffer the string of failed experiments necessary to get there.”

“Most large organizations embrace the idea of invention, but are not willing to suffer the string of failed experiments necessary to get there.”  – Amazon CEO Jeff Bezos

NextHealth CEO Eric Grossman recently wrote about why it’s important that healthcare leaders transform their organizations into test and learn cultures in his recap of the 2017 Oliver Wyman Health Innovation Summit. There are important lessons in experimentation and cost savings for healthcare industry executives from other industries including retail and financial services.

In a recent discussion during the “Finance Disrupted” event by The Economist, Capital One co-founder and QED Investors Managing Partner Nigel Morris detailed how the competitive advantage for companies today lies not just in having lots of data to run experiments but rather how companies leverage that data for insights by building a test and learn culture. Morris explained it best in his outline of Capital One’s strategy:

“The core idea was that the credit card business is not really the traditional lending business, it’s not really banking at all. What it really is is the leveraging of information in order to be able to put the right product in the right customer’s hands at the right time. The way you did that was in two or three ways. One was amassing huge amounts of data at the customer level and then using experimental design and testing different product and market combinations in order to optimize value to the consumer and net present value to the entity.”

Sound familiar?

You could replace “credit card business” in the above quote with “healthcare industry” and be accurate in describing the opportunity for health plans to build test and learn cultures that better understand and align the right products for the right members at the right time. Capital One now runs over 80,000 tests per year to pinpoint the ideal combination of product, customer, and timing.

For Amazon, Capital One, and a growing number of health plans, when it comes to reducing costs, growing revenues, and improving outcomes, the insights from the tests and how (and how quickly) they are applied are what matter most. Through thousands of experiments, Amazon learned that customers are already using its artificial intelligence framework for early disease detection that saves lives and lowers costs. Through testing and learning, CapitalOne found that people who complete an application in all capital letters pose a higher credit risk (i.e. higher costs). 

Here is how Jeff Bezos described a test and learn approach for Prime Now that was put in place in a matter of months:

“Prime Now offers members one-hour delivery on an important subset of selection, and was launched only 111 days after it was dreamed up. In that time, a small team built a customer-facing app, secured a location for an urban warehouse, determined which 25,000 items to sell, got those items stocked, recruited and onboarded new staff, tested, iterated, designed new software for internal use – both a warehouse management system and a driver-facing app – and launched in time for the holidays. Today, just 15 months after that first city launch, Prime Now is serving members in more than 30 cities around the world.”

How does NextHealth help its health plan customers test, learn and optimize outcomes quickly?

NextHealth’s Measurement and Optimization platform automates health plans’ ability to quickly test, measure and optimize any clinical program. Key benefits include:

  • Faster, data-backed insights allow teams to get to better business decisions quickly and with greater consensus

  • Standardized and consistent analytics methodologies and program set-up help elevate the organization to a shared conversation based on experimentation, building a culture of measurement

  • Automating the ability to test, learn and optimize allows talented analytics and healthcare economics resources to do more with less and operate at their highest capacity

The platform has enabled clients to measure existing programs in as little as 60 days, learning which programs are effective and which are not, gleaning administrative cost savings quickly. New programs, such as reducing avoidable ER utilization, EPDST, HEDIS improvements, and others, can be added to the platform as well, delivering medical cost savings using machine learning to optimize outcomes by assigning members to the programs that are most likely to work for them. NextHealth’s managed services offering, included in every engagement, ensures that clients have access to the learnings gleaned from our experience, furthering speed to value.

Is your organization reducing medical and administrative costs through a test and learn culture?

Our platform accelerates data-driven decisions and enables a culture of measurement. See how.

Know What Works - Make Data-Driven Decisions To Drive Down Medical Costs

Insights from the Oliver Wyman Health Innovation Summit 2017

Eric Grossman, CEO of NextHealth Technologies, recently attended the Oliver Wyman Health Innovation Summit, Nov 6-8 in Dallas, TX. Titled “Industry Interrupted: Delivering on the Promise of Change”, the event convened healthcare industry leaders to discuss disruption in healthcare. We recently sat down with Eric to highlight his thoughts on the event.

What were your three main takeaways from the event?

1. Create a test and learn culture

Being able to test and learn – at scale – is an underpinning of competing in an industry ripe for disruption. Nigel Morris from Capital One provided a great example how taking an experimental approach (i.e. a test and learn mindset) can position a company to not just weather disruption but come out ahead as a result.

Capital One conducted 46,000 test-and-learn experiments in the year 2000 to see which combinations of campaigns, products, messages and offers resonated most with consumers. The company experimented to find out what worked for each micro-segment and created an infrastructure to optimize what was working. They captured the data exhaust on everything they did so they could figure out what worked. They kept failing to find what was successful. Thomas Edison put it well when he noted: “Many of life’s failures are people who did not realize how close they were to success when they gave up.”

2. Support the supply chain

Health plans need to figure out how to derive value and align incentives in the supply chain. The physicians are saying “We have engagement fatigue. You’re calling us. You’re reaching out to us. But we only have so much time in a day. You have to help us prioritize where we can get the biggest impacts in our days.” The way we do that is through the use of analytics, and in particular, both machine learning and prescriptive analytics. Enabling physicians to be more efficient and maximize reimbursement is heavily dependent on analytics.

Prevent engagement fatigue by empowering physicians with better insights on how to maximize their return on time and focus. That will require developing this test and learn mindset.

3. Engage the connected consumer

It’s time to acknowledge and engage the connected consumer, especially the data exhaust from their digital, always-on life. Leveraging this data exhaust in an analytics environment built around the connected consumer is vital. As consumers take on more responsibility for cost, there is now a need for plans to do things other than just ingest claims and generate payments. They need to become a trusted advisor for consumers as they navigate the complexities of managing their own care and cost decisions. Health plans are trying and eager to adjust to this new reality, but to be effective, they need to have a faster, more reliable way to make data-driven decisions and an infrastructure that will help them innovate more effectively.

What’s the “landscape of disruption” look like for healthcare in 2018?

The threat of disruption is real for the healthcare industry. Look at how Amazon is getting into the pharmacy business and paid for the recent acquisition of Whole Foods with a day’s worth of capital market gains. Look at Uber, Square, etc.

Necessity is the mother of invention. We’ve got the right alignment of incentives now. The industry has to innovate because it’s threatened by disruption. At the same time, plans have the data and the membership. They have large enough populations to move the needle and also have the capital to invest in these areas to have real impact, build trusted relationships with their members, and avoid losing market share.

What’s different about the current environment?

Healthcare is unsustainable at its current cost. We (the industry) have been saying that for years so that’s not necessarily groundbreaking, but if you look at the geopolitical dynamics of healthcare you can see that things really are different now. Look at the difficulty Washington has had enacting change despite the enormous costs at stake. The unit costs are unsustainable and companies just can’t afford it anymore. The fact that commercial insurance completely subsidizes Medicare and Medicaid is just not sustainable. In addition, now that consumers are shouldering more of the risk/cost burden, they need help in learning how to better manage that responsibility. That shift creates either real opportunity or potential downfall, depending on how the industry reacts.

How do organizations create a test and learn culture?

First, without strong executive sponsorship and governance to drive a culture of measurement into the organization, the initiative will be doomed. The second priority is to drive standardization and processes around measurement that don’t rely on politics or influence, but rather rely on data and insights as the currency for decision-making. Lastly, creating a “test, learn, and optimize” environment relies on building comfort with a culture of failing a lot more and continuing to understand that failure should be seen as a means to an end instead of just an end.

How are you going to innovate if you don’t have an infrastructure that allows you to test and learn quickly? Remember, analytics is a no-regret investment.

Our platform accelerates data-driven decisions and enables a culture of measurement. See how.

NextHealth Technologies to Host Live Webinar on Measuring Program Effectiveness and Optimizing ROI

nexthealth_technologies_logo_clearspace 300

Wednesday, October 25, 2017 — NextHealth Technologies, a prescriptive analytics and consumer engagement platform that reduces medical costs for health plans, announced that it will host an exclusive webinar on Tuesday, October 31, from 3:00 PM to 4:00 PM ET. The webinar will be hosted by Anne Marie Aponte, SVP of Operations, and Dan Masciopinto, SVP of Product, and will focus on how health plans can drive attributable administrative and medical cost savings through program measurement and optimization.

“The ability to determine what is working for whom is a considerable challenge for health plans,” said Aponte. “At NextHealth, we built our platform to target specific member clusters and scientifically measure which efforts are working, how well, and for which members.” Added Masciopinto, “Plans can significantly amplify ROI by systematically optimizing resources and focusing on the programs that work and turning off the ones that don’t.”

The webinar will cover solutions to problems that health plans struggle with on a daily basis, including:

  • Measuring which interventions work for specific populations
  • Optimizing around channel effectiveness to reach certain members with the interventions that resonate
  • Allocating resources to the programs that are scientifically proven to have impact

For more information about the webinar or to register, visit the NextHealth website.

About NextHealth Technologies

NextHealth Technologies empowers people to make the best healthcare decisions. Our prescriptive analytics and consumer engagement platform has helped innovative health plans such as UnitedHealthcare, BlueCross BlueShield of Tennessee, and Florida Blue significantly reduce administrative and medical costs through better targeting, measurement, and optimization of member interventions. Scalable to multiple use cases and lines of business, plans know at a glance who to target, which programs work, which don’t, and precisely how well – all from a single dashboard. Outcomes are measured within 60 days from deployment and offer in-year ROI. NextHealth offers an optional managed services contract and puts its fees at risk based on delivered outcomes. For more information, visit

Awards and Accolades

NextHealth was named in three Gartner industry reports: “Hype Cycle for U.S. Healthcare Payers, 2017” (in the Healthcare Consumer Insights as a Service category), “Hype Cycle for Healthcare Providers, 2017” (in the Healthcare Consumer Persuasion Analytics category) and “Hype Cycle for Consumer Engagement for Health and Wellness, 2017” (in the Healthcare Consumer Insights as a Service category). Frost & Sullivan also named NextHealth in its 2017 Global Healthcare Data Analytics Companies-to-Action report.

For media inquiries:

NextHealth Technologies
Melissa O’Connor
VP of Marketing

Richard Thaler’s Nobel Prize – Can Behavioral Economics Drive Down Healthcare Costs?

Behavioral economics is critical to understanding non-rational behavior. How can plans apply these concepts to reduce medical costs?

Earlier this month Richard H. Thaler was awarded the Nobel Prize in Economic Sciences for his contributions to behavioral economics. Thaler’s research has been a seminal step towards understanding the impact of non-rational decision making that produces a theoretically worse outcome for the individual decision maker. In layman’s terms: people frequently make decisions that are not in their own best interest – economic or otherwise. 

“This type of thinking – understanding humans as non-rational decision makers – is critical in addressing healthcare both from the viewpoint of economics and designing for better outcomes.”

The insights of non-rational behavior as viewed through an economic lens has been significant for other research and development in the areas of psychology and consumer behavior. There is broad application to many fields that anticipate good behavior based on self-interest but see individuals struggle to meet expected compliance, behavior change, choice or self-care objectives. This applies to wellness, self-care and behavioral compliance with care plans across a range of areas (from Physical Therapy to Pharmaceutical Prescriptions to Discharge Plans to Utilization Choices).

Translating Thaler’s work to healthcare

Thaler’s research moved economics beyond pure logic and into the realm of irrational action and attempts to understand why we are irrational actors.  This is critically important as his work has shed an important light on individual examples of non-rational behaviors, as well as broader trends that can be identified (or shaped) with society more broadly.  In the healthcare field, his work, and the work of other psychologists and consumer behavior researchers is contributing to change in the design paradigm for how we think and act on healthcare initiatives at the individual level (care plan, utilization) and for large health populations (wellness, disease management). This type of thinking – understanding humans as non-rational decision makers –  is critical in addressing healthcare both from the viewpoint of economics (can digital therapies be more effective than drugs in some cases?), and designing for better outcomes (what message is most effective to achieve a positive health/social outcome?).

How NextHealth uses nudges to change behavior and improve outcomes

NextHealth is translating many behavior design concepts to healthcare in areas initially advanced by Thaler, and later his peers in related fields of consumer behavior and psychology. Examples of behavioral nudges used by NextHealth clients include:

  1. Selection of frames (e.g., gain frame or loss frame for potential plan benefits; social frame emphasizing the choices of relevant others)
  2. Use of key words (e.g., free benefits)
  3. Appeals to mental accounting
  4. Active choices that encourage recipients of nudge messages to make decisions while they have relevant message information in front of them

Below is an example from an outbound call script using a selection of these behavioral nudges:

“This free program is designed to help you get answers and advice about <your/your child’s>health and where to get medical help quickly and safely with just a phone call, and can be used immediately.”

Read More: NextHealth helps client reduces avoidable ER visits by 25% by implementing nudges and targeted outreach.

Additionally, NextHealth is increasing its impact by elevating the rigor around two areas abutting program design; identification of impactable target populations and validation of program efficacy.

Extending Behavioral Economics with better targeting

Certain factors in healthcare invoke significant challenges for designing programs that impact behavior. Critical aspects of behavior design assume the ability to trigger consumer action based on a consumer context or opportunity; however, the timing and acuity of many health issues can be unpredictable, which conflicts with the best state- of-the-art intervention approaches.

“NextHealth uses machine learning based on health data to find signals that indicate a particular group is a highly impactable target and economically viable to address.”

Not all consumers behave irrationally, and some people are unaware of, or have dissonance to messages and information that creates the appearance of irrational behavior.  Therefore, the ability to identify populations that would significantly benefit from a program designed to change their behavior is critical. NextHealth uses machine learning based on health data to find signals that indicate a particular group is a highly impactable target and economically viable to address.

Thaler’s research sustains the notion that people can be induced to better decisions by re-framing a process, outcome or action to off-set what otherwise might be interpreted as irrational cognition. Refining targets using machine learning enhances our ability to profile population segments and dial-in more specific behavior design elements. The specificity of the consumer targets also ensures that we can define the correct cohort to generate a Random Clinical Trial in concert with any behavior design to validate the impact of the program.

Understanding who to address, how to frame and shape decision-making, and optimizing validated results are necessary to drive and impact behavior design for healthcare.

Although Thaler is an economist, and much of his work is focused on behavioral economics, his key findings serve to open many fields to the idea that we are not always making rational decisions. In healthcare this extends to the food we eat, the activities we choose or the choice to discontinue medication compliance as well as many other short and long-term life-impacting decisions.  

Today there is an open field of opportunity to contribute advancements in ethical behavior design that can shape economics, health and society in positive ways. We can thank Richard Thaler and researchers in the field of consumer behavior for enlightening us and moving us toward more sophisticated design strategies that take into account both rational and non-rational characteristics as we address health decision making going forward.

Targeting impactable members is critical to changing behavior and reducing medical costs. See how easy it can be.

Improve the Bottom Line by Reducing Low-Cost, Low-Value Services

Low-cost, low-value, high-volume health services contribute to 65% of unnecessary medical costs – here’s what health plans can do about it.

Each year, the U.S. spends nearly $1 trillion on unnecessary medical expenses. [1] A study published by the Harvard Business Review estimated that roughly 40% of unnecessary medical spending can be avoided by addressing the clinical waste, administrative complexity, excessive prices, fraud and abuse experienced in the system. Professional guidelines, personal judgment and health plan design make these types of waste difficult to address.

Is it possible to tackle low hanging fruit in the waste equation to chip away at the egregious cost for unnecessary medical care?


Waste in U.S. Healthcare
Source: Harvard Business Review

Focus on low-value, low-cost services to start

A recent study published by Health Affairs highlights how health plans can reduce unnecessary costs by curbing low-value services. [2] Looking at the Virginia All Payer claims database for 2014, roughly $586M in unnecessary medical costs were attributed to low-value services across two categories:

  1. Low-value, low-cost services typically valued at or under $538
  2. Low-value, high-cost services typically valued over $538

Surprisingly, low-value, low-cost services made up 65% of the total unnecessary medical costs in the data set examined. [3]

Examples of low-value, low-cost services include:

  • Baseline lab tests for low-risk patients having low-risk surgery: Studies have shown that a good history, physical exam, followed by a review of a patient’s chart are sufficient for low-risk patients who are headed to get a low-risk surgery. [3, 4, 5]
  • Stress cardiac and other cardiac imaging in low-risk, asymptomatic patients: An article in the Cleveland Clinic Journal of Medicine indicated that low-risk patients that undergo unnecessary cardiac stress tests may be exposed to more risk through additional follow-up testing. [3, 4, 6]
  • Annual EKGs or other cardiac screening for low-risk asymptomatic patients: The American Academy of Family Physicians cited risks of false positives that often lead to unnecessary invasive procedures, overtreatment, and misdiagnosis for annual EKGs for low-risk patients. [3, 4, 7]

Why reducing low-cost, low-value services is difficult

Some of the challenges stem from the lack of health education and awareness that directly impacts people’s decision making abilities. Specifically, not many consumers make research-based decisions when it comes to their health. In fact, many consumers rely on their doctor’s recommendation to make key health decisions according to a McKinsey survey. [8] Therefore, if providers recommend a low-cost, low value service to a patient, they are more likely to comply – contributing to the $1 trillion in unnecessary medical expenses.

How to reduce costs

The first step focuses on targeting. Who in the plan membership is anticipated to get a low-cost, low-value service? Health plans can intervene by providing members with educational materials to help them understand the costs and benefits of getting these services so they can make informed decisions.

NextHealth enables just the type of targeting that helps health plans identify the right members to engage. Using claims and provider data, NextHealth identifies members who are predicted to get a low-cost, low-value service and intervene with a nudge that incorporates education and behavioral science theories so members make better health choices. The process is simple and can be a powerful way to tackle the low hanging fruit when it comes to reducing the $1 trillion in unnecessary medical expenses.

Contributed by Thomas Tran, Engagement Manager, NextHealth Technologies


[1] How the U.S. Can Reduce Waste in Health Care Spending by $1 Trillion

[2] Low-Cost, High-Volume Health Services Contribute the Most to Unnecessary Health Spending

[3] Study: Unnecessary health spending fueled by low-cost, low-value services

[4] Low-Cost, Low-Value Healthcare Services Ripe for Reaping

[5] Perioperative Testing

[6] Is cardiac stress testing appropriate in asymptomatic adults at low risk?

[7] Annual EKGs for Low-Risk Patients

[8] Debunking common myths about healthcare consumerism

Targeting impactable members is critical to changing behavior and reducing medical costs. See how easy it can be.

Machine Learning in Healthcare: From Data to Prediction

Machine learning for more accurate predictions and more precise targeting

Predicting consumer behavior can be a complex process, especially in a healthcare setting. Fortunately, the abundance of data sources (such as claims data and clinical statistics), provide ample opportunity to generate meaningful insights. The advancement of machine learning algorithms has opened up even more opportunities to get ahead of complex problems and to predict future behavior.

At NextHealth, we have incorporated machine learning into our platform. For example, the platform can accurately predict emergency room visits by identifying health risks and utilization patterns within identified member populations. Backed by these predictions, the platform then targets at-risk and impactable member clusters, assigns them to the most effective intervention campaigns, and measures what works for whom.

“By integrating machine learning into our platform, we can transform health data into actionable intel and impactful results.”

Better Targeting of Populations

Once a client’s raw data has been standardized and processed, NextHealth builds the algorithms to maximize predictive power. Our data scientists mainly use tree-based learning algorithms due to their regression and classification capabilities, along with their scalability into both linear and nonlinear relationships.

In order to target high risk populations that offer the greatest opportunity for impacting a particular use case, we use Decision Trees (a flowchart-like structured algorithm) due to the intuitive visualization design and interpretation capabilities. As the decision trees are processed, we split the features based on the largest information gain. The output gives us the difference between the impurity of the parent nodes and the sum of the impurity of the child nodes. This splitting process is repeated at each child node until it reaches to the very bottom leaves. In order to avoid overfitting – a very deep tree with lots of nodes – we use a “prune” technique to limit the maximum depth of the tree.

An example from the platform: In this case, decision trees help us predict the population clusters that have the highest ER utilization in comparison to the total population and offer the highest potential for use case impact

Member-Level Risk Prediction

At the member level, we run our risk prediction by using Random Forest and Gradient Boosting.

Random Forest is an ensemble of decision trees and applies a Bagging technique to tree learners. Random Forest takes random samples of the training set (with replacement) and grows a decision tree from each sample. After many trees are formed, the prediction will be aggregated and decided on majority vote. The ensemble method is believed to be robust to noise.

Gradient Boosting is an additive model for including weak learners using a gradient descent procedure – an iterative method that takes steps proportional to the negative of the gradient of the function to find a local minimum of a function. Decision trees are used as the weak learner in Gradient Boosting. Trees are implemented one at a time, and a gradient descent procedure is used to minimize the loss when adding trees.

While Random Forest reduces variance, Gradient Boosting reduces bias. We use a stacking technique to combine the two algorithms for improved accuracy.

The Result: Better Predictions, Improved Targeting

At NextHealth, we deliver measurable outcomes for our health plan customers by 1) better targeting their most impactable members, 2) deploying the personalized and persistent interventions most likely to impact behavior, and 3) measuring and optimizing what works for whom. The machine learning methods we employ drive more reliable behavioral predictions and more accurate targeting of at-risk member populations. Ultimately, these processes enable health plans to get ahead of costly behaviors and deliver the most impactful interventions to the members who are most likely to be receptive. By integrating machine learning into our platform, our customers transform big data into actionable intel and impactful results.

By Cathy Zdravevski, Data Scientist, NextHealth Technologies

Machine learning helps us get ahead of many problems. Explore other use cases.

Reduced Risk, Scalable Value: The Build-Operate-Transfer Model

When addressing complex problems, the right deployment model can be just as important as the solution.

In a world of finite resources, limited time, and competing priorities, health plans must be extra diligent when investing in new solutions. Identifying the best solution, whether it’s new technology or a streamlined business process, is merely the first step. How the investment is deployed can differentiate failure from success. Organizations must deploy solutions in a way that mitigates short-term risk, does not drain organizational bandwidth, allots time to prove ROI, and sets up the organization to successfully scale solutions long-term.

Build-Operate-Transfer deployments reduce short-term investment, prove ROI, and empower teams for long-term, scalable growth.

Implementing NextHealth’s platform via our Build-Operate-Transfer (“BOT”) methodology delivers scalable operational and financial benefit, while achieving those multi-pronged objectives – making our solution a rare find in today’s world. While NextHealth customizes the BOT deployment timeline and approach for each client, the image below illustrates how this phased approach unfolds and translates into scalable value.

Process & Timeline

Months 0 – 3: Build

NextHealth’s Managed services team leads the implementation process, including key activities such as providing project management support for data exchange processes and establishing a core governance framework and operating rhythm. In conjunction with the client, NextHealth will also begin preparing the regional deployment of new programs designed to reduce the costs associated with a pre-determined use case, such as avoidable ER utilization.

Months 3 – 18: Operate

During this critical window, NextHealth leads program execution, including direct member engagement across all channels – including telephonic, digital, and print. As results unfold, NextHealth partners closely with the client to identify how the platform fits into the health plan’s workflows to amplify existing capabilities and/or fill critical gaps in the end-to-end orchestration of cost reduction programs.  End users are identified within the client organization and trained to serve as subject matter experts.

Months 18 & Beyond: Transfer

As the initial deployment of the solution delivers tangible, causal results, NextHealth supports the client in scaling the program across a broader population to amplify cost savings. This proof point also serves as the launch pad for the identification of additional use cases, leveraging the 30+ off-the-shelf KPIs built into the platform or custom-built measures developed in the platform by the end user. During this phase, member engagement activities are transferred to the client, enabling closely knit integration and improved operational efficiencies.


The BOT deployment methodology is advantageous for customers in three primary ways, leading to increased net paid savings overtime:

  1. Risk Management: BOT enables testing of the NextHealth solution while minimizing both upfront resource requirements and financial risk. NextHealth does the upfront legwork associated with implementation and bears risk for results during the initial deployment.
  2. Optimization: BOT enables the opportunity for the client and NextHealth to partner together to identify the optimal way to integrate the platform into the health plan’s existing operations to ensure long term success.
  3. Scalability: BOT capitalizes on the scalability of the platform, leading to increased savings over time via the expansion of successful programs and deployment and testing of new use cases.

By Anne Marie Aponte, SVP of Operations, NextHealth Technologies

The NextHealth platform scales to many use cases. Explore the problems we solve.

Target, Measure, Optimize: Three Ways Health Plans Can Get Ahead of the Opioid Crisis

We continue the discussion on opioid abuse in America, following up on our post, Leveraging Advanced Analytics to Address Opioid Abuse.

Over the past twenty-five years, the United States has become the leading consumer of opioid pain medications, with the rate of prescriptions skyrocketing since 1991. In 2012 alone, 259 million prescriptions were written for opioids – enough to give every American adult his or her own bottle of pills.

opioid chart
Opioid Prescriptions Dispensed by US Retail Pharmacies, 1991 – 2013

For insurers, understanding the people, demographics, risks, and cost-drivers is an essential step towards addressing the problem. As Dr. Richard Snyder, Senior Vice President and Chief Medical Officer of Independence Blue Cross, noted in a recent interview: health plans can play a vital role in reducing opioid addiction – starting with prevention. For their part, Independence Blue Cross has multiple programs in place to limit opioid prescribing, better understand “doctor shopping” behaviors, and provide education on alternative pain therapies.

As opioid mitigation programs gain prominence, how can health plans enact preventative measures, conserve resources, and still support members coping with opioid abuse?

“There’s no doubt insurers can play an integral role in addiction prevention and recovery.”

-Dr. Richard Snyder, SVP and Chief Medical Officer, Independence Blue Cross

At NextHealth, we have identified three ways for health plans to get ahead of the opioid crisis.

1. TARGET: More accurately predict which members are at risk for opioid abuse, based on key attributes such as chronic pain management behaviors.

  • Health plans can use this knowledge in conjunction with the predictive and prescriptive capabilities of the NextHealth platform to impact member behavior and drive at-risk members to alternatives. By understanding the key behaviors of members and how best to interact with members with opioid disorders, health plans can enhance the role they play in combating this public health epidemic.

2. MEASURE:  Track and evaluate program effectiveness to help divert members to other pain management options, such as non-opioid painkillers, physical therapy, and other treatments.

  • By evaluating current programs and working to divert members to alternative options, health plans can help reduce the number of members who develop an opioid use or abuse disorder.
  • Health plans can finally understand what programs are working – and which aren’t – so resources can be strategically allocated to have the greatest impact.

3. OPTIMIZE: Refine and tailor programs, channels and messages to engage with specific populations to best impact their behavior.

  • The NextHealth platform helps plans understand which messages resonate with specific member populations, tailoring outreach to key segments.
  • Health plans can optimize programs to focus only on the most impactful messages and channels, and pivot quickly.
  • For members already dealing with addiction, our platform measures and optimizes assistance programs to provide the best resources towards recovery.

Given the scale of the problem and the associated budgetary demands, it’s more important than ever that insurers know which interventions provide the greatest benefit, so they can get the most out of every engagement dollar spent. Opioid misuse is causing increased emergency room utilization, inpatient stays and most tragically of all, overdoses. Many of these problems can be prevented, provided that opioid disorders are recognized and supported by appropriate interventions. At NextHealth, we are supporting insurers, engaging with members, and helping all of us understand how to get ahead of the opioid crisis.

By Lindsey Miller, Engagement Manager, NextHealth Technologies

The NextHealth platform scales to many use cases. Explore the problems we solve.

Optimizing Outreach to Maximize Resources and Empower Consumers

Targeted programs reduce communication fatigue for consumers and maximize investments for health plans

The topic of consumer engagement is pervasive in healthcare. Health plans often struggle to get the right tools and information to the members who need them most. Meanwhile, members are dealing with ‘engagement abrasion’ – the dilemma created by too many non-targeted, generalized messages coming their way and not providing value.

“The ability to rapidly measure and optimize a vast number of complex cost and quality interventions can drive significant value for organizations at risk for healthcare spend.”

As we shift towards an environment where members and providers assume more of the risk for managing costs, plans are pushing more information to those stakeholders to help educate them. As a result, it’s more important than ever that plans know and can prove which of their programs are working and what efforts are ineffective. The ability to rapidly measure and optimize a vast number of complex cost and quality interventions can drive significant value for organizations at risk for healthcare spend.

Harnessing the capability to measure and optimize allows organizations to:

  1. Drive greater MLR reduction by identifying and amplifying initiatives that are working for unique populations or segments
  2. Save marketing and operational dollars internally by turning off initiatives that are ineffective
  3. Free up analytic resources to spend more time driving insights and new program design
  4. Increase member satisfaction by serving up the right programs and interventions to the right individuals to meet their particular healthcare needs

At NextHealth, we use rigorous statistical measurement and machine learning to identify which outreach methods work best for specific member populations.


You mailed 600,000 members a flier and magnet on ER diversion and saw a 2% decrease in overall utilization…was it the mailer or simply a seasonal trend?

What if you could identify that your ER mailer impacted 50,000 members with children under 2, but had no impact on the other 550,000 members. You could get the same 2% decrease for a fraction of the cost.

You emailed 2 million members and saw a 1% increase in cancer screening rates…did those emails work or did something else change their behavior?

What if you could identify that your email worked on an affluent, healthy female sub-population, and you could influence that same sub-population to utilize your cost navigator tool to find lower cost, higher quality care settings for their other care needs. You could get the same or better screening rates on your total population, and reduce total cost of care for this targeted group.

You conduct thousands of interventions with members every day, from texting, email and phone to intensive case management…do they work? And for whom?

What if you could feed every campaign and every care management program through a single, purpose-built platform to measure and optimize the effectiveness of your member engagement?  

The NextHealth platform allows users to load any campaign or intervention (past, present or ongoing) and to choose the most appropriate statistical methods to measure results in real time. Users can segment results by different sub-populations and use the NextHealth engine to drive targeting based on our prescriptive insights. Once you find what works for whom, let the platform take over and continue assigning the right targeted members to the right interventions to increase your impact with maximum efficiency. All this can be done in a single, cloud-based interface that extends and enhances existing operations and IT infrastructure.

The NextHealth dashboard enables health plans to easily configure, deploy, and optimize campaigns from a single interface. Resource effectiveness can be measured at any time, providing intel for rapid improvements.

By measuring and optimizing cost and quality initiatives, NextHealth is helping our clients and their members to make the best healthcare decisions. We are causally impacting medical cost reduction and increasing operational efficiencies. We are helping our clients turn consumer engagement from a buzzword to measurable outcomes.

Contributed by Elise Mariner, VP of Client Services, NextHealth Technologies

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NextHealth Technologies Named in Frost & Sullivan's Global Healthcare Data Analytics 2017 Report

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Monday, August 31, 2017 — NextHealth Technologies, which drives measurable medical cost reduction through an innovative prescriptive analytics and consumer engagement platform, today announced that it has been included as one of the vendors profiled in Frost & Sullivan’s 2017 Global Healthcare Data Analytics Companies-to-Action report. According to the analysis, Frost & Sullivan’s Transformational Health team found that vendors that offer solutions across complete healthcare functions or therapeutic areas will be best positioned to harness growth opportunities.

“Frost & Sullivan’s analysis, Global Healthcare Data Analytics Companies-to-Action, 2017, highlights the ecosystem evolution in high-priority digital health markets and profiles notable market players that have the potential to radically transform existing industry paradigms.”

About NextHealth Technologies

NextHealth Technologies empowers people to make the best healthcare decisions. Our prescriptive analytics and consumer engagement platform has helped innovative health plans such as UnitedHealthcare, BlueCross BlueShield of Tennessee, and Florida Blue reduce medical costs by over $40 PMPM. Scalable to multiple use cases and lines of business, plans know who to target, which programs work, which don’t, and precisely how well – all from a single platform. Outcomes are measured within 10 weeks from deployment and offer in-year ROI. NextHealth offers a turn-key managed services contract and puts its fees at risk based delivered outcomes. For more information, visit

For media inquiries:

NextHealth Technologies
Melissa O’Connor
VP, Marketing