NextHealth Technologies

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?

Absolutely.

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

Sources:

[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.

Advantages

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.

Imagine…

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

Ready to see how our platform enables quick, accurate program optimization?

HOW IT WORKS


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

nexthealth_technologies_logo_clearspace 300


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 nexthealthtechnologies.com.

For media inquiries:

NextHealth Technologies
Melissa O’Connor
VP, Marketing
moconnor@nexthealthtechnologies.com


Understanding Social Determinants to Reduce Costs and Improve Outcomes

The correlation between environment and health is perhaps best encompassed in the population health mantra, your ZIP code is more important to your health than your genetic code.

Roughly 3.6 million Americans miss or delay medical care each year because of transportation issues. Social determinants, such as access to transportation and unstable housing, can significantly impact health outcomes and increase risk behavior – leading to higher medical costs. The need to understand social determinants of health has become an increased priority, especially when building programs to alter unhealthy behavior. A deeper understanding of social determinants can help health plans develop programs that lead to better health outcomes for members while also reducing costs.

Social determinants of health

The World Health Organization defines the social determinants of health as “the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life.” Broadly, these determinants include a person’s social, economic, and physical environment. Extensive research has shown that these factors are major drivers of health outcomes and medical costs. The correlation between environment and health is perhaps best compassed in the population health mantra, your ZIP code is more important to your health than your genetic code.

social determinants
Source: Kaiser Family Foundation

Translating social determinants to reduce costs

For health plans, addressing social determinants of health can reduce downstream costs and utilization. As a result, health plans like Molina, Humana, and Kaiser Permanente are investing in programs and partnerships to address social determinants for their members. At NextHealth, we work with plans to incorporate social determinants and behavioral science to enhance analytics and consumer engagement. Below are three examples of social determinants that we use to better understand behavior, segment at-risk populations, and help consumers achieve better health outcomes.

Income data

Income level is a major determinant of health. According to the World Health Organization, “higher income and social status are linked to better health. The greater the gap between the richest and poorest people, the greater the differences in health.” Additionally, data from the Kaiser Family Foundation shows that Americans with lower incomes are much less likely to report being in good health than those with high incomes.

NextHealth can enhance health plan data with information on members’ income level and educational attainment. This data allows our prescriptive analytics engine to generate insights and tailor member outreach based on socioeconomic factors.

Vehicle ownership

Members without access to a car may have difficulty accessing care or showing up to a doctor’s appointment. The NextHealth platform can identify these members and nudge them with messages about transportation options. For example, some health plans have partnered with ride-sharing companies like Lyft to provide free rides to the doctor.

English language proficiency

For patients who are not fluent in English, language barriers can have a negative impact on health outcomes. NextHealth accounts for language differences by conducting outreach in the member’s preferred language. Additionally, members that speak uncommon languages may be interested in using a telehealth or mHealth service to connect with a provider that speaks their native language.

At NextHealth, we recognize that socioeconomic factors are major drivers of health and medical costs. These are just a few examples of how we partner with health plans to help members make the best healthcare decisions. Successful programs will rely on the understanding how social determinants of health impact individuals – and providing holistic and personalized support.

Contributed by Zach Capshaw, Product Analyst, NextHealth Technologies

Sources:

Wallace & Hughes. Cost Benefit Analysis of Providing Non-Emergency Medical Transportation

Medicaid Non-Emergency Medical Transportation (NEMT) Saves Lives and Money

WHO Social Determinants of Health

Zip code better predictor of health than genetic code

Payer Collaboration Can Address Social Determinants of Health

 

Download a whitepaper to learn more about how NextHealth clients achieve causal outcomes and use behavioral nudges to change member behavior.

The NextHealth platform scales to address multiple use cases.


analytics

Leveraging Advanced Analytics to Address Opioid Abuse

One of the greatest current public health challenges is the explosion of opioid abuse disorders. Based on 2015 data, the Centers for Disease Control and Prevention has determined that more than 33,000 people die annually due to opioid abuse (including prescription opioids and heroin). Additionally, opioid abuse has been tied to the recent report indicating life expectancy declined in the US in 2015.

The Blue Cross Blue Shield Association’s Blue Health Index recently examined opioid use disorder among the commercially insured population (under 65). BCBSA, in conjunction with Blue Health Intelligence and Axial Healthcare, reviewed claims data to determine that substance use disorders were the fifth most impactful health condition affecting the US commercially insured population.

Many NextHealth clients recognize this epidemic of opioid use and overuse and grapple with two fundamental questions:

  1. How do we predict and understand the members who are driving the utilization?
  2. What can we do to change their behavior?

The NextHealth team has developed new Key Performance Indicators (KPIs) that can predict opioid abuse and use disorders, which increased 493% between 2010 and 2016.

Source: Blue Cross Blue Shield Association (2017)

Meanwhile, the surge in diagnoses has significantly outpaced the availability of treatment and support. The highest concentration of members receiving medication assisted treatment are located in the Northeast, but the highest use of opioids is seen in the South and lower Midwest.

 

Source: Blue Cross Blue Shield Association (2017)

As health plans race to combat this growing public health issue, they are trying a variety of programs and interventions to get ahead of the people who may become abusers. The NextHealth platform can help by providing real-time analytics and program evaluation on the interventions that are working and those that are not. This real-time program evaluation allows our clients to pivot quickly and focus resources on the interventions that are working. For more information on how the closed-loop process drives outcomes, see “How it Works“.

Additional sources:

  1. CDC. Wide-ranging online data for epidemiologic research (WONDER). Atlanta, GA: CDC, National Center for Health Statistics; 2016. Available at http://wonder.cdc.gov.
  2. Substance Abuse and Mental Health Services Administration. Highlights of the 2011 Drug Abuse Warning Network (DAWN) findings on drug-related emergency department visits. The DAWN Report. Rockville, MD: US Department of Health and Human Services, Substance Abuse and Mental Health Services Administration; 2013. Available from URL: http://www.samhsa.gov/data/2k13/DAWN127/sr127-DAWN-highlights.htm

Contributed by Lindsey Miller, Engagement Manager, NextHealth Technologies

NextHealth’s platform quickly scales to multiple use cases.


NextHealth Technologies Again Named in Three of Gartner’s 2017 Hype Cycle Reports

nexthealth_technologies_logo_clearspace 300


FOR IMMEDIATE RELEASE

DENVER, CO — Monday, August 21, 2017 — NextHealth Technologies, which drives measurable medical cost reduction through an innovative prescriptive analytics and consumer engagement platform, today announced that it has been named for the second year in a row as a sample vendor in three separate Gartner Hype Cycle reports: “Hype Cycle for U.S. Healthcare Payers, 2017”[1] (in both the Retail Analytics for Healthcare Payers category and [new this year] the Healthcare Consumer Insight as a Service category); “Hype Cycle for Healthcare Providers, 2017”[2] (in the Healthcare Consumer Persuasion Analytics category); and “Hype Cycle for Consumer Engagement With Health and Wellness, 2017”[3] (in both the Healthcare Consumer Persuasion Analytics category and [new this year] the Healthcare Consumer Insight as a Service category).

According to analysts Mark E. Gilbert and Vi Shaffer in the “Hype Cycle for Consumer Engagement With Health and Wellness, 2017”3, “Learning how to motivate uninformed, unmotivated or biased individuals to change the behaviors that influence their healthcare outcomes remains one of the biggest 21st century hurdles in building healthier communities and public/private insurance beneficiaries.”

“Our industry must and is desperately seeking the best way to effectively engage consumers to contain skyrocketing costs.  We are confident that ‘persuasion analytics’ combined with targeted ‘nudge’ delivery is the central investment necessary to orchestrate meaningful medical cost reduction,” said Eric Grossman, CEO of NextHealth. “We’re very honored that Gartner has again named our company’s platform in multiple Hype Cycle reports.”

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 nexthealthtechnologies.com.

Disclaimer:

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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[1] Gartner “Hype Cycle for U.S. Healthcare Payers, 2017” by Brad Holmes, Jeff Cribbs, Bryan Cole, July 14, 2017.

[2] Gartner “Hype Cycle for Healthcare Providers, 2017” by Laura Craft, Vi Shaffer, July 14, 2017.

[3] Gartner “Hype Cycle for Consumer Engagement With Healthcare and Wellness, 2017” by Mark E. Gilbert, Jeff Cribbs, July 19, 2017.

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For media inquiries:

NextHealth Technologies
Melissa O’Connor
VP, Marketing
moconnor@nexthealthtechnologies.com


Eric Grossman Interviewed at 2017 Health Evolution Summit

NextHealth CEO, Eric Grossman, was recently interviewed at the 2017 Health Evolution Summit for their Executive Interview Series. He spoke about how NextHealth’s prescriptive analytics and consumer engagement platform helps health plans move 1 out of every 2 members out of the ER who are there for avoidable reasons.

In his interview, Eric outlined five key takeaways for how to impact consumer behavior change and four critical steps to implementing analytics effectively in an organization.