Artificial Intelligence. Predictive Analytics. Bigdata. Machine Learning. HealthCare Executive Group. Benefits Costs. Patient Outcomes. Quality Standards. STAR ratings. Profit Margins. Improving Efficiencies. EQ Health Solutions. Solving the Rubik’s Cube of Payer Data. Health Plans. Payer market. evaluating healthcare analytics vendor. Data Security. Tools and Technologies.

Insight on Solving the Rubik’s Cube of Payer Data

By | analytics, HCEG Top 10, payer, Sponsor, Webinar Series | No Comments

Healthcare payers are sitting on a lot of data, from eligibility data, to claims data, to data obtained from 3rd parties, to data derived from analytics. It’s no surprise that over the last decade “Data & Analytics” has been a consistent entry on the HealthCare Executive Group’s Top 10 list of challenges, issues, and opportunities facing healthcare executives. And currently ranked #1 on the 2019 HCEG Top 10 list. To help share insight, ideas, and actionable information supporting data and analytics, our sponsor partner EQ Health Solutions presented our June Webinar Series event: Solving the Rubik’s Cube of Payer Data.

Chief Strategy & Growth Officer Mayur Yermaneni and Marina Brown, RN BSN, Vice President of Clinical Programs, from eQHealth Solutions shared information and insight on the following four topics:

  • The current state of the payer market and future considerations
  • The Rubik’s Cube of Payer Data – the Present Debacle
  • What tools and technologies will lead to continued payer success?
  • Top six things to consider when evaluating your healthcare analytics vendor

Highlights from Solving the Rubik’s Cube of Payer Data

This blog post presents some highlights from the webinar and provides access to additional information from the webinar. You can also check out this Twitter Moment summarizing live Tweets from the webinar.  The complete recording of the webinar can be found here. To jump to the specific place in the recording, click on the timestamp range [HH:MM] that accompanies each transcripted section below.

HealthCare Executive Group Top 10 list. EQ Health Solutions. Solving the Rubik’s Cube of Payer Data. Health Plans. Payer market. evaluating healthcare analytics vendor. Data Security. Tools and Technologies.

For more information on how EQ Health Solutions can advance your organization’s data and analytics initiatives and programs, contact EQ Health Solutions.

Current State of the Payer Market and Future Considerations

Mayur Yermaneni shared some insight into current data and analytics capabilities of healthcare payers: [7:16]

Some payers are firmly in an average spectrum of recognizing current trends and some and some payers are still in the infancy stages of recognizing the impact of these trends. So, I’m trying to generalize some of these themes so that everybody can actually benefit from it.

Margins are Decreasing

So, across the board, one of the key things, and I guess this is not unique to the payer market itself, is that margins are decreasing. With new regulations coming on board there are more and more cost burden associated with the payer market. Some payers are becoming a financial institution from that standpoint [of increasing regulatory burden.]

Mega Mergers

You see this a lot more in the bigger payer, payers like Aetna’s acquisitions, United’s acquisitions, WellCare and all these acquisitions that are happening is [intended] to counter their decrease in margins by creating economies of scale that they could benefit by actually saying: “If I can actually acquire another of these entities, then I can create a cross burden rate across these common units and hopefully benefit from the margins play game.”

Data Security

Nobody wants to show up and in tomorrow’s Wall Street Journal. In the current day and age, there’s an entire team dedicated just so that that payer’s name doesn’t show up on tomorrow’s newspaper. Primarily because with the PHI (Protected Health Information), the abundance of PHI information from all different sources. It’s extremely important to say: “Well how do we protect our data?” Payers have a lot more data than anybody else outside of providers.

And there are two different spectrums of the data set – and both are equally critical from the standpoint of ensuring that data security is a key aspect in your space because today, a 100 record, 500 records, or anything above that threshold you’re going to have to report it. So, data security becomes actual strategy nowadays. How do you make sure that your data security is actually playing to your advantage? And your customers have to be able to trust that and that Trust is what’s going to actually give you – even though that has nothing to do with the actual health plan itself, or the benefits members are receiving, or the card that they are receiving. But they still have to be able to trust that their data is secure. 

Showing Value Vital in Provider/Hospital Negotiations [10:17]

Finally, when it comes to providing the value of data, the data set that payers are actually having to wrestle with: how are we showing the value that we are providing to the hospital segment, the provider segment, and the member segment? 

But if you look at it, you still have to deal with all the other aspects before you get to the value component: administrative setup, data security, operating margins, and everything.Contract negotiations. HealthCare Executive Group. Benefits Costs. Patient Outcomes. Quality Standards. STAR ratings. Profit Margins. Improving Efficiencies. EQ Health Solutions. Solving the Rubik’s Cube of Payer Data. Health Plans. Payer market. evaluating healthcare analytics vendor. Data Security. Tools and Technologies.Well, how is that actually happening? Big data. Well, I’m not going to bore everybody with the definition of what big data is but, in a nutshell, in today’s world of Instagram, Facebook and Snapchat it’s all about the volume and speed and the frequency of the data that you’re receiving. And in the payer market, it’s a lot of data. It used to be a monthly fee [to obtain/access data]. Now it’s an API call to an HL7 message which is instantaneous. And the amount of frequency that you’re having to deal with is a lot more than what you had before. And the number of types of data that the payer market is actually having to deal with is a lot more. And even in there, the data can be segregated into a couple of different ways: 

  • The data that’s the primary data sources
  • The derived data sources that you’re generating as a result of your operation or as a result of some of the analysis that you’re doing on top of it. 

So now that’s another big trend that the payer market is having to actually wrestle with.

Social Determinants of Health Data are Increasingly Important

Ferris Taylor [HCEG’s Executive Director] indicated that this [Data & Analytics] was the top topic and social determinants of health were one of the key aspects to it. And that hasn’t changed. What has changed is how that’s being viewed. Instead of being a peripheral data source to actually being a central component to how your operations need to be done from social terms of health standpoint.

Marina Brown, EQHealth’s Vice President of Clinical Programs added:

I was just going to say that I do think that this is really a big one for the industry. Social determinants of health are definitely going to help change the way that we deliver health care. And that’s a very important distinguishment. It’s not going to change the way that we do health care because we treat a diabetic the same but it will change the way that we deliver care simply by helping to better guide the interventions that we’re utilizing to create more meaningful behavior change over time.

Tools and Technologies to Solve the Rubik’s Cube of Payer Data

Marina and Mayur shared an overview of the tools and technologies that healthcare payers are using to identify trends, root causes of patient and population-level issues, and transforming healthcare payer’s data and analytics infrastructure.

Another key aspect is artificial intelligence. Now again I don’t want to get into the definitions of artificial intelligence, but the key aspect is, with the advent of big data with the advent of the amount of data you’re having to deal with. It’s not humanly possible for a supervisor or a manager or a management team to be able to simulate all the data and actually say: What am I making use of this data? And how am I going to make use of this data? And what decisions am I making?

So artificial intelligence – or machine learning – and they’re not necessarily synonymous but in some in some aspect they’re synonymous in terms of combining the wealth of data that you’re getting and actually seeing what insights can be derived based on all those data sets; at a much more faster pace and a more timely manner compared to what we would have had to do if we were doing it manually. And there is an element of: how do we use the machine learning algorithms or artificial intelligence approaches to say: Can I do a better prognosis?

Everybody’s aware of [IBM] Watson’s cancer cure approaches to it and Watson has evolved a lot of other stuff. But predominantly in the mainstream the payer market, this hasn’t yet taken off into a full-fledged problem because we’re dealing with not necessarily a literature research but more in the realm of operational research and operational analytics.

Hear more from Mayur and Marina about tools and technologies at [13:09] and [24:53] in the recording.Artificial Intelligence. Predictive Analytics. Bigdata. Machine Learning. HealthCare Executive Group. Benefits Costs. Patient Outcomes. Quality Standards. STAR ratings. Profit Margins. Improving Efficiencies. EQ Health Solutions. Solving the Rubik’s Cube of Payer Data.

How can we employ artificial intelligence or machine learning concepts into the operational realm of the payer operation? [14:40]

There are some positive trends. There’s a huge growth of Medicare Advantage (MA) plans. Their margins continue to increase because it’s a catch-22 situation for MA plans because of the risks. And now MA plans are able to accurately reflect their risk scores. And as a result, their premiums are being reflected the right way – which actually helped them from their margin standpoint because their operations were still on the same aspects of it because in the previous era they were not reporting their risk the right way because they didn’t have all the data gathering up opportunities. But now that they’re able to gather their [data analysis] opportunities, they can predict their risk a lot more accurately, so their premiums are going up. As a result, the margins are getting better and also the operations have stayed the same.

Government Plans Off-Loading Operational Functions to Health Plans

And in the Medicaid managed care space what you’re seeing is a lot more growth in that space for, predominantly, what we could say s for one single reason: most of the state administrative entities are actually trying to off-load the burden onto the plans so that risk is being passed on to the managed care plans and the state entities become the administrative agency. Of course, with that, they’re also holding performance measures as an accountability which is not just about the financial side of it but also the quality side of it because they don’t want to sacrifice the quality of care being rendered to their beneficiaries. But as a result, you’re seeing a lot of growth in the managed care space Medicaid managed care well

What does this mean to me or my organization as a payer? [16:29]

If I actually eliminate all the big terminology, fundamentally there are two simple concepts:

  1. Is our plan performing better than what it was before from a cost standpoint? And with the qualifier added, is the plan performing to a level where the plan can afford too? Because one of which you’re collecting to your risk is what you’re paying out. That’s one of the key foundations. That’s a simple question that you’re going to answer.

And the second aspect of it is:

  1. Are we improving the quality of our plan? And quality can be defined in multiple ways. I think the STAR rating, the HEDIS measures, and all that stuff. But at the end of the day it’s really are you improving quality in terms of outcomes for the members?

And the second point is actually impacting the first point from a long-term standpoint. So, if you’re impacting the quality aspects of it, then you’re able to impact the cost aspect of it as well. But it doesn’t happen every year, it happens over as a strategic view. You have to put that as a strategic view long term view so that on the short run your cost structure might have variances but over a long run, you’re actually improving the trends of that one.Rubik’s Cube of Payer Data. Artificial Intelligence. Predictive Analytics. Bigdata. Machine Learning. HealthCare Executive Group. Benefits Costs. Patient Outcomes. Quality Standards. STAR ratings. Profit Margins. Improving Efficiencies. EQ Health Solutions. Solving the Rubik’s Cube of Payer Data. Health Plans. Payer market. evaluating healthcare analytics vendor. Data Security. Tools and Technologies.

Operational Simplicity and the Health of Your Health Plan [17:54]

But what does that mean in terms of a payer when you think about how you have to think about it?

It comes down to two things: operational efficiency and health of your health plan. How do we make a difference in looking at all the data that we have and actually answer these two business questions; and then tie them back to the simple questions of ‘Am I performing better in terms of cost?’ And ‘Am I improving the cost?’

Marina added: [18:38]

I think that operationally looking at the data is really going to, as a program administrator, is going to give me insight into things like the following:

  • What care management programs or medical management programs are most needed for my population?
  • What programs that I’m currently utilizing are really the most effective ones?

Taking that a step farther as you look into those specific programs that are most effective, you’ll also then be able to look at things like: What are the interventions that are most effective in this population. From a utilization review perspective?

Is my UR working only as a gatekeeper for my health plan or are we actually effectively managing acute episodes and beyond that acute episodes? And then really helping us determine all of this ultimately helps us determine what care intervention strategies do we need to tweak? Which ones do we need to add to our programs to create that meaningful behavior change that increases the health of our membership, increases the quality of the care that’s being provided to that membership, and ultimately reduces the cost?

The Rubik’s Cube of Payer Data – the Present Debacle

Mayur shared some insight into the struggle that many payers have regarding reporting and analytics: [20:03]

In a lot of ways, payers are struggling between: Am I doing reporting or am I doing an analysis? And how am I looking at it? Am I doing the analysis for the sake of reporting or am I doing analysis for the sake of improving or answering the two questions that we started out with?

  1. Is our plan performing better than what it was before from a cost standpoint?
  2. Are we improving the quality of our plan?

HealthCare Executive Group. Benefits Costs. Patient Outcomes. Quality Standards. STAR ratings. Profit Margins. Improving Efficiencies. EQ Health Solutions. Solving the Rubik’s Cube of Payer Data. Health Plans. Payer market. evaluating healthcare analytics vendor. Data Security. Tools and Technologies.And those could be the patient member outcomes, quality standards, STAR ratings, keeping benefits cost down, maintaining the profit margin, improving efficiencies. All of these are questions that every payer is asking.

And the list goes on and on and you guys are actually dealing with a lot more in today’s world. I’m sure every organization has a ton more questions to add to it but, fundamentally, why and how to do it is where the biggest question comes into play because often everybody goes down the path of: ‘Okay, I need to solve this reporting problem so I need to have this kind of technology in place. I need to solve my data analysis problem from a predictive modeling standpoint, so I need to have this technology base.

And as a result, you’re creating more and more silos within the analytic space and not necessarily taking advantage of the full spectrum of the data that you have or creating in its entirety in a holistic view. Because at the end of the day, if the technology analytics is being used for the reporting purposes then you only solve 30% of your problems because the majority of your problems are deriving insights from your data and actually saying how can we make a difference in our operations? How can we make a difference in our outcomes?

Payers have multiple data sources and everything is often viewed as a silo. [23:30]

Healthcare organizations are maturing but fundamentally they’re still struggling with the aspects of:

  • Am I doing quality analysis?
  • Am I doing financial analysis?
  • Am I doing operational analysis?
  • Or am I doing just reporting for the regulatory agencies?

Payers need to design their operational strategy to leverage all quadrants of dimensions: Quality, Financials, Operations, and Predictive Analytics.

Marrying Clinical Expertise with Data Analytic Capabilities [25:04]

HealthCare Executive Group Top 10 list. EQ Health Solutions. Solving the Rubik’s Cube of Payer Data. Health Plans. Payer market. evaluating healthcare analytics vendor. Data Security. Tools and Technologies.

I want to talk briefly about the key components that are going to make a difference. Often what happens is an analyst is asked a question and they actually come back and that data set is then presented to clinical leadership. And then clinical leadership asks a follow-up question and then makes some decisions on top of it. But in reality, what if you change that and involve that clinician up front during the analysis itself, along with the data scientist? So, what we view in the industry is that there’s a lot more benefit if you actually pair the clinicians and the data scientists together up front in the design and analysis phase.

So that 1) you can cut down your cycle crime and 2) you’re asking the questions up front and how to think about your operations. And that’s going to help frame your reporting and analytics problem in a way where you’re getting to a solution much faster.

Marina added:

I think that’s a really important point that you’re making. I think bringing these two teams of people together helps to bring about that important balance and maximize your outputs because your data scientists are experts at identifying the trends and the data. And when that information is presented to the clinicians, they can then help interpret those trends. That’s going to ultimately formulate your adjustments to your operations, your program design, etc. I think that’s a great point.

Pairing Clinicians with Data Scientists Frees Up Time for Patient Engagement

Mayur continued:

And another aspect to it is, when you’re thinking for clinicians, you’re actually taking away their valuable time working with a member. If you’re asking them to understand what’s happening with the data and go into the exercise and then making the decision to it. But if you pair them up front, you’ve solved the problem and then you’re giving them time to have their team’s focus more on the members then they are focusing on the data itself.

Marina added:

Right. Care teams are so busy trying to make that outreach to the members that having that technology available to them, to be able to guide them to identify trends or issues with that particular member, is going to save time. And it ensures too that all of the important or pertinent trends for that particular member, for that particular population, are being identified. Because at the end of the day, clinicians are just that, clinicians. They’re not data analysts.

Developing a Multi-Dimensional, 360-Degree View of Your Data

Marina and Mayur presented some insight and ideas on how to create a decision-making framework providing a multi-dimensional, 360-degree view for your clinical, operational, administrative, and financial teams.

See [28:15] for more information, insight, and ideas on creating a multi-dimensional, 360-degree view of your clinical, operational, administrative, and financial data.

Top Six Things to Consider When Evaluating Healthcare Analytics Vendors

Here are top six things that you should consider when you think about analytics or in the majority of organization’s how you want to get there.

  1. Data Security
  2. In-House Experts
  3. Intuitive Easy-To-Use Platform
  4. Actionable Real-Time Data Visualization
  5. Data Accuracy
  6. Acceptance of Data in Any Format

For details on the importance of each of the above considerations for evaluating healthcare analytics vendors, listen in starting at [36:04].

Questions from Webinar Series Attendees

Our organization currently executes minimal analytical formalities, processes, etc and we are at an immature analytical state. Would investing and working with an analytics vendor refute all [our efforts] at this stage in our organization? [44:37]

Mayur: No. You can view it from the standpoint of: if you’re in the early stages of maturity then that would be the perfect time to assess how you want to design your system and what kind of systems you want to have in place. And you may not have to go through the same evolution steps that the entities started out early on. You may actually leapfrog by taking in all that stuff up front itself. So absolutely, even if you don’t have all the data organized in a unified view that’s fine too because you do have data sets. The first steps very well could be how do you get them into the unified view. So I wouldn’t hesitate working with and investing in analytics if you’re in the early stages of maturity because this very well could be an opportunity where you don’t have to redo the some of the things that you might have done if you’re already in further stages.Artificial Intelligence. Predictive Analytics. Bigdata. Machine Learning. HealthCare Executive Group. Benefits Costs. Patient Outcomes. Quality Standards. STAR ratings. Profit Margins. Improving Efficiencies. EQ Health Solutions. Solving the Rubik’s Cube of Payer Data. Health Plans. Payer market. evaluating healthcare analytics vendor. Data Security. Tools and Technologies.

Our organization prides itself on taking the best care of our patients. Can you give us examples of how using an analytics vendor can improve our patient outcomes vs. just us monitoring it internally? [46:03]

Marina responded to this question with an interesting story about how EQ health identified and assisted high-utilization, low literacy, diabetic patients in the Mississippi Delta.  Listen at [46:22] as to how EQHealth made life easier for patients and improved their health, all while reducing emergency room visits and inpatient admissions.

My team is discussing the decision to build an analytics platform internally or buy and outsource it with a vendor. Do you have any insight into what is more successful and pros and cons? [50:50]

Mayur: I don’t think there is a right answer or wrong answer. It really centers on your strategy. Are you trying to make that as your core competency or are you wanting to retain your core competency to manage plan operations but want to have the benefit of the analytics and the analytics platform; then at that point you should outsource. But if you’re wanting to make analytics your core competency, then you need to have that in-house. But when you do decide to make it in-house, you still need to… hear the rest of Mayur’s answer at [51:08]

Listen to more questions and answers from Solving the Rubik’s Cube of Payer Data here.

More Insight for Healthcare Leaders

Our Webinar Series events are one example of how the HealthCare Executive Group helps to share information and promote collaboration between our members, associates and sponsor partners. Our next Webinar Series event will be ‘Using People, Process & Technology to Grow Your Business’ and will be presented by our sponsor partner HealthEdge on July 25th, 2019 at 2:00 pm ET.HCEG. HealthCare Executive Group Webinar Series: ‘Using People, Process & Technology to Grow Your Business’ HealthEdge.

HCEG’s 2019 Annual Forum

Save The Date HCEG Annual Forum

In addition to connecting with us on Twitter and LinkedIn and subscribing to our eNewsletter, consider joining other healthcare executives and industry thought leaders at our 2019 Annual Forum in Boston, MA on September 9-11, 2019. In addition to the always insightful, information-packed sessions and networking opportunities our annual forum offers, we’re including two special networking events on Monday, September 9th:

  • Tour of the IBM Watson Research Facility in the morning
  • Red Sox vs. Yankees Baseball Game at Fenway Park in the evening

For more information, click here and/or contact us at [email protected].

HCEG Webinar Series Event. “Solving the Rubik’s Cube of Payer Data” Digital transformation. HCEG’s Top 10 Data & Healthcare Analytics. Artificial Intelligence, Machine Learning. Electronic Health Records. EHR. Claims Data. EqHealth Solutions. CMS’s Meaningful Use program. Industry Pulse Social Determinants of Health. Value-based Care. Alternative Payment Models

Healthcare Organizations Focus on Data & Analytics for Digital Transformation

By | analytics, Sponsor, Value-Based Payment, Webinar Series | No Comments

If analytics is the machine powering your digital transformation initiatives, then data is the power making that digital transformation machine run. The importance of data and analytics has been identified by our members in each of the last ten years HCEG’s Top 10 list of challenges, issues, and opportunities have been created. For 2019, “Data & Analytics” is ranked #1 on the HCEG Top 10. It’s clear that healthcare leaders believe that data is a catalyst to accelerate meaningful change. And that the use of analytics – particularly prescriptive analytics – is a fundamental strategy for succeeding in a new era of healthcare.

Mountains of Data Waiting to Power Your Healthcare Analytics Machine

Good analytics begins with good data and healthcare organizations are sitting on a mountain of data. According to America’s Health Insurance Plans (AHIP), the typical regional payer processes $8 billion in claims each year with each claim providing its own set of unique data points – largely financial and administrative. But healthcare payers are increasingly collecting, matching, and using clinical data to provide richer, more comprehensive insight on their members.

Given the proliferation of Electronic Health Records (EHR) incented by CMS’s Meaningful Use program, it’s no surprise that more and more data is being pulled from EHR’s. And risk-sharing agreements between payers and providers has resulted in health plans sharing more claims data with their provider partners. In fact, the current Industry Pulse report indicates that EHR data is one of the top two primary sources of clinical data with 30% of health plans reporting they utilize EHR data.

digital transformation. HCEG’s Top 10 Data & Analytics. Artificial Intelligence, Machine Learning. Electronic Health Records. EHR. Claims Data. EqHealth Solutions. CMS’s Meaningful Use program. Industry Pulse Social Determinants of Health. Value-based Care. Alternative Payment ModelsOther sources of clinical data that organizations are using to complement their claims data include ancillary data such as pharmacy, lab, and imaging (17%) and real-time admission, discharge, and transfer notifications (10%)

RELATED: 9th Annual Industry Pulse Research Survey Results

Popular Use Cases for Healthcare Analytics

These enhanced data sources are becoming more and more useful due to the power of artificial intelligence (AI) and machine learning.

New research from Dimensional Insight identifies care quality measures and finance as two top use cases for healthcare organization usage of analytics today. Additional use cases for leveraging data by analytics include

  • Addressing Social Determinants of Health (#3 on the 2019 HCEG Top 10)
  • Value-based Care and Alternative Payment Models (#4 on the 2019 HCEG Top 10)
  • Improving Patient Engagement and Satisfaction
  • Patient Outcomes Improvement

Analytics Budgets are Increasing for Healthcare Organizations

According to a recent report from the Society of Actuaries, greater than 60 percent of payers and providers are planning to increase their analytics budgets by 15% or more.

Additionally, the report finds that 89% of healthcare executives plan to use predictive analytics over the next five years. It’s clear that healthcare payers and health systems have a keen focus on leveraging the massive amounts of data they possess. These data serve to reveal trends, patterns, and insights to help ensure their success going forward.

Solving the Rubik’s Cube of Payer Data

i.e. Lining Up All Your Data to Rapidly and Accurately Gain Unique Insights

For insight into how your healthcare organization’s data can be used to improve health outcomes and reduce costs, join our next Webinar Series Event on June 6th at 2:00 PM EDT / 11:00 AM PDT. Our sponsor partner eQHealth Solutions presents “Solving the Rubik’s Cube of Payer Data.”In this complimentary webinar, you will learn how to aggregate and parse provider data, how you can use data captured outside of your own system, and other practical solutions to use your data to create knowledge for actionable use and outcomes. Attendees will have a chance to ask questions and all registrants will receive a copy of the presentation afterward.HCEG Webinar Series Event. “Solving the Rubik’s Cube of Payer Data” Digital transformation. HCEG’s Top 10 Data & Healthcare Analytics. Artificial Intelligence, Machine Learning. Electronic Health Records. EHR. Claims Data. EqHealth Solutions. CMS’s Meaningful Use program. Industry Pulse Social Determinants of Health. Value-based Care. Alternative Payment Models

Population Health, Value-Based Care, & The Engaged Digital Consumer – An Executive Leadership RoundTable

By | AHIP, analytics, Executive Leadership Roundtable, HCEG Top 10, Nashville, Population Health, Social Determinants of Health, Value-Based Care, Value-Based Payment | No Comments

On the 2018 HCEG Top 10 list, Clinical and Data Analytics, Value-based Payments and The Engaged Digital Consumer were ranked #1, #3 and #10 respectively by health plan, health system and healthcare provider executives who participated in identifying and ranking the 2018 HCEG Top 10. It seems fair to say that these three topics are front and center on the mind of executives and thought leaders in the healthcare industry.

Leverage Your AHIP Event & Nashville Connection

If you’re attending AHIP’s 2017 Consumer Experience & Digital Health Forum in Nashville or if you’re a healthcare leader in Nashville the afternoon of Thursday, December 7th, consider joining other healthcare executives and thought leaders at our Executive Leadership Roundtable. A panel of prominent healthcare leaders will meet at Nashville’s Center for Medical Interoperability at 1:00pm CT to accelerate the seamless exchange of information to improve healthcare for all by exploring emerging and high-priority healthcare opportunities at the intersection of population health, value based care, and the engaged digital consumer.

Join Healthcare Leaders & Forum Attendees in a Boardroom-like Setting

HCEG Executive Leadership Roundtable events are held in an intimate, informal and free-flowing setting where the free exchange of ideas, questions and comments are encouraged. This roundtable event will be moderated by Dr. David Diloreto with three distinguished panelists sharing their unique perspective and insight:

Dr. David DiloretoBen LeedleFerris TaylorDavid Gallegos
Senior VP of Healthcare-Population Health at General ElectricPresident & CEO at Blue Zones and former President & CEO of HealthwaysHCEG Board Chair and COO/Consultant at Arches Health PlanSenior VP of Consulting Services at Change Healthcare

Timely Topics for Healthcare Leaders

A timely and valuable set of topics – with a special focus on Social Determinants and Clinical Data Impacting Population Health – are planned for panelists and attendees:

  • Innovative strategies health plans, health systems and provider organizations are using to reduce downstream spending while improving overall health outcomes by addressing social determinants of health.
  • How state-of-the-art data and technologies and opening new opportunities to move consumer health forward.
  • Opportunities to work with community leaders to identify the factors having the most influence on individual health and quality of life.
  • Considerations for tailoring specific approaches and investment to address the needs of health plan members and healthcare patients in their communities.
  • How ground-level community stakeholders can guide health plans and health systems to where funding creates the most effective SDOH improvements.

Extend the Value of Your AHIP Consumer Experience & Digital Health Forum Attendance

In addition to the value described above, this Executive Leadership Roundtable event will include a tour of the Center for Medical Interoperability, lunch and the opportunity for professional networking with roundtable panelists and participants. The Center for Medical Interoperability is a ten-minute ride from the AHIP Consumer Experience & Digital Health Forum being held at the Music City Center in Nashville, TN.

Reserve Your Seat Today!

Attendance at the roundtable is free for current and former HCEG members, attendees of the AHIP Consumer Experience & Digital Health Forum and local healthcare executives.  If you have any questions, please contact us.

Healthcare Executive Leadership Forum at Guidewell Innovation Center

‘Next Gen’ Data Strategy, Architecture and Technology to Achieve Innovation & Growth

By | AHIP, analytics, Sponsor | No Comments

marklogic ahip institute Operationalize Before You Analyze: Innovation and Growth Powered by DataMany of our sponsor partners participated in the 2017 AHIP Institute & Exhibition in Austin, Texas earlier this month – sharing info on their healthcare products and services; and sharing information via informal and formal presentation sessions.

Bill Fox, VP of Healthcare and Life Sciences of our sponsor MarkLogic, moderated a panel titled “Operationalize Before You Analyze: Innovation and Growth Powered by Data.” The panel of business and technical leaders discussed how they have used “next gen” data strategy, architecture and technology to achieve innovation, growth and modernization results.  Panel members included:

Sunil Godbole, Senior Director, Application Development at Aetna Inc.

Glen Schuster, Consultant, former CTO at Centene Corp

Shahran Haider, Managing Director of Enterprise Data Strategy and Analytics at L.A. Care

Analyzing Data and Operationalizing Data Are Not the Same Thing

Bill Fox began the panel discussion by offering that analyzing data and operationalizing data are not the same thing and that many health care organizations have focused their innovation and growth investment on the “shiny ball” of analytics — the end stage of the data journey — instead of first improving the agility and speed at the beginning “operational” stages of the data journey.

Save Time on Operations – More Time for Innovation

Glen Schuster: “When companies try to do operations and analytics at same time, it’s operations that almost always ‘wins’”

Sharan Haider: “Now is the time to innovate. And to do that, organizations have to free up time and iterate through faster execution cycles that add more value to operations while improving member and consumer experience.”

Sharan Haider: “If we shorten the amount of time needed to get data together, we can innovate and do analytics better and faster.”

Flexible, Secure, Multi-Model Database Systems are Key

Bill Fox: “Next generation systems must be able to provide users with what they want, how they want it, and when they want it. Data can’t be siloed across numerous legacy systems but must be virtualized in a multi-model database capable of supporting multiple data models against a single, integrated back end where structured and unstructured data in multiple formats are all supported by a flexible and secure infrastructure.”

Glen Schuster: “Value-based reimbursement and managing risk demand that healthcare firms deal with their legacy architecture and employ the resources necessary to facilitate change. Data is classically under reported. A company that can gather data and improve its quality will be in a better position to manage its risk and gain a significant competitive advantage.”multi-model database data models integrated backend structured unstructured marklogic hceg ahip institute

Rapid Implementation with Proven Business Case

Glen Schuster: “It’s easier now to create a hard dollar business case for operationalizing data. Do you know where your data is? How difficult is it to collect, combine and operationalize your data? Over-analyzing cost vs. worth can be an unproductive conversation.”

Sharan Haider: “I know I have a problem. I come to conferences and get excited at what I see. But I’m also a realist. I need to be able to implement solutions from my point of view. To be able to collect, merge and manage my data better and faster.”

Sharan Haider: “We are working to develop a 360 view of our provider customer service, appeals and grievances data in 4-6 weeks. What was a long-term pain and seemed unsolvable was suddenly doable.”

Centers of Excellence and Scaled Agile Framework

Sunil Godbole: “We had an impossible data problem and started our journey 2 ½ ago. We strive to make whatever we build with reusable assets. We established a Center of Excellence (COE) and got the best resources available on market. Our COE performs governance, builds frameworks (ex. Logging, alerts, ingest and egress methods, etc.) that we can extend to all lines of business, affiliates, and other data centers.”

Sunil Godbole: “Code quality has to be present. We employ a Scaled Agile Framework (SAFe) and consistently enforce its use. We do brown bags with scrum teams, new developers and business stakeholders to maintain and grow our skills based and data agility-focused culture.”

Learn More About Healthcare Innovation & Transformation

For more insight and ideas on digitally transforming your healthcare operations and analytics, check out our sponsor partners and consider following the Healthcare Executive Group and our sponsors on social media.

Change Healthcare –> @Change_HC
Cumberland Consulting Group –> @CumberlandCG
GuideWell Connect –> @_GWConnect
HealthEdge –> @HealthEdge
MarkLogic –> @MarkLogic
McKesson –> @McKesson
Softheon –> @Softheon
Virtual Health –> @VirtualHealth_

An Executive Leadership Forum at GuideWell Innovation Center

By | analytics, Executive Leadership Forum, Security | No Comments

Executive Leadership Forum at GuideWell Innovation Center hcldr hitsm innovationOur Executive Leadership Forum held at the GuideWell Innovation Center on Monday, May 8th was attended by 21 healthcare executives and solution provider thought leaders. The three-hour event – titled Operationalizing Before Analyzing: Healthcare’s Modern Journey Powered by Data – focused on some of the underlying challenges and issues regarding how healthcare data and analytics technologies impact consumers, providers and health plans.

The forum included lively discussion on real world use cases for healthcare data and analytics, a demonstration of live 3D interaction possibilities and a tour of the GuideWell Innovation Center. The forum was capped off by a happy hour for participants to network with each other and forum sponsors: MarkLogic and Intel.

In this post, highlights of the discussion between forum participants and key takeaways will be presented. In future posts, an overview of the 3D interaction demo and tour of the GuideWell Innovation Center will be shared.

HCEG Board Chair Ferris Taylor shared some information on the tour of the GuideWell Innovation Center and Live 3D Collaboration in this post on LinkedIn.

Demand for Real-time Data and Transactions

A lot discussion during the forum centered around current complexities and how demand for real-time data and transactions—across clinical, administrative and financial operations–is increasing exponentially every day and putting significant demands on service model / operations and legacy infrastructure, which are mostly batch / file transfer oriented.  Several issues were identified as current concerns:

  1. Many underlying data challenges
  2. Lack of agility in quickly responding to opportunities
  3. Inadequate data governance/provenance with ETL approaches in the legacy data pipeline

All audience members agreed they wanted faster time to market and better ability to respond to clients / market / regulations and be more agile when it comes to data. There was broad agreement that “data integration” is a journey that should follow a new data integration pathway instead of the legacy Extract-Transform-Load (ETL) approach:

Real World Use Cases

Over the course of the discussion there were a number of data capture and analytics use cases shared between forum participants. One use case described enrollment data submitted to the IRS on the 1095-B Health Coverage forms sent to individuals noting their qualified health coverage during each month in the year.

One participant described how the IRS had reported back to the health plan that 40% of the records submitted by the health plan to the IRS had errors in name, social security number and/or dependent status; basic required enrollment data elements that the plan was not able to validate or authenticate during the initial enrollment process and remained that way throughout the entire year. Garbage-In-Garbage-Out.

This “1095-B use case” elicited feedback from one forum participant having recent experience at the Census Bureau with the participant describing how government agencies often don’t have complete, accurate data. Just because CMS might have data of one quality level, they don’t always share that data with related agencies so the IRS or the SSA or state Medicaid administrators likely have different data.

Leverage All Data Types & 3rd Parties

Forum participants shared unique perspectives and a Q&A ensued on the example of how the Census Bureau uses associated data to significantly improve the timelines, accuracy and overall value of census data by editing it against 3rd party sources.  This Census Bureau use case and another use case described by forum participants of a BCBS plan emphasized that 3rd party data sources and unstructured data are very important to service improvement, member/patient experience, innovation and growth-oriented project investments.

Primary Investment Areas: Data Improvement & Integration Projects

Forum members identified the following investment areas for data improvement and integration projects that healthcare executives may implement over the next 12-18 months to modernize healthcare data and applications:

healthcare-data-integration-investment-areas-ELF-Blues-MarkLogicThought Leader Presentations

This Executive Leadership Forum was co-sponsored by MarkLogic and Intel. The information shared by these two sponsors are made available here:

    “Healthcare ‘Next Gen’ Data Projects”Bill Gaynor, U.S. Healthcare Director – MarkLogic, Inc.

    “Intel Healthcare Security Readiness Program Overview”Joan Hankin – Global Director of Marketing & Business Development – Healthcare & Life Sciences at Intel Corporation

In addition to information shared by MarkLogic and Intel, Constance Sjoquist, former Research Director at Gartner, also participated:

    “Disrupting the Status Quo in Healthcare” – By Constance Sjoquist, Chief Content Officer – HLTH, LLC.

Three Basic Tenets Unanimously Agreed

At the end of the forum, participants unanimously agree on three basic tenets:

  1. Complete and accurate data – especially basic demographic and social determinants – MUST begin with the first member/consumer/patient-provider interactions at the point of service
  2. Data needs to be authenticated, validated, verified and ENRICHED against other sources – then normalized across other supportive partners and their ‘systems of record’
  3. Today’s technology can support the capture, validation and use of healthcare data on a relatively inexpensive basis.

Join Other Healthcare Leaders

For more information on the Healthcare Executive Group and how you can become more ‘in the know’ and effective as a healthcare executive or thought leader, check out this information about becoming a member. You can also follow us on Twitter, friend us on FaceBook and follow us on LinkedIn.

How Predictions About Healthcare in 2017 Compare to HCEG Top 10 List

By | analytics, payer, Top 10 | No Comments

2017 Healthcare Predictions HCEG

It’s that time of year when everyone is sharing their thoughts on healthcare predictions and trends for 2017. And the Healthcare Executive Group wants to take this opportunity to share what it considered the Top 10 Priorities, Issues and Challenges facing healthcare supply-side constituents: health plans, payers, providers and health systems.

History of HCEG Top 10 List

The HCEG Top 10 list of Healthcare Priorities, Issues and Challenges has been a pillar of the Healthcare Executive Group for the last 12 years. The list is developed each year during HCEG’s annual forum and reflects what HCEG healthcare executive members think will be their primary focus for the following year.

The HCEG Top 10 list for 2017 includes the following items:

  1. Value-based Payments: targeting specific medical conditions to manage cost and quality of care
  2. Total Consumer Health: improving member’s overall well-being – medical, social, financial, and environmental
  3. Clinical and Data Analytics: leveraging big data with clinical evidence to segment populations, manage health and drive decisions
  4. Cybersecurity: protecting the privacy and security of consumer information
  5. Cost Transparency: growing legislation and consumer demand
  6. Harnessing Mobile Health Technology: improving disease management, member engagement, and data collection/distribution
  7. Addressing Pharmacy Costs: implementing strategies to address growth of pharma costs versus benefits to quality of care and total medical costs
  8. Care Redesign: leveraging team-based care models, focusing on behavioral health and social needs
  9. Accessible Points of Care: telehealth, retail clinics and micro-hospitals vs. large, integrated systems
  10. Next Generation ACOs: additional programs in bundled payment, episodes of care-shared savings, and growing participant base

To be sure, the items on the HCEG Top 10 list may not be considered predictions as much as they are ‘important areas for those on healthcare’s supply side to be aware of in 2017.’

“It’s tough to make predictions, especially about the future” – Yogi Berra

And it’s not just HCEG members who compile lists of predictions and trends for the healthcare industry. In the waning weeks of the year, industry professionals, health plan and hospital system CEO’s, leading consulting firms like PWC and Accenture, research firms like Gartner, media reporters, and a host of others all share their take on what they consider to be important trends and predictions for the upcoming year. Here’s a list of some of those sharing their 2017 Healthcare Predictions.

Given the ubiquity of “predictions for healthcare in 2017” and the fact that healthcare was a primary issue in the U.S. presidential election, it seemed that comparing HCEG ‘s Top 10 list to the summarized results of 2017 healthcare predictions made by others would confirm HCEG’s list and/or call out differences. The fact that the HCEG Top 10 list was compiled BEFORE the presidential election and all of the comparison lists were created AFTER the election is envisioned to, at least somewhat, account for any impact the election may have had on people’s interpretation of priority and value.

Collection of Predictions about Healthcare & Healthcare Technology in 2017

To establish a baseline list of predictions and trends for healthcare in 2017, the lists contained in this blog post were reviewed with categorized based on their primary and secondary categories with the results compared to the items on the HCEG Top 10 list. A few facts and observations about this baseline list:

  1. 36 lists containing a total of 179 “predictions” were curated
    HCEG 2017 Predictions - Major Categories

    HCEG 2017 Predictions – Major Categories

  2. Only predictions that were clearly understood and of sufficient granularity were included
  3. Each prediction was coded with one of the following 19 primary categories
  4. Where possible, a secondary category was assigned

Analysis of 2017 Predictions

Most Frequently Referenced Categories

In terms of most frequently referenced predictions (regardless as too rank) found among the 30 lists reviewed, Emerging Technologies, Reform/Regulations, Analytics & Big Data, Value-based Reimbursement, Access, and Consumerism were among the most frequently cited areas of focus in 2017.

CategoryCountCorresponding HCEG Top 10 Item(s)
Emerging Technologies296-Harnessing Mobile Technology
Reform/Regulations248-Care Redesign (loose correlation)
Analytics & Big Data193-Clinical and Data Analytics
Value-Based Reimbursement161-Value-based Payments

5-Cost Transparency

Access139-Accessible Points of Care
Consumerism112-Total Consumer Health
Interoperability9
Finance/Reimbursement91-Value-based Payments

5-Cost Transparency

7-Addressing Pharmacy Costs

Cybersecurity84-Cybersecurity
Mobile Health66-Harnessing Mobile Technology
Processing Efficiency6
Digital Transformation56-Harnessing Mobile Technology
Collaboration510-Next Generation ACOs
Mergers & Acquisitions4
Health Literacy42-Total Consumer Health

5-Cost Transparency

Pharmacy37-Addressing Pharmacy Costs
Resources3
Precision Medicine28-Care Redesign
Wearables26-Harnessing Mobile Technology
Patient Experience12-Total Consumer Health

9-Accessible Points of Care

Categories by Top 3 Rankings

In an attempt to present the data in a more generalized fashion, the following table reflects the ranking of the categories based on the sum of the top three rankings for each item.

CategoryCountTop 3 CountTop 3 % of CountCorresponding HCEG Top 10 Item(s)
Reform/Regulations241563%8-Care Redesign (loose correlation)
Emerging Technologies291448%6-Harnessing Mobile Technology
Analytics/Big Data191263%3-Clinical and Data Analytics
Consumerism11873%2-Total Consumer Health

5-Cost Transparency

Access13754%9-Accessible Points of Care
Value-based Care16744%1-Value-based Payments

5-Cost Transparency

Cybersecurity8675%4-Cybersecurity
Finance/Reimbursement9667%1-Value-based Payments

5-Cost Transparency

7-Addressing Pharmacy Costs

Mobile Health66100%6-Harnessing Mobile Technology
Collaboration55100%10-Next Generation ACOs
Digital Transformation55100%6-Harnessing Mobile Technology
Interoperability9556%
Processing Efficiency6583%
Health Literacy4375%2-Total Consumer Health
Mergers & Acquisitions4375%
Pharmacy33100%7-Addressing Pharmacy Costs
Resources33100%

Insights on How HCEG List Compares to General 2017 Predictions

While certainly subject to some interpretation and discussion, the following four areas listed by many of those sharing their 2017 Predictions were NOT directly matched to any of the items on HCEG’s Top 10 list.

CategoryPrediction from Article
Interoperability
  • Acceleration of Interoperability
  • EHR access
  • Financially stable, regional IDNs are spending big dollars toward extended connectivity while rest of the pack looks on
  • Integrated systems
  • Integration of medical & social determinants of health
  • Interoperability: Continuing progress
  • More progress and collaboration around interoperability
  • Organizations choosing platforms vs. application silos will only accelerate
Processing Efficiency
  • $1 of innovation will need $7 of core execution
  • Adoption of auto-adjudication will accelerate
  • Auto-adjudication will drive providers to interact with EHRs, revenue cycle management and practice management vendors.
  • Complex claims outsourcing market grows
  • Cost reduction pressures require balance with compliance demands
  • Focus on front end and middle office business office functions & RCM outsourcing intensifies.
M&A
  • Consolidation of activities to Top 7 Digital Giants
  • Continued growth of merger and acquisitions as the reimbursement mechanisms favor organized groups of providers.
  • Many more insurers will drop out of the marketplaces.
  • Maturation of digital health startups and increasing merger and acquisition activity
Resources
  • Human resources shortage
  • Skilled hospital tech staff recruitment is even more challenging.
  • The rise of non-CIO executives in technology decisions: Not quite yet

Note: Items in above table were culled from various articles listing 2017 Predictions. 

Overall Rankings of 2017 Predictions

The following major categories of 2017 Healthcare Predictions are based on the rank assignments as noted by the author of each of the individual articles/posts.

#1 Ranking36% of Ttl#4 Ranking22% of Ttl
Reform/Regulations719%Value-Based Care523%
Emerging Technologies411%Analytics/Big Data418%
Value-Based Care411%Reform/Regulations314%
Cybersecurity411%Interoperability29%
Finance/Reimbursement38%Access29%
Analytics/Big Data38%
Consumerism38%#5 Ranking17% of Ttl
Emerging Technologies424%
#2 Ranking34% of TtlValue-Based Care212%
Analytics/Big Data618%Processing Efficiency212%
Emerging Technologies515%
Reform/Regulations515%#6 Ranking12% of Ttl
Digital Transformation39%Access217%
Consumerism26%Emerging Technologies217%
Finance/Reimbursement26%Reform/Regulations217%
Processing Efficiency26%
Mobile Health26%#7 Ranking11% of Ttl
Emerging Technologies327%
#3 Ranking31% of TtlReform/Regulations218%
Emerging Technologies516%Analytics/Big Data19%
Access516%
Mobile Health310%#8 Ranking6% of Ttl
Analytics/Big Data310%Emerging Technologies350%
Consumerism310%Resources117%
Reform/Regulations310%Consumerism117%

Note: Some lists didn’t explicitly rank their predictions as #1, #2, #3, etc. In those cases, rank was assigned based on the precedence of the prediction in the article. I.e. if a specific prediction was listed before another prediction , it was assumed that prediction ranked higher.

Other Insights

The Most Frequently Referenced Categories, Categories by Top 3 Rankings and Overall Rankings of 2017 Predictions Results listed above provide a few instances of correlation with and diversion from the 2017 HCEG’s Top 10 list.

Note: The contents of the tables below were were culled from the various articles listing 2017 Predictions. 

Emerging Technologies

On area of divergence between the HCEG Top 10 list and 2017 Healthcare Predictions Baseline is that Emerging Technologies were not clearly identified by HCEG as of primary focus in 2017. In general, “emerging technologies” are identified as things like 3D printing, AI/machine learning, augmented reality, Blockchain, cloud, drones, Internet of Things, medical devices and robotics. One may argue that, given HCEG’s membership is skewed toward health plans/payers, that  these emerging technologies are not part and parcel of a healthplan/payer-based focus. Given their dominance and potential value, perhaps they should be?

Some Predictions on Emerging Technologies

Adoption of technologies within realm of AI, including RPA and machine learning, will move very fast and take over in many different ways.
Blockchain will move from theory to practice, as pilots and production-ready applications become a reality.
Hype around the Cloud quiets down as it becomes the primary way to build enterprise architecture.
60% of healthcare applications will collect real-time location data and clinical IoT device data and embed cognitive capabilities to discover patterns
Gadgets will continue to be commoditized and competition will grow
IoT will save $1 Trillion a year in maintenance, services & consumables
50% increase in the use of robots to deliver medications, supplies, and food throughout the hospital

Health Reform/Regulations

Given the largely unexpected results of the presidential election, it’s not a surprise that the uncertainty of healthcare reform and regulations jumped to the top position for impacts to healthcare in 2017. Elections have consequences. No doubt as one prognosticator stated “The Trump Presidency Will Rock the Healthcare Boat.”

Some Predictions on Health Reform/Regulations

Massive confusion on status of the ACA
President-elect Donald Trump will likely not fulfill his promise to completely repeal the ACA
The Trump Presidency Will Rock the Healthcare Boat
Regulation drives demand for advanced data and analytics capabilities
Movement by employers away from defined benefit plans to defined contribution plans and increased participation in private exchanges. –
Expand the use of health savings accounts for consumers.
Medicaid expansion costs will be incorporated in the Medicaid block grants
Republicans will attempt to “modernize” Medicare through vouchers or tax credits
There will be continued movement to narrow network products in an attempt to hold down costs.
Federal insurance license changes allowing for competition and selling over state lines
Healthcare startups: Make nice with regulators in 2017

Analytics & Big Data

Predictions about the importance of healthcare analytics made by HCEG members was one area that matched the general baseline as ranking #3.

Some Predictions on Analytics & Big Data

AI (artificial intelligence) or machine learning to translate big data into actionable insights
Convo on healthcare becoming one of most interesting “Big Data” petri dishes society has to offer begins.
Evidence-based decision making (expanded use of data and analytics) to eliminate unnecessary utilization and increase patient safety
Contextualization algorithms will advance exponentially
Advancing data governance
Combining structured and unstructured data
Consortiums of data: genomic, social, EMR, complaint and prescription data, emerge that will create insights never before possible
Mastery of unstructured data will deliver customer insight
Moving to metadata
Taking advantage of real-time data
Startups in analytics space begin to challenge  large, incumbent players and healthcare organizations will begin to actively engage with these new players.

Value-based Reimbursement

Value-based care and reimbursement were highly ranked on both the HCEG Top 10 list and the 2017 Healthcare Predictions Baseline. Given the importance of value-based reimbursement and general bi-partisan support for value-based initiatives like MACRA, VBR should largely survive drastic alteration under the new administration.

Some Predictions on Value-based Reimbursement 

Value-based care will drive adoption of tools for chronic disease management
Easing the training wheels off value-based payment
2017 will be a year for learning about the alternative reimbursement methodologies and planning for the compliance program requirements of the future.
Preparing medical students for work in a value-based world
More performance-based measures beyond cost to quality and satisfaction
Renewed and upgraded Enterprise Resource Planning Systems (ERP) swings back into importance, now for Value Based Care Costing.

Access

HCEG members ranked ‘access’ topics lower than the general baseline.

Some Predictions on Access

The rise of decentralized healthcare and the decline of hospitals.
Significant rise in voluntary services/ healthcare for the wealthy
Self-select virtual care – for convenience
Telehealth will no longer be on the outskirts, pushed into the mainstream with expanded reimbursement policies, usage and outreach programs

Additional Insight Can Be Obtained Here

HCEG Top 10 Info

Collection of 2017 Healthcare Predictions

Raw Data – here is the raw data collected from the various articles on 2017 Healthcare Predictions

Following is a List of Articles used for this analysis – See more info here.

#Title
1“3 Mega Trends for Healthcare Marketers to Leverage in 2017”
2“5 healthcare technology trends taking center stage in 2017”
3“7 Bold Predictions for Healthcare in 2017”
4“Healthcare CFOs weigh in on 2017 challenges, trends in latest surveys”
5“Healthcare Industry Trends to Watch”
6“Healthcare Predictions for 2017”
7“Healthcare Technology Trends for 2017”
8“How Consolidation Will Impact Hospitals and Health Systems in 2017”
9“List Top 10 predictions for IT in 2017 and beyond”
10“5 healthcare technology predictions for 2017 from Connexica” 
11“Retail Trumps Healthcare in 2017: Health/Care Forecast for the New Year”  
13“These Trends Could Reshape Healthcare Tech in the Very Near Future”
14“Top health industry issues of 2017: A year of uncertainty and opportunity”
16“Upcoming Trends and Innovations in Healthcare IT 2017”
17“What to Watch: Health Care Trends for 2017”
18“10 Predictions for How the Healthcare Industry Will Change in 2017”  
19“2017 Predictions: Big Data, Digital, and Virtual Care Key to Engage Healthcare’s Empowered Consumer”
21“4 Business Trends to Watch in the Insurance Industry for 2017”
22“5 Digital Health Predictions for 2017”
23“5 Healthcare IT Trends to Watch In 2017” 
24“7 (plus 1) predictions for healthcare IT in 2017” 
25“8 Health Tech Challenges and Opportunities in 2017” 
26“9 Healthcare Tech Trends in “The New Year of Uncertainty” 
27“Coming Soon to Your Hospital: IoT, Cognitive Computing, Robots and More Ransomware”  
28“Healthcare Predictions 2017: Accelerated Adoption of Alternative Payment Models”   
30“How market changes will influence data priorities in healthcare”
31“Post-Election Predictions for the Healthcare Industry”  
32“7 digital health predictions for 2017” 
33“Tom Main and Welltok’s Jeff Margolis Make Their 2017 Predictions” 
35“2017 Healthcare Trends Forecast: Spok Leaders Weigh In” 
36“2017 Predictions from Healthcare Leaders Across the Country” 
37“Trends in health IT for 2017: Ransomware, RPA, blockchain predictions”  
38“8 technologies that will transform healthcare in 2017 and beyond”  
39“Five Health IT Trends I’m Looking Forward to in 2017” 
40“The election is over: 3 health care predictions”  
41“2017 Predictions: Medicare, Drug Costs, Cybersecurity and More”