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Self-Learning Analytics and Making Analytics Useful

Posted on April 2, 2018 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

One of the shocks to me at HIMSS 2018 was that there wasn’t nearly as much discussion around healthcare analytics as I thought there would be. I thought for sure we’d see an explosion of proven analytics that healthcare organizations could start to take advantage of. Maybe I just missed it, but I certainly didn’t see anything all that new.

It’s too bad because that’s one of the huge opportunities I see for healthcare. I was looking through some old notes from conferences and saw a note where I wrote: “What you do with the data is the competitive differentiator, not the data.

Certainly, you need access to the data to be successful, but there are a lot of organizations out there which have access to health data and they’re not making any sort of dent. Many of the now defunct HIEs had access to the data, but they didn’t know what to do with all that data. I’m still on the search for more analytics which are useful.

One other idea I found in my notes was the concept of a self-learning analytic. Related to this was the discussion we had about black box analytics in a recent #HITsm Twitter chat. I don’t think they have to be the same, but I do think that the key to successful healthcare analytics is going to require some component of self-learning.

The concept is simple. The analytic should look at its past recommendations and then based on the results of past recommendations, the analytic should adjust future recommendations. Notice that I still call it recommendations which I think is still the right approach for most analytics. This approach to constantly learning and evolving analytics is why it’s so hard to regulate healthcare analytics. It’s hard to regulate moving targets and a self-learning analytic needs to be moving to be most effective.

This is possibly why we haven’t seen an explosion of healthcare analytics. It’s hard to get them right and to prove their effectiveness. Plus, they need to continually evolve and improve. That’s the opposite of what researchers want to hear.

This is why the future of healthcare analytics is going to require deep collaboration between healthcare analytics vendors and provider organizations. It’s not a black box that you can buy and implement. At least not yet.

What’s been your experience with healthcare analytics? Where are you seeing success? We’d love to hear your thoughts in the comments.

#HIMSS18 First Day:  A Haze Of Uncertainty

Posted on March 7, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Entering the HIMSS exhibit area always feels like walking straight into a hurricane. But if you know how to navigate the show, things usually start to come into focus.

There’s a bunch of young, scrappy and hungry startups clustered in a hive, a second tier of more-established but still emerging ventures and a scattering of non-healthcare contenders hoping to crack the market. And of course, there are the dream places put in place by usual suspects like Accenture, SAP and Citrix. (I also stumbled across a large data analytics company, the curiously-named splunk> — I kid you not – whose pillars of data-like moving color squares might have been the most spectacular display on the floor.)

The point I’m trying to make here is that as immense and overwhelming as a show like HIMSS can be, there’s a certain order amongst the chaos. And I usually leave with an idea of which technologies are on the ascendance, and which seem the closest to practical deployment. This time, not so much.

I may have missed something, but my sense on first glance that I was surrounded by solutions that were immature, off-target or backed by companies trying to be all things to all people. Also, surprisingly few even spoke the word “doctor” when describing their product.

For example, a smallish HIT company probably can’t address IoT, population health, social determinants data and care coordination in one swell foop, but I ran into more than one that was trying to do something like this.

All told, I came away with a feeling that many vendors are trapped in a haze of uncertainty right now. To be fair, I understand why. Most are trying to build solutions without knowing the answers to some important questions.

What are the best uses of blockchain, if any? What role should AI play in data analytics, care management and patient interaction? How do we best define population health management? How should much-needed care coordination technologies be architected, and how will they fit into physician workflow?

Yes, I know that vendors’ job is to sort these things like these out and solve the problems effectively. But this year, many seem to be struggling far more than usual.

Meanwhile, I should note that there seems to be a mismatch between what vendors showed up and what providers say that they want. Why so few vendors focused on RCM or cybersecurity, for example? I know that to some extent, HIMSS is about emerging tech rather than existing solutions, but the gap between practical and emerging solutions seemed larger than usual.

Don’t get me wrong – I’m learning a lot here. The wonderful buzz of excited conversations in the hall is as intense as always. And the show is epic and entertaining as always. Let’s hope that next year, the fog has cleared.

Partners AI System Gives Clinicians Better Information

Posted on January 25, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

While HIT professionals typically understand AI technology, clinicians may not. After all, using AI usually isn’t part of their job, so they can be forgiven for ignoring all of the noise and hype around it.

Aware of this problem, Partners Connected Health and partner Hitachi have come together to create an AI-driven process which isolates data physicians can use. The new approach, dubbed ‘explainable AI,’ is designed to list the key factors the system has relied upon in making projections, making it easier for physicians to make relevant care decisions.

Explainable AI, a newer term used by the two organizations, refers not only to the work being done to develop the Partners system, but also a broader universe in which machines can explain their decisions and actions to human users. Ultimately, explainable AI should help users trust and use AI tools effectively, according to a Hitachi statement.

Initially, Partners will use the AI system to predict the risk of 30-day readmissions for patients with heart failure. Preventing such readmissions can potentially save $7,000 per patient per year.

The problem is, how can organizations like Partners make AI results useful to physicians? Most AI-driven results are something of a black box for clinicians, as they don’t know what data contributed to the score. After all, the algorithm analyses about 3,000 variables that might be a factor in readmissions, drawing from both structured and unstructured data. Without help, there’s little chance physicians can isolate ways to improve their own performance.

But in this case, the AI system offers much better information. Having calculated the predictive score, it isolates factors that physicians can address directly as part of the course of care. It also identifies which patients would be the best candidates for a post-discharge program focused on preventing readmissions.

All of this is well and good, but will it actually deliver the results that Partners hoped for? As it turns out, the initial results of a pilot program are promising.

To conduct the pilot, the Partners Connected Health Innovation team drew on real-life data from heart failure patients under its care. The patients were part of the Partners Connected Cardiac Care Program, a remote monitoring education program focused on managing their care effectively in reducing the risk of hospitalization.

The test compared the results calculated by the AI system with real-life results drawn from about 12,000 heart failure patients hospitalized and discharged from the Partners HealthCare network in 2014 in 2015. As it turned out, there was a high correlation between actual patient readmissions and the level predicted by the system. Next, Partners will share a list of variables that played the biggest role in the AI’s projects. It’s definitely a move in the right direction.

New Program Trains Physicians In Health Informatics Basics

Posted on January 18, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

A new program has emerged to help physicians make better use of the massive flow of health information they encounter on a day-to-day basis. With any luck, it will not only improve the skills of individual doctors but also seed institutions with clinicians who understand health IT in the practice of medicine.

The Indiana Training Program in Public and Population Health Informatics, which is supported by a five-year, $2.5 million award from the National Library of Medicine, focuses on public and population health issues. Launched in July 2017, it will support up to eight fellows annually.

The program is sponsored by Indiana University School of Medicine Richard M. Fairbanks School of Public Health at Indiana University-Purdue University Indianapolis and the Regenstrief Institute. Regenstrief, which is dedicated to healthcare quality improvement, supports healthcare research and works to bring scientific discoveries to bear on real-world problems.

For example, Regenstrief participates in the Healthcare Services Platform Consortium, which is addressing interoperability issues. There’s also the Regenstrief EHR Clinical Learning Platform, an AMA-backed program training medical student to cope with misidentified patient data, learn how different EHRs work and determine how to use them to coordinate care.

The Public and Population Health training, for its part, focuses on improving population health using advanced analytics, addressing public health problems such as opioid addiction, obesity and diabetes epidemics using health IT and supporting the implementation of ACOs.

According to Regenstrief, fellows who are accepted into the program will learn how to manage and analyze large data sets in healthcare public health organizations; use analytical methods to address population health management; translate basic and clinical research findings for use in population-based settings; creating health IT programs and tools for managing PHI; and using social and behavioral science approaches to solve PHI management problems.

Of course, training eight fellows per year is just a tiny drop in the bucket. Virtually all healthcare institutions need senior physician leaders to have some grasp of healthcare informatics or at least be capable of understanding data issues. Without having top clinical leaders who understand informatics principles, health data projects could end up at a standstill.

In addition, health systems need to train front-line IT staffers to better understand clinical issues — or hire them if necessary. That being said, finding healthcare data specialists is tricky at best, especially if you’re hoping to hire clinicians with this skill set.

Ultimately, it’s likely that health systems will need to train their own internal experts to lead health IT projects, ideally clinicians who have an aptitude for the subject. To do that, perhaps they can use the Regenstrief approach as a model.

Supercharged Wearables Are On The Horizon

Posted on January 3, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Over the last several years, the healthcare industry has been engaged in a rollicking debate over the value of patient-generated health data. Critics say that it’s too soon to decide whether such tools can really add value to medical care, while fans suggest it’s high time to make use of this information.

That’s all fine, but to me, this discussion no longer matters. We are past the question of whether consumer wearables data helps clinicians, which, in their current state, are under-regulated and underpowered. We’re moving on to profoundly more-capable devices that will make the current generation look like toys.

Today, tech giants are working on next-generation devices which will perform more sophisticated tracking and solve more targeted problems. Clinicians, take note of the following news items, which come from The New York Times:

  • Amazon recently invested in Grail, a cancer-detection start-up which raised more than $900 million
  • Apple acquired Beddit, which makes sleep-tracking technology
  • Alphabet acquired Senosis Health, which develops apps that use smartphone sensors to monitor health signals

And the action isn’t limited to acquisitions — tech giants are also getting serious about creating their own products internally. For example, Alphabet’s research unit, Verily Life Sciences, is developing new tools to collect and analyze health data.

Recently, it introduced a health research device, the Verily Study Watch, which has sensors that can collect data on heart rate, gait and skin temperature. That might not be so exciting on its own, but the associated research program is intriguing.

Verily is using the watch to conduct a study called Project Baseline. The study will follow about 10,000 volunteers, who will also be asked to use sleep sensors at night, and also agreed to blood, genetic and mental health tests. Verily will use data analytics and machine learning to gather a more-detailed picture of how cancer progresses.

I could go on, but I’m sure you get the point. We are not looking at your father’s wearables anymore — we’re looking at devices that can change how disease is detected and perhaps even treated dramatically.

Sure, the Fitbits of the world aren’t likely to go away, and some organizations will remain interested in integrating such data into the big data stores. But given what the tech giants are doing, the first generation of plain-vanilla devices will soon end up in the junk heap of medical history.

An Example Of ACO Deals Going Small And Local

Posted on January 2, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Until recently, ACOs have largely focused on creating large, sprawling structures linking giant providers together across multiple states. However, a news item that popped up on my radar screen reminded me that providers are quietly striking smaller local deals with hospitals and insurance companies as well.

In this case, cardiologists in Tupelo have begun to collaborate with Blue Cross & Blue Shield of Mississippi. Specifically, Cardiology Associates of North Mississippi will with Blue plan associate Magellan Health to create Accountable Cardiac Care of Mississippi.

It’s easy to see why the two agreed to the deal. The cardiology group has outpatient clinics across a wide region, including centers in Tupelo, Starkville, Columbus, Oxford and Corinth, along with a hospital practice at North Mississippi Medical Center-Tupelo. That offers a nice range of coverage for the health plan by a much sought-after specialty.

Meanwhile, the cardiology group should get a great deal of help with using data mining to deliver more cost-effective care. Its new partner, Magellan Health, specializes in managing complex conditions using data analytics. “We think we have been practicing this way all along, [but] this will allow us to confirm it,” said Dr. Roger Williams, Cardiology Associates’ president.

Williams told the News Leader that the deal will help his group improve its performance and manage costs. So far it’s been difficult to dig into data which he can use to support these goals. “It’s hard for us as physicians to monitor data,” he told the paper.

The goals of the collaboration with Blue Cross include early diagnosis of conditions and management of patient risk factors. The new payment model the ACO partners are using will offer the cardiology practices bonuses for keeping people healthy and out of expensive ED and hospital settings. Blue Cross and the Accountable Cardiac Care entity will share savings generated by the program.

To address key patient health concerns, Cardiology Associates plans to use both case managers and a Chronic Care program to monitor less stable patients more closely between doctor visits. This tracking program includes protocols which will send out text messages asking questions that detect early warning signs.  The group’s EMR then flags patients who need a case management check-in.

What makes this neat is that the cardiologists won’t be in the dark about how these strategies have worked. Magellan will analyze group data which will measure how effective these interventions have been for the Blue Cross population. Seems like a good idea. I’d suggest that more should follow this ACO’s lead.

AI Making Doctors Better Is the Right Approach

Posted on September 6, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

This summer Bertalan Meskó, MD, PhD posted 10 ways that AI (Artificial Intelligence) could make him a better doctor. Here are his 10 ways:

1) Eradicate waiting time
2) Prioritize my emails
3) Find me the information I need
4) Keep me up-to-date
5) Work when I don’t
6) Help me make hard decisions rational
7) Help patients with urgent matters reach me
8) Help me improve over time
9) Help me collaborate more
10) Do administrative work

This is a great list of ways that AI can make doctors better. No doubt there are even more ways that we’ll discover as AI continues to improve. However, I love this list because it looks at AI from the appropriate point of reference. AI is going to be something that improves the doctor, not replaces the doctor.

I know that many people have talked about how technology is going to replace the doctor. The most famous of which is Vinod Khosla. However, you have to remember that Vinod is an investor and so he needs to drum up companies with ambitious visions. I believe his statement was as much about finding companies that will push the bounds of healthcare as much as it was his prediction for the future of healthcare. However, it no doubt created a lot of fear for doctors.

The reality is that some aspects of what a doctor does will be replaced by technology, but as the list above illustrates, that can be a very good thing for doctors.

AI is coming to healthcare. In some ways, it’s already here. However, the AI that’s coming today isn’t about replacing the doctor, it’s about making the doctor better. Honestly, any doctor that can’t embrace this idea is a doctor that shouldn’t have a medical license.

Should doctors be cautious in how quickly they adopt the technology and should they take the time to make sure that the AI won’t have adverse impacts on their patients? Absolutely. However, there’s a tipping point where not using AI is going to be much more damaging to patients than the risks that are likely to make headlines and scare many. Doctors need to be more driven by what’s best for their patients than fear inducing headlines.

AI will make doctors lives better in a wide variety of ways. It won’t replace the doctor but will enhance the doctor. That’s exciting!

Number Of Healthcare AI Investments Climbing Rapidly

Posted on August 31, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

I’ve written frequently about the growing influence of artificial intelligence tools on healthcare delivery. These include not only support for advanced analytics and adaptive processes but also a growing number of clinically-oriented chatbots.

As far as I knew, these trends were early in their lifecycle, and ventures dipping their toes into healthcare AI were still just dots on a map. Apparently, I was way off on this one.

According to a recent article from CB Insights, healthcare has been, and continues to be, the top industry for AI investment deals. According to the company, there were 29 venture capital investments in healthcare AI last quarter, and from what analysts are saying, that number may rise substantially over the next few quarters. In fact, analysts noted that as of late August, it looked like this quarter’s level of healthcare AI deals would beat the previous quarter’s results.

Just to be clear, CB Insights’ definition of “healthcare AI” covers a lot of ground. The firm defines AI in healthcare as occurring when startups leverage machine learning algorithms to reduce drug discovery times, provide virtual assistance to patients or improve the accuracy of medical imaging and diagnostic procedures – plus some additional unspecified additional applications. (Its list does exclude hardware-focused robotics startups and health-related AR/VR ventures.)

Still, even if you peel away the drug discovery, research and diagnostics investments, there’s plenty of VC deals to track. For example, UK-based Babylon Health raised $60 million in funding the past quarter, the largest funding round tracked by CB Insights. Perhaps this is less surprising given that Babylon Health’s first VC deal included money from Alphabet’s DeepMind Technologies, a nice pedigree for any startup, but it’s still a huge deal. (As you’ll see if you click the link, DeepMind has plenty of healthcare IT development of its own going on.)

Other interesting funding deals included investments in mental health startup Spring Health and risk analytics company OM1, which snagged $15 million in Series A funding. Also, CB Insights found that while most deals involved US companies, four healthcare AI investments went to companies in India and three to companies in China.

Having absorbed this data, I’m eager to see whether my pet interest makes it onto CB Insights’ radar for Q3 of this year. You may already have a general idea about how AI is being deployed in predictive analytics for use in clinical care improvement, or to increase researchers’ ability to pinpoint genes for precision medicine projects, but you may not be aware that another hot application for AI use in healthcare is to provide counseling (and perhaps, in the future, psychiatric services) via chatbot.

I find these services particularly interesting because psychotherapy via AI has some characteristics which differentiate it from many other forms of AI-driven clinical options. One standout is that people may actually tell a chatbot more than they will a live person in some cases, which makes such bots helpful in supporting populations (such as soldiers with PTSD) which might be unlikely to open up otherwise. Let’s see if such applications attract big VC investors anytime soon.

3 CEO Perspectives on Medication Adherence – Part 3 of 3

Posted on August 25, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

KNB Communications recently interviewed three leaders in healthcare technology – Propeller Health Co-founder and CEO David Van Sickle, RxAnte Founder and CEO Dr. Josh Benner, and RxREVU Founder and CEO Carm Huntress – to get their insights on medication adherence.

This is part 3 in a 3 part interview on medication adherence. Be sure to read part 1 and part 2 as well.

Q: How can technology be harnessed to collect patient-reported outcomes such as real-time symptoms and perceptions of medications?

DVS: Propeller sensors passively collect information about use of inhaled medications and transmit that information through a smartphone to Propeller. Then, the system tries to make sense of how the person is doing, to estimate their level of risk and impairment, and to report back its impression and suggestions through digital apps and interfaces.

We ask people to add details about their symptoms, tell us what they perceived to have triggered their episode, and to answer periodic questionnaires that provide other kinds of information, such as whether they are waking up at night. Altogether, this information teaches us a lot about how asthma is affecting that individual in their daily life and how they are responding to treatment.

With this combination of self-reported information and medication use data, Propeller is able to inform physicians about which of their patients need more attention, to help them better understand what might need adjustment to gain control of the symptoms, and to encourage collaborative efforts to improve its care and treatment.

JB: I think this concept has a lot of merit in managing adherence, because if we can get people to communicate with us about how they’re using their medicine and how their medicines are making them feel in real-time, then we can more actively detect and overcome those barriers to nonadherence before they become a decision to stop the medicine.

Phone calls and mobile apps alike can be used to collect information from patients, assess how the medication is working, and tailor the intervention program.  For example, we use our live pharmacist call center to collect patient-reported outcomes and potential reasons why patients may have trouble using their medications as prescribed.  Response rates to digital approaches are typically lower, but they are also less costly.

CH: This is a critical issue because most technologies today, especially electronic health record systems, aren’t really set up to store anything beyond basic patient clinical factors. We need a lot more technology today that can go beyond these basic factors.  We need to think about socioeconomic, patient-reported outcome measures, and other factors to really improve our understanding of medication adherence. How effective a medication is, what outcome it’s really delivering for certain types of patients, and really looking at technologies that are sophisticated decision support systems that capture all this at the point of care, similar to what we’re doing at RxREVU, with our prescription decision support platform, and capturing those key socioeconomic factors.

If we know the patient has a poor adherence, why is that happening and is it a side effect? Is it a socioeconomic factor? What are those patient-reported outcome measures we can capture and store and then longitudinally feed that data across a whole host of patients to better understand how those factors are affecting adherence?

At the patient level, we’re looking at really simple technologies today, Even text messaging is a great solution, especially for many low-income patients that may not have a smartphone, to engage with them and capture that information.

We don’t need sophisticated apps yet. We’re not there at all, in terms of capturing these types of measurements. It’s really about these simple technologies that can engage a patient with a simple question, allow them to answer that through a technology like SMS, and then obviously store that information and make it available to stakeholders to evaluate and better understand adherence issues. Those are definitely some things I think about, as we start to get better at capturing patient-reported outcomes measures that directly affect adherence.

Additional Comments

JB: There’s an exciting tidal wave of interest in the topic of medication adherence across the healthcare system. Fifteen years ago, pharmaceutical companies were the only ones investing heavily in medication adherence. But this has changed dramatically, especially over the past six to seven years.

It’s changed because of new evidence that helped us better understand the consequences of non-adherence as a population health management problem. This stimulated the development of consensus-based quality measures for medication use.

Today, health plans, providers, pharmacies and pharmacy benefit management companies are increasingly being compensated based on the quality of care they deliver—and that is an incentive to improve adherence to critical medications. RxAnte’s products and services are used by all of these stakeholders—and in the years ahead, we want to facilitate unprecedented collaboration among these parties to help patients get more from medicines.

CH: In terms of adherence, we at RxREVU really take a different point of view. Many companies are focused clearly on the patient’s experience and around adherence and how they improve that. But ultimately, all these decisions start at the point of care. We are solely focused on helping the provider at the point of care make the most informed decision that’s going to drive an appropriate prescription to the patient, that they can afford, and they can adhere to.

As we look to the future, I think this is a critical piece that we need more and more technologies at the point of care supporting clinician’s decisions, because ultimately, you as the patient aren’t making the decision; your provider is. That’s sometimes missed, and providers are a key component to the decision-making. It is really is a shared decision-making and technologies that can sit alongside those patients and providers in the exam room and support those decisions are really going to be critical in the coming years.

This was part 3 in a 3 part interview on medication adherence. Be sure to read part 1 and part 2 to read the full interview.

About David Van Sickle

David Van Sickle is co-founder and CEO of Propeller Health – the leader in respiratory digital health. David received his PhD in medical anthropology. His dissertation research, funded by the National Science Foundation, examined the rising prevalence of asthma and allergy in India. He was then an Epidemic Intelligence Service officer at the Centers for Disease Control and Prevention in Atlanta, where he was assigned to the Air Pollution and Respiratory Health Branch. During this time, he provided epidemiological support to the National Asthma Control Program, and investigated the health effects of a variety of environmental exposures. In addition, he helped establish emergency illness and injury surveillance in coastal Mississippi after Hurricane Katrina. David was also named a Champion of Change by the White House for his work on innovation.

About Josh Benner

A leading voice on medication adherence, Dr. Benner’s award-winning research and numerous publications have shed new light on the problem of nonadherence and identified promising approaches to improving it.  He is the founder and CEO of RxAnte, the leading provider of predictive analytics and targeted clinical programs for improving medication use.

Before joining RxAnte, Dr. Benner was Fellow and Managing Director at the Brookings Institution’s Center for Health Care Reform, where he focused on medical technology policy.

Prior to Brookings, Dr. Benner was principal at ValueMedics Research, an analytic and consulting services firm. Following the acquisition of ValueMedics by IMS Health in 2007, he served as senior principal in health economics and outcomes research and global lead for medication adherence at IMS. Dr. Benner received his Doctor of Pharmacy degree from Drake University and his Doctor of Science in health policy and management from the Harvard University School of Public Health.

About Carm Huntress

Carm Huntress is an entrepreneur and strategic leader with over 20 years of experience in startups focused around consumer and enterprise technology. His first web development and hosting company he started while in high school was eventually acquired in 2001.  After finishing his degree in electrical engineering at Northeastern University in 2004, he went on to work for PlumVoice, an IVR and voice technology startup, where he ran their network operations.  He later was asked to run product development at My Perfect Gig, a Northbridge and Commonwealth Venture start-up.

After two years as CTO at Reef Partners, where he ran the technology for a number of portfolio companies, he became CTO at Audiogon.com, the largest high end audio site in the world.  He managed the transition of the core technology platform and team for growth.  In 2013 he moved to Denver where he founded RxREVU.

3 CEO Perspectives on Medication Adherence – Part 2 of 3

Posted on August 24, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

KNB Communications recently interviewed three leaders in healthcare technology – Propeller Health Co-founder and CEO David Van Sickle, RxAnte Founder and CEO Dr. Josh Benner, and RxREVU Founder and CEO Carm Huntress – to get their insights on medication adherence.

This is part 2 in a 3 part interview on medication adherence. Be sure to read part 1 and part 3 as well.

Q: A recent study by the Journal of the American Board of Family Medicine underscores the emotional and behavioral barriers faced by patients with chronic illnesses. How do we leverage technology to reduce the impact of social and economic factors such as poverty, transportation challenges, and medication costs?

DVS: We know that, in some cases, people avoid taking their daily medicines for asthma because they’re costly and they can’t afford the required co-pay or co-insurance amounts. But without those medications, people are more likely to develop symptoms, and may have to spend quite a lot of their discretionary income dealing with the costs of uncontrolled asthma, whether it’s because they’re forced to miss a day of work or school, or because they need to seek medical attention. The faster we’re able to help bring someone’s disease under control, the sooner they can avoid unnecessary costs and suffering.

We know that a lot of things in the environment, such as workplace exposures or air pollution in the community, can have a material effect on a person with chronic respiratory disease. By learning about the locations where people have symptoms, Propeller aims to help them avoid or mitigate those exposures.

For the past few years, Propeller has been part of program in Louisville to help residents better manage their asthma and to collect information about where, when and among whom asthma is happening across the metro. Aggregate data from thousands of participants has highlighted how socioeconomic context contributes to poor respiratory health. At the same time, by making these patterns visible, we’ve also opened new opportunities for municipal discussion, policy decisions, and applied public health interventions to try to address these risk factors, and to increase the respiratory health of the entire community.

JB: These are really important barriers. The cost of medications is going up. That makes them unaffordable for some patients, and those are often the patients that are also most vulnerable to the consequences of non-adherence—like low-income and older Americans for whom these medications are really important to them staying out of the hospital, keeping a job, or otherwise living independently. So, we are increasingly doing work in the Medicare, Medicaid and dual-eligible populations. We use advanced predictive analytics to identify members of those populations who are at risk, which means we predict whether they’ll be able to be adherent to the medications that have been prescribed for them.

More than that, we also predict the consequences of their expected adherence. For example, we’ll predict what their non-adherence is likely to cost over the next year or two. That score enables us to prioritize members of those populations tailor programs to the patients who are most likely to benefit.  Another technology we developed, RxEffect, allows us to deliver this information in prioritized workflows to physician offices or care managers, so they always know in real time which of their patients need their attention and what problems to focus on.

Different interventions can solve for different barriers. We use telephone outreach with interactive voice response, because that’s an effective way to facilitate a refill for a patient. On the more intensive end of the spectrum, we use live pharmacist care managers to make sure that they understand the importance and the benefits of remaining adherent and to troubleshoot drug therapy problems that the patient might report.  If they say, “I’m having a side effect with this med,” or, “I can’t afford this med,” the pharmacist is able to go back to the patient’s prescriber, get it changed to something that the patient might find more tolerable or more affordable, and call the patient back to offer to help get that prescription filled.

A third approach is to use so-called “digital therapeutics” or a combination of digital devices and communication tools to maintain long-term engagement with the patient. These services can be delivered through mobile phones like secure text messaging and secure chat to create an ongoing dialogue with the individual.  That provides a conduit to deliver things like a video on how to use your asthma inhaler correctly, so that you and your asthmatic child can use that medicine correctly and stay out of the hospital. Or to deliver a co-pay assistance coupon or some other patient assistance tool provided by the manufacturer to overcome the cost barriers for that particular patient. This is potentially cost-effective and scalable because of the growing mobile and smartphone adoption among these populations.

CH: First and foremost, socioeconomic factors need to be brought into the equation in terms of determining what medication is right for a patient, which will ultimately lead to their adherence. Things we specifically look at are concepts around, for instance, pharmacy deserts, and the challenge for patients, because of public transportation combined with the location of specific pharmacies can lead many patients, especially low-income ones, into situations where they don’t have access to a supermarket or pharmacy within a reasonable distance, that has a pharmacy where they can get their medication.

Another issue is cost and understanding of patients’ income and what they’re ultimately going to be able to afford. Patients won’t take medications or won’t be adherent to medications they can’t afford, period. There’s really no way around that and I think that’s something that is directly tied to socioeconomic factors.

Technologies that can bring those concepts forward and identify those socioeconomic factors up-front and address them in both the exam room as well as the patient’s in a process of getting their medication filled or refilled are going to be critical, because there are a lot of programs that can support patients’ costs. Obviously identify these patients and help support them. There’s a lot of data out there that’s just not being collected and brought together cohesively and made easily accessible to patients to find and access this type of information. I think those are some critical things that really relate to the socioeconomic pieces of adherence.

This was part 2 in a 3 part interview on medication adherence. Be sure to read part 1 and part 3 to read the full interview.

About David Van Sickle

David Van Sickle is co-founder and CEO of Propeller Health – the leader in respiratory digital health. David received his PhD in medical anthropology. His dissertation research, funded by the National Science Foundation, examined the rising prevalence of asthma and allergy in India. He was then an Epidemic Intelligence Service officer at the Centers for Disease Control and Prevention in Atlanta, where he was assigned to the Air Pollution and Respiratory Health Branch. During this time, he provided epidemiological support to the National Asthma Control Program, and investigated the health effects of a variety of environmental exposures. In addition, he helped establish emergency illness and injury surveillance in coastal Mississippi after Hurricane Katrina. David was also named a Champion of Change by the White House for his work on innovation.

About Josh Benner

A leading voice on medication adherence, Dr. Benner’s award-winning research and numerous publications have shed new light on the problem of nonadherence and identified promising approaches to improving it.  He is the founder and CEO of RxAnte, the leading provider of predictive analytics and targeted clinical programs for improving medication use.

Before joining RxAnte, Dr. Benner was Fellow and Managing Director at the Brookings Institution’s Center for Health Care Reform, where he focused on medical technology policy.

Prior to Brookings, Dr. Benner was principal at ValueMedics Research, an analytic and consulting services firm. Following the acquisition of ValueMedics by IMS Health in 2007, he served as senior principal in health economics and outcomes research and global lead for medication adherence at IMS. Dr. Benner received his Doctor of Pharmacy degree from Drake University and his Doctor of Science in health policy and management from the Harvard University School of Public Health.

About Carm Huntress

Carm Huntress is an entrepreneur and strategic leader with over 20 years of experience in startups focused around consumer and enterprise technology. His first web development and hosting company he started while in high school was eventually acquired in 2001.  After finishing his degree in electrical engineering at Northeastern University in 2004, he went on to work for PlumVoice, an IVR and voice technology startup, where he ran their network operations.  He later was asked to run product development at My Perfect Gig, a Northbridge and Commonwealth Venture start-up.

After two years as CTO at Reef Partners, where he ran the technology for a number of portfolio companies, he became CTO at Audiogon.com, the largest high end audio site in the world.  He managed the transition of the core technology platform and team for growth.  In 2013 he moved to Denver where he founded RxREVU.