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As Patient Engagement Advances, It Raises Questions About Usefulness

Posted on September 26, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Reading ONC’s recent summary of patient engagement capabilities at US hospitals left me feeling both hopeful and wistful. The ONC, as usual, is trying to show off how much progress the field of health IT has made since Meaningful Use started, and the statistics in this dashboard meet those goals. On the other hand, I look at the statistics and wonder when real patient empowerment will emerge from these isolated gains.

The ONC dashboard includes information both on raw data exchange–what Meaningful Use called view, download, and transmit (VDT)–and the uses of that data, which ultimately mean much more than exchange.

I considered at first how important I would find it to download hospital information. I certainly would like my doctors to get the results of tests performed there, and other information related to my status upon discharge, but these supposedly are sent to the primary care physician in a Continuity of Care Document (CCD). If I or a close relative of mine had a difficult or chronic condition, I would certainly benefit from VDT because I would have to be an active advocate and would need the documentation. My point here is that our real goal in health reform is coordinated care, rather than data transfer, and while VDT is an important first step, we must always ask who is using that information.

The ONC did not ask the hospitals how much of their data patients can download. God is in the details, and I am not confident that an affirmative answer to the question of downloading data means patients can get everything that is in their records. For instance, my primary care physician has a patient portal running on eClinicalWorks (not his choice, but the choice of the hospital to which he is affiliated). From this portal I can get only a few pieces of information, such as medications (which I happen to know already, since I am taking them) and lab results. Furthermore, I downloaded the CCD and ran it through a checker provided online by the ONC for a lark, and found that it earned D grades for accurate format. This dismal rating suggests that I couldn’t successfully upload the CCD to another doctor’s EHR.

Still, I don’t want to dismiss the successes in the report. VDT is officially enabled in 7 out of 10 hospitals, a 7-fold growth between 2013 and 2015. Although the dashboard laments that “Critical Access, medium, and small hospitals lag,” the lag is not all that bad. And the dashboard also shows advances in the crucial uses of that data, such as submitting amendments to the data

A critical question in evaluating patient engagement is how the Congress and ONC define it. A summary of the new MACRA law lists several aspects of patient engagement measured under the new system:

  • Viewing, downloading, and transmitting, as defined before. As with the later Meaningful Use requirements, MACRO requires EHRs to offer an API, so that downloading can be done automatically.

  • Secure messaging. Many advances in treating chronic conditions depend on regular communications with patients, and messaging is currently the simplest means toward that goal. Some examples of these advances can be found in my article about a health app challenge. Conventional text messaging is all in plain text, and health care messaging must be secure to meet HIPAA requirements.

  • Educational materials. I discount the impact of static educational materials offered to patients with chronic conditions, whether in the form print brochures or online. But educational materials are part of a coordinated care plan.

  • Incorporating patient-generated data. The MACRA requirements “ask providers to incorporate data contributed by the patient from at least one unique patient.” Lucky little bugger. How will he or she leverage this unprecedented advantage?

That last question is really the nub of the patient engagement issue. In Meaningful Use and MACRA, regulators often require a single instance of some important capability, because they know that once the health care provider has gone through the trouble of setting up that capability, extending it to all patients is less difficult. And it’s heartening to see that 37 percent of hospitals allowed patients to submit patient-generated data in 2015.

Before you accept data from a patient, you need extra infrastructure to make the data useful. For instance:

  • You can check for warning signals that call for intervention, such as an elevated glucose level. This capability suggests a background program running through all the data that comes in and flagging such warning signals.

  • You can evaluate device data to see progress or backsliding in the patient’s treatment program. This requires analytics that understand the meaning of the data (and that can handle noise) so as to produce useful reports.

  • You can create a population health program that incorporates the patient-generated data into activities such as monitoring epidemics. This is also a big analytical capability.

Yes, I’m happy we’ve made progress in using data for patient engagement. A lot of other infrastructure also needs to be created so we can benefit from the big investment these advances required.

What Data Do You Need in Order to Guide Behavioral Change?

Posted on June 2, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

This is an exciting time for the health care field, as its aspirations toward value-based payments and behavioral responses to chronic conditions converge on a more and more precise solution. Dr. Joseph Kvedar has called this comprehensive approach connected health and has formed both a conference and a book around it. BaseHealth, a predictive analytics company in healthcare, has teamed up with TriVita to offer a consumer-based service around this approach, which combines access to peer-reviewed research with fine-tuned guidance that taps into personal health and behavioral data and leverages the individual interests of each participant.

I have previously written about BaseHealth’s assessment engine, which asks individuals for information about their activities, family history, and health conditions in order to evaluate their health profile and risk for common diseases. TriVita is a health coaching service with a wide-ranging assessment tool and a number of products, including cutely named supplements such as Joint Complex and Daily Cleanse. TriVita’s nutritionists, exercise coaches, and other staff are overseen by physicians, but their service is not medical: it does not enter the heavily regulated areas where clinicians practice.

I recently talked with BaseHealth’s CEO, Prakash Menon, and Dan Hoemke, its Vice President of Business Development. They describe BaseHealth’s predictive analytics as input that informs TriVita’s coaching service. What I found interesting is the sets of data that seem most useful for coaching and behavioral interventions.

In my earlier article, I wrote, “BaseHealth has trouble integrating EHR data.” Menon tells me that getting this data has become much easier over the past several months, because several companies have entered the market to gather and combine the data from different vendors. Still, BaseHealth focuses on a few sources of medical data, such as lab and biometric data. Overall, they focus on gathering data required to identify disease risk and guide behavior change, which in turn improves preventable conditions such as heart disease and diabetes.

Part of their choice springs from the philosophy driving BaseHealth’s model. Menon says, “BaseHealth wants to work with you before you have a chronic condition.” For instance, the American Diabetes Association estimated in 2012 that 86 million Americans over the age of 20 had prediabetes. Intervening before these people have developed the full condition is when behavioral change is easiest and most effective.

Certainly, BaseHealth wants to know your existing medical conditions. So they ask you about them when you sign up. Other vital signs, such as cholesterol, are also vital to BaseHealth’s analytics. Through a partnership with LabCo, a large diagnostics company in Europe, they are able to tap into lab systems to get these vital signs automatically. But users in the United States can enter them manually with little effort.

BaseHealth is not immune to the industry’s love affair with genetics and personalization, either. They take about 1500 genetic factors into account, helping them to quantify your risk of getting certain chronic conditions. But as a behavioral health service, Menon points out, BaseHealth is not designed to do much with genetic traits signifying a high chance of getting a disease. They deal with problems that you can do something about–preventable conditions. Menon cites a Health 2.0 presentation (see Figure 1) saying that our health can, on average, be attributed 60 percent to lifestyle, 30 percent to genetics, and 10 percent to clinical interventions. But genetics help to show what is achievable. Hoemke says BaseHealth likes to compare each person against the best she can be, whereas many sites just compare a user against the average population with similar health conditions.

Relative importance of health factors

Figure 1. Relative importance of health factors

BaseHealth gets most of its data from conditions known to you, your environment, family history, and more than 75 behavioral factors: your activity, food, over-the-counter meds, sleep activity, alcohol use, smoking, several measures of stress, etc. BaseHealth assessment recommendations and other insights are based on peer-reviewed research. BaseHealth will even point the individual to particular studies to provide the “why” for its recommendations.

So where does TriVita fit in? Hoemke says that BaseHealth has always stressed the importance of human intervention, refusing to fall into the fallacy that health can be achieved just through new technology. He also said that TriVita fits into the current trend of shifting accountability for health to the patient; he calls it a “health empowerment ecosystem.” As an example of the combined power of BaseHealth and TriVita, a patient can send his weight regularly to a coach, and both can view the implications of the changes in weight–such as changes in risk factors for various diseases–on charts. Some users make heavy use of the coaches, whereas others take the information and recommendations and feel they can follow their plan on their own.

As more and more companies enter connected health, we’ll get more data about what works. And even though BaseHealth and TriVita are confident they can achieve meaningful results with mostly patient-generated data, I believe that clinicians will use similar techniques to treat sicker people as well.