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Alexa Can Truly Give Patients a Voice in Their Health Care (Part 3 of 3)

Posted on October 20, 2017 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.

Earlier parts of this article set the stage for understanding what the Alexa Diabetes Challenge is trying to achieve and how some finalists interpreted the mandate. We examine three more finalists in this final section.

DiaBetty from the University of Illinois-Chicago

DiaBetty focuses on a single, important aspect of diabetes: the effect of depression on the course of the disease. This project, developed by the Department of Psychiatry at the University of Illinois-Chicago, does many of the things that other finalists in this article do–accepting data from EHRs, dialoguing with the individual, presenting educational materials on nutrition and medication, etc.–but with the emphasis on inquiring about mood and handling the impact that depression-like symptoms can have on behavior that affects Type 2 diabetes.

Olu Ajilore, Associate Professor and co-director of the CoNECt lab, told me that his department benefited greatly from close collaboration with bioengineering and computer science colleagues who, before DiaBetty, worked on another project that linked computing with clinical needs. Although they used some built-in capabilities of the Alexa, they may move to Lex or another AI platform and build a stand-alone device. Their next step is to develop reliable clinical trials, checking the effect of DiaBetty on health outcomes such as medication compliance, visits, and blood sugar levels, as well as cost reductions.

T2D2 from Columbia University

Just as DiaBetty explores the impact of mood on diabetes, T2D2 (which stands for “Taming Type 2 Diabetes, Together”) focuses on nutrition. Far more than sugar intake is involved in the health of people with diabetes. Elliot Mitchell, a PhD student who led the T2D2 team under Assistant Professor Lena Mamykina in the Department of Biomedical Informatics, told me that the balance of macronutrients (carbohydrates, fat, and protein) is important.

T2D2 is currently a prototype, developed as a combination of Alexa Skill and a chatbot based on Lex. The Alexa Skills Kit handle voice interactions. Both the Skill and the chatbot communicate with a back end that handles accounts and logic. Although related Columbia University technology in diabetes self-management is used, both the NLP and the voice interface were developed specifically for the Alexa Diabetes Challenge. The T2D2 team included people from the disciplines of computer interaction, data science, nursing, and behavioral nutrition.

The user invokes Alexa to tell it blood sugar values and the contents of meals. T2D2, in response, offers recipe recommendations and other advice. Like many of the finalists in this article, it looks back at meals over time, sees how combinations of nutrients matched changes in blood sugar, and personalizes its food recommendations.

For each patient, before it gets to know that patient’s diet, T2D2 can make food recommendations based on what is popular in their ZIP code. It can change these as it watches the patient’s choices and records comments to recommendations (for instance, “I don’t like that food”).

Data is also anonymized and aggregated for both recommendations and future research.

The care team and family caregivers are also involved, although less intensely than some other finalists do. The patient can offer caregivers a one-page report listing a plot of blood sugar by time and day for the previous two weeks, along with goals and progress made, and questions. The patient can also connect her account and share key medical information with family and friends, a feature called the Supportive Network.

The team’s next phase is run studies to evaluable some of assumptions they made when developing T2D2, and improve it for eventual release into the field.

Sugarpod from Wellpepper

I’ll finish this article with the winner of the challenge, already covered by an earlier article. Since the publication of the article, according to the founder and CEO of Wellpepper, Anne Weiler, the company has integrated some of Sugarpod functions into a bathroom scale. When a person stands on the scale, it takes an image of their feet and uploads it to sites that both the individual and their doctor can view. A machine learning image classifier can check the photo for problems such as diabetic foot ulcers. The scale interface can also ask the patient for quick information such as whether they took their medication and what their blood sugar is. Extended conversations are avoided, under the assumption that people don’t want to have them in the bathroom. The company designed its experiences to be integrated throughout the person’s day: stepping on the scale and answering a few questions in the morning, interacting with the care plan on a mobile device at work, and checking notifications and messages with an Echo device in the evening.

Any machine that takes pictures can arouse worry when installed in a bathroom. While taking the challenge and talking to people with diabetes, Wellpepper learned to add a light that goes on when the camera is taking a picture.

This kind of responsiveness to patient representatives in the field will determine the success of each of the finalists in this challenge. They all strive for behavioral change through connected health, and this strategy is completely reliant on engagement, trust, and collaboration by the person with a chronic illness.

The potential of engagement through voice is just beginning to be tapped. There is evidence, for instance, that serious illnesses can be diagnosed by analyzing voice patterns. As we come up on the annual Connected Health Conference this month, I will be interested to see how many participating developers share the common themes that turned up during the Alexa Diabetes Challenge.

Alexa Can Truly Give Patients a Voice in Their Health Care (Part 2 of 3)

Posted on October 19, 2017 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.

The first part of this article introduced the problems of computer interfaces in health care and mentioned some current uses for natural language processing (NLP) for apps aimed at clinicians. I also summarized the common goals, problems, and solutions I found among the five finalists in the Alexa Diabetes Challenge. This part of the article shows the particular twist given by each finalist.

My GluCoach from HCL America in Partnership With Ayogo

There are two levels from which to view My GluCoach. On one level, it’s an interactive tool exemplifying one of the goals I listed earlier–intense engagement with patients over daily behavior–as well as the theme of comprehensivenesss. The interactions that My GluCoach offers were divided into three types by Abhishek Shankar, a Vice President at HCL Technologies America:

  • Teacher: the service can answer questions about diabetes and pull up stored educational materials

  • Coach: the service can track behavior by interacting with devices and prompt the patient to eat differently or go out for exercise. In addition to asking questions, a patient can set up Alexa to deliver alarms at particular times, a feature My GluCoach uses to deliver advice.

  • Assistant: provide conveniences to the patient, such as ordering a cab to take her to an appointment.

On a higher level, My GluCoach fits into broader services offered to health care institutions by HCL Technologies as part of a population health program. In creating the service HCL partnered with Ayogo, which develops a mobile platform for patient engagement and tracking. HCL has also designed the service as a general health care platform that can be expanded over the next six to twelve months to cover medical conditions besides diabetes.

Another theme I discussed earlier, interactions with outside data and the use of machine learning, are key to my GluCoach. For its demo at the challenge, My GluCoach took data about exercise from a Fitbit. It can potentially work with any device that shares information, and HCL plans to integrate the service with common EHRs. As My GluCoach gets to know the individual who uses it over months and years, it can tailor its responses more and more intelligently to the learning style and personality of the patient.

Patterns of eating, medical compliance, and other data are not the only input to machine learning. Shankar pointed out that different patients require different types of interventions. Some simply want to be given concrete advice and told what to do. Others want to be presented with information and then make their own decisions. My GluCoach will hopefully adapt to whatever style works best for the particular individual. This affective response–together with a general tone of humor and friendliness–will win the trust of the individual.

PIA from Ejenta

PIA, which stands for “personal intelligent agent,” manages care plans, delivering information to the affected patients as well as their care teams and concerned relatives. It collects medical data and draws conclusions that allow it to generate alerts if something seems wrong. Patients can also ask PIA how they are doing, and the agent will respond with personalized feedback and advice based on what the agent has learned about them and their care plan.

I talked to Rachna Dhamija, who worked on a team that developed PIA as the founder and CEO of Ejenta. (The name Ejenta is a version of the word “agent” that entered the Bengali language as slang.) She said that the AI technology had been licensed from NASA, which had developed it to monitor astronauts’ health and other aspects of flights. Ejenta helped turn it into a care coordination tool with interfaces for the web and mobile devices at a major HMO to treat patients with chronic heart failure and high-risk pregnancies. Ejenta expanded their platform to include an Alexa interface for the diabetes challenge.

As a care management tool, PIA records targets such as glucose levels, goals, medication plans, nutrition plans, and action parameters such as how often to take measurements using the devices. Each caregiver, along the patient, has his or her own agent, and caregivers can monitor multiple patients. The patient has very granular control over sharing, telling PIA which kind of data can be sent to each caretaker. Access rights must be set on the web or a mobile device, because allowing Alexa to be used for that purpose might let someone trick the system into thinking he was the patient.

Besides Alexa, PIA takes data from devices (scales, blood glucose monitors, blood pressure monitors, etc.) and from EHRs in a HIPAA-compliant method. Because the service cannot wake up Alexa, it currently delivers notifications, alerts, and reminders by sending a secure message to the provider’s agent. The provider can then contact the patient by email or mobile phone. The team plans to integrate PIA with an Alexa notifications feature in the future, so that PIA can proactively communicate with the patient via Alexa.

PIA goes beyond the standard rules for alerts, allowing alerts and reminders to be customized based on what it learns about the patient. PIA uses machine learning to discover what is normal activity (such as weight fluctuations) for each patient and to make predictions based on the data, which can be shared with the care team.

The final section of this article covers DiaBetty, T2D2, and Sugarpod, the remaining finalists.

Alexa Can Truly Give Patients a Voice in Their Health Care (Part 1 of 3)

Posted on October 16, 2017 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.

The leading pharmaceutical and medical company Merck, together with Amazon Web Services, has recently been exploring the potential health impacts of voice interfaces and natural language processing (NLP) through an Alexa Diabetes Challenge. I recently talked to the five finalists in this challenge. This article explores the potential of new interfaces to transform the handling of chronic disease, and what the challenge reveals about currently available technology.

Alexa, of course, is the ground-breaking system that brings everyday voice interaction with computers into the home. Most of its uses are trivial (you can ask about today’s weather or change channels on your TV), but one must not underestimate the immense power of combining artificial intelligence with speech, one of the most basic and essential human activities. The potential of this interface for disabled or disoriented people is particularly intriguing.

The diabetes challenge is a nice focal point for exploring the more serious contribution made by voice interfaces and NLP. Because of the alarming global spread of this illness, the challenge also presents immediate opportunities that I hope the participants succeed in productizing and releasing into the field. Using the challenge’s published criteria, the judges today announced Sugarpod from Wellpepper as the winner.

This article will list some common themes among the five finalists, look at the background about current EHR interfaces and NLP, and say a bit about the unique achievement of each finalist.

Common themes

Overlapping visions of goals, problems, and solutions appeared among the finalists I interviewed for the diabetes challenge:

  • A voice interface allows more frequent and easier interactions with at-risk individuals who have chronic conditions, potentially achieving the behavioral health goal of helping a person make the right health decisions on a daily or even hourly basis.

  • Contestants seek to integrate many levels of patient intervention into their tools: responding to questions, collecting vital signs and behavioral data, issuing alerts, providing recommendations, delivering educational background material, and so on.

  • Services in this challenge go far beyond interactions between Alexa and the individual. The systems commonly anonymize and aggregate data in order to perform analytics that they hope will improve the service and provide valuable public health information to health care providers. They also facilitate communication of crucial health data between the individual and her care team.

  • Given the use of data and AI, customization is a big part of the tools. They are expected to determine the unique characteristics of each patient’s disease and behavior, and adapt their advice to the individual.

  • In addition to Alexa’s built-in language recognition capabilities, Amazon provides the Lex service for sophisticated text processing. Some contestants used Lex, while others drew on other research they had done building their own natural language processing engines.

  • Alexa never initiates a dialog, merely responding when the user wakes it up. The device can present a visual or audio notification when new material is present, but it still depends on the user to request the content. Thus, contestants are using other channels to deliver reminders and alerts such as messaging on the individual’s cell phone or alerting a provider.

  • Alexa is not HIPAA-compliant, but may achieve compliance in the future. This would help health services turn their voice interfaces into viable products and enter the mainstream.

Some background on interfaces and NLP

The poor state of current computing interfaces in the medical field is no secret–in fact, it is one of the loudest and most insistent complaints by doctors, such as on sites like KevinMD. You can visit Healthcare IT News or JAMA regularly and read the damning indictments.

Several factors can be blamed for this situation, including unsophisticated electronic health records (EHRs) and arbitrary reporting requirements by Centers for Medicare & Medicaid Services (CMS). Natural language processing may provide one of the technical solutions to these problems. The NLP services by Nuance are already famous. An encouraging study finds substantial time savings through using NLP to enter doctor’s insights. And on the other end–where doctors are searching the notes they previously entered for information–a service called Butter.ai uses NLP for intelligent searches. Unsurprisingly, the American Health Information Management Association (AHIMA) looks forward to the contributions of NLP.

Some app developers are now exploring voice interfaces and NLP on the patient side. I covered two such companies, including the one that ultimately won the Alexa Diabetes Challenge, in another article. In general, developers using these interfaces hope to eliminate the fuss and abstraction in health apps that frustrate many consumers, thereby reaching new populations and interacting with them more frequently, with deeper relationships.

The next two parts of this article turn to each of the five finalists, to show the use they are making of Alexa.

HL7 Releases New FHIR Update

Posted on April 3, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

HL7 has announced the release of a new version of FHIR designed to link it with real-world concepts and players in healthcare, marking the third of five planned updates. It’s also issuing the first release of the US Core Implementation Guide.

FHIR release 3 was produced with the cooperation of hundreds of contributors, and the final product incorporates the input of more than 2,400 suggested changes, according to project director Grahame Grieve. The release is known as STU3 (Standard for Trial Use, release 3).

Key changes to the standard include additional support for clinical quality measures and clinical decision support, as well as broader functionality to cover key clinical workflows.

In addition, the new FHIR version includes incremental improvements and increased maturity of the RESTful API, further development of terminology services and new support for financial management. It also defined an RDF format, as well as how FHIR relates to linked data.

HL7 is already gearing up for the release of FHIR’s next version. It plans to publish the first draft of version 4 for comment in December 2017 and review comments on the draft. It will then have a ballot on the version, in April 2018, and publish the new standard by October 2018.

Among those contributing to the development of FHIR is the Argonaut project, which brings together major US EHR vendors to drive industry adoption of FHIR forward. Grieve calls the project a “particularly important” part of the FHIR community, though it’s hard to tell how far along its vendor members have come with the standard so far.

To date, few EHR vendors have offered concrete support for FHIR, but that’s changing gradually. For example, in early 2016 Cerner released an online sandbox for developers designed to help them interact with its platform. And earlier this month, Epic announced the launch of a new program, helping physician practices to build customized apps using FHIR.

In addition to the vendors, which include athenahealth, Cerner, Epic, MEDITECH and McKesson, several large providers are participating. Beth Israel Deaconess Medical Center, Intermountain Healthcare, the Mayo Clinic and Partners HealthCare System are on board, as well as the SMART team at the Boston Children’s Hospital Informatics Program.

Meanwhile, the progress of developing and improving FHIR will continue.  For release 4 of FHIR, the participants will focus on record-keeping and data exchange for the healthcare process. This will encompass clinical data such as allergies, problems and care plans; diagnostic data such observations, reports and imaging studies; medication functions such as order, dispense and administration; workflow features like task, appointment schedule and referral; and financial data such as claims, accounts and coverage.

Eventually, when release 5 of FHIR becomes available, developers should be able to help clinicians reason about the healthcare process, the organization says.

E-Patient Update: Patients Need Better Care Management Workflows

Posted on March 10, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Now and then, I get a little discouraged by the state of my health data. Like providers, I’m frustrated as heck by the number of independent data sources I must access to get a full picture of my medications, care and health status. These include:

* The medication tracker on my retail pharmacy’s site
* My primary care group’s portal
* My hospital’s Epic MyChart portal
* A medication management app to track my compliance with my regimen
* A health tracker app in which I track my blood pressure
* My Google calendar, to keep up with my health appointments
* Email clients to exchange messages with some providers

That’s not all – I’m sure I could think of other tools, interfaces and apps – but it offers a good idea of what I face. And I’m pretty sure I’m not unusual in this regard, so we’re talking about a big issue here.

By the way, bear in mind I’m not just talking about hyperportalotus – a fun term for the state of having too many portals to manage – but rather, a larger problem of data coordination. Even if all of my providers came together and worked through a shared single portal, I’d still have to juggle many tools for tracking and documenting my care.

The bottom line is that given the obstacles I face, my self-care process is very inefficient. And while we spend a lot of time talking about clinician workflow (which, of course, is quite important) we seldom talk about patient/consumer health workflow. But it’s time that we did.

Building a patient workflow

A good initial step in addressing this problem might be to create a patient self-care workflow builder and make it accessible website. Using such a tool, I could list all of the steps I need to take to manage my conditions, and the tool would help me develop a process for doing so effectively.

For example, I could “tell” the software that I need to check the status of my prescriptions once a week, visit certain doctors once a month, check in about future clinical visits on specific days and enter my data in my medication management app twice a day. As I did this, I would enter links to related sites, which would display in turn as needed.

This tool could also display critical web data, such as the site compiling the blood sugar readings from my husband’s connected blood glucose monitor, giving patients like me the ability to review trends at a glance.

I haven’t invented the wheel here, of course. We’re just talking about an alternate approach to a patient portal. Still, even this relatively crude approach – displaying various web-based sources under one “roof” along with an integrated process – could be quite helpful.

Eventually, health IT wizards could build much more sophisticated tools, complete with APIs to major data sources, which would integrate pretty much everything patients need first-hand. This next-gen data wrangler would be able to create charts and graphs and even issue recommendations if the engine behind it was sophisticated enough.

Just get started

All that being said, I may be overstating how easy it would be to make such a solution work. In particular, I’m aware that integrating a tool with such disparate data sources is far, far easier said than done. But why not get started?

After all, it’s hard to overestimate how much such an approach would help patients, at least those who are comfortable working with digital health solutions. Having a coordinated, integrated tool in place to help me manage my care needs would certainly save me a great deal of time, and probably improve my health as well.

I urge providers to consider this approach, which seems like a crying need to me. The truth is, most of the development money is going towards enabling the professionals to coordinate and manage care. And while that’s not a bad thing, don’t forget us!

A New Meaning for Connected Health at 2016 Symposium (Part 4 of 4)

Posted on November 8, 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.

The previous section of this article continued our exploration of the integration of health care into daily life. This section wraps up the article with related insights, including some thoughts about the future.

Memorable moments
I had the chance to meet with Casper de Clercq, who has set up a venture capital plan devoted to health as a General Partner at Norwest Venture Partners. He recommends that manufacturers and clinicians give patients a device that collects data while doing something else they find useful, so that they are motivated to keep wearing it. As an example, he cited the Beddit sleep tracker, which works through sensors embedded (no pun intended) in the user’s bed.

He has found that successful companies pursue gradual, incremental steps toward automated programs. It is important to start with a manual process that works (such as phoning or texting patients from the provider), then move to semi-automation and finally, if feasible, full automation. The product must also be field-tested; one cannot depend on a pilot. This advice matches what Glen Tullman, CEO of Livongo Health, said in his keynote: instead of doing a pilot, try something out in the field and change quickly if it doesn’t work.

Despite his call for gradual change, de Clercq advises that companies show an ROI within one year–otherwise, the field of health care may have evolved and the solution may be irrelevant.

He also recommends a human component in any health program. The chief barrier to success is getting the individual to go along with both the initial activation and continuing motivation. Gamification, behavioral economics, and social connections can all enhance this participation.

A dazzling keynote on videogames for health was delivered by Adam Gazzaley, who runs Neuroscience labs at the University of California at San Francisco. He pointed out that conventional treatments get feedback on patient reactions far too slowly–sometimes months after the reaction has occurred. In the field of mental health, His goal is to supplement (not replace) medications with videogames, and to provide instant feedback to game players and their treatment staff alike. Videogames not only provide a closed-loop system (meaning that feedback is instantaneous), but also engage patients by being fun and offering real-time rewards. Attention spans, anxiety, and memory are among the issues he expects games to improve. Education and wellness are also on his game plan. This is certainly one talk where I did not multitask (which is correlated with reduced performance)!

A future, hopefully bigger symposium
The Connected Health symposium has always been a production of the Boston Partners Health Care conglomerate, a part of their Connected Health division. The leader of the division, Dr. Joseph Kvedar, introduced the symposium by expressing satisfaction that so many companies and organizations are taking various steps to make connected health a reality, then labeled three areas where leadership is still required:

  • Reassuring patients that the technologies and practices work for them. Most people will be willing to adopt these practices when urged by their doctors. But their privacy must be protected. This requires low-cost solutions to the well-known security problems in EHRs and devices–the latter being part of the Internet of Things, whose vulnerability was exposed by the recent attack on Dyn and other major Internet sites.

  • Relieving the pressures on clinicians. Kvedar reported that 45 percent of providers would like to adopt connected health practices, but only 12 percent do so. One of the major concerns holding them back is the possibility of data overload, along with liability for some indicator of ill health that they miss in the flood of updates. Partners Connected Health will soon launch a provider adoption initiative that deals with their concerns.

  • Scaling. Pilot projects in connected health invest a lot of researcher time and offers a lot of incentives to develop engagement among their subjects. Because engagement is the whole goal of connected health, the pilot may succeed but prove hard to turn into a widespread practice. Another barrier to scaling is consumers’ lack of tolerance for the smallest glitches or barriers to adoption. Providers, also, insist that new practices fit their established workflows.

Dr. Kvedar announced at this symposium that they would be doing future symposia in conjunction with the Personal Connected Health Alliance (Formerly the mHealth Summit owned by HIMSS), a collaboration that makes sense. Large as Partners Health Care is, the symposium reaches much farther into the health care industry. The collaboration should bring more resources and more attendees, establishing the ideals of connected health as a national and even international movement.

A New Meaning for Connected Health at 2016 Symposium (Part 3 of 4)

Posted on November 7, 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.

The previous section of this article paused during a discussion of the accuracy and uses of devices. At a panel on patient generated data, a speaker said that one factor holding back the use of patient data was the lack of sophistication in EHRs. They must be enhanced to preserve the provenance of data: whether it came from a device or from a manual record by the patient, and whether the device was consumer-grade or a well-tested medical device. Doctors invest different levels of trust in different methods of collecting data: devices can provide more objective information than other ways of asking patients for data. A participant in the panel also pointed out that devices are more reliable in the lab than under real-world conditions. Consumers must be educated about the proper use of devices, such as whether to sit down and how to hold their arms when taking their blood pressure.

Costantini decried the continuing silos in both data sharing and health care delivery. She said only half of doctors share patient data with other doctors or caretakers. She also praised the recent collaboration between Philips and Qualcomm to make it easier for device data to get into medical records. Other organizations that have been addressing that issue for some time include Open mHealth, which I reviewed in an earlier article, and Validic.

Oozing into workflow
The biggest complaint I hear from clinicians about EHRs–aside from the time wasted in their use, which may be a symptom of the bigger problem-is that the EHRs disrupt workflow. Just as connected health must integrate with patient lives as seamlessly as possible, it should recognize how teams work and provide them with reasonable workflows. This includes not only entering existing workflows as naturally as capillary action, but helping providers adopt better ones.

The Veterans Administration is forging into this area with a new interface called the Enterprise Health Management Platform (eHMP). I mentioned it in a recent article on the future of the VA’s EHR. A data integration and display tool, eHMP is agnostic as to data source. It can be used to extend the VistA EHR (or potentially replace it) with other offerings. Although eHMP currently displays a modern dashboard format, as described in a video demo by Shane Mcnamee, the tool aims to be much more than that. It incorporates Business Process Modeling Notation (BPMN) and the WS-Human Task Specification to provide workflow support. The Activity Management Service in eHMP puts Clinical Best Practices directly into the workflow of health care providers.

Clinicians can use eHMP to determine where a consultation request goes; currently, the system is based on Red Hat’s BPMN engine. If one physician asks another to examine the patient, that task turns up on the receiving physician’s dashboard. Teams as well as individuals can be alerted to a patient need, and alerts can be marked as routine or urgent. The alerts can also be associated with time-outs, so that their importance is elevated if no one acts on them in the chosen amount of time.

eHMP is just in the beginning stages of workflow support. Developers are figuring out how to increase the sophistication of alerts, so that they offer a higher signal-to-noise ratio than most hospital CDS systems, and add intelligence to choose the best person to whom an alert should be directed. These improvements will hopefully free up time in the doctor’s session to discuss care in depth–what both patients and providers have long said they most want from the health care field.

At the Connected Health symposium, I found companies working on workflow as well. Dataiku (whose name is derived from “haiku”) has been offering data integration and analytics in several industries for the past three years. Workflows, including conditional branches and loops, can be defined through a graphical interface. Thus, a record may trigger a conditional inquiry: does a lab value exceed normal limits? if not, it is merely recorded, but if so, someone can be alerted to follow up.

Dataiku illustrates an all-in-one, comprehensive approach to analytics that remains open to extensions and integration with other systems. On the one hand, it covers the steps of receiving and processing data pretty well.

To clean incoming data (the biggest task on most data projects), their DSS system can use filters and even cluster data to find patterns. For instance, if 100 items list “Ohio” for their location, and one lists “Oiho”, the system can determine that the outlier is a probably misspelling. The system can also assign data to belonging to broad categories (string or integer) as well as more narrowly defined categories (such as social security number or ZIP code).

For analysis, Dataiku offers generic algorithms that are in wide use, such as linear regressions, and a variety of advanced machine learning (artificial intelligence) algorithms in the visual backend of the program–so the users don’t need to write a single line of code. Advanced users can also add their own algorithms coded in a variety of popular languages such as Python, R, and SQL. The software platform offers options for less technically knowledgeable users, pre-packaged solutions for various industries such as health care, security features such as audits, and artificial intelligence to propose an algorithm that works on the particular input data.

Orbita Health handles workflows between patients and providers to help with such issues as pain management and medication adherence. The company addresses ease of use by supporting voice-activated devices such as Amazon Echo, as well as some 250 other devices. Thus, a patient can send a message to a provider through a single statement to a voice-activated device or over another Internet-connected device. For workflow management, the provider can load a care plan into the system, and use Orbita’s orchestration engine (similar to the Business Process Modeling Notation mentioned earlier) to set up activities, such as sending a response to a patient’s device or comparing a measurement to the patient’s other measurements over time. Orbita’s system supports conditional actions, nests, and trees.

CitiusTech, founded in 2005, integrates data from patient devices and apps into provider’s data, allowing enterprise tools and data to be used in designing communications and behavioral management in the patient’s everyday life. The company’s Integrated Analytix platform offer more than 100,000 apps and devices from third-party developers. Industry studies have shown effective use of devices, with one study showing a 40% reduction in emergency room admissions among congestive heart failure patients through the use of scales, engaging the patients in following health protocols at home.

In a panel on behavior change and the psychology of motivation, participants pointed out that long-range change requires multiple, complex incentives. At the start, the patient may be motivated by a zeal to regain lost functioning, or even by extrinsic rewards such as lower insurance premiums. But eventually the patient needs to enfold the exercise program or other practice into his life as a natural activity. Rewards can include things like having a beer at the end of a run, or sharing daily activities with friends on social media.

In his keynote on behavioral medicine, the Co-founder & CEO of Omada Health, Sean Duffy, put up a stunningly complex chart showing the incentives, social connections, and other factors that go into the public’s adoption of health practices. At a panel called “Preserving the Human Touch in the Expanding World of Digital Therapies”, a speaker also gave the plausible advice that we tell patients what we can give back to them when collecting data.

The next section of this article offers some memorable statements at the conference, and a look toward the symposium’s future.

A New Meaning for Connected Health at 2016 Symposium (Part 2 of 4)

Posted on November 4, 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.

The previous section of this article talked about making health a routine part of everyday life, particularly where consumer devices are concerned. We’ll continue in this section with other considerations aired at the symposium.

Tullman’s principles of simplicity, cited in the previous section, can be applied to a wide range of health IT. For instance, AdhereTech pill bottles can notify the patient with a phone call or text message if she misses a dose. Another example of a technology that is easily integrated into everyday life is a thermometer built into a vaginal ring that a woman can insert and use without special activation. This device was mentioned by Costantini during her keynote. The device can alert a woman–and, if she wants, her partner–to when she is most fertile.

Super-compact devices and fancy interfaces are not always necessary for a useful intervention. In a keynote, John Dwyer, Jr., President of the Global Alzheimer’s Platform Foundation, discussed a simple survey that his organization got large numbers of people to take. They uncovered a lot of undiagnosed cases of mental decline. I imagine that the people who chose to take the survey were experiencing possible symptoms and therefore were concerned about their mental abilities. Yet they apparently had not expressed concerns to their doctors; instead they responded to the online suggestion to take a survey.

Most of us spend a large chunk of our day at work, so wellness programs there are theoretically promising. A panel on workplace-connected health solutions talked about some of the barriers:

  • Inadequate communications. Employees need to be informed regularly that a program is available, and its benefits

  • Privacy guarantees. Employees must feel assured of a firewall between their employer and the organization handling their sensitive data.

  • Clear goals. A wellness program is not just a check-off box. Employers must know what they want to achieve and design programs around these goals.

I would add that employers should examine their own environment honestly before setting up a wellness program. It’s pretty hypocritical to offer a wellness program on the one hand while subjecting employees to stress, overwork, and bad ergonomics on the other.

Telehealth is also likely to grow, and in fact, 200 bills to improve regulation of telehealth are pending in Congress. A speaker at a panel on preserving the human touch said that the Centers for Medicare & Medicaid Services are held back by uncertainty about how to measure telehealth’s value. Another speaker pointed out that we have a severe shortage of mental health professionals, and that many areas lack access to them. Telehealth may improve access.

It all comes down to the environment
Health care has to fully acknowledge the role of environmental factors in creating sickness. These include the marketing of fatty and sugary foods, the trapping of poor and minority people in areas with air and water pollution, the barriers to getting health care (sick leave, geography, insurance gaps, ignorance of gender issues, and so forth), the government subsidization of gambling, and much more. Similar issues came up during a keynote by David Torchiana, President & CEO and Partners HealthCare.

In her keynote, Jo Ann Jenkins, the CEO of AARP, quoted Atul Gawande as saying that we have medicalized aging and are failing to support the elderly. We have to see them as functioning individuals and help to support their health instead of focusing on when things go wrong. This includes focusing on prevention and ensuring that they have access to professional health care while they are still well. It also means restructuring our living spaces and lifestyles so the elderly can remain safely in their homes, get regular exercise, and eat well.

These problems call for a massive legislative and regulatory effort. But as a participant said on the panel of disruptive women in health care, plenty of money goes into promoting the interests of large hospitals, insurers, and device manufacturers, but nobody knows how to actually lobby for health care. Look at the barriers reached by Michelle Obama’s Let’s Move campaign, which fell short of ambitious goals in improving American’s nutrition.

Grounding devices on a firm foundation
A repeated theme at this symposium was making data collection by patients easier–so easy in fact that they can just launch data collection and not think about it. To be sure, some people are comfortable with health technology: according to Costantini, 60 percent of US smartphone users manage their health in some way through those devices. Nevertheless, if people have to consciously choose when to send data–even a click of a button–many will drop out of the program.

At a break-out session during the 2015 Health Datapalooza, I heard prospective device makers express anxiety over the gargantuan task of getting their products accepted by the industry. The gold standard for health care adoption, of course, is FDA approval based on rigorous clinical trials. One participant in the Datapalooza workshop assured the others that he had gotten his device through the FDA process, and that they could to.

Attitudes seem to have shifted over the past year, and many more manufacturers are treating FDA approval as a natural step in their development process, keeping their eyes on the prize of clinical adoption. Keith Carlton, CEO of HUINNO, in a panel on wearables, said that accuracy is critical to stand out in the marketplace and to counter the confusion caused by manufacturers that substitute hype for good performance.

Clinical trials for devices don’t have to be the billion-dollar, drawn-out ordeals suffered by pharma companies. Devices are rarely responsible for side effects (except for implantables) and therefore can be approved after a few months of testing.

A representative of BewellConnect told me that their road to approval took 9-12 months, and involved comparing the results of their devices to those of robust medical devices that had been previously approved. Typical BewellConnect devices include blood pressure cuffs and an infrared thermometer that quickly shows the patient’s temperature after being held near his temple. This thermometer has been used around the world in situations where it’s important to avoid contact with patients, such as in Ebola-plagued regions.

What’s new over the past three years is Bluetooth-enabled devices that can transmit their results over the network. BewellConnect includes this networking capability in 17 current devices. The company tries to provide a supremely easy path for the patient to transmit the device over a phone app to the cloud. The patient can register multiple family members on the app, and is prompted twice to indicate who was using the device so as to prevent errors. BewellConnect is working on an alert system for providers, a simple use case for data collection.

Many products from BewellConnect are in widespread use in France, where the company is based, and they have launched a major entry into the US market. I asked BewellConnect’s CEO, Olivier Hua, whether the US market presents greater problems than France. He said that the two markets are more similar than we think.

Health care in the US has historically been fragmented, whereas in France it was unified under government control. But the Affordable Care Act in the US has brought more regulation to the market here, whereas private health care providers (combining insurance and treatment) have been growing in France. As of January 1 of this year, France has required all employers to include a private option in their health care offerings. For the first time, French individuals are being hit with the copays and deductibles familiar to Americans, and are weighing how often to go to the doctor. Although the US market is still more diverse, and burdened by continuing fee-for-service plans, it is comparable to the French market for a vendor such as BewellConnect.

The next section of this article will continue with a discussion of barriers in the use of patient data, and other insights from the Connected Health symposium.

A New Meaning for Connected Health at 2016 Symposium (Part 1 of 4)

Posted on November 3, 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.

Those of us engaged in health care think constantly about health. But at the Connected Health symposium, one is reminded that the vast majority of people don’t think much about health at all. They’re thinking about child care, about jobs, about bills, about leisure time. Health comes into the picture only through its impacts on those things.

Certainly, some people who have suffered catastrophic traumas–severe accidents, cancer, or the plethora of unfortunate genetic conditions–become obsessed about health to the same extent as health professionals. These people become e-patients and do all the things they need to do regain the precious state of being they enjoyed before their illness, often clashing with the traditional medical establishment in pursuit of health.

But for most people with chronic conditions, the opposite holds true. A whimsical posting points out that we willingly pay more to go to a masseur or hairdresser than to a doctor. I appreciate this observation more than the remedies offered by the author, which fall into the usual “patient engagment” activities that I have denigrated in an earlier article.

Understanding health as a facet and determinant of everyday life becomes even more important as we try to reverse the rise of costs, which in many nations are threatening economic progress and even the social contract. (Witness the popular anger in the current US election over rising insurance premiums and restrictions on choice.) We have to provide health solutions to people who are currently asymptomatic. The conventional focus on diagnosed conditions won’t serve us.

It’s thus commendable that the Connected Health symposium for 2016 has evolved to the point where participants can think not only of reaching out to patients, but to embedding their interventions so deeply into patient life that the patient no longer has to think about her health to benefit. This gives a new meaning to the word “connected”. Whereas, up to now, it referred to connecting a patient more closely with their clinicians and care-takers (through data collection, messaging, and online consultations), “connected” can also mean connecting our healthful interventions to the patient’s quotidian concerns about work, family, and leisure.

We can do this by such means as choosing data collection that the patient can enable and then stop thinking about, and integrating care with the social media they use regularly. In her keynote, Nancy Brown, CEO of the American Heart Association, pointed out that social connections are critical to health and are increasingly taking place online, instead of someone dropping by her neighbor for coffee. The AHA’s Go Red For Women program successfully exploited social connections to improve heart health.

If you want an overview of what people mean by the term “connected health,” you would do well to get The Internet of Healthy Things, by Dr. Joseph Kvedar, leader of Partners Connected Health and chief organizer of this symposium. For a shorter overview, you can read my review of the book, and my report from an earlier symposium. Now in its 13th year, the annual symposium signed up 1200 registered attendees–the biggest number yet. This article looks over the people and companies I heard from there.

Exhausting the possibilities of passive data collection
Glen Tullman, CEO of Livongo Health, offered basic principles for consumer health in a keynote: it must be personal, simple, context-aware, and actionable. As an example, he cited Livongo’s own program for sending text messages to diabetes patients: they are tailored to the individual and offer actionable advice such as, “Drink a glass of water”.

A panel on consumer technology extolled the value of what analysts like to call data exhaust: the use of data that can be collected from people’s everyday behavior. After all, this exhaust is what marketers used all the time to figure out what we want to buy, and what governments use to decide whether we’re dangerous actors. It can have value in health too.

As pointed out by Jim Harper, Co-Founder and COO of Sonde Health, providers and researchers can learn a lot from everyday interactions with devices–diagnosing activity levels from accelerometers, for instance, or depression from a drop in calls or text messages. Similarly, a symposium attendee suggested to me that colleges could examine social connections among students to determine which ones are at risk of abusing alcohol.

Lauren Costantini, President and CEO of Prima-Temp, said in a keynote that we can predict all kinds of things from your circadian rhythm–as measured by a sensor–such as an oncoming infection, or the best way to deliver chemotherapy.

Spire offers a device that claims to help people suffering from anxiety, with a low barrier to adoption and instant feedback. It’s a device worn on the body that can alert the user in various ways (buzzes, text messages) when the user’s anxiety level is rising.

Does the Spire device work? They got a partial answer to this in a study by Partners Health Care, where people had an option of using the device on its own or in conjunction with a headband from Muse that helps train people to meditate. (There was no control group.) Unlike the Spire device, which one can put on and forget about, the Muse purchaser is expected to make a conscious decision to meditate using the device regularly.

The Partners study showed modest benefits to these devices, but had mixed results. For instance, fewer than half the subjects continued use of the devices after the study finished. Those who did continue showed a strong positive effect on stress, and those who discontinued use showed a very small positive effect. Strangely there was a small overall increase in tension for all participants, even though they also demonstrated increases in “calm” periods. There is no correlation between the length of time that individuals used their devices and their outcomes.

Jonathan Palley, CEO & Co-founder of Spire, said participants often liked their devices, but stopped using them because they have learned from the devices how to identify stress and felt they could self-regulate and no longer needed the devices. I believe this finding may apply to other consumer devices as well. The huge rate at which devices are abandoned after six months, the subject of frequent reports and agonized commentaries, may simply indicate that users have reached their goal and can continue their fitness programs on their own. Graeme Moffat, VP of Scientific & Regulatory Affairs at Muse, reported that many purchasers use their headband for only three months, but come back to it over time to refresh their training.

We’ll look at some more aspects of integrating devices into patient lives in the next section of this article.

Study: Health IT Costs $32K Per Doctor Each Year

Posted on September 9, 2016 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

A new study by the Medical Group Management Association has concluded that that physician-owned multispecialty practices spent roughly $32,500 on health IT last year for each full-time doctor. This number has climbed dramatically over the past seven years, the group’s research finds.

To conduct the study, the MGMA surveyed more than 3,100 physician practices across the U.S. The expense number they generated includes equipment, staff, maintenance and other related costs, according to a press release issued by the group.

The cost of supporting physicians with IT services has climbed, in part, due to rising IT staffing expenses, which shot up 47% between 2009 and 2015. The current cost per physician for health IT support went up 40% during the same interval. The biggest jump in HIT costs for supporting physicians took place between 2010 and 2011, the period during which the HITECH Act was implemented.

Practices are also seeing lower levels of financial incentives to adopt EHRs as Meaningful Use is phased out. While changes under MACRA/MIPS could benefit practices, they aren’t likely to reward physicians directly for investments in health IT.

As MGMA sees it, this is bad news, particularly given that practices still have to keep investing in such infrastructure: “We remain concerned that far too much of a practice’s IT investment is tied directly to complying with the ever-increasing number of federal requirements, rather than to providing patient care,” the group said in a prepared statement. “Unless we see significant changes in the final rule, practice IT costs will continue to rise without a corresponding improvement in the care delivery process.”

But the MGMA’s own analysis offers at least a glimmer of hope that these investments weren’t in vain. For example, while it argues that growing investments in technologies haven’t resulted in greater administrative efficiencies (or better care) for practices, it also notes that more than 50% of responders to a recent MGMA Stat poll reported that their patients could request or make appointments via their practice’s patient portal.

While there doesn’t seem to be any hard and fast evidence that portals improve patient care across the board, studies have emerged to suggest that portals support better outcomes, in areas such as medication adherence. (A Kaiser Permanente study from a couple of years ago, comparing statin adherence for those who chose online refills as their only method of getting the med with those who didn’t, found that those getting refills online saw nonadherence drop 6%.)

Just as importantly – in my view at least – I frequently hear accounts of individual practices which saw the volume of incoming calls drop dramatically. While that may not correlate directly to better patient care, it can’t hurt when patients are engaged enough to manage the petty details of their care on their own. Also, if the volume of phone requests for administrative support falls enough, a practice may be able to cut back on clerical staff and put the money towards say, a nurse case manager for coordination.

I’m not suggesting that every health IT investment practices have made will turn to fulfill its promise. EHRs, in particular, are difficult to look at as a whole and classify as a success across the board. I am, however, arguing that the MGMA has more reason for optimism than its leaders would publicly admit.