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Patient Burnout – #HITsm Chat Topic

Posted on October 31, 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.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 11/3 at Noon ET (9 AM PT). This week’s chat will be hosted by Erin Gilmer (@GilmerHealthLaw) on the topic of “Patient Burnout.”

“We talk a lot about physician burnout. When do we talk about patient burnout?”

A few weeks ago I tweeted this out and it seems to have struck a nerve. Patient (and caregiver) burnout is a topic that is not addressed nearly enough outside of patient communities. However, burnout needs to be recognized and acknowledged in order to understand the patient experience and to create new solutions to improve health.

Patients are tasked with a lot to maintain and improve their health – things like scheduling appointments, dealing with insurance, managing multiple medications at the pharmacy, preparing for and going to appointments, communicating with healthcare providers, coordinating care between providers, and following care plans at home. All of this is in addition to their everyday lives – including family, work, social lives, and more – and dealing with sometimes very disabling conditions or while in great pain.

Providers who recognize this burnout may be able to understand why a patient might be “noncompliant” and find ways to address the patient’s needs. And those in HIT who want to create real change, can learn from the patient experience and work with patients to ease the burden patients face in managing their health.

Note: Before the chat, you might read: Rethinking the patient: using Burden of Treatment Theory to understand the changing dynamics of illness (open access).

Join us as we dive into this topic during this week’s #HITsm chat using the following questions.

Topics for This Week’s #HITsm Chat:

T1: What does patient burnout mean to you? #hitsm

T2: What would you like healthcare providers to know about patient burnout? #hitsm

T3: How could healthcare providers help you feel less burnt out? #hitsm

T4: What ways can technology help ease patient burnout? #hitsm

T5: What ways has technology made patient burnout worse? #hitsm

BONUS: What helps you deal with patient burnout? What advice would you give to other patients about burnout? Or what do you wish others had told you about burnout? #hitsm

Upcoming #HITsm Chat Schedule
11/10 – Medical Data Impact to Financial Health, Disability and Job Protection
Hosted by Kimberly George (@kimberlyanngeo) from @sedgwick

11/17 – TBD
Hosted by TBD

11/24 – Thanksgiving Break!

12/1 – Using Technology to Fight EHR Burnout
Hosted by Gabe Charbonneau, MD (@gabrieldane)

12/8 – TBD
Hosted by Homer Chin (@chinhom) and Amy Fellows (@afellowsamy) from @MyOpenNotes)

12/15 – TBD
Hosted by David Fuller (@genkidave)

We look forward to learning from the #HITsm community! As always, let us know if you’d like to host a future #HITsm chat or if you know someone you think we should invite to host.

If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.

HIPAA BAA Proliferation

Posted on October 30, 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.

There are a wide variety of forces at work in healthcare that are causing healthcare organizations to outsource more and more of their technology and services. No doubt the move to the cloud has brought in a number of new organizations that didn’t previously host PHI for a healthcare organization. This has added hundreds of outside companies who now have access to your patients’ PHI.

In a recent conversation I had with Rita Bowen and Anthony Murray from MRO at the AHIMA Annual Convention they also commented how many organizations were choosing to outsource their ROI and other services in order to keep their staffing ratios down. What a tremendous insight. We’ve all seen those charts (see the one at the left) that show the growth in provider count over time versus the growth in the number of administrators. We all see these charts and see it as a big problem in healthcare.

In order to combat this perception, it’s no surprise that healthcare organizations are trying to keep these admin to doctor ratios at a better level. One way they’re massaging those numbers is to outsource more of their services. We could talk about whether this is a good strategy or not, but that’s a topic for another blog post. The reality is that these ratios and many other drivers are causing organizations to work with a growing number of outside companies.

I was talking with a hospital CIO who told me that they had 300 different health IT systems. As healthcare organizations have brought on more health IT systems and outsourced many of their services, we have seen what I call HIPAA BAA (Business Associate Agreement) Proliferation. Each of these health IT organizations and outside health services will likely need to sign a BAA.

Healthcare organizations are now managing hundreds of business associate agreements with hundreds of partners. Plus, this doesn’t take into account that many of your BAs also have subcontractors for which they need BAAs and so forth down the line. This cascade of BAAs that are needed by a healthcare organization has to keep a lot of risk managers and HIPAA compliance officers up at night. Unfortunately, I don’t believe that most healthcare organizations are doing a great job managing the hundreds and thousands of BAAs that their organizations need.

Rita Bowen and Anthony Murray from MRO offered one suggestion that could help HIPAA compliance officers and risk managers that are charged with managing the overwhelming task of business associate agreement compliance. They suggested that the volume of BAAs has gotten so large that it’s time to start evaluate BAA vetting efforts based on the amount of information being shared with the business associate. An ROI (release of information) company who has access to all of your patients’ PHI should be vetted differently than an IT service company who may have some tangential access to PHI but has no direct access. Does your BAA vetting process take this into account? My experience is that it doesn’t, but given the volume it probably should.

As health data breaches become more and more common, putting in an effective BAA compliance plan that effectively vets your business associates both during the purchase process and then after purchase and implementation is going to be key. Analyzing a business associate’s access to PHI and risk of being compromised is one strategy healthcare organizations will need to use to better handle BAA proliferation in their organization.

What are you doing to handle BAA proliferation in your organization? Are you seeing this happen? Does this keep you up at night? Let us know your thoughts and experiences in the comments.

Health Data Tracking Is Creeping Into Professional Sports

Posted on October 27, 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.

Pro athletes are used to having their performance tracked minutely, not only by team owners but also by legions of fans for whom data on their favorite players is a favored currency. However, athletic data tracking has taken on a shape with the emergence of wearable devices.

For example, in spring of last year, Major League Baseball approved two devices for use during games, the Motus Baseball Sleeve, which tracks stress on elbows, and the Zephyr Bioharness, which monitors heart and breathing rates, skin temperature and sleep cycle.

In what must be a disappointment to fans, data from the devices isn’t available in real time and only can be downloaded after games. Also, clubs use the data for internal purposes only, which includes sharing it with the player but no one else. Broadcasters and other commercial entities can’t access it.

More recently, in April of this year, the National Football League Players Association struck a deal with wearables vendor WHOOP under which its band will track athletes’ performance data. The WHOOP Strap 2.0 measures data 100 times per second then transmits the data automatically to its mobile and web apps for analysis and performance recommendations.

Unlike with the MLB agreement, NFL players own and control the individual data collected by the device, and retain the rights to sell their WHOOP data through the Players Association group licensing program.

Not all athletes are comfortable with the idea of having their performance data collected. For example, as an article in The Atlantic notes, players in the National Basketball Association included the right to opt out of using biometric trackers in their latest collective-bargaining agreement, which specifies that teams requesting a player wear one explain in writing what’s being tracked and how the team will use the information.  The agreement also includes a clause stating that the data can’t be used or referenced as part of player contract negotiations.

Now, it’s worth taking a moment to note that concerns over the management of professional athlete performance data file into a different bucket than the resale of de-identified patient data. The athletic data is generated only during the game, while consumer wearables collect data the entire time a patient is awake and sometimes when they sleep. The devices targeting athletes are designed to capture massive amounts of data, while consumer wearables collect data sporadically and perhaps not so accurately at times.

Nonetheless, the two forms of data collection are part of a larger pattern in which detailed health data tracking is becoming the norm. Athletic clubs may put it to a different purpose, but both consumer and professional data use are part of an emerging trend in which health monitoring is a 24/7 thing. Right now, consumers themselves generally can’t earn money by selling their individual data, but maybe there should be an app for that.

Is It Time To Redefine Interoperability?

Posted on October 26, 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.

Recently, an article appearing in healthcare journal HealthAffairs argued that hospitals’ progress toward interoperability has been modest to date. The article, which looked at the extent to which hospitals found, sent, received and integrated information from outside providers in 2015, found that they’d made few gains across all four categories.

Researchers found that the percent of hospitals engaging in all four activities rose to 29.7% that year, up from 24.5% in 2014. The two activities that grew the most in frequency were sending (growing 8.1%) and receiving (8.4%). Despite this expansion, only 18.7% of hospitals reported that they used this data often. The extent to which hospitals integrated the information they received didn’t change from 2014 to 2015.

Interesting, isn’t it, how these stats fail to align with what we know of hospitals’ priorities?  Not only did the rate hospitals sent and received data increase slowly between those two years, hospitals don’t seem to be making any advances in integrating (and presumably, using) shared data. This doesn’t make sense given hospitals’ intense efforts to make interoperability happen.

The question is, are hospitals still limping along in their efforts, or are we failing to measure their progress effectively? For years now, looking at the extent to which they sent/received/found/integrated data has been the accepted yardstick most quarters. To my knowledge, though, those metrics haven’t been validated by formal research as being the best way to define and capture levels of interoperability.

Yes, hospital health data interoperability may be moving as slowly as the HealthAffairs article suggests. After all, I hardly have to tell readers like you how difficult it has been to foster interoperability in any form, and how challenging it has been to achieve any kind of consensus on data staring standards. If someone tells progress toward health data exchange between hospitals hasn’t reached robust levels yet, it probably won’t surprise you in the least.

Still, before we draw the sweeping conclusions about something as important as interoperability, it probably wouldn’t hurt to double-check that we’re asking the right questions.

For example, is the extent to which providers send data to outside organizations as important as the extent to which they receive such data?  I know, in theory, that health data exchanges would be just that, a back and forth between parties on both sides. Certainly, such arrangements are probably better for the industry as a whole long term. But does that mean we should discount the importance of one side or the other of the process?

Perhaps more importantly, at least in my book, is the degree to which hospitals integrate the data into their own systems a good proxy for measuring who’s making interoperability progress? And should be assumed that if they integrate the data, they’re likely to use it to improve outcomes or streamline care?

Don’t misunderstand me, I’m not suggesting that the existing metrics are useless. However, it would be nice to know whether they actually measure what we want them to measure. We need to validate our tools if we want use them to make important judgments about care delivery. Otherwise, why bother with measurements in the first place?

Patient Portal Use Rising Rapidly

Posted on October 25, 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.

A new study has concluded that patient portal use has shot up over the past few years, with a substantial majority of patients reporting that they use provider portals if possible.

The purpose of the study, results of which was published in Perspectives in Health Information Management, was to examine how healthcare consumers saw their interactions with provider portals, their use of personal health records and their take on the process of releasing health data.

According to a 2015 study cited by the article’s authors, 53% of HIM professionals reported charging consumers for both electronic and paper copies of their health information. Thirty-eight percent said they had a patient portal, but less than 5% of patients were using it.

Over the last two years, however, the picture has changed a great deal. Researchers conducting the current study found that only 10% of consumers were charged for their health information. In addition, 49% reported that they maintained a personal health record. Eighty-three percent of respondents said that their providers had portals, and 82% said that they were taking advantage of their provider’s portal where available.

Patient uses for portals included viewing lab results (35%), requesting medication refills (19%), requesting appointments (22%), secure messaging (19%) and other (5%). Among portal users, 53% were very satisfied and 38% were satisfied with their experiences.

Meanwhile, 49% of respondents said they maintained PHRs, with top record format being combined paper and electronic (46%), followed by paper only (35%), electronic only (18%) and other (1%).

It’s important to note that the study population was especially healthcare-savvy. Participants chosen were campus-based and online students enrolled in a College of Health Professions course, alumni of BA programs in HIM at the researchers’ university, local AHIMA members and the researchers’ family and friends.

The article argues that because the participants were all current healthcare consumers, they were qualified participants. That may be so, but the high concentration of HIM-friendly respondents probably stacked the deck somewhat. (To be fair, the authors admit this.)

That being said, even these relatively sophisticated respondents weren’t completely comfortable with the health data access they had. Complaints cited by consumers included a lack of interoperability between physicians’ offices and electronic PHI, as well as the difficulty of getting data into the portal or updated when already present. Others reported having concerns about health data security.

All told, it looks like the hoped-for growth in patient health data use is taking place over time. I suspect that a direct comparison between less-informed consumers from 2015 and today would show less pronounced changes, though.

 

Aggregating the Patient Perspective and Incorporating It Into Software to Change Healthcare – #HITsm Chat Topic

Posted on October 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.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 10/27 at Noon ET (9 AM PT). This week’s chat will be hosted by CP Nerve Center (@Cpnervecenter), Lisa Davis Budzinski (@lisadbudzinski), and Becky Brandt, RN (@bbhomebody) on the topic of “Aggregating the Patient Perspective and Incorporating It Into Software to Change Healthcare.”

“Fragmented Care” is costly and common

The term “feed forward” refers to designing an information system to collect patient data in real time as care is delivered. Data collection occurs from the first visit, and moves with the patient.

*If we cannot understand patients within our systems of care, how are we going to improve? Perhaps these problems can be overcome by designing data-rich, patient-centric, feed-forward information environments with real-time feedback using a novel approach that is described below.

*The objective is to turn an individual’s data into useful information that can guide intelligent action and to aggregate this patient-level information to show quantifiable results within the clinical microsystem, the healthcare macrosystem, and the community.

Join us as we dive into this topic during this week’s #HITsm chat using the following questions.

Topics for This Week’s #HITsm Chat:

T1: What extra data should be collected @ appts, to improve outcomes, patient satisfaction & help future patients? #hitsm

T2: Share an example of how Feed-Forward clinical data sytms have helped or harmed you as a pt, Or in caring for a patient. #hitsm

T3: What incentives could be used to create & improve patient centric clinical data systems? How do we connect more facilities? #hitsm

T4: Would patient satisfaction outcomes improve if patients carried full EHR on a thumb drive (etc), to share & update at the end of each visit? #hitsm

T5: Does your Doctor ask for your perspective about your plan of care or how your care is going? And about your satisfaction? #hitsm

BONUS: Is patient-centric care occurring at your medical facility? Are you asked your opinion? #hitsm

Upcoming #HITsm Chat Schedule
11/3 – Patient Burnout
Hosted by the Erin Gilmer (@GilmerHealthLaw)

11/10 – TBD
Hosted by TBD

11/17 – TBD
Hosted by TBD

11/24 – Thanksgiving Break!

12/1 – Using Technology to Fight EHR Burnout
Hosted by Gabe Charbonneau, MD (@gabrieldane)

12/8 – TBD
Hosted by Homer Chin (@chinhom) and Amy Fellows (@afellowsamy) from @MyOpenNotes)

We look forward to learning from the #HITsm community! As always, let us know if you’d like to host a future #HITsm chat or if you know someone you think we should invite to host.

If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.

Health IT Continues To Drive Healthcare Leaders’ Agenda

Posted on October 23, 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.

A new study laying out opportunities, challenges and issues in healthcare likely to emerge in 2018 demonstrates that health IT is very much top of mind for healthcare leaders.

The 2018 HCEG Top 10 list, which is published by the Healthcare Executive Group, was created based on feedback from executives at its 2017 Annual Forum in Nashville, TN. Participants included health plans, health systems and provider organizations.

The top item on the list was “Clinical and Data Analytics,” which the list describes as leveraging big data with clinical evidence to segment populations, manage health and drive decisions. The second-place slot was occupied by “Population Health Services Organizations,” which, it says, operationalize population health strategy and chronic care management, drive clinical innovation and integrate social determinants of health.

The list also included “Harnessing Mobile Health Technology,” which included improving disease management and member engagement in data collection/distribution; “The Engaged Digital Consumer,” which by its definition includes HSAs, member/patient portals and health and wellness education materials; and cybersecurity.

Other hot issues named by the group include value-based payments, cost transparency, total consumer health, healthcare reform and addressing pharmacy costs.

So, readers, do you agree with HCEG’s priorities? Has the list left off any important topics?

In my case, I’d probably add a few items to list. For example, I may be getting ahead of the industry, but I’d argue that healthcare AI-related technologies might belong there. While there’s a whole separate article to be written here, in short, I believe that both AI-driven data analytics and consumer-facing technologies like medical chatbots have tremendous potential.

Also, I was surprised to see that care coordination improvements didn’t top respondents’ list of concerns. Admittedly, some of the list items might involve taking coordination to the next level, but the executives apparently didn’t identify it as a top priority.

Finally, as unsexy as the topic is for most, I would have thought that some form of health IT infrastructure spending or broader IT investment concerns might rise to the top of this list. Even if these executives didn’t discuss it, my sense from looking at multiple information sources is that providers are, and will continue to be, hard-pressed to allocate enough funds for IT.

Of course, if the executives involved can address even a few of their existing top 10 items next year, they’ll be doing pretty well. For example, we all know that providers‘ ability to manage value-based contracting is minimal in many cases, so making progress would be worthwhile. Participants like hospitals and clinics still need time to get their act together on value-based care, and many are unlikely to be on top of things by 2018.

There are also problems, like population health management, which involve processes rather than a destination. Providers will be struggling to address it well beyond 2018. That being said, it’d be great if healthcare execs could improve their results next year.

Nit-picking aside, HCEG’s Top 10 list is largely dead-on. The question is whether will be able to step up and address all of these things. Fingers crossed!

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.