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A Missed Opportunity For Telemedicine Vendors

Posted on June 29, 2018 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.

Today, most direct-to-consumer telemedicine companies operate on a very simple model.

You pay for a visit up front. You talk to the doctor via video, the doctor issues as a prescription if needed and you sign off. Thanks to the availability of e-prescribing options, it’s likely your medication will be waiting for you when you get to the pharmacy.

In my experience, the whole process often takes 45 minutes or less. This beats the heck out of having to wait in line at an urgent care center or worse, the emergency department.

But what about caring for chronic illnesses that can’t be managed by a drive-by virtual visit? Can telemedicine vendors play a role here? Maybe so.

We already know that combining telemedicine with remote monitoring devices can be very effective. In fact, some health systems have gone all-in on virtual chronic care management.

One fascinating example is the $54 million Mercy Virtual Care Center, which describes itself as a “hospital without beds.” The Center, which has a few hundred employees, monitors more than 3,800 remote patients; sponsors a telehealth stroke program offering neurology services to EDs nationwide; manages a team of virtual hospitalists caring for patient around-the-clock using virtual visit tools; and runs Mercy SafeWatch, which the Center says is the largest single-hub electronic intensive care unit in the U.S.

Another example of such hospital-based programs is Intermountain Healthcare’s ConnectCare Pro, which brings together 35 telehealth programs and more than 500 clinicians. Its purpose is to supplement existing staffers and offer specialized services in rural communities where some of the services aren’t available.

Given the success of programs that maintain complex patients remotely, I think a private telemedicine company managing chronic care services might work as well. While hospitals have financial reasons to keep such care in-house, I believe an outside vendor could profit in other ways. That’s especially the case given the emergence of wearable trackers and smartwatches, which are far cheaper than the specialized tools needed in the past.

One likely buyer for this service would be health plans.

I’ve heard some complain publicly that in essence, telemedicine coverage just encourages patients to access care more often, which defeats the purpose of using it to lower healthcare costs. However, if an outside vendor offered to manage patients with chronic illnesses, it might be a more attractive proposition.

After all, health plans are understandably wringing their hands over the staggering cost of maintaining the health of millions of diabetics. In 2017, for example, the average medical expense for people diagnosed with diabetes was about $16,750 per year, with $9,600 due to diabetes. If health plans could lay the cost off to a specialized telemedicine vendor, some real savings might be possible.

Of course, being a telemedicine-based chronic care management company would be far different than offering direct-to-consumer telemedicine services on an occasional basis. The vendor would have to have comprehensive health data management tools, an army of case managers, tight relationships with clinicians and a boatload of remote monitoring devices on hand. None of this would come cheaply.

Still, while I haven’t fully run the numbers, my guess is that this could be a sustainable business model. It’s worth a try.

Alexa Voice Assistant Centerpiece Of Amazon Health Effort

Posted on June 1, 2018 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.

I don’t know about you, but until recently I had thought of the Amazon Echo is something of a toy. From what I saw, it seemed too cute, too gimmicky and definitely too expensive for my taste. Then I had a chance to try out the Echo my mother kept in her kitchen.

It’s almost embarrassing to say how quickly I was hooked. I didn’t even use many of Alexa’s capabilities. All I had to do was command her to play some music, answer some questions and do a search on the Amazon.com site and I was convinced I needed to have one. Its $99 price suddenly seemed like a bargain.

Of course, being a health IT geek I immediately wondered how the Alexa voice assistant might play a part in applications like telemedicine, but I was spending too much time playing “Name That Song” (I’m an 80s champ) to think things through.

But I had the right instincts. It’s become increasingly clear that Amazon sees Alexa as a key channel for reaching healthcare decision-makers.

According to a story appearing on the CNBC website, Amazon has built a 12-person team within the Alexa voice-assisted division called “health & wellness” whose focus is to make Alexa more useful to healthcare patients and providers. Its first targets include diabetes management, care for mothers and infants and aging, according to people who spoke anonymously with CNBC.

Of course, this effort would involve working through HIPAA rules, but it’s hard to imagine that a company like Amazon couldn’t buy and/or cultivate that expertise.

In the piece, writers Eugene Kim and Christina Farr argue that the mere existence of the health & wellness group is a clear sign that Amazon plans to bring Alexa to healthcare. As long as the Echo can share and upload data in a secure, HIPAA-compliant fashion, the possibilities are almost endless. In addition to sharing data with patients and clinicians, this would make it possible to integrate the data with secure third-party apps.

Of course, a 12-person unit is microscopic in size within a company like Amazon, and from that standpoint, the group might seem like a one-off experiment. On the other hand, its work seems more important when you consider the steps Amazon has already taken in the healthcare space.

The most conspicuous move Amazon has made in healthcare came in early 2018, when it announced a joint initiative with Berkshire Hathaway and J.P. Morgan focused on improving healthcare services. To date, the partnership hasn’t said much about its plans, but it’s hard to argue that something huge could emerge from bringing together players of this size.

In another, less conspicuous move, Alexa took a step towards competing in the diabetes care market. In the summer of 2017, working with Merck, Amazon offered a prize to developers building Alexa “skills” which could help people with diabetes manage all aspects of their care. One might argue that this kind of project could be more important than something big and splashy.

It’s worth noting at this point that even a monster like Google still hasn’t made bold moves in healthcare (though it does have extraordinarily ambitious plans). Amazon may not find it easy to compete. Still, it will certainly do some interesting things, and I’m eager to see them play out. In fact, I’m on the edge of my seat – aren’t you?

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.

CVS Launches Analytics-Based Diabetes Mgmt Program For PBMs

Posted on December 29, 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.

CVS Health has launched a new diabetes management program for its pharmacy benefit management customers designed to improve diabetes outcomes through advanced analytics.  The new program will be available in early 2017.

The CVS program, Transform Diabetes Care, is designed to cut pharmacy and medical costs by improving diabetics’ medication adherence, A1C levels and health behaviors.

CVS is so confident that it can improve diabetics’ self-management that it’s guaranteeing that percentage increases in spending for antidiabetic meds will remain in the single digits – and apparently that’s pretty good. Or looked another way, CVS contends that its PBM clients could save anywhere from $3,000 to $5,000 per year for each member that improves their diabetes control.

To achieve these results, CVS is using analytics tools to find specific ways enrolled members can better care for themselves. The pharmacy giant is also using its Health Engagement Engine to find opportunities for personalized counseling with diabetics. The counseling sessions, driven by this technology, will be delivered at no charge to enrolled members, either in person at a CVS pharmacy location or via telephone.

Interestingly, members will also have access to diabetes visit at CVS’s Minute Clinics – at no out-of-pocket cost. I’ve seen few occasions where CVS seems to have really milked the existence of Minute Clinics for a broader purpose, and often wondered where the long-term value was in the commodity care they deliver. But this kind of approach makes sense.

Anyway, not surprisingly the program also includes a connected health component. Diabetics who participate in the program will be offered a connected glucometer, and when they use it, the device will share their blood glucose levels with a pharmacist-led team via a “health cloud.” (It might be good if CVS shared details on this — after all, calling it a health cloud is more than a little vague – but it appears that the idea is to make decentralized patient data sharing easy.) And of course, members have access to tools like medication refill reminders, plus the ability to refill a prescription via two-way texting, via the CVS Pharmacy.

Expect to see a lot more of this approach, which makes too much sense to ignore. In fact, CVS itself plans to launch a suite of “Transform Care” programs focused on managing expensive chronic conditions. I can only assume that its competitors will follow suit.

Meanwhile, I should note that while I expect to see providers launch similar efforts, so far I haven’t seen many attempts. That may be because patient engagement technology is relatively new, and probably pretty expensive too. Still, as value-based care becomes the dominant payment model, providers will need to get better at managing chronic diseases systematically. Perhaps, as the CVS effort unfolds, it can provide useful ideas to consider.

Jubilee Health Community and NoMoreClipboard Combine Forces To Help Diabetes Patients

Posted on December 20, 2012 I Written By

Katie Clark is originally from Colorado and currently lives in Utah with her husband and son. She writes primarily for Smart Phone Health Care, but contributes to several Health Care Scene blogs, including EMR Thoughts, EMR and EHR, and EMR and HIPAA. She enjoys learning about Health IT and mHealth, and finding ways to improve her own health along the way.

According to the U.S. Department of Health and Human Services, 20.8 million people in the United States are affected by diabetes. This amounts to around seven percent of the population, which is a fairly large percentage. Many of those with diabetes likely have no health insurance

Jubilee  Health Community and NoMoreClipboard PHR are working together to help uninsured manage diabetes, according to a recent press release. The objectives of this include:

  • Explore the use of a PHR by rural, uninsured patients with diabetes
  • Improve patient health outcomes by providing patients with a PHR to share and track daily glucose readings
  • Improve diabetes care management by sharing health information between a clinician and patients using a PHR.

28 diabetes patients of Jubilee Health Community were given a smartphone-enabled version of the NoMoreClipboard PHR about a year ago to assist them in managing their diabetes. Immediate feedback was given when glucose values were entered, and lab results were input within about 72 hours.

These patients and their use of the PHR were monitored over the course of a year, and that findings were interesting. Here are some of the stats that were listed in the press release:

  • 37.5 percent of the patients remained actively engaged and regularly entered blood glucose readings via NoMoreClipboard
  • Of those 37.5 percent of patients, 28.6 had improved A1C levels and reported feeling better
  • Those that did not actively use the PHR, 21.4 percent had no improvement or increased A1C levels
  • Of those that did not stay engaged, one of the patients whose A1C level increased suffered an MI.

Diabetes is linked to a host of other health problems, which include adult blindness, kidney failure, non-traumatic amputations, and heart disease and strokes. Obviously, there is a great need for some additional help for these patients, and this PHR seems like it could really do a lot of good. The sample size might not be the greatest to glean the most accurate results on the effectiveness of the PHR, but it does give some insight to indicate it would be worth trying. I think it’s great that some of those who used the PHR regularly did see improvement.

Jeff Donnell, president of NoMoreClipboard, offered some commentary concerning the value of electronic patient engagement:

This project reinforces the value of electronic patient engagement in helping underserved patients manage chronic conditions. Providers are often skeptical that populations including seniors and safety net patients will be able to cross the digital divide and use a PHR. Our experience with rural and urban underinsured patients make it clear that these individuals are looking for tools to help them take a more active role, and they will use those tools when they provide benefit.

In general, I feel like when people are accountable and regularly track information concerning their health (whether it be for diabetes, trying to lose weight, etc.) there will be an increase in their health and well-being. The problem is, it can be very hard to stay on track with systems like this –which is evidenced by the fact that over 60 percent of the people didn’t remain active at the end of the trial period. It raises the question, what can be done to convince people to keep track of their health on things like the NoMoreClipboard PHR?

Text Messaging as a Tool for Behavior Change in Disease Prevention and Management

Posted on April 29, 2011 I Written By

Recently I posted a few different pieces about technology being used to help people quit smoking, lose weight, and even manage their diabetes.  A new study is showing how valuable text messaging can be when it comes to managing your health.  It is by far the most expansive study I have read and makes a lot of interesting points and logical conclusions.

One of the biggest advantages to text messaging is that it is already widely used, and it is extremely inexpensive to use.  This low cost allows organizations without major financial backing to use text messaging as a tool for their patients.  There is no need create a new device or develop expensive software.  You simply use text messaging to distribute the desired messages to your patients.

The study specifically referenced studies that showed how text messaging was beneficial to people that were trying to quit smoking by holding them accountable for their actions.  The same principle applied to people that were trying to lose weight.  Taking responsibility for your actions is a huge part of both of these issues, and using text messaging allowed the affected people to accept that responsibility.

Text messaging can also be used to help manage diseases such as diabetes by sending out reminders to the patients.  There are so many aspects to properly managing diabetes that getting helpful reminders can only be a good thing.

While the study doesn’t compare text messaging to other technology that can be used for managing our health it does an excellent job of analyzing the benefits of this inexpensive and widely used technology.  The numbers that they present are quite staggering in some areas, and it is definitely worth a look at the complete study.