Engaging Patients Through Trust

Barbara Massoudi, BreathEasy Principal Investigator, RTI International
Rita Sembajwe, BreathEasy Project Manager, RTI International

Editor's note: This post is fifth in a series on patient engagement.

When describing the BreathEasy project patient population to colleagues, we’re often met with skepticism about the wisdom of working with an economically disadvantaged population. Some people ask whether it wouldn’t have been easier to work with a middle income population or with people who already own smartphones. The assumptions underlying these questions are that this population can’t be trusted with expensive equipment, or won’t be reliable recorders of their observations of daily living (ODLs). Our colleagues are expecting that the choice of population will somehow negatively impact our ability to conduct the research, and therefore, should be avoided.

We tell them the members of the BreathEasy patient population were selected specifically because they stand to benefit the most from using the application as they inherently have fewer resources at their disposal! Patients enrolled in the study were selected because of socioeconomic status based on their residential zip code, and that method worked well for us. The median income for BreathEasy patient participants is between $10,000-15,000 annually; participants have a high school diploma or less education; and most are unemployed.

Our experience working with these patients has proven to be very different from what our colleagues anticipated. As we approach the conclusion of the six-month evaluation period, we’re still seeing very consistent reporting of ODLs by the patients. In fact, whenever patients have anticipated a time when they won’t be tracking consistently, such as a planned surgery or childbirth, we’ve received text messages stating that they’ll be off the application for some time, but back on soon. We’ve also received phone calls and text messages when patients have had unexpected events, such as hospitalizations, that have caused them not to report. The patients have been very apologetic about not recording for a few days.

What we find striking about this is that the level of patient engagement we’re seeing exceeds that of middle class populations. Perhaps the BreathEasy population is more grateful for the mobile application and the opportunity to participate in the study. We’ve heard patients express that such an app “…will help me and my doctor track my asthma a lot easier,” which tells us that they do feel like the app serves a purpose. We have also heard patients express the view that “the app is designed by us, for us, and for our benefit.” These are certainly encouraging words for researchers taking a user-centered design approach. We also think there’s an important element of trust and fulfillment of expectations here. As Barbara’s mother used to say, “If you expect people to do great things and let them know it, they usually won’t let you down.” We’d say there’s more than a bit of that happening here. Stay tuned for a future post on the outcomes of our evaluation period.

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BreathEasy by the Numbers

Barbara L. Massoudi, M.P.H., Ph.D., BreathEasy Principal Investigator, RTI International

We're excited to share a quick update now that we're just about at the halfway point in the intervention:

• We've recruited 30 patients who have been actively submitting data through our mobile app for about three months now.


• The patient-generated data is viewed by two types of clinicians participating in the study: family physicians (n=13) and nurses (n=7).


• The nurses review the data at least once a week, but some review more frequently. When they see something that concerns them, the nurses flag the data for additional review by the patient’s physician.


• Twenty-two patients have been in for clinical visits since the intervention phase began, but not necessarily to be seen for their asthma.


• Two patients have received new diagnoses as a result of the intervention.


• Sadly, two of the mobile phones have been stolen to date; one was retrieved and the other is being replaced. We've worked through the appropriate safeguards and reporting processes related to these losses.

Check back next month to learn about the many technical challenges we’ve had that relate to the phones.

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Build It and They Will Come: Can Technology Change Behavior?

Murrey G. Olmsted, Ph.D., BreathEasy Senior Methodological Advisor, RTI International

I recently heard a story on the news about the famed “Field of Dreams” farm in Dyersville, Iowa. This story reminded me of the approach taken with personal health records (PHRs) and health tracking devices over the past decade. Well intentioned clinicians, researchers, technologists, and others have brought many products to the market and have assumed that if you build a new device or PHR then people will use it to improve their health. As a result, we now have electronic devices that track steps taken, food consumed, water drunk, hours slept, and many other indicators of health and health-promoting behaviors. Now even our smartphones can provide many of these functions via apps that take advantage of motion sensors, GPS tracking, photo uploading, social networking, and barcode scanning. One common feature that most of these tools share is that they are tied to a record system such as a diary, tracking log, or PHR.

This all sounds great! More technology to enhance health that is portable, easy to use, and probably works on the smartphone I already have. If I were only to read the promotional literature, I might be convinced we are heading toward a golden age of health improvement with technology leading the way.

However, there is some trouble in the world of PHRs and health-promoting technologies:

• First, the annual CDC reports indicate that on average people are still significantly overweight, developing diabetes at alarming rates, and struggling with many chronic health conditions.
• Second, most devices or record systems don’t talk to each other. For instance, my smartphone tracks walking and running data on a website provided by a major sports manufacturer. The record is great in terms of helping me track my activity and communicate with my friends, but it does not connect to my own physician’s clinical electronic health record (EHR) or any other system that I have.
• Third, the PHR used at my doctor’s office provides tools for tracking my historical health data, but does not provide any help on what steps I need to take to enhance my health going forward; this is a common problem with PHRs, as most serve only as patient information portals rather than offering the full functionality needed.
• Fourth, the options for consumer-oriented PHRs are declining. For instance, Google Health announced earlier this year that they would be shutting down their PHR service at end of 2011 due to the lack of broad consumer adoption. As a result, I now have to choose between the PHR offered by my doctor or one of the few remaining national PHRs still available (e.g., Microsoft HealthVault, WebMD PHR, etc.).

So what’s the problem? I thought we had the technology? 

It turns out—not surprisingly—that behavior is difficult to change. Technology is great and people generally enjoy using it, but the impact is frequently not long-lasting unless fundamental behavior change occurs. To do that, the current crop of technological solutions will need to address not only the challenges listed above (in particular connecting all patient records), but will also need to help users change their behaviors. Published research is increasingly citing the need for behavior change as a key component of health-promoting technology. Also, authors are beginning to draw the distinction between PHRs that function as health information banks (e.g., look-up systems for lab results) and those that are truly ‘personal’ which can be customized to the needs of the user. What is really needed are tools that can serve the specific needs of users by guiding and encouraging them along in their journey toward behavior change, not just simply track their data and hold it for safekeeping. If the technology can make this shift, then we may start to see better results in those annual CDC reports.

Let us know what you think: How is behavior change key to successful health technology development and use?

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Health 2.0 Recap, Part 2: The Pioneer Portfolio Approach

Robert Furberg, MBA, Ph.D., BreathEasy Text Messaging Pilot Lead, RTI International

Read Health 2.0 Recap, Part 1: The Conference

The Robert Wood Johnson Foundation’s Pioneer portfolio sent about 20 people to Health 2.0, including Project HealthDesign grantees, to discuss how best to move the early consumer health concepts from Health 2.0 into the clinical mainstream. Pioneer attendees were asked specifically, “Can we build better bridges to connect your work, Health 2.0 and clinicians?” and “How can we collaborate to leverage patient self-learnings as well as the work of health care professionals?” 

The Pioneer portfolio group attended sessions, networked, and sought inspiration. In the evenings, we reconvened as a group for receptions or over dinner to discuss what we had heard and how we thought we could contribute. One of the most interesting things I noticed was that we tended to stick together in a pack, sharing our experiences with our own Project HealthDesign work, reflecting on interesting conversations, and explicitly addressing the elephants in the room — rigorous and valid evaluation of Health 2.0 ideas and/or technologies and fostering mainstream adoption of the nascent Health 2.0 movement.

We wrapped up the experience with a half-day Pioneer workshop to try to envision how better bridges can be built to connect our work with other worlds in transformative ways. We worked together to discuss questions like:

• What changes need to occur for the innovations on parade at Health 2.0 to become viable and credible among clinicians? Among the general population? Among health care systems?
  
• What kinds of policy changes need to be enacted before ODLs, self quantification, and other patient-generated data sources are integral to an electronic health record? 

It was an exhausting, but invigorating, several days. The potential for Project HealthDesign to impart good evaluation practices and sound experimental methodology among the innovators at Health 2.0 is huge. This brand of collaboration is one that makes sense for all of us who reside at the intersection of technology and health.

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Health 2.0 Recap, Part 1: The Conference

Robert Furberg, MBA, Ph.D., BreathEasy Text Messaging Pilot Lead, RTI International

The worlds of health and technology collided over in late September for the 2011 Health 2.0 Annual Conference in San Francisco, continuing the trend of impressive growth that reflects the accelerating pace of change in medicine. More than 1,500 people attended the conference, which boasts an agenda that included 100+ live technology demos, a dizzying array of corporately sponsored keynotes, deep dives, parallel tracks, and receptions. Amazingly, all of this was preceded by a week of code-a-thons, HealthCamp San Francisco, and a four-track pre-conference workshop (Health Law 2.0, Patients 2.0, Doctors 2.0, and Employers 2.0).

The first day kicked off with a general focus on high quality, low cost and connectivity. The event began with a presentation by Health 2.0 co-founders, Matthew Holt and Indu Subaiya, who provided a summary of how much the health care and technology landscapes have changed over the past few years and how the notion of Health 2.0 fits into the current state of health care. Dr. Mark Smith, president of the California HealthCare Foundation, suggested during the keynote address that, in order to attract the interest of investors and customers, products and services should address at least one of the pain points in the health care system. Numerous startups and joint ventures demoed throughout the day, with a large focus on mobile applications and the gamification of disease prevention and management.

The second day focused on how data liquidity can improve care and reduce health care costs. Topics included mobile applications, the Quantified Self movement, health behavior change, social media-based gamification, open APIs, and the availability of federal data sets. Even more startups and joint ventures provided demos and launch announcements throughout the day. A highlight of the day was the involvement of several federal representatives who were as engaged as the conference attendees.  Leaders from ONC, including Dr. Farzad Mostashari, Lygeia Ricciardi, and Jodi Daniel, held a town hall meeting to discuss the importance and ease with which patients can now access their electronic health record (EHR) data. The day ended with a pair of significant events that focused on patient and family engagement: first, a Patients 2.0 panel that featured ONC staff fielding questions on health data access that had been generated by patients during a pre-conference workshop and then an announcement that the Society for Participatory Medicine is seeking to certify 10,000 physicians as “patient-centered providers.”

Check back tomorrow for Health 2.0 Recap, Part 2: The Pioneer Portfolio Approach.

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Project HealthDesign at AMIA 2011 Annual Symposium

Libby Dowdall, Communications Coordinator, Project HealthDesign National Program Office 

The American Medical Informatics Association (AMIA) 2011 Annual Symposium begins this weekend and runs Oct. 22-26 in Washington D.C. We congratulate BreathEasy Co-Principal Investigator Barbara Massoudi, who will receive a Leadership Award at the Symposium’s Leadership Dinner, for her success in advancing the association’s public health informatics activities.

Project HealthDesign Director Patricia Flatley Brennan will also attend the AMIA 2011 Annual Symposium. If you’ll be participating in the conference, we invite you to attend one of Dr. Brennan or Dr. Massoudi’s sessions:

Tutorial T05: Personal Health Records, Patient Portals and Consumer-Facing Health IT
Saturday, Oct. 22, 8:30 a.m. to noon
Patricia Flatley Brennan, University of Wisconsin-Madison; Jonathan Wald, Partners HealthCare System; Stephen Ross, University of Colorado Denver

Panel S60: The Role of the Clinician in a Patient Power Context
Tuesday, Oct. 25, 1:45-3:15 p.m.
Charles Safran, Warner Slack, Harvard Medical School; Patricia Flatley Brennan, University of Wisconsin–Madison; Sally Okun, PatientsLikeMe

Panel S68: The Next Informatics Agenda for Public Health
Tuesday, Oct. 25, 3:30-5 p.m.
Barbara Massoudi, RTI International

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This post was updated Oct. 24 at 9 a.m. CST.

Identifying Potential Participants from an EMR, Part 2: Now That’s More Like It!

Stephen Rothemich, M.D., M.S., BreathEasy Co-Principal Investigator and Clinical Lead

Last November I wrote (okay, whined) about the challenges to selecting a pool of potential subjects for the design phase of the BreathEasy project. At that time, the limited data in our newly implemented EMR made it necessary to use medication lists to find patients. It was both complicated (I needed an EMR data programmer to do the query) and messy (I did a lot of chart reviews to winnow a list of 271 down to 151).

What a difference a few months has made! We needed to identify a slightly different patient pool for the evaluation phase. In the interim, clinicians at our two study practices, including me, have been diligently inputting medical conditions into the EMR’s problem list. With that additional data, this time we simply looked for patients with asthma on the problem list, a prescription for an asthma controller medicine prescription in the last 12 months (a proxy for moderate to severe asthma) and residence in an urban zip code. A second advantage was that had I learned to use the EMR data query tool. As a result I could do the query myself, come up with a list of 83 patients that I was confident met our selection criteria, and avoid hours of chart reviews. After just a few days of calls, we've already recruited a quarter of the30 participants needed. If necessary, it will be simple for me to expand the pool a bit by replacing the maintenance medication criteria with a prescription for a steroid taper (used to treat asthma exacerbations, so another reasonable proxy for more than mild asthma).

This time it was actually fun. Bottom line: Better data plus a data retrieval tool I could use myself equals better results with a lot less effort.

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Pairing Text Messaging with the BreathEasy Application

Robert Furberg, MBA, Ph.D., BreathEasy Text Messaging Pilot Lead, RTI International

In the past 10 years, there’s been a huge increase in the use of cell phones (particularly smartphones); social media, including Twitter, Facebook and blogs; networking tools; and information sharing systems, including mobile geolocation applications such as Foursquare. These tools may offer new opportunities for enhancing techniques and processes for collecting health data, including participant recruitment; tracing; maintaining contact with participants in longitudinal studies; cognitive interviewing; and passive data collection.

Text messaging is one of the most popular communication methods in the world. The pervasiveness, low cost and convenience of mobile phones make Short Message Service (SMS) texting an ideal tool for disseminating health information to—as well as gathering health information from—consumers. It’s also a direct and immediate route to reach people; I tend to think of it as the most intimate form of high-tech communication.

Despite these advantages, rigorous evaluations of new technologies in health services research applications have been rare. The few SMS interventions that have been well-studied suggest that text messaging systems can effectively increase medication and appointment adherence and sustain health promotion behaviors such as smoking cessation, diabetes, asthma management and depression.

I’ve been so enamored of texting and its potential over the past couple of years that I decided to build an SMS platform for sending and receiving messages for health behavior change interventions. After reflecting on these trends and considering how we can make the BreathEasy smartphone experience more engaging, we hit on the idea of integrating SMS notifications with the application.

So that’s where we are now: devising and testing methods to tie our SQL back end from the BreathEasy application side to the SMS platform in order to generate three kinds of messages. The first type of tailored reminder prompts participants to complete diary entries and/or provide peak flow readings; the second involves health alerts related to air quality, excessive use of rescue inhalers and peak flow readings; the third type of messages are health promotion messages that address general wellness and smoking cessation.

For BreathEasy, rather than focusing on text messaging as a mode of intervention or primary collection of observations of daily living (ODLs), we decided to try using SMS as an adjunctive technology. Our SMS-adjunct (SMS-a), is intended to support the collection of ODLs; SMS-a provides participants interactive, dynamically tailored compliance reminders via a smartphone application. Beyond serving as a technical and process proof of concept, we intend to evaluate the effect of SMS-a on increasing participant satisfaction, retention and data quality.

We’re eager to get started with ODL collection and even more excited to observe how things go with this integration. We’ll be sure to update you about our experience when we go live.

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Planning for Evaluation: What to Take and What to Leave Behind

Lucia Rojas-Smith, M.P.H., Dr.P.H., BreathEasy Evaluation Lead, RTI International

Summer arrived in Maryland over the holiday weekend with searing temperatures in the 90s, high humidity and a plague of black biting flies. I don’t ever recall seeing spring leave in such a huff without so much as an “until we meet again.” My only mental escape was to begin planning for my annual retreat to Deer Isle, Maine. The escape was short-lived as I also needed to finalize the BreathEasy evaluation protocol and write this post about it before the weekend was over. It occurred to me, as I was pulling weeds in the sweltering heat, that planning for evaluation and planning for a trip are really very similar. In planning an evaluation or a trip, what you take and what you leave behind set the stage for the journey. If you’ve planned well, your chances of achieving your goal without undue stress are exponentially enhanced. If planning goes by the wayside, you may find yourself buying an overpriced pair of dress shoes (assuming you can even find a department store two hours before the wedding) or wearing running shoes with your suit and becoming the butt of family jokes for years to come.

As I pack for a trip, every single item in my suitcase is put in and taken out at least twice. Each item has to pass three criteria: 1) It must be essential; 2) It must complement at least two other outfits; 3) The amount of space it takes up must be commensurate to its utility. The criteria for selecting the final measures for the evaluation are essentially the same. All items that make the final cut must: 1) Be critical to the measuring of the process or outcome; 2) Complement other items to form a more cohesive understanding of the process or outcome; 3) Be worth the burden of collection.

Good evaluation, much like packing well, involves trade-offs, so identifying what is critical involves careful attention to a logic model and revisiting assumptions periodically. We began developing the evaluation many months ago. Over that time, we became quite attached to all the measures we selected, because each represented something important to each member of the evaluation team. It was hard giving them up! However, we now have a much clearer sense than we did at the beginning of the project of what the BreathEasy application will do and how it will be used. As we weighed the pros and cons of dropping each item, we had to ask: Do we really think BreathEasy will lead to this outcome or engage this process and, if so, why? Is it even the most important outcome or process? Without a logic model and a set of explicit selection criteria it would have been very difficult for us to make the cuts in a reasoned fashion. Even so, we may have more measures than we can collect, so the decisions become even more focused on the critical pathways to key outcomes.

Deciding what to bring and what to leave behind is largely determined by what you want to do once you reach your destination. The BreathEasy application, we hypothesize, will lead clinicians to make better – or at least more timely — treatment decisions, which will result in improved asthma-related health outcomes for their patients. The health outcome measures easily make the critical list, but as we envision how BreathEasy will be used by clinicians it becomes obvious that we have to understand how the application will impact communication and clinical workflow. If we reach the end of the journey and cannot explain why clinicians changed (or didn’t change) their treatment practices, the whole trip would be a bust.

However, capturing communication and workflow in a clinical setting or, as Co-Investigator Stephen Rothemich says, “following the bouncing ball” is a daunting task. We developed a laundry list of measures for our clinician baseline and follow-up surveys, but concluded that these items were impractical and highly imperfect methods of capturing a complex process that changes daily and from patient to patient.

So, short of following clinicians around the office with clipboards for six months, what is the alternative? The alternative is leveraging the analytics from the BreathEasy dashboard and developing a process to document communications among the nurses, doctors and patients in response to BreathEasy. The timestamp and unique user identification number allows us to readily track the frequency and duration of BreathEasy use by clinicians. More granular information is captured in a message abstraction form that nurses complete after they review the dashboard. The form is designed to track each communication to a physician or patient to its final disposition. We will be able to assess, for example, how many dashboard reviews resulted in prescription refills or calls to the patients, as well as the reasons for the calls. We’ve tried to keep the form simple, but we recognize that it may be burdensome to complete – especially if there are multiple points of communication and interaction involving the physician, nurse and patient that need to be documented.

We also recognize that the message abstraction form may overlook some key step or process. Another truism of trip planning applies here as well: some of the best moments on a trip are unplanned, and being open to the moment is as essential as a guidebook or GPS.  BreathEasy is moving into uncharted waters; we can’t possibly plan for or foresee every possible impact it will have on communication and workflow. Validating our hypotheses about these processes may be gratifying, but it’s the prospect of learning something new and unexpected that makes the trip memorable.

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Usability Testing: What We Should Have Known

Rita Sembajwe, Health Informatics Specialist, BreathEasy Project Manager, RTI International
Sarah Cook, Survey Methodologist, BreathEasy Usability Testing Lead, RTI International

We just completed usability testing for both our Android smartphone application for patients and our clinician dashboard. Overall, it was a success and we received great feedback on the look, feel and functionality of both technologies. Equally as important, we learned a lot about what we would need to consider the next time around as we recruit for and carry out usability testing sessions.

When we were recruiting for usability testing sessions, we needed to be more prepared for patient no-shows.  Usability testing is dependent on the turnout and participation of the relevant testing audience. You might think to plan for one or two no-shows, but what could you do to prepare for a 50 percent turnout rate? How could you encourage the participants to show up?

Although our patient usability testing session slots filled up quickly when we were recruiting, we had trouble getting at least half of our patients to turn up for the actual sessions. At the last minute, we managed to reschedule and interview a few, but the effort was an unexpected undertaking. In retrospect, we now recognize several factors we needed to consider:

• Our patient population may have higher odds for no-shows due to possible depression and anxiety co-morbidities that influence their behavior.
• There may be challenges with public transportation and finding the session locations.
• Participants may not understand exactly what usability testing entails.

We now realize that there are a few things we could do proactively to increase attendance rates in the future. We could:

• Follow up with participants more frequently after they agree to participate in the sessions.
• Hold sessions in the most convenient locations.
• Increase the incentives for participation.
• Identify back-up participants in case we need additional people at the last minute.

The usability testing session for the smartphone application also taught us that we must schedule time for a crash course on how to use the smartphone device prior to or at the beginning of the usability testing sessions. Such planning would ensure that the usability testing sessions focus more on testing the application and less on learning how to use a smartphone.

Finally, we believe it would benefit us to incorporate a review of the patient smartphone application into the clinician dashboard testing session, preferably toward the end. From our interactions with clinicians, it is clear that they would appreciate seeing the technology their patients would be using to submit ODL data, and that it would offer them a greater understanding of how the patient-generated data translates into feedback for them on the clinician dashboard. 

We learned many lessons — all worth consideration. We plan to prepare for all of these the next time around!