Patient Attitudes About Sharing Patient-generated Data with Health Care Providers

Matthew Lee, dwellSense Lead Researcher, Ph.D. Student in Human-Computer Interaction, Carnegie Mellon University

In our evaluation of dwellSense, each study participant had a different primary care provider. We wanted to engage with each one of these physicians to identify how they would use the patient-generated data about medication taking, phone use, and coffee making. Unlike many of the other current Project HealthDesign teams that had one or two clinicians on their team who provided direct care for the participants, we had to reach out to the clinicians who were in our participants’ existing care networks.

The first step was convincing participants to allow us to speak to their health care providers (PCPs, specialists, nurses, therapists, etc.). Because they felt the data we were collecting about their observations of daily living were valuable for their doctors to have, it wasn't a stretch for them to give us permission. Our patients generally had very trusting and positive relationships with their health care providers. From this experience, we expect that a technological solution or service that shares data about ODLs or activities of daily living (ADLs) with clinicians would not normally be met with much opposition.

However, participants were a little tentative when we asked them to sign a release form authorizing their health care providers to speak to us, the research team members, about their medical conditions when we evaluated how care providers utilized the data about ODLs in their workflow. At this point, we reassured them that the point of the study wasn't to dig up all the details of their medical history from their care providers, but rather to give permission to the care providers to bring up any details that were relevant for evaluating the usefulness of patient-generated data in their workflow. All participants trusted us to keep matters confidential, as we were bound by university IRB confidentiality rules. Furthermore, all participants were open in sharing the details of their medical history and conditions with us as part of the study, so it was unlikely we would discover any secrets when speaking with their care providers.

Extrapolating from our experiences and applying it to how a third-party technology or service might share patient-generated data and collect medical details from the health care provider, we envision that these systems should limit the additional information they collect from health care providers, or at least allow the patient to control what information their health care providers can disclose to the system. Integrating patient-generated data about ODLs and ADLs directly into EHRs may work around this issue, but the patient-generated data, visualizations, and analytics may still reside with a third-party. Any information about how the patient-generated data are used or accessed by the care provider may reveal sensitive patient information. Thus, we are learning that the information flows among patients, care providers, and third-party services should be an important part of designing a useable system for sharing and using patient-generated data about ODLs and ADLs.

Learn more about the dwellSense project.
Read more posts from the dwellSense team.

If I’d Only Known Then What I Know Now (A Letter to Myself)

Katherine Kim, M.P.H., MBA, iN Touch Principal Investigator, San Francisco State University

Dear Kathy,

Three years from now you are going to be finishing the iN Touch project. You’ll have done some things well, made plenty of mistakes, and learned so much. I’m writing this letter to share some of those lessons.

1. You and Christina made the right decision to apply for the Project HealthDesign grant, even though you were worried because those grants from the Robert Wood Johnson Foundation are so competitive.


2. When you start hitting road bumps, lean on your team. Christina, Hali, Judy, Cam-tu, Holly, Ed, Janelle, and Yulia will amaze you with their creativity, optimism, gumption and all-around smarts.


3. The IRB approval process will take twice as long as you expect. The phased IRB that Barbara Massoudi suggests will be the way to go. Submit the application design and testing IRB right away, then work on the intervention IRB which will probably undergo some changes based on the testing. Just-in-time IRB will not be soon enough.


4. Recruitment will take twice as long as you expect. Prototype your recruitment process with the clinicians and staff. Don’t be discouraged by the disconnected phone numbers and no-shows. Remember that life is complicated and messy for the patients. Start recruiting as early as possible.


5. Over-recruit. I just said life is complicated and messy for patients. Even if they want to finish the study, a third of them won’t be able to. Don’t feel bad, this is typical for health and lifestyle studies and those studies with younger and minority participants have even higher dropout rates. You’ll need to recruit more to compensate.


6. Developing attractive, useful reports of ODL data will be harder than you expect. The clinicians won’t know exactly what they want so you’ll have to start out with a mock-up. Recruit a visualization/design expert next time.  Oh yeah, the hospital, clinic, and school will all be on different browsers and versions and they won’t want to update just for you. So make sure to test the reports on multiple browsers.


7. Use multiple communication modes for reminders and scheduling. Paper notes still work!  Deliver them to the classroom to remind youths to come to their appointments. Some of them will want reminders to record ODLs through their iPod Touches, others via text messages to their phones. Forget about email – they never check email.


8. Be ready to educate and evangelize. Hospital, clinic, and school staff members haven’t heard of observations of daily living (ODLs) before and they’re not sure how they feel about mobile technology. You are not just asking them to partner with you on a project, you are asking them to change how they work and engage with patients.


9. The youths who participate in the study will amaze you. They are motivated and excited to use the technology and new strategies to meet their health goals. They’ll teach you a lot about improving health behaviors.

Have a great time with the iN Touch project.

Kathy

Balancing Patients’ and Clinicians’ Needs [Video]

Libby Dowdall, Communications Coordinator, Project HealthDesign National Program Office

 

iN Touch Co-Principal Investigator Katherine Kim, M.P.H, MBA, talks about some of the challenges her team has faced as they’ve implemented their study. These challenges include:

Balancing patients’ and clinicians’ needs when developing PHR applications and dashboards.
Participants in the iN Touch study say they want to review their ODL data on a daily basis to they can reflect on the patterns and make changes as needed. However, clinicians say they want to see summary reports of the ODL data on a weekly or monthly basis and before their patients come in for visits.

Integrating patient-generated ODL data into clinical electronic health record (EHR) systems.
Clinicians aren’t likely to visit an additional portal or external system to review patient-sourced ODL data; the data must be integrated into existing clinical EHR systems and workflows. However, Meaningful Use requirements have prompted extensive changes to many hospital EHR systems. Because of these changes, hospital IT departments are currently less available to help with ODL data integration.

Learn more about iN Touch.
Read posts from the iN Touch team.

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.

Learn more about BreathEasy.
Read more posts from the BreathEasy team.

ODL Prescriptions and Patient Data Capture - Is Provider Liability an Issue?

Deryk Van Brunt, Dr.P.H., Chronology.MD Principal Investigator, University of California, Berkeley, Healthy Communities Foundation
Kathleen Morrison, M.P.H., Chronology.MD Project Manager, Healthy Communities Foundation

We live in a country where the American Trial Lawyer’s Association is one of the biggest contributors to political campaigns — to whichever party is in office. Although several attempts at federal legislative overhaul of our medical malpractice system have been introduced in the last 25 years, none has succeeded. The threat of medical malpractice lawsuits can influence the way providers practice medicine. One consequence is the practice of “defensive medicine,” which often results in more expensive care — including unnecessary tests and procedures, as well as recommended protocols. Although attempts have been made to reduce the fear and threat of malpractice liability in the medical profession (e.g., clinical guidelines, best practices, etc.), the reality is that this threat remains quite salient for many providers.

It should come as no surprise, therefore, that liability was a significant concern in the early phases of the design of our technology. On Pioneering Ideas, Steve Downs recently mentioned the Crohnology.MD ODL Prescription (read his post). The concept of the ODL Prescription, put forward here by Dan Bernstein, Nikolai Kirienko, Deryk Van Brunt and Kathleen Morrison, was developed out of a collaboration between iMedic8 and the Healthy Communities Foundation and has been embraced by the Crohnology.MD team.

The ODL Prescription is an agreement between patients and providers that details which biometrics and observations of daily living (ODLs) will be captured between visits. An ODL Prescription is the outcome of a patient/provider negotiation and represents a balance between collecting what’s important to both parties while also considering what’s most relevant in managing the patient's health. The ODL Prescription identifies which ODLs the patient will track and designates how often and when they will be collected. This patient ODL data will be captured and viewable by the patient, and it will then be shared with the provider during the next clinical appointment.

Some members of our team were concerned about the liability risk to our participating providers. For example, is it possible that once a patient logs ODL data, then the provider could be liable if a negative outcome were to result? And what if clues in the patient’s ODL data had pointed toward the negative result?

Our clinical partner, Dr. Jonathan Terdiman, quickly put the liability fears to rest. From his perspective, the ODL information that would be shared at the time of the clinical visit does not represent new information beyond what was previously being discussed; the information is just being captured and shared more thoroughly and reliably. Because the ODL data will only be shared with the clinician at the time of the clinical visit, this data is, in effect, no different from any other information a patient discusses with his or her provider at the time of the clinical appointment. The key element is that initially the system will not even allow the physician to retrieve and see the data between visits. This data workflow will be reinforced once we make our clinicians and patients aware of this protocol. Because there is an understanding that the data will not be shared between appointments, nor reviewed by the clinicians outside of the appointments, we see the ODL data as a visually enhanced — and perhaps more comprehensive — patient narrative.

This approach does, however, raise questions for future versions of our system — and other systems — as we consider sharing the ODL data in real time. Certainly, if a patient’s ODLs indicate that a situation is urgent and requires immediate clinical attention, then that data could be used to inform the clinician of the situation and to instruct the patient to seek treatment immediately. In such a case, would the clinical team be held responsible and liable if they do not act upon this data? The answer will likely relate to the expectations established and agreements made between the patient and his or her care team.

In the meantime, the ODL Prescription will allow our Chronology.MD patients to collect data that may be both clinically and personally significant, allowing us to evaluate whether the information positively impacts the efficiency and value of the patient narrative.

Learn more about the Chronology.MD project.
Read more posts from the Chronology.MD team.

Project HealthDesign Workshop and Emerging ODL Themes

Libby Dowdall, Communications Coordinator, Project HealthDesign National Program Office

We routinely hold workshops that allow the five Project HealthDesign teams, the national program office and other project advisers to meet in person. At a recent workshop at the Vanderbilt Center for Better Health, we focused on the evaluation phase of the project.

 

During the workshop, we identified several themes that resonate across the five teams:

Patients and clinicians have different perspectives on which ODLs are important.
The observations of daily living (ODLs) that are crucial to a particular patient’s daily life and health may not seem as important to his or her clinician. Or, a patient may grow tired of collecting data about an ODL that the clinician finds important. In “Whose ODLs Are They Anyway?” on Pioneering Ideas, Steve Downs, chief technology and information officer at Robert Wood Johnson Foundation, further examines this difference in perspective, and also details the Crohnology.MD team’s innovative approach to negotiating common ground between the two perspectives.

Patients may want flexibility in how they use ODLs.
Because the projects are breaking new ground as they look to see whether and how ODLs enter the clinical decision-making process, several teams left a measure of flexibility for patient preference. They recognized that even though patient and clinician focus groups helped to choose and prioritize the ODLs tracked in each study, each individual patient might value another ODL that is not part of the study’s standard ODL set. The iN Touch team, for example, allows participants to choose an extra function in The Carrot platform that they’re interested in tracking. Additionally, each participant in the BreathEasy study will be able to use a journal feature to write narratives pertaining to the ODLs that matter to him or her.

Clinical workflow varies by team, but several use “intermediaries” to review ODL data.
The five project teams were chosen, in part, for the various types of clinical partners with which they work. Thus, it is no surprise that each project team has taken a different approach to incorporating ODLs into the clinical workflow. We were intrigued, however, to see that several teams are using an “intermediary,” such as a health coach or nurse, to routinely analyze the ODL data and act upon the findings.

 

Our teams are beginning to recruit (and even enroll) patients for the evaluation phase of their projects. We’re excited to think that data is already being collected from sensors in several elders’ apartments as they use the phone, and dozens of overweight teens are meeting regularly with their health coaches and collecting ODLs. Rest assured that the teams will soon be sharing new developments as their studies progress!

BreathEasy Clinician Proposes New Model for Patient-centered Health Information Systems

Barbara L. Massoudi, Research Triangle Institute, BreathEasy Principal Investigator

Alex Krist, MD, MPH, a member of the BreathEasy team from the Virginia Commonwealth University Department of Family Medicine, recently published a commentary in the Journal of the American Medical Association (JAMA), “A Vision for Patient-Centered Health Information Systems” (JAMA, Jan. 19, 2011, Vol 305, No.3). In the commentary, he discusses the current state of patient-centered health information technology and proposes a model for a patient-centered health information system based on five levels of functionality (see graphic). 

Upon reading the commentary, I started to think about which level of functionality the BreathEasy project falls into, or for that matter, which level any one of the Project HealthDesign projects would fall into. The highest level of functionality is designed to help patients take action — certainly something that fits well with the Project HealthDesign focus on observations of daily living (ODLs) and putting “tools” into patients’ hands. In describing this level of functionality, Dr. Krist says “Trust comes when the personal health record has the endorsement of the physician and is designed to seamlessly interface with care delivery, as when output is shared and the personal health record refers patients back to their physician for assistance or helps them prepare for upcoming office visits.” This is certainly the goal of most, if not all, of our projects.

Dr. Krist goes on to describe some of the challenges related to building systems that function at the highest level, including programming to personalize messages, cultural competency and integration with clinical workflow. These are all issues we’ve considered at length while working on the BreathEasy project. We’ll be conducting lab-based usability testing of our BreathEasy application with both patients and clinicians in the next couple of months, so we’ll soon see how we’re doing.

Learn about BreathEasy.
Read more posts from the BreathEasy project team.

Image: JAMA

Oodles of ODLs

Katherine Kim, San Francisco State University, iN Touch Principal Investigator

In early October, I attended San Francisco’s Health Innovation Week (http://healthinnovationweek.com/) – an annual, week-long “immersion in the world of health and technology innovation” event that combines forums on HIPAA (privacy and security), regional extension centers/health information exchange, electronic health records, HealthCampSFBay and Health 2.0.

As I immersed myself in the HIPAA Forum, I considered how much we still needed to know about ODLs and how to handle them (these questions were keeping me up at night). I realized that we ask our iN Touch participants to record ODLs so that they are more mindful of their actions, able to analyze their decisions, and can improve the collaboration with their care team. Those same prompts would be helpful when it came to the questions swirling in my mind so I came up with these ODLs as I travelled through the sessions.

• Privacy ODLs: Podls (poodles) Oct 4, 2010, 1:30 pm

DHHS Office for Civil Rights is holding consumer “listening” sessions to hear their concerns about HIPAA privacy. I wonder how much concern consumers have about privacy of personal health records. Wish I could attend.

• Regulation ODLs: Rodls (Roodles) Oct 5, 2010, 6:45 am

FDA may regulate mobile devices and health decision making software as medical devices.  Will that include programs like iN Touch?

• Mobile ODLs: Modls (moodles) Oct 5, 2010, 11:00 am

DHHS Office of Minority Health says mobile applications are widely used (PDAs, text messaging) by minorities, an effective approach internationally.

Check out National Health IT (NHIT) Collaborative for the Underserved http://www.shireinc.org/nhit/

• Security ODLs: Scodls (pronounced scoodles) Oct 5, 2010, 2:15 pm

Security for social media for healthcare. Texting, email, social networking, health information exchange. Consumers are way ahead of the healthcare industry. We need to catch up and still be secure.

• Safety ODLs: Safodls (safeoodles) Oct 5, 2010, 7:39 pm

In the news - cell phones may cause brain damage? Good thing we are using iPod Touch, it’s not held near the head. Will patients or their parents/guardians be concerned about this for our project?

• To Do List ODLs: ToDodls (Todoodles)

Write a blog about the Project HealthDesign ODLs and ask “Track one of these ODLs for a few days and send me your findings.”

Maybe we should start using these terms more throughout our project because some of the names are sure catchy. Feel free to start using of these ODLs and send us your findings.

Participatory Medicine @ UCSF: Off the Whiteboard and onto the Smartphone

By Nikolai Kirienko, UC Berkeley

As a patient at UCSF, I’ve witnessed bedside technology evolve at a rapid pace over the years. From nurses capturing vitals on tablet computers, to patients escaping through 50-inch HDTVs, high tech surfaces are helping us connect and accomplish our age-old goals in very modern ways.

Yet, during a recent admission, the interactive surface that most captured my attention was an upgrade to a decidedly low power device: the patient whiteboard. 

As strange as it may sound, this was the most engaging piece of technology in my hospital room: it was a collaborative medium for asking questions, coordinating specialist teams, mapping out treatment options and otherwise sequencing the series of events leading up to the most important day of my hospitalization: my planned date of discharge.

Dr. Niraj Sehgal, a product champion for the newly revamped whiteboards recently wrote in the Journal of Hospital Medicine, “Patient whiteboards can serve as a communication tool between hospital providers and as a mechanism to engage patients in their care, but little is known about their current use or best practices.” 

In my experience, I witnessed the whiteboards performing the function of ‘random access memory’ within our group collaboration process; a kind of short-term, shared memory vital to executing a task. It made sure that everyone was looking at the same information at the same time, much as we hope to accomplish with the design of Crohnology.MD.

So, perhaps the wisdom the whiteboards can offer us as designers of personal health care applications is an illustration of participatory medicine as best defined by patient engagement, which does not always require the latest in technology to be effective. For example, in preliminary user tests we've found that SMS can engage as well as or even better than a native app for capturing certain ODLs.

Ultimately, the whiteboards at UCSF, and the culture of patient participation they represent, are steadily paving the way for all the advanced bedside collaboration technologies destined to take their place. And even if people and their processes evolve slowly, when it comes to putting the patient in the driver’s seat, sometimes the right technology is just a surface to write on. In the meantime, I'll be snapping pictures on my smartphone- until we finish a smarter dashboard. 

Action Research: A cyclical intensity for sustainable social change

By Gillian Hayes, University of California, Irvine, FitBaby Principal Investigator.

Read all FitBaby blog posts.

“The best way to understand something is to try to change it.” – Kurt Lewin

My research projects tend to focus on the creation of local,
sustainable, social change.  To me, it is impossible to develop
feasible solutions to real problems without intense, and sometimes
very messy, engagement with the people and problems that lie at the
heart of these projects.  Action Research (AR) offers a systematic
collaborative approach to research that satisfies both the need for
scientific rigor and promotion of sustainable social change.

AR is explicitly democratic, collaborative, and interdisciplinary.
The focus when conducting AR is to create research efforts “with”
people experiencing real problems in their everyday lives not “for,”
“about,” or “focused on” them.  AR is cyclical in nature, with an
emphasis on problem formulation, design of an intervention, action,
observation of the effects of the action, reflection, and then
redefinition of the problem to start the cycle again. The goal is not
to arrive at the solution but to attempt to create a solution that is
in some way “better” than previous solutions and helps the actors to
learn through the action they take.

 The steps we take in my lab usually fit the model for AR:

(1)    Find a community partner. We always try to remember, we are
research facilitators and partners not observers outside the realities
of the situation.
(2)    Develop problem statements and research questions together with
community partners.
(3)    Design sociotechnical interventions with our community partners
not for them.
(4)    Evaluate our interventions while considering outcomes that are
important to community stakeholders and to our research team.
(5)    Write with our community partners…. Not just by adding their
names to our papers or getting casual feedback, but really writing
together.
(6)    Celebrate the things that have gone well regularly.
(7)    When we leave, make sure we created sustainable change, which
means they don’t need us anymore.
(8)    Act ethically, which for AR means ensuring community partners
have a lot of power as both participants in the research and
co-creators of the research design.