The Persuasive Health Record

By Nikolai Kirienko, UC Berkeley, Crohnology.MD Project Director

Read all Crohnology.MD blog posts

A personal health record needs to be persuasive in multiple dimensions at once: doctors need to trust it, and patients need to use it. So, as designers and researchers of systems that intend to promote health related actions, we have to master the dynamics of computers and persuasion if we want to build a truly meaningful personal health application. Thankfully, Prof. BJ Fogg, who directs the Persuasive Computing Lab on another influential Bay Area campus, has coined a term, and in fact an entire field of study to help sort it all out: Captology, or 'the study of computers as persuasive technologies'.   

According to Prof. Fogg, "We don't adopt our smartphones; we marry them." So, what does that say about the apps we use? If a health-care app doesn't want to be a casual fling, at least in my experience, it has to live up to a similar standard of domestic co-habitation: we have to want to live together. And that means seeing (and trusting) each other almost every day, and enjoying it. Suffice to say, I'm still looking for (and now trying to build) that ideal app.

As a result, in defining the core ODL's for Crohnology.MD, our team has encountered some interesting questions regarding the role of persuasion. When viewing our initial list of observations through the lens of a 'patient narrative', (the story you share about your illness) it became apparent that the names of the ODL's themselves may in fact have an unintended persuasive effect. For example, the name for a widely used observation measuring energy captures a 'Tiredness & Fatigue’ score on a scale of one through ten. I wondered what might happen to the scores (and perhaps the stories) if we framed the exact same question around ratings of 'Energy & Strength'?  

While these may seem like subtle details at first glance the persuasive tone they set shouldn't be underestimated. For those living with chronic illness our attitude and focus are often among the most powerful healing forces still under our control. In my estimation, the personal health apps that 'get' (and nurture) that relationship will in all likelihood be the ones that patients and doctors truly enjoy interacting with the most. And those are the apps we'll keep sharing our personal and professional lives with, in sickness and in health.  

What do you think? When it comes to frequent observations, how important is a name?

Preparing to Dive into Cross-Cutting Policy Issues at the September Grantee Workshop A Call for Input

By Deven McGraw, Director, Health Privacy Project, Center for Democracy & Technology

Read all Manatt and CDT blog posts

As part of our role as regulatory/assurance consultants to Project HealthDesign, my Manatt colleagues and I are looking to identify “cross-cutting policy issues” that are either currently impacting your use of observations of daily living (ODLs) to enhance patient care, or that may create obstacles to more widespread use of ODLs.  

To date, the Manatt-CDT team has focused on the privacy and security legal issues affecting the structure and implementation of each grantee’s project.  For this next phase, we want to take it up a notch and think about issues beyond just the application of HIPAA and state health privacy laws. Based on our experience in working with the grantees, as well as conversations with the Project HealthDesign National Program Office, we have created an initial list of cross-cutting policy issues that we want to discuss during our the upcoming retreat (September 8-9) in Nashville.  The list includes:

• Provider liability concerns, including those related to reliance on inaccurate or incomplete data (stemming from ODLs or otherwise) and potential malpractice liability for not accessing or using information generated by patients.
• Assuring the security of information transmitted between portable devices and other computer systems, including use of text messages by providers to communicate with patients.
• The lack of privacy and security protections for many types of Personal Health Records (e.g., those not created on behalf of a HIPAA Covered Entity) and for models of collecting ODLs that may leverage social networking websites.

Our goal is to develop strategies to prevent these issues from impeding wider adoption of ODLs into clinical practice by providers throughout the country.  But before we take another step in our preparation for Nashville, we want to make sure that this list is the right list – that these are the policy issues that are “keeping you up at night,” (or at least nagging in the back of your mind).  Please jump in with comments below - feel free to send us your laundry list of favorite policy concerns.  We look forward to seeing you in Nashville.

In Assimilating ODL Data Personal Experience Plus an Open Mind Equals More Effectiveness

By Sheba George, Charles Drew University, FitBaby Medical Sociologist.

We are fortunate to have a lot of diversity on our team for the FitBaby project – from our academic disciplines to our cultural backgrounds, personal lives and responsibilities for children.

The parents on our team, including me, try to bring not only our professional expertise but also our own life experiences to bear on the problems we are tackling. For me, going home from the hospital with a healthy baby was nerve racking and exhausting. It’s hard for me to even imagine the added worry about your child’s health and whether you are doing the right thing as the parents of high risk infants. Evidence from the literature and from our work indicates that these challenges can be even greater for parents from lower socioeconomic and educational backgrounds who may have limited resources.

My instinct as a parent was that parents/caregivers would appreciate features that give a) immediate feedback on the health status of their babies based on input of current data; b) alerts to indicate that immediate attention is needed for their child; and c) guidelines on what they can do at home to address potential problems. Parents in our studies have also wanted to know if their children are “okay” and be alerted if they might not be. What surprised me though were the differences we saw between my instincts and what the parents we interviewed have said. While I am not alone in wanting instant feedback on my children, the participants in our studies have been more focused on social support and sharing information about their infants than on seeing the details of daily life. These kinds of differences remind us how important it is to take in multiple perspectives and remember we aren’t designing for ourselves.

We had not consciously chosen to have parents on the team but for me, as a social scientist, my status as a parent has become important in my own thinking about this project. My recent memories of parental zombiehood kick in to remind me of the importance of making sure that the functionalities we build into the system are going to meet the needs and motivate use by the likely exhausted parents. We are learning, as a team, that leveraging our diversity and being consciously reflexive about our different perspectives helps us collect and interpret ODL data, as well as build our system more effectively.

Watch us while we work – and see a PHR mosaic form right before your eyes!

By Patricia Flatley Brennan, Director, Project HealthDesign.

Mosaics are an art form in which images are created by juxtaposing small bits of stone or colored glass in alignment. Viewed from too close a perspective, one sees only bits of color separated by grout. Move back and a beautiful image emerges. Every single stone or piece of colored glass plays in important role in creating the image.

Mosaics provide a useful metaphor for characterizing the work of Project HealthDesign as seen through the eyes of our bloggers. Nine months into this round of Project HealthDesign seems to be the right distance to gaze back at the mosaic of our blog –the image created by the 54 posts from our grantees, advisory committee members, legal and technical consultants, students and program office staff is exciting and promising.

Most people read blogs sequentially, following a line of reasoning initiated by one person and developing over time. We at Project HealthDesign took a different path to blogging, one that more aptly captures the myriad visions, experiences, and technologies that now make up the ecosystem of our program. Some of the postings provide an update on the status of a project; others call out for help with a particular technical issue.  Still others represent the impulsive musing of the NPO director (me!) on the state of patient-facing HIT - where it is, where I’d like it to be, and how to get there.  Our approach challenges the reader to look at each post not as an isolated but beautiful piece of glass, but as a part of an emerging larger whole image.

Our blog presents Project HealthDesign as a mosaic of experiences, insights, and opinions about PHRs, ODLs, technology and tools – there may be other, more efficient ways to understand PHRs, but certainly there is none more enjoyable.

Using technology and health coaches to motivate youth

Holly Logan, iN Touch Graduate Research Assistant, San Francisco State University.

Read all iN Touch blog posts.

Over the past month I have been researching the use of mobile technology in the health care process and the role of a health coach as someone to help patients manage their conditions.

Motivational and reminder text messages are a focus of a lot of the literature. Studies have used text messages to encourage individuals to get HIV testing in developing countries, to remind individuals with chronic conditions to take their medicine, or to remind people to eat their fruits and vegetables and to get motivated and physical. Although these studies have supported the idea that text messages work to help motivate individuals to achieve their goals, there is very little research about using text messages specifically with youth. It is important to remember our audience and think about what text messages would actually be considered useful by the youth. For instance, would the youth find a message telling them to eat carrots instead of candy compelling, silly, or annoying?

The health coaches that our project will utilize will also be trying to find the balance of what language is motivational. They must be able to discuss with a patient what will help them, but also be sure not to tell a patient what they must do. Developing a relationship in which the youth feel comfortable enough to discuss concerns and challenges is key.

The literature in our two areas of interest is fairly limited.  But the studies that have been done using mobile technology or use of a health coach have revealed to me all of the exciting and useful things that are changing in health care to put the control into the hands of the patient. 

They can’t do it alone – ONC needs everyone’s input!

By Patricia Flatley Brennan, Director, Project HealthDesign.

It’s no secret to anyone in the HIT field that meaningful use is an important concept.  We at Project HealthDesign want to make meaningful use really useful for patients – and now ONC has given us the opportunity to help shape the objectives and measures for Stages 2 (2013) and 3 (2015).

Let’s look first at the goals of Stage 2 and Stage 3. 

• By 2013, meaningful use of HIT should guide and support care processes and care coordination.
• By 2015 meaningful use of HIT should yield measurable improvements in quality, safety and outcome of care processes (including enhanced quality measures and extensive decision support) at the individual and population level and enriched tools for patient self -management. 

CMS proposes new rule making in these areas over the next year, and our voices need to be heard!

We start by listening to what we’ve been told by lay people who have participated in Project HealthDesign activities to date. 

• Make sure my doctor knows about and has access to my data.
• Make sure my data are secure, but don’t overdo the privacy lock up. 
• Use technologies that reduce the burden on me to remember to collect data, and help my doctor and I see patterns in the data I collect.
• ABOVE ALL: Let me tell my doctor what is important to me, in my words, and help me in reporting what my doctor wants to know.

We’ve also been listening to the physicians, nurses, public health workers and other clinicians tell us that they want to better understand their patient’s story.

• Don’t just dump a lot of data on me.
• Make sure I can practice in a legally safe manner, and not worry that some little bit of critical information is hidden in some computer file that I need to wade through. 
• ABOVE ALL: Let me understand what is important to the patient and how I can enlist them in being an active participant in their care.

The techies have also weighed in.

• They are ready with solutions, like sensors and networks, but want to be sure there is a market for software and a protection from liability. 
• Distributed computing, apps and clouds may finally be robust enough for health care – but we’re not sure they can really scale.
• ABOVE ALL: Give us clear standards that we can build to and insure that our products, solutions and apps can be certified.

We need your help to make sense out of all of this noise, so that we can tell ONC how to make meaningful use really useful for patients.  What priorities would you set? What can’t wait, and must be included as core objective criteria for Stage 2. What can wait for Stage 3? ABOVE ALL, how can Stage 2 build on the experience unfolding under Stage 1 efforts, and set the stage (so to speak!) for Stage 3?

Weigh in on a few objectives listed below – a simple, “yes, I’m with you,” or “No, don’t waste our time,” will be enough to get us started in looking at these possible specific recommendations.

1. Provide clinical decision at the point of care (including the home) for diabetes management
2. Standardize bar coding on the packaging of dispensed medication so that patients can use scanners for medication reconciliation and administration.
3. Using acceptable identity management and data security protocols, upload calibrated data in a standard format for weight, blood pressure and blood glucose from home monitoring devices to third party platforms.
4. Require all cell phones whose owners have registered them to receive public health alerts
5. Create a generalized data structure to receive automatically captured or self-report information about activity (exercise, sleep, walking, restfulness), at an individually-determined frequency
6. YOUR IDEAS HERE!

Soon I’ll be back with you to pose a new set of objectives and criteria.

Reformation or Revolution? ODLs in the medical record: from patient narrative to patient safety

By Nikolai Kirienko, University of California, Berkeley, Crohnology.MD Project Director

Read all Crohonology.MD blog posts

“History is a guide to navigation in perilous times.  History is who we are, and why we are the way we are.”

David C. McCullough vividly brought this to life in his chronicles of the American Revolution. I’m moved by the significance of these words in the context of yet another great American saga.  It’s one whose story is still being written, and upon which the future health and prosperity of our country now depends -- our definition of the meaningful use of health care IT.

As we unleash an unprecedented national effort to reform our ailing health care system, like a patient navigating in perilous times, we should look to our medical history for guidance on who we are, and why we are the way we are.  In this history of health care reform, just a few of us can be providers, but everyone is a patient.  And patients have stories to tell, too.

Yet, if history really is written by the victors, perhaps now is a good time to stop and ask: in our current system of keeping medical records, one upon which the nation has embarked on a $27 billion quest to modernize over the next five years, who will write the history?

Over the last 10 years, despite logging well over a year in the hospital, I have only read my chart a handful of times.  In each of these instances, it was only because the chart was literally placed in my lap while I sat in a wheelchair, waiting for a CT Scan.  And each and every time, I have been surprised, and occasionally shocked by what I read. 

In short, my journey as a patient has too often been shaped not by my own methodical input, but by a game of telephone, through which a group of relative strangers author a narrative about my life. As the patient, I am neither the author nor the reader by design.

I’ve met and lost young friends in the hospital due to preventable error, and all of these tragic experiences have hardened me into an unapologetic advocate for patient safety, a movement perpetually defined by its challenges to the status quo.  As such, I have no doubt that ODL's in an open medical record would have prevented many of the scars I bear today. 

In our definitions of meaningful use for technology fueled health care reform, it would be a mistake to merely build a more efficient electronic billing machine that only makes our system faster at its flaws. 

Rather, we should embrace this as the once in a lifetime opportunity it is to re-imagine, re-engineer, and re-create a unified, patient-centered digital work flow. One built around collaborative clinical documents with structured, patient defined, and clinically useful input flowing in and out of the medical record. In other words, hospitals need to open the door to well researched ODL’s, as a matter of patient safety.

But first, we need to open the medical history. We need to make it accessible to the individual patient. In this reform, 'We, the people', are all patients.  And the goal of these reforms should be to give us all a hand with which to help write our own medical history. That would be a revolution.

This is a task of monumental proportions.  Thankfully, I see a bright future; one in which the pioneering ideas behind Project OpenNotes and Project HealthDesign can combine into a single, patient-centered record, obscuring the distinctions we once made between an EMR and a PHR.  This is the beginning of a history I can’t wait to experience. 

What do you want from meaningful use: revolution or reform?  Add your thoughts to the record, in the comments below!  

Collecting information: Automated vs. Manual

By Anind K. Dey, Carnegie Mellon University, Embedded Assessment Principal Investigator

Read all Embedded Assessment blog posts.

Through our work in personal informatics we have learned lessons about the collection of information. Collection often means not only collecting information about the activity you care about, but also on other related contexts or activities, to help you make sense of the primary information. For example, seeing a log of how much you sleep would make more sense if it were overlaid with information about how much work you had to do or your travel schedule.

We have found through an investigation of a series of tools to help promote physical activity, that there is a real trade off between the degree of automation in collection and the value of that collection. Too little automation can create a burden on the person collecting the information, however, too much automation can be harmful as well. Manual collection of information means the collector is focusing on the data (whenever collection occurs) and has the opportunity for short reflections, and can keep abreast of the data more easily. We have found that completely automating collection removes these opportunities and can actually hinder individuals in keeping track of and making sense of their data.

Investigation of Personal Infomatics and ODLs

By Anind K. Dey, Carnegie Mellon University, Embedded Assessment Principal Investigator

Read all Embedded Assessment blog posts.

In my research group, we are studying a field called personal informatics, in which individuals collect information about themselves, similar to the concept of observations of daily living. Some of the questions we have been investigating overlap with our study of ODLs as part of Project HealthDesign.

For example, one theme is the motivation for collection and then subsequently what people do with the information they collect. Is it to compare their current behavior to past behavior, understand their current behavior (e.g., in reference to some goal they've set), or simply because it makes them "feel good"? There is evidence, for example, that just writing down how much you weigh every day is correlated with losing more weight.

Once people have collected the information and, for some, made an attempt to understand it, what do they do? Again, it seems people fall into three categories: make no change, attempt to change their behavior (including goal setting, hypothesis testing), or have a conversation with others to discuss and understand further. All of this is true for how we expect people to use and how we have seen people use ODLs, as well. It seems like we could learn more from how people collect and use information outside of ODLs to gauge how they will make use of ODLs, even in a clinical context.

To better understand personal informatics tools and systems and how they support collection and reflection, we constructed a model that helps to compare and evaluate different tools. The model has five stages: preparing for data collection (figuring out what should be collected), collecting the data, integrating multiple sources of data together, reflecting on that data, and taking action based on that data. I won't dive into the details of the model here, but we have found it to be very useful, and I believe it will be useful for assessing systems that collect and support reflection on ODLs as well.

The goals for our work on Project HealthDesign line up quite well with our goals for personal informatics. In Project HealthDesign, we are supporting the collection of ODLs to support exploration and meaning-making, to reveal changes in behavior that will spur conversation between the collectors, loved ones and clinicians, and possibly promote behavior change. In personal informatics, we are working towards a tool that will assist with all five stages of the model from preparation to action and iteration between those stages, including goal setting, hypothesis testing, collaboration amongst interested people, and motivational tools. It seems there is a lot of overlap between the two, and we hope to report more on this in the near future.