Reflections on the AMIA 2011 Symposium

Kathy Johnson, R.N., M.S., Project HealthDesign Ph.D. Candidate in Nursing, University of Wisconsin-Madison

The American Medical Informatics Association (AMIA) recently held its fall symposium in Washington, D.C. This was the fifth symposium I’ve attended as a nursing doctoral student. The past five years have seen significant changes in symposium foci. This year, meaningful use, the amazing power of Watson, and the impending volume of patient-sourced data were major topics. In fact, during his keynote address, NIH Director Frances Collins, M.D., Ph.D., noted that the amount of data coming from patients directly will soon far outweigh clinically generated data. This year, it was very clear to me that this expanding horizon of patient-sourced data brings new opportunities for nurses and greater recognition of their role in patient care.

Seasoned nurses will remember “SOAP” charting:  documentation of the subjective (S-patient reports and complaints), objective (O – clinical measurements at time of presentation) elements of the patient’s presentation, followed by a nursing assessment (A) and plan (P).  Nursing informaticists have developed standard nursing terminologies and languages and demonstrated their key role in telehealth. Today’s technologies, particularly mobile health applications and their integration with a patient’s health and health care, demonstrate that there is a key role for nurses in this frontier.

Nurses know that the patient experience of health and illness that occurs outside of the clinical visit is essential to understanding the patient. In the past, documenting the patient reports, the “S”, has been limited by what our medical knowledge tries to read into a patient subjective report. The current Project HealthDesign teams’ work expands both what subjective experiences are (S) and how they can be measured (O). The inclusion of patient-sourced data into the EHR or, at minimum, clinical conversation, validates the patient’s participation in their care.

In my view, over the past five years, the AMIA symposiums have showcased an amazingly fast progression of technology and computing power. These advancements have moved from biomedical ontologies, imaging capabilities, and genomic mapping to solid advancements that have a tangible influence on the way patients can manage their own health.

Connect with Project HealthDesign at Health 2.0

Libby Dowdall, Communications Coordinator, Project HealthDesign National Program Office

The Robert Wood Johnson Foundation’s Pioneer portfolio, which supports bold ideas that could transform health and health care, has invited a diverse group of grantees and friends to participate in next week’s Health 2.0 Conference in San Francisco.

We’re sending members from each of our five current Project HealthDesign teams, as well as several members of our National Advisory Committee, to engage in conversations with other health innovators. We can’t wait to connect with the other Pioneer portfolio attendees, including inspiring researchers from Open mHealth and avant-garde self-experimenters from Quantified Self. If you’ll be attending the conference, keep an eye out for our group, and be sure to introduce yourself!

In the meantime, visit Pioneering Ideas and help us get the conversation started by sharing your thoughts on the following questions:

1. What are the most important challenges to address in order to get more people collecting their own health data and information?
   
   
2. What are the most important hurdles to overcome in order for patients to bring this information to their doctors and for it to inform clinical care? 
   
   
3. Of all the things you can track, what is the one piece of patient-generated data that has the most potential value to both personal health and clinical care?

We look forward to hearing your input and hope these questions will help generate meaningful conversation during—and after—Health 2.0.

Share your answers by commenting on the Pioneering Ideas blog.

Progress Made on Direct Patient Access to Lab Results

Robert Belfort, Project HealthDesign Regulatory and Assurance Advisory Group, Manatt, Phelps & Phillips, LLP

The federal government recently took an important step to advance its goal of enabling individuals to play a more active role in their health care. On September 12, 2011, the U.S. Department of Health and Human Services (HHS) released a proposed regulation that would amend the Clinical Laboratory Improvement Amendments of 1988 (CLIA) regulations and the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule to allow individuals to gain access to lab test results directly from laboratories. Although individuals could always get their lab test results from their doctor’s office, the potential for health information technology tools to facilitate broader exchange of information and the growing interest of individuals in being more active participants in their care appears to have driven HHS to propose the change.

Why Can’t Individuals Access Their Lab Test Results Directly From Labs Right Now?

Most clinical laboratories are regulated under the CLIA regulations, which provide that labs may only release test results to specified recipients, including “individuals authorized under state law to order or receive tests” and to “the individual responsible for using the test results and the laboratory that initially requested the test.” CLIA does not define “individuals responsible for using the test results.” So to whom labs can disclose test results usually depends on what state law says about who is authorized to order or receive tests. Only a few states place patients in that category. Further, HIPAA exempts the provision of clinical lab results by labs from provisions generally requiring health care providers to give patients access to their medical information.

How Would the Proposed Rule Fix the Problem?

The fix to this problem is surprisingly simple — at least as legal and regulatory changes go. HHS is proposing to add a new section to the CLIA regulations to specify that, upon an individual’s request, the laboratory may provide the individual with access to his or her completed lab test results that, using the laboratory’s authentication processes, can be identified as belonging to that individual. At the same time, HHS would remove the exceptions in the HIPAA Privacy Rule that exempt lab test results from the information that laboratories must provide to individuals upon request. If adopted, the proposed changes to the HIPAA Privacy Rule would preempt any contradictory state laws that prohibit a HIPAA-covered laboratory from directly providing access to an individual.

Rationale for Providing Individuals with Direct Access to Lab Test Results

Lab test results are critical to an individual’s efforts to take control over his or her health care. Today, however, lab test results rarely make it to individuals. A 2009 study published in the Archives of Internal Medicine indicated that health care providers failed to notify patients (or document notification) of abnormal test results more than 7 percent of the time. The National Coordinator for Health IT recently put the figure closer to 20 percent.

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Consumer groups like the National Partnership for Women and Families are lining up in support of the proposal. Indeed, the proposal seems consistent with Project HealthDesign’s mission of increasing individuals’ engagement in their health care. But we want to hear from the current Project HealthDesign teams and other researchers:

Is HHS’s proposed regulation to enable individuals to directly access their lab test results from labs a positive development? Do you see any potential downfalls that could result from this new policy?

View the proposed regulation.
Read more posts about legal and policy issues.

Kirienko Provides Patient Perspective on Improving Patient Access to Health Information at Consumer Health IT Summit

Libby Dowdall, Communications Coordinator, Project HealthDesign National Program Office

A Sept. 11 article in USA Today featured Nikolai “Kolya” Kirienko, patient advocate and project director of Project HealthDesign’s Crohnology.MD study. The story, “HHS Aims to Improve Patients' Access to Electronic Records,” previewed new initiatives that support patients as they seek access to their own health information.

The following initiatives were then formally introduced at the U.S. Department of Health and Human Services (HHS) Consumer Health IT Summit on Sept. 12:

• Federal rules (pdf) that would strengthen patients’ rights to access their own laboratory test results.
• A straightforward model privacy notice for personal health record (PHR) vendors.
• BlueButtonData.org, which encourages organizations to register their commitment to offering Blue Button data download functionality to their patients and users.

Kirienko, who has Chron’s disease, also appeared at the Consumer Health IT Summit, along with patient advocates Donna Cryer and Denis Stasulis. "We desperately need collaborative medical records,” said Kirienko, whose story illustrates how patient access to health information and patient-clinician cooperation can help improve care for patients with chronic diseases.

As project director of Crohnology.MD, Kirienko has casted a vision for and helped to develop a mobile personal health application that allows patients with Crohn’s disease to self-track observations of daily living (ODLs) and symptoms between clinical visits. Because the application allows users to customize data views and share them with their clinicians, he and his team hope to see the application spark and support richer conversations between patients and providers during clinical visits.

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

The Process of Making Sense of ODL Data

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

One of the many reasons observations of daily living (ODLs) are interesting is because people don’t normally pay much attention to them as they live their everyday lives. If ODLs easily lent themselves to simple mental accounting, we would not need special sensors or mobile applications to log them. Thus, when we present ODL data back to the user, they often encounter an odd feeling that mixes familiarity (because, after all, the data show their own behaviors) and unfamiliarity (because they have never seen this particular behavior logged and presented this way). This showcasing of the mundane allows people to explore and attempt to make sense of this new kind of data. Is there a process by which people explore their own ODLs?

We had a chance to understand this process in our pilot study with two elders and four months of sensor data about their medication adherence. We gave them each a special pillbox to use that could keep track of when they picked it up and opened the pillbox doors. When we showed them their data, our participants went through a process that involved three basic steps: 1) looking for anomalies, 2) explaining these anomalies, and 3) confirming their explanations with the details in the data. When first presented with their data, our participants wanted to find the anomalous behavior — in this case, instances of days when they did not take their pills. The visualization we used actually made it rather difficult to find these days where no pill-taking event occurred, but nonetheless our users were persistent in finding the days with missing pills. After finding these anomalies, they wanted to find an explanation for why they might have missed their pills. They first tried to find a benign explanation such as being away on travel, but they also looked for explanations that might show their own forgetfulness and lack of structure in their routines. And finally, after coming up with possible explanations for why they might have missed their pills on one occasion, they were able to use the low-level details in the data to confirm their explanations.

We observed one instance with a study participant that illustrates the process involved in making sense of ODL data: As she reviewed the data, the participant noticed that she had missed her evening pills on a Friday evening two weeks prior. She thought back and explained that she visited her nephew that day and had probably taken her evening pills with her and took the pills at her nephew’s home. She then looked at the detailed view of the data for the pillbox for that day and noticed that she had the door open for 20 seconds in the morning — much longer than she thought was normal. She reasoned that she must have been taking her evening pills from that box and filling her travel pillbox in those 20 seconds.

This same sense-making process, which involves identifying anomalies, explaining them and confirming them with other or more detailed streams of data, can also apply to other times when people are exploring their ODLs for the first time. Granted, our example focuses on only one data stream, pillbox activity, but this process may very well be expanded and developed to account for multiple streams of data and different types of ODLs.

For more details on this process of making sense of ODL data, read our CHI 2011 paper.

Learn more about the Embedded Assessment project.
Read more posts from the Embedded Assessment team.

Project HealthDesign, Meet Quantified Self

 Libby Dowdall, Communications Coordinator, Project HealthDesign National Program Office

This weekend, we’re sending Project HealthDesign National Program Director Patricia Flatley Brennan, R.N., Ph.D., out to California to participate in the inaugural Quantified Self Conference. The Quantified Self describes itself as a community of “users and tool makers who share an interest in self-knowledge through self-tracking.” Health and wellness topics are some of the most frequent topics for self-experimentation. 

Outside the conference, Quantified Self community members hold regular “Show & Tell” meetups in 15 U.S. cities and around the world. The largest and longest-standing meetup occurs in the San Francisco Bay Area and is hosted by Quantified Self Co-Founders Gary Wolf and Kevin Kelly, along with Quantified Self Director Alexandra Carmichael.

What types of things do Quantifies Self community members track, analyze and optimize?

• Seth Roberts spent several months tracking how his work efficiency varied by time of day and found that his efficiency improved when he began reviewing the data visually in a progress display graph.
  
  
• Matt Bell used a Zeo to track his sleep data in order to optimize his sleep quality (which he anticipated would boost his energy during the day). So far, he’s learned that meeting new people in the evening and having emotionally difficult conversations late at night negatively impact his sleep. Watch a video of Matt to learn more about his experiment.

Self-quantifiers track lots of different things as they seek to optimize their lives. Even simple experiments have yielded useful results.

Quantified Self, Meet Project HealthDesign

 

Project HealthDesign’s first nine project teams completed a user-centered design process to create health tools that provide people with actionable information to help them manage their health. The patients who interacted with these teams helped us to recognize the concept of observations of daily living (ODLs). ODLs are sensations, feelings, thoughts, attitudes and behaviors that provide cues to a person about their health state.

Our five current teams are examining how personal health technology tools can collect and integrate observations of daily living (ODLs) into personal health decision-making and clinical care. They’re currently conducting studies to find out which ODLs patients value and how tracking ODLs impacts people’s health in everyday living.

If you’re part of the Quantified Self community, we want to learn from you! Because ODLs are personally meaningful health indicators, many self-quantifiers are already experimenting with data about ODLs like mood, stress level, sleep quality, socializing, etc. Engage with our work by reading our blog or sharing your recent experiments with us on Twitter (@prjhealthdesign). We look forward to more Project HealthDesign/Quantified Self introductions!

Federal Health IT Strategic Plan Comment: Creating a Patient-Centered Health Information Ecosystem

Patricia Flatley Brennan, R.N., Ph.D., Project HealthDesign Director

I want to thank ONC for the challenging yet thoughtful goals set forth in the Federal Health Information Technology Strategic Plan. This vision for the future of health IT will surely encourage everyone from clinicians and provider groups to researchers and developers to think—together—how we might best lead the country forward into a new, more connected era of health that considers both clinical health care and health in everyday living.

Goals III and IV are the most relevant to my work with Project HealthDesign, a Robert Wood Johnson Foundation national project that examines the potential for PHRs and observations of daily living (ODLs) to help people live healthier lives and get better care. We believe that ODLs, or data that reflect patients’ perceptions of their everyday health, serve to inform individuals about their health and help them take action or make decisions about their health. Our five current project teams are also working to see how ODL data (e.g., information about pain, mood, sleep, etc.) could help inform better clinical decision-making by allowing clinicians a peek into patients’ everyday lives.

As is suggested in Goal III, inspiring patient trust in the health information ecosystem is vital. We must use many different approaches in order to educate individuals about the risks and consequences of opting in or out of sharing personal health information. Additionally, efficient mechanisms that would allow individuals to access, review and update their personal health information permissions are needed. Individuals must be able to verify that their wishes have been documented and implemented as desired.

When considering Goal IV, we must not forget that health occurs outside the context of the health care system as well as within it. Every day, factors outside the system impact individuals’ abilities to manage their health. Additionally, the term “patient-centered” can mean different things to different people. Perhaps the most common understanding is that the patient is the target of health care.  A more expansive definition of the term defines the patient as the source and center of all health. I find the latter to be a more appropriate definition given our collective mission to improve health and reduce the burden of disease management. We must plan for and implement health IT that encompasses both definitions.

Project HealthDesign has shown that individuals are ready to become involved in our work with health IT. For example, participants in our teams’ studies have been eager to help us improve our PHR tools, including applications that track observations of daily living (ODLs). We have also found that as the participants provided this type of feedback, they became more aware of how these tools could help them improve or manage their health.

As we work toward a modern health information ecosystem, we must take into account many different types of patient-generated health information. Some patient-generated health information results from the clinician’s desire to know information about signs and symptoms experienced at home. Patients’ individual perspectives on health create another type of patient-generated health information: observations of daily living (ODLs). Health data generated by caregivers (e.g., parents of infants and caretakers of the elderly) are a third type of patient-generated data. Environmental factors that affect one or more people (e.g., pollen count, particulates in the air, radiation levels) comprise a fourth category.

Our project teams are finding that it is important to incorporate patient-generated data into the clinical workflow in ways that minimize the burden on the clinician. Early feedback from one of our teams suggests that clinicians do value patient-generated data, but that the ODLs a clinician values might be different from the ODLs a patient values.

Truly patient-centered care has the potential to revolutionize health care from both the patient and provider perspectives. Capitalizing on this new paradigm will require new processes and tools. We must remember the power of an individual’s unique perspective on his or her own health and equip patients to engage in these types of conversations as we plan toward the future of health IT.

This comment was submitted to ONC in response to the recently released Federal Health IT Strategic Plan. To read the Strategic Plan or other comments on the plan, please visit the Health IT Buzz blog.

Evaluating Meaningful Use of Health Information Systems

Kathy Johnson, R.N., M.S., Project HealthDesign Ph.D. Candidate in Nursing, University of Wisconsin-Madison

Right now, we are witnessing the birth of a health information technology system architecture. Because of the complexity of this integrated structure, the evaluation of this process requires a great deal of thought.

The Health Information Technology Policy Committee (HITPC) recently solicited public comments on proposed meaningful use Stage 2 criteria [pdf]. May and colleagues’ Normalization Process Model provides theoretical guidance for this type of evaluation (May, et al., 2007). This model proposes that the evaluation of complex intervention implementations requires more than the measurement of outcomes and effectiveness; it holds that the social relations and processes related to the work that leads to those outcomes must also be considered. It emphasizes the processes by which complex interventions are made workable and integrated into everyday practice.

I argue that there is an implicit normativity, or reliance on common perceptions, in the emerging structures of the health information technology system. The proposed criteria for clinician meaningful use reflect only the clinical side of a system that is meant to be used by everyone. This approach to meaningful use is clinician-centric; the opportunity for patients to contribute health information in a format that is meaningful to them has not been addressed. Furthermore, efforts to evaluate the effectiveness of these systems have only been in terms of percentages of information bins filled; the only “meaning” in this rubric is the completion of a task.

Others may assert that there is nothing wrong with an implicit normativity by arguing that the professional is “in charge” of the patient and that the root purpose of the system is the provision of patient-centered care. If that is the case, then we are not moving toward a system that invites patients to participate in their care. Instead we are merely moving from paper to electronic documentation. Before us is a stellar and unprecedented opportunity to create a system that is meaningful for all.

Related resource:

• May, C., Finch, T., Mair, F., Ballini, L., Dowrick, C., Eccles, M., . . . Heaven, B. (2007). Understanding the implementation of complex interventions in health care: The normalization process model. BMC Health Services Research, 7, 148. doi:10.1186/1472-6963-7-148

Stakeholders Weigh in on PCAST Report

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

Project HealthDesign Director Patti Brennan recently blogged about the report issued by the President’s Council of Advisors on Science and Technology (PCAST), which set forth recommendations to facilitate more effective use of technology for health information exchange. In the post, she praised the more expansive vision of exchange promoted by PCAST and noted the absence of a robust discussion on the need to include patient-generated data as part of this broad vision.

Efforts to analyze the PCAST report and determine how its vision of greater health data liquidity can be achieved have begun in earnest. The Health IT Policy Committee (HITPC) has established a PCAST Report Workgroup, which held a day-long public hearing on Feb. 15.

Stakeholder groups testifying included consumers and patients, providers, technology experts, and health information exchanges. Nearly all agreed with the goal of facilitating more widespread electronic exchange of health data for treatment and secondary data uses like public health and research. But stakeholders also raised a number of concerns about some of the recommendations in the report, including:

• fears that exchange of information at an “atomic data element” level would rob the information of the context necessary for providers and researchers to understand it;
• concerns that providing patients with very granular choices about how their data is shared could be difficult for patients and providers to manage;
• uncertainty about whether the PCAST recommendation for a “universal exchange language” would disrupt (or build on) existing data standardization efforts; and
• questions about whether the designated approach to protecting privacy – tagging data elements with meta data about privacy preferences and other applicable data sharing constraints – would be workable and effective.

The key task for the PCAST Workgroup, the federal advisory committees, and ultimately HHS will be to find a path forward to promote the PCAST vision in a way that builds on work that has been done in the past and effectively responds to implementation concerns raised by stakeholders. Here are a few possibilities:

• Ramp up the requirements for health information exchange in Stages 2 and 3 of meaningful use, including active exchange of data with patients.
• Adopt and implement standards that will allow patients and providers to exchange computable data with one another no matter which EHR, PHR or software application is being used.
• Develop the infrastructure for a query-response model of health data exchange that is based on the needs of the patient.
• Pilot privacy-enhancing technologies (including but not limited to the meta data tagging approach recommended by PCAST) and research both their efficacy and impact on care.

This first year of the meaningful use program provides us with an opportunity to test the efficacy of current strategies for effective use of health IT to improve health and health care. The PCAST Report provides yet another opportunity to consider whether these efforts are headed in the right direction and how we can accelerate progress toward the goals we share.

This week, those interested in HIT have another opportunity to influence future public policy in this arena: HITPC is soliciting public comments on proposed Meaningful Use Stage 2 objectives through Friday, Feb. 25.

Do People Hide “Bad” Observations of Daily Living?

Tim Patton, Project HealthDesign Ph.D. in Engineering Student, University of Wisconsin-Madison
Uba Backonja, Project HealthDesign Ph.D. in Nursing Student, University of Wisconsin-Madison

People might not be willing to share all of their observations of daily living (ODLs). This may be old news to health care providers, but it was a bit of a surprise to the engineers among us as we looked for information to help us design systems that support patients’ real needs in regard to personal health management, decision-making and monitoring behaviors.

Because they are indicators to which an individual pays attention and finds important to his or her health, ODLs are very specific to individual patients. To begin to obtain a systematic understanding of ODLs, we recently conducted a pilot in which we performed one-on-one interviews with 10 college students. The ODLs that emerged focused on health behaviors (e.g., exercise) and monitoring symptoms (e.g., pain). Because we framed the questions in terms of health, this is largely what we had expected. Throughout the pilot, we found that participants seemed willing to talk about very personal ODLs and discuss their personal habits’ and relationships’ impacts on their health.

Because of this apparent comfort with disclosing highly personal information, we assumed that participants would be comfortable disclosing all ODLs. However, we have some reservations regarding whether that assumption is true. During the interviews, not one student mentioned drinking alcohol, smoking, drug use, sex (unsafe or otherwise) or partying. In fact, none of the ODLs the students reported to us carried a negative social stigma, or could be seen as a “bad” ODL.

Were we simply lucky with our sample? The CDC estimates that 21.4% of adults ages 18–24 smoke and that  young adults and adolescents under 21 drink 11% of all alcohol consumed in the United States. Furthermore, the CDC estimates that 43% of all students report drinking in a high-risk manner at some point during college. Statistically, it is unlikely that such behavior was truly absent in our sample population.

Thus, we are left to ponder why the “bad” ODLs were missing. We have considered the following:

1. Our questions may have biased participants toward ODLs that improve or maintain health.
2. Participants didn’t think to observe the effects of “bad” things as ODLs.
3. Participants may deliberately avoid mentioning ODLs that might cast them in negative lights.

First, given that participants did mention things that detracted from health (e.g., lack of sleep, poor diet), we don’t think this can be explained by a positive bias in our interview questions. Second, other negative behaviors were noted (e.g., poor diet choices and exercise habits). Thus, we are left with a sense that people deliberately avoided telling us about “bad” ODLs.

Due to the anonymous nature of our interviews and the encouraging early results, we were hopeful we could avoid this potential issue and strive to account for it in future work. To properly design systems in support of ODLs, we must understand the full range of personal observations, including those that people prefer to keep to themselves. Thus, as we continue to push for systems that support personal health, we will likely need to find ways to safely and securely elicit all ODLs, whether good or “bad.”

Read more posts about ODLs.