Chronology.MD: Lessons Learned and Next Steps

Kathleen Morrison, Chronology.MD Project Director, Healthy Communities Foundation; Linda Neuhauser, Chronology.MD Co-Principal Investigator, University of California, Berkeley; Deryk Van Brunt, Chronology.MD Co-Principal Investigator, Healthy Communities Foundation; Marcos Athanasoulis, Chronology.MD Chief Technology Officer, Healthy Communities Foundation

Crohn’s disease presents major treatment challenges for patients and clinicians to manage. The Chronology.MD project has developed an interactive mobile system in which patients with Crohn’s disease can input important observations of daily living (ODLs) such as symptoms, medication adherence, sleep, and activity, and share these data with clinicians during visits to enhance treatment decisions. In our last post, we reviewed preliminary data from patient responses to our online survey. We found that the vast majority of our patient participants liked our system and used it. We learned that patients had diverse views of the value of specific ODLs, and that age and sex may influence their views of what is personally relevant. For example, patients ages 40-50 were slightly more likely to track stress, while patients ages 20-30 were slightly more likely to track pain. Women reported that menstrual cycle information would have been an important ODL. Because our small cohort comprised only 30 patients, this information is not statistically significant, but it does help inform future research and practice.

We learned from patient interviews that each patient has a unique story of their illness, as well as unique priorities. Tracking ODLs often helped patient participants identify important factors (e.g., activity, sleep, stress, medications) that influence their symptoms and pain. Our use of contextual inquiry (focus groups, surveys, and interviews) allowed us a more comprehensive understanding of important ODLs and the factors that influence a patient’s use of a mobile device for ODL collection.

Clinician participants primarily saw the Chronology.MD system as an important patient app – a data collection and visualization system that helps patients focus and prepare for office visits. If patients are more focused, then the visit is more efficient and both patients and providers will be more satisfied with the encounter. Our clinician participants suggested that we incorporate the ODL data visualization graphs into the University of California San Francisco clinic’s Epic EHR system in real time. That way, the provider wouldn’t be overwhelmed by too much data in their EHR interface outside of the appointment. This way, providers would pull up the data at the time of the appointment, and the patients could discuss the ODLs that were most important since the last visit.

Because we developed our technology during the study and used iterative participatory design processes, we had a lot to do in a relatively short amount of time. Going forward, we know that our patients would like a single app for data collection and visualization, along with the ability to enter ODL data via SMS text message. We also learned that system bugs and crashes are a deterrent to utilization, and that a more comprehensive list of ODLs should be included. Our patients are committed to finding a way to continue using and improving the system, and many have reported that the use of the system is what keeps them healthier, more pain-free, and able to reduce the use of narcotic pain-killers.

Going forward, our clinicians would like to see this app add even more utility to the clinical visit. For example, incorporating data that address validated indices such as the CDAI (Crohn’s Disease Activity Index) and/or the Harvey-Bradshaw index (a simpler Crohn’s disease index), would permit providers to review these index scores with patients in real time and would allow patients to monitor their scores on a daily or weekly basis. Clinicians said that incorporating one or both of these indices would greatly enhance their ability to collaborate with patients.

In addition, our clinicians felt that this app could be used to equip patients with important information about Crohn’s disease – including where the disease occurs, the course of the disease, how to determine remission, the importance of medication adherence, the benefits of biologic vs. steroid drugs, and the importance of paying attention to general health maintenance (e.g., up-to-date vaccinations, pap-smears, and skin cancer screening). Ultimately, if this app could help better educate, inform, and prepare patients for office visits (including visits to other specialty providers not well-versed in Crohn’s disease) and if it could include more detailed information about medications, lab tests, scans (e.g., last colonoscopy, GI involvement), and symptoms to discuss, then providers would see it not only as an important patient app, but also as a very useful provider app. Clinicians told us that this app could  change the standard of care for Crohn’s.

We have learned from this pilot study that both clinicians and patients are interested in finding the balance between collecting and tracking data that is important to each group. Neither group wants to collect extraneous data, nor do they want to collect data for extended periods of time. The balance point between clinician and patient, and the ODLs that are personally relevant to patients, as well as clinically significant for providers, we call the ODL Prescription (ODL Rx). We are exploring support for future studies that will build on pilot study findings to create a technology that helps identify the ODL Rx for individual patients and satisfies the goals of both patients and providers to help manage this complex disease.

Learn more about the Chronology.MD project.
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Looking Long-Term

Anind Dey, Ph.D., dwellSense Principal Investigator, Carnegie Mellon University

One idea that pervades each of the Project HealthDesign studies is that computing and advanced technology has the potential to change both people’s impressions of their health and their actual health. At least that’s the promise. One of the challenges is that these positive changes often occur over a long period of time, and usually require individuals to integrate a new technology into their lives.

In human-computer interaction, the research field I call home, most of the studies of technologies for behavior change occur over a few weeks, with only a few lasting more than a month. The difficulties in running a longer study are well-documented: recruitment, attrition of participants, maintaining ecological validity while keeping the study as “clean” as possible, researcher fatigue, analysis strategies, funding, etc. Additionally, researchers are able to conduct research and get papers published without conducting such long studies.

The benefits too are well-documented: a long-term study may be the only reasonable and ecologically valid way to study the impact of a technological intervention, novelty effects of introduced technologies are minimized, there’s more time to test out technology in the field and to evolve it before needing to collect data, it gives time for users to feel comfortable with researchers and introduced technologies, and it provides an opportunity to study phenomena that occur over a long period of time.

In our project, we have the opportunity to conduct a long-term study with a few of the early-stage users of our technology. We reported on their use of visualizations of their activities after they had used our embedded assessment system for four months. Our subjects have now used our system for about a year, and we are planning on a follow-up study to understand 1) whether the problems they noticed in the performance of everyday activities caused them to change their behavior to improve performance, 2) whether repeated but infrequent reflection on their data helps them understand their performance data better than with a one-time reflection, and 3) whether our users still find value in the embedded assessment system now.

Although short-term studies of such technologies are useful and common, truly understanding how performance of activities changes over time requires a long-term study.

Learn more about the dwellSense project.
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Is Theory-based Design Practical?

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

A meta-review by Webb, et al.² showed that Internet and mobile health interventions designed based on a behavioral theory resulted in better health outcomes with larger effect sizes than those that were not based on a theory. Of the studies included in the review, those that had used Aizen’s Theory of Planned Behavior were the most successful in improving health outcomes. Aizen’s Theory states that individual attitudes and social norms contribute to motivation. But, motivation alone is not sufficient to yield behavior change. There must also be an adequate level of perceived behavioral control which means the individual must think they possess the ability to make the change (and have the capability to make the change). Sounds good, but how do you actually design based on a theory?

For iN Touch, here’s how we thought about it:

For motivation, we needed to elicit individual attitudes/beliefs/values and reinforce positive social norms. The health coach drew out the participant’s individual attitudes through conversation and reinforced the values of health, well-being, and empowerment to make change. She also facilitated self-reflection about the ODLs and identification of trends and patterns in the combinations of ODLs. Weigh-ins and measurements were also a form of reinforcement by revealing objectively whether behavior changes each person made were effective or not. These contributed to motivation in an ongoing way.

We spent a great deal of effort designing perceived behavioral control, using both online and offline tools. The iN Touch application itself was a tool for behavioral control because it allowed the participant to capture the ODLs, review them in real-time, and conduct ad hoc comparisons. We designed the application within a "Five Clicks, Five Minutes" (per day) rule our Youth Advisory Board provided to minimize data entry burden (Sabee, et al.¹). Our post last month provided a detailed overview of the application. The iPod Touch device itself is portable and highly accessible, further contributing to perceived behavioral control.

Offline, we provided participants with a “My Experiment” tool for weekly goal setting and action planning. The key to this coaching tool is it provides the participant a way to make a short-term commitment, prepare for any obstacles, assess their level of confidence, and plan for follow-up. It gives them permission to try out a behavior change and have full control over the conduct of their experiment.  

Finally, our intervention included multi-modal interaction with the health coach in order to provide support when and where the participant needed it, another way of putting control in the participant’s hands. Participants were able to meet with the health coach in person or by phone, during scheduled or drop-in appointments, and communicate via text message. All of these strategies contributed to perceived control by participants.

We used the theory of planned behavior to inform both design of the technology and programmatic elements. The use of health behavior change theory in technological design is still emerging. We are eager to hear about other examples where this has been applied. Please share your experiences with us in the comments.

References:

¹ Sabee CM, Kim KK, Charles J, Logan H, Young E. (October, 2011).  Five Clicks, Five Minutes: Providing a Voice for Youth with Obesity and Depression with a Mobile Health Platform. Manuscript presented at the International Conference on Communication in Healthcare: Chicago, IL.  

² Webb TL, Joseph J, Yardley L, Michie S. (2010). Using the Internet to Promote Health Behavior Change: A Systematic Review and Meta-analysis of the Impact of Theoretical Basis, Use of Behavior Change Techniques, and Mode of Delivery on Efficacy. J Med Internet Res,12(1):e4). doi:10.2196/jmir.137.

 

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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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Thinking about Science, Evaluation and e-Health Design

Linda Neuhauser, Dr.P.H., Crohnology.MD Co-Principal Investigator, School of Public Health, University of California, Berkeley

One of the big challenges we have faced in the Crohnology.MD project is developing an evaluation plan. We are all familiar with the trade-offs between using qualitative and quantitative methods. If we choose a primarily quantitative approach, we may have statistical results, but may not really understand the phenomena being tested. If we select a qualitative approach, it’s hard to know whether the results would be similar if tested on a larger cohort. This is the typical tension in evaluation design. My view is that traditional evaluation methods are not well suited to novel e-health experiments, like the Project HealthDesign projects. I’ll start with a personal story:

Last March, I participated in a conference on Artificial Intelligence and Health Communication at Stanford University. There were many fascinating state-of-the-art projects. I was especially intrigued by a project using avatars as health coaches. The developers described how they gathered some preliminary (formative) information at the project outset, implemented the project, and then quantitatively evaluated the outcomes. The developers and the funder considered this an acceptable design, as would many evaluators. However, the results uncovered an important problem—the users did not find the avatars adequately believable and that interfered with their engagement with the virtual coaching. Similar surprises cropped up in other projects that were presented, even though the developers of the projects were highly talented, had given careful thought to the evaluation, and had used both qualitative and quantitative methods. As a result, a number of these projects will now need to be re-funded, redesigned and re-evaluated. I left the conference with the strong impression that some of these problems could have been avoided if the developers had used different evaluation methods. Certainly, e-health evaluation is an area that needs a lot more attention.

I believe the roots of the evaluation conundrum lie in the foundations of scientific inquiry. Before the mid-20^th century, the dominant “positivist” view was that truth is knowable and generalizable and the focus was on discovering the laws that govern the physical world. This perspective advanced the idea that quantitative methods (like randomized controlled trials) should be the gold standard of research and that their findings could be broadly extrapolated. In the past 50 years, the scientific paradigm has shifted. In the “post-positivist” world, the “critical realists” have emerged and posit that it is impossible for humans to adequately perceive the real world, and that claims about reality must be subjected to the widest possible examination.

There is now a greater understanding that it can be very difficult to define what we want to study, much less quantify the results. This is particularly true when we move from the natural sciences to human sciences—people don’t follow the more predictable laws of the physical world. In the health arena, we now have a host of social sciences to help us understand the connections between people and health. Changes in evaluation design have paralleled changes in views about scientific inquiry. Qualitative methods are considered increasingly important to achieve a deeper understanding of the complicated nature of human health and behavior. Likewise, there is a growing recognition that formative work needs to take place before investigators even know enough to finalize a research design that focuses on outcomes.

Scientists have identified a newer research challenge: one posed by what is now called “design (or artificial) sciences.” This field is concerned “not with how things are, but with how they might be.” (Simon, 1996).  Those who study design sciences say that they pose special challenges for research methods because understanding a problem and solving that problem often happen at the same time. Similarly, there is no “end” to the design and problem-solving process. Obviously, design science efforts are not well suited to traditional research approaches that test a priori hypotheses. For this reason, design sciences emphasize real-time, iterative investigative approaches, such as usability testing, over the more simplistic “before” and “after” methods of traditional evaluations. In other words, just as we are experimenting with observations of daily living (ODLs) to get finer, time-sensitive information about participant data, we need to do the same in our evaluations.

In my view, the Project HealthDesign projects, which create new technologies and measure complex daily interactions between people, their environments, and their health, lie at the intersection of human and design sciences. Effective evaluation designs for these projects will need to include a strong focus on usability and other iterative testing over time, artfully linked with formative and outcome measures. There is no definitive guidance for such evaluation designs. Fortunately, the Project HealthDesign teams have taken a pioneering experimental approach to finding a better path forward.

Have you successfully employed both quantitative and qualitative evaluation techniques on a project? What advice can you share with us?

Reference:
Simon, H. 1996. The Sciences of the Artificial, 3^rd Ed. MIT Press.

Learn more about the Chronology.MD project.
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Guest Post: Measuring a Patient's Skill and Confidence in Self-Management

Judith Hibbard, Dr.P.H., Professor Emerita, University of Oregon Department of Planning, Public Policy and Management

Patient Activation Measure

The Patient Activation Measure (PAM) is a 13-item questionnaire that measures the latent concept of activation. The PAM provides a score on a 0-100 scale.  Being activated refers to the degree to which an individual understands his or her own role in maintaining and promoting personal health and the extent to which he/she possesses a sense of self-efficacy for taking on this role. It is a global construct reflecting an individual’s overall knowledge, skill and confidence for self-management. Thus, the concept involves beliefs about one’s role, as well as knowledge and self-efficacy for taking stewardship of one’s own health.  Multiple studies have shown that activation scores are predictive of most health behaviors and many health outcomes. Further, studies show that activation is changeable, and that when activation changes, outcomes also change.

Read the following to learn more about the PAM:

• “Improving the Outcomes of Disease Management by Tailoring Care to the Patient’s Level of Activation” in The American Journal of Managed Care (pdf)
• “Do Increases in Patient Activation Result in Improved Self-Management Behaviors?” in Health Services Research
• “Is Patient Activation Associated With Future Health Outcomes and Healthcare Utilization Among Patients With Diabetes?” in The Journal of Ambulatory Care Management (pdf)
• "Measuring self-management of patients' and employees' health: Further validation of the Patient Activation Measure (PAM) based on its relation to employee characteristics" in Patient Education and Counseling

Clinician Support for Patient Activation Measure

The Clinician Support for Patient Activation Measure (CS-PAM), which was adapted from the PAM, assesses a clinician’s beliefs about the importance of patient self-management. The CS-PAM, like the PAM, was created using Rasch analysis and, like the PAM, has strong psychometric properties. Research shows the CS-PAM to be a reliable measurement tool that can assess and differentiate clinicians on their beliefs and attitudes about the importance of patient self-management and behaviors. Clinicians scoring higher on this measure are more likely to engage in a number of behaviors supportive of the patient role.

Read the following for more information about the CS-PAM:

• “The development and testing of a measure assessing clinician beliefs about patient self-management” in Health Expectations

For licensing information on the PAM or CS-PAM, or to learn about two versions of the PAM tailored to parents of chronic or well children, please contact Craig Swanson, Insignia Health founder, at [email protected].

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Editor’s note: We invited Dr. Hibbard to write this guest post because several of our current teams are using the PAM and/or CS-PAM with the patient and clinician participants in their studies. The following quote from FitBaby Co-Principal Investigator Karen Cheng, describes her team’s unique approach to using the PAM:

“Preterm birth that results in admittance to the Neonatal Intensive Care Unit is an unexpected shock for parents. Many of the parents find themselves overwhelmed by the sheer number of appointments with health care providers and navigating the medical system. In our FitBaby project, we hope to empower parents by giving them an easy way to record and access their baby’s ODL data, so that they can become active advocates in their child’s care. We decided to use the Patient Activation Measure (PAM) in our evaluation, because it captures the idea of patients becoming active advocates for their own care. We revised the language of the measure so that it reflects parents’ activation, and we hope to see increased parent activation among parents who use the FitBaby system, compared to parents who do not use it.”
-Karen Cheng, Ph.D., FitBaby Co-Principal Investigator, Charles Drew University of Medicine and Science

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.
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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!

Brrr! The Challenges of Cold Calling

Janelle Charles, San Francisco State University, iN Touch Research Assistant

One of the most challenging ways to recruit participants for a clinical research project is through cold calling. I’m certain the reason this style is compared to the cold is because first you must warm patients up in order to spark their interest in your project.

In order to be successful at engaging participants during cold calls, you should capture their attention during the first 30 seconds of the interaction. To do so, it is important to be cheerful, personable and relatable on the phone. Don’t sound tired or monotonous. Participants need to feel your excitement for the study in order to get excited. So, be lively!  Once you’ve set the warm ambiance, it is easier to go in for the close and—for research assistants that have a multistep recruitment process—you may have a better chance at an opportunity of meeting prospects in person.

The first impression isn’t the only factor that can influence your success. You may encounter several other obstacles while making cold calls. Here are some cold calling challenges specific to our study:

1. Protective parents: Most of our prospective participants are under 18 and the first step in recruitment is talking to their parents. Our strategy in winning parents over is explaining study details simply and clearly. We also make sure to emphasize their child’s rights.
2. Language barriers: A significant number of our prospective participants live in Spanish-speaking homes. Our bilingual research assistants communicate study goals and details to parents in Spanish. We also employ the interested youth by encouraging them to discuss the project with their parents.
3. Being creative with the IRB-approved script: When calling prospects, observe their responses to the script. If you are not successful at first, try to play around with your voice cadences and rhythm. You have to stick to the script, but make it fun!

Our team is currently in the process of recruiting. Here are some of our preliminary results:

Cold calling: We made a total of 29 cold calls to prospective participants. Eighteen either did not answer or were unavailable to speak with the research assistant; six refused to participate; and five agreed to meet with our staff to determine eligibility.

Clinician referrals: When the school nurse at one of our sites talked with the candidate first, we had a much higher recruitment rate. Of 15 candidates referred by the nurse, 12 agreed to participate. The remaining three are still awaiting follow-up.

Have you faced similar challenges when recruiting? How did you address the challenges you faced?

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.