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. 

Challenges to Identifying Potential Participants Using a New EMR

By Stephen Rothemich, MD, MS, BreathEasy Co-Principal Investigator and Clinical Lead

With BreathEasy’s focus on people with asthma and comorbid anxiety and/or depression, one of the challenges is how to identify potential subjects for upcoming focus groups. While we are working with two inner-city clinics using the same electronic medical record (EMR), the process has not been as simple as you might expect, as our health system is still in the process of implementing the EMR.

Ideally we could have used patients’ problem lists in the EMR to identify those with the overlapping conditions of interest. While both practices have been using the EMR for labs and prescriptions for a while now, one site began full electronic documentation just a few months ago. Since it will take a while for these practice populations to have office visits, most patients don’t yet have an electronic problem list. Identifying potential subjects starting with manual reviews of the lists in paper charts was impractical; there were 6,277 patients in our target age range!

Next was the diagnosis billing codes from recent visits. Here we encountered two pitfalls: 1) every chronic condition present or even addressed at a visit doesn’t necessarily get included in the maximum of four diagnosis codes that we submit for each visit and 2) our billing system is separate from our EMR system. Since we just had access to the latter for this project, we could only capture billing diagnoses associated with orders for labs or x-rays.

That left the medication lists. Both clinics have been using the EMR to generate prescriptions for over a year. So while we incorporated data from problem and diagnosis lists, our search strategy relied on the better populated medication lists. However, medications can be prescribed for more than one purpose. Some antidepressants are also used for sleep or chronic pain, or even conditions we needed to exclude, such as bipolar disorder. An oral medication might be used for allergies and not for asthma control.

We found 271 potential subjects based on all available electronic data in the problem lists, diagnoses, and medications that might be used for the target conditions. Because we relied so heavily on medication data and the exact indication for many prescriptions was ambiguous, review of electronic charts was necessary in 176 cases. Paper charts were reviewed for 38 patients where EMR review was not helpful. All in all, we had 151 subjects with the conditions of interest. While we didn’t have to do the whole process with paper chart review, good electronic problem lists would have made life easier. So I’ve decided to stop grumbling about building those lists when I see my own patients. Stay tuned to learn what we’ve heard from the focus groups!

Introducing a PHR Cross-cutting Policy Issues Paper

By Robert Belfort - Manatt, Phelps & Phillips, LLC

Following on the heels of Deven McGraw’s blog post last month – Manatt and the Center for Democracy & Technology, along with the National Program Office and other Project HealthDesign consultants, are taking the feedback provided by the grantees at the Nashville meeting and using it to draft a “Cross Cutting Policy Issues” related to PHRs paper.

With this paper, we will address potential obstacles for widespread adoption of health care quality improvement models that leverage technology, like PHRs and EHRs. The paper will also discuss potential public policy solutions for overcoming these obstacles in order to successfully bridge the information gap between clinical care teams and patients. This is especially relevant for the current round of grantees, given the patient/clinical provider focus.

Based on recent discussions and brainstorming with the grantees, we plan to focus on three sets of issues: (1) provider liability concerns relating to the availability of patient-supplied information; (2) uncertainty about legal obligations for assuring the security of information transmitted between portable devices and other computer systems and (3) the lack of a clear legal framework for many types of personal health records. Link to full outline http://bit.ly/c1UFNw

Since this is your paper too, we will be seeking your feedback every step of the way! For starters, what do you think of the proposed issue areas? Anything specific you’d like addressed? Any additional concerns?

 

How Long is Long Enough for an Intervention?

By Barbara L. Massoudi, Project Director and Murrey G. Olmsted, Senior Advisor, BreathEasy, RTI International

For patients using our smartphone application for collecting and tracking ODLs, lately the team has been wrestling with the question of how long to run the intervention. Given that asthma is a chronic condition with intermittent, and often unpredictable acute exacerbations, we would need to collect the ODLs for a sufficiently long time to increase the likelihood that we’d capture data during at least one acute exacerbation period, but not so long that the patients would tire of using the application.

It seemed to us that there would be some ideal length of time that would balance both of these considerations, while giving us adequate time to allow for iterative improvements to the application based on patient and clinician feedback. The question of how long to run the intervention is made more complicated by the fact that typically, behavioral interventions are supported by regular interactions with clinicians over time, and that there is a process to incorporate the intervention into the patients’ lifestyle and the clinical practice.

We consulted with Project HealthDesign National Advisory Committee member, David Ahern, Ph.D., to get his recommendations on this question. After an interesting discussion with David, we concluded that the best approach would be to conduct two short intervention periods of two to four weeks each, and then run the final, full trial for three months. 

During week one, David predicted, patients and clinicians would be getting used to the tool. The following two to four weeks would provide enough time then to get good compliance with ODL tracking. Following this four week intervention period, we’d collect feedback from patients and clinicians, adapt the system and then run another short intervention. We’d again make improvements to the tools and then begin the full evaluation trial for a three month period, giving us enough time to gather ODLs when patients were likely to have at least one acute exacerbation.

This timeframe for the evaluation discussed feels right to the team. We never expected that we’d create a tool that patients would necessarily have to use forever. The key to ultimately answering this question will be fine-tuning the intervention period to determine just how long patients and clinicians will need to use the tools to see the benefit. To answer that question definitively, we’d need to do a follow-up study looking at differing lengths of interventions and their relative effectiveness in achieving the intended outcomes. For now, we’ll focus on getting the tool right and achieving patient and clinician compliance for our limited evaluation phase.

To those who have had similar scenarios with patients, have you ever encountered an issue quite like this?  If so, how did you test it out to find what works best for patients?