The Science of Patient Experience


By: Doug Engfer: President & CEO, invivodata

invivodata integrates science and technology to improve the process of measuring patient experience, resulting in more timely, more valid clinical data. invivodata delivers a new total solution for capturing patient experience-in real time, in the real world-one that combines the advantages of handheld electronic diary technology with the principles of clinical and behavioral science.


Patient experience

Patient experience - self-observations of symptoms, relief, and quality of life following treatment administration - is an increasing focus of pharmaceutical science. Obtaining reliable, valid measures of patient experience requires a deep understanding of the processes through which patients observe and report about themselves and their behavior. A valid scientific approach to measuring patient experience, known as Ecological Momentary Assessment (EMA), is rooted in scientific principles involving cognitive psychology, statistical sampling, psychometrics, study design, and human memory. There are many considerations in deploying a technology-based EMA solution; this article discusses those considerations in light of new and emerging technologies.

It All Starts with the Subject…

In trying to understand how to deploy a technology-based EMA-based solution, it's useful to examine the roots of EMA research. When Dr. Saul Shiffman, professor of psychology at the University of Pittsburgh and co-founder of invivodata, inc, began his work on nicotine addiction and smoking cessation in the 1970s, he approached the work from a subject-centered perspective. Dr. Shiffman was interested in taking research out of the laboratory and understanding the psychology of smoking in everyday life. He wanted to know why people return to smoking after quitting, and, more importantly, why people smoke when they do-what triggers these smoking "episodes" and how can we understand these episodes within the overall fabric of the smokers' lives?

Like so many researchers using written diaries at the time, Dr. Shiffman would frequently find subjects completing a week's worth of diaries in the waiting room before a research visit. What was needed was a way of capturing, in a scientifically valid way, what people were doing and feeling in the real world at the time when they were actually experiencing something. In his efforts to understand how best to circumvent the biases of existing paper- based methods of data collection, he established the study of Ecological Momentary Assessment (EMA). The outcome of that work can be boiled down to a fairly straightforward guideline: in order to capture and measure valid and reliable patient experience data, one must collect the data in the real world, in real time.

That simple statement has deep implications, however. Proper application of EMA methodologies involves creating a rich set of samples of patient experience, against which episodic events can be measured and compared in statistically valid ways. From their work Dr. Shiffman and his peers and associates derived some fundamental rules for devices to be used in any EMA-based study:

1. The most appropriate data collection device must be portable, because assessments are made throughout the day and must not interfere with the subjects' normal life.
2. The user interface must be extraordinarily easy and fast to use, because assessments are made repeatedly and in real time.
3. The means of user interaction must be natural, so that a wide range of possible subjects can use the device.
4. The collection device must accommodate the subject's lifestyle, so that the subject remains inclined to carry the device with them at all times.

Interface Modalities

In clinical studies, researchers deal with a cross-section of the population, covering many demographics. The devices we develop to conduct this research must be usable by this broad demographic-whether young or old, technically savvy or naïve, in the U. S. or worldwide. Even with the explosion of technology in the U.S., the fact remains that here, as well as throughout the rest of the world, a majority of people gets through each day without directly, consciously interacting with a computer. While companies have developed a number of simple, keypad-based interfaces (ATMs, phones, etc.), there's nothing quite so natural for people as simply pointing at something. A particular beauty of today's handheld computing platforms is that they support this very simple and literal "point-to-select" interface modality. These easy- to-use, intuitive modes of interaction engage the subject and help drive high levels of protocol compliance.


Programmability may seem to be a given, but it's worth exploring, if only to look at some emerging technologies. EMA-based studies rely on protocol designs that engage and interact with the subject. In many cases, these interactions change based on when, where, and how the subjects respond to the interview questions. For example, consider a clinical trial designed to measure time to relief. In such a study, when subjects record that they have taken a medication, the device should repeatedly sample the subjects' perceived relief during the critical time window to ensure a sensitive test of when they first experience symptom relief. This type of dynamic sampling dramatically increases the sensitivity of measurement (e.g., Shiffman, Elash, et al., 2000). Only a programmable device allows researchers to change sampling schedules so that certain data types and time windows for data collection are built into the diary protocol.

Some interesting platforms to consider for the future are the intelligent phone and the wireless PDA. Especially as devices similar to Kyocera's SmartPhone become widely available (merging handheld computing with wireless telephony), having a programmable platform that also supports wireless communication will be very useful for EMA-based studies. Similarly, wireless PDAs similar to the Palm VII provide a larger display and back-end wireless communications over networks equivalent to those provided by the paging industry.

Platform Stability

This final technological factor is less technically oriented and more a market consideration. Given the nature of clinical research-long lead times and study durations, broad constituencies, and the need for peer and regulatory approval-it's only natural that the industry be concerned about the long-term viability of any computing platform they use. It's important for anyone pursuing EMA-based research to consider this and to choose a computing platform that is going to be around not just when the study is run, but also when the results are reviewed by FDA.

User Interface

Most fundamentally, successful EMA-based research must stress ease-of-use in the interface, almost literally to the point of instant usability. Subjects are really the key, the linchpin, to clinical research and they must feel respected, valued, and supported throughout the study process because they carry a heavy burden of responsibility. EMA techniques, properly applied in the user interface, can actually encourage, support, and engage the subject, driving higher subject compliance with the study protocol than is possible with any other methodology. Conversely, complicated user interfaces that require text entry or extended cognitive effort during assessments discourage participation and undermine compliance.

As a consequence, in an EMA user interface, simple is better. Use a small number of well-known interface widgets with good real-world analogues (sliding scales, check-boxes, number spinners, and so on) and sound psychometric properties. This approach also drives consistency in the interface. Because the interface consists of a small number of widgets, the subject quickly learns how each works and can apply that knowledge to new and different assessments. The result: higher subject performance, better subject compliance.

We touched earlier on the subjects' capacity to learn the assessment regime. As subjects become familiar with the various questions in the interviews, their response times drop dramatically. Subjects quickly get to the point where they recognize questions ("Oh, the mood question") and respond almost instantly to the prompts. As such, there is little value in posing long-winded, wordy prompts. Better to use brief, succinct prompts and support the assessment with a bit of launch-time training. Wordy approaches continuously burden the subject, eroding compliance.

Finally, the interface must be reasonable and respectful at all times. The data collection device must fit into the subjects' daily lives, both in terms of its form factor and with respect to user interface. Well-designed EMA-based interfaces include many "livability" features-suspend, bedtime, alarm, etc.-that are designed to accommodate the varied patterns of subjects' daily lives. Let's discuss suspend as an example. There are times during almost every day when a subject simply can't be interrupted to respond to a random prompt. EMA devices need to respect that, and provide a mechanism for the subjects to remain compliant while suspending their participation for limited amounts of time.

One of the most disrespectful things that a clinical study device can do is create subject burden. In a user interface, few things are as annoying as system failures-crashes, hangs, involved procedures, reboots, whatever. Any EMA data collection device should be rock-solid. While in the Windows® world we've come to accept our daily reboot (if that infrequent!), the world of clinical research simply cannot tolerate such a burden on the subject, not to speak of the risk these errors pose to data reliability. A well-crafted EMA-based study will generate, on average, as few as .025 Help Desk calls per subject-week (one call per week with 40 patients in the field).

Data Collection

The next step in the process, after having assessed the subject over some period of time, is to collect and analyze the subject's data. Here, again, all of the basic principles of an EMA platform come into play. The approach must balance the needs of the sponsor with the needs of the subject, providing a secure, reliable means to collect data while not burdening the subject unnecessarily. Some handheld platforms provide a fairly natural means to collect data that does not burden the patient: data synchronization. Palm's HotSync® technology is probably the best-known, most-reliable, most-popular example. Such tools provide a flexible, extensible, reliable means to move study data from the collection device to the study database. When accomplished at regular site visits, this approach adds no burden to the subject, and delivers timely data to the sponsor for appropriate analysis.

For study designs that demand either more-frequent data upload, or where site visits are infrequent, sponsors should consider using wire-line modems to collect data from the subjects. In deploying a modem-based solution, it's important to consider and mitigate the potential subject burden associated with data-upload that may occur as often as daily. Well-designed software eliminates any need for the patient to be concerned about re-dial attempts, busy signals, etc. Well-designed equipment packaging makes it straightforward for even technologically naïve subjects to set up their data-transfer kit. The net result is a system of data collection that allows study sponsors ready access to recent data.

Finally, for studies that need data even more frequently than once per day, or that include real-time subject feedback, wireless systems are ideal. Such systems can allow the patient to send and receive data effortlessly in the normal course of daily living. Cost and coverage are both important considerations when deploying wireless studies. Also, given the limitations of wireless coverage, study software must not rely on continuous access to the network. A thick-client approach, taking occasional advantage of the wireless network, provides the best compromise between ready data access for sponsors and continual application availability to study subjects.

Personal Area Networking

One truly fascinating area of current research and development concerns short-distance or "personal area" networking. These wireless protocols, whether infrared- or radio-based, offer the promise of integrating various sensors that can augment the patient experience data stream. For example, imagine being able to integrate the EMA data collection device with a device that reads heart rate and blood pressure. At a minimum, one could devise a protocol that reads that physiological data, automatically, as a part of the EMA assessment interview. Further, though, one could imagine triggering an EMA assessment based on a given heart rate or BP threshold value being achieved. Or, conversely, based on the specific results of a diary assessment, one could cause the device to take a reading. In all cases, those physiological data would be logged as part of the EMA data stream. To a limited extent, in this case the future is now. Studies have linked Palm technology to ambulatory blood pressure monitors to collect simultaneous streams of physiological and psychological data (see Kamarck et al., 1998).

As work with Bluetooth, 802.11b, and other short-distance wireless protocols continues to advance, expect that this kind of integration will proliferate, not only in clinical research, but also in patient and chronic-disease management applications.


Doug Engfer is president, CEO and co-founder of invivodata, inc.

invivodata is headquartered in Scotts Valley, CA and the Clinical Operations Center is located in Pittsburgh, PA.


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