Sara Koliner, Policy Analysis Project Assistant, Project HealthDesign National Program Office
Last week, the Patient-Centered Outcomes Research Institute (PCORI) approved 51 awards as part of its second cycle of funding in support of the development of a National Patient-Centered Clinical Research Network, part of the “Accelerating Patient-Centered and Methodological Research” Priority for Research.
Studies in Comparative Effectiveness Research (CER) rely on dense and nuanced information in order to accurately assess the quality of one treatment over another. The studies approved by PCORI, especially those concerning the assessment of prevention, diagnosis, and treatment options, cannot rely on coarse measurements such as mortality rates or a running list of potential side effects to inform medical providers and policymakers about the quality of life lived by treated patients. Instead, studies such as this could benefit from the real-time collection of the patient’s observations during treatment — information that Observations of Daily Living (ODLs) readily provide.
For example, a PCORI-funded University of Pennsylvania study has proposed to investigate the comparative effectiveness between two treatments for inflammatory bowel diseases, including Crohn’s disease. In order to quantify patient preferences for relevant treatment outcomes, a discrete choice experiment will be implemented using known attributes (e.g. the risk of serious infection, treatment failure requiring surgery, etc.). While these attributes of a treatment are important to informed decision making, they do not capture the entirety of patient-preference, especially with regard to unpredicted effects experienced during treatment.
The Project HealthDesign team, Chronology.MD, also focused on individuals with Crohn’s disease, but with the focus on their experiences during the study, rather than just the clinical outcomes. By giving patients a way to self-monitor through the collection of ODLs, the team made an enlightening observation (discussed in a blog post last year):
“Overall, the ODLs that the patients felt were the most personally relevant to track were (in order of most frequently cited): abdominal pain, weight, energy, journal, stress, daily activity, medications, sleep, lab tests, and trigger foods. […]Patients in the 25-34 years age group were more likely to report abdominal pain and weight as the two most relevant ODLs for them to share with their providers; patients in the 35-44 age group reported that the journal and abdominal pain were most relevant to share; and patients in the 45-54 age group unanimously reported stress and energy as the two most relevant ODLs to share with their providers.”
We already know that patient-defined, patient-generated ODLs provide incomparable insight into a person’s health experiences on the individual scale—but that’s only half the story. The translation of these personal cues into values that can be compiled, cross-listed, and categorized brings patient-level data to the scale of a population. Through the amalgamation of individual-level data, the Chronology.MD team could see that a 30-year-old patient with Crohn’s Disease may prioritize weight over stress as an indication of health, while a 50-year-old may more likely do the opposite. When attempting to assess the effect of a treatment—especially in terms of quality of life—researchers must take these (in this case, age-related) preferences into account. Patient-centered outcomes rely on the perspectives, vocabularies, and concerns of real patients, not just the outcomes that clinicians are concerned about.
As we wrap up our eight year project and look to the future, it is important to also stress how much value remains to be produced by ODLs in the research agenda of patient-centered outcomes. Mobile technology and application software have never been more ready to be utilized by those working outside the confines of the traditional clinical research lab, and we are excited to see how patient-defined, patient-generated data illuminates the Comparative Effectiveness Research field.