Care Triad

Patient-collected data

In April 2018, I participated in the 2018 Quantified Self (QS) Symposium on Cardiovascular Diseases held in San Diego. I was reminded of that session several weeks ago while attending the 2nd Annual Meeting of the Society for Participatory Medicine. In both conferences I was struck by the power of patients’ observations and measurements to manage their own diseases.

I first learned about the Quantified Self movement a few years ago while reading about Larry Smarr, an astrophysicist and computer scientist who started tracking his own exercise and weight but ultimately began expanding his self-tracking to include blood tests when he was told he had “pre-diabetes”. He ultimately diagnosed his own Crohn’s disease long before he had any symptoms based on analyzing his own blood and stool tests (including twice weekly stool microbiome analysis). He has since published a how-to guide in a biotechnology journal and participated in planning his own bowel resection for Crohn’s disease in 2016.

The Quantified Self conference participants were a very eclectic group – people who self-track using wearable devices, researchers, device-manufacturers, entrepreneurs, patient advocates, etc. One group of quantified self enthusiasts presented self-tracking (or N-of-1) experiments each of them had designed using an at-home blood cholesterol measurement tool. Their experiments showed that blood cholesterol levels vary according to the time of day (leading to “abnormal” levels at certain points in the day) and that cholesterol levels vary over the course of the menstrual cycle in women. Neither of these observations was previously known and both could have important implications for clinical care.

At the Society for Participatory Medicine conference, 2 mother-daughter pairs presented their own patient-collected data stories. Angela Kennedy, a health information executive learned that her adopted daughter, Grace, had cystic fibrosis when she was 11 years old. Fragmented paper medical records contributed to the delay in diagnosis. Grace, now 16, tracks her own disease and she and her mother have put together a care team across state lines. When visiting with her doctors, Grace insists on seeing her medical record, making corrections and sharing her observations about her health, even if the doctor does not ask about them.

Kristina Sheridan, who is trained as an aerospace engineer became frustrated when her 5th grade daughter Kate failed to improve after treatment for Lyme disease. Kate went from being a star athlete and excellent student to being wheelchair-bound and in need of remedial help at school. When numerous doctors were unable to figure out what was wrong, mother and daughter put together their own geographically dispersed care team and created their own tracking spreadsheet of Kate’s medications and 26 symptoms. Through their efforts Kate ultimately improved and her mother is now working with MITRE Corporation to develop a patient-friendly tracking system for use by other patients.

Traditionally medical data comes from research studies that look at “average” patients and are inherently flawed and ill-suited to make individual healthcare decisions. Patients live with their diseases around-the-clock but only see their doctors for short visits at intervals making it impossible, for example, to discuss and manage 26 symptoms.

Medical professionals need to trust patient-generated data, encourage patients to collect it and listen to their patients’ interpretations. Working together they can incorporate the data into the most appropriate, personalized care plan.