Around the bend: What’s coming and why it matters
April 21, 2020
Over the coming months and years, the data surge will continue unabated—not only in volume, but in quality and breadth. “Data for the sake of data” will no longer cut it: the information collected will need to serve an increasingly clear purpose. Here’s what to watch for.
Straight from the source
Data generated from patients themselves, known as patient-reported outcome measurements (PROMs), is on an upswing. Take CAPTURE ALS, a pan-Canadian database of amyotrophic lateral sclerosis (ALS) patients in current development. The data collected will range from biologic samples to PROMs, giving researchers a clearer path to personalized treatments.14 And who better to validate PROMS than patients themselves? That’s what’s happening in an agreement between the Coalition Priorité Cancer du Québec (a patient group) and Value-Based Health Care Canada, which has patients validating PROMs for breast, lung, and colorectal cancer to help identify gaps and inefficiencies along the care continuum.15
High performance
How can our healthcare system bear the load of specialty drugs without compromising patient health? Stakeholders are turning to RWD to solve this puzzle. By shining a lens on a drug’s performance in the real world, RWD can help funders make decisions that support best care. Indeed, a 2019 report from the Advisory Council on the Implementation of National Pharmacare recommends using RWD to underpin performance-based funding agreements for rare disease drugs.16 The more data collected over the long term, the greater its power to help patients access effective drugs with the minimum delay.
Fair play
Nobody wants a repeat of the 2018 Facebook scandal, in which millions of Facebook users saw their personal data harvested without their consent.17 As big data gets even bigger, concerns about privacy will become still more pressing. Prepare yourselves for a lot of conversations about the social implications of collecting and using patient data. Questions to hash out include: Why exactly is the data being collected? Does it infringe on basic rights? Does it favour certain patient groups over others? A case in point: Winterlight Labs, a Toronto start-up using speech recognition technology to identify neurological diseases such as Alzheimer’s, soon discovered that the technology only worked for Canadians with a particular dialect.18 A priori discussions between the data scientists, doctors and patients could have prevented this “oops.”
Above all, all parties need to agree on how the data will be used. Consensus takes time, but the gears are in motion.
References:
13 - Wang G et al. From unstructured clinical data to to standardized structured reports [poster]. https://www.linkedin.com/posts/medlior-health-outcomes-research-ltd-_wids2020-widscsm2020-datascience-activity-6640366964822855681-q-Oq
14 - ALS Canada. Other Initiatives. https://www.als.ca/research/als-canada-research-program/other-initiatives/
15 - A dose of reality: patients redefining the future of healthcare in Canada. Nov. 12-13, 2019 summit, Toronto.
16 - A prescription for Canada: achieving Pharmacare for all. Final report of the Advisory Council on the Implementation of National Pharmacare. June 2019.
17 - Facebook Cambridge Analytica data scandal. https://en.wikipedia.org/wiki/Facebook%E2%80%93Cambridge_Analytica_data_scandal
18 - Gershgorn D. Quartz daily brief, Sept. 6, 2018. https://qz.com/1367177/if-ai-is-going-to-be-the-worlds-doctor-it-needs-better-textbooks/