Information Quality Challenges of Patient-Generated Data in Clinical Practice

A characteristic trend of digital health has been the dramatic increase in patient-generated data being presented to clinicians, which follows from the increased ubiquity of self-tracking practices by individuals, driven, in turn, by the proliferation of self-tracking tools and technologies. Such tools not only make self-tracking easier but also potentially more reliable by automating data collection, curation, and storage. While self-tracking practices themselves have been studied extensively in human–computer interaction literature, little work has yet looked at whether these patient-generated data might be able to support clinical processes, such as providing evidence for diagnoses, treatment monitoring, or postprocedure recovery, and how we can define information quality with respect to self-tracked data. In this article, we present the results of a literature review of empirical studies of self-tracking tools, in which we identify how clinicians perceive quality of information from such tools. In the studies, clinicians perceive several characteristics of information quality relating to accuracy and reliability, completeness, context, patient motivation, and representation. We discuss the issues these present in admitting self-tracked data as evidence for clinical decisions.

Abstract licence: CC BY

1. 4.

   “You Get Reminded You’re a Sick Person”: Personal Data Tracking and Patients With Multiple Chronic Conditions · 2015

2. 11.

   Patient-centered activity monitoring in the self-management of chronic health conditions · 2015

3. 13.

   Behavioral Functionality of Mobile Apps in Health Interventions: A Systematic Review of the Literature · 2015

4. 20.

   Health 2050: The Realization of Personalized Medicine through Crowdsourcing, the Quantified Self, and the Participatory Biocitizen · 2012

5. 25.

   A systematic review of the content of critical appraisal tools · 2004

6. 34.

   The Rise of Consumer Health Wearables: Promises and Barriers · 2016

34 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.