Creating Evidence from Real World Patient Digital Data

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Editorial

24 February 2021

Editorial: Creating Evidence From Real World Patient Digital Data

Jane Nikles

,

Eric J. Daza

,

Suzanne McDonald

,

Eric Hekler

and

Nicholas J. Schork

2,061 views

3 citations

Editors

5

Jane Nikles

The University of Queensland

Eric J. Daza

Boehringer Ingelheim (United States)

Suzanne McDonald

The University of Queensland

Eric Hekler

University of California, San Diego

Nicholas Schork

Translational Genomics Research Institute (TGen)

Impact

About

N-of-1 randomized controlled trials (RCTs) provide an opportunity to evaluate individual patient response to interventions, by randomly allocating different time periods within an individual to repeated intervention and control conditions and comparing responses. N-of-1 observational studies involve the repeated measurement of an outcome (e.g. pain) in a patient over time, but with no intervention implemented, in order to draw conclusions about naturally-occurring patterns and predictors of outcomes over time. Both N-of-1 RCTs and observational studies can have a ‘self-study’ design, where an individual conducts the study on themselves, to answer research questions they have generated themselves. N-of-1 RCTs and observational studies provide individualized findings that can be aggregated to produce results equivalent to those found in traditional group-based RCTs and population-level epidemiological studies, respectively, but requiring fewer patients for the same power.

N-of-1 RCTs and observational studies are well-suited to complement, strengthen, and generate advances in precision medicine, patient-centred healthcare, and personalised health. Since 2015, the number of N-of-1 articles has doubled annually.
Similarly, digital health is an exploding field, with over 1,000 studies registered on clinicaltrials.gov.
Digital health, and digital therapeutics in particular, complement N-of-1 RCTs and observational studies by providing relevant individualized health data from, for example, worn sensors, implants, regular lab assays, or -omics sequencing. Such data can be compared to population-health databases to target a patient’s strongest possible treatment option (as in cancer-risk studies) and, in turn, inform the design of an N-of-1 RCT to evaluate it.
Digital health data can also be continuously monitored during the study itself and used to help tailor a treatment to the needs and preferences of patients in real time.

This Research Topic will cover digital health applications, delivery, and analysis of N-of-1 RCTs and observational studies (including self-studies) in any health discipline.
The focus is on:
- mobile health (mHealth) and applications (apps)
- wearable devices, sensors and implants,
- real-time tracking, data analytics and online registries,
- patient experience of digital health and mobile health, patients as collaborators in personalised medicine, self-tracking in citizen science, etc.

The articles can be original research, methodology pieces, opinion pieces, reviews, systematic reviews, protocols, short reports, or case studies.

Topic Editor Dr Eric Daza is Senior Statistician at Clarify Health Solutions. All other Topic Editors declare no competing interests with regards to the Research Topic subject.

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Editors

Jane Nikles

The University of Queensland

Eric J. Daza

Boehringer Ingelheim (United States)

Suzanne McDonald

The University of Queensland

Eric Hekler

University of California, San Diego

Nicholas Schork

Translational Genomics Research Institute (TGen)

Impact

124,984 Total views

100,595 Article views

17,052 Article downloads

7,337 Topic views

Published In

Frontiers in Computer Science

Digital Public Health

Frontiers in Psychology

Health Psychology, Psychology for Clinical Settings

Frontiers in Psychiatry

Public Mental Health, Social Psychiatry and Psychiatric Rehabilitation

Frontiers in Neurology

Neurorehabilitation

Frontiers in Public Health

Public Mental Health, Digital Public Health

Frontiers in Digital Health

Connected Health, Personalized Medicine, Health Informatics

Frontiers in Sociology

Public Mental Health

Frontiers in ICT

Digital Public Health

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