ArticleDigital biomarkers
An Algorithm for Digital Medicine Testing: A NODE.Health Perspective Intended to Help Emerging Technology Companies and Healthcare Systems Navigate the Trial and Testing Period prior to Full-Scale Adoption.
Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Evaluating the Impact of a Point-of-Care Cardiometabolic Clinical Decision Support Tool on Clinical Efficiency Using Electronic Health Record Audit Log Data: Algorithm Development and Validation.JMIR medical informatics · 2022Article
- Design and testing of a mobile health application rating tool.NPJ digital medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Over the last several years, there has been rapid growth of digital technologies attempting to transform healthcare. Unique features of digital medicine technology lead to both challenges and opportunities for testing and validation. Yet little guidance exists to help a health system decide whether to undertake a pilot test of new technology, move right to full-scale adoption or start somewhere in between. To navigate this complexity, this paper proposes an algorithm to help choose the best path toward validation and adoption. Special attention is paid to considering whether the needs of patients with limited digital skills, equipment (e.g., smart-phones) and connectivity (e.g., data plans) have been considered in technology development and deployment. The algorithm reflects the collective experience of 20+ health systems and academic institutions that have established the Network of Digital Evidence for Health, NODE. Health, plus insights from existing clinical research taxonomies, syntheses or frameworks for assessing technology or for reporting clinical trials.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.