ReviewYearbook of medical informatics2024
Consumer Health Informatics to Advance Precision Prevention.
Review in Yearbook of medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Digital health and consumer health informatics: past and future.Medical research archives · 2026Article
- Nutrigenomics meets multi-omics: integrating genetic, metabolic, and microbiome data for personalized nutrition strategies.Genes & nutrition · 2025Review
- Digital Health for Precision Prevention.Yearbook of medical informatics · 2024Article
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
No grant is acknowledged in the PubMed record.
Abstract
objectiveConsumer health informatics (CHI) has the potential to disrupt traditional but unsustainable break-fix models of healthcare and catalyse precision prevention of chronic disease - a preventable global burden. This perspective article reviewed how consumer health informatics can advance precision prevention across four research and practice areas: (1) public health policy and practice (2) individualised disease risk assessment (3) early detection and monitoring of disease (4) tailored intervention of modifiable health determinants.
methodsWe review and narratively synthesise methods and published recent (2018 onwards) research evidence of interventional studies of consumer health informatics for precision prevention. An analysis of research trends, ethical considerations, and future directions is presented as a guide for consumers, researchers, and practitioners to collectively prioritise advancing two interlinked fields towards high-quality evidence generation to support practice translation. A health consumer co-author provided critical review at all stages of manuscript preparation, moderating the allied health, medical and nursing researcher perspectives represented in the authorship team.
resultsPrecision prevention of chronic disease is enabled by consumer health informatics methods and interventions in population health surveillance using real-world data (e.g., genomics) (public health policy and practice), disease prognosis (regression modelling, machine learning) (individualized disease risk assessment), wearable devices and mobile health (mHealth) applications that generate digital phenotypes (early detection and monitoring), and targeted behaviour change interventions based upon personalized risk algorithms (tailored intervention of modifiable health determinants). In our disease case studies, there was mixed evidence for the effectiveness of consumer health informatics to improve risk-stratified or behavioural prevention-related health outcomes. Research trends comprise both consumer-centred and healthcare-centred innovations, with emphasis on inclusive design methodologies, social licence of health data use, and federated learning to preserve data sovereignty and maximise cross-jurisdictional analytical power.
conclusionsTogether, CHI and precision prevention represent a potential future vanguard in shifting from traditional and inefficient break-fix to predict-prevent models of healthcare. Meaningful researcher, practitioner, and consumer partnerships must focus on generating high-quality evidence from methodologically robust study designs to support consumer health informatics as a core enabler of precision prevention.
Indexed as
Identifiers
What Socratic 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 Socratic graph.