ArticleBMJ health & care informatics2020
Does not compute: challenges and solutions in managing computable biomedical knowledge.
Article in BMJ health & care informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Article
- Data-Driven Guideline Adherence in Data Representation and Compliance Measurement: Scoping Review.Journal of medical Internet research · 2026Review
- Automated Monitoring of Adherence to Evidenced-Based Clinical Guideline Recommendations: Design and Implementation Study.Journal of medical Internet research · 2023Article
- A framework for understanding, designing, developing and evaluating learning health systems.Learning health systems · 2023Article
- Computable knowledge is the enemy of disease.BMJ health & care informatics · 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computers can potentially play a key role in resolving knowledge mobilisation bottlenecks in health and care through decision support at the point of care based on computable biomedical knowledge (CBK). But the management of CBK comes with a range of significant computer science challenges. Some of these have been suitably addressed through the development of CBK methods and tools, while others require further research and development. We review the main challenges associated with creating, reasoning with and sharing CBK, and describe current state-of-the-art solutions as well as outstanding issues. We argue that a radical approach, in which all evidence generation is suitable for computation at the outset, is ultimately needed to take full advantage of CBK.
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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.