ArticleMMWR supplements2024
A Standard Framework for Evaluating Large Health Care Data and Related Resources.
Article in MMWR supplements, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Case Definitions and Data Sources for NNCSS Parkinson Disease Surveillance: A Systematic Review.JAMA network open · 2026Pooled it
- Implementing a digital audit-and-feedback surveillance system for diabetic ketoacidosis: study protocol for the DEKODE programme.Frontiers in health services · 2026Article
- Healthcare claims and health interview survey data for chronic disease surveillance: agreement and comparative validity of prevalence indicators for 20 chronic conditions in a general population sample in France.European journal of public health · 2025Article
- Enhanced data quality to improve malaria surveillance in Papua, Indonesia.Malaria journal · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since 2000, the availability and use of large health care data and related resources for conducting surveillance, research, and evaluations to guide clinical and public health decision-making has increased rapidly. These trends have been related to transformations in health care information technology and public as well as private-sector efforts for collecting, compiling, and supplying large volumes of data. This growing collection of robust and often timely data has enhanced the capability to increase the knowledge base guiding clinical and public health activities and also has increased the need for effective tools to assess the attributes of these resources and identify the types of scientific questions they are best suited to address. This: MMWR supplement presents a standard framework for evaluating large health care data and related resources, including constructs, criteria, and tools that investigators and evaluators can apply and adapt.
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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.