ArticleEGEMS (Washington, DC)2013
Using multifactorial experiments for comparative effectiveness research in physician practices with electronic health record.
Article in EGEMS (Washington, DC), 2013. 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.
- Adapting Evaluations of Alternative Payment Models to a Changing Environment.Health services research · 2018Article
- Analytical Methods for a Learning Health System: 2. Design of Observational Studies.EGEMS (Washington, DC) · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Two key challenges related to conducting comparative effectiveness research are the lack of available data and the lack of rigorous techniques for efficiently and quickly testing the effectiveness of the many possible ways of implementing components of care. The confluence of two things offers the promise of overcoming these challenges: (1) the increased adoption of electronic health records (EHRs), which can provide easier access to clinical information, and (2) burgeoning appreciation for an under-used but powerful statistical research and evaluation method for multifactor interventions known as multifactor experimental design. The use of multifactorial experiments paired with EHR data has great potential to help providers conduct rapid-cycle comparative effectiveness research and examine alternative ways of implementing care. Its power is its ability to enable scientifically rigorous testing of many facets of care provision simultaneously in real-world settings where change is ongoing. In this paper, we identify the opportunities for using efficient multifactorial designs and EHR data to evaluate quality-improvement efforts in physician practices. We illustrate the power of multifactorial designs through several examples relevant to physician practices with EHRs, such as evaluating clinical decision support features and studying components of a patient-centered medical home.
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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.