ArticleJournal of the American Medical Informatics Association : JAMIA2021
Data Consult Service: Can we use observational data to address immediate clinical needs?
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. 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.
- The Role of Data Science in Closing the Implementation Gap.Critical care clinics · 2023Review
- Building a Learning Health System: Creating an Analytical Workflow for Evidence Generation to Inform Institutional Clinical Care Guidelines.Applied clinical informatics · 2022Article
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
Abstract
objectiveA number of clinical decision support tools aim to use observational data to address immediate clinical needs, but few of them address challenges and biases inherent in such data. The goal of this article is to describe the experience of running a data consult service that generates clinical evidence in real time and characterize the challenges related to its use of observational data. MATERIALS AND
methodsIn 2019, we launched the Data Consult Service pilot with clinicians affiliated with Columbia University Irving Medical Center. We created and implemented a pipeline (question gathering, data exploration, iterative patient phenotyping, study execution, and assessing validity of results) for generating new evidence in real time. We collected user feedback and assessed issues related to producing reliable evidence.
resultsWe collected 29 questions from 22 clinicians through clinical rounds, emails, and in-person communication. We used validated practices to ensure reliability of evidence and answered 24 of them. Questions differed depending on the collection method, with clinical rounds supporting proactive team involvement and gathering more patient characterization questions and questions related to a current patient. The main challenges we encountered included missing and incomplete data, underreported conditions, and nonspecific coding and accurate identification of drug regimens.
conclusionsWhile the Data Consult Service has the potential to generate evidence and facilitate decision making, only a portion of questions can be answered in real time. Recognizing challenges in patient phenotyping and designing studies along with using validated practices for observational research are mandatory to produce reliable evidence.
Indexed as
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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.