Data Consult Service: Can we use observational data to address immediate clinical needs?
| Autor: | George Hripcsak, Patrick B. Ryan, Philip Zachariah, Anna Ostropolets, Ruijun Chen |
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| Rok vydání: | 2021 |
| Předmět: |
Academic Medical Centers
Service (systems architecture) Computer science Communication Reproducibility of Results Health Informatics Information needs Evidence-based medicine 030204 cardiovascular system & hematology Research and Applications Clinical decision support system Data science 03 medical and health sciences Identification (information) 0302 clinical medicine Research Design Humans Observational study 030212 general & internal medicine Study Execution Referral and Consultation Coding (social sciences) |
| Zdroj: | J Am Med Inform Assoc |
| ISSN: | 1527-974X |
| DOI: | 10.1093/jamia/ocab122 |
| Popis: | Objective A 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 Methods In 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. Results We 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. Conclusions While 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. |
| Databáze: | OpenAIRE |
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