ArticleEGEMS (Washington, DC)2016
A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine.
Article in EGEMS (Washington, DC), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03548779 (North Carolina Genomic Evaluation by Next-generation Exome Sequencing, 2), which is not on this 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.
North Carolina Genomic Evaluation by Next-generation Exome Sequencing, 2
Who cites it
5 citing papers in PubMed.
- Meeting the challenge: Health information technology's essential role in achieving precision medicine.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- A Model Information Management Plan for Molecular Pathology Sequence Data Using Standards: From Sequencer to Electronic Health Record.The Journal of molecular diagnostics : JMD · 2019Article
- Prospects and challenges for clinical decision support in the era of big data.JCO clinical cancer informatics · 2018Article
- Contributions from the 2016 Literature on Clinical Decision Support.Yearbook of medical informatics · 2017Review
- Individualized Knowledge Graph: A Viable Informatics Path to Precision Medicine.Circulation research · 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
7 authors.
Funding
Abstract
introductionIn genomics and other fields, it is now possible to capture and store large amounts of data in electronic medical records (EMRs). However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients. Nevertheless, the use of large-scale medical data is likely to grow. To meet emerging challenges and facilitate optimal use of genomic data, our institution initiated a comprehensive planning process that addresses the needs of all stakeholders (e.g., patients, families, healthcare providers, researchers, technical staff, administrators). Our experience with this process and a key genomics research project contributed to the proposed framework. FRAMEWORK: We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the "Clinical Mendeliome" as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the "Archival Value Criterion" as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data. We describe a prototype Genomic CDSS that we developed as a first step toward implementation of the framework.
conclusionThe proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs. The framework also can be broadly applied to additional fields, including other '-omics' fields. We advocate for the creation of a Task Force on the Clinical Mendeliome, charged with defining Clinical Mendeliomes and drafting clinical guidelines for their use.
Indexed as
Identifiers
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.