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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Interacting with Genomic Data: Clinician Requirements and Prototype Structure.

Dana Bradford1, Shlomo Berkovsky1, Melissa Martyn2

  • 1Australian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation, Australia.

Studies in Health Technology and Informatics
|July 31, 2017
PubMed
Summary
This summary is machine-generated.

Genomic sequencing in healthcare requires clinician support tools. Engaging clinicians in development optimizes the adoption of these personalized medicine advancements for better patient diagnosis and treatment.

Keywords:
Clinician decision support toolclinician portaldata repositorygenomic sequencinghuman computer interactionuser centric design

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Area of Science:

  • Genomic medicine
  • Clinical informatics
  • Personalized healthcare

Background:

  • Genomic sequencing is transforming healthcare and personalized medicine.
  • Clinicians need access to genomic data and decision support for effective use.
  • Integrating genomic data into clinical practice is crucial for advancing patient care.

Purpose of the Study:

  • To define specifications for a clinician portal supporting genomic data use.
  • To outline the development of a decision support tool for clinicians.
  • To explore methods for evaluating the adoption and impact of genomic technologies.

Main Methods:

  • Utilized data from clinician workshops and interviews.
  • Conducted horizon scanning of relevant technologies.
  • Defined preliminary clinician portal specifications based on user needs.

Main Results:

  • A preliminary structure for a clinician decision support tool was developed.
  • Specifications for a clinician portal were defined through user engagement.
  • A framework for technology evaluation was proposed.

Conclusions:

  • Clinician engagement is key to developing relevant and adoptable genomic decision support tools.
  • A structured approach to tool development and evaluation is necessary for successful genomic medicine implementation.
  • Future work should focus on refining and evaluating the proposed decision support tool in clinical settings.