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Performing an Informatics Consult: Methods and Challenges.

Alejandro Schuler1, Alison Callahan1, Kenneth Jung1

  • 1Center for Biomedical Informatics Research, Stanford University, Stanford, California.

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|February 4, 2018
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Summary
This summary is machine-generated.

This study introduces an informatics consult service that uses aggregated patient data to provide practice-based evidence at the bedside. This approach aims to reduce healthcare waste and improve patient outcomes by translating scientific insights into clinical practice.

Keywords:
Learning health systemclinical informaticsobservational studypractice-based evidence

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Area of Science:

  • Health Informatics
  • Clinical Research
  • Data Science

Background:

  • Healthcare systems face challenges with underutilized patient data, leading to missed opportunities, waste, and patient harm.
  • Translating scientific insights into clinical practice remains a significant hurdle in improving healthcare delivery.
  • Existing systems often overlook valuable evidence that could enhance patient care.

Purpose of the Study:

  • To develop and describe a novel informatics consult service.
  • To bridge the gap between practicing physicians and clinical researchers/data scientists.
  • To enable the use of aggregate patient data for practice-based evidence at the point of care.

Main Methods:

  • Clinician questions are processed and classified.
  • Relevant aggregate patient data are identified and extracted.
  • Data undergo rigorous analysis to generate actionable answers.
  • A 48-hour response time is targeted for informatics consults.

Main Results:

  • The informatics consult service facilitates direct physician engagement with data scientists and researchers.
  • Methods for data extraction, processing, and analysis within the consult are detailed.
  • The service aims to provide timely, evidence-based answers to clinical questions.

Conclusions:

  • The informatics consult service is a key component in moving towards a learning healthcare system.
  • Directly connecting clinicians with data expertise enhances the utilization of patient data.
  • Continuous refinement of the service is ongoing to maximize its impact on healthcare quality.