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Purpose of Health Records I01:11

Purpose of Health Records I

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The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
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Using Electronic Health Records To Generate Phenotypes For Research.

Sarah A Pendergrass1, Dana C Crawford2

  • 1Biomedical and Translational Informatics Institute, Geisinger Research, Rockville, Maryland.

Current Protocols in Human Genetics
|December 6, 2018
PubMed
Summary

Electronic health records (EHRs) offer valuable longitudinal patient data for research. Extracting high-quality variables through electronic phenotyping is crucial for unlocking the potential of EHRs in biomedical studies.

Keywords:
computable phenotypingelectronic health recordselectronic medical recordselectronic phenotypingprecision medicine

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Area of Science:

  • Biomedical Informatics
  • Clinical Data Research
  • Health Data Science

Background:

  • Electronic health records (EHRs) capture comprehensive patient data, including diagnoses, procedures, vitals, and notes.
  • Longitudinal data from repeated clinic visits in EHRs offer insights into disease progression and treatment response.
  • Widespread EHR adoption provides opportunities for population-scale real-world clinical data in research.

Purpose of the Study:

  • To describe common and emerging electronic phenotyping approaches for EHR data.
  • To identify limitations and biases in using clinically collected EHR data for research.
  • To facilitate the extraction of research-grade variables from clinical data warehouses.

Main Methods:

  • Review of electronic phenotyping methodologies applied to EHRs.
  • Analysis of data types within EHRs (e.g., billing codes, lab results, physician notes).
  • Assessment of data quality and potential biases for research applications.

Main Results:

  • EHRs contain rich longitudinal data suitable for various research applications.
  • Electronic phenotyping methods are essential for deriving research-ready variables from EHRs.
  • Limitations and biases in EHR data require careful consideration for accurate research findings.

Conclusions:

  • High-quality variable extraction from EHRs is key to realizing their research potential.
  • Understanding electronic phenotyping approaches and data limitations is critical for robust biomedical research.
  • EHR data, when properly processed, can significantly advance genetic association studies and other research.