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Methods of Documentation VII: EMR01:30

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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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Health Information Technology (HIT)
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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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Charting by Exception, or CBE, is a method of documentation used in healthcare, particularly in nursing, that focuses on documenting only significant or abnormal findings rather than recording every detail. This approach aims to streamline the documentation process, improve efficiency, and ensure that healthcare providers can quickly identify deviations from normalcy in patient assessments.
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Source-oriented records, or SOR, are medical record-keeping organized by the data source. The SOR system was first developed in the mid-1900s to organize the growing patient data in hospitals and other healthcare facilities.
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Manually Abstracted versus Electronic Health Record Data for Surgical Quality Improvement.

James L Galloway1, Vivi W Chen2, Jennifer Kramer3

  • 1Veterans Affairs Quality Scholars Program, Atlanta VA Health Care System, Decatur, Georgia; Department of Surgery, Emory University School of Medicine, Atlanta, Georgia.

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Automating data collection for the Veterans Affairs Surgical Quality Improvement Program (VASQIP) using electronic health records (EHR) shows high accuracy for most variables. This automation can enhance surgical quality improvement (QI) programs by saving resources and improving data timeliness.

Keywords:
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Area of Science:

  • Health Informatics
  • Surgical Quality Improvement
  • Data Science in Healthcare

Background:

  • Manual data abstraction is the benchmark for surgical quality improvement (QI) programs.
  • Automating data collection can significantly benefit QI initiatives by reducing resource demands.
  • The Veterans Affairs Surgical Quality Improvement Program (VASQIP) relies on manual abstraction.

Purpose of the Study:

  • To assess the accuracy and concordance of electronic health record (EHR)-derived variables compared to manually abstracted VASQIP variables.
  • To determine the feasibility of automating data collection for VASQIP.
  • To evaluate the potential of EHR data for enhancing surgical QI.

Main Methods:

  • A national, cross-sectional analysis comparing EHR-derived VASQIP variable correlates with manually abstracted VASQIP variables (2016-2020).
  • Used Cohen's kappa, sensitivity, specificity, and predictive values to measure agreement.
  • Defined strong agreement as kappa ≥80%.

Main Results:

  • Evaluated 533,164 cases across 113 hospitals.
  • High agreement (median kappa 98.1%) for race and ethnicity.
  • Variable agreement for preoperative risk factors (median 28.6%) and postoperative complications (median 15.1%).
  • Strong agreement for preoperative labs (median 91.9%) and intraoperative factors (median 93.9%).

Conclusions:

  • EHR-derived correlates demonstrate high accuracy for automating data collection for many VASQIP variables, excluding postoperative complications.
  • Automation can reduce manual data abstraction resources.
  • Increased timeliness and robustness of surgical QI programs are achievable through EHR data utilization.