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Electronic Health Record Recording of Patient Pain: Challenges and Discrepancies

  • Regenerative Pain Medicine/Interventional Pain Medicine (E Cornett Bradley, Section Editor)
  • Published:
Current Pain and Headache Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

In the present review, various categories of pain, clinician-observed pain scales, and patient-reported pain scales are evaluated to better understand factors that impact patient pain perceptions. Additionally, the expansion of areas that require further research to determine the optimal way to evaluate pain scale data for treatment and management are discussed.

Recent Findings

Electronic health record (EHR) data provides a starting point for evaluating whether patient predictors influence postoperative pain. There are several ways to assess pain and choosing the most effective form of pain treatment. Identifying individuals at high risk for severe postoperative pain enables more effective pain treatment. However, there are discrepancies in patient pain reporting dependent on instruments used to measure pain and their storage in the EHR. Additionally, whether administered by a physician or another healthcare practitioner, differences in patient pain perception occur. While each scale has distinct advantages and limitations, pain scale data is a valuable therapeutic tool for assisting clinicians in providing patients with optimal pain control. Accurate assessment of patient pain perceptions by data extraction from electronic health records provides a potential for pain alleviation improvement.

Summary

Predicting high-risk postoperative pain syndromes is a difficult clinical challenge. Numerous studies have been conducted on factors that impact pain prediction. Postoperative pain is significantly predicted by the kind of operation, the existence of prior discomfort, patient anxiety, and age.

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Data Availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Author information

Author notes

  1. Sahar Shekoohi

    Present address: Department of Anesthesiology, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA

Authors and Affiliations

  1. School of Medicine, Louisiana State University Health Sciences Center New Orleans, 433 Bolivar Street, New Orleans, LA, 70112, USA

    Yasmeen Kawji, Hanna Almoaswes, Claire Bise, Adrienne Murphy & Tanner D. Reed

  2. Department of Internal Medicine, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA

    Lena Kawji

  3. Department of Radiology, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA

    Rachel J. Klapper

  4. Department of Anesthesiology, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA

    Shahab Ahmadzadeh, Elyse M. Cornett & Alan D. Kaye

  5. Departments of Anesthesiology and Pharmacology, Toxicology, and Neurosciences, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA

    Alan D. Kaye

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All authors listed have made a direct and intellectual contribution to the work and approved for publication.

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Correspondence to Sahar Shekoohi.

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Kawji, Y., Almoaswes, H., Bise, C. et al. Electronic Health Record Recording of Patient Pain: Challenges and Discrepancies. Curr Pain Headache Rep 27, 737–745 (2023). https://doi.org/10.1007/s11916-023-01170-x

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