Complexities and approaches for deriving longitudinal daily morphine milligram equivalents using electronic health record prescription data

TL;DR

This paper outlines the difficulties and methods for calculating daily opioid doses from electronic health records for a study on opioid reduction in chronic pain patients.

Contribution

The paper introduces a systematic approach to clean and analyze electronic prescription data for longitudinal opioid dose tracking.

Findings

8% of extracted prescriptions were unusable due to data issues.

Challenges included incomplete data and overlapping prescriptions.

Significant data cleaning is required before using prescription data in research.

Abstract

To describe challenges and solutions for calculating longitudinal daily opioid dose in morphine milligram equivalents from electronic health record prescriptions for a clinical trial of voluntary opioid reduction in patients with chronic non-cancer pain.

Researchers obtained opioid prescriptions for 525 participants from the National Patient-Centered Clinical Research Network datamart at three health systems. Daily opioid dose was calculated using dose conversions and summing across prescriptions after applying assumptions, reviewing suspect prescribing patterns, and removing spurious prescriptions.

Out of 16 071 extracted prescriptions, 1207 (8%) were unusable, and 14 864 (92%) were analyzed.

Numerous challenges were identified related to incomplete data, inaccurate refill dates, and overlapping or duplicate prescriptions.

Using electronic prescription data to calculate daily doses of opioid consumption is challenging and requires significant cleaning prior to use in research. This paper recommends steps to review and clean electronic opioid prescription data.

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