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Agreement between Patient-reported Pain Medication Use and Electronic Medical Record Data in Surgical Amputation
Carrie A Kubiak1, Jennifer C Lee1, Jennifer B Hamill1
1From the Department of Surgery, Section of Plastic Surgery, Michigan Medicine, Ann Arbor, Mich.
Background:
Opioid misuse after surgery remains a public health crisis in the United States. Recent efforts have focused on tracking pain medication use in surgical populations. However, accurate interpretations of medication use remain quite challenging given inconsistent usage of different datasets. The purpose of this study was to investigate the agreement between electronic medical records (EMR) versus patient self-reported use of pain medications in a surgical amputation population.
Methods:
Patients undergoing major lower extremity amputation or amputation-related procedures were included in this study. Both self-reported and EMR data for pain medication intake were obtained for each patient at three time points (preoperatively, 4 months postoperatively, and 12 months postoperatively). Percentage agreement and the kappa statistic were calculated for both usage (yes/no) and dose categories.
Results:
Forty-five patients were included in this study, resulting in 108 pairs of self-reported and EMR datasets. Substantial levels of agreement (>70% agreement, kappa >0.61) for opioid use was seen at preoperative and 12 months postoperative. However, agreement dropped at 4 months postoperatively. Anticonvulsant medication showed high levels, whereas acetaminophen showed lower levels of agreements at all time points.
Conclusions:
Either self-reported or EMR data may be used in research and clinical settings for preoperative or 12-month postoperative patients with little concern for discrepancies. However, at time points immediately following the expected end of acute surgical pain, self-reported data may be needed for more accurate medication reporting. With these findings in mind, usage of datasets should be driven by study objectives and the dataset's strength (eg, accuracy, ease, lack of bias).
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