Discrepancies in written versus calculated durations in opioid prescriptions: Pre-post study

Benjamin H. Slovis, John Kairys, Bracken Babula, Melanie Girondo, Cara Martino, Lindsey M. Roke, Jeffrey Riggio

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: The United States is in the midst of an opioid epidemic. Long-term use of opioid medications is associated with an increased risk of dependence. The US Centers for Disease Control and Prevention makes specific recommendations regarding opioid prescribing, including that prescription quantities should not exceed the intended duration of treatment. Objective: The purpose of this study was to determine if opioid prescription quantities written at our institution exceed intended duration of treatment and whether enhancements to our electronic health record system improved any discrepancies. Methods: We examined the opioid prescriptions written at our institution for a 22-month period. We examined the duration of treatment documented in the prescription itself and calculated a duration based on the quantity of tablets and doses per day. We determined whether requiring documentation of the prescription duration affected these outcomes. Results: We reviewed 72,314 opioid prescriptions, of which 16.96% had a calculated duration that was greater than what was documented in the prescription. Making the duration a required field significantly reduced this discrepancy (17.95% vs 16.21%, P<.001) but did not eliminate it. Conclusions: Health information technology vendors should develop tools that, by default, accurately represent prescription durations and/or modify doses and quantities dispensed based on provider-entered durations. This would potentially reduce unintended prolonged opioid use and reduce the potential for long-term dependence.

Original languageEnglish
Article numbere16199
JournalJMIR Medical Informatics
Volume8
Issue number3
DOIs
StatePublished - Mar 2020
Externally publishedYes

Keywords

  • Duration
  • Electronic health record
  • Informatics
  • Opioids
  • Prescription

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