An analysis of errors, discrepancies, and variation in opioid prescriptions for adult outpatients at a teaching hospital

Authors

  • Mark C. Bicket, MD
  • Deepa Kattail, MD
  • Myron Yaster, MD
  • Christopher L. Wu, MD
  • Peter Pronovost, MD, PhD

DOI:

https://doi.org/10.5055/jom.2017.0367

Keywords:

opioid analgesics, pain medication, medication use, prescription error

Abstract

Objective: To determine opioid-prescribing patterns and rate of three types of errors, discrepancies, and variation from ideal practice.

Design: Retrospective review of opioid prescriptions processed at an outpatient pharmacy.

Setting: Tertiary institutional medical center.

Patients: We examined 510 consecutive opioid medication prescriptions for adult patients processed at an institutional outpatient pharmacy in June 2016 for patient, provider, and prescription characteristics.

Main Outcome Measure(s): We analyzed prescriptions for deviation from best practice guidelines, lack of two patient identifiers, and noncompliance with Drug Enforcement Agency (DEA) rules.

Results: Mean patient age (standard deviation) was 47.5 years (17.4). The most commonly prescribed opioid was oxycodone (71 percent), usually not combined with acetaminophen. Practitioners prescribed tablet formulation to 92 percent of the sample, averaging 57 (47) pills. We identified at least one error on 42 percent of prescriptions. Among all prescriptions, 9 percent deviated from best practice guidelines, 21 percent failed to include two patient identifiers and 41 percent were noncompliant with DEA rules. Errors occurred in 89 percent of handwritten prescriptions, 0 percent of electronic health record (EHR) computer-generated prescriptions, and 12 percent of non-EHR computer-generated prescriptions. Interrater reliability by κ was 0.993.

Conclusions: Inconsistencies in opioid prescribing remain common. Handwritten prescriptions continue to demonstrate higher associations of errors, discrepancies, and variation from ideal practice and government regulations. All computer-generated prescriptions adhered to best practice guidelines and contained two patient identifiers, and all EHR prescriptions were fully compliant with DEA rules.

Author Biographies

Mark C. Bicket, MD

Assistant Professor, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland

Deepa Kattail, MD

Assistant Professor, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland

Myron Yaster, MD

Professor, Children’s Hospital Colorado, University of Colorado-Anschutz Medical Campus, Aurora, Colorado

Christopher L. Wu, MD

Professor, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland

Peter Pronovost, MD, PhD

Professor, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland;Department of Surgery, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland

References

Colquhoun M, Koczmara C, Greenall J: Implementing system safeguards to prevent error-induced injury with opioids (narcotics): An ISMP Canada collaborative. Healthc Q. 2006; 9: 36-42.

Hicks RW: MEDMARX 5th anniversary data report: A chartbook of 2003 findings and trends 1999–2003. Medical Benefits. 2005; 22: 10-11.

Leape LL: Systems analysis and redesign: The foundation of medical error prevention. In Cohen MR (ed): Medication Errors. 2nd ed. Washington, DC: American Pharmaceutical Association, 2007: 3-14.

Heneka N, Shaw T, Rowett D, et al.: Quantifying the burden of opioid medication errors in adult oncology and palliative care settings: A systematic review. Palliat Med. 2016; 30(6): 520-532.

Lee BH, Lehmann CU, Jackson EV, et al.: Assessing controlled substance prescribing errors in a pediatric teaching hospital: An analysis of the safety of analgesic prescription practice in the transition from the hospital to home. J Pain. 2009; 10(2): 160-166.

George JA, Park PS, Hunsberger J, et al.: An analysis of 34,218 pediatric outpatient controlled substance prescriptions. Anesth Analg. 2016; 122(3): 807-813.

Califf RM, Woodcock J, Ostroff S: A proactive response to prescription opioid abuse. N Engl J Med. 2016; 374(15): 1480-1485.

Institute for Safe Medication Practices: Electronic prescribing can reduce medication errors. 2000. Available at http://www.ismp.org/Newsletters/acutecare/articles/Whitepaper.asp. Accessed August 2, 2016.

Institute for Safe Medication Practices: ISMP's list of error-prone abbreviations, symbols, and dose designations. 2014. Available at http://www.ismp.org/Tools/errorproneabbreviations.pdf. Accessed August 2, 2016.

Rannazzisi JT, Caverly MW: Practitioner's manual: An informational outline of the controlled substances act. Washington, DC: United States Department of Justice Drug Enforcement Administration, Office of Diversion Control, 2006. Available at https://www.deadiversion.usdoj.gov/pubs/manuals/pract/pract_manual012508.pdf. Accessed August 1, 2016.

The Joint Commission: Ambulatory care national patient safety goals. 2016. Available at https://www.jointcommission.org/assets/1/6/2016_NPSG_AHC_ER.pdf. Accessed August 2,

The Joint Commission: National patient safety goals. 2016. Available at https://www.jointcommission.org/standards_information/npsgs.aspx. Accessed August 1, 2016.

Bates DW, Boyle DL, Vander Vliet MB, et al.: Relationship between medication errors and adverse drug events. J Gen Intern Med. 1995; 10(4): 199-205.

Meyer TA: Improving the quality of the order-writing process for inpatient orders and outpatient prescriptions. Am J Health Syst Pharm. 2000; 57(suppl 4): S18-S22.

Zimmer KP, Miller MR, Lee BH, et al.: Narcotic prescription writer: Use in medical error reduction. J Patient Saf. 2008; 4(2): 98-105.

Food and Drug Administration: Acetaminophen prescription combination drug products with more than 325 mg: FDA statement - recommendation to discontinue prescribing and dispensing. 2014. Available at http://www.fda.gov/Safety/MedWatch/SafetyInformation/SafetyAlertsforHumanMedicalProducts/ucm381650.htm, Accessed August 15, 2016.

Clark R, Fisher JE, Sketris IS, et al.: Population prevalence of high dose paracetamol in dispensed paracetamol/opioid prescription combinations: An observational study. BMC Clin Pharmacol. 2012; 12: 11.

Centers for Medicare & Medicaid Services: CMS releases prescriber-level Medicare data for first time. 2015. Available at https://www.cms.gov/newsroom/MediaReleaseDatabase/Fact-Sheets/2015-Fact-sheets-items/2015-04-30.html. Accessed August 15, 2016.

Michna E, Duh MS, Korves C, et al.: Removal of opioid/acetaminophen combination prescription pain medications: Assessing the evidence for hepatotoxicity and consequences of removal of these medications. Pain Med. 2010; 11(3): 369-378.

Food and Drug Administration: A guide to safe use of pain medicine. 2009. Available at http://www.fda.gov/ForConsumers/ConsumerUpdates/ucm095673.htm. Accessed August 20, 2016.

Dart RC, Surratt HL, Cicero TJ, et al.: Trends in opioid analgesic abuse and mortality in the United States. N Engl J Med. 2015; 372(3): 241-248.

Kharasch ED, Brunt LM: Perioperative opioids and public health. Anesthesiology. 2016; 124(4): 960-965.

Published

01/01/2017

How to Cite

Bicket, MD, M. C., D. Kattail, MD, M. Yaster, MD, C. L. Wu, MD, and P. Pronovost, MD, PhD. “An Analysis of Errors, Discrepancies, and Variation in Opioid Prescriptions for Adult Outpatients at a Teaching Hospital”. Journal of Opioid Management, vol. 13, no. 1, Jan. 2017, pp. 51-57, doi:10.5055/jom.2017.0367.