Chukwuma Anyanwu1, Oliver Egwim2. 1. Consultant for Managed Care and Clinical Outcomes, Bizmart Pharmacy Group, Houston, TX, and was Clinical Pharmacist-QA/Anesthesiology/OR, Department of In-Patient Pharmacy, Ben Taub Hospital, Harris Health System, Houston, during this study. 2. Pharmacy Operations Manager, Department of In-Patient Pharmacy, Ben Taub Hospital, Harris Health System, Houston.
Abstract
BACKGROUND: Healthcare institutions are often faced with challenges and accreditation requirements for improving treatment quality, reducing waste, and avoiding diversion of drugs, particularly controlled substances. Many automated systems have replaced manual systems but may be fraught with challenges, especially when multiple users are involved. OBJECTIVE: To describe the characteristics of controlled substance discrepancies observed in a Level I trauma hospital for Medicare. METHODS: Discrepancy data were captured for each user involved in a transaction for a controlled substance at the Level I trauma hospital (in Ben Taub Hospital, Houston, TX), and the information was stored in a computerized database repository. Data for the 1-year study period (from January 1 through December 31, 2013) were collected for Medicare beneficiaries, using an Excel 2013 spreadsheet, and were analyzed according to basic discrepancy characteristics and descriptive statistics. RESULTS: During the 12-month study period, 114,000 controlled substance discrepancies were found for 100,000 Medicare patients at this Level I trauma hospital. Vending activities accounted for the majority (52.6%) of these discrepancies. Discrepancies were most likely to occur on Wednesdays, and the medications involved most frequently were combination drugs of hydrocodone and acetaminophen. CONCLUSION: Approximately 1 (1.14) discrepancy involving a controlled substance occurred for each Medicare patient treated at the study facility. Healthcare institutions need to improve their efforts to ensure high-quality care and prevent diversion of drugs.
BACKGROUND: Healthcare institutions are often faced with challenges and accreditation requirements for improving treatment quality, reducing waste, and avoiding diversion of drugs, particularly controlled substances. Many automated systems have replaced manual systems but may be fraught with challenges, especially when multiple users are involved. OBJECTIVE: To describe the characteristics of controlled substance discrepancies observed in a Level I trauma hospital for Medicare. METHODS: Discrepancy data were captured for each user involved in a transaction for a controlled substance at the Level I trauma hospital (in Ben Taub Hospital, Houston, TX), and the information was stored in a computerized database repository. Data for the 1-year study period (from January 1 through December 31, 2013) were collected for Medicare beneficiaries, using an Excel 2013 spreadsheet, and were analyzed according to basic discrepancy characteristics and descriptive statistics. RESULTS: During the 12-month study period, 114,000 controlled substance discrepancies were found for 100,000 Medicare patients at this Level I trauma hospital. Vending activities accounted for the majority (52.6%) of these discrepancies. Discrepancies were most likely to occur on Wednesdays, and the medications involved most frequently were combination drugs of hydrocodone and acetaminophen. CONCLUSION: Approximately 1 (1.14) discrepancy involving a controlled substance occurred for each Medicare patient treated at the study facility. Healthcare institutions need to improve their efforts to ensure high-quality care and prevent diversion of drugs.
Entities:
Keywords:
Level I trauma hospital; Medicare patients; automated dispensation; controlled substances; discrepancies; drug diversion
Authors: Steven R McClure; Brian C O'Neal; Dennis Grauer; Rick J Couldry; Allison R King Journal: Am J Health Syst Pharm Date: 2011-04-15 Impact factor: 2.637
Authors: Richard Gentry Wilkerson; Hong K Kim; Thomas Andrew Windsor; Darren P Mareiniss Journal: Emerg Med Clin North Am Date: 2016-02-17 Impact factor: 2.264
Authors: Jenny E Dolan; Hannah Lonsdale; Luis M Ahumada; Amish Patel; Jibin Samuel; Ali Jalali; Jacquelin Peck; JoAnn C DeRosa; Mohamed Rehman; Anna M Varughese; Allison M Fernandez Journal: Appl Clin Inform Date: 2019-07-31 Impact factor: 2.342