Prospective cohort study of opioid use after total knee arthroplasty in a single center.

OBJECTIVES: Fewer opioids prescribed for postoperative pain may help reduce the number of surplus opioids available in the community and decrease the risk of opioid dependence. Published data on patients' opioid use after total knee arthroplasty (TKA) are limited. METHODS: This was a prospective study designed to characterize opioid use after TKA. Patients who have undergone TKA and met inclusion criteria were recruited to complete a survey after orthopedic surgeon follow-up appointments approximately 2 and 6 weeks postoperatively. Questions included satisfaction with pain management strategies, type and quantity of medication prescribed, and quantity of leftover medication. Additional data on opioid use and baseline characteristics were determined through chart review. RESULTS: A total of 60 patients completed surveys after TKA. All patients spent at least 1 night in the hospital or skilled nursing facility with an average length of stay of 1.2 days and an average consumption of 5.2 tablets of oxycodone 5 mg equivalents. After discharge, the mean number of oxycodone 5 mg tablet equivalents prescribed in the initial prescription was 38.6, with an average of 72.6 prescribed over 6 weeks. Patients reported an average of 15.7 unused oxycodone 5 mg tablet equivalents. CONCLUSION: These results could help guide the development of TKA-specific opioid prescribing guidelines and confirm that patients are generally prescribed more opioids than they consume.

Assessing automated product selection success rates in transmissions between electronic prescribing and community pharmacy platforms.

OBJECTIVE: Wrong drug product errors occurring in community pharmacies often originate at the transcription stage. Electronic prescribing and automated product selection are strategies to reduce product selection errors. However, it is unclear how often automated product selection succeeds in outpatient pharmacy platforms. MATERIALS AND METHODS: The intake of over 800 e-prescriptions was observed at baseline and after intervention to assess the rate of automated product selection success. A dispensing accuracy audit was performed at baseline and postintervention to determine whether enhanced automated product selection would result in greater accuracy; data for both analyses were compared by 2x2 Chi square tests. In addition, an anonymous survey was sent to a convenience sample of 60 area community pharmacy managers. RESULTS: At baseline, 79.8% of 888 e-prescriptions achieved automated product selection. After the intervention period, 84.5% of 903 e-prescriptions achieved automated product selection (P = .008). Analysis of dispensing accuracy audits detected a slight but not statistically significant improvement in accuracy rate (99.3% versus 98.9%, P = .359). Fourteen surveys were returned, revealing that other community pharmacies experience similar automated product selection failure rates. DISCUSSION: Our results suggest that manual product selection by pharmacy personnel is required for a higher than anticipated proportion of e-prescriptions received and filled by community pharmacies, which may pose risks to both medication safety and efficiency. CONCLUSION: The question of how to increase automated product selection rates and enhance interoperability between prescriber and community pharmacy platforms warrants further investigation.