Purpose: This study analyzed the efficacy of Post-Ease, a custom essential oil aromatherapy blend, in decreasing postoperative nausea and vomiting (PONV) and the need for antiemetic drugs in an orthopaedic surgical population. Study Design: This is retrospective cohort study, utilizing electronic health record data pre- and post-implementation of a nurse-driven quality improvement intervention. Methods: The study examined the impact of an inhaled custom blend of essential oils containing lavender, peppermint, ginger and lemon to assist in decreasing PONV and reduce the use of antiemetic medications. Data on the use of antiemetic drugs in pre- and post-intervention periods were analyzed. Findings: Nurses provided the Post-Ease blend 384 times in 2020 to patients as an option before proceeding, if necessary, to antiemetic drugs. The intervention group demonstrated a statistically significant reduction in the number of unique surgical patients’ need for antiemetics as treatment (22%; p = .05). Similarly, the total doses of antiemetics administered was significantly reduced (21%; p ≤ .05) during the study period. Conclusion: This study supports the use of aromatherapy to reduce PONV and minimize antiemetic use in an orthopaedic population.

Low back pain related to work injury has major socioeconomic implications. Theoretically, the early detection of patients at risk for continued work disability after 6 months of work absence, and of those with a recurrence of pain (RP) and leave work once again, should be cost-effective if combined with effective intervention. The objective of this prospective research was to analyze the cost-effectiveness of a detection-intervention system (DIS) developed from a logistic predictive model of work status. A sample of newly injured workers (N=135 males) were assessed following a first episode of compensated low back pain. A predictive biopsychosocial profile was obtained from a series of univariate and multivariate regression analyses. Structural diagnosis, pain rating, length of inactivity before treatment, negative life changes, and self-efficacy expectancies were found to be best predictors. With a correct classification rate of 72% the predictive model parameters (sensitivity and specificity) were chosen in order to reduce the number of false negatives (recurrence of pain or chronic patients not detected). The calculation of the cost/benefit proportions reveals that the detection-intervention system generates savings of up to $39,595 Can./100 patients a year. By combining low treatment expenses ($250 Can to $1,000 Can.) and increasing the success rates (40-75% return to work), the detection-intervention system is potentially more cost effective than the current approach without detection-intervention.

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