A budget impact analysis of a clinical medication review of patients in an Irish university teaching hospital. (November 2018)

• Record Type: Journal Article
• Authors: Kearney, Alan; Walsh, Elaine K; Kirby, Ann; Halleran, Ciaran; Byrne, Derina; Haugh, Jennifer; Sahm, Laura J
• Is Part Of: Global & regional health technology assessment. Volume 2018(2018)
• Publication Date: 2018-11
• Subjects: Budget impact analysis -- cost analysis -- medication review -- pharmacy; Medical technology -- Evaluation -- Periodicals; Medical technology -- Economic aspects -- Periodicals; 610
• DOI: 10.1177/2284240318807726
• Languages: English
• ISSNs: 2284-2403

Abstract

To measure the net benefit of a pharmacist-led medication review in acute public hospitals. To identify and measure the resources used when completing a pharmacist-led medication review, an observational study was conducted in an acute urban university teaching hospital. Health Information and Quality Authority guidelines were used to value resources used in a pharmacist-led medication review. Model inputs included demographic data, probability of adverse drug events associated with the pharmacist interventions, estimates of future discharges and cost data. The cost of a pharmacist-led medication review and savings generated from avoidance of adverse drug events were estimated and projected over a 5-year period, using hospital discharge rates taken from the hospital inpatient enquiry system and the census of population. Using the per-patient cost of a medication review, the annual cost of delivering a bi-weekly medication review is projected to vary between €6 m and €6.4 m over a 5-year period from 2017 to 2021. The per-patient net benefit of a bi-weekly medication review is €45.88. Therefore, the projected annual net benefit of a bi-weekly medication review is between €29.5 m and €31.2 m over the 5-year period of 2017 to 2021. Introducing a pharmacist-led medication review for each inpatient saves in the short and longer term. The results are consistent with previous findings. Substantial savings were estimated, regardless of variation in model parameters tested in sensitivity analysis.