Bettina Wulff Risør1, Marianne Lisby2, Jan Sørensen3. 1. Centre for Health Economics Research (COHERE), Department of Public Health, University of Southern Denmark, Odense C, Denmark; Hospital Pharmacy, Aarhus C, Denmark. Electronic address: bettriso@rm.dk. 2. Research Centre of Emergency Medicine, Aarhus University Hospital, Aarhus C, Denmark. 3. Centre for Health Economics Research (COHERE), Department of Public Health, University of Southern Denmark, Odense C, Denmark; Healthcare Outcome Reseach Centre, Royal College of Surgeons in Ireland, Dublin, Ireland.
Abstract
OBJECTIVES: To evaluate the cost-effectiveness of an automated medication system (AMS) implemented in a Danish hospital setting. METHODS: An economic evaluation was performed alongside a controlled before-and-after effectiveness study with one control ward and one intervention ward. The primary outcome measure was the number of errors in the medication administration process observed prospectively before and after implementation. To determine the difference in proportion of errors after implementation of the AMS, logistic regression was applied with the presence of error(s) as the dependent variable. Time, group, and interaction between time and group were the independent variables. The cost analysis used the hospital perspective with a short-term incremental costing approach. The total 6-month costs with and without the AMS were calculated as well as the incremental costs. The number of avoided administration errors was related to the incremental costs to obtain the cost-effectiveness ratio expressed as the cost per avoided administration error. RESULTS: The AMS resulted in a statistically significant reduction in the proportion of errors in the intervention ward compared with the control ward. The cost analysis showed that the AMS increased the ward's 6-month cost by €16,843. The cost-effectiveness ratio was estimated at €2.01 per avoided administration error, €2.91 per avoided procedural error, and €19.38 per avoided clinical error. CONCLUSIONS: The AMS was effective in reducing errors in the medication administration process at a higher overall cost. The cost-effectiveness analysis showed that the AMS was associated with affordable cost-effectiveness rates.
OBJECTIVES: To evaluate the cost-effectiveness of an automated medication system (AMS) implemented in a Danish hospital setting. METHODS: An economic evaluation was performed alongside a controlled before-and-after effectiveness study with one control ward and one intervention ward. The primary outcome measure was the number of errors in the medication administration process observed prospectively before and after implementation. To determine the difference in proportion of errors after implementation of the AMS, logistic regression was applied with the presence of error(s) as the dependent variable. Time, group, and interaction between time and group were the independent variables. The cost analysis used the hospital perspective with a short-term incremental costing approach. The total 6-month costs with and without the AMS were calculated as well as the incremental costs. The number of avoided administration errors was related to the incremental costs to obtain the cost-effectiveness ratio expressed as the cost per avoided administration error. RESULTS: The AMS resulted in a statistically significant reduction in the proportion of errors in the intervention ward compared with the control ward. The cost analysis showed that the AMS increased the ward's 6-month cost by €16,843. The cost-effectiveness ratio was estimated at €2.01 per avoided administration error, €2.91 per avoided procedural error, and €19.38 per avoided clinical error. CONCLUSIONS: The AMS was effective in reducing errors in the medication administration process at a higher overall cost. The cost-effectiveness analysis showed that the AMS was associated with affordable cost-effectiveness rates.
Authors: Charlotte Arp Sørensen; Annette de Thurah; Marianne Lisby; Charlotte Olesen; Signe Bredsgaard Sørensen; Ulrika Enemark Journal: Ther Adv Drug Saf Date: 2020-08-29
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Authors: Hamimatul Hayat Abdul Nasir; Hui Poh Goh; Daniel Vui Teck Wee; Khang Wen Goh; Kah Seng Lee; Andi Hermansyah; Yaser Mohammed Al-Worafi; Long Chiau Ming Journal: Int J Environ Res Public Health Date: 2022-09-09 Impact factor: 4.614