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Impact of integrated medication management program on medication errors in a medical center: an interrupted time series study

BACKGROUND: Medication errors (MEs) are harmful to patients during hospitalization, especially elderly patients. To reduce MEs, an integrated medication management (IMM) model was developed in a 2500-bed medical center, allowing a clinical pharmacist to participate in the daily ward round and perfor...

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Autores principales: Chen, Kuan-Lin, Hunag, Chih-Fen, Sheng, Wang-Huei, Chen, Yu-Kuei, Wang, Chi-Chuan, Shen, Li-Jiuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210585/
https://www.ncbi.nlm.nih.gov/pubmed/35725537
http://dx.doi.org/10.1186/s12913-022-08178-w
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author Chen, Kuan-Lin
Hunag, Chih-Fen
Sheng, Wang-Huei
Chen, Yu-Kuei
Wang, Chi-Chuan
Shen, Li-Jiuan
author_facet Chen, Kuan-Lin
Hunag, Chih-Fen
Sheng, Wang-Huei
Chen, Yu-Kuei
Wang, Chi-Chuan
Shen, Li-Jiuan
author_sort Chen, Kuan-Lin
collection PubMed
description BACKGROUND: Medication errors (MEs) are harmful to patients during hospitalization, especially elderly patients. To reduce MEs, an integrated medication management (IMM) model was developed in a 2500-bed medical center, allowing a clinical pharmacist to participate in the daily ward round and perform medication reconciliation and medication reviews. This study aimed to evaluate the impact of the IMM model on MEs and medication utilization using a quasi-experimental design. METHODS: We conducted an interrupted time-series study using the aggregated data of monthly admissions from two wards of a medical center, where one ward served as the intervention and the other served as the external control. The pre- and post-intervention phases comprised of 40 and 12 monthly observational units, respectively. The primary outcome was the mean number of ME reports, which were further investigated for different ME types. The mean number of daily inpatient prescriptions, mean number of daily self-prepared medications, and median daily medication costs were measured. All outcomes were measured per admission episode. Segmented regression was used to evaluate the level and slope changes in the outcomes after IMM model implementation, and subgroup analyses were performed to examine the effects on different groups. RESULTS: After IMM model implementation, the mean number of ME reports increased (level change: 1.02, 95% confidence interval [CI]: 0.68 to 1.35, P < 0.001). The number of reports has shown a dramatic increase in omissions or medication discrepancies, inappropriate drug choices, and inappropriate routes or formulations. Furthermore, the mean number of daily inpatient prescriptions was reduced for patients aged ≥75 years (level change: −1.78, 95% CI: −3.06 to −0.50, P = 0.009). No significant level or slope change was observed in the control ward during the post-intervention phase. CONCLUSIONS: The IMM model improved patient safety and optimized medication utilization by increasing the reporting of MEs and decreasing the number of medications used. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08178-w.
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spelling pubmed-92105852022-06-22 Impact of integrated medication management program on medication errors in a medical center: an interrupted time series study Chen, Kuan-Lin Hunag, Chih-Fen Sheng, Wang-Huei Chen, Yu-Kuei Wang, Chi-Chuan Shen, Li-Jiuan BMC Health Serv Res Research BACKGROUND: Medication errors (MEs) are harmful to patients during hospitalization, especially elderly patients. To reduce MEs, an integrated medication management (IMM) model was developed in a 2500-bed medical center, allowing a clinical pharmacist to participate in the daily ward round and perform medication reconciliation and medication reviews. This study aimed to evaluate the impact of the IMM model on MEs and medication utilization using a quasi-experimental design. METHODS: We conducted an interrupted time-series study using the aggregated data of monthly admissions from two wards of a medical center, where one ward served as the intervention and the other served as the external control. The pre- and post-intervention phases comprised of 40 and 12 monthly observational units, respectively. The primary outcome was the mean number of ME reports, which were further investigated for different ME types. The mean number of daily inpatient prescriptions, mean number of daily self-prepared medications, and median daily medication costs were measured. All outcomes were measured per admission episode. Segmented regression was used to evaluate the level and slope changes in the outcomes after IMM model implementation, and subgroup analyses were performed to examine the effects on different groups. RESULTS: After IMM model implementation, the mean number of ME reports increased (level change: 1.02, 95% confidence interval [CI]: 0.68 to 1.35, P < 0.001). The number of reports has shown a dramatic increase in omissions or medication discrepancies, inappropriate drug choices, and inappropriate routes or formulations. Furthermore, the mean number of daily inpatient prescriptions was reduced for patients aged ≥75 years (level change: −1.78, 95% CI: −3.06 to −0.50, P = 0.009). No significant level or slope change was observed in the control ward during the post-intervention phase. CONCLUSIONS: The IMM model improved patient safety and optimized medication utilization by increasing the reporting of MEs and decreasing the number of medications used. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08178-w. BioMed Central 2022-06-20 /pmc/articles/PMC9210585/ /pubmed/35725537 http://dx.doi.org/10.1186/s12913-022-08178-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Kuan-Lin
Hunag, Chih-Fen
Sheng, Wang-Huei
Chen, Yu-Kuei
Wang, Chi-Chuan
Shen, Li-Jiuan
Impact of integrated medication management program on medication errors in a medical center: an interrupted time series study
title Impact of integrated medication management program on medication errors in a medical center: an interrupted time series study
title_full Impact of integrated medication management program on medication errors in a medical center: an interrupted time series study
title_fullStr Impact of integrated medication management program on medication errors in a medical center: an interrupted time series study
title_full_unstemmed Impact of integrated medication management program on medication errors in a medical center: an interrupted time series study
title_short Impact of integrated medication management program on medication errors in a medical center: an interrupted time series study
title_sort impact of integrated medication management program on medication errors in a medical center: an interrupted time series study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210585/
https://www.ncbi.nlm.nih.gov/pubmed/35725537
http://dx.doi.org/10.1186/s12913-022-08178-w
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