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Drug-Drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in East Gojjam Zone, Amhara Regional State, Ethiopia

OBJECTIVES: This study was aimed to assess the type, prevalence, characteristics of drug interaction and factors associated from admitted patients in medical wards at primary, district and referral hospitals in East Gojjam Zone, Amhara Regional State, Ethiopia. METHODS: A facility-based retrospectiv...

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Autores principales: Tessema, Zenaw, Yibeltal, Desalegn, Wubetu, Muluken, Dessie, Bekalu, Molla, Yalew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312158/
https://www.ncbi.nlm.nih.gov/pubmed/34367641
http://dx.doi.org/10.1177/20503121211035050
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author Tessema, Zenaw
Yibeltal, Desalegn
Wubetu, Muluken
Dessie, Bekalu
Molla, Yalew
author_facet Tessema, Zenaw
Yibeltal, Desalegn
Wubetu, Muluken
Dessie, Bekalu
Molla, Yalew
author_sort Tessema, Zenaw
collection PubMed
description OBJECTIVES: This study was aimed to assess the type, prevalence, characteristics of drug interaction and factors associated from admitted patients in medical wards at primary, district and referral hospitals in East Gojjam Zone, Amhara Regional State, Ethiopia. METHODS: A facility-based retrospective cross-sectional study design was conducted among admitted patients in medical wards at different hospitals of East Gojjam Zone from September 2019 to February 2020. Patient-specific data were extracted from patient medical prescription papers using a structured data collection tool. Potential drug–drug interaction was identified using www.drugs.com as drug–drug interaction checker. Data were analyzed using SPSS version 23.0. To identify the explanatory predictors of potential drug–drug interaction, logistic regression analysis was done at a statistical significance level of p-value < 0.05. RESULTS: Of the total 554 prescriptions, 51.1% were prescribed for females with a mean (±standard deviation) age of 40.85 ± 23.09 years. About 46.4% prescriptions of patients had one or more comorbid conditions, and the most frequent identified comorbid conditions were infectious (18.6%) and cardiac problems (6.3%) with 0.46 ± 0.499 average number of comorbid conditions per patient. Totally, 1516 drugs were prescribed with 2.74 ± 0.848 mean number per patient and range of 2–6. Two hundred and forty-two (43.7%) prescriptions had at least one potential drug–drug interaction, and it was found that 292 drug interactions were presented. Almost half of the drug–drug interaction identified was moderate (50%). Overall, the prevalence rate of drug–drug interaction was 43.7%. Older age (adjusted odds ratio = 8.301; 95% confidence interval (5.51–12.4), p = 0.000), presence of comorbidities (adjusted odds ratio = 1.72; 95% confidence interval (1.10–2.68), p = 0.000) and number of medications greater or equal to 3 (adjusted odds ratio = 2.69; 95% confidence interval (1.42–5.11), p = 0.000) were independent predictors for the occurrence of potential drug–drug interaction. CONCLUSION: The prevalence of potential drug–drug interaction among admitted patients was relatively high. Pharmacodynamic drug–drug interaction was the common mechanism of drug–drug interaction with moderate degree. Therefore, close follow-up of hospitalized patients is highly recommended.
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spelling pubmed-83121582021-08-06 Drug-Drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in East Gojjam Zone, Amhara Regional State, Ethiopia Tessema, Zenaw Yibeltal, Desalegn Wubetu, Muluken Dessie, Bekalu Molla, Yalew SAGE Open Med Original Research Article OBJECTIVES: This study was aimed to assess the type, prevalence, characteristics of drug interaction and factors associated from admitted patients in medical wards at primary, district and referral hospitals in East Gojjam Zone, Amhara Regional State, Ethiopia. METHODS: A facility-based retrospective cross-sectional study design was conducted among admitted patients in medical wards at different hospitals of East Gojjam Zone from September 2019 to February 2020. Patient-specific data were extracted from patient medical prescription papers using a structured data collection tool. Potential drug–drug interaction was identified using www.drugs.com as drug–drug interaction checker. Data were analyzed using SPSS version 23.0. To identify the explanatory predictors of potential drug–drug interaction, logistic regression analysis was done at a statistical significance level of p-value < 0.05. RESULTS: Of the total 554 prescriptions, 51.1% were prescribed for females with a mean (±standard deviation) age of 40.85 ± 23.09 years. About 46.4% prescriptions of patients had one or more comorbid conditions, and the most frequent identified comorbid conditions were infectious (18.6%) and cardiac problems (6.3%) with 0.46 ± 0.499 average number of comorbid conditions per patient. Totally, 1516 drugs were prescribed with 2.74 ± 0.848 mean number per patient and range of 2–6. Two hundred and forty-two (43.7%) prescriptions had at least one potential drug–drug interaction, and it was found that 292 drug interactions were presented. Almost half of the drug–drug interaction identified was moderate (50%). Overall, the prevalence rate of drug–drug interaction was 43.7%. Older age (adjusted odds ratio = 8.301; 95% confidence interval (5.51–12.4), p = 0.000), presence of comorbidities (adjusted odds ratio = 1.72; 95% confidence interval (1.10–2.68), p = 0.000) and number of medications greater or equal to 3 (adjusted odds ratio = 2.69; 95% confidence interval (1.42–5.11), p = 0.000) were independent predictors for the occurrence of potential drug–drug interaction. CONCLUSION: The prevalence of potential drug–drug interaction among admitted patients was relatively high. Pharmacodynamic drug–drug interaction was the common mechanism of drug–drug interaction with moderate degree. Therefore, close follow-up of hospitalized patients is highly recommended. SAGE Publications 2021-07-24 /pmc/articles/PMC8312158/ /pubmed/34367641 http://dx.doi.org/10.1177/20503121211035050 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research Article
Tessema, Zenaw
Yibeltal, Desalegn
Wubetu, Muluken
Dessie, Bekalu
Molla, Yalew
Drug-Drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in East Gojjam Zone, Amhara Regional State, Ethiopia
title Drug-Drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in East Gojjam Zone, Amhara Regional State, Ethiopia
title_full Drug-Drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in East Gojjam Zone, Amhara Regional State, Ethiopia
title_fullStr Drug-Drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in East Gojjam Zone, Amhara Regional State, Ethiopia
title_full_unstemmed Drug-Drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in East Gojjam Zone, Amhara Regional State, Ethiopia
title_short Drug-Drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in East Gojjam Zone, Amhara Regional State, Ethiopia
title_sort drug-drug interaction among admitted patients at primary, district and referral hospitals’ medical wards in east gojjam zone, amhara regional state, ethiopia
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312158/
https://www.ncbi.nlm.nih.gov/pubmed/34367641
http://dx.doi.org/10.1177/20503121211035050
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