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Mathematical modeling of clinical engineering approach to evaluate the quality of patient care

At present, the patient care delivery system (PCDS) in a hospital/medical institute/clinic is absolutely medical technology-dependent and this tendency is found to increase day by day. To ensure the quality of patient care (QPC) appropriate implementation of the patient care technology management sy...

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Autores principales: Hossain, Md. Anwar, Ahmad, Mohiuddin, Islam, Md. Rafiqul, David, Yadin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7222130/
https://www.ncbi.nlm.nih.gov/pubmed/32432021
http://dx.doi.org/10.1007/s12553-019-00390-9
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author Hossain, Md. Anwar
Ahmad, Mohiuddin
Islam, Md. Rafiqul
David, Yadin
author_facet Hossain, Md. Anwar
Ahmad, Mohiuddin
Islam, Md. Rafiqul
David, Yadin
author_sort Hossain, Md. Anwar
collection PubMed
description At present, the patient care delivery system (PCDS) in a hospital/medical institute/clinic is absolutely medical technology-dependent and this tendency is found to increase day by day. To ensure the quality of patient care (QPC) appropriate implementation of the patient care technology management system (PCTMS) is necessary. Unfortunately, it is found to be absent in the healthcare delivery system in most of the countries in the world. The situation is very much severe, particularly, in medium- and low-income countries like Malaysia, India, Sri Lanka, Bangladesh, Pakistan, etc. The opposite scenario is found in high-income countries, specifically, in Japan where QPC has been improved significantly by adopting the clinical engineering approach (CEA) in their PCDS. Up to now, QPC is determined based on prediction as there are no mathematical ways to evaluate it properly. In this study, we for the first time, propose a mathematical model to evaluate the QPC quantitatively based on feedback control analogy taking into account of CEA in PCTMS, particularly, for clinical and surgical equipment. The model consists of three subsections: the clinical engineering department (CED), PCTMS, and health care engineering directorate (HCED). The correlation among the subsections and their performance parameters are defined and standardized. Multiple linear regression method is applied to derive the least square normal equations for each of the subsections and then the regression coefficients are solved by the standard data taken from 1000 beds hospitals of different countries. The model is applied to reveal the present status of QPC for 18 different countries including high-, middle-, and low-income countries of the world. The results obtained from the model demonstrate that the present status of QPC in Japan is 84.69% and in Pakistan, it is only 0.20%. This huge discrepancy is identified to be caused by the inclusion of CEA in PCDS of Japan. The proposed model can be applied to evaluate the QPC of a hospital/in a country and hence to take necessary steps accordingly for establishing the proposed research methodology. It is to be mentioned here that the proposed model cannot be applied to evaluate the QPC in some countries like Bangladesh, Bhutan, Nepal, etc. due to the unavailability of data related to the model parameters.
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spelling pubmed-72221302020-05-14 Mathematical modeling of clinical engineering approach to evaluate the quality of patient care Hossain, Md. Anwar Ahmad, Mohiuddin Islam, Md. Rafiqul David, Yadin Health Technol (Berl) Original Paper At present, the patient care delivery system (PCDS) in a hospital/medical institute/clinic is absolutely medical technology-dependent and this tendency is found to increase day by day. To ensure the quality of patient care (QPC) appropriate implementation of the patient care technology management system (PCTMS) is necessary. Unfortunately, it is found to be absent in the healthcare delivery system in most of the countries in the world. The situation is very much severe, particularly, in medium- and low-income countries like Malaysia, India, Sri Lanka, Bangladesh, Pakistan, etc. The opposite scenario is found in high-income countries, specifically, in Japan where QPC has been improved significantly by adopting the clinical engineering approach (CEA) in their PCDS. Up to now, QPC is determined based on prediction as there are no mathematical ways to evaluate it properly. In this study, we for the first time, propose a mathematical model to evaluate the QPC quantitatively based on feedback control analogy taking into account of CEA in PCTMS, particularly, for clinical and surgical equipment. The model consists of three subsections: the clinical engineering department (CED), PCTMS, and health care engineering directorate (HCED). The correlation among the subsections and their performance parameters are defined and standardized. Multiple linear regression method is applied to derive the least square normal equations for each of the subsections and then the regression coefficients are solved by the standard data taken from 1000 beds hospitals of different countries. The model is applied to reveal the present status of QPC for 18 different countries including high-, middle-, and low-income countries of the world. The results obtained from the model demonstrate that the present status of QPC in Japan is 84.69% and in Pakistan, it is only 0.20%. This huge discrepancy is identified to be caused by the inclusion of CEA in PCDS of Japan. The proposed model can be applied to evaluate the QPC of a hospital/in a country and hence to take necessary steps accordingly for establishing the proposed research methodology. It is to be mentioned here that the proposed model cannot be applied to evaluate the QPC in some countries like Bangladesh, Bhutan, Nepal, etc. due to the unavailability of data related to the model parameters. Springer Berlin Heidelberg 2019-11-24 2020 /pmc/articles/PMC7222130/ /pubmed/32432021 http://dx.doi.org/10.1007/s12553-019-00390-9 Text en © IUPESM and Springer-Verlag GmbH Germany, part of Springer Nature 2019 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Hossain, Md. Anwar
Ahmad, Mohiuddin
Islam, Md. Rafiqul
David, Yadin
Mathematical modeling of clinical engineering approach to evaluate the quality of patient care
title Mathematical modeling of clinical engineering approach to evaluate the quality of patient care
title_full Mathematical modeling of clinical engineering approach to evaluate the quality of patient care
title_fullStr Mathematical modeling of clinical engineering approach to evaluate the quality of patient care
title_full_unstemmed Mathematical modeling of clinical engineering approach to evaluate the quality of patient care
title_short Mathematical modeling of clinical engineering approach to evaluate the quality of patient care
title_sort mathematical modeling of clinical engineering approach to evaluate the quality of patient care
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7222130/
https://www.ncbi.nlm.nih.gov/pubmed/32432021
http://dx.doi.org/10.1007/s12553-019-00390-9
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