Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector

Service quality is believed to influence the productive efficiency of firms, particularly in a service focused industry such as healthcare. However, there is mixed evidence in the literature of both positive and negative correlation (e.g., the cost drivers of care providers vis-à-vis capacity expans...

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Main Authors: Utsav Pandey, Sanjeet Singh
Format: Article
Language:English
Published: Ram Arti Publishers 2025-04-01
Series:International Journal of Mathematical, Engineering and Management Sciences
Subjects:
Online Access:https://www.ijmems.in/cms/storage/app/public/uploads/volumes/17-IJMEMS-24-0599-10-2-300-349-2025.pdf
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author Utsav Pandey
Sanjeet Singh
author_facet Utsav Pandey
Sanjeet Singh
author_sort Utsav Pandey
collection DOAJ
description Service quality is believed to influence the productive efficiency of firms, particularly in a service focused industry such as healthcare. However, there is mixed evidence in the literature of both positive and negative correlation (e.g., the cost drivers of care providers vis-à-vis capacity expansion for better quality of service) between quality and efficiency. To address this challenge, a two-phase data-driven analysis is undertaken. In the first stage, an output-oriented Data Envelopment Analysis is employed to model the interdependency between operational efficiency and service quality by assessing the allocation of the input resources for achieving these two objectives. While accounting for the external influences and avoiding the ‘best practice trap’ in the healthcare sector, a set of classification algorithms are used to quantify the impact of external factors on efficiency levels. The proposed model is empirically tested using healthcare data of 31 provinces of China for a period from 2013 to 2018. The results show that the efficiency scores in operational productivity and quality of service are 67% and 64%, respectively. The major source of inefficiency is the number of cases in observation rooms (almost 47%) followed by health examination (22%). The provinces are categorized into three classes (optimally chosen number of clusters) using K-means clustering. The second phase of the analysis starts with selecting a subset of relevant features from 33 explanatory variables using information gain and correlation analysis. The proposed two-phased integrated technique enhances the performance of healthcare services and provides a roadmap for improvement for inefficient regions.
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spelling doaj-art-f623149f504e42729e4bc8998dd3a2c12025-02-07T15:42:17ZengRam Arti PublishersInternational Journal of Mathematical, Engineering and Management Sciences2455-77492025-04-01102300349https://doi.org/10.33889/IJMEMS.2025.10.2.017Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare SectorUtsav Pandey0Sanjeet Singh1Decision Sciences Area, Indian Institute of Management Lucknow, Lucknow, 226013, Uttar Pradesh, India.Decision Sciences Area, Indian Institute of Management Lucknow, Lucknow, 226013, Uttar Pradesh, India.Service quality is believed to influence the productive efficiency of firms, particularly in a service focused industry such as healthcare. However, there is mixed evidence in the literature of both positive and negative correlation (e.g., the cost drivers of care providers vis-à-vis capacity expansion for better quality of service) between quality and efficiency. To address this challenge, a two-phase data-driven analysis is undertaken. In the first stage, an output-oriented Data Envelopment Analysis is employed to model the interdependency between operational efficiency and service quality by assessing the allocation of the input resources for achieving these two objectives. While accounting for the external influences and avoiding the ‘best practice trap’ in the healthcare sector, a set of classification algorithms are used to quantify the impact of external factors on efficiency levels. The proposed model is empirically tested using healthcare data of 31 provinces of China for a period from 2013 to 2018. The results show that the efficiency scores in operational productivity and quality of service are 67% and 64%, respectively. The major source of inefficiency is the number of cases in observation rooms (almost 47%) followed by health examination (22%). The provinces are categorized into three classes (optimally chosen number of clusters) using K-means clustering. The second phase of the analysis starts with selecting a subset of relevant features from 33 explanatory variables using information gain and correlation analysis. The proposed two-phased integrated technique enhances the performance of healthcare services and provides a roadmap for improvement for inefficient regions.https://www.ijmems.in/cms/storage/app/public/uploads/volumes/17-IJMEMS-24-0599-10-2-300-349-2025.pdfhealthcare efficiencyqualitydeahealthcare analytics
spellingShingle Utsav Pandey
Sanjeet Singh
Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector
International Journal of Mathematical, Engineering and Management Sciences
healthcare efficiency
quality
dea
healthcare analytics
title Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector
title_full Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector
title_fullStr Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector
title_full_unstemmed Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector
title_short Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector
title_sort incorporating contextual factors into a comprehensive analysis of operational efficiency and service quality in healthcare sector
topic healthcare efficiency
quality
dea
healthcare analytics
url https://www.ijmems.in/cms/storage/app/public/uploads/volumes/17-IJMEMS-24-0599-10-2-300-349-2025.pdf
work_keys_str_mv AT utsavpandey incorporatingcontextualfactorsintoacomprehensiveanalysisofoperationalefficiencyandservicequalityinhealthcaresector
AT sanjeetsingh incorporatingcontextualfactorsintoacomprehensiveanalysisofoperationalefficiencyandservicequalityinhealthcaresector