Association Rules Mining for Hospital Readmission: A Case Study

As an indicator of healthcare quality and performance, hospital readmission incurs major costs for healthcare systems worldwide. Understanding the relationships between readmission factors, such as input features and readmission length, is challenging following intricate hospital readmission procedu...

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Autores principales:	Nor Hamizah Miswan, ‘Ismat Mohd Sulaiman, Chee Seng Chan, Chong Guan Ng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Apriori algorithm association rules mining (ARM) hospital readmission Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/813a73bb8ab14fe8985571256c1d2961
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id	oai:doaj.org-article:813a73bb8ab14fe8985571256c1d2961
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spelling	oai:doaj.org-article:813a73bb8ab14fe8985571256c1d29612021-11-11T18:15:58ZAssociation Rules Mining for Hospital Readmission: A Case Study10.3390/math92127062227-7390https://doaj.org/article/813a73bb8ab14fe8985571256c1d29612021-10-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/21/2706https://doaj.org/toc/2227-7390As an indicator of healthcare quality and performance, hospital readmission incurs major costs for healthcare systems worldwide. Understanding the relationships between readmission factors, such as input features and readmission length, is challenging following intricate hospital readmission procedures. This study discovered the significant correlation between potential readmission factors (threshold of various settings for readmission length) and basic demographic variables. Association rule mining (ARM), particularly the Apriori algorithm, was utilised to extract the hidden input variable patterns and relationships among admitted patients by generating supervised learning rules. The mined rules were categorised into two outcomes to comprehend readmission data; (i) the rules associated with various readmission length and (ii) several expert-validated variables related to basic demographics (gender, race, and age group). The extracted rules proved useful to facilitate decision-making and resource preparation to minimise patient readmission.Nor Hamizah Miswan‘Ismat Mohd SulaimanChee Seng ChanChong Guan NgMDPI AGarticleApriori algorithmassociation rules mining (ARM)hospital readmissionMathematicsQA1-939ENMathematics, Vol 9, Iss 2706, p 2706 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Apriori algorithm association rules mining (ARM) hospital readmission Mathematics QA1-939
spellingShingle	Apriori algorithm association rules mining (ARM) hospital readmission Mathematics QA1-939 Nor Hamizah Miswan ‘Ismat Mohd Sulaiman Chee Seng Chan Chong Guan Ng Association Rules Mining for Hospital Readmission: A Case Study
description	As an indicator of healthcare quality and performance, hospital readmission incurs major costs for healthcare systems worldwide. Understanding the relationships between readmission factors, such as input features and readmission length, is challenging following intricate hospital readmission procedures. This study discovered the significant correlation between potential readmission factors (threshold of various settings for readmission length) and basic demographic variables. Association rule mining (ARM), particularly the Apriori algorithm, was utilised to extract the hidden input variable patterns and relationships among admitted patients by generating supervised learning rules. The mined rules were categorised into two outcomes to comprehend readmission data; (i) the rules associated with various readmission length and (ii) several expert-validated variables related to basic demographics (gender, race, and age group). The extracted rules proved useful to facilitate decision-making and resource preparation to minimise patient readmission.
format	article
author	Nor Hamizah Miswan ‘Ismat Mohd Sulaiman Chee Seng Chan Chong Guan Ng
author_facet	Nor Hamizah Miswan ‘Ismat Mohd Sulaiman Chee Seng Chan Chong Guan Ng
author_sort	Nor Hamizah Miswan
title	Association Rules Mining for Hospital Readmission: A Case Study
title_short	Association Rules Mining for Hospital Readmission: A Case Study
title_full	Association Rules Mining for Hospital Readmission: A Case Study
title_fullStr	Association Rules Mining for Hospital Readmission: A Case Study
title_full_unstemmed	Association Rules Mining for Hospital Readmission: A Case Study
title_sort	association rules mining for hospital readmission: a case study
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/813a73bb8ab14fe8985571256c1d2961
work_keys_str_mv	AT norhamizahmiswan associationrulesminingforhospitalreadmissionacasestudy AT ismatmohdsulaiman associationrulesminingforhospitalreadmissionacasestudy AT cheesengchan associationrulesminingforhospitalreadmissionacasestudy AT chongguanng associationrulesminingforhospitalreadmissionacasestudy
_version_	1718431894540910592

Association Rules Mining for Hospital Readmission: A Case Study

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