{"title":"Intelligent Data Management to Facilitate Decision-Making in Healthcare","authors":"Mourya Pathapati, Saikat Gochhait","doi":"10.1109/DASA54658.2022.9765260","DOIUrl":null,"url":null,"abstract":"The advancements in digitization are transforming the healthcare industry, one of the prominent industries producing critical data through patient care. The management of structured and processed data is becoming a challenge. Collecting, storing, and analyzing the data by efficiently reducing the complexity of data management makes the healthcare industry one of the most valuable industries. Creating meaningful and accurate disease predictions is critical in the healthcare sector. A study was conducted using VOSviewer software, which led to four clusters of keywords from different domains based on occurrences and relevance taken from 1500 documents from 1995 to 2021 from Web of Science. These keywords were mapped to the fields impacting the data management in Healthcare to explore the potential problems based on several types of research to establish a framework with an exploratory analysis. The methodology applied in this analysis describes the progress in data management in Healthcare and can let researchers, scholars, and healthcare professionals gain insights for facilitating the healthcare decision-makers.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DASA54658.2022.9765260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The advancements in digitization are transforming the healthcare industry, one of the prominent industries producing critical data through patient care. The management of structured and processed data is becoming a challenge. Collecting, storing, and analyzing the data by efficiently reducing the complexity of data management makes the healthcare industry one of the most valuable industries. Creating meaningful and accurate disease predictions is critical in the healthcare sector. A study was conducted using VOSviewer software, which led to four clusters of keywords from different domains based on occurrences and relevance taken from 1500 documents from 1995 to 2021 from Web of Science. These keywords were mapped to the fields impacting the data management in Healthcare to explore the potential problems based on several types of research to establish a framework with an exploratory analysis. The methodology applied in this analysis describes the progress in data management in Healthcare and can let researchers, scholars, and healthcare professionals gain insights for facilitating the healthcare decision-makers.
数字化的进步正在改变医疗保健行业,这是通过患者护理产生关键数据的重要行业之一。结构化和已处理数据的管理正在成为一个挑战。通过有效降低数据管理的复杂性来收集、存储和分析数据,使医疗保健行业成为最有价值的行业之一。创建有意义和准确的疾病预测在医疗保健部门至关重要。使用VOSviewer软件进行了一项研究,该研究基于1995年至2021年来自Web of Science的1500份文档的出现次数和相关性,得出了来自不同领域的四组关键词。将这些关键字映射到影响医疗保健数据管理的领域,以探索基于几种类型研究的潜在问题,并通过探索性分析建立框架。本分析中应用的方法描述了医疗保健领域数据管理的进展,可以让研究人员、学者和医疗保健专业人员获得促进医疗保健决策者的见解。