{"title":"Predicting Patient Hospital Charges Using Machine Learning","authors":"Dolley Shukla, Preeti Chandrakar","doi":"10.3103/s0735272723010016","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>As the health care system moves toward value-based care, Clinical Management System (CMS) has designed a number of programs to improve the quality of patient care. One of these programs is called the Hospital Patient Admission Cost Analysis Program, which helps the patient and the hospital to diagnose the disease and estimate the cost of hospitalization. According to the World Health Organization (WHO), the personal and medical costs have skyrocketed faster than the global economy. Major attributes which cause an increase in expenditure include smoking, ageing and increased Body Mass Index (BMI). In this study, we find a correlation between medical costs and various items using the insurance data of different people with characteristics such as smoking, age, the number of children, region and BMI. This study can also be used to demonstrate different models of regression that can be used to forecast insurance costs. Machine learning significantly reduces human efforts because machine learning models can compute cost calculations in short time, for which human beings take much more time.</p>","PeriodicalId":52470,"journal":{"name":"Radioelectronics and Communications Systems","volume":"37 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radioelectronics and Communications Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3103/s0735272723010016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
As the health care system moves toward value-based care, Clinical Management System (CMS) has designed a number of programs to improve the quality of patient care. One of these programs is called the Hospital Patient Admission Cost Analysis Program, which helps the patient and the hospital to diagnose the disease and estimate the cost of hospitalization. According to the World Health Organization (WHO), the personal and medical costs have skyrocketed faster than the global economy. Major attributes which cause an increase in expenditure include smoking, ageing and increased Body Mass Index (BMI). In this study, we find a correlation between medical costs and various items using the insurance data of different people with characteristics such as smoking, age, the number of children, region and BMI. This study can also be used to demonstrate different models of regression that can be used to forecast insurance costs. Machine learning significantly reduces human efforts because machine learning models can compute cost calculations in short time, for which human beings take much more time.
期刊介绍：
Radioelectronics and Communications Systems covers urgent theoretical problems of radio-engineering; results of research efforts, leading experience, which determines directions and development of scientific research in radio engineering and radio electronics; publishes materials of scientific conferences and meetings; information on scientific work in higher educational institutions; newsreel and bibliographic materials. Journal publishes articles in the following sections:Antenna-feeding and microwave devices;Vacuum and gas-discharge devices;Solid-state electronics and integral circuit engineering;Optical radar, communication and information processing systems;Use of computers for research and design of radio-electronic devices and systems;Quantum electronic devices;Design of radio-electronic devices;Radar and radio navigation;Radio engineering devices and systems;Radio engineering theory;Medical radioelectronics.
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