坦桑尼亚国家健康保险基金索赔支付的建模和预测

Imani Kapungu, Emmanuel Evarest, Nyimvua Shaban, Andongwisye J. Mwakisisile
{"title":"坦桑尼亚国家健康保险基金索赔支付的建模和预测","authors":"Imani Kapungu, Emmanuel Evarest, Nyimvua Shaban, Andongwisye J. Mwakisisile","doi":"10.4314/tjs.v49i4.12","DOIUrl":null,"url":null,"abstract":"The expenses of medical services are increasing across the globe. As a result, pressure is placed on government and insurance companies’ budgets. The amounts of money collected are not enough to cover the claim payments. Therefore, it threatens the sustainability of the health insurance companies due to the mismatch of income and expenditures. This study aimed to model and forecast claim payments for the national health insurance fund (NHIF) in Tanzania. The claim payment data for the period of 2001–2021 from NHIF were used in building the ARIMA model. It was proven that ARIMA (0, 2, 2) is the most accurate model for forecasting the claim payments from 2022 to 2031. Furthermore, numerical results show that the claim payments for NHIF will grow by 68% by 2031.","PeriodicalId":22207,"journal":{"name":"Tanzania Journal of Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modelling and Forecasting Claim Payments of Tanzania National Health Insurance Fund\",\"authors\":\"Imani Kapungu, Emmanuel Evarest, Nyimvua Shaban, Andongwisye J. Mwakisisile\",\"doi\":\"10.4314/tjs.v49i4.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The expenses of medical services are increasing across the globe. As a result, pressure is placed on government and insurance companies’ budgets. The amounts of money collected are not enough to cover the claim payments. Therefore, it threatens the sustainability of the health insurance companies due to the mismatch of income and expenditures. This study aimed to model and forecast claim payments for the national health insurance fund (NHIF) in Tanzania. The claim payment data for the period of 2001–2021 from NHIF were used in building the ARIMA model. It was proven that ARIMA (0, 2, 2) is the most accurate model for forecasting the claim payments from 2022 to 2031. Furthermore, numerical results show that the claim payments for NHIF will grow by 68% by 2031.\",\"PeriodicalId\":22207,\"journal\":{\"name\":\"Tanzania Journal of Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tanzania Journal of Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/tjs.v49i4.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tanzania Journal of Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/tjs.v49i4.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在全球范围内,医疗服务费用正在增加。因此,政府和保险公司的预算受到了压力。所收取的款项不足以支付索赔款项。因此,由于收入与支出的不匹配,它威胁着健康保险公司的可持续性。本研究旨在模拟和预测坦桑尼亚国家健康保险基金(NHIF)的索赔支付。建立ARIMA模型时使用了2001-2021年国民健康保险基金的理赔数据。结果表明,ARIMA(0,2,2)是预测2022 - 2031年理赔金额最准确的模型。此外,数值结果表明,到2031年,国民健康保险基金的理赔金额将增长68%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling and Forecasting Claim Payments of Tanzania National Health Insurance Fund
The expenses of medical services are increasing across the globe. As a result, pressure is placed on government and insurance companies’ budgets. The amounts of money collected are not enough to cover the claim payments. Therefore, it threatens the sustainability of the health insurance companies due to the mismatch of income and expenditures. This study aimed to model and forecast claim payments for the national health insurance fund (NHIF) in Tanzania. The claim payment data for the period of 2001–2021 from NHIF were used in building the ARIMA model. It was proven that ARIMA (0, 2, 2) is the most accurate model for forecasting the claim payments from 2022 to 2031. Furthermore, numerical results show that the claim payments for NHIF will grow by 68% by 2031.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信