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What causes high costs for rural tuberculosis inpatients? Evidence from five counties in China
Tuberculosis (TB) still causes high economic burden on patients in China, especially for rural patients. Our study aims to explore the risk factors associated with the high costs for TB inpatients in rural China from the aspects of inpatients' socio-demographic and institutional attributes. Gen...
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Published in: | BMC infectious diseases 2020-07, Vol.20 (1), p.501-14, Article 501 |
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description | Tuberculosis (TB) still causes high economic burden on patients in China, especially for rural patients. Our study aims to explore the risk factors associated with the high costs for TB inpatients in rural China from the aspects of inpatients' socio-demographic and institutional attributes.
Generalized linear models were utilized to investigate the factors associated with TB inpatients' total costs and out-of-pocket (OOP) expenditures. Quantile regression (QR) models were applied to explore the effect of each factor across the different costs range and identify the risk factors of high costs.
TB inpatients with long length of stay and who receive hospitalization services cross provincially, in tertiary and specialized hospitals were likely to face high total costs and OOP expenditures. QR models showed that high total costs occurred in Dingyuan and Funan Counties, but they were not accompanied by high OOP expenditures.
Early diagnosis, standard treatment and control of drug-resistant TB are still awaiting for more efforts from the government. TB inpatients should obtain medical services from appropriate hospitals. The diagnosis and treatment process of TB should be standardized across all designated medical institutions. Furthermore, the reimbursement policy for migrant workers who suffered from TB should be ameliorated. |
doi_str_mv | 10.1186/s12879-020-05235-9 |
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Generalized linear models were utilized to investigate the factors associated with TB inpatients' total costs and out-of-pocket (OOP) expenditures. Quantile regression (QR) models were applied to explore the effect of each factor across the different costs range and identify the risk factors of high costs.
TB inpatients with long length of stay and who receive hospitalization services cross provincially, in tertiary and specialized hospitals were likely to face high total costs and OOP expenditures. QR models showed that high total costs occurred in Dingyuan and Funan Counties, but they were not accompanied by high OOP expenditures.
Early diagnosis, standard treatment and control of drug-resistant TB are still awaiting for more efforts from the government. TB inpatients should obtain medical services from appropriate hospitals. The diagnosis and treatment process of TB should be standardized across all designated medical institutions. Furthermore, the reimbursement policy for migrant workers who suffered from TB should be ameliorated.</description><identifier>ISSN: 1471-2334</identifier><identifier>EISSN: 1471-2334</identifier><identifier>DOI: 10.1186/s12879-020-05235-9</identifier><identifier>PMID: 32652944</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Adolescent ; Adult ; Aged ; Analysis ; China ; Community health care ; Compensation ; Costs ; Diagnosis ; Drug resistance ; Economic aspects ; Economic burden ; Expenditures ; Family income ; Female ; Generalized linear models ; Health Care Costs ; Health care facilities ; Health Expenditures ; Health services ; Hospital patients ; Hospitalization ; Hospitals ; Households ; Humans ; Infectious diseases ; Inpatients ; Length of Stay - economics ; Male ; Medical diagnosis ; Medical research ; Microbial drug resistance ; Middle Aged ; Migrant labor ; Migrant workers ; Patients ; Payment systems ; Population ; Quantile regression ; Regression Analysis ; Risk analysis ; Risk factors ; Rural areas ; Rural China ; Rural Population ; Socio-demographic status ; Sociodemographics ; Statistical models ; Studies ; Tertiary Care Centers - economics ; Tuberculosis ; Tuberculosis - diagnosis ; Tuberculosis - economics ; Tuberculosis - therapy ; Tuberculosis, Multidrug-Resistant - diagnosis ; Tuberculosis, Multidrug-Resistant - economics ; Tuberculosis, Multidrug-Resistant - therapy ; Young Adult</subject><ispartof>BMC infectious diseases, 2020-07, Vol.20 (1), p.501-14, Article 501</ispartof><rights>COPYRIGHT 2020 BioMed Central Ltd.</rights><rights>2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c631t-1fb574550c14f322d1bb0215042a9e5794a5809991b92182617447bd3c96e973</citedby><cites>FETCH-LOGICAL-c631t-1fb574550c14f322d1bb0215042a9e5794a5809991b92182617447bd3c96e973</cites><orcidid>0000-0001-9400-0308</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7353759/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2424736892?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25744,27915,27916,37003,37004,44581,53782,53784</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32652944$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Haomiao</creatorcontrib><creatorcontrib>Cheng, Bin</creatorcontrib><creatorcontrib>Chen, Yingchun</creatorcontrib><title>What causes high costs for rural tuberculosis inpatients? Evidence from five counties in China</title><title>BMC infectious diseases</title><addtitle>BMC Infect Dis</addtitle><description>Tuberculosis (TB) still causes high economic burden on patients in China, especially for rural patients. Our study aims to explore the risk factors associated with the high costs for TB inpatients in rural China from the aspects of inpatients' socio-demographic and institutional attributes.
Generalized linear models were utilized to investigate the factors associated with TB inpatients' total costs and out-of-pocket (OOP) expenditures. Quantile regression (QR) models were applied to explore the effect of each factor across the different costs range and identify the risk factors of high costs.
TB inpatients with long length of stay and who receive hospitalization services cross provincially, in tertiary and specialized hospitals were likely to face high total costs and OOP expenditures. QR models showed that high total costs occurred in Dingyuan and Funan Counties, but they were not accompanied by high OOP expenditures.
Early diagnosis, standard treatment and control of drug-resistant TB are still awaiting for more efforts from the government. TB inpatients should obtain medical services from appropriate hospitals. The diagnosis and treatment process of TB should be standardized across all designated medical institutions. Furthermore, the reimbursement policy for migrant workers who suffered from TB should be ameliorated.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Analysis</subject><subject>China</subject><subject>Community health care</subject><subject>Compensation</subject><subject>Costs</subject><subject>Diagnosis</subject><subject>Drug resistance</subject><subject>Economic aspects</subject><subject>Economic burden</subject><subject>Expenditures</subject><subject>Family income</subject><subject>Female</subject><subject>Generalized linear models</subject><subject>Health Care Costs</subject><subject>Health care facilities</subject><subject>Health Expenditures</subject><subject>Health services</subject><subject>Hospital patients</subject><subject>Hospitalization</subject><subject>Hospitals</subject><subject>Households</subject><subject>Humans</subject><subject>Infectious diseases</subject><subject>Inpatients</subject><subject>Length of Stay - economics</subject><subject>Male</subject><subject>Medical diagnosis</subject><subject>Medical research</subject><subject>Microbial drug resistance</subject><subject>Middle Aged</subject><subject>Migrant labor</subject><subject>Migrant workers</subject><subject>Patients</subject><subject>Payment systems</subject><subject>Population</subject><subject>Quantile regression</subject><subject>Regression Analysis</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Rural areas</subject><subject>Rural China</subject><subject>Rural Population</subject><subject>Socio-demographic status</subject><subject>Sociodemographics</subject><subject>Statistical models</subject><subject>Studies</subject><subject>Tertiary Care Centers - economics</subject><subject>Tuberculosis</subject><subject>Tuberculosis - diagnosis</subject><subject>Tuberculosis - economics</subject><subject>Tuberculosis - therapy</subject><subject>Tuberculosis, Multidrug-Resistant - diagnosis</subject><subject>Tuberculosis, Multidrug-Resistant - economics</subject><subject>Tuberculosis, Multidrug-Resistant - therapy</subject><subject>Young Adult</subject><issn>1471-2334</issn><issn>1471-2334</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNkk-L1DAYxoso7jr6BTxIwIseuuZvk1yUZVh1YGFBF70Z0jRpM3SaMWkH_famO-u6FQ-SQ0Le3_uE98lTFM8RPENIVG8SwoLLEmJYQoYJK-WD4hRRjkpMCH1473xSPElpCyHiAsvHxQnBFcOS0tPi29dOj8DoKdkEOt92wIQ0JuBCBHGKugfjVNtopj4kn4Af9nr0dhjTO3Bx8I0djAUuhh1w_mBz7zTk8syBdecH_bR45HSf7LPbfVVcv7-4Xn8sL68-bNbnl6WpCBpL5GrGKWPQIOoIxg2qa4gRgxRraRmXVDMBpZSolhgJXCFOKa8bYmRlJSerYnOUbYLeqn30Ox1_qqC9urkIsVU6jt70VglNUcOcEKjGlEAtZAWxwQ7WhBhnXNZ6e9TaT_XONiYPm21YiC4rg-9UGw6KE0Y4k1ng1a1ADN8nm0a188nYvteDDVNSmOa_QrgSNKMv_0K3YYpDdmqmKCeVkPgP1eo8gB9cyO-aWVSdZ_syUuWnV8XZP6i8GrvzJgzW-Xy_aHi9aMjMaH-Mbc5CUpvPn_6fvfqyZPGRNTGkFK278w5BNQdXHYOrcnDVTXDVbNqL-67ftfxOKvkFgmjklw</recordid><startdate>20200711</startdate><enddate>20200711</enddate><creator>Li, Haomiao</creator><creator>Cheng, Bin</creator><creator>Chen, Yingchun</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QL</scope><scope>7T2</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9400-0308</orcidid></search><sort><creationdate>20200711</creationdate><title>What causes high costs for rural tuberculosis inpatients? Evidence from five counties in China</title><author>Li, Haomiao ; Cheng, Bin ; Chen, Yingchun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c631t-1fb574550c14f322d1bb0215042a9e5794a5809991b92182617447bd3c96e973</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Analysis</topic><topic>China</topic><topic>Community health care</topic><topic>Compensation</topic><topic>Costs</topic><topic>Diagnosis</topic><topic>Drug resistance</topic><topic>Economic aspects</topic><topic>Economic burden</topic><topic>Expenditures</topic><topic>Family income</topic><topic>Female</topic><topic>Generalized linear models</topic><topic>Health Care Costs</topic><topic>Health care facilities</topic><topic>Health Expenditures</topic><topic>Health services</topic><topic>Hospital patients</topic><topic>Hospitalization</topic><topic>Hospitals</topic><topic>Households</topic><topic>Humans</topic><topic>Infectious diseases</topic><topic>Inpatients</topic><topic>Length of Stay - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC infectious diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Haomiao</au><au>Cheng, Bin</au><au>Chen, Yingchun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>What causes high costs for rural tuberculosis inpatients? Evidence from five counties in China</atitle><jtitle>BMC infectious diseases</jtitle><addtitle>BMC Infect Dis</addtitle><date>2020-07-11</date><risdate>2020</risdate><volume>20</volume><issue>1</issue><spage>501</spage><epage>14</epage><pages>501-14</pages><artnum>501</artnum><issn>1471-2334</issn><eissn>1471-2334</eissn><abstract>Tuberculosis (TB) still causes high economic burden on patients in China, especially for rural patients. Our study aims to explore the risk factors associated with the high costs for TB inpatients in rural China from the aspects of inpatients' socio-demographic and institutional attributes.
Generalized linear models were utilized to investigate the factors associated with TB inpatients' total costs and out-of-pocket (OOP) expenditures. Quantile regression (QR) models were applied to explore the effect of each factor across the different costs range and identify the risk factors of high costs.
TB inpatients with long length of stay and who receive hospitalization services cross provincially, in tertiary and specialized hospitals were likely to face high total costs and OOP expenditures. QR models showed that high total costs occurred in Dingyuan and Funan Counties, but they were not accompanied by high OOP expenditures.
Early diagnosis, standard treatment and control of drug-resistant TB are still awaiting for more efforts from the government. TB inpatients should obtain medical services from appropriate hospitals. The diagnosis and treatment process of TB should be standardized across all designated medical institutions. Furthermore, the reimbursement policy for migrant workers who suffered from TB should be ameliorated.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>32652944</pmid><doi>10.1186/s12879-020-05235-9</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-9400-0308</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adult Aged Analysis China Community health care Compensation Costs Diagnosis Drug resistance Economic aspects Economic burden Expenditures Family income Female Generalized linear models Health Care Costs Health care facilities Health Expenditures Health services Hospital patients Hospitalization Hospitals Households Humans Infectious diseases Inpatients Length of Stay - economics Male Medical diagnosis Medical research Microbial drug resistance Middle Aged Migrant labor Migrant workers Patients Payment systems Population Quantile regression Regression Analysis Risk analysis Risk factors Rural areas Rural China Rural Population Socio-demographic status Sociodemographics Statistical models Studies Tertiary Care Centers - economics Tuberculosis Tuberculosis - diagnosis Tuberculosis - economics Tuberculosis - therapy Tuberculosis, Multidrug-Resistant - diagnosis Tuberculosis, Multidrug-Resistant - economics Tuberculosis, Multidrug-Resistant - therapy Young Adult |
title | What causes high costs for rural tuberculosis inpatients? Evidence from five counties in China |
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