Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data
Cystic fibrosis (CF) is a progressive disease with treatments intensifying as patients get older and severity worsens. To inform policy makers about the cost burden in CF, it is crucial to understand what factors influence the costs and how they affect the costs. Based on 1,060 observations (from 73...
Gespeichert in:
Veröffentlicht in: | The European journal of health economics 2015-09, Vol.16 (7), p.709-717 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 717 |
---|---|
container_issue | 7 |
container_start_page | 709 |
container_title | The European journal of health economics |
container_volume | 16 |
creator | Gu, Yuanyuan García-Pérez, Sonia Massie, John van Gool, Kees |
description | Cystic fibrosis (CF) is a progressive disease with treatments intensifying as patients get older and severity worsens. To inform policy makers about the cost burden in CF, it is crucial to understand what factors influence the costs and how they affect the costs. Based on 1,060 observations (from 731 patients) obtained from the Australian Data Registry, individual annual health care costs were calculated and a regression analysis was carried out to examine the impact of multiple variables on the costs. A method of retransformation and a hypothetical patient were used for cost analysis. We show that an additional one unit improvement of FEVlpp (i.e., forced expiratory volume in 1 s as a percentage of predicted volume) reduces the costs by 1.4 %, or for a hypothetical patient whose FEVlpp is 73 the cost reduction is A$252. The presence of chronic infections increases the costs by 69.9-163.5 % (A$ 12,852-A$30,047 for the hypothetical patient) depending on the type of infection. The type of CF genetic mutation and the patient's age both have significant effects on the costs. In particular, being homozygous for p.F508del increases the costs by 26.8 % compared to all the other gene mutations. We conclude that bacterial infections have a very strong influence on the costs, so reducing both the infection rates and the severity of the condition may lead to substantial cost savings. We also suggest that the patient's genetic profile should be considered as an important cost determinant. |
doi_str_mv | 10.1007/s10198-014-0621-5 |
format | Article |
fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_1704352680</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>24774068</jstor_id><sourcerecordid>24774068</sourcerecordid><originalsourceid>FETCH-LOGICAL-c528t-9913f601c710a252b75dd1bcdda3f7c2bfa5922ce63835fb250ece510406fff3</originalsourceid><addsrcrecordid>eNp9kU9PHCEYxomp0e3qB_BQQ9JLL6O8MAwzvTUbtSYmXrwThoEJm13YAtNkv73sjramh54g8Hue98-D0BWQGyBE3CYg0LUVgboiDYWKn6AFNNBWoiHw6f3Ou_YcfU5pTQilgrIzdE45kEawZoGGVUgZB4u1igbbELHep-w0tq6PIbn0HSuPnf9tyuuosgv-SB9Ug8kmbp1XPic8JedH7I-E2uBoRpdy3ONBZXWBTq3aJHP5di7Ry_3dy-pn9fT88Lj68VRpTttcdR0wWzrXAoiinPaCDwP0ehgUs0LT3ireUapNw1rGbU85MdqUUWrSWGvZEn2bbXcx_JpKw3LrkjabjfImTEmCIDXjtGlJQb_-g67DFEvjR4rxGtrCLhHMlC6rSNFYuYtuq-JeApGHBOScgCwJyEMCkhfN9Zvz1G_N8EfxvvIC0BlI5cuPJn4o_R_XL7NonXKIf01rIcrwLXsFon6a6g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1703541804</pqid></control><display><type>article</type><title>Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data</title><source>MEDLINE</source><source>SpringerLink Journals</source><source>JSTOR Archive Collection A-Z Listing</source><creator>Gu, Yuanyuan ; García-Pérez, Sonia ; Massie, John ; van Gool, Kees</creator><creatorcontrib>Gu, Yuanyuan ; García-Pérez, Sonia ; Massie, John ; van Gool, Kees</creatorcontrib><description>Cystic fibrosis (CF) is a progressive disease with treatments intensifying as patients get older and severity worsens. To inform policy makers about the cost burden in CF, it is crucial to understand what factors influence the costs and how they affect the costs. Based on 1,060 observations (from 731 patients) obtained from the Australian Data Registry, individual annual health care costs were calculated and a regression analysis was carried out to examine the impact of multiple variables on the costs. A method of retransformation and a hypothetical patient were used for cost analysis. We show that an additional one unit improvement of FEVlpp (i.e., forced expiratory volume in 1 s as a percentage of predicted volume) reduces the costs by 1.4 %, or for a hypothetical patient whose FEVlpp is 73 the cost reduction is A$252. The presence of chronic infections increases the costs by 69.9-163.5 % (A$ 12,852-A$30,047 for the hypothetical patient) depending on the type of infection. The type of CF genetic mutation and the patient's age both have significant effects on the costs. In particular, being homozygous for p.F508del increases the costs by 26.8 % compared to all the other gene mutations. We conclude that bacterial infections have a very strong influence on the costs, so reducing both the infection rates and the severity of the condition may lead to substantial cost savings. We also suggest that the patient's genetic profile should be considered as an important cost determinant.</description><identifier>ISSN: 1618-7598</identifier><identifier>EISSN: 1618-7601</identifier><identifier>DOI: 10.1007/s10198-014-0621-5</identifier><identifier>PMID: 25106736</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer</publisher><subject>Adult ; Age ; Age Factors ; Australia ; Bacterial diseases ; Bacterial infections ; Bacterial Infections - complications ; Bacterial Infections - economics ; Body mass index ; Chronic Disease - economics ; Chronic illnesses ; Computer Simulation ; Cost control ; Costs ; Cystic fibrosis ; Cystic Fibrosis - economics ; Cystic Fibrosis - genetics ; Cystic Fibrosis - microbiology ; Dependent variables ; Drug prices ; Economic Policy ; Female ; Forced Expiratory Volume ; Gender ; Health Care Costs - statistics & numerical data ; Health care expenditures ; Health Care Management ; Health care policy ; Health Economics ; Hospitalization - economics ; Humans ; Hypotheses ; Male ; Medicine ; Medicine & Public Health ; Methicillin-Resistant Staphylococcus aureus ; Mutation ; Original Paper ; Patients ; Pharmacoeconomics and Health Outcomes ; Public Finance ; Public Health ; Registries ; Regression Analysis ; Regulation ; Staphylococcal Infections - complications ; Staphylococcal Infections - economics ; Transplants & implants ; Variables ; Young Adult</subject><ispartof>The European journal of health economics, 2015-09, Vol.16 (7), p.709-717</ispartof><rights>Springer-Verlag Berlin Heidelberg 2015</rights><rights>Springer-Verlag Berlin Heidelberg 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c528t-9913f601c710a252b75dd1bcdda3f7c2bfa5922ce63835fb250ece510406fff3</citedby><cites>FETCH-LOGICAL-c528t-9913f601c710a252b75dd1bcdda3f7c2bfa5922ce63835fb250ece510406fff3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/24774068$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/24774068$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,27924,27925,41488,42557,51319,58017,58250</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25106736$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gu, Yuanyuan</creatorcontrib><creatorcontrib>García-Pérez, Sonia</creatorcontrib><creatorcontrib>Massie, John</creatorcontrib><creatorcontrib>van Gool, Kees</creatorcontrib><title>Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data</title><title>The European journal of health economics</title><addtitle>Eur J Health Econ</addtitle><addtitle>Eur J Health Econ</addtitle><description>Cystic fibrosis (CF) is a progressive disease with treatments intensifying as patients get older and severity worsens. To inform policy makers about the cost burden in CF, it is crucial to understand what factors influence the costs and how they affect the costs. Based on 1,060 observations (from 731 patients) obtained from the Australian Data Registry, individual annual health care costs were calculated and a regression analysis was carried out to examine the impact of multiple variables on the costs. A method of retransformation and a hypothetical patient were used for cost analysis. We show that an additional one unit improvement of FEVlpp (i.e., forced expiratory volume in 1 s as a percentage of predicted volume) reduces the costs by 1.4 %, or for a hypothetical patient whose FEVlpp is 73 the cost reduction is A$252. The presence of chronic infections increases the costs by 69.9-163.5 % (A$ 12,852-A$30,047 for the hypothetical patient) depending on the type of infection. The type of CF genetic mutation and the patient's age both have significant effects on the costs. In particular, being homozygous for p.F508del increases the costs by 26.8 % compared to all the other gene mutations. We conclude that bacterial infections have a very strong influence on the costs, so reducing both the infection rates and the severity of the condition may lead to substantial cost savings. We also suggest that the patient's genetic profile should be considered as an important cost determinant.</description><subject>Adult</subject><subject>Age</subject><subject>Age Factors</subject><subject>Australia</subject><subject>Bacterial diseases</subject><subject>Bacterial infections</subject><subject>Bacterial Infections - complications</subject><subject>Bacterial Infections - economics</subject><subject>Body mass index</subject><subject>Chronic Disease - economics</subject><subject>Chronic illnesses</subject><subject>Computer Simulation</subject><subject>Cost control</subject><subject>Costs</subject><subject>Cystic fibrosis</subject><subject>Cystic Fibrosis - economics</subject><subject>Cystic Fibrosis - genetics</subject><subject>Cystic Fibrosis - microbiology</subject><subject>Dependent variables</subject><subject>Drug prices</subject><subject>Economic Policy</subject><subject>Female</subject><subject>Forced Expiratory Volume</subject><subject>Gender</subject><subject>Health Care Costs - statistics & numerical data</subject><subject>Health care expenditures</subject><subject>Health Care Management</subject><subject>Health care policy</subject><subject>Health Economics</subject><subject>Hospitalization - economics</subject><subject>Humans</subject><subject>Hypotheses</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Methicillin-Resistant Staphylococcus aureus</subject><subject>Mutation</subject><subject>Original Paper</subject><subject>Patients</subject><subject>Pharmacoeconomics and Health Outcomes</subject><subject>Public Finance</subject><subject>Public Health</subject><subject>Registries</subject><subject>Regression Analysis</subject><subject>Regulation</subject><subject>Staphylococcal Infections - complications</subject><subject>Staphylococcal Infections - economics</subject><subject>Transplants & implants</subject><subject>Variables</subject><subject>Young Adult</subject><issn>1618-7598</issn><issn>1618-7601</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kU9PHCEYxomp0e3qB_BQQ9JLL6O8MAwzvTUbtSYmXrwThoEJm13YAtNkv73sjramh54g8Hue98-D0BWQGyBE3CYg0LUVgboiDYWKn6AFNNBWoiHw6f3Ou_YcfU5pTQilgrIzdE45kEawZoGGVUgZB4u1igbbELHep-w0tq6PIbn0HSuPnf9tyuuosgv-SB9Ug8kmbp1XPic8JedH7I-E2uBoRpdy3ONBZXWBTq3aJHP5di7Ry_3dy-pn9fT88Lj68VRpTttcdR0wWzrXAoiinPaCDwP0ehgUs0LT3ireUapNw1rGbU85MdqUUWrSWGvZEn2bbXcx_JpKw3LrkjabjfImTEmCIDXjtGlJQb_-g67DFEvjR4rxGtrCLhHMlC6rSNFYuYtuq-JeApGHBOScgCwJyEMCkhfN9Zvz1G_N8EfxvvIC0BlI5cuPJn4o_R_XL7NonXKIf01rIcrwLXsFon6a6g</recordid><startdate>20150901</startdate><enddate>20150901</enddate><creator>Gu, Yuanyuan</creator><creator>García-Pérez, Sonia</creator><creator>Massie, John</creator><creator>van Gool, Kees</creator><general>Springer</general><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</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>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>L.-</scope><scope>M0C</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYYUZ</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20150901</creationdate><title>Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data</title><author>Gu, Yuanyuan ; García-Pérez, Sonia ; Massie, John ; van Gool, Kees</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c528t-9913f601c710a252b75dd1bcdda3f7c2bfa5922ce63835fb250ece510406fff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adult</topic><topic>Age</topic><topic>Age Factors</topic><topic>Australia</topic><topic>Bacterial diseases</topic><topic>Bacterial infections</topic><topic>Bacterial Infections - complications</topic><topic>Bacterial Infections - economics</topic><topic>Body mass index</topic><topic>Chronic Disease - economics</topic><topic>Chronic illnesses</topic><topic>Computer Simulation</topic><topic>Cost control</topic><topic>Costs</topic><topic>Cystic fibrosis</topic><topic>Cystic Fibrosis - economics</topic><topic>Cystic Fibrosis - genetics</topic><topic>Cystic Fibrosis - microbiology</topic><topic>Dependent variables</topic><topic>Drug prices</topic><topic>Economic Policy</topic><topic>Female</topic><topic>Forced Expiratory Volume</topic><topic>Gender</topic><topic>Health Care Costs - statistics & numerical data</topic><topic>Health care expenditures</topic><topic>Health Care Management</topic><topic>Health care policy</topic><topic>Health Economics</topic><topic>Hospitalization - economics</topic><topic>Humans</topic><topic>Hypotheses</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Methicillin-Resistant Staphylococcus aureus</topic><topic>Mutation</topic><topic>Original Paper</topic><topic>Patients</topic><topic>Pharmacoeconomics and Health Outcomes</topic><topic>Public Finance</topic><topic>Public Health</topic><topic>Registries</topic><topic>Regression Analysis</topic><topic>Regulation</topic><topic>Staphylococcal Infections - complications</topic><topic>Staphylococcal Infections - economics</topic><topic>Transplants & implants</topic><topic>Variables</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gu, Yuanyuan</creatorcontrib><creatorcontrib>García-Pérez, Sonia</creatorcontrib><creatorcontrib>Massie, John</creatorcontrib><creatorcontrib>van Gool, Kees</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ABI/INFORM Collection China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>The European journal of health economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gu, Yuanyuan</au><au>García-Pérez, Sonia</au><au>Massie, John</au><au>van Gool, Kees</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data</atitle><jtitle>The European journal of health economics</jtitle><stitle>Eur J Health Econ</stitle><addtitle>Eur J Health Econ</addtitle><date>2015-09-01</date><risdate>2015</risdate><volume>16</volume><issue>7</issue><spage>709</spage><epage>717</epage><pages>709-717</pages><issn>1618-7598</issn><eissn>1618-7601</eissn><abstract>Cystic fibrosis (CF) is a progressive disease with treatments intensifying as patients get older and severity worsens. To inform policy makers about the cost burden in CF, it is crucial to understand what factors influence the costs and how they affect the costs. Based on 1,060 observations (from 731 patients) obtained from the Australian Data Registry, individual annual health care costs were calculated and a regression analysis was carried out to examine the impact of multiple variables on the costs. A method of retransformation and a hypothetical patient were used for cost analysis. We show that an additional one unit improvement of FEVlpp (i.e., forced expiratory volume in 1 s as a percentage of predicted volume) reduces the costs by 1.4 %, or for a hypothetical patient whose FEVlpp is 73 the cost reduction is A$252. The presence of chronic infections increases the costs by 69.9-163.5 % (A$ 12,852-A$30,047 for the hypothetical patient) depending on the type of infection. The type of CF genetic mutation and the patient's age both have significant effects on the costs. In particular, being homozygous for p.F508del increases the costs by 26.8 % compared to all the other gene mutations. We conclude that bacterial infections have a very strong influence on the costs, so reducing both the infection rates and the severity of the condition may lead to substantial cost savings. We also suggest that the patient's genetic profile should be considered as an important cost determinant.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer</pub><pmid>25106736</pmid><doi>10.1007/s10198-014-0621-5</doi><tpages>9</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1618-7598 |
ispartof | The European journal of health economics, 2015-09, Vol.16 (7), p.709-717 |
issn | 1618-7598 1618-7601 |
language | eng |
recordid | cdi_proquest_miscellaneous_1704352680 |
source | MEDLINE; SpringerLink Journals; JSTOR Archive Collection A-Z Listing |
subjects | Adult Age Age Factors Australia Bacterial diseases Bacterial infections Bacterial Infections - complications Bacterial Infections - economics Body mass index Chronic Disease - economics Chronic illnesses Computer Simulation Cost control Costs Cystic fibrosis Cystic Fibrosis - economics Cystic Fibrosis - genetics Cystic Fibrosis - microbiology Dependent variables Drug prices Economic Policy Female Forced Expiratory Volume Gender Health Care Costs - statistics & numerical data Health care expenditures Health Care Management Health care policy Health Economics Hospitalization - economics Humans Hypotheses Male Medicine Medicine & Public Health Methicillin-Resistant Staphylococcus aureus Mutation Original Paper Patients Pharmacoeconomics and Health Outcomes Public Finance Public Health Registries Regression Analysis Regulation Staphylococcal Infections - complications Staphylococcal Infections - economics Transplants & implants Variables Young Adult |
title | Cost of care for cystic fibrosis: an investigation of cost determinants using national registry data |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T15%3A47%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Cost%20of%20care%20for%20cystic%20fibrosis:%20an%20investigation%20of%20cost%20determinants%20using%20national%20registry%20data&rft.jtitle=The%20European%20journal%20of%20health%20economics&rft.au=Gu,%20Yuanyuan&rft.date=2015-09-01&rft.volume=16&rft.issue=7&rft.spage=709&rft.epage=717&rft.pages=709-717&rft.issn=1618-7598&rft.eissn=1618-7601&rft_id=info:doi/10.1007/s10198-014-0621-5&rft_dat=%3Cjstor_proqu%3E24774068%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1703541804&rft_id=info:pmid/25106736&rft_jstor_id=24774068&rfr_iscdi=true |