Cancer impact on lower-income patients in Malaysian public healthcare: An exploration of out-of-pocket expenses, productivity loss, and financial coping strategies
Cancer patients often grapple with substantial out-of-pocket (OOP) expenses and productivity loss, with the ramifications being particularly crucial for lower-income households. This study aims to estimate OOP costs incurred by cancer patients, assess their productivity loss, and analyse the financi...
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| Veröffentlicht in: | PloS one 2024-10, Vol.19 (10), p.e0311815 |
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| creator | Aminuddin, Farhana Raman, Sivaraj Bahari, Mohd Shahri Zaimi, Nur Amalina Mohd Nor Sham Kunusagaran, Mohd Shaiful Jefri Zainuddin, Nur Azmiah Mostapha, Marhaini Ping, Tan Yui Mohd Hassan, Nor Zam Azihan |
| description | Cancer patients often grapple with substantial out-of-pocket (OOP) expenses and productivity loss, with the ramifications being particularly crucial for lower-income households. This study aims to estimate OOP costs incurred by cancer patients, assess their productivity loss, and analyse the financial coping mechanisms employed by individuals within the lower-income bracket. The study employed face-to-face interviews among cancer patients aged 40 years and above, currently undergoing treatment, and belonging to the lower-income group. Participants were recruited from six public cancer referral hospitals. OOP expenses, encompassing medical and non-medical costs, along with productivity loss, were measured. A generalized linear model was applied to identify potential OOP determinants. Additionally, the coping mechanisms employed by individuals to finance their cancer OOP expenses were also determined. Among the 430 participants recruited, predominantly female (63.5%), and aged 60 or older (53.9%). The annual mean total cancer costs per patient were US$ 2,398.28 (±2,168.74), including 15% for medical costs US$ 350.95 (±560.24), 34% for non-medical costs US$820.24 (±818.24), and 51% for productivity loss costs US$1,227.09 (±1,809.09). Transportation, nutritional supplements, outpatient treatment, and medical supplies were notable cost contributors to total OOP expenditures. Ethnicity (β = 1.44; 95%CI = 1.15-1.79), household income (β = 1.40; 95%CI = 1.10-1.78), annual outpatient visits (β = 1.00; 95%CI = 1.00-1.01), age (β = 0.74; 95%CI = 0.56-0.98), and employment status (β = 0.54; 95%CI = 0.72-1.34) were identified as significant predictors of OOP costs among cancer patients. Notably, 91% of participants relied on household salaries and savings, while 15% resorted to interest-free borrowing, 11% sold possessions, and 0.5% borrowed with interest to finance their expenses. This study offers crucial insights into the economic impact of cancer on individuals and their families, providing policymakers with valuable information to tackle challenges faced in their journey. Despite substantial public healthcare subsidies, the study revealed that cancer costs can remain a potential barrier to accessing essential treatment. Therefore, there is a need for reinforced system-level infrastructure to facilitate targeted financial navigation services. |
| doi_str_mv | 10.1371/journal.pone.0311815 |
| format | Article |
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This study aims to estimate OOP costs incurred by cancer patients, assess their productivity loss, and analyse the financial coping mechanisms employed by individuals within the lower-income bracket. The study employed face-to-face interviews among cancer patients aged 40 years and above, currently undergoing treatment, and belonging to the lower-income group. Participants were recruited from six public cancer referral hospitals. OOP expenses, encompassing medical and non-medical costs, along with productivity loss, were measured. A generalized linear model was applied to identify potential OOP determinants. Additionally, the coping mechanisms employed by individuals to finance their cancer OOP expenses were also determined. Among the 430 participants recruited, predominantly female (63.5%), and aged 60 or older (53.9%). The annual mean total cancer costs per patient were US$ 2,398.28 (±2,168.74), including 15% for medical costs US$ 350.95 (±560.24), 34% for non-medical costs US$820.24 (±818.24), and 51% for productivity loss costs US$1,227.09 (±1,809.09). Transportation, nutritional supplements, outpatient treatment, and medical supplies were notable cost contributors to total OOP expenditures. Ethnicity (β = 1.44; 95%CI = 1.15-1.79), household income (β = 1.40; 95%CI = 1.10-1.78), annual outpatient visits (β = 1.00; 95%CI = 1.00-1.01), age (β = 0.74; 95%CI = 0.56-0.98), and employment status (β = 0.54; 95%CI = 0.72-1.34) were identified as significant predictors of OOP costs among cancer patients. Notably, 91% of participants relied on household salaries and savings, while 15% resorted to interest-free borrowing, 11% sold possessions, and 0.5% borrowed with interest to finance their expenses. This study offers crucial insights into the economic impact of cancer on individuals and their families, providing policymakers with valuable information to tackle challenges faced in their journey. Despite substantial public healthcare subsidies, the study revealed that cancer costs can remain a potential barrier to accessing essential treatment. Therefore, there is a need for reinforced system-level infrastructure to facilitate targeted financial navigation services.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0311815</identifier><identifier>PMID: 39383152</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adaptation, Psychological ; Adult ; Aged ; Cancer ; Cancer patients ; Coping Skills ; Cost analysis ; Cost of Illness ; Costs ; Dietary supplements ; Economic aspects ; Economic impact ; Efficiency ; Energy consumption ; Engineering and Technology ; Expenditures ; Female ; Finance ; Financial management ; Health aspects ; Health care ; Health care expenditures ; Health Expenditures - statistics & numerical data ; Health facilities ; Health services ; Hospitals ; Households ; Humans ; Income ; Labor productivity ; Low income groups ; Malaysia ; Male ; Medical economics ; Medicine and Health Sciences ; Methods ; Middle Aged ; Neoplasms - economics ; Neoplasms - psychology ; Neoplasms - therapy ; Oncology ; Patients ; Physiological aspects ; Pilot projects ; Poverty ; Productivity ; Radiation therapy ; Sample size ; Social aspects ; Social Sciences ; Standard deviation ; Statistical models</subject><ispartof>PloS one, 2024-10, Vol.19 (10), p.e0311815</ispartof><rights>Copyright: © 2024 Aminuddin et al. 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This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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This study aims to estimate OOP costs incurred by cancer patients, assess their productivity loss, and analyse the financial coping mechanisms employed by individuals within the lower-income bracket. The study employed face-to-face interviews among cancer patients aged 40 years and above, currently undergoing treatment, and belonging to the lower-income group. Participants were recruited from six public cancer referral hospitals. OOP expenses, encompassing medical and non-medical costs, along with productivity loss, were measured. A generalized linear model was applied to identify potential OOP determinants. Additionally, the coping mechanisms employed by individuals to finance their cancer OOP expenses were also determined. Among the 430 participants recruited, predominantly female (63.5%), and aged 60 or older (53.9%). The annual mean total cancer costs per patient were US$ 2,398.28 (±2,168.74), including 15% for medical costs US$ 350.95 (±560.24), 34% for non-medical costs US$820.24 (±818.24), and 51% for productivity loss costs US$1,227.09 (±1,809.09). Transportation, nutritional supplements, outpatient treatment, and medical supplies were notable cost contributors to total OOP expenditures. Ethnicity (β = 1.44; 95%CI = 1.15-1.79), household income (β = 1.40; 95%CI = 1.10-1.78), annual outpatient visits (β = 1.00; 95%CI = 1.00-1.01), age (β = 0.74; 95%CI = 0.56-0.98), and employment status (β = 0.54; 95%CI = 0.72-1.34) were identified as significant predictors of OOP costs among cancer patients. Notably, 91% of participants relied on household salaries and savings, while 15% resorted to interest-free borrowing, 11% sold possessions, and 0.5% borrowed with interest to finance their expenses. This study offers crucial insights into the economic impact of cancer on individuals and their families, providing policymakers with valuable information to tackle challenges faced in their journey. Despite substantial public healthcare subsidies, the study revealed that cancer costs can remain a potential barrier to accessing essential treatment. Therefore, there is a need for reinforced system-level infrastructure to facilitate targeted financial navigation services.</description><subject>Adaptation, Psychological</subject><subject>Adult</subject><subject>Aged</subject><subject>Cancer</subject><subject>Cancer patients</subject><subject>Coping Skills</subject><subject>Cost analysis</subject><subject>Cost of Illness</subject><subject>Costs</subject><subject>Dietary supplements</subject><subject>Economic aspects</subject><subject>Economic impact</subject><subject>Efficiency</subject><subject>Energy consumption</subject><subject>Engineering and Technology</subject><subject>Expenditures</subject><subject>Female</subject><subject>Finance</subject><subject>Financial management</subject><subject>Health aspects</subject><subject>Health care</subject><subject>Health care expenditures</subject><subject>Health Expenditures - statistics & numerical data</subject><subject>Health facilities</subject><subject>Health 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Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aminuddin, Farhana</au><au>Raman, Sivaraj</au><au>Bahari, Mohd Shahri</au><au>Zaimi, Nur Amalina</au><au>Mohd Nor Sham Kunusagaran, Mohd Shaiful Jefri</au><au>Zainuddin, Nur Azmiah</au><au>Mostapha, Marhaini</au><au>Ping, Tan Yui</au><au>Mohd Hassan, Nor Zam Azihan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cancer impact on lower-income patients in Malaysian public healthcare: An exploration of out-of-pocket expenses, productivity loss, and financial coping strategies</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-10-09</date><risdate>2024</risdate><volume>19</volume><issue>10</issue><spage>e0311815</spage><pages>e0311815-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Cancer patients often grapple with substantial out-of-pocket (OOP) expenses and productivity loss, with the ramifications being particularly crucial for lower-income households. This study aims to estimate OOP costs incurred by cancer patients, assess their productivity loss, and analyse the financial coping mechanisms employed by individuals within the lower-income bracket. The study employed face-to-face interviews among cancer patients aged 40 years and above, currently undergoing treatment, and belonging to the lower-income group. Participants were recruited from six public cancer referral hospitals. OOP expenses, encompassing medical and non-medical costs, along with productivity loss, were measured. A generalized linear model was applied to identify potential OOP determinants. Additionally, the coping mechanisms employed by individuals to finance their cancer OOP expenses were also determined. Among the 430 participants recruited, predominantly female (63.5%), and aged 60 or older (53.9%). The annual mean total cancer costs per patient were US$ 2,398.28 (±2,168.74), including 15% for medical costs US$ 350.95 (±560.24), 34% for non-medical costs US$820.24 (±818.24), and 51% for productivity loss costs US$1,227.09 (±1,809.09). Transportation, nutritional supplements, outpatient treatment, and medical supplies were notable cost contributors to total OOP expenditures. Ethnicity (β = 1.44; 95%CI = 1.15-1.79), household income (β = 1.40; 95%CI = 1.10-1.78), annual outpatient visits (β = 1.00; 95%CI = 1.00-1.01), age (β = 0.74; 95%CI = 0.56-0.98), and employment status (β = 0.54; 95%CI = 0.72-1.34) were identified as significant predictors of OOP costs among cancer patients. Notably, 91% of participants relied on household salaries and savings, while 15% resorted to interest-free borrowing, 11% sold possessions, and 0.5% borrowed with interest to finance their expenses. This study offers crucial insights into the economic impact of cancer on individuals and their families, providing policymakers with valuable information to tackle challenges faced in their journey. Despite substantial public healthcare subsidies, the study revealed that cancer costs can remain a potential barrier to accessing essential treatment. Therefore, there is a need for reinforced system-level infrastructure to facilitate targeted financial navigation services.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>39383152</pmid><doi>10.1371/journal.pone.0311815</doi><tpages>e0311815</tpages><orcidid>https://orcid.org/0000-0001-7097-8336</orcidid><orcidid>https://orcid.org/0000-0002-0683-1249</orcidid><orcidid>https://orcid.org/0000-0003-2958-5017</orcidid><orcidid>https://orcid.org/0000-0002-7157-8235</orcidid><orcidid>https://orcid.org/0000-0001-8865-0777</orcidid><orcidid>https://orcid.org/0000-0002-2010-5593</orcidid><orcidid>https://orcid.org/0000-0002-6530-8677</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2024-10, Vol.19 (10), p.e0311815 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_3114799522 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Adaptation, Psychological Adult Aged Cancer Cancer patients Coping Skills Cost analysis Cost of Illness Costs Dietary supplements Economic aspects Economic impact Efficiency Energy consumption Engineering and Technology Expenditures Female Finance Financial management Health aspects Health care Health care expenditures Health Expenditures - statistics & numerical data Health facilities Health services Hospitals Households Humans Income Labor productivity Low income groups Malaysia Male Medical economics Medicine and Health Sciences Methods Middle Aged Neoplasms - economics Neoplasms - psychology Neoplasms - therapy Oncology Patients Physiological aspects Pilot projects Poverty Productivity Radiation therapy Sample size Social aspects Social Sciences Standard deviation Statistical models |
| title | Cancer impact on lower-income patients in Malaysian public healthcare: An exploration of out-of-pocket expenses, productivity loss, and financial coping strategies |
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