Household Catastrophic Health Expenditure From Oral Potentially Malignant Disorders And Oral Cancer In Public Healthcare Of Malaysia Presentation Slides by Mr Sivaraj Raman, presented on the 14th National Conference for Clinical Research (NCCR) 2021 Dr Wu Lien Teh Youth Investigator Awards (YIA) on 19th August 2021 Following are the links for this presentation on Zenodo Repository: Presentation Slides: https://zenodo.org/record/5348498 E-Poster: https://zenodo.org/record/5348963

1. Household Catastrophic Health Expenditure
amongst OPMD and Oral Cancer Patients
in Public Healthcare of Malaysia
Sivaraj Raman

2. BACKGROUND
● Oral cancer and Oral Potentially Malignant Disorders (OPMD)
causes significant disease burden and financial distress1
● Catastrophic healthcare expenditures (CHE) from unforeseen
payments, debilitating disease and treatment traps
households in economic crises2
● ASEAN Costs In Oncology (ACTION) initiative reported 48% of
the households with cancer patients experienced CHE3
1. Rezapour A, et al. The economic burden of oral cancer in Iran. PloS one. 2018;13(9):e0203059
2. Amarasinghe H, et al. Economic burden of managing oral cancer patients in Sri Lanka: a cross-sectional hospital-based costing study. BMJ open. 2019;9(7):e027661
3. Kimman M, et al. CHE and 12-month mortality associated with cancer in Southeast Asia: Results from a longitudinal study in eight countries. BMC Medicine. 2015;13(1):190

3. SIGNIFICANCE
● While Malaysian public healthcare is
highly subsidized, Out-Of-Pocket (OOP)
expenditure for treatment is expected to
be multifold higher1
● Prevalent among the underprivileged,
female and indigenous communities2,3
● More than 70% of cases are still
diagnosed at later stages2
1. Raman S, et al. Provider cost of treating oral potentially malignant disorders and oral cancer in Malaysian public hospitals. Plos one. 2021;16(5):e0251760.
2. Azizah A, et al. Malaysian National Cancer Registry Report 2012-2016. National Cancer Institute, Malaysia. 2019
3. Zain RB, et al. A national epidemiological survey of oral mucosal lesions in Malaysia. Community dentistry and oral epidemiology. 1997;25(5):377-83.
Estimated incidences in Malaysia
(The Global Cancer Observatory, 2020)
2020
742
2040
1,413

4. OBJECTIVES
To estimate household expenditures amongst
OPMD and oral cancer patients
To determine extent of CHE among households
To explore predictors of CHE
1
2
3

5. MATERIALS & METHODS
3. Cost Estimation Simulation Model
1. Prospective Patient Survey
2. Retrospective Record Abstraction
• Sociodemographic data, income,
healthcare OOP expenditures
• Healthcare utilization,
hospitalization and visit details
• To generate hospital fees,
travel and transport cost
Healthcare
OOP expenditure* X 100%
Household income
CHE = 10%*
* ALL cost estimated for the first 1 year after diagnosis
● Association of sociodemographic factors with CHE was
analyzed via multivariate binary logistic regression
● Patients with oral cancer and OPMD were recruited from oral maxillofacial specialist clinics in
Hospital Tengku Ampuan Rahimah and Hospital Umum Sarawak.
*Wagstaff A. Measuring financial protection in health: The World Bank; 2008

6. FINDINGS

7. RESULTS
Characteristics
OPMD
(n=52)
Oral cancer
(n=52)
P-value
Age < 60 years 25 (48.1) 26 (50.0) 0.844
> 60 years 27 (51.0) 26 (50.0)
Gender Male 18 (34.6) 24 (46.1) 0.230
Female 34 (65.4) 28 (53.9)
Race Malay 14 (26.9) 7 (13.5) 0.110
Chinese 6 (11.5) 14 (26.9)
Indian 27 (51.9) 24 (46.2)
Indigenous 5 (9.6) 7 (13.5)
Location Urban 26 (50.0) 23 (44.2) 0.556
Rural 26 (50.0) 29 (55.8)
Income T20 2 (3.8) 3 (5.8) 0.900
M40 3 (5.8) 3 (5.8)
B40 47 (90.4) 46 (88.4)
Education None 7 (13.5) 8 (15.4) 0.094
Primary 11 (21.2) 22 (42.3)
Secondary 25 (48.1) 17 (32.7)
Tertiary 9 (17.3) 5 (9.6)
Employment Not working 21 (40.4) 23 (44.2) 0.414
Employed 20 (38.5) 14 (26.9)
Retired 11 (21.2) 15 (28.9)
52
10
42 OPMD
Early Cancer
Late Cancer
(II) Clinical diagnosis and lesion site
(I) Sociodemographic characteristics
a Pearson Chi-Square Test with significance set to p< 0.05
Site Frequency (%)
Buccal mucosa 57 (54.8)
Tongue 27 (26.0)
Othersb 20 (19.2)
b Consists of the gingiva, alveolar, lip, floor of
mouth, palate, mandible, and other sites
a

8. RESULTS: Average OOP Expenditures & Income Share
1,082
1,463
380
989
2,788
940
1,189
1,577
MYR 1,214
MYR 3,260
MYR 5,021
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
OPMD Early Cancer Late Cancer
%
of
income
share
65.5 %
22.3 %
9.1 %
OOP
expenditures
(MYR)
Other Healthcare Expenditure
Public Healthcare Fees
Travel & Transport

9. RESULTS: Prevalence of CHE
Household facing CHE
OPMD Oral cancer
p-valuea
freq % freq %
Over first-year 10 19.2 45 86.5 <0.0001
a Pearson Chi-square test for proportions with significance set to p< 0.05
86.5%
19.2%
OPMD Oral Cancer

10. RESULTS: Factors associated with CHE
Variable Characteristics Odd ratio p-valuea Adjusted
Odd ratio
Adjusted
p-value b
Ageb <59
>60 2.69 0.086 2.78 0.137
Gender Male
Female 1.46 0.502
Raceb Malay
Chinese 4.50 0.029 4.05 0.185
Indian 4.74 0.009 5.72 0.046*
Sarawak Bumiputera/others 3.43 0.092 5.62 0.143
Location Urban
Rural 1.29 0.630
Educationb No formal education/ Primary
Secondary/ Tertiary 0.47 0.162 0.72 0.590
Occupation Not working
Employed/ Self-employed /Retired 0.73 0.586
Incomeb >RM4360 (M40, T20)
<RM4360 (B40) 11.67 0.008 14.32 0.023*
a Sociodemographic variables were explored in univariate binary logistic regression by holding diagnosis
(OPMD or oral cancer) constant
b Multivariate binary logistic regression indicated that there was a significant collective effect between age
group, race, income group, education, and diagnosis with CHE, χ2(7) = 68.95, p< 0.001

11. DISCUSSIONS

12. DISCUSSION:
● Pattern of larger OOP share for travelling consistent in
countries with universal health coverage 1
● Larger travel cost in late stage cancer was contributed
by frequent visits for multidisciplinary care and longer
distance travelled by patients in rural areas
[MYR 896 (urban) vs MYR 1,870 (rural)]
● Traveling cost to access health services can become a
barrier, even if treatments are subsidized 2
1. Iragorri N, et al. The Out-of-Pocket Cost Burden of Cancer Care—A Systematic Literature Review. Current Oncology. 2021;28(2):1216-48.
2. Chauhan AS, et al. Economic Burden of Head and Neck Cancer Treatment in North India. Asian Pacific journal of cancer prevention: APJCP. 2019;20(2):403.

13. DISCUSSION:
● Indian ethnicity was not associated with late-stage
diagnosis and lower income. It may be interlinked with
CHE through other socio-economic factors
● B40 households spent larger percentages of their
income on healthcare than M40/T20 groups1
● However, OOP expenditures were similar across income
groups due to high subsidization and cost capping.
Thus, income was the determinant of CHE2
1. Kim Y, Yang B. Relationship between catastrophic health expenditures and household incomes and expenditure patterns in South Korea. Health policy. 2011;100(2-3):239-46.
2. O'donnell O, et al. Analyzing health equity using household survey data: a guide to techniques and their implementation: The World Bank; 2007

14. DISCUSSION:
● Despite the high subsidization, oral cancer in
Malaysia echoed similar financial burden with
other ASEAN countries 1,2
● Fixed-subsidization policies may not
necessarily cater to the poorer community
● PeKa B40 to incentivise patients is timely, but
none of the current respondents benefitted
from the initiative3
Treatment
completion
MYR 1,000
Travel &
Transport
MYR 1,000-5,000
PeKa B40
1. Raman S, et al. Provider cost of treating oral potentially malignant disorders and oral cancer in Malaysian public hospitals. Plos one. 2021;16(5):e0251760.
2. Kimman M, et al. CHE and 12-month mortality associated with cancer in Southeast Asia: Results from a longitudinal study in eight countries. BMC Medicine. 2015;13(1):190
3. Yap S-L, et al. Assessing the Relationship between Socio-demographic, Clinical Profile and Financial Toxicity: Evidence from Cancer Survivors in Sarawak. ACJPC. 2020;21(10):3077-83.

15. CONCLUSION:
CLINICIANS
Current provision of subsidies
and financial supports may
still be inadequate and
inaccessible to shield the
more vulnerable group from
CHE
POLICY MAKERS
1
2
Traveling to access health
services can become a financial
barrier, even if treatments are
highly subsidized

16. ACKNOWLEDGMENT
Universiti Sains Malaysia
Cancer Research Malaysia
Ministry of Health and Dental Health Program
USM Fundamental Research Grant Scheme (FRGS)
We would like to thank all the parties that
contributed towards the conduct of the study :

17. THANK YOU!