| Literature DB >> 28392749 |
Sharifa Ezat Wan Puteh1, Siti Nurul Akma Ahmad2, Azimatun Noor Aizuddin1, Ramli Zainal3, Ruhaini Ismail4.
Abstract
BACKGROUND: Malaysia is an upper middle income country that provides subsidized healthcare to ensure universal coverage to its citizens. The challenge of escalating health care cost occurs in most countries, including Malaysia due to increase in disease prevalence, which induced an escalation in drug expenditure. In 2009, the Ministry of Health has allocated up to Malaysian Ringgit (MYR) 1.402 billion (approximately USD 390 million) on subsidised drugs. This study was conducted to measure patients' willingness to pay (WTP) for treatment of chronic condition or acute illnesses, in an urbanized population.Entities:
Keywords: Acute diseases; Chronic conditions; Urban state; Willingness-to-pay; drugs expenditure
Year: 2017 PMID: 28392749 PMCID: PMC5379617 DOI: 10.1186/s12930-017-0035-5
Source DB: PubMed Journal: Asia Pac Fam Med ISSN: 1444-1683
Frequency distribution of patients’ socio-demographic
| Variables | Frequency (n = 324) | % |
|---|---|---|
| Age (years) | ||
| Younger (18–47) | 169 | 52.2 |
| Older (48 and above) | 155 | 47.8 |
| Gender | ||
| Male | 146 | 45.1 |
| Female | 178 | 54.9 |
| Ethnicity | ||
| Malay | 192 | 59.3 |
| Chinese | 30 | 9.3 |
| Indian | 95 | 29.3 |
| Others | 7 | 2.2 |
| Marital status | ||
| Married | 256 | 79.0 |
| Single | 52 | 16.1 |
| Widow | 16 | 4.9 |
| Level of education | ||
| Lower level of education | 246 | 75.9 |
| Higher level of education | 78 | 24.1 |
| Personal income | ||
| Lower income (RM0-950) | 163 | 50.3 |
| Higher income (RM951 and above) | 161 | 49.7 |
| Household income | ||
| Lower income (RM0-1900) | 165 | 50.9 |
| Higher income (RM1901 and above) | 159 | 49.1 |
| Disease status | ||
| Chronic conditions | 162 | 50.0 |
| Acute illness | 162 | 50.0 |
| Insurance status | ||
| Yes | 103 | 31.8 |
| No | 221 | 68.2 |
| NHI implementation | ||
| Yes | 181 | 55.9 |
| No | 130 | 40.1 |
| Not sure | 13 | 4.0 |
The association between socio-demographic factors and willingness to pay for drugs (n = 324)
| Variables | WTP for drugs | χ2 | p value | |
|---|---|---|---|---|
| Yes (%) | No (%) | |||
| Age (years) | ||||
| 18–47 | 21 (12.4) | 148 (87.6) | 2.446 | 0.118 |
| 48 and above | 29 (18.7) | 126 (81.3) | ||
| Gender | ||||
| Male | 25 (17.1) | 121 (82.9) | 0.582 | 0.445 |
| Female | 25 (14.0) | 153 (86.0) | ||
| Ethnicity | ||||
| Malay | 29 (15.1) | 163 (84.9) | 0.039 | 0.844 |
| Non-Malay | 21 (15.9) | 111 (84.1) | ||
| Marital status | ||||
| Married | 43 (16.8) | 213 (83.2) | 1.741 | 0.187 |
| Single | 7 (10.3) | 61 (89.7) | ||
| Level of education | ||||
| Lower level of education | 36 (14.6) | 210 (85.4) | 0.499 | 0.480 |
| Higher level of education | 14 (17.9) | 64 (82.1) | ||
| Personal income | ||||
| Lower level (RM0-950) | 18 (11.0) | 145 (89.0) | 4.842 |
|
| Higher level (RM951 and above) | 32 (19.9) | 129 (80.1) | ||
| Household income | ||||
| Lower level (RM0-1900) | 18 (10.9) | 147 (89.1) | 5.271 |
|
| Higher level (RM1901 and above) | 32 (20.1) | 127 (79.9) | ||
| Number of children | ||||
| Less than 3 | 37 (19.1) | 157 (80.9) | 4.909 |
|
| 4 and above | 13 (10.0) | 117 (90.0) | 1.051 | |
| Status of prior insurance | ||||
| Have insurance | 19 (18.4) | 84 (81.6) | 0.305 | |
| No insurance | 31 (14.0) | 190 (86.0) | ||
WTP willingness to pay
* p < 0.05; χ Pearson Chi Square
Logistic regression of influencing factors towards willingness to pay
| Variable | β | S.E | Wald | p value | Exp (β) | 95% CI for exp (β) | |
|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||
| Age | |||||||
| Older | 0.428 | 0.441 | 0.941 | 0.332 | 1.534 | 0.646 | 3.642 |
| Younger | 1.000 | ||||||
| Gender | |||||||
| Male | 0.037 | 0.342 | 0.012 | 0.913 | 1.038 | 0.531 | 2.031 |
| Female | 1.000 | ||||||
| Ethnicity | |||||||
| Non-Malay | 0.047 | 0.337 | 0.019 | 0.889 | 1.048 | 0.542 | 2.027 |
| Malay | 1.000 | ||||||
| Marital status | |||||||
| Married | 0.576 | 0.483 | 1.419 | 0.234 | 1.778 | 0.690 | 4.585 |
| Single | 1.000 | ||||||
| Level of education | |||||||
| Higher level | 0.128 | 0.425 | 0.091 | 0.763 | 1.137 | 0.494 | 2.616 |
| Lower level | 1.000 | ||||||
| Personal income | |||||||
| Higher level | 0.449 | 0.477 | 0.887 | 0.346 | 1.567 | 0.615 | 3.988 |
| Lower level | 1.000 | ||||||
| Household income | |||||||
| Higher level | 0.510 | 0.403 | 1.600 | 0.206 | 1.666 | 0.755 | 3.673 |
| Lower level | 1.000 | ||||||
| Type of occupation | |||||||
| Employed | 0.092 | 0.454 | 0.041 | 0.840 | 1.096 | 0.450 | 2.671 |
| Unemployed | 1.000 | ||||||
| Number of dependents | |||||||
| 0 to 3 | 0.965 | 0.372 | 6.732 | 0.009** | 2.625 | 1.266 | 5.442 |
| 4 and above | 1.000 | ||||||
| Type of health condition | |||||||
| Chronic | 0.033 | 0.406 | 0.007 | 0.935 | 1.034 | 0.467 | 2.290 |
| Acute | 1.000 | ||||||
| TCM practice | |||||||
| Practice TCM | 0.045 | 0.375 | 0.014 | 0.905 | 1.046 | 0.502 | 2.179 |
| Not practice TCM | 1.000 | ||||||
| Health insurance | |||||||
| No health insurance | −0.127 | 0.382 | 0.110 | 0.740 | 0.881 | 0.416 | 1.864 |
| With health insurance | 1.000 | ||||||
β standardized coefficient, S.E standard error, Exp (β) odds ratio
** p < 0.05