| Literature DB >> 16504017 |
Hideo Yasunaga1, Hiroo Ide, Tomoaki Imamura, Kazuhiko Ohe.
Abstract
BACKGROUND: The application of Willingness To Pay (WTP) measurement with Contingent Valuation Method (CVM) to medical services is gradually increasing. Knowing what influences WTP is an important matter because validity of CVM in medical services remains controversial. The objective of this survey is to measure WTP for the treatment of typical acute illnesses and to analyze the factors affecting WTP.Entities:
Mesh:
Year: 2006 PMID: 16504017 PMCID: PMC1395359 DOI: 10.1186/1472-6963-6-12
Source DB: PubMed Journal: BMC Health Serv Res ISSN: 1472-6963 Impact factor: 2.655
Figure 1The relationship between the presented price and the number of individuals who are willing to pay more than the price. Y = α e, X: presented price [USD], Y: the number of tolerant individuals, α, β: constant, R2: coefficient of determination.
Figure 2WTP by Annual Income. Horizontal axis: presented price, Vertical axis: the ratio of individuals who can tolerate purchasing the medical services at a higher price than the presented price.
Mean WTP by annual income and results of Kruskal Wallis test for comparison of mean WTP among three groups
| Annual Income | Common Cold | Retinal Detachment | Myocardiac Infarction |
| Low income group (n = 92) | 30.0 | 1,929 | 7,728 |
| Medium income group (n = 371) | 29.7 | 2,205 | 8,725 |
| High income group (n = 266) | 29.8 | 2,399 | 9,440 |
| p-value | 0.910 | 0.044 | 0.049 |
Results of ordinal regression analysis
| 40–44 | -0.118 | 0.58 | 0.447 |
| 45–49 | 0.017 | 0.01 | 0.917 |
| 50–54 | 0.075 | 0.19 | 0.667 |
| 55–59 | Reference | ||
| Male | -0.016 | 0.03 | 0.853 |
| Female | Reference | ||
| Low | -0.077 | 0.32 | 0.574 |
| Medium | 0.014 | 0.02 | 0.876 |
| High | Reference | ||
| Have insurance | 0.058 | 0.40 | 0.527 |
| Don't have insurance | Reference | ||
| Yes | 0.075 | 0.83 | 0.362 |
| No | Reference | ||
| Bad | 0.277 | 5.96 | 0.015 |
| Average | 0.218 | 4.97 | 0.026 |
| Good | Reference | ||
| Pseudo-r square = 0.018 | |||
| 40–44 | -0.011 | 0.00 | 0.949 |
| 45–49 | -0.099 | 0.30 | 0.586 |
| 50–54 | -0.023 | 0.01 | 0.904 |
| 55–59 | Reference | ||
| Male | -0.077 | 0.67 | 0.414 |
| Female | Reference | ||
| Low | -0.484 | 8.98 | 0.003 |
| Medium | -0.136 | 1.86 | 0.172 |
| High | Reference | ||
| Have insurance | -0.012 | 0.01 | 0.905 |
| Don't have insurance | Reference | ||
| Yes | 0.172 | 3.48 | 0.062 |
| No | Reference | ||
| Bad | 0.184 | 2.07 | 0.150 |
| Average | 0.142 | 1.62 | 0.203 |
| Good | Reference | ||
| Pseudo-r square = 0.021 | |||
| 40–44 | 0.117 | 0.42 | 0.518 |
| 45–49 | 0.099 | 0.28 | 0.597 |
| 50–54 | 0.177 | 0.78 | 0.377 |
| 55–59 | Reference | ||
| Male | -0.215 | 5.18 | 0.023 |
| Female | Reference | ||
| Low | -0.481 | 8.82 | 0.003 |
| Medium | -0.157 | 2.47 | 0.116 |
| High | Reference | ||
| Have insurance | -0.004 | 0.00 | 0.969 |
| Don't have insurance | Reference | ||
| Yes | 0.064 | 0.48 | 0.490 |
| No | Reference | ||
| Bad | 0.087 | 0.46 | 0.496 |
| Average | 0.104 | 0.88 | 0.349 |
| Good | Reference | ||
| Pseudo-r square = 0.022 | |||
Descriptive Statistics (n = 795)
| 40–44 | 385 | 48% |
| 45–49 | 218 | 27% |
| 50–54 | 125 | 16% |
| 55–59 | 67 | 8% |
| Male | 463 | 58% |
| <10,000 USD | 13 | 2% |
| 10,000–20,000 | 11 | 1% |
| 20,000–30,000 | 27 | 3% |
| 30,000–40,000 | 41 | 5% |
| 40,000–60,000 | 153 | 19% |
| 60,000–80,000 | 218 | 27% |
| 80,000–100,000 | 139 | 17% |
| 100,000–150,000 | 105 | 13% |
| >150,000 | 22 | 3% |
| Don't want to answer | 68 | 8% |
| Have Insurance | 546 | 69% |
| Don't have insurance | 221 | 28% |
| Don't want to answer | 28 | 4% |
| Yes | 381 | 48% |
| Very good | 58 | 7% |
| Good | 165 | 21% |
| Average | 376 | 47% |
| Slightly bad | 178 | 22% |
| Bad | 18 | 2% |