1 Role of Health Insurance in Averting Economic Hardship in Families After Acute Stroke in China Emma Heeley, PhD; Craig S. Anderson, MD; Yining Huang, MD; Stephen Jan, PhD; Yan Li, MD; Ming Liu, MD; Jian Sun, MD; En Xu, MD; Yangfeng Wu, PhD; Qidong Yang, MD; Jingfen Zhang, MD; Shihong Zhang, MD; Jiguang Wang, MD; for the ChinaQUEST Investigators Background and Purpose Stroke is a major health burden in China, but there are limited data on its economic effects on households. We aimed to examine the economic impact of stroke and to assess the influence of health insurance. Methods In a nationwide, prospective, 62-hospital registry study of acute stroke in China, we recorded information on patient demographics, clinical features, socioeconomic factors, management, and costs of medical care. Information on out-of-pocket health expenses was obtained in surviving patients at 3- and 12-month follow-up. Catastrophic healthcare payments, defined as 30% of total household annual income, were estimated from reported household annual income. Results Among month survivors of stroke with outcome data, average hospital and medication costs were Chinese Yuan Renminbi (US $2361) and out-of-pocket costs were Chinese Yuan Renminbi (US $2068). Overall, 3384 (71%) patients had experienced catastrophic out-of-pocket expenditure. Workers without health insurance were 7 times (OR, 6.9; 95% CI, 4.6 to 10.3) more likely to experience catastrophic payments than workers with insurance. Health insurance also protected against catastrophic payments in patients who were either retired or not working (no insurance: OR, 4.7; 95% CI, 3.1 to 7.2; OR, 1.82; 95% CI, 1.3 to 2.6, respectively). Conclusions Because healthcare costs are high relative to income in China, families face considerable economic hardship after stroke. Health insurance protects families against catastrophic healthcare payments, thus highlighting the need to accelerate the ongoing process of building a comprehensive healthcare system in both urban and rural settings in China. (Stroke. 2009;40: ) Key Words: epidemiology health policy stroke Over the last 3 decades, market reforms and trade liberalization policies have brought significant wealth and economic prosperity to the people of China. The downside to these changes, however, has been a decline in access to health care for the poor and increasing levels of out-of-pocket payments for health care. 1 The high costs of health care has meant that many people face the tragic choice of either forgoing treatment or incurring financial hardship with the onset of illness. 1 3 Stroke is an enormous health issue in China as the second most common cause of death, accounting for almost 20% of all deaths in both rural and urban settings. 4 As its huge population undergoes rapid aging, urbanization, and other lifestyle and social changes, stroke is an ever-increasing burden on the Chinese healthcare system. 5 In common with other forms of cardiovascular disease, stroke can have serious economic consequences to families due to loss of income and the cost of health care. 6 In China, where 60% of healthcare expenditure is financed from out-of-pocket payments, illness is a major cause of economic hardship and poverty. 7 There is no one accepted criterion for defining a level of payment that is defined as catastrophic ; criteria vary from 10% of income, 8,9 10% of household consumption, 10 and 40% of disposable income. 11 In a recent population-based survey, 13% of households in China were found to have incurred a catastrophic payment when defined as 10% of total household expenditure and 5% when defined as 40% of nonfood expenditure. 7 Alternatively, healthcare payments can be seen as catastrophic if, once payments are deducted from annual income, they push households below an absolute poverty threshold. 12,13 It is estimated that 13.7% of the population of China have incomes below a poverty threshold of US $1.08 per day and 44.6% below a threshold of US $2.15 per day. Out-of-pocket payments for health care have been shown to result in 32 million individuals (2.6% increase) being pushed below the US $1.08 a day income Received October 23, 2008; final revision received December 2, 2008; accepted December 3, From The George Institute for International Health (E.H., C.S.A., S.J.), Royal Prince Alfred Hospital and the University of Sydney, Sydney, Australia; Peking University First Hospital (Y.H.), Beijing, China; Shanghai Institute of Hypertension (Y.L., J.W.), Rui Jin Hospital, Shanghai Jiagtong University, Shanghai, China; West China Hospital (M.L., S.Z.), Sichuan University, Chengdu, China; The George Institute China (J.S., Y.W.), Peking University Health Science Center, Peking, China; The Second Affiliated Hospital of Guangzhou Medical College (E.X.), Guangzhou, China; Xiangya Hospital of Centre South University (Q.Y.), Changsha, China; and Baotou Cental Hospital (J.Z.), Baotou, Inner Mongolia, China. Correspondence to Emma Heeley, PhD, The George Institute for International Health, PO Box M201, Missenden Road, Camperdown NSW 2050, Australia American Heart Association, Inc. Stroke is available at DOI: /STROKEAHA
2 2150 Stroke June 2009 threshold and 23 million individuals (1.8% increase) pushed below the US $2.15 threshold. 13 Health insurance is seen as an important means of offering financial protection from such economic catastrophe. In urban areas of China, social health insurance schemes based on employment were introduced in 1998 with coverage provided principally to employees of state enterprises and some areas of the private sector In its early phase, the urban health insurance initiative was shown to have had some success in reducing the financial burden on patients 15 and in reducing overall cost pressures. 16 However, recent data suggest that the anticipated expansion of coverage has not materialized and that levels of participation among vulnerable groups such as women, low-income earners, rural to urban migrant workers, and employees on short-term contracts has been falling. 17 Furthermore, copayments and gaps in benefit packages can lead to potentially significant out-of-pocket costs, even for those with insurance. 18 The effects are being felt by the population; health care was the social issue of most concern of people interviewed as part of a recent nationwide survey of families conducted by the National Bureau of Statistics of China. 19 In a large hospital registry study, we aimed to examine the economic impact of stroke on households in China using data on self-reported healthcare expenditures. We aimed to determine the influence of health insurance coverage with varying levels of reimbursement and the socioeconomic situation on healthcare costs faced by families. Methods Design The China Quality Evaluation of Stroke care and Treatment (QUEST) study was a nationwide prospective 62 hospital registry study of the characteristics, management, and outcome of acute stroke due to cerebral infarction or intracerebral hemorrhage. At each site, key neurology investigators were trained in the protocol and procedures and were asked to recruit at least 50 consecutive patients who fulfilled standard definitions for stroke during a 5-month study period in The hospitals were provided with a small grant to assist clinicians with enrollment and the collection and entry of data using prospectively developed systems and a 12-month follow-up period. Patients (aged 18 years) were eligible if they had experienced an acute (first-ever or recurrent) stroke as defined by the World Health Organization standard definition of rapidly developing clinical signs of focal (or global) disturbance of cerebral function lasting more than 24 hours (unless interrupted by surgery or death) with no apparent cause other than of vascular origin. Acute strokes due to cerebral infarction or intracerebral hemorrhage diagnosed with neuroimaging, or of undetermined pathology without neuroimaging, were included; but those due to subarachnoid hemorrhage were excluded. A case managed in the hospital was defined as a registered admission to the hospital within 30 days of the onset of stroke. Case fatality was defined as the proportion of patients who died within a specified time interval from the onset of the stroke. Especially designed case record forms in Chinese were used to obtain baseline information that was extracted from medical records and by in-person interviews that included patient sociodemographic characteristics, medical history, presenting features, and the prehospital course. Patients were asked to indicate the total annual household income (Chinese Yuan Renminbi [CNY]) according to the following categories: 2000; 2000 to 4999; 5000 to 9999; to ; to ; to ; and Follow-up data on living arrangements, use of healthcare resources, health status, physical function, caregiver, and economic impact were collected through interviews at 3 and 12 months after the onset of stroke. Data were entered through the Internet to a secure, central, password-protected database located at The George Institute for International Health in Sydney, Australia. Sites were monitored to check the quality of conduct and to identify and correct any data-related discrepancies. Statistical Analyses The payment of medical expenses that included in-hospital treatment and the purchase of medications and equipment in the first 3 months after the onset of stroke were defined as catastrophic if out-of-pocket expenses accounted for 30% of total annual household income that was reported at baseline. Annual income was based on the midpoint of each of 7 predefined income bands with the highest band CNY assigned a value of CNY. For patients without health insurance, we assumed that they paid the full cost of hospital care and medications. For those with health insurance, out-of-pocket costs were estimated on the basis of 3 components of payment: (1) an up-front copayment of a fixed amount, which varied from 800 CNY (US $114) in poorer regions (eg, Chengdu, West China) to 2000 CNY (US $286) in richer regions (eg, Shanghai, East China), that is charged to patients on admission to hospital, or where an exact amount was not known, we assumed that the amount was 1000 CNY (US $143); (2) the excess of hospital expenses that were not covered by health insurance; and (3) the full 3-month cost of medications and posthospital care. The location of hospitals was either in a rich or poor area defined according to whether the 2004 Gross Regional Product per capita for the province was above or below the national average (2004 Gross Domestic Product per capita CNY [US $1509]). 20 Differences between groups were tested with using the 2 test for categorical variables, the independent t test for continuous variables, and the Mann Whitney U test for differences between medians. Sensitivity analysis were conducted on the proportion of patients experiencing catastrophic payments according to different levels of health insurance cover ( 25%, 25% to 50%, 51% to 75%, and 76% to 100%) and using 10%, 20% and 40% thresholds of out-of-pocket health expenses relative to household income. Proportions of patients who fall below the poverty line due to out-of-pocket expenses were calculated using 2 income threshold definitions of poverty, US $1 (2555 CNY) and US $2 (5110 CNY) per day, respectively, based on an exchange rate of US $1 being equivalent to 7 CNY, which is used throughout. To identify factors that predicted catastrophic payment of 30% or more of household annual income, we first conducted univariate logistic regression and then selected the significant variables (P 0.05) for a multivariate model. To take account of any effect of clustering at the hospital level, we obtained estimates adjusted for confounders using a random effects logistic regression model with hospital as a random effect and including 13 patient-level variables (age, gender, level of education, major lifetime occupation, main income earner or not, employment status, and the presence of comorbid cardiovascular disease or diabetes, type of stroke, severity of stroke on admission) where scores of 3 to 8 and 8 to 15 on the Glasgow Coma Scale 21 indicated moderate severe and mild grades of severity, respectively), health insurance status, disability at the time of hospital discharge (according to scores of 3 to 5 on the modified Rankin Scale 22 ), the number of readmissions to the hospital, and the location of the hospital in either a rich or poor area based on per capita Gross Regional Product. In developing the model, an interaction was found between employment status and health insurance; this was included as an interaction term and the effect of no insurance was analyzed separately for different categories of employment status. We estimated the discrimination of the model to predict those patients that experience catastrophic payments using an overall c statistic, which is analogous to the area under the receiver operating characteristic curve. All statistical analyses were conducted using STATA version 9.2 (Stata Corporation, College Station, Texas). Ethics Ethics committees of the hospitals accepted the approval of the ethics committee of either Peking University First Hospital (Beijing) or
3 Heeley et al Economic Impact of Stroke on Families in China patients screened for eligibility 6508 enrolled 6416 with complete baseline data 5557 survivors with 3 month follow up data 4739 survivors with complete 3 month cost data 6530 excluded 1890 (29%) final diagnosis not stroke 2137 (33%) not a recent acute stroke 2099 (32%) refused to participate 202 (3%) died rapidly before enrolment 202 (3%) other reasons 81 ineligible 42 (52%) Not a recent acute stroke 27 (33%) final diagnosis not stroke 11 (14%) missing data 859 excluded 697 (81%) deaths 112 (13%) missing 3 month data 50 (6%) from a single hospital in Hong Kong 818 excluded 723 (88%) no income data 82 (10%) no cost data 113 (14%) neither income or cost data Figure 1. Flow of patients. Ruijin Hospital (Shanghai); the study was also approved by ethics committees at the Prince of Wales Hospital (Hong Kong) and The University of Sydney. Good clinical practice guidelines in accordance with the Declaration of Helsinki were used and the privacy of patients was strictly protected. Written informed consent was obtained from all patients or an appropriate family member in situations in which the patient was disabled. Results Figure 1 shows the flow of patients. Of 5557 patients who were alive and available for interview at 3 months poststroke, 818 were excluded from the analyses due to missing data on income or healthcare expenditure. Although these patients had the same distribution of gender, age, baseline stroke severity, and level of disability at hospital discharge as the 4739 patients with complete information, they were more often from the wealthy provinces and less likely to report difficulties in making payments for food, accommodations, and other necessities ( 2 12 and 16, respectively; both P 0.005). There were 82 of these patients who did provide some income data; they had significantly higher levels of income than the 4739 patients with complete information ( 2 19, P 0.001). In the month survivors of stroke, a total of 3384 (71%) were estimated to have experienced catastrophic healthcare costs according to the threshold of 30% annual income (Table 1). Table 1 shows the demographics of these patients overall and according to whether they had experienced catastrophic costs. Patients with nonmanual jobs and higher incomes were less likely to experience catastrophic payments, although these variables were interrelated because nonmanual workers earned relatively higher salaries ( P 0.001). Catastrophic payments occurred more often in those patients without health insurance (47%) than in those with health insurance (14%). Only a minority (14%) of patients with health insurance reported paying this entirely by themselves; most (86%) had health insurance paid either in full or subsidized by a third party, typically their employer. Other factors that were more frequent in those experiencing catastrophic costs were having had strokes that were more severe at onset, due to intracerebral hemorrhage, or resulting in greater disability at hospital discharge. Patients who experienced catastrophic payments also reported that they were under financial stress as a result of having to meet out-of-pocket expenses. Table 2 shows that on average, patients with catastrophic payments had hospital costs of CNY (US $2653) and out-of-pocket costs of CNY (US $2320) compared with CNY (US $1645) hospital costs and CNY (US $1438) out-of-pocket costs in those without catastrophic payments. As expected, the proportion of patients experiencing catastrophic costs decreased with increasing level of health insurance coverage. The association was apparent across different thresholds, from 10% to 40% costs of annual household income (Figure 2). Because the level of health insurance coverage indicated in Figure 2 pertains only to the residual hospital costs after the upfront copayment had been made, and does not include the initial copayment and costs of medications, there were still a large number of patients who experienced catastrophic costs (ie, the copayment and medication costs alone represented 30% of annual household income) even among those with 100% level of health insurance coverage. Table 3 indicates the effect of out-of-pocket payments in relation to poverty thresholds, which at US $1 per day indicates that 1650 (37%) of patients with premorbid annual household incomes above this threshold fell below it once out-of-pocket costs were deducted. This effect was more pronounced in people with no health insurance, with 62% (978) falling below the threshold as a result of out-of-pocket payments compared with 23% (672) of those with health insurance. In developing a predictive model for catastrophic payments at the 30% threshold of annual household income, an interaction was identified between employment status (working/ nonworking/retired) and health insurance, necessitating an interaction term being used in the multivariate model. ORs were therefore presented on the effect of health insurance within workers, and retired and nonworkers, separately (Table 4). Workers without health insurance were nearly 7 times more likely to experience catastrophic costs than workers with health insurance (OR, 6.87; 95% CI, 4.59 to 10.27). Health insurance remained protective against catastrophic payments in patients who were retired and nonworkers (OR for no insurance, 4.71; 95% CI, 3.07 to 7.20 and 1.82; 95% CI, 1.25 to 2.64, respectively). Overall, patients with stroke who presented to the hospital with no health insurance had higher incomes (41% [1218 of 2961] versus 15% [286 of 1778]) with annual household incomes CNY (US $2857); P 0.001), males (67% versus 53%, P 0.001), younger (mean age, 61 versus 65 years; P 0.001), and where the patient was the main earner in the household (72% versus 44%; P 0.001) than in patients who presented with health
4 2152 Stroke June 2009 Table 1. Baseline Characteristics of Patients Overall and by Catastrophic Payments From Medical Expenses After Acute Stroke* Catastrophic Payments Total (n 4739) Yes (n 3384) No (n 1355) Age, years 63 (12) 63 (12) 65 (12) Males 2932 (62%) 2007 (59%) 925 (68%) Married 4003 (84%) 2848 (84%) 1155 (85%) Main earner in household 2910 (61%) 1988 (59%) 922 (68%) Occupation Nonmanual worker 2186 (46%) 1354 (40%) 832 (61%) Manual worker 2273 (48%) 1790 (53%) 483 (36%) No lifetime occupation or unknown 280 (6%) 240 (7%) 40 (3%) Highest level of schooling completed None 894 (19%) 708 (21%) 186 (14%) Primary 1293 (27%) 1020 (30%) 273 (20%) Junior middle 1316 (28%) 932 (28%) 384 (28%) Secondary and above 1236 (26%) 724 (21%) 512 (38%) Total household income, CNY 9999 ( US $1428) 1731 (37%) 1703 (50%) 28 (2%) (US $ ) 1522 (32%) 1263 (37%) 259 (19%) ( US $2857) 1486 (31%) 418 (12%) 1068 (79%) Level of health insurance coverage None 1778 (38%) 1586 (47%) 192 (14%) 25% 135 (3%) 120 (4%) 15 (1%) 25% 179 (4%) 167 (5%) 12 (1%) 50% 457 (10%) 339 (10%) 118 (9%) 75% 2069 (44%) 1137 (34%) 932 (69%) 100% 121 (3%) 35 (1%) 86 (6%) Patients living in a poor provincial area 1740 (37%) 1368 (40%) 372 (27%) Pathological type of stroke Cerebral infarction 3682 (78%) 2515 (74%) 1167 (86%) Intracerebral hemorrhage 1013 (21%) 830 (25%) 183 (14%) Unknown 44 (1%) 39 (1%) 5 (0%) Severe Glasgow Coma Scale score on presentation 226 (5%) 196 (6%) 30 (2%) Median time from stroke onset to presentation (hours) 16 (3 53) 16 (3 55) 17 (3 50) Median length of stay in hospital (days) 17 (12 24) 17 (12 25) 17 (13 24) Disabled at hospital discharge 1745 (37%) 1388 (41%) 357 (26%) *Data are mean (SD), no. (percentage), or median (interquartile range). Catastrophic payments defined as out-of-pocket expenses that are 30% of total household annual income. Manual work includes construction, farming/forestry/fishing and related, installation and related, manufacture and production, transportation and driver occupations. Nonmanual work includes management, professional and related, service, sales/commercial, armed forces, and clerical/administration support occupations. Poor provincial area defined as below the national average of CNY (US $1509) per capita gross regional product in Severe score 8 in range 3 (low) to 15 (high, normal). Disability defined as score of 3 to 5 on the modified Rankin Scale. 22 insurance. A higher proportion of workers and retired patients who presented to the hospital had health insurance (55% and 89%, respectively) compared with nonworkers (16%). Other factors that predicted catastrophic payments were being the main income earner in the household (OR, 1.60; 95% CI, 1.31 to 1.94), a manual worker (OR, 1.33; 95% CI, 1.11 to 1.59), less educated (OR no schooling compared with secondary or above 2.69; 95% CI, 2.21 to 3.27), having an intracerebral hemorrhage (OR, 1.26; 95% CI, 1.02 to 1.55), a severe stroke at admission (OR, 1.71; 95% CI, 1.11 to 2.72), being disabled at hospital discharge (OR, 2.01; 95% CI, 1.69 to 2.4), and having multiple readmissions to the hospital (OR, 1.33; 95% CI, 1.14 to 1.54). Discussion Our large countrywide study provides evidence to support growing concerns of rising economic burden from healthcare costs in the general population of China. 1,2 We have shown
5 Heeley et al Economic Impact of Stroke on Families in China 2153 Table 2. Medical Expenses and Outcomes Overall and by Catastrophic Payments From Medical Expenses After Acute Stroke* Total (n 4739) Yes (n 3384) Catastrophic Payments No (n 1355) P Total cost of medical expenses in the first 3 months, CNY Mean Coefficient of variation Median Out-of-pocket expenses in the first 3 months, CNY Mean Coefficient of variation Median Out-of-pocket expenses in first 3 months as a proportion of total annual household income Mean 158% 214% 17% Coefficient of variation Median 57% 89% 17% Patients experiencing catastrophic payments 3384 (71%) 3384 (100%) Outcomes at 12 months Dead 174 (4%) 139 (4%) 35 (3%) Disabled 1112 (23%) 854 (25%) 258 (19%) Dead or disabled 1286 (27%) 993 (29%) 293 (22%) Reported financial stress 925 (20%) 723 (21%) 202 (15%) Reported unable to pay for preventative medications 907 (19%) 653 (19%) 254 (19%) *Data are no. (percentage). Catastrophic payments defined as out-of-pocket expenses that are 30% of total household annual income. To convert CNY to US dollars, divide by 7. Coefficient of variation is equal to the SD divided by the mean. Disability defined as score of 3 to 5 on the modified Rankin Scale. 22 P value for the difference between those experiencing catastrophic payments and those not. Financial stress was defined as being unable to pay utilities or living costs, or having to borrow money, to meet out-of-pocket medical expenses. that acute stroke imposes catastrophic healthcare payments in the majority of households with an affected individual with many at risk of impoverishment. Health insurance can avert these risks albeit provided there is a high enough level of coverage ( 75%) as was present in nearly half of the patients in this study. Given the looming regional epidemic of stroke and other chronic diseases, our findings re-emphasize the need for initiatives to expand health insurance coverage in both rural and urban settings in China and also in other developing countries where out-of-pocket expenses comprise a significant proportion of healthcare financing. 13 Such initiatives would need to be augmented by efforts to ensure that the level of coverage offered provides adequate levels of financial protection. Greater financial autonomy in the health sector and reduced government subsidies to hospitals and health centers in China has led to market-oriented financing strategies for health providers that have driven up costs, reduced the provision of primary care and preventive services, and moved resources away from rural areas where the majority of the population resides. 1,2 These and other changes have led to a fragmentation of the healthcare system, the emergence of health inequities, and exposure of individuals, their families, and communities to increased stress from the impact of chronic diseases such as stroke. 1,2,5 Our study shows that health insurance provides protection from such effects, particularly in workers, although those with no health insurance but still presenting to the hospital tend to be those with higher incomes and thus potentially have sufficient confidence in their ability to access resources to pay hospital bills. A previous multicity population-based study showed that there is generally a high (83%) number of patients hospitalized with stroke in China with higher frequencies in developed urban compared with rural populations. 23 It is possible that patients with low household incomes and without health insurance who experience stroke are not presenting to the hospital, but our study was not designed to address the pathways of care outside the hospital. The level of health insurance coverage has been highlighted as being an important aspect to the protection from experiencing catastrophic payments offered to households. Even so, the cost of the initial copayment and medication costs in the first 3 months poststroke alone (which are generally not covered by health insurance) can still constitute a catastrophic payment for many patients despite them having the nominal 100% coverage of health insurance.
6 2154 Stroke June Patients experiencing catastrophic costs (%) % 30% 20% 10% Figure 2. Effects of stroke in causing catastrophic payments using different thresholds. 0 None <25% 25-50% 50-75% % 100% Level of insurance cover Another approach to examining the impact of out-ofpocket health expenses is to consider the extent to which households with incomes above the poverty level are brought below this level once such expenses are deducted. On the basis of this measure, we found that 37% of patients (and their families) fell below the poverty line set at US $1 per day and 39% when it was set at US $2 per day after stroke. However, having health insurance was protective (23% with compared with 62% without health insurance falling below the poverty line of US $1 per day). Our study has limitations that deserve comment. First, we indirectly elicited the data on out-of-pocket expenses for each patient and based them on self-reported total medical costs and the patient s level of health insurance coverage. Such extrapolation may have resulted in some error because it may not have captured variations in the type of insurance coverage held by individuals, although we believe this is unlikely to have greatly influenced the results. Second, there is the potential that we overestimated the proportion of patients who experienced catastrophic payments after stroke because the 818 patients who were excluded from the study due to incomplete income or healthcare expenditure data tended to reside in the wealthier provinces. However, given that the data were generally derived from urban or semiurban areas of major cities, it is more likely that we have underestimated the effects of stroke in rural populations. Moreover, because our data set was based entirely on a hospital-based cohort, we did not include those who may not have accessed care for various reasons, including the barrier imposed by potential costs. These people would most likely have been from poorer segments of the community and without health insurance. Finally, due to having only outcomes to 12 months, we were unable to ascertain the long-term economic impact of stroke, particularly in relation to ongoing treatment, rehabilitation, and readmissions to hospital, although other studies have highlighted that the major costs of stroke occur within the first few months of the event. 24 Despite these limitations, our study provides evidence to support changes in the healthcare system in China. Currently the Chinese government is consulting on a multipronged initiative to improve the health of China s 1 3 billion residents by The key to this round of health system reform is to increase government spending on health and committing to health insurance for the whole population, including people in rural areas and nonworkers. 26 This is a massive undertaking and must be encouraged because this should help reduce inequities in health care. In the interim, however, the rolling out of health insurance schemes to workers and nonworkers nationwide should help avoid such catastrophic payments associated with stroke being experienced by many families, although it is likely that the coverage provided through the redesign of current schemes 17,18 will alone be inadequate to remove the risk of economic catastrophe. Table 3. Proportions of Patients in Poverty From Payment of Medical Expenses After Stroke* Poverty Line US $1 per Day Poverty Line US $2 per Day Patients with incomes above the poverty line at the onset of stroke People who were above and moved below the poverty line due to out-of-pocket expenses Total Health Insurance No Health Insurance Total Health Insurance No Health Insurance (n 4739) (n 2961) (n 1778) (n 4739) (n 2961) (n 1778) 4466 (94%) 2885 (97%) 1581 (89%) 3984 (84%) 2731 (92%) 1253 (70%) 1650 (37%) 672 (23%) 978 (62%) 1560 (39%) 766 (28%) 794 (63%) *Proportions of patients who fell below the poverty line due to out-of-pocket medical expenses were calculated using 2 definitions of the poverty line, US $1 (2555 CNY) and US $2 (5110 CNY) per day, respectively, based on an exchange rate of US $1 being equivalent to 7 CNY. Denominator, patients who were above the poverty line at baseline.
7 Heeley et al Economic Impact of Stroke on Families in China 2155 Table 4. Predictors of Catastrophic Payment of Medical Expenses After Stroke Variable Crude OR (95% CI) P Adjusted* OR (95% CI) P Age group, years (reference) 1.0 (reference) ( ) ( ) ( ) ( ) ( ) ( ) Female 1.48 ( ) ( ) Highest level of schooling completed Secondary and above 1.0 (reference) 1.0 (reference) Junior middle 1.72 ( ) ( ) Primary 2.64 ( ) ( ) None 2.69 ( ) ( ) Occupation Nonmanual worker 1.0 (reference) 1.0 (reference) Manual worker 2.28 ( ) ( ) No lifetime occupation or unknown 3.69 ( ) ( ) Main income earner in household 0.67 ( ) ( ) Employment Working 1.0 (reference) Retired 0.64 ( ) Not working 3.13 ( ) Health insurance status None 5.34 ( ) None in working patients 6.87 ( ) None in retired patients 4.71 ( ) None in nonworking patients 1.82 ( ) Current cigarette smoker 0.82 ( ) Living in a poor area compared to rich area 1.79 ( ) ( ) Medical history Previous cardiovascular disease 0.77 ( ) ( ) Known diabetes mellitus 0.73 ( ) ( ) Stroke characteristics Intracerebral hemorrhage versus other 2.08 ( ) ( ) Severity of stroke on admission Moderate 1.0 (reference) 1.0 (reference) Severe 2.73 (1.85, 4.03) ( ) Unknown 1.71 (0.86, 3.43) ( ) Length of stay in hospital (days) ( ) Disability at discharge Not disabled 1.0 (reference) 1.0 (reference) Disabled 1.94 ( ) ( ) Disability unknown 0.61 ( ) ( ) Multiple readmissions to hospital 1.14 ( ) ( ) C statistic 0.75 *Model adjusted for all variables with significant ORs in univariate analyses. In the multivariate analyses, there was an interaction between working status and health insurance. Therefore, data are presented on the effect of no insurance in workers, retired, and nonworkers separately. In workers, there were 398 without and 482 with health insurance. In retired patients, there were 248 without and 2083 with health insurance. In nonworkers, there were 1132 with and 396 without health insurance. Previous cardiovascular disease was defined as a history of any prior stroke or transient ischemic attack, prior myocardial infarction, and known prior atrial fibrillation. Stroke severity defined by Glasgow Coma Scale, 21 in which moderate is for scores 8 to 15 (high, normal) and severe for scores 3 to 7. Disability defined as score of 3 to 6 on the modified Rankin Scale. 22
8 2156 Stroke June 2009 These findings in relation to the extent of out-of-pocket payments and level of economic catastrophe associated with stroke can be generalized to urban China. For rural China, however, where there are greater levels of poverty and lower levels of health insurance coverage, it is likely that a greater proportion of patients will fail to present to the hospital; and when they do, they are more likely to face greater risk of economic catastrophe from stroke and similar acute disabling illnesses. Sources of Funding The ChinaQUEST study was supported by grants from the Macquarie Bank Foundation, The George Foundation, and AstraZeneca Pharmaceutical China. Dr Alexander Headley, and also Dr Dashiel Gantner who assisted with the study, were supported by the AusAID Australian Youth Ambassadors for Development scheme over 12- month periods during 2005 to Acknowledgments We thank the scientific, data management, and statistical teams associated with the study and all the patients and their families for their cooperation in participating in the study. Disclosures C.S.A. receives salary support from The George Institute for International Health and as a Principal Research Fellow of National Health and Medical Research Council (NHMRC) of Australia. He reports receiving grant support and consulting and lecture fees from Astra Zeneca, Boehringer Ingelheim, Sanofi-Aventis, and Servier; J.W. reports receiving consulting and lecture fees from Astra- Zeneca, Boehringer Ingelheim, GSK, Novartis, Pfizer, Sanofi- Aventis, Servier, and Takeda and grants from Mitsubish-Tanabe through the Shanghai Institute of Hypertension. References 1. Liu T. 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