понедельник, 8 октября 2012 г.

States tackle the health insurance crisis. (State Policy Watch).(Brief Article) - Healthcare Financial Management

The problems just don't seem to want to go away. Small - employer health insurance premiums continue to skyrocket at double-digit rates. Individuals' health spending continues to rise through higher premium sharing, deductibles, and copayments. The number of uninsured individuals continues to grow.

And states continue to struggle to meet the challenges. State legislators are seeking policies that will make health insurance more affordable, particularly in the small-group market. According to results of the Health Policy Tracking Service's 2003 Health Care Priorities Survey, 38 states intend to make health insurance issues a top priority.

Enacted Legislation

Although the 2002 sessions focused primarily on balancing state budgets, a few states, such as Colorado and Maine, managed to enact significant reform measures. The Colorado bill allowed small-group carriers to sell high-deductible plans with medical savings accounts.

In Maine, Coy. Angus King signed into law bills establishing the Small Business Coverage Plan and Consumer Choice Health Plan. The Small Business Coverage Plan establishes a private-public partnership designed to provide healthcare coverage to small employers, self-employed individuals, and their employees and dependents. The Consumer Choice Health Plan is an independent executive agency charged with negotiating and purchasing healthcare coverage for both individuals and small employers. The plan's five-member board of directors is charged with contracting with participating health insurance carriers to offer at least three health benefit plans to enrollees-a fee-for-service plan, a managed care plan, and a point-of-service plan.

Legislation on the Table

To date in the 2003 legislative sessions, several states have introduced various proposals that address the current health insurance crisis.

Twelve states--California, Colorado, Georgia, Hawaii, Indiana, Maine, Missouri, Montana, New Hampshire, New Mexico, New York, and Pennsylvania--have introduced legislation establishing tax credits/tax deductions to offset the cost of rising health insurance premiums.

Five states have introduced purchasing alliance legislation. Montana introduced legislation that amends its current purchasing-pool provisions by decreasing the number of employees needed to form a voluntary purchasing pool from 1,000 to 51. The other states that have introduced legislation establishing purchasing alliances or amending existing requirements are Arkansas, New York, Tennessee, and Utah.

In his state-of-the-state address, Wisconsin governor Jim Doyle mentioned that he would establish a statewide health insurance purchasing pool, targeting small businesses and farmers. Details were not provided in his address.

Four states--Colorado, Oklahoma, South Dakota, and Vermont-introduced legislation establishing or changing the state's high-risk pool.

And although radical coverage bills are unlikely to be enacted, nine states--California, Connecticut, Hawaii, Maine, Massachusetts, Minnesota, Missouri, New York, and Vermont--introduced legislation that either establishes a publicly funded single-payer system or an employer-based healthcare coverage system that would provide health insurance coverage to every employee.

Outlook

Regarding mandated-benefit legislation, HPTS anticipates that relatively few states will enact new coverage requirements for insurers during the 2003 sessions, compared with the results of past surveys. Instead, legislators may introduce bills that would allow insurers to sell 'bare-bones' or stripped-down policies-- policies that don't provide coverage for all the state-mandated health benefits-to create more affordable health insurance policies. Arkansas, North Dakota, and Utah have enacted bills that allow for the provision of 'barebones' health insurance policies in their respective health insurance markets.

State lawmakers may continue requiring cost-benefit analyses to accompany bills providing coverage for specified benefits and services. Since 2001, six states--California, Florida, Louisiana, North Dakota, South Carolina, and West Virginia--have enacted legislation to study the financial impact of assessing new coverage requirements and/or evaluating current coverage mandates.

While Congress continues to deliberate the various measures before it, state policymakers will continue to seek solutions and enact policies that will make health insurance more accessible and affordable for their constituents. State policymakers are in a better position to address innovative policies that will provide an overall decrease in the number of uninsured nationwide by taking quicker action on proposals that make it easier for individuals and small businesses to purchase affordable health insurance policies.

RELATED ARTICLE: STATE HEALTHCARE INFORMATION

Following is a list of various on-line resources offering a wealth of information about state-level healthcare delivery and financing.

CMS Directories

State and Federal Medicaid Contacts (www.cms.hhs.gov/medicaid/mcontact.asp)

CMS Intermediary and Carrier Directory (cms.hhs.gov/contacts/ incardir.asp)

CMS: State Children's Health Insurance Program (SCHIP) Status Report and Contact Information (www.cms.hhs.gov/schip/ statepln.asp)

State Government Directories

State and Local Government on the Net (www.piperinfo.com/ state/index.cfm)

State Insurance Department Web Sites (www.naic.org/lregulator/ usamap.htm)

Federal Agencies and Research Organizations

Census Bureau (www.census.gov) provides national and state-level statistics on population, poverty, area profiles, and more.

Center for Studying Health System Change (www.hschange.com) offers reports on healthcare costs, coverage, emerging market trends, and more.

CMS Health Care Indicators (cms.hhs.gov/statistics/health-indicators/default.asp) contains data and analysis of recent trends in healthcare spending, employment, and prices and the anticipated direction and magnitude of healthcare cost changes.

Kaiser Family Foundation (www.kff.org) funds research to help inform policymakers and the public on key healthcare issues. Includes State Health Facts Online, a free resource that will be especially useful in identifying other key state resources (www.statehealthfacts.kff.org).

National Center for Health Statistics (www.cdc.gov/nchs) provides a wealth of healthcare-related data, including life expectancy, leading causes of death, hospital utilization, and key national indicators of well-being. Some data are available at the state level.

воскресенье, 7 октября 2012 г.

DOYLE SIGNS BILL THAT CREATES REGIONAL HEALTH INSURANCE POOLS.(LOCAL/WISCONSIN) - The Wisconsin State Journal (Madison, WI)

Byline: Robert Imrie Associated Press

WAUSAU -- Thousands of farm families, small business owners and self-employed workers in Wisconsin became eligible Thursday for a new program designed to help them get more affordable health insurance.

Gov. Jim Doyle signed legislation into law that creates five regional health insurance purchasing cooperatives with the power to pool individuals to negotiate directly with health insurance providers and collectively bargain for cheaper coverage.

Wisconsin farmers face a health-care crisis, already paying three times as much for their health insurance as salaried employees working for a company, Doyle said.

'We can raise prices and productivity of our farmers, but it won't matter if increased profits just go to cover rising health-care premiums or if farms go under because our farmers can't afford health-care coverage for their families,' Doyle said.

The governor said some Wisconsin farmers pay $1,900 a month for health insurance premiums that include a $2,500 annual deductible.

'It is no wonder 25 percent of Wisconsin farmers have no health insurance coverage at all,' Doyle said.

It's believed the new alliances can negotiate health insurance policies that lower the premiums at least 10 percent and perhaps as much as 35 percent compared to what farmers now pay, said Bill Oemichen, president and CEO of the Wisconsin Federation of Cooperatives, a primary advocate of the legislation.

DO ADULT CHILDREN MATTER?-THE EFFECTS OF NATIONAL HEALTH INSURANCE ON RETIREMENT BEHAVIOR: EVIDENCE FROM TAIWAN - Contemporary Economic Policy

This paper examines the effect of the 1995 implementation of National Health Insurance (NHI) on retirement behavior in Taiwan. The identification strategy is based on the fact that, in Taiwan, adult children offer significant insurance to elderly parents. The results suggest that NHI had significant effects on retirement among the elderly lacking an adequate traditional 'safety net.' NHI raised the conditional probability that a male, private sector worker over the age of 51 would retire by more than 60%. However, men with a stronger safety net in the form of adult sons were less responsive to NHI.

(JEL I18, J14, J26)

ABBREVIATIONS

DGBAS: Directorate-General of Budget, Accounting and Statistics

FI: Farmer's Insurance

GEI: Government Employee's Insurance

LFPR: Labor Force Participation Rate

LI: Labor Insurance

NHI: National Health Insurance

OECD: Organisation for Economic Co-operation and Development

(ProQuest: ... denotes formulae omitted.)

I. INTRODUCTION

Population aging and low fertility rate have brought a challenge to more and more countries as the growth in early retirement places an unsustainable burden on the younger generation. Between 2006 and 2050, the projected percentage of population aged 60 yr or older will grow worldwide from 11% to 22%, in North America from 17% to 27%, in Europe from 21% to 34%, in China from 11% to 31%, and in Japan from 27% to 42% (United Nations, Department of Economic and Social Affairs, Population Division, 2006). However, labor force participation among senior populations is decreasing with time. As a result, increasing the labor force participation rate (LFPR) of people aged 55-64 yr is one of the major goals of social policy within the European Union under the Lisbon and Amsterdam Treaties (Leibfritz, 2003).

Previous studies of retirement behavior mainly document that health status and postretirement income (including pensions, disability insurance, or social security) are primary determinants of one's retirement decision. However, before 1990, there was virtually no work on the impact of health insurance on labor supply and job mobility decisions (Gruber and Madrian, 2002). As medical costs continue to rise globally, the availability of postretirement health insurance has since 1990 drawn much attention in this line of research. The U.S. literature suggests that access to postretirement health insurance or pensions makes early retirement more attractive (Currie and Madrian, 1999; Gruber and Madrian, 1995, 2002; Madrian, 1994; Rogowski and Karoly, 2000). Medicare is also an important concern when workers in the United States consider the timing of their retirement (Madrian and Beaulieu, 1998; Rust and Phelan, 1997). Gruber and Madrian (1995) found that 1 yr of continuation of coverage raises the retirement hazard by 30% in the United States. They concluded that policies to provide universal health insurance coverage could lead to a large increase in the rate of early retirement. On the other hand, there has been little investigation into this issue in Asian countries where aging is as prominent as it is in Western societies. This article addresses this gap by conducting a case study for Taiwan. In Taiwan, postretirement health insurance was limited to government employees before the introduction of National Health Insurance (NHI) on March 1, 1995. Because NHI provides universal health insurance coverage for all citizens, private workers gain postretirement health insurance. This social experiment makes it feasible for economists to examine people's response to postretirement health insurance when they consider their labor force participation decisions.

Mete and Schultz (2002) conducted the first analysis of the effect of Taiwan's NHI on labor force participation among the elderly. Their study comparing public workers (who always had postretirement health insurance) to private workers (who gained postretirement health insurance) suggested that NHI had little impact. However, their work does not take into account a pension reform in the public sector that occurred at the same time. This paper develops a new identification strategy based on the strong tendency among Taiwanese adult children to provide their elderly parents with significant 'family insurance.' Specifically, the author questions whether or not NHI has had a greater impact on people with fewer adult children. The effects of health insurance on retirement decisions may differ in Taiwan compared to Western countries because the elderly depend on their children to a much greater extent. In fact, despite an increasing trend toward living independently, the majority of elderly Taiwanese citizens still live with their children. Moreover, most adult children (no matter whether they reside with their parents or not) offer substantial financial support to their parents. These facts are in line with the argument of Kotlikoff and Spivak (1981) that families can self-insure against uncertainties. Therefore, elderly citizens with a 'safety net' in the form of supportive children could be less responsive to public programs. One noteworthy social norm in Taiwan is that adult sons take more responsibility for supporting their parents than do adult daughters. Consequently, the author also attempts to examine whether prospective retirees consider the gender of their children when assessing the potential role of their adult children in securing their economic future.

This study constructs a duration data set from the Survey of Health and Living Status of the Middle Aged and Elderly in Taiwan. Drawing on estimates from a proportional hazard model, the empirical analysis obtains two findings. First, NHI raised by more than 60% the conditional probability that a male, private sector worker over the age of 51 would retire. However, men with more adult sons were less responsive to NHI than their counterparts. Second, men with more adult sons had a significantly higher conditional probability of retirement (retirement hazard) than men with fewer adult sons and women with more adult daughters had a significantly higher conditional probability of retirement than women with fewer adult daughters. This difference is particularly striking for women given social norms dictating that sons take primary responsibility of their aging parents.

Until April 2007, 30 countries in the world had implemented a universal health care system, while many others had debated whether they should introduce one. Implementing NHI in a nation without postretirement health insurance is equivalent to providing postretirement health insurance to senior citizens. This study can help policymakers to assess the extent to which NHI or similar programs would affect labor markets, especially in societies with family caretaking social norms similar to those in Taiwan. Because the financing of many welfare and social insurance programs in various countries is payroll related, the resulting increase in early retirement not only causes a decrease in aggregate output as more experienced and productive workers leave the labor force but also influences the financing of these public programs. These associated long-term effects need to be accounted for by policymakers in considering NHI or similar policies.

The rest of this paper proceeds as follows. Section II provides the background. Section III describes the data. After explaining methods in Section IV, the author presents results in Section V. Section VI concludes and provides directions for future research.

II. BACKGROUND

A. Trends in Elderly Labor Force Participation

As in many countries, the LFPR of the elderly population in Taiwan has decreased over the past several decades. A growing tendency toward earlier retirement contributes to this decline (Directorate-General of Budget, Accounting and Statistics [DGBAS], Executive Yuan, Taiwan, 2001a, 2001b). These trends have continued since the 1995 implementation of NHI. For example, LFPR among male workers aged 65 yr and older was 14.39% in 1995 but fell to 11.54% in 2002. LFPR among men aged 50-64 yr decreased by approximately 10 percentage points between 1995 and 2002. Despite a slight increase in LFPR for women aged 50-54 yr, women over 55 yr experienced a decline in LFPR after 1995. Because of these preexisting time trends, a before-and-after analysis is insufficient to answer the research question posed by this paper. Rather, an identification strategy based on the traditional family safety net in Taiwan will be adopted in the following analysis.

B. Dependence on Children among the Elderly

The number of adult children is not a common predictor for retirement decision in previous research focusing on Western societies. Because most Western countries have a wellestablished social insurance system and welfare programs, senior citizens have not needed to depend on their children after retirement.1

On the contrary, the elderly in Taiwan depend on their children in many ways. First, most elderly parents live with their children. Although more senior citizens have chosen to live independently in recent years, the fraction of people living with their children was still over 60% in 1996 (Kan, Park, and Chang, 2001). This rate remained as high as 75.6% among elderly Taiwanese women in 2000 (The Ministry of the Interior, Taiwan, 2002). Second, many adult children, regardless of whether they live with their parents, provide parents with financial aid. Among those over 65 yr, 47.13% of respondents said that the majority of their financial support came from their children, while 15.39% and 13.72% said that the majority came from pensions and labor income, respectively. Sixty-three percent of women over 65 yr reported that the majority of their financial support came from their children, whereas 6.2% said that support was derived from pensions and only 9.8% from labor income (The Ministry of the Interior, Taiwan, 2002). Third, children are important caregivers when parents are hospitalized.2 Among elderly males over 50 yr, 37.48% stated that their wife cared for them and 29.01% said that their children cared for them when they were hospitalized. Among women over 50 yr, 16.02% stated that their husband took care of them and 40.45% said that their children took care of them when they were hospitalized (The Ministry of the Interior, Taiwan, 2000). Finally, many children pay their parents' medical expenses.3 Among the 3,511 individuals who answered the question 'Who paid most of your medical fees last year?' in the 1989 wave of the Survey of Health and Living Status of the Middle Aged and Elderly in Taiwan, 39.82% of respondents chose 'myself,' 27.11% chose 'insurance,' and 26.63% chose 'children or children-in-law.' If we restrict the sample to respondents with children, we find that 39.87% of respondents chose 'myself,' 26.19% 'insurance,' and 28.05 % 'children or children-in-law.'

Lee, Parish, and Willis (1994) used the 1989 Taiwan Family and Women Survey to study intergenerational support in Taiwan. Their evidence shows that the loan hypothesis and the insurance hypothesis implied by the altruism model are highly consistent with their data. Repayment of parents' human capital investment in children is an important reason behind adult children's financial support. These findings explain the source of children's altruism toward their parents in Taiwan. In short, because adult children act as a safety net for the elderly, NHI coverage is expected to be more valuable to senior citizens with fewer adult children.

C. Health Insurance in Taiwan

NHI was formally implemented in Taiwan in March 1995 and provides universal health insurance coverage to all citizens. Before the implementation of NHI, an individual could obtain health insurance through one of three programs-labor insurance (LI), farmer's insurance (FI), and government employee's insurance (GEI). These insurance programs are government sponsored and tied to an individual's employment status. GEI covers government employees, LI covers private employees and a few blue-collar workers in the public sector, and FI covers farmers. There is very little private health insurance coverage in Taiwan.

In 1994, the year immediately preceding the implementation of NHI, 2.95% of the population were covered by GEI, 0.67% by retired government employees' insurance, 8.23% by FI, and 40.22% by LI. The 48% of the population without health insurance coverage were mostly children, housewives, and senior citizens. Because of the enforcement of NHI, the percentage of the population with health insurance coverage increased from 52% in 1994 to 96% in 2000. NHI consolidates the previous health insurance system through replacing maternity, injury, and illness benefits of GEI, LI, and FI programs. It also covers severe illnesses and preventative health care services. The NHI premium is payroll related, the deduction being shared by the employee, employer, and government. For outpatient visits, the out-of-pocket expense ranges from NT$50 to NT$360.4 For hospitalization, the co-payment ranges from 5% to 30% for both acute and chronic care, depending on length of stay in the hospital. In the case of severe illness or injury, no co-payment is required (Chou, Liu, and Hammitt, 2003).

Two differences between NHI and previous public health insurance programs are relevant here. First, postretirement health insurance was only available in the GEI plan before the introduction of NHI. Consequently, the previously LI-insured and FI-insured are expected to find early retirement more attractive after 1995. Second, unlike GEI and FI, LI does not provide insurance coverage for dependents. Hence, the generosity of NHI coverage may provide the previous LI-insured additional incentive to retire earlier in that NHI now covers all their dependents.

Mete and Schultz (2002) conducted the first investigation of the effect of Taiwan's NHI on labor force participation among the elderly. Drawing on 1989, 1993, and 1996 data from the Survey of Health and Living Status of the Middle Aged and Elderly in Taiwan, they used public workers as a control group and found that NHI did not contribute to a reduction in LFPRs of the elderly in 1996. However, in 1995, the Taiwanese government introduced a pension reform to the public sector, changing the original unfunded system into a fully funded system.5 This new policy might have affected the labor force participation of public workers and makes the control group (government employees) of Mete and Schultz (2002) suspect.

Two previous studies examined the effect of NHI on other outcomes. Chou and Staiger (2001) showed that NHI was associated with a decline of 4.6 percentage points in the labor force participation of women aged 20-65 yr whose husbands were paid employees. The effect was larger (6.7 percentage points) among wives of less educated men. Chou, Liu, and Hammitt (2003) documented that NHI lowered average savings by 6.9% and raised average consumption by 2.4%. The effect on savings was especially strong for the households with the least savings. However, these results must be interpreted with caution because, like the investigation conducted by Mete and Schultz (2002), these studies relied on government employees as the control group.

III. DATA

This paper constructs a duration data set from the Survey of Health and Living Status of the Middle Aged and Elderly in Taiwan.6 This survey was initiated in 1989 with 4,049 respondents aged 60 yr or older. Of these, 3,155, 2,669, and 2,310 individuals were reinterviewed in the 1993, 1996, and 1999 followups, respectively. Launching a second panel of individuals aged 50-66 yr in 1996 extended the survey. The completed second sample contains 2,462 individuals. For convenience, the author will denote the original panel as the 'old panel' and the new panel as the 'young panel.' Because NHI started in 1995, the empirical investigation in this paper will use the 1989, 1993, 1996, and 1999 surveys (of both the old panel and the young panel).

The Survey of Health and Living Status of the Middle Aged and Elderly in Taiwan provides rich information about an individual's background characteristics, family structure, marital history, health status, residential history, and employment history (e.g., occupation, start date, end date, and employment status of each job after age 50). This allows the author to construct a unique duration data set characterizing a worker's job history from age 50 onward. The younger cohort's job history began in later years. Although a few work histories in the old panel go back as far as the 1950s, most people's work history began after 1960. In order to have a time period more comparable to the 1990s, when NHI was introduced, the author confines the analysis to the period 1980-1999.

Although the Survey of Health and Living Status of the Middle Aged and Elderly in Taiwan has a panel structure that facilitates the task of investigating a senior citizen's retirement behavior in a dynamic framework, this survey provides limited information about an individual's income, wealth, and consumption and neither is detailed age-varying income available. Each respondent was asked about income from jobs in 4 yr (1989, 1993, 1996, and 1999) only. Because the response rate to these questions was very low, interviewers asked people who declined to report their exact income about the 'range' of income instead. But the response rate was low even in this case. Therefore, the author does not use this information.

A. The Definition of Retirement

According to Madrian (1994), the definitions of retirement include (a) a permanent departure from the labor force, (b) a substantial reduction in the number of hours worked, (c) self-reported retirement, and (d) receipt of pension or social security benefits.

The 1989 survey of the old panel contains self-reported retirement status and age at retirement. These data come from the following questions: 'Have you ever retired from work? If so, how long ago?' Another question concerning retirement is 'When did you stop doing your last job?'8 The 1993, 1996, and 1999 surveys, however, ask only the second question, which is more ambiguous than the self-reported one. In order to identify 'retirement' more precisely, this paper uses the 1989 retirement status as a starting point for the old panel. The author traces each respondent's subsequent labor force attachment in the 1993, 1996, and 1999 follow-ups and updates his/her retirement status accordingly except for those who left the survey due to attrition. If an individual self-reported himself/herself retired in 1989 and did not resume working between 1989 and 1999, then he/she is considered to be retired and permanently out of the labor force according to Definition (a). If an individual self-reported himself/herself retired in 1989, but resumed work afterward, the individual is not categorized as 'retired' unless he/she stopped working again later on. A similar procedure is applied to the young panel.

To prevent the loss of information from deceased or lost subjects (a 'mover') in the follow-ups, this paper employs an unbalanced panel. A mover who had already retired when he/she left the survey is included in the sample. A mover who was still working when he/she left the survey is treated as a general righthand censoring-the survival time is measured from the time of entrance (entered the state of 'being at risk of retiring') to the last contact. In essence, when constructing the duration data set, the author traced each individual until he/she retired or became censored.

Individuals who had never worked and the self-employed are excluded from the sample. People over 80 yr in 1996 are also excluded from the sample to avoid the impact of outliers. In addition, the sample excludes workers who stopped working due to layoff, shutdown, or business failure so that voluntary retirement is highlighted. Because it is difficult to define retirement for farmers, they are also excluded from the sample. Due to the pension reform in the public sector starting in 1995, public employees are not included in the sample either. In sum, the following analysis focuses on private employees in nonagricultural sectors.

B. Survival Functions

A survival function derived from the above duration data set can measure the probability of a person working at least until a specific age (i.e., the survival rate). In other words, it shows the probability that a person retires after a specific age. The comparison of unconditional survival rates among various demographic groups is helpful before any regression analysis. For example, the Kaplan-Meier survival estimates of male private employees working in nonagricultural sectors (Figure 1) show that men with NHI coverage (NHI =1) have lower survival rates than men without NHI coverage (NHI = 0). This difference is obvious for most age groups in Figure 1. On the other hand, in Figure 2, the distinction between the survival rate of women with NHI coverage and the survival rate of women without NHI coverage is not as noticeable as that in the men's sample. It shows that women could respond to the policy to a less extent than men. To explore this gender difference further, the author investigates the policy effect on men and women separately in Section V.

Breaking down the sample into groups with different family safety nets gives us more insight into people's retirement behavior. In particular, the comparison between Figure 3 and Figure 4 indicates that the decrease in survival rate after NHI for observations with no adult children is of greater magnitude than that for observations with three or more adult children.

In other words, elderly employees with a weaker safety net (as in Figure 3) are more responsive to NHI than their counterparts (Figure 4). This observation motivates a new approach to identify the policy effect in this paper. Because people with different numbers of adult children alter their retirement decision in different ways in response to NHI, it has become feasible to measure the policy effect in spite of the preexisting trend toward early retirement. In light of this, the following empirical analysis will use an interaction term between the NHI indicator and the number of adult children to capture the effect of NHI.

IV. METHODS

As Hausman and Wise (1985) suggested, retirement behavior can be modeled in the following hazard framework.9 Define the age of retirement of any particular person as a continuous random variable, A, and denote a as a realization of A. Furthermore, consider a large population of people who entered the state of being at risk of retiring at 51 yr.10 Then, the probability that a person has retired by age a is given by the distribution function:

where the hazard function A(.) > 0. This specification has an intuitive interpretation that the probability of retirement goes to 1 as an individual gets older (i.e., when a gets larger).

The Cox proportional hazard model with age-varying covariates can be specified by the hazard relationship as follows:

where h^sub 0^(a) is an arbitrary and unspecified baseline hazard function; Z(a) = (z^sub 1^, z^sub 2^(a)) consists of age-invariant covariates z^sub 1^ and age-varying covariates z^sub 2^(a) and β is a column vector of regression parameters. In this framework, h(a; Z(a)) represents the 'retirement hazard' that measures the probability that a worker would retire at age a, given that this worker was still working before age a. Therefore, it is the conditional probability of retirement at age a.

The proportional hazard model is nonparametric in that it involves an unspecified baseline hazard function. Estimating a flexible model like this prevents the analysis from deriving conclusions driven by a specific parametric assumption. Consequently, the conclusions in this article will be robust and independent of the choice of functional form of the baseline hazard function. This study uses Cox's partial-likelihood estimation to estimate β. It was shown by Cox (1975) that the method used to construct this likelihood offers maximum partial likelihood estimates that are consistent and asymptotically normally distributed (Kalbfleisch and Prentice, 1980).

The explanatory variables in the model (Z(a)) consist of age-invariant variables z^sub 1^ and age-varying variables z^sub 2^(a). These are summarized in Table 1.

Inspired by the comparison between Figure 3 and Figure 4 in Section III, the following empirical analysis will include not only the policy indicator NHI^sub a^ but also the number of adult children at age a and an interaction term between these two variables. These will help test whether individuals with different numbers of adult children behaved differently before and after the introduction of the NHI program.

Table 2 provides the observation-level descriptive statistics by numbers of adult children.

The men's sample and the women's sample both show that workers with no adult children are more likely to be single persons and mainlanders.11 In order to investigate whether mainlanders have a different taste for retirement or not, the author runs a set of beforeNHI regressions.

Results in Table 3 suggest that mainlanders did not behave significantly differently from the other demographic groups before the implementation of the NHI program.12

V. RESULTS

The main spirit of the empirical model in Equation (2) is that all workers of the same age group (say, age a) 'compete' to retire given that they were still working before age a. Therefore, age is a fixed constant for each 'competition.' Table 4 shows estimates of Equation (2) for private employees in nonagricultural sectors from 1980 to 1999. The number of retirees and censored individuals are presented in each regression too. Instead of reporting coefficient estimates, the author presents the more intuitive exponential coefficients, which are the hazard ratios.

In order to investigate the gender difference shown in Figures 1 and 2, we can focus on the full sample and read the relative hazard ratio of men and women (i.e., ea in Equation (A4) of the Appendix). Table 4 shows that this relative hazard ratio is approximately 0.7 and statistically significant. In other words, the retirement hazard (the conditional probability of retirement) of males is 30% less than that of females. This is consistent with the stylized fact that men tend to stay in the labor market longer than women do. Breaking down the sample into men and women, the results show that a male employee with a spouse has a significantly lower retirement hazard than a single man. However, the spouse effect for women workers is not significant.14

Individuals with chronic conditions have a significantly higher retirement hazard rate than their counterparts. This indicates that healthier workers stay in the labor market longer. It is also expected that people with chronic conditions change their retirement behavior after they obtain eligibility for NHI. For individuals with chronic conditions at age a, the relative hazard ratio e^sup β^sub 1^^+^sup β^sub 3^^ (see Equation (A6) in the Appendix) measures their average response to the policy. The estimate based on specification [1] in Table 4 provides a significant ratio equal to 1.570 (z = 2.233) for all workers. The men's sample reacts significantly to the policy as well (e^sup β^sub 1^^+^sup β^sub 3^^ = 1.906 [z = 2.5291). However, the response of women (e^sup β^sub 1^^+^sup β^sub 3^^ = 1.031 [z = 0.088]) is not statistically significant. Other things being equal, the average influence of NHI on observations without chronic conditions is reflected by e^sup β^sub 1^^. It is 1.639 (z = 2.29) for the full sample, 1.953 (z = 2.44) for men, and 1.103 (z = 0.26) for women. These estimates show that the increase in the conditional probability of retirement among people with chronic conditions is less than that of their counterparts. It is possible that people with chronic illnesses received better health care and became more productive after the implementation of NHI.

The key estimates in this paper are hazard ratios for the number of adult children ac^sub a^, the policy indicator NHI^sub a^, and the interaction effect spotlighted by ac^sub a^ � NHI^sub a^. As expected, employees with more adult children have a significantly higher retirement hazard than their counterparts. Considering individuals with aca adult children at age a, e^sup β^sub 1^^+^sup β^sub 5^^ (see Equation (A10) of the Appendix) gives the ratio of after-policy retirement hazard to the before-policy retirement hazard. Other things being equal, e^sup β^sub 1^^ measures the average response of people without adult children. Take regression [1] in Table 4 as an example. The average increase in the conditional probability of retirement for people without adult children is significantly greater than 60% for the full sample (e^sup β^sub 1^^ = 1.639 [z = 2.29]). On the other hand, for people with one adult child in the full sample, the response to NHI (e^sup β^sub 1^^+^sup β^sub 5�1^^) is equal to 1.524 and is statistically significant (z = 2.137). For people with two adult children in the full sample, the response to NHI e^sup β^sub 1^^^sup β^sub 57times;2^^ is equal to 1.417 and is statistically significant too (z = 2.035). Evidently, the safety net's effect is smaller for people with more adult children.

Because adult sons and their families take most of the responsibility for the care of parents in Taiwan, the author also tries to test whether there exists gender bias when prospective retirees consider potential financial support from their adult children. The author replaces the predictor aca with 'the number of adult sons' and 'the number of adult daughters' to probe differences in retirement decisions caused by the gender of children. It is interesting that elderly men with more adult sons had a significantly higher retirement hazard than men with fewer adult sons and elderly women with more adult daughters had a significantly higher retirement hazard than women with fewer adult daughters. We can use specification [2] in Table 4 to test the presence of this gender bias. The findings show that the marginal effect (the growth in retirement hazard) caused by one additional son is 25% more than that caused by one additional daughter for male employees (see Equation (A11) in the Appendix; e^sup γ^sub 1^^/e^sup γ^sub 2^^ = 1.251 (z = 2.699) according to Table 4), while the marginal effect of one additional son is 11% less than that of one additional daughter for female employees (e^sup γ^sub 1^^/e^sup γ^sub 2^^ = 0.886 [z = -1.424]). In other words, male employees are significantly more dependent on adult sons, while women are more dependent on adult daughters.

Specification [2] in Table 4 suggests that male employees' response to NHI decreases significantly with the number of adult sons. In this light, the number of adult sons is relevant when men changed their retirement behavior in response to NHI. To focus on the effect of adult sons, the author employs a specification with the number of sons, but not the number of daughters, as a predictor for the men's sample. The response to NHI (the increase in retirement hazard after 1995) associated with this specification is summarized in Table 5. It is shown that the response to NHI is a decreasing function of the number of adult sons for men.

In addition, these estimates are significantly different from each other (e^sup β^sub 5^^ = 0.864 [z = - 1.84]). Men with four or more sons are expected to respond to NHI program with smaller and less significant growth in retirement hazard.16 Overall, NHI raised the conditional probability (retirement hazard) that a male worker with no adult children would retire by more than 60% (e^sup β^sub 1^^ = 1.613 [z = 1.89]). However, men with a stronger safety net in the form of adult sons are less responsive to NHI.

Comparing male employees with different numbers of adult sons, we see that people with a weak familial safety net (only one adult son) increase their retirement hazards significantly after NHI. The more adult sons a man has, the smaller and less significant his to NHI. In short, male private employees with more adult sons respond to NHI in lesser magnitude than their counterparts.17 Notice that elderly women are insensitive to NHI. Perhaps this is due to the fact that the female sample is relatively small in the data set.18

In summary, the NHI coverage is less important for individuals with more adult children. So the insurance provided by adult children offsets part of NHI's effects on retirement. For men, NHI increases their conditional probability of retirement by more than 60%. However, their response to NHI significantly decreases with the number of adult sons. This interesting phenomenon is in accord with Taiwanese social norms.

VI. CONCLUSIONS

This article quantifies the impact of NHI on an individual's retirement behavior. Taking advantage of the longitudinal structure of the Survey of Health and Living Status of the Middle Aged and Elderly in Taiwan, this study builds a duration data set to evaluate how prospective retirees with varying numbers of adult children responded to NHI. The evidence suggests that NHI raised the conditional probability that a male worker in the private sector over the age of 51 would retire by more than 60%. The magnitude of the support from adult children makes parents behave differently when NHI was implemented. Particularly, elderly males who had a stronger safety net in the form of adult sons were less responsive to NHI. This could be a phenomenon unique to an East Asian country like Taiwan, where social security and health insurance systems are not well established and the elderly often depend on their adult children.

In an important review of the literature, Gruber and Madrian (2002) pointed out that there was virtually no work on the impact of health insurance on labor supply and job mobility decisions before 1990. Although more than 50 scholarly articles have been written since 1990, most of them focus on the U.S. data. The case study of Taiwan in this paper adds new evidence to this line of research. In addition, it provides an opportunity to compare the empirical evidence from a Western country with that from an Asian country. For example, Gruber and Madrian (1995) showed that 1 yr of continuation of health insurance coverage raises the retirement hazard by 30% in the United States. Their paper concluded that policies to provide universal health insurance coverage could lead to a large increase in the rate of early retirement and impact the financing of such policies. The response (the increase in retirement hazard) to NHI from the male sample with three sons in this article is also approximately 30% (e^sup β^sub 1^^+^sup β^sub 5^^�3 = 1.267 in Table 5, i.e., NHI raises the retirement hazard by 26.7%), albeit people with weaker family safety nets responded in greater magnitude to NHI. The findings in this article not only support the assertion that postretirement health insurance has an impact on retirement but also show that this impact differs across various demographic groups.

Comparing this article's estimated effects with the evidence from Medicare in the United States, it is conjectured that Medicare might have less impact on retirement if there were similar familial safety nets in the United States. For example, people with employer-provided health insurance but without employer-provided retiree health insurance might be more willing to leave the labor force before the statutory retirement age if they had additional financial support from their children. Madrian and Beaulieu (1998) documented that the lack of Medicare-dependent coverage creates an incentive for men who are covered by employer-provided health insurance and are themselves Medicare eligible to continue working until their wives are Medicare eligible as well. This effect might be less pronounced if adult children in the United States provided more financial assistance to their parents.

The evidence in this paper also presents differing gender bias among men and women. It was found that, consistent with Taiwanese social norms, male employees with more adult sons had a significantly higher conditional probability of retirement than men with fewer adult sons. However, female employees with more adult daughters had a significantly higher conditional probability of retirement than women with fewer adult daughters. Due to limited information, the author could not model fertility choice in this paper. If a suitable data set is available in the future, incorporating the joint decision of fertility and other life cycle choices into a sequential decision model would present an interesting direction for future research.

Finally, one caveat should be addressed. The safety net effect found in this study may represent an initial impact only. People may alter the degree of dependence on their children in the long run now that a national program is in place. Therefore, it is possible that the safety net effect will wane in the future.

As aging societies and increasing health care costs are becoming global phenomena, more countries are calling for reforms in welfare programs in response to changes in the social and economic environment. For example, the Organisation for Economic Co-operation and Development (OECD) stated that the aging of OECD societies in the future will require comprehensive reforms addressing the fiscal, financial, and labor market implications of aging, as well as the implications for pension, social benefits, and systems of health care and long-term care (OECD, 2007). The empirical findings in this paper could provide insight to policymakers in different countries. In developed countries, immigration is increasing and most immigrants come from societies relying on family insurance. These immigrants may respond to health insurance policies differently from people who rely less on their families for financial support. In developing countries, the family safety net is usually very important. Policymakers who propose to introduce universal health care, retiree health insurance policies, or universal pension plans in developing countries should expect to see various policy effects across different demographic groups. These issues pose both interesting directions for future study as well as ongoing concerns for policymakers. The author leaves these for future research.

[Reference]

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Chou, Y. J., and D. Staiger. 'Health Insurance and Female Labor Supply in Taiwan.' Journal of Health Economics, 20, 2001, 187-211.

Cox, D. R. 'Partial Likelihood.' Biometrika, 62, 1975, 269-76.

Currie, J., and B. C. Madrian. 'Health, Health Insurance and the Labor Market.' in The Handbook of Labor Economics, Vol. 3C, edited by O. C. Ashenfelter and D. Card. Amsterdam: North Holland, 1999, 3309-416.

Directorate-General of Budget, Accounting and Statistics, Executive Yuan, Taiwan. 'The Analysis of the Trend in Labor Force Participation Rate.' 2001a.

_____. 'The Analysis of the Employment of the Middle-aged and the Old-aged Workers in Taiwan.' 2001b.

_____. 'The Statistical Report of National Situation.' 2001c.

_____. 'The Statistical Report of National Situation, No. 170.' 2002.

Gruber, J., and B. C. Madrian. 'Health-Insurance Availability and the Retirement Decision.' American Economic Review, 85, 1995, 938-48.

_____. 'Health Insurance, Labor Supply, and Job Mobility: A Critical Review of the Literature.' NBER Working Paper Series, Working Paper No. 8817, 2002.

Hausman, J. A., and D. A. Wise. 'Social security, Health Status, and Retirement, ' in Pensions, Labor and Individual Choice, edited by D. A. Wise. Chicago: University of Chicago Press, 1985, 159-91.

Kalbfleisch, J. D., and R. L. Prentice. The Statistical Analysis of Failure Time Data. New York: John Wiley & Sons, 1980.

Kan, K., A. Park, and M. C. Chang. 'A Dynamic Model of Elderly Living Arrangements in Taiwan.' Manuscript, 2001.

Kotlikoff, L. J., and A. Spivak. 'The Family as an Incomplete Annuities Market.' Journal of Political Economy, 89, 1981, 372-91.

Lee, Y. J., W. L. Parish, and R. J. Willis. 'Sons, Daughters, and Intergenerational Support in Taiwan.' American Journal of Sociology, 99, 1994, 1010-41.

Leibfritz, W. 'Retiring Later Makes Sense.' OECD Observer. 2003. http://www.oecdobserver.org/news/fullstory.php/aid/824/Retiring_later_makes_sense.html. Accessed March 2007.

Madrian, B. C. 'The Effect of Health Insurance on Retirement.' Breakings Papers on Economic Activity, I, 1994, 181-252.

Madrian, B. C., and N. D. Beaulieu. 'Does Medicare Eligibility Affect Retirement?' in Inquiries in the Economics of Aging, edited by D. A. Wise. Chicago, IL: University of Chicago Press, 1998, 109-31.

McGarry, K. 'Caring for the Elderly: The Role of Adult Children.' in Inquiries in the Economics of Aging, edited by D. A. Wise. Chicago, IL: University of Chicago Press, 1998, 133-63.

Mete, C, and T. P. Schultz. 'Health and Labor Force Participation of the Elderly in Taiwan.' Yale University, Economic Growth Center Discussion Paper No. 846, 2002.

Organisation for Economic Co-operation and Development. 'Ageing Society.' 2007. http://www.oecd.org/topic/0, 2686,en_2649_37435_1_1_1_1_37435, 00.html. Accessed March 2007.

Rogowski, J., and L. Karoly. 'Health Insurance and Retirement Behavior: Evidence from the Health and Retirement Survey.' Journal of Health Economics, 19, 2000, 529-39.

Rust, J., and C. Phelan. 'How Social Security and Medicare Affect Retirement Behavior in a World of Incomplete Markets.' Econometrica, 65, 1997, 781-831.

[Reference]

The Ministry of the Interior, Taiwan. 'Summary and Analysis of the Survey of the Status of the Elderly in Taiwan.' 2000.

_____. 'The Analysis of Living Status of Elderly Women.' 2002.

United Nations, Department of Economic and Social Affairs, Population Division. 'Population Ageing 2006.' 2006. http://www.un.org/esa/populauon/publications/ageing/ageing2006chart.pdf. Accessed March 2007.

van der Klaauw, W., and K. I. Wolpin. 'Social Security and the Retirement and Savings Behavior of Low Income Households.' Manuscript, 2006.

[Author Affiliation]

HSIN-LING HSIEH*

[Author Affiliation]

* This study is based on the data from the Survey of Health and Living Status of the Middle Aged and Elderly in Taiwan provided by the Bureau of Health Promotion, Department of Health, R.O.C., Taiwan. The descriptions or conclusions herein do not represent the viewpoint of the Bureau. The author especially thanks the Bureau of Health Promotion at the Department of Health in Taiwan for providing data. This is a revision of a paper presented at the Pacific Rim Conference of the Western Economic Association International (WEAI), Taipei, Taiwan, January 2003, in a session organized by Jack W. Hou, California State University, Long Beach. The author is very grateful to Janet Currie, Paul Devereux, Duncan Thomas, Christopher Erickson, Yingnian Wu, Jin-Tan Liu, Jack W. Hou, Fwu-Ranq Chang, seminar participants at the University of California, Los Angeles, participants of the WEAI conference, and anonymous referees for helpful comments. The views represented here are only those of the author. Any errors are the author's responsibility.

суббота, 6 октября 2012 г.

PELOSI BLOCKS FAIR TAX BREAK FOR HEALTH INSURANCE.(Editorial)(Editorial) - Daily News (Los Angeles, CA)

Byline: Robert de Posada

WHAT'S wrong with this picture?

House Minority Leader and U.S. Rep. Nancy Pelosi from California is worth at least $16.3 million personally, makes $125,000 a year and gets tax-free health insurance through the federal government. Yet workers who buy their own health insurance are the only people who don't get a tax break if and when they buy health insurance.

Many of these workers are landscapers, factory workers, manual laborers, delivery workers and early retirees who struggle to make ends meet. Most of them are also the faces of California's 18.3 percent uninsured population, part of the nation's 45 million uninsured, because they work for firms that do not offer health insurance.

The tax code has favored employer-provided health insurance for the last 60 years, and in that time, this important benefit has enabled most Americans to get health insurance from their employers.

But as the cost of health insurance increases, many employers are dropping coverage, leaving millions of Americans to buy their own coverage. This hits the minority community the hardest. Latinos and African-Americans account for more than 50 percent of the uninsured population. One out of every three Latinos is uninsured, as is about one out of every five African-Americans.

Workers who buy their own health insurance are the only people who don't get a tax break if they buy health insurance. This year, employer-provided and self-employed health insurance customers will enjoy a $155 billion tax break. It is fundamentally unfair that workers are discriminated against by the federal tax code in their purchase of health insurance simply because they buy a policy outside of their place of employment.

Rep. Pelosi is willing to take tax-free health insurance while millions of uninsured Latinos and other workers suffer without the tax-free benefit she receives.

But Congress could pass a bill now that would provide relief to workers. This bill, which sponsors call ``Fair Care for the Uninsured,'' would provide money for the purchase of health insurance - $1,000 for an individual, $2,000 for a couple and $3,000 for a family - each year.

Fair Care would correct the discrimination built into the tax code that currently gives unlimited tax benefits to those who get health insurance through their employer, but no tax benefit to the individual purchaser.

These tax credits would be refundable, so that workers who don't owe taxes can receive the credit to put toward health insurance. They could also be advanced to workers up front so that they would have money to buy health insurance.

If Congress passed Fair Care, 18.6 million uninsured people would be eligible for health insurance, according to a study by Fiscal Associates.

Republicans and Democrats in the U.S. Congress think Fair Care is a good idea and support the legislation. The Latino Coalition and other national groups representing Hispanics, small employers and farmers support Fair Care.

пятница, 5 октября 2012 г.

PELOSI BLOCKS FAIR TAX BREAK FOR HEALTH INSURANCE - Daily News (Los Angeles, CA)

WHAT'S wrong with this picture?

House Minority Leader and U.S. Rep. Nancy Pelosi from Californiais worth at least $16.3 million personally, makes $125,000 a yearand gets tax-free health insurance through the federal government.Yet workers who buy their own health insurance are the only peoplewho don't get a tax break if and when they buy health insurance.

Many of these workers are landscapers, factory workers, manuallaborers, delivery workers and early retirees who struggle to makeends meet. Most of them are also the faces of California's 18.3percent uninsured population, part of the nation's 45 millionuninsured, because they work for firms that do not offer healthinsurance.

The tax code has favored employer-provided health insurance forthe last 60 years, and in that time, this important benefit hasenabled most Americans to get health insurance from their employers.

But as the cost of health insurance increases, many employers aredropping coverage, leaving millions of Americans to buy their owncoverage. This hits the minority community the hardest. Latinos andAfrican-Americans account for more than 50 percent of the uninsuredpopulation. One out of every three Latinos is uninsured, as is aboutone out of every five African-Americans.

Workers who buy their own health insurance are the only peoplewho don't get a tax break if they buy health insurance. This year,employer-provided and self-employed health insurance customers willenjoy a $155 billion tax break. It is fundamentally unfair thatworkers are discriminated against by the federal tax code in theirpurchase of health insurance simply because they buy a policyoutside of their place of employment.

Rep. Pelosi is willing to take tax-free health insurance whilemillions of uninsured Latinos and other workers suffer without thetax-free benefit she receives.

But Congress could pass a bill now that would provide relief toworkers. This bill, which sponsors call 'Fair Care for theUninsured,' would provide money for the purchase of health insurance- $1,000 for an individual, $2,000 for a couple and $3,000 for afamily - each year.

Fair Care would correct the discrimination built into the taxcode that currently gives unlimited tax benefits to those who gethealth insurance through their employer, but no tax benefit to theindividual purchaser.

These tax credits would be refundable, so that workers who don'towe taxes can receive the credit to put toward health insurance.They could also be advanced to workers up front so that they wouldhave money to buy health insurance.

If Congress passed Fair Care, 18.6 million uninsured people wouldbe eligible for health insurance, according to a study by FiscalAssociates.

Republicans and Democrats in the U.S. Congress think Fair Care isa good idea and support the legislation. The Latino Coalition andother national groups representing Hispanics, small employers andfarmers support Fair Care.

четверг, 4 октября 2012 г.

STATE'S GROUP HEALTH INSURANCE SHOULD BE AVAILABLE TO ALL.(EDITORIAL)(GUEST COLUMN)(Column) - The Capital Times

Byline: Christopher G. Wren

As a state employee, I appreciate the excellent health insurance benefits offered by my employer. They served as a significant incentive to enter state service, and they remain a significant incentive for continuing in state service.

At the same time, I understand the frustration of my fellow citizens and taxpayers, who often resent state employees for their access to this benefit. I remember the irritation I felt when, during a hiatus from state employment, my wife and I had difficulty finding good and affordable health insurance coverage.

But unlike many others in similar situations, I did not begrudge state employees their good fortune. Rather, I wondered why the state did not routinely make its employee group health insurance plans available to everyone in Wisconsin - to the people who ultimately paid the bill.

I still wonder that.

The time has come for the state to make its employee group health insurance plans available to all Wisconsin residents and businesses. Various proposals have surfaced recently to broaden the availability by allowing businesses to form insurance-buying pools or consortiums, allowing specific groups (such as farmers) to buy into the group health insurance plans. These proposals, however, seem inevitably to add unnecessary layers of negotiation and red tape.

Wisconsin already has an existing insurance pool. Instead of restricting access to state employees only, the plans should be opened to anyone in Wisconsin. The state could specify that as a condition of participating as an insurer for state employees, the insurer would have to make the plan available - same policy terms, same premiums - to any employer or individual in Wisconsin. Employers and individuals would purchase their coverage directly from the insurer.

This arrangement would have several beneficial effects:

With the state acting as the negotiator and standard-setter, the public would see its interests aligned with, not in conflict with, the state's. The lower the premiums negotiated by the state, the lower the premiums the public would pay for the same coverage.

Instead of complaining about the generosity of state employees' health insurance benefits while private-sector employers steadily reduce their employees' coverage, private-sector employees might begin asking why their employers aren't buying into the state's plans or offering comparable coverage. Making the state's group health insurance plans universally available might help stanch the race to the bottom in health insurance coverage.

Extending the state's group health insurance plans to the general public should foster competition among existing private sector plans, presumably yielding better benefit packages, or premiums that better reflect the cost/benefit characteristics of those plans.

Extending the state's group health insurance plans to the general public would make coverage universally available without creating new public or private sector bureaucracies. The Department of Employee Trust Funds would continue its role as negotiator.

Extending the state's employee group health insurance program to the general public makes sense as a matter of sound policy. The state has an opportunity to do something it already does well - negotiate high-quality, cost-effective health insurance coverage - and make the benefits of those efforts available to everyone at little or no additional cost to taxpayers.

Moreover, with competition widely regarded as the best way to get the best price, putting state plans and private sector plans in direct competition ought to reduce health insurance premiums overall, or at least significantly reduce the rate of increase.

Ideally, every employer would emulate the state and offer all employees high-quality, employer-paid health insurance. Wisconsin, however, lives far from this ideal, with pressures growing to retreat further from it. If the state really wants to make employer-paid health insurance a priority, however, it could take a second step in addition to expanding access: create a 'super deduction' for employer-paid health insurance.

A super deduction - allowing an employer to value the insurance premiums at, say, 105 percent or 110 percent of cost when calculating business expenses for tax purposes - would send the message that the state considers health insurance a preferred fringe benefit.

среда, 3 октября 2012 г.

Wis. Governor Signs Health Insurance Bill - AP Online

ROBERT IMRIE, Associated Press Writer
AP Online
12-12-2003
Dateline: WAUSAU, Wis.
Thousands of farm families, small business owners and self-employed workers in Wisconsin are now eligible for a new program to help them get affordable health insurance.

Gov. Jim Doyle signed legislation into law Thursday that creates five regional health insurance purchasing cooperatives with the power to pool individuals to negotiate directly with health insurance providers and collectively bargain for cheaper coverage.

Wisconsin farmers face a health care crisis, already paying three times as much for their health insurance as salaried employees working for a company, Doyle said.

'I don't think anyone believes this will be the absolutely perfect answer, but it will provide some help,' Doyle said before signing the legislation.

'We can raise prices and productivity of our farmers, but it won't matter if increased profits just go to cover rising health care premiums or if farms go under because our farmers can't afford health care coverage for their families,' he said.

The governor said some Wisconsin farmers pay $1,900 a month for health insurance premiums that include a $2,500 annual deductible.

'It is no wonder 25 percent of Wisconsin farmers have no health insurance coverage at all,' Doyle said.

About 50 people watched the signing ceremony at FCS Financial Services, a member-owned cooperative that provides loans and other services to agricultural customers and home owners.

The legislation, based on a successful Minnesota program, was approved by both the Senate and Assembly in November.

Bill Oemichen, president and CEO of the Wisconsin Federation of Cooperatives, a primary advocate of the legislation, said each purchasing cooperative must have at least 5,000 members.

It's believed the new alliances can negotiate health insurance policies that lower the premiums on average at least 10 percent and perhaps as much as 35 percent compared with what the individuals and their families now pay, Oemichen said.

The biggest advantage will come in lower annual deductibles on the policies, perhaps to $250 to $500, he said.

The first policies could be in place by next summer, Oemichen said.

Wayne Corey, executive director of Wisconsin Independent Businesses, predicted the change Doyle signed into law would stabilize health insurance costs and revitalize many small businesses, enhance their profitability and make more money available for employee raises and other benefits.

Copyright 2003, AP News All Rights Reserved

вторник, 2 октября 2012 г.

Retirees' health insurance cut off as companies change. - Saint Paul Pioneer Press (St. Paul, MN)

Byline: Gail MarksJarvis

ST. PAUL, Minn. _ Ed Stish is not living the carefree life he envisioned when he retired from a taconite mine in Keewatin, Minn., three years ago. He has no time for lounging in a La-Z-Boy, golfing or fishing for pleasure.

Instead, Stish rises early and sets about growing vegetables, trapping beaver for pelts and harvesting wild rice on a lake near his home in Bovey. His wife, Sue, sells the bounty at farmers' markets four days a week.

They do this to survive. Just a few months after he retired at age 50 from National Steel Corp., his employer of 30 years went bankrupt, taking with it longtime promises to provide a livable pension and cheap health insurance for life.

Even though the U.S. Pension Benefit Guaranty Corp. stepped in to protect workers' pensions, Stish's monthly payment was cut almost in half to $1,350. And the buyer of the mine, U.S. Steel, never made good on the old promise to provide retiree health insurance.

That left Stish in the same predicament as countless retirees caught in an unaffordable health insurance trap they never expected. Company-paid health insurance for retirees is becoming extinct as companies try to slash costs and increase profits.

While federal law requires companies to deliver the pensions they promised workers, no such legal obligation exists for health insurance.

Eleven years ago, 46 percent of large U.S. companies helped retirees with health insurance, but now just 28 percent continue to do so, says researcher Paul Fronstin of the Employee Benefits Research Institute. Among all U.S. companies, 11 percent provide retirees with health insurance.

Fronstin says current workers of any age should not expect the benefit when they retire unless they work in some government jobs or are protected by a union contract guaranteeing coverage. His warning allows people who still have jobs to plan for their future, but retirees don't have the luxury of time or a paycheck.

In the past few years, retirees like Stish were taken by surprise when an employer went broke or was acquired by another company that didn't want to continue their health benefits. Others have lost insurance because former employers wanted to avoid spiraling health insurance costs, or they could bolster corporate profits quickly through an accounting maneuver that can turn disbanded insurance liabilities into instant income.

Last year, 10 percent of companies that gave retirees health benefits eliminated them completely and 71 percent made retirees pay a greater portion of health coverage, according to research by the Kaiser Foundation and Hewitt Associates.

(EDITORS: BEGIN OPTIONAL TRIM)

'There is no way people could have anticipated the rate of inflation in health care, and no way for a person to plan if the trend continues,' says Michael Stein, a Boulder, Colo., financial planner and author of 'The Prosperous Retirement.' 'It's a societal crunch, and society will have to make changes.'

(END OPTIONAL TRIM)

Cutting retiree benefits is considered the path of least resistance _ considerably easier than upsetting existing workers with benefit cuts or disappointing shareholders with lackluster profits. The special accounting attached to cuts in health benefits works almost magically to prop up corporate profits, even if a company has not sold more goods or services.

'Companies attack the segment of their stakeholders that have no defense,' says Jim Norby of the National Retirees Legislative Network.

The network has asked Congress to pass laws that would mandate employers to maintain their commitments to retirees, but Norby says there's not much interest.

Fronstin says policy makers could also address the erosion of retiree health benefits by expanding Medicare or other programs covering such expenses, changing tax treatment for health expenses and educating people that they must save for retirement health insurance.

Meanwhile, as companies slash benefits, retirees are left in a bind. With poor job prospects and insurance costs high for older people, many retirees can't afford thousands of dollars in unexpected expenses.

Typically, when workers consider retirement, they check on their company benefits and add up monthly living expenses ranging from heat to property taxes. If pensions, savings and Social Security look like they will cover all the costs, they may decide it's safe to retire.

But that can be a serious mistake if unanticipated health insurance costs pop up after retirement. Early retirees, those younger than 65, may have to spend $1,000 a month for insurance. People eligible for the federal Medicare program may have to spend about $250 a month on supplemental insurance because Medicare only covers about half of the costs.

An individual who retired in 2003 with employer health benefits will need between $37,000 and $750,000 in savings to pay for his supplement to Medicare, according to the Employee Benefits Research Institute. An individual without any help from an employer will need $47,000 to about $1.5 million.

Stish never considered this before he retired. Throughout his years as a mechanic in the taconite mine, he believed the company would give him cheap lifetime insurance if he just completed 30 years of work.

'Instead, I was just cast in the wind,' he says.

(EDITORS: BEGIN OPTIONAL TRIM)

To keep costs down, Stish insured his wife and himself but not a healthy daughter still living at home.

He figured he couldn't skip insurance because he and his wife have high blood pressure. Plus, he retired at 50 after his doctor warned him: 'You've got to quit, or you are going to die.'

But he can't afford much insurance. His policy will cover an expensive emergency, but each year he must pay the first $5,000 of the couple's expenses for doctors, hospitals and medicine. Besides that, he pays $750 every three months for health insurance.

That takes a big chunk out of his $1,350 monthly pension. Stish worries what will happen if his body no longer allows him to work and health insurance costs keep climbing 15 percent a year.

(END OPTIONAL TRIM)

(EDITORS: BEGIN OPTIONAL TRIM)

That threat also troubles Tom Bedford, a retired IBM engineer in Arden Hills, Minn.

In 1991, Bedford retired at age 61 from IBM specifically because he wanted a benefit that was scheduled to disappear if he waited another year _ the promise of free health insurance for life.

Despite that understanding, Bedford recently started picking up health care costs. At age 74, he must pay $100 a month for health insurance and the first $2,000 in medical expenses each year that he and his wife incur.

He can afford that now, but says 'it would be terrible if the insurance rose to $300 or $400.' Since both his parents and his wife's parents lived to their mid-90s, he knows he could far outlive his ability to work or pay the likely increases in insurance.

'I guess it's just a matter of time before the bomb is going to drop,' Bedford says.

He says he didn't consider this possibility the day he retired because 'IBM had such a good health plan you never had to worry.'

IBM says it still offers a good health plan. 'If you look at our competitors, you'll see that IBM continues to offer some of the most generous retiree medical subsidies in the industry,' says spokeswoman Kendra Collins.

(END OPTIONAL TRIM)

Rodney Peterson also didn't think he'd have a health care worry when he retired 21 years ago from Northwestern Bell in Duluth, Minn. His employer guaranteed coverage for life. But now he's paying about $800 a year, and at 81, he can't work for the extra money.

That's part of his problem. Two years ago, he moved from his home in Duluth to an apartment in Rice Lake, Wis., because he could no longer keep up a house and routine paperwork. He needed to be near a daughter in Wisconsin who could help him.

After his move, Qwest _ which had acquired the former Northwestern Bell _ told him he'd have to pay more for insurance in Wisconsin than he paid in Minnesota. With the extra financial burden, he now wonders how he will afford to fix the brakes on his car.

'I feel like we've been let down,' Peterson says.

Peterson is not the only one feeling that way. Many of Qwest's employees were absorbed from companies Qwest purchased, and their cultures were different, says Dick Caldwell of Arden Hills, Minn., a former speechwriter for Qwest executives.

When people worked for Northwestern Bell, they agreed to work for lower pay than elsewhere, but they did it because the culture promised retirement security _ including lifetime health insurance, says Caldwell.

'They should act honorably and continue paying, rather than letting a threat hang over retirees,' he says of Qwest.

He adds that the extra health costs retirees are now bearing is a slap in the face to those who rallied to Qwest's defense about a year ago.

Qwest wanted to offer long-distance phone service to customers, and the company had to get approval from state regulators. Retirees were called upon to urge regulators to help. They made the plea for Qwest so the company could keep paying pensions and health benefits, Caldwell says.

Just a short time afterward, retirees received what Tom Lee of Hopkins, Minn., calls 'our horrifying Halloween letter.' Mailed in October, the letter from Qwest told some retirees that they would have to start paying 20 percent of their health insurance costs.

Qwest declined an interview for this story, but in a written statement said, 'In an age of ever-increasing benefit costs and an extremely competitive marketplace environment, it has become necessary for Qwest _ like other major U.S. companies including AT&T, BellSouth and SBC _ to modify its benefit plans for retired employees.''

Under an accounting rule, companies are required to book their expenses for future retiree benefits years before the employees leave the company. Then, if the benefits are changed and will cost a company less in the future than earlier anticipated, the company can log the savings as income. The procedure is not one companies publicize, and IBM declined to discuss it.

Most companies are free to cut benefits at will as long as their documents say they might do it, says Minneapolis attorney John Nichols.

But most people planning for retirement don't hunt through the legalese and consequently are taken by surprise.

'I was dumb enough that I didn't read everything,' Lee says. Instead, on the day he retired at age 58, 'I jumped up in the air and clicked my heels.'

___

(c) 2004, Saint Paul Pioneer Press (St. Paul, Minn.).

Visit the World Wide Web site of the Pioneer Press at http://www.twincities.com/mld/pioneerpress/

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PHOTO (from KRT Photo Service, 202-383-6099): PFP-RETIREMENT

понедельник, 1 октября 2012 г.

The influences of Taiwan's National Health Insurance on women's choice of prenatal care facility: Investigation of differences between rural and non-rural areas.(Research article)(Survey) - BMC Health Services Research

Authors: Likwang Chen (corresponding author) [1,2]; Chi-Liang Chen [3,4]; Wei-Chih Yang [1]

Background

Although there is some dispute over how prenatal care can improve child health, its potential in this regard is well recognized [1, 2, 3]. It is thought to benefit child health and reduce maternal mortality, and it is thought to be a good vehicle for the delivery of health care, health education, and psychosocial services to women [4, 5]. Ensuring access to adequate prenatal care has been an important task for both developed and developing countries; thus, barriers to the utilization of prenatal care services have attracted much attention from health policy researchers.

Level of utilization of prenatal care has been associated with age, marital status, educational level, occupation, income, higher parity, difficulties in dealing with health service organizations, and health insurance status [6, 7, 8, 9, 10]. It has also been associated with conditions during pregnancy, including gaining excess weight during pregnancy, having a baby for the first time, carrying twins or triplets, being at a higher obstetric risk, being attended to by a doctor rather than other types of caregivers, and switching to another health care facility during pregnancy [6, 10]. Among various factors associated with prenatal care utilization, the provision of public health insurance to cover prenatal care has been a policy instrument of interest to many advanced or newly industrialized countries.

Literature specifically discussing the effect of public health insurance on prenatal care utilization is quite limited. Some studies have found that it has a positive effect. Griffin et al. (1999), comparing enrollees of a Medicaid managed care program in Rhode Island and their counterparts with private insurance, concluded that the implementation of the Medicaid program resulted in significant improvement in adequacy of prenatal care utilization [11]. Chen et al. (2001), using data from two cross-sectional surveys conducted in 1989 and in 1996 to investigate the utilization pattern of prenatal care in Taiwan, found that utilization of expensive prenatal services, such as amniocentesis and German measles testing, was substantially higher in 1996 than in the late 1980s, suggesting that the implementation of the NHI may induce greater demand for expensive prenatal services [12]. In contrast, they also found that from late 1989 to 1996 the proportion of women receiving consultation services remained stable and the proportion of women receiving family planning consultation declined [12].

Results from another study using data from the same Taiwanese cross-sectional surveys showed that Taiwanese women were more likely to receive adequate prenatal care in 1996, one year after the launch of the NHI, than in 1989 [6]. That same study found that before the NHI was inaugurated, female farmers and blue-collar workers used prenatal care services more frequently than women in other occupations, but afterwards female civil servants were the group seeking prenatal care most frequently [6]. It has also been found that Taiwanese women who visited clinics were more likely to receive adequate prenatal care than those visiting hospitals after the NHI started, though this was not found in the late 1980s [6, 10]. However, previous studies have not well investigated the differences in the choice of prenatal care facility and perceived convenience in transportation for acquiring such care between women living in areas with different levels of urbanization in Taiwan.

Since it established its national health insurance program in 1995, Taiwan has stopped using its public health system of community health care centres as the major vehicle of providing free prenatal care, and began to provide it through the NHI system, which allows expectant mothers to seek prenatal care from a variety of healthcare facilities. Before 1995, Taiwan already had three major types of public insurance programs covering about 57% of the population. The Labor Insurance program, launched in 1950, covered employees such as workers of government-run enterprises, private company employees, blue-collar employees and members of professional unions who were over 15 years of age and under 60 years of age. Established in 1958, the Government Employee Insurance (GEI) program, covered officers and full-time employees of government agencies, teaching and administrative staff of government-owned schools and private schools, and retirees from these organizations. In 1988, the Farmer's Insurance program extended coverage to members of farmers' associations and individual farmers who were over 15 years old. The three programs had similar benefits packages, covering outpatient visits, hospitalisation, diagnostic tests and prescription drugs. However, only the GEI program covered dependents, and offered free prenatal care to its enrolees through health care facilities that had contracts with this public health program.

While GEI was the only public health insurance program to provide prenatal care before the launch of the NHI, Taiwan's government had been promoting prenatal care long before the introduction of the NHI system through its public health system of community health care centres. Before 1980, each township had its own health station. Additionally, by recruiting physicians from non-rural areas to support services in rural public health stations, Taiwan's government had strengthened the functions of these public health stations and improved health care resources in remote areas by the mid-1990s. Taiwan's public health stations played an important role in providing health care to people in rural areas. For instance, most Taiwanese people in remote areas thought that the local public health station was the health care facility most close to them [13]. The public health stations also played an important role in disseminating health knowledge in rural areas in the early 1990s. A study in 1991 indicated that the major source of medical information for families in rural areas in Taiwan came from the public health nurses from these stations who made home visits [14]. Through this network of public health stations, Taiwan's government delivered free prenatal care to pregnant women long before the NHI was implemented.

Taiwan's NHI in 1995 substantially extended insurance coverage to all its citizens with an equal and comprehensive benefits package. By the end of 1995, it covered 97% of the population; by 1998, the coverage was over 99%. Since 1995, Taiwan's government has been providing ten free prenatal care visits to each pregnant woman in Taiwan through the NHI delivery system. Almost all hospitals and over 90% of clinics have contracts with the NHI program, and this has substantially expanded women's choice of health care facilities from which they can seek prenatal care. Because of the increase in facilities, it would seem natural that the NHI may substantially reduce the travelling costs for seeking prenatal care. Nevertheless, physician and health facility registration data in the NHI database show that the density of gynaecologists and obstetricians and that of health care facilities providing gynaecologic and the obstetric care were a lot lower in rural areas than non-rural areas, suggesting that the NHI could substantially expand women's prenatal health care choices only in non-rural areas.

There has not been much research on the effect of public health insurance on utilization patterns of prenatal care. What little there is has focused on the number of prenatal care visits made and when they are made. This study compares the differences in how women in rural and non-rural areas chose prenatal care facilities before and after the implementation of the NHI. To do this, we analysed women's responses to a national survey in Taiwan. We focused on their replies to questions about 'the type of major health care facility used,' and 'the convenience of transportation to and from prenatal care facility.' We compared the difference in how they answered these questions for children born before and after the implementation of the NHI.

The first indicator was chosen because it can be related to quality of care. Although many people tend to believe that health care delivered in large hospitals, which are usually better equipped, is better than that provided by clinics, some studies in Taiwan have suggested that one would be more likely to get more adequate prenatal care in a clinic than in a large hospital [6, 10]. The second indicator, 'the convenience of transportation to and from prenatal care facility,' can be related to 'the physical accessibility' to care. This indicator is worthy of investigation, especially for Taiwan, where one of the major goals of its national health insurance program was to improve accessibility to health care.

Results obtained by this investigation may help set future directions of prenatal care provision in Taiwan, and may also be used by countries hoping to improve prenatal care delivery. In particular, Taiwan's case offers a unique opportunity to study the influences of national health insurance on women's choice of prenatal care facility in a situation in which they were once able to receive it free at designated public health facilities but now can seek it in any facility they want to go to as long as it has a contractual agreement with the Bureau of National Health Insurance. Other countries may also face such policy options in the future. Therefore, Taiwan's lesson can be useful to them.

Methods

Study design and data

We wanted to know whether Taiwan's National Health Insurance influenced the aforementioned indicators differently in rural and non-rural areas. We examined what disparities existed in these indicators between women in rural and non-rural areas in various periods before and after the NHI was launched. Specifically, we selected two periods before NHI, which were the early 1990 to 1992 and 1993 to the early 1995, and two periods after NHI, which were 1996 to 1997, and 1998 to 1999.

This study used second-hand data. The data were collected retrospectively from a national face-to-face interview survey conducted by Taiwan's National Health Research Institutes in the latter half of 2000. This national survey, which was for investigating child health and related health care utilization, collected data for two national representative samples - one for children born between March 1 of 1995 and February 28 of 1996 (1,853 children), and the other for children born between March 1 of 1996 and February 28 of 1999 (2,207 children). The survey was administered to the caregivers of these children. The respondents were also asked to report information for these children's siblings born on or after March 1 of 1990. Therefore, the database of this survey included records for children born between 1990 and 2000. The response rate was 76%, with over 98% of the respondents being the children's mothers. In total, the survey collected data for 7,817 children in 3,934 families.

For each child, the survey data include the child's and the mother's demographic background, the socioeconomic conditions of the family, the child's location of residence, and childcare and health care utilization for the child. Regarding the choice of prenatal care facility, the mother was asked to reply the following question: 'What was the name of your major health care facility for acquiring prenatal care during this pregnancy, and in which township was this facility located?' Based on information collected by this question, the interviewer subsequently recorded the type of the health care facility referring to a corresponding database constructed by Taiwan's Department of Health. The mother was further asked to evaluate her perceived convenience of transportation to and from this health care facility, by the following question: 'Was it convenient for you to go to this prenatal care facility?' The corresponding responses were 'very inconvenient,' 'somewhat inconvenient,' 'moderate,' 'convenient,' and 'very convenient.'

We extracted data from this database for our study based on the following criteria. First, we excluded records reported by caregivers other than the mothers. Second, we excluded records for children born between March 1 of 1995 and December 31 of 1995, because the mothers would be pregnant both before and after the NHI was implemented. Third, we also excluded children born in 2000, a special year in Taiwan. It was the start of the new millennium, and also the year of dragon, the preferred year for having babies for Taiwanese, especially male babies. Because this year was not a typical year in Taiwan in terms of the level of fertility as well as the obstetrical care market for years after the mid-1990s, but there were not enough children born in 2000 to form a sub-sample, we excluded cases for 2000. Fourth, we excluded children whose main caregivers in infancy were not the mothers, since we had to use information on the district where a child lived in infancy to construct a proxy variable reflecting the mother's living place during pregnancy. Fifth, we excluded children whose mothers were covered by the GEI during pregnancy, since women with the GEI were a special group with public insurance covering prenatal care in the pre-NHI period.

We were left with 4,820 children after these selection processes. Within these cases, 1,575 were children from mothers who contributed one record each to these 4,820 cases, and the other 3,245 cases were children from mothers who contributed at least two records each to these 4,820 cases. This paper reports results based on data for the 1,575 children, out of a concern regarding correlation among multiple cases from a same woman. While our analytical sample did not end up being a nationally representative sample for children born in these years, it should still be appropriate for this present study, as the focus of this study is based on multivariate statistical analysis, and a rich set of explanatory variables were included in its estimation.

Unfortunately, we did not have a sufficiently large sample size to compare the experiences of prenatal care utilization for a specific cohort before and after the implementation of the NHI. We could only find 168 women who gave a birth between March 1 of 1990 and February 28 of 1995 and another in the period between 1998 and 1999. This prohibited us from comparing a cohort of women's behaviours before the NHI and in the late 1990s.

Sample characteristics

The characteristics for the 1,575 cases are presented in Table 1. As shown in Table 1, in our sample, women who delivered children during the pre-NHI period tended to deliver their first children, and also reported a younger age at delivery. This is related to the data collection process for the NHRI survey, from which we obtained our second-hand research data. To be included in the original sample for this survey, a child born in the pre-NHI period must have had at least one younger sibling born in the post-NHI period. Therefore, the sampled children born in the pre-NHI period were more likely to have a lower birth order than those born after the NHI was implemented, and women in the sample also tended to report a younger age at delivery for children born before the launch of NHI. In our analytical sample, each child born in the pre-NHI period had a younger sibling who was excluded in our sample selection process. Most of such siblings were born between March 1, 1995 and December 31, 1995, and this is related to the reasons why the proportion of males was higher and more children were born in rural areas in the cohort of children born in 1993-1995. Rural women tend to have a shorter space between having their first two births, and appear to have more baby boys. That there were more boys in the sample in years after the mid-1990s is consistent with the facts that the traditional Taiwanese culture has a strong son preference, and that high sex ratios at birth have been observed. There has been some argument over artificial selection of the gender of offspring by medical technology since the 1990s [15, 16].

Table 1 caption: Sample characteristics [table omitted]

For each cohort of children, almost all of their mothers were married in 2000. The proportion of aboriginal or foreign-born mothers was higher for children born after 1995. The proportion of mothers who immigrated to Taiwan from Mainland China was also higher for children born after 1995. This is consistent with the fact that Taiwan has more and more children who have mothers immigrating to Taiwan from Mainland China or some countries in south-eastern Asia. Women who delivered children after 1995 tended to have more education, and those delivering children in the late 1990s tended to have lower family income. This should be related to the fact that the mothers of children born after 1995 tended to be younger than the women delivering children during the pre-NHI period.

Table 2 compares the choices of prenatal care facility of women living in rural areas and those in non-rural areas. These descriptive statistics suggest that women living in rural areas were less likely to choose medical centres or regional hospitals (large hospitals) than women in non-rural areas in the pre-NHI period. However, women in rural areas were more likely to choose large hospitals as their major health facility in the late 1990s than earlier in the 1990s, while women in non-rural areas did not have such a trend. A smaller proportion of women in rural areas perceived very convenient transportation to and from prenatal care facility in the late 1990s than earlier. In contrast, more women in non-rural areas felt that their transportation for acquiring prenatal care was very convenient in years after 1992 than in 1990-1992.

Table 2 caption: The type of major health facility used for prenatal care [table omitted]

Empirical specification and statistical models

This study defined three types of health care facilities, and four levels of the convenience of transportation. (The detailed definitions of the outcome variables can be found in Table 3.) The indicator regarding 'the type of major health care facility used' is a 3-point nominal variable, and we adopted the multinomial model to investigate factors related to this indicator [17]. We used a 4-point ordinal variable as the indicator for 'the convenience of transportation' and applied the ordered probit model in our multivariate analysis [17]. The Huber/White/sandwich estimator was employed to obtain robust variance estimates. This method is a commonly used estimator of standard errors, and it is robust without assuming that the standard errors are independent from the explanatory variables and are identically distributed [18]. We used the Stata Statistical Software for our multivariate analysis.

Table 3 caption: Definitions of the outcome variables and major explanatory variables in multivariate analysis [table omitted]

We specified three major types of explanatory variables - the time period a child was born in, the level of urbanization in the area where a woman resided while being pregnant, and the interaction of these two factors. In addition to these major explanatory variables, we also controlled for a detailed set of other factors: some related to children, and some related to the mother and the family. The child characteristics included gender and birth parity. The maternal characteristics included her age when she bore the child, her abnormal obstetric health problems during this pregnancy, the year when she was born, and her ethnic background. Maternal characteristics also included the number of children she had, and her marital status and educational attainment at the time of the interview. Regarding the family, we included 'the average monthly family income in the year in which a mother was interviewed' as an explanatory variable. Due to data availability, the explanatory variables included a mother's marital status and educational attainment at the time of interview, and the average monthly family income of the year in which the interview was administered, instead of those variables at the time of pregnancy.

The empirical specification used to compare the influences of the NHI on the choice of prenatal care facility between women living in rural areas and those in non-rural areas is as follows:

[math omitted]

Y is one of the two indicators mentioned previously. Xc denotes explanatory variables other than the major ones. 1993_1995, 1996_1997, and 1998_1999 were used to capture the time trend, with the base period being from March 1, 1990 to December 31, 1992. The three interaction terms were for investigating the differences in the time trend between rural women and their counterparts in non-rural areas (The detailed definitions of the major explanatory variables can be found in Table 3).

Estimation of changes in the relative probability of choosing hospitals and in the probability of perceiving very convenient transportation from 1990-1992 to later years in the 1990s

Using coefficients and the corresponding covariance matrices estimated by the multinomial logit model, we calculated the probability of choosing a specific type of setting as the type of major health facility used for prenatal care [17, 19, 20]. We further estimated the relative probability of choosing hospitals to choosing non-hospital settings for each time period, and the changes in the relative probability from 1990-1992 to the three later periods in the 1990s [19, 20].

The relative probability of choosing large hospitals to choosing non-hospital settings was measured as the ratio of the probability of choosing large hospitals to the probability of choosing non-hospital settings. It is exp(

X 'b1 ), where X is the set of all explanatory variables and b1 is the set of coefficients corresponding to the category of visiting medical centres and regional hospitals. Similarly, the relative probability of choosing small hospitals to choosing non-hospital settings is exp(X 'b2 ), where b2 is the set of coefficients corresponding to local hospitals. The change in the relative probability from 1990-1992 to a specific later period was measured as the ratio of the relative probability for that period to the relative probability for 1990-1992. (The formulas for calculating the 95% confidence interval estimates of these changes are presented in the appendix.)

In the ordered probit model, the values of thresholds (or called 'cut points'), together with the values of coefficients, determine the probabilities of falling in various categories of the dependent variable. We used information with respect to coefficients, thresholds and their corresponding covariance matrices to calculate the probability of perceiving very convenient transportation, and estimated the changes in the probability from 1990-1992 to the three later periods in the 1990s [17, 20]. The change from 1990-1992 to a specific later period was measured as the probability for that period minus the probability for 1990-1992. (The formulas for calculating the 95% confidence interval estimates of these changes are in the appendix.)

We needed to select a representative case for calculating the probabilities of choosing a specific type of setting as the type of major health facility used for prenatal care and of perceiving very convenient transportation. Referring to the sample characteristics, we chose the following characteristics for such estimation: the child was male and the first child; the mother bore the child before thirty years old, had no abnormal condition during this pregnancy, and was born before 1970, and her ethnicity was Fu-Chien; she had two children, was married, and had senior high school education and an average monthly family income less than 50,000 Taiwanese dollars when she was interviewed in 2000. Based on these characteristics, we calculated the two kinds of aforementioned probabilities for each time period, and for rural and non-rural women, separately.

Results

Changes in the relative probability of choosing large hospitals from 1990-1992 to later years in the 1990s

The probability of choosing large hospitals for women in rural areas was significantly higher between 1998 and 1999 than between 1990 and 1992 (Table 4). According to the point estimates, for women in rural areas, the relative probability of choosing large hospitals to choosing non-hospital settings in 1998-1999 was 6.54 times of that in 1990-1992. In contrast, their relative probability of choosing local hospitals in 1998-1999 was only 1.92 times of what it was between 1990 and 1992, and it was not statistically significant.

Table 4 caption: The relative probability of choosing hospitals to choosing non-hospital settings as the type of major health facility used for prenatal care [table omitted]

Changes in the probability of perceiving transportation to be very convenient from 1990-1992 to later years in the 1990s

Regarding the changes in the probability that women would perceive transportation to be very convenient from the period between 1990 and 1992 to the three later periods in the 1990s, only the change corresponding to 1998-1999 for women in non-rural areas was statistically significant (Table 5). These women were more likely to feel very convenient transportation during the period between 1998 and 1999 than during the period between 1990 and 1992. For a non-rural woman with representative characteristics mentioned previously, she had a 26.8% probability of perceiving that transportation for obtaining prenatal care was very convenient in non-rural areas between 1990 and 1992, and was 8.4% more likely to find it very convenient there between 1998 and 1999. In contrast, women in rural areas did not have this trend, and might be less likely to perceive very convenient transportation between 1998 and 1999 than between 1990 and 1992. According to our point estimates, for a rural woman with aforementioned characteristics, her probability of perceiving transportation as being very convenient was 34.8% between 1990 and 1992, and she was 14.5% less likely to find it very convenient there between 1998 and 1999. This estimate, however, was marginally insignificant, with its upper bound of the 95% confidence interval slightly larger than 0. If our sample size could be a little larger, we would expect such a difference to be statistically significant.

Table 5 caption: The probability of perceiving very convenient transportation to and from prenatal care facilities [table omitted]

Other factors related to choice of prenatal care facility

Results from our multivariate analysis revealed there were some other factors related to the choice of prenatal care facility (detailed results available upon request). Women with abnormal health conditions were more likely to seek prenatal health care in large hospitals. Women who bore their babies between age 30 and 34, women who were born before 1970, women with higher education and higher family income were also more likely to seek prenatal care in large hospitals.

Discussion

In this study of Taiwanese women's choice of prenatal care facility from the early 1990s to the late 1990s, we found that women in rural areas were more likely to go to large hospitals to obtain prenatal care in the late 1990s than in the early 1990s. Moreover, women in rural areas were less likely to perceive that transportation had improved for acquiring prenatal care in the late 1990s than their counterparts in non-rural areas. Our findings suggest that more effort is necessary to help reduce the disparities between women in rural areas and those in non-rural areas.

Since the launch of NHI, recruiting physicians for certain specialties has been challenging for hospitals and medical professional groups, and recruiting for gynaecologic and obstetric departments have had particularly noticeable difficulties. The NHI payment scheme has generally been regarded as a factor associated with such a problem, as gynaecologists and obstetricians complained that the payment level for them is not as good as those for many other specialists [21]. Another factor making gynaecology and obstetrics become unfavourable specialties is that gynaecologists and obstetricians are more likely to be involved in medical disputes than physicians of many other specialties [21]. In the 1990s, there were quite a few cases in which some pregnant women's or lying-in women's family members went to protest or file lawsuits against their gynaecologists and obstetricians because they were not satisfied with the treatments their doctors provided.

Moreover, business has been dropping for gynaecologists and obstetricians as Taiwan's fertility rate has been dropping since the late 1990s. The total fertility rate in 1997 was 1.77, which was about the same level in the early 1990s, but it dropped to 1.56 in 1999, and further to 1.12 in 2005 [22]. The decrease in fertility is significant in both rural and non-rural areas [22]. Business is also uneven, depending on the years considered favourable for giving birth. For example, fertility was much lower in 1998 because it was a Tiger Year, traditionally considered to be unfavourable in Taiwan, and high in 2000, which is a Dragon Year and very favourable. The quickly decreasing and uneven fertility rate also makes gynaecology and obstetrics less attractive specialties.

Regarding the type of health care facility for obtaining prenatal care, we found that women in rural areas were more likely to seek prenatal care in large hospitals in the late 1990s than earlier in the 1990s, a finding that is consistent with results from one study which showed that a large hospital in Taiwan symbolized good quality care in the 1990s [23]. Taiwan's NHI payment scheme has made hospital owners to prefer to use high technology to have their hospitals re-accredited as large hospitals, so that they have had a tendency to compete on a non-price basis [24]. Since the implementation of the NHI, a substantial proportion of small hospitals have gradually exited the hospital market, and a major competition strategy adopted by hospitals is to expand their sizes and increase the use of high technology devices to signal their quality levels [24]. As health care consumers in Taiwan have no reliable information sources regarding the quality levels of health care facilities, some of them may just use the size of a health facility to judge its quality. Particularly, since it is harder for rural residents to collect information on the quality of health care facilities outside their communities, they might be more likely to judge the health care quality of a facility based on its size.

If women in rural areas believe that a larger size of hospital reflects better quality of health care, and choose to leave their living districts to seek prenatal care, it appears reasonable that they would prefer large hospitals rather than smaller health care facilities. The behaviour of enduring inconvenient transportation was also consistent with the finding shown in one research which reported that time cost was a factor with a low elasticity for utilizing ambulatory care in Taiwan in the 1990s [25]. Moreover, the decreases in the numbers of local hospitals and non-hospital health care facilities in rural areas, small cities and towns might also push women in rural areas to be more likely to seek prenatal care in large hospitals. As to why such an effect started to emerge in the late 1990s rather than right after the launch of the NHI, it might be because the influences of the NHI payment scheme and of the dropping fertility on the structure and development of Taiwan's prenatal care market was not so strong in the first a few years of this insurance program, and became stronger a couple of years after the start of the NHI. With respect to such issues, there has been no study reported in the literature, and such research is worthy of more attention.

Given that women in rural areas were more likely to leave their living districts to acquire prenatal care in large hospitals in the late 1990s, it makes sense that women in rural areas were less likely to perceive improved convenience in transportation in the late 1990s than women in non-rural areas. Women in non-rural areas appeared to feel more convenient transportation in the 1990s than earlier in the 1990s. Since the number of health care facilities providing gynaecologic and obstetric care did not increase in the late 1990s, a possible reason for this improvement might be because of the improvements in public transportation systems in non-rural areas. For instance, Taiwan has started developing 'mass rapid transit systems' in large cities since the early 1990s. Therefore, it is reasonable that there would be an increased difference in estimation of convenience of transportation to and from prenatal care facility between women in rural areas and their counterparts living in non-rural areas in the late 1990s.

One more point deserving further exploration is whether choosing large hospitals for prenatal care was worth it for women. While our data could not show whether prenatal care services in large hospitals were worse than those offered in other settings, such as clinics and public health stations, some previous studies indicated that women seeking prenatal care in clinics were more likely to obtain adequate prenatal care than those seeking such care in hospitals one year after the NHI program started [6, 10]. Our study did not focus on 'measures for adequacy of prenatal care.' It would require further study to investigate the consequences of rural women's actions of leaving their local communities and going to large hospitals for prenatal care in the post-NHI period in terms of the quality of prenatal care received and the corresponding birth outcomes.

This study, which examined disparities between rural and non-rural areas, offers new information regarding the type of major health care facility used, and women's perception of the convenience of transportation for obtaining prenatal care. It discusses in detail the links of the trend in Taiwanese women's choice of prenatal care facility with developments in Taiwan's NHI, health care market, fertility and public transportation. It thus adds important information to the field of prenatal care. Our findings should be of particular use to Taiwan and countries with similar concerns and conditions for their future reforms in the delivery of prenatal care.

How to improve access to prenatal care in rural areas should be an important challenge. The literature has indicated that women who seek obstetrical care outside their local communities are more likely to have complicated deliveries, larger chances of prematurity, and more need for neonatal care for their children [26]. Previous research has also suggested that fewer pregnancy-related health services resource in rural areas adversely affects utilization of such health care in these areas [27]. Rural women are unavoidably facing higher risks for birth delivery, since they usually have to leave their community to deliver their children. Such a circumstance makes 'use of good quality prenatal care' even more essential for women in rural areas. While it does not seem efficient to increase the number of health care facilities offering prenatal care in rural areas, some other strategies should be seriously considered and tested. For instance, it should be helpful to improve the quality of prenatal care offered in rural public health stations by recruiting good gynaecologists and obstetricians to provide services in the health stations on a periodic and regular basis, and to construct a good referral system for prenatal care using public health stations as the base. It should also be helpful to provide rural women with more convenient transportation services to and from prenatal health care facilities. Furthermore, it should be helpful to disseminate health information on the importance of and the criteria for adequate prenatal care to help pregnant women make better choices regarding prenatal care.

This study focused on reporting results based on data for 1,575 children in the 4,820 available cases, as previously mentioned. The reason is that we concerned correlation among multiple cases from a same woman, since the two statistical models we used, the multinomial logit model and the ordered probit model, cannot not handle this kind of correlation problem. However, for the purpose of sensitivity analysis, we have also done analysis based on the 4,820 cases (results not shown). While more coefficients were statistically significant in results from analysing the 4,820 cases, these results do not conflict with conclusions we made with regard to comparison between rural and non-rural areas according to our results from analysing the 1,575 cases.

There are two main limitations for this study. The first pertains to recall bias, a problem inherent in most retrospective studies that make of surveys. Nonetheless, we believe that such recall bias in our study should not be serious. It has been shown that maternal recall of births five to seven years earlier is highly accurate, and maternal reports of prenatal events more than a decade after the birth are still reasonably accurate, especially events they directly participated in or information they have been told [28, 29, 30, 31]. The literature has also indicated that health care users can reliably report factual information such as the travelling time for obtaining ambulatory care [32]. Since most Taiwanese women only have one or two children and the recall period for this study is no more than ten years, it should not be hard for them to remember which health care facilities they used for prenatal care, and how they felt about the transportation to and from the facilities.

The second limitation is that our analysis only compared different cohorts of women giving births in the 1990s without controlling for some unobserved characteristics, such as attitudes and beliefs with regard to childbearing, prenatal care, and health care quality differences among different types of facilities. We were not able to further discuss how such characteristics that might vary among different cohorts of women might interact with the NHI influences on the prenatal care market, and subsequently result in changes in women's choice of prenatal care facilities. If we could also compare the experiences of prenatal care utilization for a specific cohort before and after the implementation of the NHI, we would be able to furnish more knowledge in this area.

Conclusion

In conclusion, we found that the women in rural areas were more likely to seek prenatal care in large hospitals, but were not more likely to perceive very convenient transportation to and from prenatal care facilities in the late 1990s than in the early 1990s. In contrast, women in non-rural areas did not have a stronger tendency to seek prenatal care in large hospitals in the late 1990s than in earlier periods. In addition, they did perceive an improvement in transportation for acquiring prenatal care in the late 1990s. More efforts should be undertaken to reduce these disparities and improve access to prenatal care of good quality in rural areas.

Competing interests

The author(s) declare that they have no competing interests.

Authors' contributions

Likwang Chen designed the study, led the data collection and statistical analysis, and drafted the manuscript. Chi-Liang Chen participated in designing the framework of statistical analysis and preparing the manuscript. Wei-Chih Yang participated in analyzing data analysis and preparing the manuscript. All authors read and approved the final manuscript.

Appendix

Formulas for calculating the 95% confidence interval estimates of changes corresponding to the three later periods in the 1990s

Changes in the Relative Probability of Choosing Hospitals from 1990-1992 to Later Years in the 1990s

The 95% confidence interval estimates of changes corresponding to the three later periods in the 1990s for non-rural areas were calculated as follows:

[math omitted]

For rural areas, the 95% confidence interval estimates for the three periods were respectively calculated as follows:

[math omitted]

Changes in the Probability of Perceiving Very Convenient Transportation from 1990-1992 to Later Years in the 1990s

In our model, there were three thresholds:

K1 , K2 , K3 . The 95% confidence interval estimates of changes in the probability of perceiving very convenient transportation corresponding to the three later periods for non-rural areas were respectively calculated as follows:

[math omitted]

[phi] is the density function of the standard normal distribution.

For rural areas, the three interval estimates were:

[math omitted]

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Author Affiliation:

[1] Centre for Health Policy Research and Development, National Health Research Institutes, No.35 Keyan Road, Zhunan Town, Miaoli County 350, Taiwan

[2] Institute of Public Health & Department of Social Medicine, School of Medicine, National Yang-Ming University, Taipei City 112, Taiwan

[3] The Department of Accounting, The College of Business, Chung Yuan Christian University, Chung-Li City, Taoyuan County 320, Taiwan

[4] Department of Accounting, College of Management, National Taiwan University, Taipei City 106, Taiwan

Author Email: Likwang Chen - likwang@nhri.org.tw; Chi-Liang Chen - d90722002@ntu.edu.tw; Wei-Chih Yang - weichih@nhri.org.tw

Article history:

Received Date: 3/6/2007

Accepted Date: 3/29/2008

Published Date: 3/29/2008

Article notes:

� 2008 Chen et al; licensee BioMed Central Ltd.