The National Institute Of Aging Health And Social Care Essay

Introduction

There have been concerns about the rise in health care spending in the United States. The U.S. health care spending was approximately $2.6 trillion in 2010, accounting for 17.9% of the nation’s Gross Domestic Product (GDP) (Centers for Medicare & Medicaid Services, 2012) (Table 1). This represents $8,402 spending per capita health care in 2010. According to data provided by the Centers for Medicare and Medicaid Services (CMS), the U.S health care expenditures grew at 3.8% in 2009, which is the lowest growth rate since 1960 (Centers for Medicare & Medicaid Services, 2012). However, the health expenditures continue to increase at a rate that exceeds economic growth in the majority of the countries in the Organization for Economic Co-operation and Development (OECD). According to OECD Health Data 2012, the United States spending on health is more than double of the OECD average in 2010, which was 17.6% GDP to 9.5% GDP (OECD, 2012). Most of the study indicates the major components that drive the health care costs are advancement of technologies and prescription drugs. The rise of aging population and chronic diseases has contributed to the rising expenditures as well.

The Centers for Disease Control and Prevention shows that more than 75% of $2.6 trillion health care costs are associated with chronic conditions (Centers for Disease Control and Prevention, 2012). Today, people in older age group with chronic illness are health care’s largest and fastest growing service group. The Centers for Disease Control and Prevention reports almost 1 out of 2 adults (133 million Americans) experienced chronic illness in 2005 (Centers for Disease Control and Prevention, 2012a). This number has increased to 145 million Americans in 2009, and this number is estimated to exceed 171 million by 2030 (Anderson, 2010).

The purpose of this research paper is to examine factors responsible for the rise in health care expenditures in the United States. In order to effectively reduce the spending growth, understanding the underlying factors in health care expenditures is essential. This paper examines the impact of the aging population and chronic diseases on health care spending, and a series method to help lower and slow down the rise of health care expenditures. Current views and opinions of individual towards health care cost in the United States will be investigated as there have been various research studies conducted that explore the benefits of universal health care in most OECD countries.

Literature review

Health care spending is driven by many forces including the aging of the population, chronic diseases, health care resources and utilization, and advances in medical technology. Approximately 76.4 million babies were born in the United States from 1946 to 1964, commonly known as the baby boomers (U.S. Census Bureau, 2012) Four historical aspects of current aging trends in the United States are: the accelerated growth of the oldest old population, the life expectancy at advanced ages, the predominance of females at advanced ages, and the reduction in the age-specific mortality rates of certain major chronic degenerative diseases (Manton & Soldo, 1985). Baby boomers began to reach age 50 to 65 in the 21st century. The accelerated growth of the population, ages 65 and older, created a surge in concerns for adequate retirement and long-term care services (Manton & Soldo, 1985). As the baby boomers become the older elderly, majority of them will experience chronic illness, which is the major cause of death and disability (Rice & Feldman, 1983). Rice and Feldman (1983) indicated that the people suffering from conditions that are managed or controlled, rather than cured, have long durations, thus long term care is needed.

Hodes (2006) director of the National Institute of Aging noted:

"Never before have so many people lived for so long. Life expectancy has nearly doubled over the last century, and today there are 35 million Americans age 65 and older. The aging of the population – in past decades and in the foreseeable future – presents both a challenge and an opportunity."

According to the projections produced by the U.S. Bureau of Census (2008), there are 40 million people over age 65, 12.96% of the total population in 2010 (Table 2). In 2050, the elderly population is projected to double to 88.5 million people, comprising 20.16% of the total population (U.S. Census Bureau, 2008). This growth rate of the elderly can be explained by the continuing decline in mortality at advanced ages of the Baby Boomers. Census data indicates that life expectancy in the United States was approximately 77 years in 2000, up from about 47 years in 1900 (U.S. Census Bureau, 2008a) (Table 3). This increase can be largely attributed to improvements in medical technology which provides more ways to save lives. Over the past several years, life expectancy has increased for both males and females. As projected by the U.S. Bureau of Census (2008a), the average life expectancy age will gradually increase from 78.3 years in 2010 to 83.1 years in 2050. Projections also state that women have a longer life expectancy at 85.3 years than men at 80.9 in 2010. However, longer life expectancy of women brings additional issues. For instance, in most families, men are the primary income providers. Thus, widowhood may lead to poverty in later life for women.

By reducing the death rate among children, mainly through the control of infectious diseases, the average life expectancy rate has improved. Continued improvements have been realized in the mortality rate of chronic diseases through the spread of medical advances. According to Rice (1991), the decline in the mortality rate from 1950 to 1987 was mainly due to reductions in heart disease, a decreased of 45% death rate.

While much of the decline in mortality rate among the elderly can be attributed to treatment and prevention innovations, the future effect on disability prevalence among the elderly is unclear and has added to the difficulty in measuring disability (Manton, 1989). Life expectancy gains were due to improved treatments, thus extending age at death (Feldman, 1983). Feldman (1983) argued that people adjust for the expected length of life spent after age 65, but they ignore the problems associated with the condition of living, which is spent in a more or less healthy way. In other words, the fundamental processes of chronic disease were not being altered, people tend to live longer yet spend a greater proportion of their life span in a disabled state. Again, if medical interventions would extend survival, morbidity prevalence could be stable or decrease, even when chronic disability prevalence declines (Manton, Stallard, & Corder, 1995). Manton (1989) suggested that the age relation of mortality and disability depended upon the characteristics of a person’s health history. Healthier lifestyles such as proper nutrition and more widespread physical activities, and preventing disability (such as adjusting the risk factors like smoking, alcohol, blood pressure, and cholesterol in the early stages of the chronic disease) will reduce the prevalence of disability and enhance life expectancy.

The National Long Term Care Survey (NLTCS) has shown that disability and morbidity prevalence in the U.S. elderly population declined between 1984 and 1989 (Manton, Stallard, & Corder, 1995). However, the demand for acute and long term care services will rise with the rapid growth of the elderly. This will influence the variety of services required in the future. In order to advance biomedical research, the growth of life expectancy rates, disability and morbidity trends, and developments in morbidity and disability declines should be carefully balanced (Manton, Stallard, & Corder, 1995).

The population of 13 million Americans using long term care services in 2000 is projected to increase to approximately 27 million people by 2050; 8 million out of the 13 million Americans in 2000 were the elderly. The elderly population is expected to rise to 19 million in 2050 due to the rapid growth of that population in need of care (Department of Health and Human Services & Assistant Secretary for Planninf and Evaluation , 2003). The expectation of older Americans living longer has presented new challenges to the development of health and social policy in terms of the maintenance of quality of life and the provision of cost effective health care.

As mentioned by Greener, Miners, Petty, and Szydiowski (1992), the comparison of people who die at an older age to people who die at a young age show a higher use of acute services over a longer length of time. Also, older patients use hospital care more than average only in the later years of life. However, younger patients have a much longer pattern of use, several years before the last years of their life. Greener et al. (1992) proposed that preventive interventions directed at the elderly must be focused on increasing longevity and disability reduction as life expectancy continues to increase. The number of people dying at older ages will increase, and the total number of years of disability before death will increase as well. Therefore, excessive, high-tech care for older people in their last years before death is a much smaller problem than overall long term care for the frail and disabled elderly population.

Because of the aging of the population, the number of physician visits is expected to increase. According to the American Academy of Family Physician (2005), the number of visits to physicians’ office was 838 million in 2003 but was only 581 million in 1980, and the number of visits had increased by approximately 45%. Approximately 902 million physicians’ offices visits were made in 2006, which included 58.3% of visits were primary care specialist, 22% of visits were medical specialist, and 19.7% of visits were surgical specialist (Cherry, Hing, Woodwell, & Rechtsteiner, 2008). People aged 65 years and older have comprised 25.5% of total physician visits in 2006.

Other than the physician visits, there will also be an increase of nursing home residents, which in 1977, consisted of 1.28 million residents. This number had increased by 27% to 1.63 million in 1999 (Decker, 2005). According to the Centers for Medicare & Medicaid Services, there were approximately 3.3 million nursing home residents in 2009, where 16.7% were people aged 65-74, 32.2% were people aged 75-84, 31.7% were people aged 85-94, and 5.2% were people in age group 95 and older (Centers for Medicare & Medicaid Services, 2010). This has shown that the aging of the population affects the number of residents in nursing.

Sweden has the highest life expectancy of 81.8 years among all OECD countries (OECD, 2012) and also usually the lowest mortality rates. Sweden has a socially responsible health care system to ensure all citizens have access to health care. Because Sweden is the one of the countries that has successful health care system, a comparison between the United States and Sweden was made. As shown on Table 4, health spending in OECD countries, Sweden spent 9.6% of its Gross Domestic Product (GDP) on health care, which was slightly higher than the 9.5% average of OECD countries. Sweden’s health care spending per capita was $ 3,758 in 2010, which was $490 more than the average OECD spending per capita. Even if Sweden had higher health care expenditures than the average of the OECD in 2010, it had lower spending compared to the United States.

Compared to most industrialized countries, the United States had the highest percentage GDP spent on health care, at 17.6% of the country’s GDP in 2010. Also, the United States spent more than two times the amount on health care spending per capita ($8,233) compared to the OECD average spending per capita of $3,268.

According to Table 2, the OECD statistics for 2011, Sweden’s health care expenditures were 17.1% private expenditures, in comparison to 81% on public expenditures. In order to cover public services rendered to residents, the county councils and the municipalities levy proportional income taxes on the residents. Also, state grants and user charges can be obtained by the county councils and municipalities. According to Anell, Glenngard, and Merkur (2012), the user fees for visiting their primary physician are between Swedish Krona (SEK) 100 and SEK 200 ($15 - $30) and SEK 230 to SEK 320 ($34 - $48) for specialist visits. SEK 80 ($12) will be charged per day of hospitalization for each patient, but those who are under 20 years old will be free of charge. The pharmaceutical sector is fully run by the government and the co-payment for prescribed drugs is consistent in Sweden. The maximum annual co-payment for prescribed drugs is SEK 2200 ($329).

Most OECD countries have the public sector as their main source of health care spending. The United States has 48.1% of public health spending, which is less than 72.2% the OECD average. The United States is heavily reliant upon private health care compared to other OECD countries, which accounted to 51.9% of total expenditures on health.

Advances in medical technology have been a significant driver in the increased cost of health care and insurance premiums. The simple explanation for the rapidly increasing health care costs is that people are getting more care as they get older and the older population is growing rapidly. According to Rettig (1994), technology that affects health care costs include developments in clinical abilities and new treatments for previously untreatable terminal conditions, expansion of the indications for a treatment over time, incremental improvements in existing capabilities, and the cumulative effect of incremental improvements. Indeed, innovation in medical care has been influenced by many factors. These include consumers’ demand for better health, health insurance that assures that patients can afford the new medical products, professionals who desire to find better ways to treat their patients, and commercial companies that invest large amounts in research and development for financial reimbursement.

Cost savings will not be feasible without cost containment. New medical technology includes new diagnostic procedures, equipment, and processes to deliver medical care. Applications of established technologies such as the Magnetic Resonance Imaging (MRI) are more responsible for the cost increases than technologies that are being applied to medical care for the first time. Other than that, Computed Tomography (CT) systems, Position Emission Tomography (PET), coronary artery bypass grafting, and angioplasty also result in increased spending in general. Heart attack is one of the leading causes of death in the U.S. (Centers for Disease Control and Prevention, 2012). Advanced medical technologies have changed the treatment and prevention of heart disease over time. For instance, new drugs strategies were developed such as aspirin, beta-blockers, and statins. Better tests also have become available to diagnose heart attacks. Thus, the rate of heart attacks in the U.S. has decreased from 345.2 to 186 per 100,000 persons (Goyen & Debatin, 2009).

As shown in Table 6, the United States had more expensive diagnostic equipment installed and used in 2010 than Sweden. The number of CT scanners per million population was 40.7 and the MRI units per million population was 31.6. The United States had more than double the number of CT scanners 22.6 than the OECD’s average of 12.5 MRI units. The United States has higher figures because of the increasing number of consumers who demand better health care and purchase more health care services. The installation of PET/CT scanners in the U.S. has grown significantly, accounting for more than 40% of the 2,000 PET/CT systems worldwide (Goyen & Debatin, 2009).

According to Goyen and Debatin (2009), Medical technology is not being used cost-effectively for three reasons. First, patients sometimes make exaggerated demands on physicians because they do not pay directly for the health care they receive; second, new technology may be adopted for clinical advantage over other health care institutions while there may not be a big enough market for it yet; third, there is no widely accepted process to assess the value of new medical equipment (Goyen & Debatin, 2009). Increases are often driven by the growth in the number of machines that are installed. This leads to overcapacity and may cause doctors to prescribe treatments just to make use of the new medical equipment available. In addition, blind demand and advances in devices and drugs are driven by direct-to-consumer marketing. Double procedures and the unnecessary use of high-end procedures without adding a lot of value will drive up the costs on the use of new technology and should be avoided.

According to Goyen and Debatin (2009), annual spending on health care in the U.S. increased from $75 billion to $2 trillion from 1970 to 2005, and the estimated amount for 2015 will be $4 trillion. Most specialists believe that new medical technology accounts for a half to two-thirds of annual spending increases. Also, it is projected that the expenditures in health care will rise from 16% to 30% of the Gross Domestic Product (GDP) by 2030 (Goyen & Debatin, 2009). In fact, the rapid growth of health care costs also leads to the rise of health insurance premiums causing many people to not be able to afford insurance coverage. The high costs of insurance premiums have discouraged small businesses to launch their companies because they cannot pool risks due to the small number of workers and thus have harmed the growth of small businesses and the entire economy in the U.S.

Kellis and Rumberger (2010) indicated that government intervention is the best option to improve the cost and quality of the U.S health care system. They have recommended a universal standard insurance coverage of Americans by: 1) removing disparities in access, cost, and quality among different racial or economic groups; 2) accountable regional bodies to make health care coverage decisions and outcome; 3) alignment of physician and hospital incentives around quality outcomes rather than quantity; 4) use of information technology (IT) to identify and monitor the implementation of best practices, with predictions of over $350 billion in savings over ten years and the creation of improvements in the cost and quality of health care; and, 5) the use of quasi-competition to increase gains in quality (Kellis & Rumberger, 2010).