health care expenditures

There is concern that the demographic pressures of population ageing will lead to an unprece- dented rise in public expenditures to levels unsustainable under current financing arrangements. In the UK in 2013 approximately 17% of the population (11 million individuals) were aged 65 years or over. This represents a rise of 17.3% in this age group on a decade earlier. Projections suggest that by 2050 this group will have increased disproportionately to younger age groups accounting for approximately 25% of the population (Cracknell, 2010)). The growth in the proportion of older individuals is partly due to increased longevity and partly due to the age structure of the population, particularly ageing of the generation of baby boomers of the post war period to the early 1970s. Health care expenditures in the UK have also risen substantially over time both in real terms and proportional to economic growth. Close to the inception of the National Health Service (NHS) net expenditure (net of patient charges and receipts) on the UK NHS in 2050/51 was £ 11.7b (GBP, in 2010/11 prices); representing 3.5% of Gross Domes- tic product (GDP). This rose to £ 121.3b in 2010/11; approximately 8.2% of GDP. Over the twenty-five year period from 1999/00 to 2014/15 expenditure in England has almost doubled to £ 103.7b (2010/11 prices) with an average expenditure per head of population of £ 1,900 (Harker, 2012). Abstracting from issues such as technological innovation, the concern is that as the share of the population at older ages rises, the economic burden of providing healthcare will become increasingly unsupportable.

There is concern that the demographic pressures of population ageing will lead to an unprecedented rise in public expenditures to levels unsustainable under current financing arrangements. In the UK in 2013 approximately 17% of the population (11 million individuals) were aged 65 years or over. This represents a rise of 17.3% in this age group on a decade earlier. Projections suggest that by 2050 this group will have increased disproportionately to younger age groups accounting for approximately 25% of the population (Cracknell 2010)). The growth in the proportion of older individuals is partly due to increased longevity and partly due to the age structure of the population, particularly ageing of the generation of baby boomers of the post war period to the early 1970s. Health care expenditures in the UK have also risen substantially over time both in real terms and proportional to economic growth. Close to the inception of the National Health Service (NHS) net expenditure (net of patient charges and receipts) on the UK NHS in 2050/51 was £11.7b (GBP, in 2010/11 prices); representing 3.5% of Gross Domestic product (GDP). This rose to £121.3b in 2010/11; approximately 8.2% of GDP. Over the twenty-five year period from 1999/00 to 2014/15 expenditure in England has almost doubled to £103.7b (2010/11 prices) with an average expenditure per head of population of £1,900 (Harker 2012). Abstracting from issues such as technological innovation, the concern is that as the share of the population at older ages rises, the economic burden of providing healthcare will become increasingly unsupportable.

We examine whether and to what extent the health insurance system in Turkey provided adequate protection against high out of pocket expenditures in the period prior to “The Health Transformation Programme” (HTP) for the non elderly population. We measure health care burdens as the share of out of pocket health care expenditures within family income. We define high burdens as expenses above 10 and 20 percent of income. We find that 19 percent of the nonelderly population were living in families spending more than 10 percent of family income and that 14 percent of the nonelderly population were living in families spending more than 20 percent of family income on health care. Furthermore, the poor and those living in economically less developed regions had the greatest risk of high out of pocket burdens. More significantly, we find that the risk of high financial burdens varied by the type of insurance among the insured due to differences in benefits among the five separate public schemes that provided health insurance in the pre-reform period.

The AHEAD survey uses an innovative “brack- eting” method to collect data that are usually sub- ject to high rates of nonresponse, such as health- care expenditures [36]. When a respondent is unwilling to provide an exact amount in response to one of the expenditure questions, he/she is pre- sented with response brackets such as, “Was it more than $200?”; “more than $500?”; “less than $1000?”; etc. The responses to these bracket ques- tions are then used to impute an expenditure value for these questions that can then more easily be used in data analyses. Imputed responses for bracketed questions were derived for between 2% (home care expenditures) and 19% (doctor visits) of respond- ents for the individual expenditure categories. The full methodology for this imputation procedure is described elsewhere [37].

Results. Our findings demonstrate that the 7.3% of US children with disabilities used many more services than their counterparts without disabilities in 1999 –2000. The largest differences in utilization were for hospital days (464 vs 55 days per 1000), nonphysician professional visits (3.0 vs 0.6), and home health provider days (3.8 vs 0.04). As a result of their greater use, children with dis- abilities also had much higher health care expenditures ($2669 vs $676) and higher out-of-pocket expenditures ($297 vs $189). We also found that the distributions of total and out-of-pocket expenses were highly skewed, with a small fraction of the disabled population account- ing for a large proportion of expenditures: the upper decile accounted for 65% of total health care expenses and 85% of all out-of-pocket expenses for the population with disabilities. Health insurance was found to convey significant protection against financially burdensome ex- penses. However, even after controlling for insurance status, low-income families experienced greater financial burdens than higher income families.

Overweight and obese individuals are at in- creased risk for many diseases and health con- ditions, including but not limited to the following: hypertension; osteoarthritis; dyslipidemia; type 2 diabetes; coronary heart disease and stroke. Consequently, individuals who are obese are more likely to use health services and are more likely to use costly health services than non-obe- se individuals. Between 1987 and 2001, growth in obesity related health expenditures accoun- ted for 27 percent of the growth in inflation-ad- justed per capita health care spending. Resear- chers, popular press and the television news media have paid considerable attention to the effect that farm subsidies have on dietary habits and obesity. Prominent researchers in the field have concluded that US farm subsidies have had a negligible impact on obesity. However, even small increases in obesity rates are associated with higher health care expenditures. The prima- ry intent of this study is to break down the link- ages from farm subsidy to health expenditure and shed light on the unintended implications of the farm subsidy program. We find that agricul- tural subsidies have the potential to influence health care expenditures.

Between years 1 and 2 of the study, increasing SDM was associated with a signi fi cant decrease in total health care expenditures ( 2 $339 (95% CI: 2 $660, 2 $21) (Table 2). Total costs did not change signi fi cantly over time for those with any other SDM pattern. During the study period, prescription expenditures increased for all groups. When we assessed the relative differ- ences in the change in costs from year 1 to 2 between those with each SDM pattern (Table 4), we found that those with increasing SDM had signi fi cantly lower total and out-of-pocket health care expenditures compared with those with decreasing SDM with relative dif- ferences of 2 $584 ( 2 $1131, 2 $38) and 2 $142 ( 2 $265, 2 $19). No signi fi cant contrasts were observed between the unchanged high and low SDM groups for any outcome. These expenditure results were con fi rmed in secondary analyses with the cost percentile rank as the outcome.

There is concern that the demographic pressures of population ageing will lead to an unprece- dented rise in public expenditures to levels unsustainable under current financing arrangements. In the UK in 2013 approximately 17% of the population (11 million individuals) were aged 65 years or over. This represents a rise of 17.3% in this age group on a decade earlier. Projections suggest that by 2050 this group will have increased disproportionately to younger age groups accounting for approximately 25% of the population (Cracknell, 2010)). The growth in the proportion of older individuals is partly due to increased longevity and partly due to the age structure of the population, particularly ageing of the generation of baby boomers of the post war period to the early 1970s. Health care expenditures in the UK have also risen substantially over time both in real terms and proportional to economic growth. Close to the inception of the National Health Service (NHS) net expenditure (net of patient charges and receipts) on the UK NHS in 2050/51 was £ 11.7b (GBP, in 2010/11 prices); representing 3.5% of Gross Domes- tic product (GDP). This rose to £ 121.3b in 2010/11; approximately 8.2% of GDP. Over the twenty-five year period from 1999/00 to 2014/15 expenditure in England has almost doubled to £ 103.7b (2010/11 prices) with an average expenditure per head of population of £ 1,900 (Harker, 2012). Abstracting from issues such as technological innovation, the concern is that as the share of the population at older ages rises, the economic burden of providing healthcare will become increasingly unsupportable.

C-CDs, who frequently establish their medical home at hospital- based academic medical centers, we expect broader community access for children with NC-CDs. Children with chronic illnesses may gain the most benefit from comprehensive care coordination and managed care; yet, the NC-CD and C-CD groups were less likely to participate in Medicaid Managed Care than children WO-CDs. Wider implementation of managed care that emphasizes care coordination and increased emphasis on the primary care physician as a medical home for the pediatric Medicaid population with chronic illnesses may result in improved health and limit the growth of health care expenditures. 24 – 27

As summarized in Table 2.2, results from these studies generally demonstrate that a small proportion of individuals account for a disproportionately large share of health care expenditures, and that a small group exhibits persistently high expenditures. However, it is unclear whether the same pattern of expenditure concentration and persistence holds in individuals with AD given that this population has substantially more functional disabilities and greater burden of comorbidities. The uneven distribution may suggest that some groups obtain excessive care with benefits not commensurate with expenditures, whereas other groups underuse medical care. Understanding the dynamics of expenditure distribution can help decision makers plan equitable health insurance strategies, such as catastrophic care, carve-outs, reinsurance, and risk adjustment [Liptak et al., 2006]. Moreover, understanding the characteristics that predict persistence can be used as a management tool to help health plans identify individuals at risk of accruing high expenditures earlier in the process, and target members for intensive disease management and better care coordination [Russell and Chaudhuri, 1992; Ash et al., 2001].

In this article it is investigated the convergence of health care expenditures per capita in OECD during the 1970–2005 period by applying Lima and Resende (2007) persistence methodology. Departures across countries were evaluated in terms of panel data unit root tests advanced by Im et al. (2003). The evidence illustrated that one cannot reject the null hypothesis of unit root for the (log) of the ratio of health care expenditures of each country relative to a reference unit except average of per capita health expenditures The results, therefore, favour a very strong form of persistence for OECD expenditures inequality.

Kabir (2008) examined the context of cross-country investigation in developing countries at the beginning of the twenty-first century [20]. His findings suggested that hat there was no guarantee in the improvements in terms of per capita income, education, per capita health expenditure, and urbanization would lead to higher life expectancy among the developing countries. This is because over the last ten years many of these countries have witnessed gains in these areas but demonstrated decrease in life expectancy. However, in many developing countries, Sub-Saharan Africa in particular, the life expectancy has been decreasing. In some countries, although the income and health expenditure have increased, the life expectancy is decreasing. In lower middle income countries, like South Africa has shorter life expectancy than other similar countries. Unfortunately, HIV AIDS has taken its toll in Africa, Asia and even Latin America by reducing life expectancy in 34 different countries (26 of them in Africa). Africa is home to the world's lowest life expectancies with Swaziland (33.2 years), Botswana (33.9 years) and Lesotho (34.5 years) rounding out the bottom. Between 1998 and 2000, 44 different countries had a change of two years or more of their life expectancies from birth and 23 countries increased in life expectancy while 21 countries had a dropurdered [19].

This analysis has several limitations. First, with regards to captured costs, our data do not include costs gener- ated by off-site health care services, namely specialized outpatient care unavailable on-site, emergency admis- sions or inpatient care. Complete cost data were not available for these services since providers other than the CHUV may supply them. Off-site care is typically costly, primarily because concerned individuals require emergency admissions or hospital stays and are usually more severe. Off-site transfers also involve complex security measures and generate further non-medical ex- penses. However, off-site care complements rather than substitutes regular outpatient care in prison clinics, since prison medical staff act as gatekeepers for off-site care and are responsible for subsequent follow ups. Not ac- counting for these off-site is thus unlikely to deflate (or shift) the on-site costs. Furthermore, on-site outpatient care represents more than 95% of the total number of outpatient consultations, making this study highly rele- vant for prison health care governance. Further research aiming at evaluating individual risk factors for off-site health care utilization would be pertinent.

In this vein, Bakare and Olubokun (2011) examined health care expenditures and economic growth in Nigeria using ordinary least squares multiple regression analytical method and employed data covering 1970 to 2008. Their study showed a significant and positive relationship between health care expenditures and economic growth in Nigeria and concluded that Nigerian Government should pay attention to health sector not only by increasing its budgetary allocation but also ensuring appropriate implementation and adequate monitoring of the budget. While Odior (2011) investigated the potential impact of increase in government expenditure on health in Nigeria using computable general equilibrium (CGE) model and discovered that government health expenditure is significant in explaining economic growth in Nigeria and concluded that more resources should be channeled to health sector to provide quality of health to its citizens. Owolabi and Okwu (2010) observed in their study that human resource development is an important variable in economic growth bracket in Nigeria and they recommended among other things that government should boost revenue allocation to the health and education sector of the economy for steady and sustainable growth.

One of the most common problems with health care systems around the world is that the cost of running them tends to increase at higher rate than the rate of infl ation (see Glied & Smith, 2013). This has led among others to the introduction of visit fees by governments and/or public as well as private health care facilities and other health care providers. According to the last available data health spending is estimated to have increased by 1.0% in real terms across OECD countries in 2013, up from 0.7% in 2012 and near-zero growth in 2010. However, growth rates in 2013 remained well below pre-crisis levels: between 2000 and 2009 average growth in health spending reached 3.8% (OECD, 2015). Co-payments for physician services are common in high-income countries and are also considered in middle income countries of the Central and Eastern Europe (CEE) (Danyliv et al., 2013; Paris et al., 2010; 2016). Many high income countries increased the level of the patient cost sharing between 2000 and 2010 as a part of policy measures to reduce the level of health care spending (Zare & Anderson, 2013). In spite of higher levels of cost-sharing, out-of-pocket spending as a percentage of total spending remained unchanged in most of these countries because they instituted programs to protect certain categories of individuals. They achieved that by setting out-of-pocket limits, exempting people with certain chronic diseases, or eliminating cost sharing for certain demographic groups and low-income people (Zare & Anderson, 2013).These fees are meant to rationalize the use of the health care system and slow the growth of health care expenditures. There are also another ways how to rationalize a health care delivery system. Those include for example the substitution of ambulatory care for hospital care and promoting the system of one- day surgeries (Gavurova & Soltes, 2016).

(3.6 vs 2.4, P < 0.001), other outpatient services (2.9 vs 2.0, P < 0.05), and pharmacy prescriptions (3.1 vs 1.8, P < 0.001; Table 3). Consistent with increased HRU, the FLF (vs non- FLF) cohort incurred significantly higher mean total health care costs when measured as PPPM from the point of failure through the end of follow-up ($20,266 [SD = $18,956] vs $7,772 [SD = 15,982], P < 0.01) among all patients and annu- ally ($198,388 [SD = $196,197] vs $37,549 [SD = $40,949], P < 0.001) among patients with at least 12 months of follow- up (Figures 3 and 4). PPPM median costs were also mark- edly higher in the FLF cohort ($13,378) compared to those in the non-FLF cohort ($3,181). Annual and PPPM cost drivers were inpatient admissions, laboratory and radiology services, and other outpatient services for both the non-FLF and FLF cohorts. The FLF w/RT cohort had similar results as the FLF cohort with a consistently higher utilization of health care services and higher health care expenditures than the non-FLF cohort during follow-up (PPPM utilization and cost) and annually (12-month cost).

We restricted our study sample to the 1997 MEPS Panel 2 (approximately half of the full 1997 cohort) because only these subjects were asked questions regarding child care arrangements. We further restricted our sample to children aged 0 to 5 and selected only the youngest child from each household. To this sample of 871 children, we merged the 1998 MEPS Household Component variables that reflected child care attendance in 1997. We eliminated 1 extreme outlier from the analysis, whose 1997 total health care expenditures of nearly $100 000 were unsup- ported by any corresponding explanatory diagnosis from the MEPS diagnostic file, and were therefore considered an error.

Di Matteo (2005) used state-level data for the United States for the period 1980-1998 and province-level data for Canada for 1975-2000. He found that health care expenditures depended on income, time, and age distribution. While it is not surprising that the ageing of the population increases health expenditures, it does come as a surprise that it is not only those over 65 who tend to increase expenditures but also the proportion aged 18-44. Baltagi and Moscone (2010) also find an effect of the younger population on health care expenditures. They investigate the long-run relationship between health care expenditures and income in 20 OECD countries and find, in addition to a positive long-run relationship between health care expenditures and income, that the proportion of young people has a positive effect on health care spending.

Previous studies evaluating health care expenditures and utilization associated with diabetes and comorbid depres- sion report that in regional or selected populations, comorbid diabetes and depression are associated with more health care utilization and expenditures than diabe- tes without depression.[9,11,12] The most recent study estimating odds of diagnosed depression in individuals with diabetes and relationships between depression and health care utilization and expenditures in a nationally representative database was performed using 1996 data from the Medical Expenditure Panel Survey (MEPS). We propose to update that analysis, and hypothesize, based on recent drug developments in both diabetes manage- ment and treatment of depression, that individuals with both diabetes and minor depression will have higher rates of health care utilization in four categories: ambulatory care, inpatient care, emergency department visits, and pre- scription medications. While an increase in health care utilization often predicts a proportionate increase in expenditures, this may not hold true due to improved overall health resulting from effective treatment. There- fore, expenditures in all four categories will also be exam-

Limited research exists on the cost-effectiveness of AD pharmacotherapy; however, studies that have been conducted have demonstrated cost-savings when exposed to AD medications [8,27]. Gilligan et al. analyzed cost of care in Medicaid patient populations and found that among individuals who received 1 unique AD medication, total health care expenditures decreased significantly compared to those receiving no pharmacotherapy (p < 0.001); how- ever, when level of exposure increased to 2 or more drugs, there was no difference in cost between individu- als who received medication therapy as compared to those who received none [28]. A systematic review con- ducted by Cappell et al. examining pharmacoeconomic studies of these medications also suggests that cost of care is lower when AD patients receive pharmacotherapy [27]. Memantine is a medication that is indicated for moderate-to-severe stages of AD; therefore a potential reason why the costs of care are significantly higher in long-term care populations is most likely due to higher costs associated with later stages of AD rather than the medication itself.