“China performs more cosmetic surgery than any country except America and Brazil. Almost 1.3m licensed procedures were carried out in 2010, according to the International Society of Aesthetic Plastic Surgery (as well as many more unlicensed ones). The market, which barely existed 15 years ago, is now worth some $2.4 billion. China’s growing wealth, and its obsession with celebrity culture, is fuelling the increase. Beauty is also deemed an advantage in the competitive white-collar workplace. People in search of a job submit a photograph with their application…The three most common procedures are double eyelid surgery, liposuction and nose jobs.”

Not all is well, however.

“…a leading plastic surgeon, called for higher standards after botched surgery complaints reached 20,000 a year. Her plea echoes that of Ma Xiaowei, a vice-minister of health, who said that during a random inspection of plastic surgery clinics in 2010, fewer than half met national standards.

This is the finding of a recent JAMA paper. After controlling for patient case mix, the authors examine variation in hospital spending in the last year of a patient’s life. The authors note that “Higher-spending hospitals differed in many ways, such as greater use of evidence-based care, skilled nursing and critical care staff, more intensive inpatient specialist services, and high technology, all of which are more expensive.” Higher spending hospitals (on a per patient basis) tend to be hospitals with a larger volume of patients. They are also more likely to “be located in urban areas; be associated with regional cancer centers; have on-site computed tomography and magnetic resonance imaging scanners, cardiac catheterization laboratories, and cardiac surgery capability; and be early adopters of critical care response teams.”

Higher spending hospitals had overall reduced mortality rates for four disease considered. “In the highest- vs lowest-spending hospitals, respectively, the age- and sex-adjusted 30-day mortality rate was 12.7% vs 12.8% for AMI, 10.2% vs 12.4% for CHF, 7.7% vs 9.7% for hip fracture, and 3.3% vs 3.9% for colon cancer.”

One reason for these differences could be that high-spending areas could be located in richer areas where mortality rates are lower for a variety of reasons. Although unobserved heterogeneity in patient case mix is a problem with any study, the authors do stratify their results based on neighborhood income and find similar results.

The relevance of this study to the United States, however, is hard to determine. Although high spending hospitals decrease mortality in Canada, almost all hospitals in the U.S. would be considered high spending by Canadian standards. Thus, it is unclear that marginal returns to additional spending in the U.S. would be similar to what was observed in this study. In fact, studies in the United States by Barnato et al. and Goodman et al. show “…a positive association between spending and outcomes among low-intensity hospitals or regions but no association at average or higher intensity levels.”

Sources:

• Stukel T, et al “Association of hospital spending intensity with mortality and readmission rates in Ontario hospitals“JAMA 2012; 307: 1037-1045.
• Barnato AE, Chang CC, Farrell MH, Lave JR, Roberts MS, Angus DC. Is survival better at hospitals with higher “end-of-life” treatment intensity? Med Care. 2010;48(2):125–132.
• Goodman DC, Fisher ES, Little GA, Stukel TA, Chang CH, Schoendorf KS. The relation between the availability of neonatal intensive care and neonatal mortality. N Engl J Med. 2002;346(20):1538–1544.

Public Health Expenditures in Indonesia

In the Suharto Regime, district health offices implemented centrally determined policies, and “a large network of public health clinics (puskesmas) was set up to deliver primary outpatient care. In 2001, Indonesia’s health sector decentralized, following far-reaching reforms that involved fiscal, administrative and political decentralization.”

Under the current decentralized systems, districts have a lot of autonomy.  Districts are free to set user fees for public health and medical services and call allocate resources to any public health program they wish without having to justify their spending patterns to the central government.

Indonesia still does have some centralist features.

“The central government sets employment conditions for civil servants, including those working in public health service providers financed by district governments. It also finances and runs social safety net programs for the poor, such as targeted price subsidies for public care. Total health spending is split almost evenly between the central/provincial level on one hand and the district level on the other hand; in 2005, they accounted for 48% and 52% of public health expenditures respectively.”

Most of the districts funding come from the central government.  The funding comes from three major sources:

• 56% general allocation grant (Dana Alokasi Umum – DAU)
• 12%: shared non-tax revenues (i.e., natural resource revenues)
• 11%: shared tax revenues (i.e., property and income taxes)
• 3%: Specific allocation grant (Dana Alokasi Khusus – DAK)

The district’s own revenues fund about 10% to 16% of expenditures in the district.

Decentralization lead to a significant increase in public health spending.  Between 2001 and 2004 overall public health spending increased from 9,251 billion Indonesian Rupiah (IDR) to 16,703 IDR, a 21.8% average annual increase.

The question is, does this increased funding lead to increased public health spending at the district level and increased utilization.

Literature

Filmer and Pritchett (1999) note the lack of correlation between public health spending and child mortality and conclude that governance, or the way in which resources translate into actual programs, and crowding out of the private sector by the public sector are the missing chains that explain the low correlation.

McGuire (2006) shows that in a cross section of developing countries, access to maternal and infant health programs is correlated with decreased under 5 mortality, while public health spending is not. This indicates that it is the quality of the implemented programs that matter, and not the spending per se.

Kruse et al. Findings

Using panel data from 207 Indonesian districts between 2001 and 2004, a paper by Kruse et al. finds that the large increases in transfers from the central government large resulted in increased health spending by the district.  The authors estimate an elasticity of 0.9 (i.e., the district would spend $90 out of the $100 transfer from the central government on public health services).

The authors do not find significant crowd-out; increased public health spending does not reduce the private provision of medical services.  Increased public health spending also appear to increase health care utilization, particularly for poorer individuals.

Sources

• Ioana Kruse, Menno Pradhan, Robert Sparrow. Marginal benefit incidence of public health spending: Evidence from Indonesian sub-national data. J Health Econ, January 2012, 31(1): 147-147.
• Filmer, D., Pritchett, L., 1999. The impact of public spending on health: does money matter? Social Science & Medicine 49, 1309–1323.
• McGuire, J.W., 2006. Basic health care provision and under-5 mortality: a crossnational study of developing countries. World Development 34, 405–425.

In 2006, the Netherlands instituted a form of managed competition. According to Van Dijk et al (2012) ”Before 2006, inhabitants had either compulsory social (sickness fund, 62%) or voluntarily private (36%) health insurance depending, among others, on income (below a gross annual income of €33 000 people were socially insured).  This combined system of social and private health insurance was replaced by a compulsory single universal basic health insurance covering a legally defined package of basic benefits including GP care. GPs act as gatekeepers for secondary care…”

The implementation of a managed competition system in the Netherlands cause two major changes to the primary care payment system.   First, cost sharing was abolished for privately insured individuals.  Second, whereas previously doctors treating socially-insured patients received a capitation payment and physicians treating  privately-insured beneficiaries received a fee-for-service payments, after 2006 all physicians received a mixed capitation/fee-for-service payment system.

How did these changes affect the number of primary care visits in the Netherlands?  The authors of the study used a sample of GP practices participating in the 2005-2007 Netherlands Information Network of General Practice (LINH) study to conclude the following:

“Abolition of cost sharing led to a higher increase in patient-initiated utilisation for privately insured consumers in persons aged 65 and older. Introduction of fee-for-service for socially insured consumers led to a higher increase in physician-initiated utilisation.”

Source:

• van Dijk, C. E., van den Berg, B., Verheij, R. A., Spreeuwenberg, P., Groenewegen, P. P. and de Bakker, D. H. (2012), MORAL HAZARD AND SUPPLIER-INDUCED DEMAND: EMPIRICAL EVIDENCE IN GENERAL PRACTICE. Health Economics. doi: 10.1002/hec.2801

Health insurance in the 19th century mostly occurred through mutual aid organizations, which paid out sickness benefits if their members became ill.  By 1885, about 10% of workers had joined “Friendly Societies.”  In the latter half of the 19th century, employers and unions began to create sickness funds for their workers.  Employers wanted to attract more workers; unions hoped to increase their member’s independence by reducing their reliance on employer-based schemes.  In 1891, the government not only recognized these societies, but began to offer subsidies to help finance their operations.

“Over  the next 40 years, government legislation moved steadily toward realizing the goal of universal effective health insurance coverage.  Early regulations sought to reduce the number  of societies so that they could achieve economies of scale. The government also gradually increased the number and categories of individuals who were required to  have coverage. A gap emerged between professionals with individual contracts and  manual workers with collective contracts, with the former enjoying a higher level of insurance coverage, particularly with regard to sick pay. Sweden almost enacted a universal insurance system in 1935, but the economic crisis in that period forestalled adoption.  The legislation establishing a universal system was finally passed in 1946 and implemented in 1955.”

The CIA World Factbook provides some additional facts on the Swedish healthcare system:

• Health Spending: 9.9% GDP
• Taxes: 53% of GDP.
• Health Revenue derived from county taxes: two-thirds
• Share of local budget dedicated to health: 85%
• Life Expectancy: 81.07 years
• Total Fertility Rate: 1.67

Source: William Savedoff, Tax-Based Financing for Health Systems: Options and Experiences, WHO Discussion Paper, 2004.

“The rate of preventive care use is much higher in the USA than in Taiwan, whereas the use of hospital and emergency care is about the same. Results of our decomposition analysis suggest that higher levels of education and income, along with inferior health status in the USA, are significant factors, each explaining between 7% and 15% of the gap in preventive care use.”

Today I review some additional information about the Taiwanese health care system.  This information adds to my earlier review.

• Healthcare System.  Taiwan launched the National Health Insurance (NHI) program in 1995.
• % Uninsured.  Taiwan’s NHI covers about 98% of the population (compared with only 59% who had coverage prior to 1995)
• Benefits. NHI covers inpatient care, outpatient care, laboratory tests, pharmaceuticals, dental services, TCM, day care for the mentally ill, and nursing home care. Expensive medical services, such as magnetic resonance imaging scans and organ transplantation, are covered as well.
• Physician Supply. There are 1.4 physicians for every 1,000 persons in Taiwan (versus 2.3 in the USA, 2.1 in Canada, and 2.2 in the UK)
• Waiting Times. Hsiou and Pylypchuk (2011) claim that “Taiwanese patients can readily choose their providers without experiencing the long waiting lines that exist in the Canadian and UK systems.”
• Administrative Costs. 2%.
• Spending. 6.3% of GDP (vs. 16% in the U.S., 10% in the U.K. and Canada)
• Funding. The cost of care is primarily financed through premiums, which are calculated based on individuals’ salaries and supplemented with out‐of‐pocket payments and direct government funding.
• Provider Payments.  Fee‐for‐service payment under global budgeting (which in practice operates as a prospective payment system)
• Cost Sharing. 10% for hospital stay hospitalization.  Copayments for pharmaceuticals and physician visits (usually under $10 for primary care visit)
• Physician Visits.  Hsiou and Pylypchuk (2011) state that “primary care physicians are allotted only a few minutes to spend with patients and lack incentives to provide sufficient preventive care.”

Source: Hsiou, T. R. and Pylypchuk, Y. (2011), Comparing and decomposing differences in preventive and hospital care: USA versus Taiwan. Health Economics. doi: 10.1002/hec.1743

At least for the years 2000-2008, there is mixed evidence.  U.S. healthcare spending per person grew by 3.4%.  This is slower than Spain (4.7%), the U.K. (4.6%), the Netherlands (4.3%), Belgium (4.2%), and Sweden (3.6%).  However, spending as a share of GDP grew fastest in the U.S. of any country over this time period.  The U.S. experienced a 2.6 percentage point gain in health care spending as a share of GDP.  The next closest country was Belgium with a 2.1 percentage point increase in healthcare spending as a share of GDP and the Netherlands with a 1.9 percentage point increase.

In 2008, the disparities in healthcare spending as a share of GDP were still immense.  The U.S. spent 16% of its economic production on health care.  The next closest countries are France (11.2%), Belgium (11.1%), Switzerland (10.7%), Germany (10.5%), Austria (10.5%), Canada (10.4%), and the Netherlands (9.9%).

Even if the U.S. doesn’t reduce it’s health spending level, if the current health care spending rate does not slow, this country could be bankrupt sooner rather than later.

• Source: Kaiser Family Foundation using data from the OECD.

According to the Economist:

“Created in 1989 from the merger of two state systems, one for those in formal work and the other for everyone else, it is exceptional in Latin America, which by and large continues with the two-tier public system Brazil abandoned. The 1988 constitution declared health care to be the right of the citizen and its provision the duty of the state. ICESP enshrines that promise: according to Paulo Hoff, its clinical director, its patients, both poor and better-off, get care which compares well to that of his private patients at the nearby Sírio-Libanês Hospital.”

Brazil’s Programa Saúde da Família (PSF), launched in 1994, is one step towards interdisciplinary basic health care for most Brazilians.  The PSF implements a national policy for primary care settings with the aim of substituting part of the traditional model of primary care based on medical specialists. As its name says, its main focus is on families instead of individuals, and it is organized around multidisciplinary Family Health Teams, formed by a core of professionals such as physicians, nurses, dentists, psychologists and social workers, as well as community health agents, a kind of “barefoot doctor”. Brazil has currently (August 2009) approximately 30,000 of these teams, deployed in 5,241 of its 5,656 municipalities.  By 2005 over 80% of municipalities had been reached. However, since these consisted mostly of small rural municipalities, this covered 35% of the population.

But there is a gap between the aspirations of SUS and the reality. Funding is an inadequate hotch-potch, part-state, part-federal, and varies wildly from place to place. More than two-thirds of ICESP’s (Instituto do Câncer) budget of 350m reais ($225m) comes from São Paulo’s state government. Few other states are rich enough to provide such generous top-ups. SUS’s family doctors reach only one Brazilian in two. Another quarter have private-health insurance; the remainder, mostly poor people, live in remote rural areas or violent urban slums where the service is lacking. They must either pay out of pocket or take their chances in crowded hospital emergency rooms.”

Further, basic indicators are not as good as peer countries.  Life expectancy is lower than in Mexico, Argentina, Venezuela and Chile, and the infant mortality rate is the highest among these countries.

“A recent survey of Brazilian health care published in the Lancet, an international journal, argued that SUS gets poor value for the money it spends on drugs, because too much goes on complying with court orders granted to patients who use the constitution’s lofty promises to demand expensive treatments not automatically covered by the system. And too much of the budget still goes to hospitals rather than the Family Health Programme, says Michele Gragnolati of the World Bank.”

Statistics

• Brazil GDP per person: $10,800
• SUS (Public) spending as a share of GDP: 3.1%
• Health care spending as a share of GDP: 8%
• Share of health care spending that is privately funded: 60%
• Life expectancy at birth: 72.5 years
• Infant Mortality Rate: 21.17 deaths per 1000 live births
• Number of beds per 1,000 (global average): 2.4 (4.3)
• Nurses per 1,000 (global average): 29.1 (60.3)
• Physicians per 10,000 (global average): 16.9 (23.4)
• Brazil’s Population: 203.4 million

Sources:

• CIA World Factbook: Brazil.
• GE’s Health of Nations website using data from the World Health Organization.
• “Health care in Brazil: An injection of reality” The Economist, 30 July 2011.

“In Germany, about 90% of the population is publicly insured (Colombo & Tapay, 2004). Buying public insurance is mandatory for dependent employees with a regular employment contract as long as their income does not exceed the so-called compulsory insurance threshold. The public insurance premium equals a certain percentage (nowadays about 15% that are equally shared between the employer and the employee) of gross income up to the so-called contribution ceiling, and equal to it thereafter.”

Why would someone want private insurance? Coverage is universal in the public system and the deductibles and co-payments are limited. Here’s why”

“Contributions for private health insurance are mainly based on health and age, so buying private insurance is especially attractive for young individuals. As a consequence of this, and because of the fact that private insurers are allowed to reject individuals, the risk pool of the private insurers is much better than in the public system…Privately insured individuals can buy better care, e.g. treatment by the head doctor in a hospital or a single room in a hospital, but this comes at a higher price.  Deductibles and co-payments are much more common, and many insurers offer a rebate if an individual did not use medical services in the past calendar year.”

In fact, a paper by Hullegie and Klein (2011) finds that individuals with private insurance are much less likely visit a doctor. This is likely due to adverse selection although moral hazard may also play a role since private insurance plans have higher copayments and deductibles.

• Hullegie, P. and Klein, T. J. (2010), The effect of private health insurance on medical care utilization and self-assessed health in Germany. Health Economics, 19: 1048–1062. doi: 10.1002/hec.1642

“From the theoretical model we find that higher levels of patient complexity lead GPs [General Practitioners] to choose a lower list size, whereas the effect on income is ambiguous. The effect on total utility (income and leisure) is, however, shown to be negative. Using empirical datafrom 1039 solo practices we find that patient complexity reduces both list size and income and conclude that amixed per capita and fee for service remuneration system does not fully compensate practices with more complexpatients. Differentiated per capita payment may represent a means of ensuring fair and equal income of GPs.”

Differentiated per capita payments may provide a fairer mechanism for compensating physicians for treating more complex patients. This type of reform, however, would also incentivize providers to upcode patient diagnoses in order to increase their per capita payments. Thus, this paper may provide the optimal solution in the case where providers are honest, but this same solution may not be optimal in the case where physicians are potentially dishonest.

The remainder of this post reviews how the authors arrived at the conclusions discussed below.

The Danish Healthcare System

The around 5 million inhabitants in Denmark are served by approximately 3500 GPs organised in 2200 practices. Of those a little more than 1000 GPs are organised in solo practices. The remaining GPs are organised in partnership practices. Denmark operates a public health insurance system, where general practice has the role of gatekeeper for the rest of the healthcare system. The system is tax-funded and covers the whole population. The primary healthcare sector is organised as a list system where all citizens have to be registered with a GP and must contact this GP to receive medical advice and care. Patients are entitled to medical specialist care after referral by their GP only.

All GPs are organised as self-employed private entities and are subjected to the same remuneration scheme, which is based on a mix of fee for service (approximately 70%) and per capita (approximately 30%) payment.

Theoretical Model

The author use a theoretical model in which physicians choose the number of patients to treat. Treating more patients increases income, but decreases leisure. Additionally, the average case mix severity of the GP’s patient roster affects the amount of services–and the amount of time–GPs provide to their patients.

• U_i = p^pcn_i+p^ffs (n_iα(θ)) – C + v(l_i)

The physician maximizes the utility function above by choosing the number of patients to treat (n_i).

The model’s equilibrium predictions are that: 1) list size decreases as patient complexity increases, 2) Overall GP utility decreases as patient complexity increases, and most interestingly 3) differentiated per capita payment can prevent utility loss from serving complex patients. Differentiated capitation payments are larger for sicker patients than for healthier ones.

The data set used contains information on 1039 solo practices from the year 2006. The Health Insurance Register contain data on list size, income and the age and sex of the physician are from the Health Insurance Register. Data on weekly hours of practice personnel and information about whether the practice participates in education of new GPs are from the National Practice Count Survey conducted in December 2005.

Empirical Application

The analytical framework uses two estimation equation.  The first regresses GP characteristics and average patient illness severity on the number of patients on the GP’s rolls.  The second regresses the number of patients on the GP’s rolls, the interaction of the number of patients the GP cares for and the patients’ average illness severity, and GP characteristics on GP income.  The authors measure patient illness severity using the  Danish deprivation index (the DADI index) developed by Vedsted and Sorensen (2009).  To estimate the coefficients of interest, the authors combine the two equation and used a reduced form regression framework, using bootstrapping techniques to derive the confidence intervals.

The key drawback of this paper is that it assumes that patient complexity is exogenous. The authors find that age does have significant explanatory power for predicting patient complexity, but since this variable also has explanatory power in relation to list size, it cannot be used as instrument in the list size equation.

Results

“The GPs’ utility was in the theoretical model assumed to depend on income and leisure. The effect of patient complexity on these two factors in isolation was shown to be ambiguous as both positive and negative effects appear in both cases. However, from the theoretical model we showed that the overall GP utility is always reduced when the level of patient complexity increases. In the empirical section we analysed the impact of patient complexity on income and found that the net impact was negative.  The increase in the fee for service payment, resulting from serving patients with higher complexity, is hence not adequately compensating for the per capita income loss following the reduced list size. This indicates that the remuneration scheme is not sufficiently flexible to ensure equal income across GPs serving different population groups.”

Source:

• Olsen, K. R. (2011), Patient complexity and GPS’ income under mixed remuneration. Health Economics, 20: n/a. doi: 10.1002/hec.1731