Health care attracts major attention in terms of hospital and physician reimbursement, owing to the large share of public expenditures and the presence of welfare issues demanding regulation. The focus of this policy brief is quality adjustments of prospective payments in the health sector. Using the data on the 2013 reform in Medicare, we show differential effects of value-based purchasing, where price setting is related to benchmark values of quality measures. The theoretical and empirical evidence indicates that unintended effects appear for acute-care U.S. hospitals at the best percentiles of quality. The findings provide insights into benchmarking within pay-for-performance schemes in health care.
The Russian national project “Health”, which was started by the federal government a decade ago and has expanded to regionally financed hospitals, is an example of a public remuneration scheme targeted at increasing health care efficiency. The project emphasized the role of the primary sector and raised salaries of general practitioners. A part of salaries was linked to patients’ assessment of the quality of health care. The reimbursement was seen as a means to stimulate higher quality.
However, cautiousness is required in introducing such payment mechanisms. Indeed, international experience shows that quality-related pay in health care may lead to heterogeneous effects across different groups of providers. A recent CEFIR working paper uses administrative panels of the U.S. hospitals to analyze the changes in quality owing to the introduction of the quality-pay.
The U.S. Health Care Sector
Pilots of pay-for-performance
In the early 2000s, numerous private and public programs linking quality and reimbursements in health care existed in the U.S., mostly at employer or state level (Ryan and Blustein, 2011; Damberg et al., 2009; Pearson et al., 2008). A nationwide pilot of quality-performance reimbursement started with the Hospital Quality Incentive Demonstration, where quality measures for five clinical conditions (heart failure, acute myocardial infarction, community-acquired pneumonia, coronary-artery bypass grafting, and hip and knee replacements) were accumulated from voluntarily participating hospitals. Some of these quality-reporting hospitals opted for the pay-for-performance project (initially established for 2003-2006, and later extended to 2007-2009). The project provided respectively 2% and 1% bonus payments for hospitals in the top and second top deciles of each quality measure (as of the end of the third year of the project). Hospitals in the bottom two deciles, on the other hand, were to receive 1-2% penalties (Kahn et al., 2006). Overall, the financial incentives helped improving the quality of the participating hospitals, but the improvement was inversely related to baseline performance (Lindenauer et al., 2007). Moreover, low-quality hospitals required most investment in quality increase; yet, they were not financially stimulated (Rosenthal et al., 2004).
The accumulation of the measures within the Hospital Quality Incentive was followed by the launch of the Surgical Care Improvement Project (SCIP) and Hospital Consumer Assessment of Healthcare Providers (HCAHPS). HCAHPS was the first national standardized survey with public reporting on various dimensions of patient experience of care. The measures of the clinical process of care domain are collected within the Hospital Inpatient Quality Reporting (IQR) program. These are measures for acute clinical conditions stemming from the Hospital Quality Incentive (i.e. acute myocardial infarction, heart failure, pneumonia), as well as measures from the Surgical Care Improvement Project and Healthcare Associated Infections.
The 2013 reform of Medicare
The success of the pilot project in the U.S. in terms of average enhancement of hospital quality has resulted in the nationwide introduction of these reimbursement policies. Namely, a value-based purchasing reform started at Medicare’s acute-care hospitals in the fiscal year of 2013. The reform decreased Medicare’s prospective payment to each hospital by a factor α and redistributes the accumulated fund. As a result of this rule, all hospitals performing below the mean value of the aggregate quality are financially punished, as their so-called adjustment coefficient is less than unity. At the same time, hospitals above the mean value are rewarded (See details in the Final Rule for 2013: Federal Register, Vol.76, No.88, May 6, 2011.)
The aggregate quality – called the total performance score – is a weighted sum of the scores of the measures in several domains: patient experience of care, clinical process of care, outcome of care, and efficiency. The scores on each measure are based on the hospital’s position against the nationwide distribution of all hospitals. In short, positive scores are given to hospitals above the median, and higher scores correspond to performance at the higher percentiles. The scores are a stepwise function, assigning flat values of points to subgroups within a given percentile range. Hospitals above the benchmark (the 95th percentile or the mean of the top decile) are not evaluated according to their improvement relative to the performance in the previous year.
If one assumes that hospitals are only maximizing profit, then such a linear payment schedule should stimulate quality increases across all spectrums of hospitals. However, the theoretical literature generally separates the hospital management, interested in profits, from the physicians who make decisions affecting the level of quality. In particular, physicians are treated as risk-averse agents, who have a decreasing marginal utility of money; that is, their valuation of monetary gains of a certain size decreases as their income increases. In such behavioral model (Besstremyannaya 2015, CEFIR/NES WP 218) physicians’ decisions about the quality of care is shaped by the trade-off between the potential losses they may incur if fired in case of hospital budget deficit and/or bankruptcy and their own costly effort to maintain and improve quality.
In this respect, the reform introduced two mechanisms: (1) it decreased the level of reward for low-quality hospitals and increased it for high-quality hospitals; and (2) it established a positive dependence of reward on quality. We show that the two forces compete, and the first one may outweigh the second for physicians at hospitals with high quality. Indeed, in these hospitals improved budget financing makes the bankruptcy, and probability of firing, less likely. As a result, physicians may be satisfied with a given sufficient level of a positive reward and not willing to exert any further efforts to raise the amount of this reward. Furthermore, physicians may even become de-stimulated. As a result, in these higher quality hospitals, the quality of care stabilizes or even goes down after the reform.
To sum up, we hypothesize that quality scores increase at the lowest tails of the nationwide distribution, while it may stay stable or fall among the highest quality hospitals. The sign of the mean/median effect is ambiguous.
Data on quality measures and hospital characteristics such as urban/rural location and ownership come from Hospital Compare. The panel covers the period from July 2007 to December 2013, and consists of 3,290 hospitals (12,701 observations). We exploit first-order serial correlation panel data models – longitudinal models where the value of the dependent variable in the previous period (lagged value) becomes one of the explanatory variables (see notations and definitions of analyzed measures in Tables 1-2.) The empirical part of the study evaluates the impact of the reform on changes of the quality scores of hospitals belonging to different percentiles of the nationwide distribution of each quality measure.
Table 1. Patient experience of care
|Comp-1-ap||Nurses always communicated well|
|Comp-2-ap||Doctors always communicated well|
|Comp-3-ap||Patients always received help as soon as they wanted|
|Comp-4-ap||Pain was always well controlled|
|Comp-5-ap||Staff always gave explanation about medicines|
|Clean-hsp-ap||Room was always clean|
|Quiet-hsp-ap||Hospital always quiet at night|
|Hsp-rating-910||Patients who gave hospital a rating of 9 or 10 (high)|
Notes: Score on each measure is the percent of patients’ top-box responses to each question.
Table 2. Clinical process of care
|AMI-8a||Primary PCI received within 90 minutes of hospital arrival|
|HF-1||Discharge instructions (heart failure)|
|SCIP-Inf1||Prophylactic antibiotic received within 1 hour prior to surgical incision|
|SCIP-Inf3||Prophylactic antibiotics discontinued within 24 hours after surgery end time|
|SCIP-Inf4||Cardiac surgery patients with controlled 6 a.m. postoperative blood glucose|
|SCIP-VTE2||Surgery patients who received appropriate venous thromboembolism prophylaxis within 24 hours prior to surgery to 24 hours after surgery|
Notes: Score on each measure is the percent of percent of cases with medical criteria satisfied.
The results of the estimates offer persuasive evidence for a non-rejection of our hypotheses: quality goes up at 1-5th deciles and falls at the 6-9th deciles (see Figures 1-2).
Figure 1. Mean change of scores owing to value-based purchasing across percentile groups of hospitals
It should be noted that the hypotheses concerning differential effects also rely on the fact that there is a certain population of hospitals to which each of the step-rates apply (Monrad Aas, 1995). Hence, the threshold and/or benchmark value in the national schedule may be worse than the value in a given hospital. Therefore, reimbursement with benchmarking becomes an additional cause of undesired effects.
Figure 2. Mean change of scores owing to value-based purchasing across percentile groups of hospitals
Our analysis confirms the presence of adverse effects of quality performance pay in health care. A remedy may be found in establishing benchmark at the value of the best performing hospital or employing ‘episode-based’ payment, which rewards a hospital for treating each patient case with corresponding criteria satisfied (Werner and Dudley, 2012; Rosenthal, 2008).
While the above results are based on the US data, they suggest that cautiousness is required in applying the pay-for-performance schemes to healthcare financing also in transition countries, and much attention should be paid to the potential adverse effects.
- Besstremyannaya, Galina, 2015. “The adverse effects of incentives regulation in health care: a comparative analysis with the U.S. and Japanese hospital data” (2015) CEFIR/NES Working Papers, No.218, www.cefir.ru/papers/WP218.pdf
- Damberg, Cheryl L, Raube, Kristiana, Teleki, Stephanie S and dela Cruz, Erin, 2009. ”Taking stock of pay-for-performance: a candid assessment from the front lines”, Health Affairs, Volume 28, pages 517-525.
- Kahn, Charles N, Ault, Thomas, Isenstein, Howard, Potetz, Lisa and Van Gelder, Susan, 2006. “Snapshot of hospital quality reporting and pay-for-performance under Medicare”, Health Affairs, Volume 25, pages 148-162.
- Lindenauer, Peter K, Remus, Denise, Roman, Sheila, Rothberg, Michael B, Benjamin, Evan M, Ma, Allen and Bratzler, Dale W, 2007. “Public reporting and pay for performance in hospital quality improvement”, New England Journal of Medicine, Volume 356, pages 486-496.
- Monrad Aas, I., 1995. Incentives and financing methods, Health policy, Volume 34, pages 205-220.
- Pearson, Steven D, Schneider, Eric C, Kleinman, Ken P, Coltin, Kathryn L and Singer, Janice A, 2008. “The impact of pay-for-performance on health care quality in Massachusetts, 2001-2003”, Health Affairs, Volume 27, pages 1167-1176.
- Rosenthal, Meredith B, Fernandopulle, Rushika, Song, HyunSook Ryu and Landon, Bruce, 2004. “Paying for quality: providers’ incentives for quality improvement”, Health Affairs, Volume 23, pages 127-141.
- Ryan, Andrew M and Blustein, Jan, 2011. “The effect of the MassHealth hospital pay-for-performance program on quality”, Health Services Research, Volume 46, pages 712-72.
- Werner, Rachel M and Dudley, R Adams, 2012. “Medicare’s new hospital value-based purchasing program is likely to have only a small impact on hospital payments”, Health Affairs, Volume 31, Number 9, pages 1932-1940.
This policy brief summarizes common trends in the development of health care systems in the Czech Republic, Slovakia, and Russia in late 1990s–early 2000s. These countries focused on regulated competition between multiple health insurance companies. However, excessive regulation led to various deficiencies of the model. In particular, improvements in such quality indicators of the three health care systems as infant and under-five mortality are unrelated to the presence of multiple insurers or insurer competition.
A number of transition countries in Central and Eastern Europe and the former Soviet Union introduced health care systems with compulsory enrollment, obligatory insurance contributions unrelated to need and coverage according to a specified package of medical services. This so-called social health insurance (SHI) model (Culyer, 2005) is regarded as a means for achieving universal coverage, stable financial revenues, and consumer equity (Balabanova et al. 2012; Gordeev et al., 2011; Zweifel and Breyer, 2006; Preker et al., 2002). While most transition countries chose to only have a single health insurance provider on the market, the Czech Republic, Slovakia, and Russia allowed competitive (and often private) insurers in the new system. However, the evidence from the three countries shows excessive regulation of health insurers and limited instruments for insurer competition within indebted post-reform health care systems (Naigovzina and Filatov, 2010; Besstremyannaya, 2009; Medved et al., 2005). Consequently, the three countries may have been over-enthusiastic in putting large emphasis on market forces in the reorganization of health care systems in economies with a legacy of central planning (Diamond, 2002).
This brief addresses the results of Besstremyannaya (2010), which assesses the impact of private health insurance companies on the quality of health care system. While various performance measures reflect different goals of national and regional health care systems (Joumard et al., 2010; Propper and Wilson, 2006; OECD, 2004; WHO, 2000), aggregate health outcomes directly related to the quality of health care are commonly infant and under-five mortality (Lawson et al., 2012; Gottret and Schieber, 2006; Wagstaff and Claeson, 2004; Filmer and Pritchett, 1999). Consequently, Besstremyannaya’s (2010) analysis regards mortality indicators as variables reflecting the overall quality of health care system.
The estimations employ data on Russian regions in 2000-2006. The results indicate that regions with only private health insurers have lower infant and under-five mortality. However, given the low degree of competition on the social health insurance market in Russia, we hypothesize that this effect is mostly driven by positive institutional reforms in those regions. Indeed, incorporating the effect of institutional financial environment, we find that the impact of private health insurers becomes insignificant.
Development of a Social Health Insurance Model in the Czech Republic, Slovakia, and Russia
At the beginning of their economic transition, the Czech Republic, Slovakia, and Russia established a model for universal coverage of citizens by mandatory health insurance (Balabanova et al., 2012; Medved et al., 2005; Sheiman, 1991). The revenues of the new SHI system came from a special payroll tax and from government payments for health care provision to the non-working population. The main reason for combining certain features of taxation-based and insurance-based systems was the desire to establish mandatory health insurance as a reliable source of financing in an environment with unstable budgetary revenues (Lawson and Nemec, 2003; Preker et al., 2002; Sheiman, 1994). The insurance systems instituted in the three transition countries correspond to the major SHI principles implemented in Western Europe: contributions by beneficiaries according to their ability to pay; transparency in the flow of funds; and free access to care based on clinical need (Jacobs and Goddard, 2002).
The Czech Republic, Slovakia, and Russia placed emphasis on regulated competition, decreeing that SHI should be offered by multiple private insurance companies with a free choice of the insurer by consumers. Managers of private insurance companies were assumed to perform better than government executives (Lawson and Nemec, 2003; Sinuraya, 2000; Curtis et al., 1995), so an intermediary role for private insurance companies was seen as a key instrument for introducing market incentives and improving the quality of the health care system (Sheiman, 1991).
However, the activity of health insurance companies in the three countries was heavily regulated, since the content of benefit packages, size of subscriber contributions, and the methods of provider reimbursement were decided by government, and tariffs for health care were frequently revised (Lawson et al., 2012; Rokosova et al., 2005; Zaborovskaya et al., 2005; Praznovcova et al., 2003; Hussey and Anderson, 2003). In particular, Russian health care authorities enforced rigid assignments of areas, whose residents were to be served by a particular health insurance company (Twigg, 1999) and imposed informal agreements with health insurance companies to finance providers regardless of the quality and quantity of the health care (Blam and Kovalev, 2006). As a result, the three countries experienced an initial emergence of a large number of health insurance companies, followed by mergers between them, resulting in high market concentration (Sergeeva, 2006; Zaborovskaya et al., 2005; Medved et al., 2005).
In Russia, the Health Insurance Law (1991) specified that until private insurers appeared in a region, the regional SHI fund or its branches could play the role of insurance companies. Therefore, several types of SHI systems emerged in Russian regions in the 1990s and early 2000s: the regional SHI fund might be the only agent on the SHI market; the regional SHI fund might have branches, acting as insurance companies; SHI might be offered exclusively by private insurance companies; or SHI might be offered by both private insurance companies and branches of the regional SHI fund (Figure 1). The variety of SHI systems reflects the fact that many regions opposed market entry by private insurance companies (Twigg, 1999). Indeed, the boards of directors of regional SHI funds usually included regional government officials (Tompson, 2007; Tragakes and Lessof, 2003) who were reluctant to reduce government control over SHI financing sources (Blam and Kovalev, 2006; Twigg, 2001). The controversy with health insurance legislation created a substantial confusion at the regional and the municipal level (Danishevski et al., 2006).Figure 1. Health insurance agents in Russia in 2000-2006, (number of regions)
This context suggests that Russian regions provide an interesting study field to address the impact of private health insurance companies on the quality of health care system. In particular, the wide variety of SHI systems across Russian regions, as well as the gradual introduction of the health insurance model in Russia provide a sufficient degree of variation in practices and outcomes to allow for a well-specified empirical analysis.
Data and Results
In our analysis we use data on Russian regional economies between 2000 and 2006 (as based on data availability). Our measures of health outcomes are given by the pooled regional data on infant and under-five mortality. Our key explanatory variable is the presence of only private health insurers in the region. Arguably, the coexistence of public and private health insurance companies does not enable effective functioning of private health insurers owing to their discrimination by the territorial health insurance fund. Therefore, in the empirical estimations we focus on the presence of only private health insurers in the region, regarding it as a measure of effective health insurance model. The analysis also employs a variety of important socio-economic and geographic variables influencing health outcomes (per capita gross regional product (GRP), share of private and public health care expenditure in gross regional product, share of urban population, average temperature in January).
The results of the first set of our empirical estimations demonstrate that the presence of only private health insurers in a region leads to lower infant and under-five mortality. Furthermore, an increase in the share of private health care expenditure in GRP leads to a decrease in both mortality indicators. The result is consistent with numerous findings about the association between personal income and health status in Russia (Balabanova et al., 2012; Sparling, 2008).
Prospective reimbursement of health care providers is associated with a decrease in infant and under-five mortality. The finding suggests the existence of a quasi-insurance mechanism in the Russian SHI market. Operating in an institutional environment where provider reimbursement is based on prospective payment, private insurance companies in effect shift a part of their risk to providers (Glied, 2000; Sheiman, 1997; Chernichovsky et al., 1996).Table 1. Factors leading to decreased infant and under-five mortality in Russia
Although our analysis shows that the presence of only private health insurers is statistically associated with improvements in infant and under-five mortality, we believe that the influence is indirect. Namely, the overall positive institutional environment in the region may result in both a decrease of mortality indicators and a lower coercion of regional authorities towards the presence of private health insurance companies.
To test this hypothesis, we use financial risk in a region as a measure of institutional environment and incorporate it in the analysis through an instrumental variable approach. (We measure financial risk by an expertly determined rank ordered variable by RA expert rating agency; this variable reflects the balance of the budgets of enterprises and governments in the region, with lower ranks corresponding to smaller risk.)
In line with our hypothesis, the results suggest that the presence of private health insurance companies now becomes insignificant in explaining infant and under-five mortality.
The existing literature suggests that the improvement in infant and under-five mortality in the Czech Republic, Slovakia, and Russia can be attributed primarily to an increase of health care spending (Gordeev et al. 2011; Besstremyannaya, 2009; Lawson and Nemec, 2003) rather than being an effect of the social health insurance model with multiple competing insurers. It should be noted that insufficient government payments for the non-working population and a decline of the gross domestic product in the early transition years left SHI systems in the three countries indebted (Naigovzina and Filatov, 2010; Sheiman, 2006; Medved et al., 2005), which undermined the development of the managed competition in the health care provision.
In Russia (and also in the Czech Republic and Slovakia) there is little competition between insurers, and surveys show that the main factors causing consumers to change their health insurance company are change of work or residence, and not dissatisfaction with the insurer (Baranov and Sklyar, 2009). The fact that law suits on defense of SHI patient rights are rarely submitted to courts through health insurers (Federal Mandatory Health Insurance Fund, 2005) may also be evidence of the failure of Russian health insurance companies to win customers on the basis of their competitive strengths.
Summary and Policy Implications
The above findings as well as the other mentioned literature suggest that improvements of infant and under-five mortality in the Czech Republic, Slovakia, and Russia are not associated with the positive role of managed competition in the social health insurance system. In particular, in Russia the decrease in infant and under-five mortality is likely to be related to financial environment, rather than the existence of insurance mechanisms or competition between health insurance companies. One possible explanation of this absence of effect may come from the excessive regulation of the private insurance markets, as well as the insufficient competition between insurers. Importantly, the health insurance reform, implemented in Russia in 2010, both addressed underfinancing (by raising payroll tax rates) and took a step towards fostering provider competition, by allowing private providers to enter the social health insurance market (Besstremyannaya 2013). However, insurance companies are still not endowed with effective instruments for encouraging quality by providers, which may greatly undermine their efficiency.
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