In China, the majority of hospitals, particularly public hospitals, have to adhere to very strict price regulations. Hospitals must follow government-specified price regulation standards while pricing their medical services and drugs. The purpose of price regulation is to maintain fairness in access to medical services by reducing the price of basic medical services, usually below the marginal cost [1]. In compensation, subsidies and tax incentives are provided by the government, and barriers to entry in the medical market are also backed by government. However, government subsidies to public hospitals have been gradually decreased after the medical marketization reform, accounting for less than 10% of the medical revenue of hospitals. Public hospitals have to set high prices for other services to maintain a reasonable level of revenue, especially drugs and high-tech diagnostic test, such as CT and MRI scans [1, 2]. Therefore, the distorted incentive mechanism caused by price regulation may undermine the efficiency and fairness of medical system. Price regulation has long been criticized for excessive medical treatment in China [2–4].
price regulation distorts the signaling role played by price in resource allocation. Due to the presence of relatively serious information asymmetry in the medical service market, price regulation will lead to excessive medical treatment. Since Pricing and payment is predominantly on a FFS (fee-for-service) basis, hospitals and doctors tend to avoid the price regulation of medical services by drug overusing and over-checking [5–7]. For example, after the implementation of the Zero Markup Drug Policy, hospitals and pharmaceutical companies conspired to increase drug prices and deny the market to low-price drugs. When the government controls the drug expenditure proportion, hospitals compensate for this decline in proportion by increasing their diagnostic test expenditure [8–12].
When the prices of most of the basic medical services and drugs are regulated, hospitals achieve their profits mainly by inducing demand and doctors play a significant role in this process of inducing demand [13–20]. As multitasking agents, doctors are often simultaneously entrusted various tasks by both hospitals and patients. As the patients’ agent, a doctor's task is to provide the patients with professional medical services and maximize their benefit in the diagnosis process. Further, as the hospital’s agent, a doctor must not only provide diagnoses for patients but also generate income for the hospital and satisfy other assessment indicators of the hospital. However, while acting as agents, doctors may feel conflicted when their personal interests contradict patients’ interests [21–25]. For example, Lu [26] pointed out that when offered economic incentives, doctors might deviate from their agent obligations and use information advantages to induce patients with a strong ability to pay to pay for more medical services to maximize their personal interest. On encountering price regulation, such as a reduction in the proportion of drug expenditure, doctors increase the non-drug expenditure, rather than reducing the drug expenditure, of patients. Although this action does not alleviate the financial burden on patients, it distorts, to a certain extent, the expenditure structure and reduces the welfare of patients [1, 9]. Since doctors have information advantage and hospitals monopolize the medical services market, price regulation cannot improve patients’ welfare without changing the advantageous position of hospitals and doctors.
Since the implementation of the new healthcare reform in 2009, the government has been introducing several measures to reform the medical service market, such as encouraging the access of private hospitals and relaxing the price controls on some hospitals [27–30]. Some public hospitals restructured to private hospitals, and a large number of new private hospitals entered the medical market. Before 2013, the government had different pricing policies for these private hospitals: Whereas the pricing of medical services was unregulated for private for-profit hospitals, private nonprofit hospitals implemented government-guided pricing. That is, the pricing of private nonprofit hospitals, most of them reformed from public hospitals, was subject to price regulation policies, similar to that of public hospitals. In September 2013, the State Council issued a policy that explicitly required the deregulation of the pricing of medical services by nonpublic hospitals, which aimed to promote the supply of diverse medical services. The series of reforms implemented under the aforementioned policy ensures that both for-profit and nonprofit private hospitals in China abolish price regulation and perform independent pricing. Since the cancellation of the price regulation of private nonprofit hospitals by the government, all private hospitals have been implementing market pricing, whereas all public hospitals have been continuing to implement the government’s price regulation. This ensures a perfect policy environment to examine the impact of price regulation on hospital behavior and patients’ medical expenditure.
Table 1
Government’s price regulation policies for medical services in China
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Pricing before 2014
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Pricing after 2014
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Government-run hospitals (public hospitals)
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Government guided
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Government guided
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private
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Nonprofit
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Government guided
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Market independent
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For-profit
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Market independent
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Market independent
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Although the literature provides clear theoretical analyses of the effects of price regulation [14, 31], it offers limited evidence to support these inferences. This study attempts to overcome the aforementioned research gap and empirically examine the impact of medical services pricing deregulation on patients’ welfare and expenditure. For this purpose, we establish a DID model to compare the changes in inpatients’ medical expenditure and expenditure structure in private nonprofit hospitals before and after price deregulation, keeping public hospitals as the control group. Further, to clarify the influence of market competitiveness on hospital decision-making and perform robustness evaluation, we use data pertaining to the differences in competitiveness among hospitals.
The paper comprises four parts: In the first part, we discuss relevant data and variables, and, in the second, we describe the study’s setting and establish a DID model to test the impact of deregulation on patients’ medical expenditure. The third part presents the empirical study, for which we mainly use patient-level expenditure data to analyze the behaviors of over medical treatment. Finally, the fourth part depicts the implications of the study’s findings and presents the study’s conclusions.
Data
Data sources
In this study, we used the claim data of insured inpatients residing in a major Chinese city for the period 2010–2015. The data included variables such as the expenditure for each inpatient visit, length of hospital stay, age, gender, and ICD code (International Classification of Diseases code). These data were the real-time recording of insured patients and accurately record the expenditure, occurrence time, and patient outcomes during the period of hospitalization. In the regression analysis performed in this study, to reduce the impact of rare diseases on regression results, we excluded the diseases for which the total number of patients is less than 500. Further, we mainly examined the changes in inpatient expenditure and expenditure structure before and after the implementation of price regulation. The patients who were treated in private nonprofit secondary hospitals formed our experimental group, whereas those treated in public nonprofit secondary hospitals that were subject to price regulation before and after the policy change formed the control group. To avoid the impact of rank evaluation of hospitals, we excluded the hospitals that were rated as tertiary hospitals during the study period. Further, since some private hospitals were not appointed hospitals offering medical insurance, only 14 private nonprofit secondary hospitals were included in the data analysis. Moreover, two hospitals were excluded because they were rated as tertiary hospitals in 2015. Finally, the experimental group included 12 secondary hospitals and 40,411 patient samples. The total patient sample is 250,270.
Variables
This study focused on the total and itemized expenditures of inpatients per hospital visit, such as diagnostic test, drug, and physician service expenditure. Further, we examined the expenditure structure, such as the proportions of diagnostic test expenditure and drug expenditure. To reduce statistical bias, we removed the samples whose total expenditure was missing or 0. Moreover, regarding patient characteristics, the study mainly considered age and gender. Gender was represented using a dummy variable, whose values were 1 for male patients and 0 for female patients. In addition, to ensure the comparability of expenditures, we controlled the diagnostic ICD code of inpatients, that is, the main diagnosis results of patients in a hospital. To exclude the influence of extreme values, we deleted the samples who were more than80 years old or who stayed more than 200 days in a hospital.