Study on the Effects of the Deregulation of Drug Price Control on

Orphan Drug Price: Empirical Study with Big Data on Drug Price

Data of 16 Provinces in China

Zeyu Zhang and Ying Bian

Institute of Chinese Medicine, University of Macau-State Key Laboratory of Quality Research in Chinese Medicine, Macau

999078, China

Keywords: Orphan Drugs, Price Difference, Drug Price, Big Data.

Abstract: Objective: To analyze the price changes of orphan drugs before and after the reform. To explore the impact of

the abolition of drug price control and market liberalization on the price of orphan drugs. And to provide

reference for the formulation of policies related to orphan drugs. Method: We used drug price data monitored

by Beijing Municipal Bureau of Health from February 2014 to June 2017. 32 kinds of 12222 orphan drug

data were extracted. Based on the interrupt time-series model and the accumulation of drug price differences

frequency, this research analyzes and compares the price level of orphan drug before and after the

deregulation. And the impact of reform on the price of orphan drugs were put forward. Results: After the

deregulation, the orphan drug price level increased significantly (slope change amount β

=3.45×10

-1

, P <0.05).

In 2014, 1.77% of the orphan drugs were at high price differences, and 1.22% in 2015, compared with 2.57%

in 2016 and 4.25% in 2017. Conclusion: After the deregulation, the Laspeyres index level of orphan drugs

increased significantly, and the situation of high price differences drug became more serious. It is difficult to

improve the accessibility of orphan drugs by market-oriented control measures alone. A better pricing

mechanism needs to be introduced to protect the rights and interests of patients with rare diseases.

1 INTRODUCTION

The accessibility and affordability of drugs are the

important attributes of drugs, and the drug price is of

great significance for drug accessibility and

affordability. Drug prices have always been one of the

focus of medical and health undertakings. In recent

years, China's drug expenses account for about 40%

of the total health expenditure of (https

://www.who.int/medicines/publications/pharm_guid

e_country_price_policy/en/.), which is at a high level

compared with developed countries. Statistics from

the Organization for Economic Cooperation and

Development (OECD) (https://data.oecd.org/

healthres/ pharmaceutical-spending.html) show that

the drug costs of most developed countries remain at

10% to 20% or less. Therefore, reasonable regulation

of drug prices is very important to relieve the

economic burden of individuals and even the country.

Government intervention is one of the main

means of drug price control, the (Huang, 2005;

Technology Information, 1997; China

Pharmaceuticals, 1999). However, the drug price

control system did not achieve the expected effect,

but induced some adverse phenomena, such as high

price differences (Shen, 2014), "Hu Piao effect"

(Ruan, 2008) caused by drug manufacturers avoiding

price reduction, excessive competition (Shi, 2014)

manifested in anti-price competition. There is also the

"exit effect" (Zhu, 2005), which makes too low prices

drugs gradually disappear from the prescription.

In the case of the chronic failure of China's drug

price control measures, on May 4, 2015, the National

Development and Reform Commission, the Health

and Family Planning Commission, the Food and Drug

Administration and other departments issued the

Opinions on Promoting the Drug Price Reform (F R

ANCO, 2013). Since June 1, 2015, in addition to

anesthetic drugs and type I psychotropic drugs, the

regulation of drug price has been canceled, and the

actual sales price of drugs has been formed by market

competition, marking the prelude to a new round of

drug price reform.

Zhang, Z. and Bian, Y.

Study on the Effects of the Deregulation of Drug Price Control on Orphan Drug Price: Empirical Study with Big Data on Drug Price Data of 16 Provinces in China.

DOI: 10.5220/0012019900003633

In Proceedings of the 4th International Conference on Biotechnology and Biomedicine (ICBB 2022), pages 285-289

ISBN: 978-989-758-637-8

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

285

Rare disease, also known as an orphan disease.

The definition of rare diseases is not unified around

the world, mainly with low prevalence, very low total

population, life-threatening, difficult treatment, low

enthusiasm for drug development and high treatment

cost of (F R ANCO, 2013). Orphan drugs are drug for

rare diseases, refer to the drug (Liu, 2019) used in the

treatment, diagnosis, or prevention of specific rare

diseases.

On May 11,2018, the National Health

Commission, the National Drug Administration and

other five departments jointly formulated China's

First Batch of Rare Diseases List, clearly listing 121

rare diseases, aiming at safeguarding the health rights

and interests of patients with rare diseases, which is a

milestone in the management of rare diseases in

China. However, there are few studies on the drug

price of rare diseases in China. China's population

base is large, and although the incidence of rare

diseases is low, its patient population still cannot be

ignored. This study is based on the drug price data

from 16 provinces from 2014 to 2017. It aims to

analyze the price changes of orphan drugs before and

after the reform, explore the impact of abolishing

price control and market liberalization on the price of

orphan drugs, and provide a basis for the policy

formulation related to orphan drugs.

2 DATA AND METHODS

2.1 Data Sources

The research data originated from the national drug

price monitoring data of the Beijing Municipal

Bureau of Health from February 2014 to June2017,

and the cooperative research institution is the Peking

University School of Pharmaceutical Sciences. In this

study, 32 kinds of 12222 orphan drug data from 16

provinces including Gansu, Shandong, Heilongjiang,

Shanghai, Jiangsu, Zhejiang, Hubei, Jilin, Liaoning,

Inner Mongolia, Ningxia, Shandong, Shanxi,

Sichuan, Yunnan and Chongqing were selected. The

types of orphan drugs refer to the research of Liu Xin

(Liu, 2019) on the status quo of orphan drugs in

China. The drug data include the general name,

specification, production unit, monitoring unit, sales

volume, price and other data.

2.2 Data Analysis

This study used daily dose (DDD) as the unit of

measurement to compare drugs of different

manufacturers, dosage forms and specifications, with

the total DDDs of each drug as the amount of drugs

every two months. The DDD data for the drugs were

obtained from the WHO Collaborating Centre for

Drug Statistics Methodology

(https://www.whocc.no/).

2.3 Drug Price Differences

The drug price differences is the ratio of the

difference between the actual retail price and the

factory price and the factory price, and its expression

is as follows:

Price Diference cs





Actual retail price − factory price

factory price

×100%

According to Shen Hongtao's research (Shen,

2014) on drug price structure in many countries, he

proposed that the factory price of less than or equal to

50% retail price is unreasonable, that is, the drug price

is artificially high. More than 50% of the average

evaluation price ratio is relatively reasonable, that is,

the drug price is not artificially high. Therefore, drugs

with a price differences above 100% were high price

difference drug.

2.4 Laspeyres Index

Laspeyres index can measure the overall price level

of a drug (Ye, 2016), that is, keep the weight of each

drug unchanged, and compare the drug price level

after the calculated period with the drug price of the

base period. Collect drug prices for the calculated and

base periods (P

, P

) and Basal usage (Q

). The

Laspeyres index was calculated using the following

formula:

𝐿=

∑

𝑃



𝑄



∑

𝑃



𝑄



In this study, the drug price data from February

2014 was used as the base period data to calculate the

pull price index of each period.

2.5 Interrupt Time Series Model

Interrupt time-series (ITS) design is designed to

collect outcome data from multiple time points before

and after the intervention, and evaluate the effect of

the intervention with statistical models, including

level changes and trend changes, which is mostly

used to evaluate policy (Shao, 2015). Its nature is a

linear regression (Lagarde, 2011) for a piecewise fit.

Set up X

For the time variable of the count, X

＝

1,2,3,…,n; X

Represents the intervention, and the

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286

pre-intervention X

=0. After the intervention X

＝1;

Represents the slope, and set X

=0 represents the

pre-intervention observations, X

Represents the

observations after the intervention, and εt is a random

error term. The fit level and slope change models

were performed as follows:

＝β

+β

+∑β

+εt, ∑β

Represents a set of covariates which is not considered

here. Generation the variables X

, X

, and X

into the

formula, the pre-intervention model is: Y

＝β

+β

εt; The post-intervention model is: Y

=β

+β

+εt =β

+β

×1+β

+εt

=(β

+β

)+(β

+β

+εt =β

+β

+ t; β

and β

are

Called adjust parameters. β

is the slope of pre-

intervention, β

is the amount of horizontal change, β

is the amount of slope change, (β

+β

) Is the slope

after the intervention. The hypothesis test of the

regression coefficient is the significance test of

horizontal change and slope change. The interrupt

point of this study was in June 2015. Analysis using

the Durbin-Watson test found that there was

autocorrelation in the pre-intervention regression

equation. Use generalized least-squares estimation to

solve the first-order autocorrelation bias (Shao,

2015).

SPSS 25.0 statistical analysis software was used,

and P <0.05 was set to indicate statistical significance.

3 RESULT

3.1 The Impact of Deregulation on the

Price Level of Orphan Drugs

A total of 32 orphan drugs were included in this study,

including 12,222 drug price data. Take the time as the

horizontal coordinate and take the fixed Roche price

index as the ordinate. Fig. 1 shows the impact of the

deregulation on the overall price of orphan drugs.

Figure 1: Effect of drug price deregulation on orphan drugs prices.

The slope (β

) of the orphan drug price index

before the deregulation is 0.006. The level change

after the deregulation is -0.394 and the amount of

slope change is 0.345 (P <0.05). The difference before

and after was significant, indicating that the price

level of orphan drugs increased significantly after the

deregulation.

3.2 Drug Price Differences Before and

After the Deregulation

The drug price increase rate was taken as the abscissa,

and the cumulative frequency was taken as the

ordinate for drawing.

In Fig. 2, when the drug price differences was at

the highest price increase rate set by the government,

the cumulative frequency curve increased almost

vertical. After more than 15%, the growth rate slowed

down, and the price differences of most drugs was

0.8

0.9

1.1

1.2

1.3

1.4

1.5

1.6

2014 2015 2016 2017

Laspeyres index

Year

Study on the Effects of the Deregulation of Drug Price Control on Orphan Drug Price: Empirical Study with Big Data on Drug Price Data of

16 Provinces in China

287

Figure 2: Cumulative frequency of orphan drug price increase rate from 2014 to 2017.

within 100%. In 2014,1.77% were high-priced drugs,

1.22% were high prices in 2015, compared with

2.57% in 2016 and 4.25% in 2017.

4 DISCUSSION

4.1 The Effect of Drug Price Control

Policy Reform Has Both

Advantages and Disadvantages

Fig. 1 results show that after the deregulation, the

price level of orphan drug rose significantly, and the

Laspeyres index rose sharply in 2017. Combined with

the results of Fig. 2, in 2016 and 2017, when the price

control was abolished, the proportion of high price

difference drugs increased year by year, indicating

that the problem of the inflated price of orphan drugs

is becoming more and more prominent, and the role

of the completely competitive market in leading the

price change is not obvious. Yang mingchun (Yang,

2018) believes that after the abolition of control, in

order to see from the production period, the drug price

will generally increase by in order to gain more

benefits. Through empirical research, Jiang Zaiduo

(Jiang, 2016) found that the drug price was still

inflated and the existed after the policy reform. This

study confirms these two conclusions that the

abolition of government pricing can not curb the

problem of inflated drug prices.

As can be seen in the previous section of the chart,

the proportion of drugs with low price differences in

2016 and 2017 also increased significantly, which has

certain benefits to its own sustainable development.

The regulation of the "zero margin" of essential drugs

is too extreme. In the absence of government health

spending, zero margin blocks hospitals' income when

using essential drugs, but causes medical institutions

to try to circumvent price controls. The same is true

for low-priced drugs in orphan drugs. The reform is

of great significance to the price rise of low-priced

drugs. Most low-priced drugs are still low-priced

drugs after experiencing price increases. The price

increase effectively alleviates the "dead standard"

situation of some low-priced drugs, guarantees the

supply of low-priced drugs, protects the interests of

low-priced drug manufacturers, and enables the

market to develop (Wang, 2020) healthily. At the

same time, for patients with rare diseases, the

accessibility of low-cost orphan drugs can also be

guaranteed to reduce the economic pressure of

patients.

4.2 The Effect of Policy Reform Still

Needs to Be Long-Term Evaluation

The reform of government pricing is aimed to

establish a market-led price formation mechanism.

Considering the operation of the market and the lag

of the reform and the emergence of volume

procurement policy, the subsequent effect remains to

be further observed.

4.3 The Letter of Drug Price

Formation Mechanism Needs to Be

Improved

The previous drug price customization mechanism is

defective, and the laws and regulations are also

0.2

0.4

0.6

0.8

0 0.2 0.4 0.8 1 1.2

Cumulative frequency

0.6

Drug price differences

2014

2015

2016

2017

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imperfect. Due to policy support and monopoly, there

is an unreasonable price gap between patented drugs

and generic drugs, while products with significantly

better quality and efficacy are allowed to be priced

separately. However, due to the differences in

manufacturers, brands, and geographical location, the

price difference between the same drugs is also very

large (Ruan, 2008). At the same time, the government

pricing of drugs is mainly the cost price increase, and

the lack of consideration of the circulation cost is also

one of the reasons for the inflated price of (Liu, 2006).

China's population base is large, and although the

incidence of rare diseases is low, its patient

population still cannot be ignored. Orphan drugs are

very important in the treatment of rare diseases, so the

price change and inflated price of orphan drugs

should be paid more attention. At present our orphan

drug accessibility is compared with developed

countries still has a certain gap (Liu, 2019), for

orphan drugs and all the long-term benign

development of drug prices, suggest a more perfect

pricing mechanism, medical and health undertakings,

pharmaceutical enterprises, medical institutions,

patients and other interests, fully consider drugs in

addition to the production cost of circulation, storage,

and sales costs, to achieve a more reasonable balance.

5 CONCLUSION

After the abolition of drug government pricing, the

Laspeyres index of orphan drugs increased

significantly, and the inflated price of drug became

more and more serious. The proportion of drugs with

high price increase rate increased from 1.77% in 2014

to 4.25% in 2017. It is difficult to improve the

accessibility of orphan drugs by market-oriented

control measures alone, and a better pricing

mechanism needs to be introduced to protect the

rights and interests of patients with rare diseases.

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Study on the Effects of the Deregulation of Drug Price Control on Orphan Drug Price: Empirical Study with Big Data on Drug Price Data of

16 Provinces in China

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