The Effect of Unannounced Inspection on Prevention of Drug Fraud

Manman Zhang, Juliang Zhang, T. C.E. Cheng, Guowei Hua, Xiaojie Yan, Yi Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Alarge number of incidents related to fake/inferior-quality drugs have occurred in China in recent years. In order to reduce drug crimes, the China Food and Drug Administration (CFDA) has exploited the new supervision approach, i.e., unannounced inspection (UI), since September 2014. However, the effectiveness of UI in driving drug producers to put more effort into meeting the requirements of Good Manufacturing Practice (GMP) is yet to be ascertained. In this paper we apply game theory to study the effects of UI on the prevention of drug fraud, drug producers’ profits, and social welfare under scenarios of complete and incomplete information. We show that UI is not always an effective way of supervision. Specifically, if the upper bound on the punishment is not very large, UI can drive the firmto make the largest self-supervision effort only when the firm’s technical level is high and the supervision cost is low. Otherwise, UI cannot drive the firm to make the largest self-supervision effort. Under incomplete information, firms with a high technical level would adopt more self-supervision and make more profit than those with a low technical level. Moreover, we design a new mechanism under incomplete information that can incentive drug producers to make greater self-supervision effort to meet the requirements of GMP under certain conditions.

Original languageEnglish
Pages (from-to)63-90
Number of pages28
JournalJournal of Systems Science and Systems Engineering
Volume28
Issue number1
DOIs
Publication statusPublished - 1 Feb 2019

Keywords

  • Drug supervision
  • game theory
  • healthcare system
  • incomplete information
  • mechanism design
  • Nash equilibrium

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems

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