Sorrell V. IMS Health, Inc., Supreme Court Ruling on Pharmaceutical Data Mining Fuels Continuing Debate

By Daniel, Lara; Kemp, Katie | Journal of Legal, Ethical and Regulatory Issues, January 2015 | Go to article overview

Sorrell V. IMS Health, Inc., Supreme Court Ruling on Pharmaceutical Data Mining Fuels Continuing Debate


Daniel, Lara, Kemp, Katie, Journal of Legal, Ethical and Regulatory Issues


INTRODUCTION

A recent United States Supreme Court ruling protecting the use of data mined information as a guide in developing promotional strategies in the pharmaceutical industry positively impacts all business organizations using similar data collection and analysis. The purpose of this paper is to examine the use of data mining in the pharmaceutical industry, review its criticism, describe the Supreme Court decision, and assess the impact of the Court's holding.

In Sorrell v. IMS Health, Inc. (2011) a data mining health information company won its constitutional challenge of a Vermont statute that restricted the sale and use of data mined information. The Supreme Court held that such information was protected by the First Amendment and invalidated the statute as an infringement of free speech. There are those who see this outcome as an erosion of the privacy interests that might be advanced by keeping that information confidential (Huhn 2011), but the ruling is a victory for any business wishing to gain access to information that will facilitate their commercial transactions (Denniston 2011). Some legal commentators opine that Sorrell represents a new era of protection for commercial speech (Outterson 2011). Although there are differing views of that proposition, there is no doubt that the ruling positively impacts any business that uses information about consumer buying behavior to guide its marketing and sales strategies.

RELEVANT MARKETING LITERATURE

Data mining involves utilizing electronic methods for distilling meaningful information, trends and predictions from large volumes of data collected for some other purpose. The concept has been defined as "the process of secondary analysis of large databases aimed at finding unsuspected relationships that are of interest or value to the database owners" (Klosgen and Zytkow 2002, p. 637). From a marketing perspective, the patterns discovered in the data have value because they can impact the bottom line of a business (Peacock 1998). The end result is new insights and knowledge discovery (Fiske 2002). Businesses either generate their own information from data mining or purchase the gleaned information in order to improve marketing planning and decision making.

As described by Rafalski (2002), the process of data mining begins with "trend analysis and the search for patterns in the underlying data. Once a pattern of interest is identified, statistical analysis is applied to determine whether the pattern is significant. If it is found to be of significance, root cause analysis is applied to determine the cause of the trend" (p. 609). Tools utilized include query tools, descriptive statistics, visualization tools, regression-type models, association rules, decision trees, case-based reasoning, neural networks and genetic algorithms (Peacock 1998).

Data Mining in the Pharmaceutical Industry

This paper focuses on data mining doctors' prescription data which is purchased from participating pharmacies by health information companies such as IMS Health, SDI Health (formerly known as Verispan), and Source Healthcare Analytics (Information Management 2011). The channel of distribution in the pharmaceutical industry is unique in that the intended user of a product cannot access it without a physician, a middleman whose involvement is mandated by law. The original data is generated when a prescription is filled by a patient; the name, dose, and quantity of the drug is collected along with the date of the prescription and the physician's name. The patient's name is not retrieved. The data miner, however, assigns a specific number to the patient for tracking future prescriptions to permit analysis of the patient's prescription history (Orentlicher 2010). In 2007 IMS was reported to have obtained records on over two thirds of prescriptions filled in community pharmacies (Fugh-Berman 2007). Some pharmacies, e.g., WalMart, do not sell their prescription records (Pharmaceutical Sales Jobs 2012). …

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