Big Data and Pharmacovigilance: Using Health Information Exchanges to Revolutionize Drug Safety

• Author: Ryan Abbott
• Position: Associate Professor, Southwestern Law School & Visiting Assistant Professor, David Geffen School of Medicine at University of California, Los Angeles
• Pages: 225-292

Big Data and Pharmacovigilance:

Using Health Information Exchanges to

Revolutionize Drug Safety

Ryan Abbott∗

ABSTRACT: Data on individual p atients collected through state and

federal health information excha nges has the potential to usher in a new era

of drug regulation. These exchanges, prod uced by recent health care reform

legislation, will amass an unprecedented amount of clinical information on

drug usage, demographic variables, a nd patient outcomes. This informatio n

could aid the Food and Drug Administration (“FDA”) with post-market

drug surveillance because it more accurately reflects clinical p ractice

outcomes than the trials the FDA relies upon for dr ug approval. However,

even with this data available, the m arket-driven impetus to use it to polic e

drugs is weak. This is fixable; the p ost-market drug regulatory process needs

new incentives to boost third party participation. While a variety of

mechanisms could achieve this , the best option for generat ing robust results

may be an administrative bounty proceed ing that will allow third parties to

submit evidence to the FDA to contest th e claimed safety and efficacy profiles

of drugs already on the market. This Article uses a case study of Merck’s

former blockbuster drug Vioxx to demonstrate how this system might wo rk.

In creating a new incentive that co unters the powerful financial motivation

of drug manufacturers to obscu re or misrepresent safety profiles , the proposed

bounty proceeding could lead to an impro ved balance of the risks and

benefits of drugs used by the American public. More broadly , this Article

illustrates how to create an in centive for the private sector t o supplement

regulatory activity in a complex field .

∗ Associate Professor, Southwestern Law School & Visiting Assistant Professor, David

Geffen School of Medicine at University of California, Los Angeles. M.D., University of

California, San Diego School of Medicine, 2011; J.D., Yale Law School, 2011; M.T.O.M.,

Emperor’s College, 2005; B.S., University of California, Los Angeles, 2005. Thanks to Ian Ayres,

Einer Elhauge, Barbara Evans, Jennifer Herbst, Carissa Hessick, Bonnie Kaplan, Reichi Lee,

Arthur McEvoy, Eric Orts, Jerome Reichman, William Sage, Mark Seidenfeld, Elizabeth Sepper,

and Sean Williams for their thoughtful reviews. Thanks also to Anna Aran and Danielle Doumar

for their excellent research assistance.

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226 IOWA LAW REVIEW [Vol. 99:225

I. INTRODUCTION .................................................................................... 227

A. POST-MARKET REGULATION OF DRUGS AND MEDICAL DEVICES .......... 231

1. Drug Regulation and Post-Market Assessment .................... 231

2. Randomized Control Trials Versus Observational

Studies ................................................................................... 233

3. Existing Resources in Pharmacovigilance............................ 237

4. Regulatory Shortcomings ..................................................... 240

B. THE STRUGGLE FOR ACCEPTANCE .................................................... 247

1. Health Information Technology and Health

Information Exchange ......................................................... 247

2. The Government Steps In: The HITECH Act and the

Affordable Care Act .............................................................. 251

3. Establishing Health Information Exchanges ....................... 252

II. THE FDA, PRODUCT SPONSORS, AND THIRD PARTIES .......................... 253

A. USING HIES TO POWER PHARMACOVIGILANCE .................................. 253

B. GOVERNMENT AGENCIES ................................................................. 256

C. PRODUCT SPONSORS ....................................................................... 257

D. THIRD PARTIES .............................................................................. 259

E. NEW USES AND NEW USE PATENTS ................................................... 263

F. IN SEARCH OF NEW INCENTIVES—LOOKING TO QUI TAM

LITIGATION ................................................................................... 266

G. MODELING A BOUNTY PROCEEDING AFTER AN FCA QUI TAM

ACTION ......................................................................................... 269

1. Standing and Settlement ...................................................... 270

2. Venue .................................................................................... 273

H. PAYING FOR A BOUNTY PROCEEDING ................................................ 276

I. COST BEARERS ............................................................................... 279

J. THE CHALLENGES OF CREATING A NEW INDUSTRY ............................ 282

K. A VIOXX HYPOTHETICAL ................................................................. 285

III. CONCLUDING THOUGHTS .................................................................... 291

2013] BIG DATA AND PHARMACOVIGILANCE 227

I. INTRODUCTION

Every day 2.5 quintillion bytes of data are created—so much that 90

percent of the world’s data has been produced in the last two years alone.1

This information revolution is transforming education, labor markets, and

social relationships, and is creating entirely new industries.2 Some of the

greatest advances have and will come in biotechnology and bioinformatics,

where “big data” is altering new drug development, clinical practices, and

health care financing.3 It also has the potential to lead to a new kind of

understanding of how drugs work in the real world. In 1991, the Food and

Drug Administration (“FDA”) based its approval of the cholesterol-lowering

drug simvastatin on pre-market controlled clinical studies that included a

total of 2423 patients.4 In 2011 alone, health care providers, just in the

United States, wrote almost a hundred m illion prescriptions for the drug.5

Imagine the impact of being able to analyze data from every one of those

patients to evaluate whether simvastatin is safe and effective. Better yet,

imagine analyzing data from every patient who has ever taken the drug in

every country in the world. That is the vision of a drug regulatory system

powered by big data. Historically, that type of research has been

unachievable. But now, for the first time in human history, it is a possibility.

However, it remains just that—a possibility. Although a vision for a new

type of post-market regulatory system exists, a plan does not. If the vision is

to come to fruition, policymakers must address some operational challenges.

First, the right kinds of data will need to be collected. Second, researchers

have to aggregate the raw data in order to analyze it more easily. Third, the

aggregated data will need to be effectively plugged into the regulatory

process. Unfortunately, because an industry motivated by profit rather than

patient outcomes dominates our current post-market drug regulatory

system, it is not structured to meaningfully use such data. While another

stakeholder in the process—the FDA—has a different set of motivations and

political pressures, the agency lacks the resources, information, and

entrepreneurial drive of the 1.1 trillion-dollar-a-year private industry it

1. Bringing Big Data to the Enterprise, IBM, http://www-01.ibm.com/software/ph/data/

bigdata/ (last visited Sept. 20, 201 3).

2. Peter F. Drucker, Beyond the Information Revolution, ATLANTIC (Oct. 1, 1999, 12:00 PM),

http://www.theatlantic.com/magazine/archive/1999/10/beyond-the-information-revolution/

304658/.

3. See Ryan Abbott, Overcoming Barriers to a Global Treaty on Medical Funding and R&D, 7

REVISTA ELETRÔNICA DO IBPI [J. BRAZILIAN INST. FOR INTELL. PROP.] 70 (2012) (Braz.).

4. MERCK SHARP & DOHME LTD., MERCK & CO., INC., HIGHLIGHTS OF PRESC RIBING

INFORMATION: ZOCOR (SIMVASTATIN ) TABLETS 7 (2010), available at http://www.accessdata.fda.gov/

drugsatfda_docs/label/2010/ 019766s078lbl.pdf.

5. IMS INST. FOR HEALTHCARE INFORMATICS, THE USE OF MEDICIN ES IN THE UNITED

STATES: REVIEW OF 2011, at 38 (2012), available at http://www.imshealth.com/ims/Global/

Content/Insights/IMS%20Institute%20for%20Healthcare%20Informatics/IHII_Medicines_in

_U.S_Report_2011.pdf.