Pharmacovigilance database

Details Pharmacovigilance database Pharmacovigilance database

2001-05-02

2004-08-17

Robinson, Greta (Department: 2171)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000, C704S010000

Reexamination Certificate

active

06778994

ABSTRACT:

BACKGROUND OF INVENTION
1. Field of the Invention
The present invention relates generally to systems and methods for developing a pharmacovigilance database from source data, both publicly available and privately developed, and reference data.
2. Description of the Related Art
In September 1997, information regarding cardiopulmonary disease related to the use of fenfluramine and phentermine (“fen-phen”) prompted the United States Food and Drug Administration (FDA) to request the manufacturers of these drugs to voluntarily withdraw both treatments for obesity from the market. Subsequent studies show a 25 percent incidence of heart valve disease apparently resulting from diet drug use. Thus, up to 1,250,000 people may have sustained heart valve damage from these diet drugs and the FDA indicates that this may be the largest adverse drug effect they have ever dealt with.
Under existing federal regulations, post-marketing safety reports are be submitted to the FDA for serious and unexpected adverse experiences from all sources (domestic and foreign); and spontaneously reported adverse experiences that occur domestically and that are: serious and expected; or non-serious and unexpected; or non-serious and expected.
To facilitate reporting and data analysis, the FDA created the Spontaneous Reporting System (SRS), a pharmacovigilance database. The SRS contains adverse drug reaction reports from a variety of sources over a period covering 1969 through 1997. This data is available in an ASCII flat file from the FDA. However, the flat file, by its nature is not a relationally structured database amenable to typical query.
Over the past several years (1997 2001), the FDA has implemented a follow-on system to SRS, i.e., the Adverse Event Reporting System (AERS). AERS is a non-cumulative database of post-market drug adverse events. Its purpose is to serve as an early warning indicator or signaling system for adverse drug reactions not detected during pre-market testing. The data, without a search engine, is available on CD ROM from the federal government in a combination of ASCII delimited flat file and SGML format. The files include: demographic and administrative information; along with drug, reaction, patient outcome, and source for each case.
Beyond SRS and AERS, pharmaceutical companies, hospitals, and other entities have also been known to track adverse drug effects; often using unique database structures. The existence of these various databases using different structures presents an obstacle to efficient use of potentially valuable data. As with SRS and AERS, database structure can vary within an organization over time, and also between concurrent adverse event databases. Such variability makes it cumbersome to query across databases.
In addition, differing terminology employed by disparate databases also make conventional queries cumbersome and the results unreliable. This problem is acute in the area of medical information related to substances such as drugs. Drugs and other prescription and non-prescription therapeutic substances may be known by a variety of names. In addition to the chemical name, many drugs have several clinical names recognized by health care professionals in the field. It is not uncommon for a drug to have several different trade names depending on the manufacturer. This matter is further complicated by one or more functional names that may be associated with a drug or other substance. For example, an antidepressant may be Prozac, a fluoxetine, a serotonin reuptake inhibitor, or a serotonin receptor specific modulator. However, antidepressants include many other drugs, such as lithium and other catecholaminergic drugs, and there are serotonin reuptake inhibitors in addition to Prozac. Even “standardized” terminology can differ between databases. For example, some adverse event databases request reaction terminology consistent with the Medical Dictionary for Regulatory Activities (MedDRA™), while other databases request, or already contain, input consistent with World Health Organization Adverse Reaction Terminology (WHO-ART) or Coding Symbols for a Thesaurus of Adverse Reaction Terms (COSTART) developed and maintained by the FDA's Center for Drug Evaluation and Research.
Further, data corruption in databases such as SRS and AERS is acknowledged, but not quantified, by the proponents. Data corruption at the database field level can include extraneous non-alpha characters, noise words, misspellings, and dislocations (e.g., data that is valid for one field, erroneously entered into another, inappropriate field). Databases that allow entry of free text information are especially susceptible to data corruption. At a higher level, existing adverse event databases have been known to contain redundant cases documenting the same adverse event.
U.S. Pat. No. 5,634,053 to Noble et al., “Federated Information Management (FIM) System And Method For Providing Data Site Filtering And Translation For Heterogeneous Databases” discloses an information management system that integrates data from a plurality of interconnected local databases to provide users with access to a virtual database. The system includes a user interface for generating a global query to search the virtual database, a smart dictionary database that contains configuration data, a data information manager that decomposes the global query into local queries, and a plurality of local information managers that execute the local queries to search for and retrieve data from the enumerated databases. A filter generates a list of those local databases that contain information relevant to the global query. As a result, the data information manager only generates local queries for the enumerated local databases. An input translator converts the global query into the respective local formats for the local databases so that the system provides true integration of heterogeneous databases. An output translator converts the data retrieved from each local database into a uniform input/output format so that the data presented to the user is integrated. The user typically selects the input/output format as his or her local format or a global format associated with the virtual database.
U.S. Pat. No. 5,664,109 to Johnson et al., “Method For Extracting Pre-Defined Data Items From Medical Service Records Generated By Health Care Providers” discloses a central medical record repository for a managed health care organization that accepts and stores medical record documents in any format from medical service providers. The repository then identifies the document using information automatically extracted from the document and stores the extracted data in a document database. The repository links the document to a patient by extracting from the document demographic data identifying the patient and matching it to data stored in a patient database. Data is extracted automatically from medical records containing “unstructured” or free form text by identifying conventional organization components in the text and is organized by executing rules that extract data with the aid of such information. Documents for a patient are retrieved by identifying the patient using demographic data.
U.S. Pat. No. 5,845,255 to Mayaud, “Prescription Management System” discloses a wirelessly deployable, electronic prescription creation system for physician use which captures into a prescription a patient condition-objective of the prescribed treatment and provides for patient record assembly from source elements, with privacy controls for patient and doctor, adverse indication review and online access to comprehensive drug information including scientific literature. Extensions to novel multi-drug packages and dispensing devices, and an “intelligent network” remote data retrieval architecture as well as onscreen physician-to-pharmacy and physician-to-physician e-mail are also provided.
U.S. Pat. No. 5,911,132 to Sloane, “Method (Of) Using (A) Central Epidemiological Database” discloses a method in which patient disease is diagnosed and/or treated usi

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