Monthly Archives: November 2011

EHR Tracking for Drugs and Devices

Cloud-based, integrated electronic health records (EHR or EMR) systems provide a new paradigm for the collection and use of data for long term research about drugs and devices after FDA approval—commonly referred to as Phase IV testing.

The new paradigm is particularly relevant for drugs and devices for chronic diseases and conditions because long term use may lead to adverse events that do not occur during the shorter term testing required prior to FDA approval. The significance of chronic conditions is indicated by the following statistics:

  • Chronic diseases cause 7 in 10 deaths each year in the United States.
  • About 133 million Americans, nearly 1 in 2 adults, live with at least one chronic illness.
  • More than 75% of health care costs are due to chronic conditions.

The primary differences between the EHR based paradigm and traditional Phase IV testing are listed here (Notes and comments are in italics.)

EHR description: Data is drawn from a database that provides for multiple uses of the data to maximize value.
Traditional Process: Data is collected for a single use—little or no cost sharing.

EHR description: A wide range of available data is identified and collected to provide flexibility during analysis.
Traditional Process: A narrow and focused range of data is collected to manage cost.

EHR description: Samples of existing data are used to validate test objectives and methods early in the research project.
Traditional Process: Prior similar studies and assumptions are used to validate objectives and methods.
Breakthrough drugs or devices may require significantly different objectives and/or methods than required in prior tests.

EHR description: Test subjects—people with the disease—and matching control subjects can be found in the database.
Traditional Process: Test subjects and matching control subjects must be found using a variety of means.
A computer can find test subjects in an existing database very quickly and at very low cost. Traditional processes for finding and recruiting test subjects are significantly more costly and time consuming.

EHR description: Data collection and analysis is conducted in accordance with HIPAA privacy requirements and patient participation is not required.
Traditional Process: Patients must be contacted and enrolled in the data collection process.
The initial data is available in the database day-one of the test to minimize start time and cost.

EHR description: Data collection is totally independent of and not biased by the research.
Traditional Process: Data collection may be suspect under some circumstances.
The process of contacting and enrolling patients may lead to changes in behavior such as greater care in taking drugs as prescribed and greater participation in follow-up visits. Independent data collection may provide a sample more closely aligned with actual patient behavior.

EHR description: Able to add new test and control subjects as needed including their history from the database.
Traditional Process: Ability to add new test and control subjects with past data is very limited.
If adverse events are concentrated in patients with a defined set of characteristics it may be necessary to expand the number of patients with those characteristics in both the test and control group to assure statistically reliable results and a sufficiently large sample to meet the HIPPA privacy rule.

EHR description: Additional historic data can be added from the existing database if preliminary analysis indicates it may be significant, e.g., prior use of similar drugs or a history of another ailment.
Traditional Process: Very difficult to obtain additional historic data from patient records late in study.
If adverse events are found in patients with defined prior conditions including prior use of similar drugs, exposure to other diseases, etc., the database can be searched to add subjects and findings related to that topic for further study and to assure statistical reliability.

EHR description: Off-label uses can be tracked through analysis of electronic medical records and prescriptions.
Traditional Process: Off-label uses are difficult to track based on paper records.
Off-label use can identify new marketing opportunities and a second parallel test can be conducted at relatively low cost to assure continued safety and effectiveness of both uses.

EHR description: If the drug or device has been on the market for some time historic and future data can be concatenated to expand the test horizon.
Traditional Process: It is difficult to find and map historic data to a current test.
Is a newly discovered side affect new or just newly discovered? Does a longer period of documented use show greater risk?

EHR description: The entire database can be used to assure the test and control groups are representative of all patients who are taking the drug or using the device.
Traditional Process: The study itself does not provide means to assure a representative sample over time.
The patient population may change over time; the test should change to assure that the entire patient population is adequately represented.

EHR description: Analysis can be conducted in near-real-time to minimize damage to patients that may occur between the time an adverse reaction is discovered and the time appropriate action is taken.
Traditional Process: Traditional analysis moves at the speed of paper which can delay appropriate actions to minimize damages.
Quicker response to adverse reactions reduces cost and provides an opportunity to demonstrate concern for patient well being to minimize punitive damages.

Cloud based, integrated electronic health records offer a new paradigm for tracking drugs and devices after FDA approval. This approach allows more testing to be done at lower cost. It supports faster analysis to minimize actual damages to patients and subsequent compensatory and punitive damages awarded to plaintiffs’ and their attorneys. Better healthcare at lower cost.

Originally published under this title on EHRbloggers, October 12, 2011

Short link: http://wp.me/pyfFd-9Z

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