Science and Law
14th May 2015

9 Tips for Reanalyzing Science-Based Data for Litigation

Whether you are litigating a pharmaceutical or medical device case, a toxic tort, a consumer fraud case involving health claims, or any case involving complex scientific concepts, there are always data to be considered.

9 Tips for Reanalyzing Science-Based Data for Litigation

This piece was co-authored by Catherine Vick, an epidemiologist at Venebio, who offers services to an array of clients, from lawyers litigating complex scientific cases to research organizations requiring advanced data analytics and data management. Ms. Vick has over 15 years of experience in public health, program evaluation, and health outcomes research in academic, federal, and biopharmaceutical arenas.

Whether you are litigating a pharmaceutical or medical device case, a toxic tort, a consumer fraud case involving health claims, or any case involving complex scientific concepts, there are always data to be considered. In many cases, the data are being used by your adversary to support their position. It could be a case involving specific databases – for example, a mass tort, personal injury case relying on scientific publications showing a product is associated with an adverse health outcome at a higher rate than would otherwise be expected, or a consumer fraud case allegedly documenting that a product fails to incur its advertised benefits.

In each of these situations, the allegations involve data – in many cases, lots of data.

You have probably already considered a re-analysis of the data to confirm or dispute the allegation being made. In fact, in our experience, many times a reanalysis of the data can lead to an enhancement of your case, but it is important to make sure careful steps are taken to properly analyze the data.

We provide below 9 tips for reanalyzing data in support of litigation

1. Determine exactly what you want to analyze.

There may be a significant amount of data out there, and determining what questions you want to answer will pave the way for the most efficient analysis possible.  It will also narrow down exactly what information you need to acquire/request/petition. For instance, do you want to replicate findings from specific publications, or do you want to examine publically available or proprietary surveillance (safety) data in support of your argument?

2. Ask for the data with specificity and clarity

Once you have determined what you want to analyze, be very specific in your data request. Develop a set of questions that clearly delineate the nature of the data you are looking for from your adversary and specify how you would like to receive them.

3. Get the raw data, not the processed data

Many times, data that have already been assembled – with all of the key variables derived – will seem like the right data to request. It could pay off, though, to request the original data so that you can attempt to replicate how the data were assembled and how variables were derived. The process involved in getting to the analytic dataset is, quite often, more important than the analytic dataset itself.

4. Get the right analytic support for the job

Data management and analysis is about more than experience in a certain statistical programming language. Make sure you get someone very experienced who knows not only how to program, but knows the ins and outs of data privacy, HIPAA and relevant regulatory guidelines, data assembly and management, biostatistics, and practical knowledge of how research studies are designed and conducted. The right epidemiologist or biostatistician can make a huge difference in your timelines.

5. Pull in analytic help the moment you think you might ask for data.

Once the requested data are transferred, you will want answers as soon as possible. After all, time is critical in litigation. Therefore, make sure you identify and recruit your analytic support ahead of time. Not only can your consultant help you request the right data and navigate the practical aspects of data transfer, this will give them time to prepare and set up an analytic plan before the data come in, so that everyone can hit the ground running.

6. Consider the value of the right line listings

Many times it will be your job to document the existence of individual cases that refute your opponent’s position. For example, your opponent might allege that normal, therapeutic doses cause an adverse health effect and you may want to argue that the effect only occurs in the context of an overdose. A simple listing of all cases with the adverse effect and the drug dose could be a very powerful demonstrative exhibit in your case.

7. Take baby steps in your analysis

In our experience, you often don’t get the information you require to perform a complete analysis. Your analytic team will need to make sure that data are set up in a useable format, and one that can correctly link subjects across sub-datasets (for instance, matching laboratory records to clinical visits). Also, many dates and other variables are protected as HIPAA identifiers, and so may only be delivered in a masked or partial format, if at all.

Setting up an analytic plan ahead of time, and reviewing exactly what questions you need to answer will help your analytic team best review the fields quickly when you receive data, and to ensure that you have the data in a form that will allow you to do the full analysis. If you find you don’t have all the data you need, your analytic team can help you with specific language as you work to file the proper motions to get the right data.

8. Recreate before you innovate

Once you get the raw data, you will be eager to dive in and start rebutting your opposition’s case. But before you do any substantive analyses, be sure you can recreate the analytic datasets and descriptive statistics you are being confronted with. If you have all the data and you can’t even recreate the tables in a published paper or unpublished report, you might have enough to go on without doing anything more.

9. Don’t get lost in the sauce

It is not uncommon for a study to include tens of thousands (or even hundreds of thousands) of records with hundreds of variables collected per subject. Be sure to have a clear objective of what you are looking for to make your legal case and focus on the highest value analyses.

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