Monday, April 20, 2009

MedDRA and WHO Drug Easy as a Google Search?

In a world where information can easily be accessed by applying a Google search, mapping unstructured clinicians term or verbatim terms from an adverse event or a drug name to a standard term no longer needs to be an arduous task. One of the challenges of working with coding medical terminology is combining several skills that are diverse from many different disciplines. The user needs to be clinically trained to understand and interpret the meaning of the adverse events or the drug names. A conceptual understanding of the normalized database and the multi-axial hierarchical structure is required to navigate the dictionary. The user must also be adept at adding to the source data and joining the case report form data with the proper fields of the dictionary tables to derive at the final mapped data. Expecting users to overcome these hurdles without a clear process or tools can lead to an error prone, laborious and painful process. This paper will address many of the issues confronted when coding terms by demonstrating tried and true methodologies and technologies to automate and make the process efficient and easy.
  1. Auto Coding Auto code with existing dictionaries against source data for efficient mapping.
  2. Google like Search – Searching for terms in the dictionary or mapping decision history can be as simple as a Google Search.
  3. Optimize Coding Decision – Intelligence search recommendations, review process, and managing split terms are some techniques used to optimize.
  4. Optimize Dictionary – Loading source dictionary from MSSO (MedDRA) or UMC (WHO Drug) in an optimized fashion for performance.
  5. Managing Multiple Dictionaries – Organize dictionary in a centralized and hierarchical manner to have consistent coding decisions.
  6. Build Knowledge Base – Manual code only once and the term will be added to a knowledge base for future coding.
  7. Create new Mapped Data – Techniques for creating mapped data sets with the use of email to make the process seamless.

It is essential that you have a consistent thesaurus dictionary when performing an analysis on clinical terminologies. This paper will show processes along with SAS based software solutions such as Sy/Map™ to allow clinical users to function optimally with data managers and clinical programmer analysts. Armed with the understanding of the process and the right tools, you can narrow the gap between the different disciplines required to perform mapping decisions in a manner that is as easy as applying a Google search.

Controlled Terminology Introduction
The coding of patient data is critical in the grouping, analysis, and reporting of data. Coding decisions directly impact submissions for New Drug Applications (NDAs), safety surveillance, and product labeling. The success of a submission to the FDA can be significantly impacted by the analysis of adverse events, medical history and concomitant medications. The analysis relies on the interpretation of what has been transcribed from the subject CRF (Case Report Form). The original clinical term is referred to as the clinician’s term or verbatim term. This term needs to be re-interpreted or coded into a preferred term in order for it to be used during analysis. This is because different verbatim terms can have the same meaning such as in the example of the term "pain in head" or "headache". In this case, the two distinct verbatim terms are coded to one synonymous preferred term. The identical terms and the consistent classification of the term allow the analysis to draw valid statistical conclusions pertaining to the subject’s experience. The coding process can therefore affect the statistical interpretation of the adverse events or medications in which the subject is taking during the clinical trial.

There is room for inconsistency or error since the process contains many factors that go into making a decision. The following considerations are evaluated in making the optimal interpretation of the true meaning of the clinician’s term.

Clinical Accuracy – The interpretation of the meaning of the original term has to be clinically correct. In addition to the original term, other supportive information in the CRFs (e.g. drug indication and strength) is also used to ensure the accuracy of the mapping decision. The person performing this task needs to be clinically trained to decipher the meaning of the verbatim term as it relates to the preferred terms.

  • Global or Project Specific – The coding decision of a term in one specific project can be used again on other projects. It is therefore important to keep a global perspective while making a decision. However, there are instances where a coding decision needs to be applied specifically to special circumstances of the project.
  • Patient History – It is useful to look at the clinical history of the patient in order to understand what led up to the current situation. This allows the clinician to have a historic understanding and therefore make a more accurate interpretation of the terms. However, the decision cannot be subject specific since this needs to be applied to all subjects.
  • Dictionary Update - Understanding the structure of the dictionary and keeping up with the changes to the dictionary is critical for the success of mapping terms.

There are many factors that affect the interpretation of a clinical term and therefore the process becomes very complex. Besides the decision process, there are other operational and logistical considerations. The original clinician term can contain multiple terms so it needs to be split into separate distinct terms. This will therefore be coded separately. There are different versions to the dictionaries so version control becomes very important. There are many team members involved in this effort so training and standard operating procedures need to be established in order for the team to work together consistently. This multi-faceted process is complex but once a process is established, everything can work together in harmony so that terms are coded systematically and accurately to produce efficient results.

Mapping Methodologies
After the SAS based customized dictionary is established, the mapping can be preformed. There is a series of steps that needs to be performed in order to have your verbatim adverse events or drug names coded to the synonymous preferred terms. This section will describe the methodologies used to effectively manage thesaurus dictionaries and code the verbatim terms.

Before individual terms can be coded, thesaurus dictionaries need to be organized and managed. You would need to first identify and classify the types of dictionaries. The types of classifications for dictionaries include:

  • Dictionary Class - Example classifications of dictionaries include WHO Drug, MedDRA or Costart. This describes the content of the terms pertaining to drug or adverse event names and how it is related to an "external" dictionary. The word "external" in this case means a level of dictionary which will be described in more detail in the next section.
  • Level – A dictionary can be globally applied to all studies or it can be used specifically for a certain study. It can therefore be distinguished as either "global" or "project specific". These two types of dictionary levels pertain to terms managed internal to your organization. This is different from the dictionaries that are managed by an "external" organization such as MSSO who manages MedDRA. These external dictionaries are updated regularly by an external vendor and are managed differently from internal project specific or global level dictionaries.
  • Attribute – Administrative attributes or metadata that describe the dictionaries are also essential in managing dictionaries. This includes values such as a unique name, physical location where associated dictionary files are located, and data sets name that stores the dictionary.

The classification information mentioned above needs to be managed in a way which allow users to register new dictionaries in the event that a new version of the dictionary is made available. Modifications to existing information are also necessary in the event that the underlying metadata is changed. The deletion of an existing dictionary can also be applied. Note that this does not necessarily mean that you are deleting the underlying data sets which store the content of the dictionary, but rather just removing the registered information or metadata. External dictionaries are managed by the vendor but internal dictionaries such as global or project specific need the capabilities of having old terms retired. This means that when a specific coding decision based on a term in the dictionary is no longer valid, it can be removed from the dictionary by a designated administrator. These are some of the tasks that are necessary in managing thesaurus dictionaries in order to optimize the performance of coding terms.

complete paper available at Coding Dictionaries Papers and related AE Coding Software

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  1. Hi,
    Thanks for a good article. I am looking at requirements for MedDRA coding in a system where the verbatim terms first need translation to English.
    I like the knowledgebase approach to have the thesaurus grow over time.

  2. Hi Kevin,

    The software Symap which we have implemented in this paper does have an interface to translate the term from other languages to English as recommendations. Can you clarify if it is Danish or do you have specific languages that you plan to have the verbatim term entered?