International biomedical research networks -- cultural and language barriers

In a world that is becoming flatter and flatter, the expansion of international biomedical research networks is a natural consequence of the globalization process. Similar to the cultural barriers faced by marketing departments looking into expanding the distribution of their products, research networks also face cultural barriers of their own while attempting to collect research data. These are encountered in four main areas, namely:


1. Informatics standards for data collection
In this category are the multiple standard terminologies and ontologies created to standardize the way biomedical research information is communicated. Examples abound, going from SNOMED (Systematized Nomenclature of Medicine), "a systematically organised computer processable collection of medical terminology covering most areas of clinical information such as diseases, findings, procedures, microorganisms, pharmaceuticals" (Wikipedia), to the widespread ICD (International Statistical Classification of Diseases and Related Health Problems). SNOMED standards, now transitioning to the International Health Terminology Standards Development Organisation, is actually a good example of the problems encountered during internationalization of biomedical research. Despite its widespread use in the US to standardize the capture of health-related information, to date besides the original version in English only the German and Spanish versions have been officially accepted as fulfilling their strict quality criteria.

2. Standards for outcome scales
In this category are standardized questionnaires used to measure a widespread range of patient-reported and clinician-reported measures of health and disease. Examples include scales to measure health-related quality of life, functional activity (ability to perform activities of daily living, depression, anxiety, etc), among many others

3. Clinical workflow
Although frequently delegated to a second level, clinical workflow frequently determines the quality of the data collected in a clinical environment. Of crucial importance, clinical workflow varies substantially across cultures and healthcare systems and can therefore determine the success or failure of an associated data collection effort.

4. Other questionnaires
Finally, this category focuses on the other multiple questions that are captured during the data collection process and that do not follow under any of the previously mentioned categories. Here, standardized methodologies are available focusing on the translation of texts using techniques to improve their reliability (translation and back-translation, use of language and domain experts) as well as qualitative interviews with both clinicians and patients to determine their level of understanding and familiarity with these terms.

The intent of bringing together these four levels of data standards is to create a system allowing for reliable data collection of culturally similar data points and that would ultimately lead to seamless data exchange. The end result, or at least the one we hope would happen, is the production of biomedical information and knowledge to improve the life of a much larger portion of the global population than what we can currently reach.