The 2011 Information without Borders conference at Dalhousie University was held on February 3rd. Dr. Peggy Cunningham, the Dean at the Faculty of Management, opened by pointing out the need for new models in management that can overcome the common symptom of paralysis of analysis. These models must be capable of analyzing massive quantities of information, synthesizing and making it usable.

One example of the importance of such management models is evident in the presentation from Capital Health by Dr. Calvino Cheng.  Dr. Cheng’s presentation titled, ‘Navigating Uncharted Waters: The increasing role of informatics and business intelligences in the diagnostic laboratory”, discussed the importance of extracting quality data as the critical precursor to usable information. If the critical set of information (metadata) are not extracted or identified, the latter stages of management will essentially be “Garbage in -> Garbage Out”- unmanageable. It is with the extraction of quality data and maintenance of its integrity that a systematic approach to massive dynamic datasets can become viable. Dr. Cheng stated, “A systematic problem requires a systematic solution.” As demonstrated from his work in automating, analyzing, visualizing, and increasing efficiency in the Nova Scotia blood transfusion system, good data brings about a good scan of the situation and allows it to become manageable. A more effective inventory management system can ensure the freshness of blood supplies and their inventory levels. This efficiency not only brings about a better local system but also greater potential for the national system. The significance of capturing the critical data on blood will not only provide better patient care services but also more valuable resources for other sections.

As I listened, there were three statements that Dr. Cheng mentioned which stuck out. The first is “Garbage in -> Garbage out.” The second is “A systematic problem requires a systematic solution.”The third is, “from impossible to possible.” Even as I agree with the statements, questions, paralysing questions tangent off in my mind as I pondered, how do we identify these critical metadata regarding health informatics in the vast sea of information in the first place? How will we know when the system or the set of metadata we identify is actually functional? How will we know what is possible? In essence, how can we know? I would have to agree with Dr. Cheng that the answer is in more cooperation across disciplines, quality data extraction, visualization, and automation. I would further emphasize the importance of cooperative and collaborative metadata generation, extraction, and error detection as a process toward a critical and comparative identification of key metadata that can enable further digestion of information.

The increase in access and usability of health information through technology can bring about not only a different work flow but also the need for a better information policy in order to address the associated updates to ensure privacy, security, and effective access. As the management of health information and patient level records become more dynamic and co-locational, the development and maintenance of vital information policy, such as blood, will pave the way for other even more sensitive information, such as the future management of DNA level information. The integration of health information with geospatial datasets will be a double edge sword where hopefully the information system lessons learned from the blood transfusion program can flow to the correct veins of future policy making.