Re: Viewing Observation. The Philosophy of Medical Imaging.

Visualisation and observation are distinct, though interrelated activities. Observation involves the sensing of data. Visualisation renders data tractable to the specific sense of vision. There is no visualisation without observation, and some observation requires visualisation for it to happen at all. Visualisation and observation have long been understood as critical underpinnings of theory formation, as well as practice.Over time, a series of debates have prised apart the supposed strict division between looking and theorising, as well as the assumed passivity of looking. These challenges replaced the assertion of independence with claims of causal influence running in both directions.Earlier discussion has focussed on the role of human observers, with the understanding that instrumentation played a mere enabling role, enhancing observation through technology for visualisation and visual enhancement. But new approaches in the philosophy of technology have also questioned this assumption.Postphenomenology, the set of practices leading to contemporary philosophy of technology, encompasses a set of approaches for re-evaluating the role of technology in observation, and with it reassessing the impact of observation on theory formation and clinical practice. With reference to ideas from postphenomenology, we consider the contours of a biophilosophical theory of visual observation.

Implementation and management of a biomedical observation dictionary in a large healthcare information system.

OBJECTIVE: This study shows the evolution of a biomedical observation dictionary within the Assistance Publique Hôpitaux Paris (AP-HP), the largest European university hospital group. The different steps are detailed as follows: the dictionary creation, the mapping to logical observation identifier names and codes (LOINC), the integration into a multiterminological management platform and, finally, the implementation in the health information system. METHODS: AP-HP decided to create a biomedical observation dictionary named AnaBio, to map it to LOINC and to maintain the mapping. A management platform based on methods used for knowledge engineering has been put in place. It aims at integrating AnaBio within the health information system and improving both the quality and stability of the dictionary. RESULTS: This new management platform is now active in AP-HP. The AnaBio dictionary is shared by 120 laboratories and currently includes 50 000 codes. The mapping implementation to LOINC reaches 40% of the AnaBio entries and uses 26% of LOINC records. The results of our work validate the choice made to develop a local dictionary aligned with LOINC. DISCUSSION AND CONCLUSIONS: This work constitutes a first step towards a wider use of the platform. The next step will support the entire biomedical production chain, from the clinician prescription, through laboratory tests tracking in the laboratory information system to the communication of results and the use for decision support and biomedical research. In addition, the increase in the mapping implementation to LOINC ensures the interoperability allowing communication with other international health institutions.