Evaluating Communication in the Medical Field
Picture this: Your leg has been aching for a couple days, showing no signs of improvement, so you decide to visit your general practitioner. He does a thorough examination but is unable to determine the root of the problem so he sends you to a specialist. The specialist takes a look and then orders a blood test and an ultrasound. Now, this could go on and on, but it shows how even the treatment of something seemingly trivial can require a group effort. For the group of physicians and specialists to be successful they all have to be able to communicate effectively in a timely fashion.
This article discusses the need for an effective communication system among the medical community. The number of potential messages or communications increases exponentially as the number of medical professionals involved increases. All this information travels along communication channels in different forms constrained by an individual system’s policies and protocols. In an attempt to sift through a myriad of patients in an orderly fashion according to priority, we have used methods like a nurse-operated telephone triage. Urgent cases are sent to emergency rooms while less severe ailments can now be assessed over the phone. But even if a hospital can communicate within itself well, it also needs to be prepared to share data with other hospitals or doctors. Once inter- and intra- hospital communications have been optimized, the technology employed also has to be convenient for medical professionals to use.
It’s clear that the communication network of just one hospital can be a complex maze and attempting to improve it is a daunting task. It may be unrealistic to draw a graph of the communication in an entire hospital, similarly to how it is unhelpful to draw a graph of the friendships across the globe. On the other hand, looking at the communication surrounding one person in a hospital may be of more use. A graph around a patient, for example, would have nodes for each person that communicates information about the patient: the nurse, loved ones, the radiologist, the surgeon, etc. The edges would signify some form of communication between two nodes that could be weighted according to the frequency of contact. Using a graph centered on the patient could help evaluate how well-informed the patient and their loved ones are, as well as determining how efficiently the hospital staff is communicating with each other. In order to improve intra-hospital interactions, it would be helpful to look at which communication lines are weighted heavily to make sure they are not overloaded with data, as well as making sure that nodes at the end of lighter communication lines are not being left out of the loop.
Source: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1579411/
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