what-when-how
In Depth Tutorials and Information
research examples. Healthcare involves patients, individual medical staff, and
large medical groups, all acting in a complex social network to achieve the best
possible care for each patient. he social network that healthcare forms connects
all these different entities together as well as acting as a discrete tool for each
participant.
A sociotechnical network can be formed to integrate the various complex rela-
tionships in the current healthcare system. his network ranges from an individual
tool that allows a doctor to make a particular diagnosis, to large-scale data-gather-
ing systems that connect various large healthcare providers to a government body
for oversight.
One way to analyze this model is to start at the smallest individual compo-
nent and work toward the larger interconnecting parts. Each smaller piece of the
network builds on other pieces to form a larger system that relates all the users
and the technical tools, and by examining the steps that go from the small to
the large, one may slowly arrive at an understanding of how the sociotechnical
network is formed.
14.2 EpiSimsDiseaseModel[1]
One example of small-scale technical analysis in the medical field is infectious
disease spread. By using a network modeling system, it is possible to predict vec-
tors of disease transmission to provide crisis plans and give estimations on how
quickly and how far a disease may spread. he Modeling Infectious Disease Agent
Study (MIDAS) is being conducted by the National Institute of Health to exam-
ine different methodologies toward these systems. One approach in particular, the
Epidemiological Simulation System (EpiSims) [1], was created to model disease
vectors particularly in computer environments.
One of the first tasks that must be accomplished in order to provide the func-
tional basis for such a network is the accumulation of the necessary background
data to form an environment in which to function. If one considers such simulation
to be created to be a probability universe, then that universe must be populated by
different entities and factors that approximate the real world. In the case of infec-
tious disease spread, this would be actual places, census data, distances, transporta-
tion networks, and information regarding the activities that take place. All of these
are necessary to create a simulation that outputs data that are meaningful in any
real-world situation.
he EpiSims model uses a “person-activity” approach toward calculating vectors
of disease transmission. Individual people are created to represent entities within
the network. hese people have diferent characteristics, be it race, gender, age,
social status, etc. For every person, an appropriate set of activities is constructed to
create a working timeline that places a given person in different places for different
instances of time. he model also considers the travel from location to location as
