Abstract:
In recent times, contemporary hospitals continue to become
smart by automating their administrative processes using up to
date equipment and incorporating latest technological
principles into their activities. It has been seen over the years
that the area of medical diagnosis systems require the use of
diagnostic systems as they have been proven to have led to
increased diagnostic accuracy and relieve experts from routine
tasks. The easiest way to prevent women from suffering and
dying from Cancer of the cervix is through early detection of
the Human Papilloma Virus hence the recommendation of
Visual Inspection with Acetic acid (VIA) to be done in
developing countries by the World Health Organization.
There is need for systems that can assist health workers in
confirmation of results gotten after VIA tests has been done
on patients to reduce misdiagnosis and overtreatment but such
systems need to be developed by putting users need into
consideration. Evaluating users’ acceptance of such systems is
one of the most important metrics in ensuring the success of
such systems as it helps to predict users’ willingness to accept
or reject them.
The Technology Acceptance Model (TAM) was used to
evaluate the level of eagerness of users to use such systems
and the measuring instrument was analyzed using SPSS
version 21.0. A total of 150 respondents participated in this
study with a response rate of 86%. From the analysis, it was
realized that a total of 80.7% of the sampled population
subscribed to the use of diagnostic expert systems, 89.1%
believed that the use of such systems will have a positive
impact and 87.6% were willing to use it. The results of TAM
indicated the willingness of users to use such systems, the
need to repeat the study after executing the system in real life
was suggested as users intention could change, and also to
identify factual usage of the system. The work brought to light
the impact of putting users’ needs into consideration first
since this increases user acceptability which could eventually
lead to the success of such diagnostic systems at large.
