| dc.description.abstract | In Sri Lanka, approximately 94% of
expectant mothers rely on public-sector health
facilities for antenatal care. However, the manual
collection of information on pregnant mothers using
pen and paper presents significant challenges, leading
to a time-consuming and cumbersome process. This
study addresses the need for an efficient solution to
manage antenatal care records, aiming to reduce the
Maternal Mortality Ratio (29 per 100,000 live births)
and enhance overall maternal care. A comprehensive
web-based application is proposed. The system
involves five key actors: Primary care staff
(MOH/Midwife), Obstetrician, Hospital staff, Patient,
and System admin. The primary objectives include the
development of a patient database system specific to
the Medical Officer of Health (MOH) area and an
electronic referral system to identify and address
potential risk factors in real time. The integration of
NLP allows for the automated analysis of patient
feedback and consultation records, enabling the
identification of common concerns and areas for
improvement in antenatal care. By applying sentiment
analysis, topic modelling, and named entity
recognition, the system can extract valuable insights
from textual data, facilitating data-driven decisionmaking and personalized care plans. The system will
undergo a pilot implementation in three selected MOH
areas for a month, followed by validation and fullscale implementation. The focus of the system design
was to expedite and simplify information management
in the antenatal department, providing a faster, more
convenient, and efficient solution. By leveraging
technology, this study proposes a system to
significantly improve the overall quality of antenatal
care, contributing to the reduction of maternal
mortality and facilitating informed decision-making
during emergencies | en_US |
