Macro Level GIS Integrated Health Care Management using Optimized Planning System

Abstract

Unavailability of appropriate space for the patients and their attendants in public hospitals, lack of awareness towards health
and hygiene and unavailability of efficient informatics program-resulting from conventional orthodox mentality of the
patients, to inform rural population of India, leaves them untreated, hence enhancing the chances of their diseases to grow,
become fatal and possibly leading to a break of epidemic. Reason behind the mismanagement of health workers is the lag in
adopting a complete digital resource management system. To overcome the present scenario of poor ratio of patients to
necessary number of health workers needed to attend them, a system is presented that will be working on the principal of
location intelligence where Cloud Computing, Location Analytics, Mobile, Social, GIS and Secure Services act as the
foundation pillars. Kiosks will be installed in every village and urban locality, operated by a government appointed medical
official. The patients will approach this facility when in need of a doctor. The operator will key in the symptoms in the kiosk,
which will generate prescription on the basis of the keyed in symptoms. The prescription generating algorithm is a neural
network taking parameters such as historical data about patient’s health, real weather conditions of his geographical
residence and primary symptoms diagnosed by the medical officer. The system will store the spatial location of the patient
so that if in future similar symptoms appear on other individuals too, then spatial pattern analysis can be performed to
diagnose the probable cause of spreading symptoms. The system is so designed that in case of no reporting from patient
within the prescribed number of days, a medical officer can locate the patient using his/her geographic location and can feed
his/her present condition in the system using Mobile devices. It is an integrated system with GIS at heart which enables to
remotely monitor each patient. The system will also be feeding the information to a central dashboard having ESRI or Google
Maps as one of the key components to display the location of the patient, thus making it easier to attend to them in cases of
emergency.