SMS based channeling guide to select physicians based on native language processing

Abstract

Channelled consultation service plays a major role in private medical care in Sri Lanka. But it lacks a proper referral system where patients are directed to the correct specialist. Therefore, there is a lot of confusion when choosing the specialist. Patients do not have easily accessible medical content which can be utilised to make such a decision, as most of the content is in English. With the wide spread use of the mobile technology, short messaging service (SMS) can be utilised to implement such a system which is easily accessible and sufficiently reliable. The objective is to develop a SMS based solution to suggest to the general public a list of possible consultants, based on client’s gender, age, other medical conditions and presenting symptoms submitted in native language through SMS. Then the client will receive an SMS with a suggested list of clinicians. The clients submit gender, age, other medical information, presenting symptoms and location using SMS. The submitted SMSs are subjected to text/ natural language analysis to extract keywords. The extracted keywords in Sinhala (Singlish) are mapped to English keywords. Then the expert system will analyse the keywords and suggest relevant clinicians. The list of clinicians will be filtered according to the location of the client.