PeopleSave: Recommending effective drugs through web crowdsourcing

Abstract

In this paper, we describe PeopleSave - a drug recommendation and feedback system for doctors on the basis of contextual patient reviews crowd-sourced from the Internet. Unlike other systems proposed in the past, we filter information sources to check for crowdsourcing feasibility and then assess the drug's effectiveness based on its reported detrimental effect on a patient. This helps in eliminating certain drugs that would almost certainly have an adverse effect on the patient's health and thereby obtain a set of recommendable drugs. These recommendations are further refined by analyzing the sentiment behind the opinions of patients who have been administered these drugs in the past. The resultant set of prescribable drugs agrees with those suggested by the consulted physicians for the considered sample set of diabetes patients. The critical assessment of the prototype system for Diabetes Type II drugs by both doctors and patients also reiterates the need for a feedback system that can possibly go a long way in improving patient experience of a drug. This leads us to conclude that PeopleSave, as a combination of the recommendation system prototype and the proposed feedback system, can be successful in improving the process of prescription of medicines for a varied range of medical conditions.