Identification of high-risk patients for referral through machine learning assisting the decision making to manage minor ailments in community pharmacies.

ABSTRACT: Background: Data analysis techniques such as machine learning have been used for assisting in triage and the diagnosis of health problems. Nevertheless, it has not been used yet to assist community pharmacists with services such as the Minor Ailment Services These services have been implemented to reduce the burden of primary care consultations in general medical practitioners (GPs) and to allow a better utilization of community pharmacists' skills. However, there is a need to refer high-risk patients to GPs. Aim: To develop a predictive model for high-risk patients that need referral assisting community pharmacists' triage through a minor ailment service. Method: An ongoing pragmatic type 3 effectiveness-implementation hybrid study was undertaken at a national level i

SUBMITTER: Amador-Fernandez N 

PROVIDER: S-EPMC10368471 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature