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

N Amador-Fernández, SI Benrimoj… - Frontiers in …, 2023 - frontiersin.org
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 …

[HTML][HTML] Assessment of minor health disorders with decision tree-based triage in community pharmacies

D Stämpfli, BA Winkler, SB Vilei, AM Burden - Research in Social and …, 2022 - Elsevier
Background Triaging in community pharmacies can lower the burden of minor health
disorders on other primary health care settings. The netCare service, introduced in 2012 by …

Strengthening patients' triage in community pharmacies: A cluster randomised controlled trial to evaluate the clinical impact of a minor ailment service

N Amador-Fernández, SI Benrimoj… - PloS one, 2022 - journals.plos.org
Background Self-perceived minor ailments might conceal other health conditions if patients
are not appropriately assisted by health care professionals. The aim of the study was to …

Machine learning-based prediction model for emergency department visits using prescription information in community-dwelling non-cancer older adults

S Park, C Lee, SB Lee, J Lee - Scientific Reports, 2023 - nature.com
Older adults are more likely to require emergency department (ED) visits than others, which
might be attributed to their medication use. Being able to predict the likelihood of an ED visit …

Development of machine-learning models using pharmacy inquiry database for predicting dose-related inquiries in a tertiary teaching hospital

J Cho, AR Lee, D Koo, K Kim, YM Jeong… - International Journal of …, 2024 - Elsevier
Abstract Background Drug-related problems (DRPs) are a significant concern in healthcare.
Pharmacists play a vital role in detecting and resolving DRPs to improve patient safety. A …

Consensus methodology to determine minor ailments appropriate to be directed for management within community pharmacy

H Nazar, Z Nazar, A Yeung, M Maguire… - Research in Social and …, 2018 - Elsevier
Abstract Background National Health Service (NHS) 111, a medical helpline for urgent care
used within the England and Scotland, receives significant numbers of patient calls yearly …

Developing a warning model of potentially inappropriate medications in older Chinese outpatients in tertiary hospitals: a machine-learning study

Q Hu, F Tian, Z Jin, G Lin, F Teng, T Xu - Journal of Clinical Medicine, 2023 - mdpi.com
Due to multiple comorbid illnesses, polypharmacy, and age-related changes in
pharmacokinetics and pharmacodynamics in older adults, the prevalence of potentially …

A machine learning-based risk warning platform for potentially inappropriate prescriptions for elderly patients with cardiovascular disease

W Xingwei, C Huan, L Mengting, Q Lv… - Frontiers in …, 2022 - frontiersin.org
Potentially inappropriate prescribing (PIP), including potentially inappropriate medications
(PIMs) and potential prescribing omissions (PPOs), is a major risk factor for adverse drug …

[HTML][HTML] Using machine learning to predict early preparation of pharmacy prescriptions at psmmc-a comparison of four machine learning algorithms

N Alhorishi, M Almeziny, R Alshammari - Acta Informatica Medica, 2021 - ncbi.nlm.nih.gov
Background: Patient satisfaction is one of the primary Key Performance Indicator (KPI) goal
of health care service, and it creates many reasons for implementing research, plans, and …

Pharmacogenomics driven decision support prototype with machine learning: A framework for improving patient care

F Kidwai-Khan, CT Rentsch, R Pulk, C Alcorn… - Frontiers in big …, 2022 - frontiersin.org
Introduction A growing number of healthcare providers make complex treatment decisions
guided by electronic health record (EHR) software interfaces. Many interfaces integrate …