Factors influencing Drug Consumption and Prediction Methods

09/24/2021
by   Denis Koala, et al.
0

Estimating the needs of healthcare products and inventory management are still challenging issues in hospitals nowadays. Centers are supposed to cope with tight budgets and patient satisfaction at the same time. Some issues can be tackled in advance, especially regarding the prediction of drug consumption needs. This work delves into the literature in order to highlight existing methods of quantifying and estimating the needs for drugs in health facilities. A second objective is to draw up a list of factors that impact drug consumption in particular, factors that are used in these prediction methods. Following this literature review, it appears that six sustainable methods are being used by practitioners around the world, taking into account certain prerequisites and types of data. Thirty-four factors are identified as well and grouped into three categories. These results should participate in setting up new tools for predicting the need of drugs, to facilitate the upstream dimensioning of new pharmaceutical warehouses and to solve some hospital logistics issues.

READ FULL TEXT

Authors

page 5

02/22/2019

Drug-drug interaction prediction based on co-medication patterns and graph matching

Background: The problem of predicting whether a drug combination of arbi...
10/05/2019

Maturity assessment and maturity models in healthcare: A multivocal literature review

Context: Maturity of practices and infrastructure in healthcare domain d...
03/23/2021

GA-SVM for Evaluating Heroin Consumption Risk

There were over 70,000 drug overdose deaths in the USA in 2017. Almost h...
06/16/2021

Predictive Modeling of Hospital Readmission: Challenges and Solutions

Hospital readmission prediction is a study to learn models from historic...
05/17/2021

Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery

Knowledge Graphs (KG) and associated Knowledge Graph Embedding (KGE) mod...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.