Addressing data accuracy and information integrity in mHealth using ML

The aim of the study was finding a way in which Machine Learning can be applied in mHealth Solutions to detect inaccurate data that can potentially harm patients. The result was an algorithm that classified accurate and inaccurate data

Understanding New Emerging Technologies Through Hermeneutics. An Example from mHealth

New technologies such as mHealth have entered the health domain as an innovative technology to connect people suffering from a chronic disease with healthcare services to reduce the pressure on healthcare systems. The primary driver for these technologies is data and they contain valuable information. Understanding what the data means and the accuracy of the data can be complex. Hermeneutics has been applied in previous Information Systems studies that interpret data to provide a meaning about unexplored and complex phenomenon. This paper provides background information about Hermeneutics and an example of Hermeneutics applied in a new mHealth study

Using Machine Learning to address Data Accuracy and Information Integrity in Digital Health Delivery

Today, much of healthcare delivery is digital. In particular, there exists a plethora of mHealth solutions being developed. This in turn necessitates the need for accurate data and information integrity if superior mHealth is to ensue. Lack of data accuracy and information integrity can cause serious harm to patients and limit the benefits of mHealth technology. The described exploratory case study serves to investigate data accuracy and information integrity in mHealth, with the aim of incorporating Machine Learning to detect sources of inaccurate data and deliver quality information

Data accuracy considerations with mHealth

With the plethora of mHealth solutions developed being digital, this necessitates the need for accurate data and information integrity. Lack of data accuracy and information integrity in mHealth can cause serious harm to patients and limit the benefits of such promising technology. Thus, this exploratory study investigates data accuracy and information integrity in mHealth by examining a mobile health solution for diabetes, with the aim of incorporating Machine Learning to detect sources of inaccurate data and deliver quality information