A Cloud-Native Knowledge Management Framework for Patient-Generated Health Data
Source of Publication
2023 Tenth International Conference on Social Networks Analysis, Management and Security (SNAMS)
Societal proliferation with mobile and wearable devices has given rise to patient-generated health data (PGHD). This refers to data from such devices that monitor, observe and report patient health status based on diverse metrics. Subse-quently, these data assists patients to adopt better behavioural and lifestyle patterns towards healthy living. It also implies access to the data by health providers facilitate patient health assessment. Despite these, several challenges exist with use of such data in clinical environments. These include issues with verification of the data, data interoperability and normalization, standardisation for defining data context and several others. Hence, this research investigates how these can be addressed and proposes a cloud-native knowledge management framework. The framework adopts fundamental knowledge management principles with a cloud-first paradigm towards addressing PGHD challenges relating to data standardisation, normalization, inter- operability, and real-time availability for healthcare providers. Furthermore, the framework defines architectural endpoints for diverse categories of authorised stakeholders to utilise and analyse processed PGHD to inform decision making towards addressing public health concerns in a changing world.
Medicine and Health Sciences
Patient-generated health data, Cloud-native, Knowledge management framework, Data interoperability, Data standardization
Majdalawieh, Munir; Hani, Anoud Bani; Al-Sabbah, Haleama; Adedugbe, Oluwasegun; and Benkhelifa, Elhadj, "A Cloud-Native Knowledge Management Framework for Patient-Generated Health Data" (2023). All Works. 6330.
Indexed in Scopus