Background: In the last decade, social media users across the world have crossed 1 billion, making it one of the fastest growing sources of big data. Also, people needing healthcare continue to increase in every society. Through accessibility, communication and interaction between health practitioners and patients, this type of ever-growing, social media subscriber–based platform can be of significant use in improving healthcare delivery to society. However, users encounter serious challenges in their attempts to make use of social media and big data for health-related services. The challenges are primarily caused by factors such as integration, complexity, security and privacy. The challenges are mainly owing to the sensitive nature of the healthcare environment, as a result of personalisation and privacy of information. Objectives: The objectives of the study were to examine and gain a better understanding of the complexities that are associated with the use of social media and healthcare big data, through influencing factors, and to develop a framework that can be used to improve health-related services to the patients. Methods: The interpretivist approach was employed, within which qualitative data were collected. This included documents and existing literature in the areas of social media and healthcare big data. To have a good spread of both previous and current state of events within the phenomena being studied, literature published between 2006 and 2016 were gathered. The data were interpretively analysed. Results: Based on the analysis of the data, factors of influence were found, which were used to develop a model. The model illustrates how the factors of influence can enable and at the same time constrain the use of social media for healthcare services. The factors were interpreted from which a framework was developed. The framework is intended to guide integration of social media with healthcare big data through which service delivery to patients can be improved. Conclusion: This study can be used to guide integration of social media with healthcare big data by health facilities in the communities. The study contributes to healthcare workers’ awareness on how social media can possibly be used to improve the services that they provide to the needy. Also, the study will benefit information systems and technologies and academic domains, particularly from the health services’ perspective.
In South Africa, there has been for many years challenges in how healthcare big data are accessed, used, and managed by facilities, particularly the small health facilities. The challenges arise from inaccuracy and inconsistency of patients' data and have impact on diagnoses, medications, and treatments, which consequently contributes to fatalities in South Africa, particularly in the rural areas of the country. The problem of inaccuracy and inconsistency of patients' data is often caused by lack of or poor analysis (or analytics) of data. Thus, the objective of this research was to understand the factors that influence the use and management of patients' big data for healthcare service delivery. The qualitative methods were applied, and a South African healthcare facility was used as a case in the study. Actor network theory (ANT) was employed as a lens to guide the analysis of the qualitative data. Based on the findings from the analysis, a model was developed, which is intended to guide analytics of big data for healthcare purposes, towards improving service delivery in the country.
In South Africa, there has been for many years challenges in how healthcare big data are accessed, used, and managed by facilities, particularly the small health facilities. The challenges arise from inaccuracy and inconsistency of patients' data and have impact on diagnoses, medications, and treatments, which consequently contributes to fatalities in South Africa, particularly in the rural areas of the country. The problem of inaccuracy and inconsistency of patients' data is often caused by lack of or poor analysis (or analytics) of data. Thus, the objective of this research was to understand the factors that influence the use and management of patients' big data for healthcare service delivery. The qualitative methods were applied, and a South African healthcare facility was used as a case in the study. Actor network theory (ANT) was employed as a lens to guide the analysis of the qualitative data. Based on the findings from the analysis, a model was developed, which is intended to guide analytics of big data for healthcare purposes, towards improving service delivery in the country.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.