Evaluation of Predictive Analytic Techniques in Healthcare Research: A PRISMA Style Review
Document Type
Article
Publication Date
2017
Publication Title
Issues in Information Systems
ISSN
1529-7314
Abstract
Preventing hospital admissions and readmission has the potential to reduce healthcare costs nationwide. Disease and readmission prevention can be assisted by applying data science and predictive analytics to healthcare data. This paper presents a PRISMA style literature review of pneumonia readmissions based on the Medline, Healthsource Academic, and CINHAL databases. These databases were searched for articles that contained 'pneumonia' and 'readmission' in the titles. While disease and readmission predication are well represented in the literature, the application of more advanced data science techniques is under represented. Regression appeared to be the most dominant technique applied and future research studies should study more data science and predictive analytic approaches. Adopting analytical techniques can help make more robust and precise analysis and can aid in the classroom instruction of data analytics and health informatics.
Recommended Citation
Wimmer, Hayden, Carl M. Rebmann Jr., Queen E. Booker.
2017.
"Evaluation of Predictive Analytic Techniques in Healthcare Research: A PRISMA Style Review."
Issues in Information Systems, 18 (3): 89-99.
https://digitalcommons.georgiasouthern.edu/information-tech-facpubs/81
