EconPapers    
Economics at your fingertips  
 

IT-based reminders for medication adherence: systematic review, taxonomy, framework and research directions

Neetu Singh and Upkar Varshney

European Journal of Information Systems, 2020, vol. 29, issue 1, 84-108

Abstract: IT-based reminders have been one of the most promising interventions to improve medication adherence. Even with considerable research, it is not clear what types of reminders are effective for different patients and diseases and how much improvement in adherence is sustainable over time. To answer this, we conduct a systematic literature review of IT-based reminders. We utilise a six-step process reflecting the systematicity and transparency which is implemented using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Then, we develop a taxonomy of reminders, using Nickerson’s method, including thirteen characteristics categorised in four different dimensions. The findings are used in deciding when and where and how to use reminders with what type of patients for how long in improving medication adherence. The subsequent detailed analysis of the articles brought numerous insights leading to the development of Comprehensive Framework for Medication Reminders (CFMR). The framework can be used by the IS researchers for developing theoretical models to study the effectiveness of interventions for improving medication adherence. The taxonomy can be extended to a multi-level taxonomy using the proposed framework and research directions and can be further evaluated using domain experts.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/0960085X.2019.1701956 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjisxx:v:29:y:2020:i:1:p:84-108

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjis20

DOI: 10.1080/0960085X.2019.1701956

Access Statistics for this article

European Journal of Information Systems is currently edited by Par Agerfalk

More articles in European Journal of Information Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tjisxx:v:29:y:2020:i:1:p:84-108