A Systematic Review of Compensation and Technology-Mediated Strategies to Maintain Older Adults' Medication Adherence.
Hening PratiwiSusi Ari KristinaAnna Wahyuni WidayantiYayi Suryo PrabandariIkhwan Yuda KusumaPublished in: International journal of environmental research and public health (2023)
Elderly medication adherence is a challenge in health care. The elderly are often at higher risk for non-adherence, and more likely to be on multiple prescription medications for many comorbidities. This systematic review aimed to explore the current strategies for maintaining older adults' medication adherence with compensation and technology-mediated strategies. We conducted a systematic review to examine related articles published in the PubMed, Web of Science, and Scopus databases, as well as Google Scholar for additional reference sources by cross-reference review. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to guide this review. A total of 217 articles were screened, and 27 studies fulfilled the inclusion criteria. Older adults applied a variety of methods to maintain or enhance their medication adherence. Three studies indicated compensation strategies, 19 studies reported technological assistance, two studies used other strategies (community-offered help or caregivers help), and three studies used a combination of compensation with another strategy or technology. Studies identified various compensation- and technology-based strategies carried out by older adults to help remind them to take medication. This review identified potential benefits of technology and compensation strategy implementation in older adults to increase medication adherence. Although we are conscious of the heterogeneity of the included studies, it remains challenging to determine which elements underpin the most effective approaches.
Keyphrases
- meta analyses
- systematic review
- healthcare
- case control
- physical activity
- public health
- primary care
- randomized controlled trial
- emergency department
- type diabetes
- single cell
- metabolic syndrome
- machine learning
- social media
- skeletal muscle
- adverse drug
- clinical practice
- artificial intelligence
- weight loss
- climate change