AI in Medication Adherence Monitoring: Supporting Pharmacists in Collaborative Care Models—A Systematic Review and Meta-Analysis
Author(s)
Balaji Thiyagarajan, Pharm D1, Dhanshika Vijayabaskar, PharmD2, Shailaja Krishnamoorthy, Ph.D3.
1student, c.l.baid metha college of pharmacy, Chennai, India, 2Student, C.L.Baid Metha College of Pharmacy, Chennai, India, 3Pharm D, The Tamil Nadu Dr. M.G.R. Medical University, chennai, India.
1student, c.l.baid metha college of pharmacy, Chennai, India, 2Student, C.L.Baid Metha College of Pharmacy, Chennai, India, 3Pharm D, The Tamil Nadu Dr. M.G.R. Medical University, chennai, India.
OBJECTIVES: To evaluate and examine the influence the influence of digital platforms on patient results in practical healthcare environments.
METHODS: A comprehensive search was carried out in the PubMed , Scopus and Cochrane databases were included between the year 2015 to 2024. Studies that reported quantifiable patient outcomes and assessed digital platforms in clinical practice were accepted. There were nine studies (n=7,842). A meta-analysis with random effects was used to synthesize the data. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the study.
RESULTS: Interventions supported by AI resulted in a marked enhancement in adherence to medication. The integration of pharmacists with AI tools also led to a 22% reduction in the risk of hospital readmissions. A moderate level of heterogeneity was noted (I² = 40-52%). The average reduction in HbA1c among diabetic populations was -0.44%. Quality evaluations indicated that 7 out of 9 studies received a high rating on the NOS.
CONCLUSIONS: Tools for adherence monitoring powered by AI, when combined with care models led by pharmacists, greatly enhance medication adherence and clinical results. These technologies provide scalable solutions applicable to real-world scenarios that bolster collaborative care and should be emphasized in upcoming digital health initiatives
METHODS: A comprehensive search was carried out in the PubMed , Scopus and Cochrane databases were included between the year 2015 to 2024. Studies that reported quantifiable patient outcomes and assessed digital platforms in clinical practice were accepted. There were nine studies (n=7,842). A meta-analysis with random effects was used to synthesize the data. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the study.
RESULTS: Interventions supported by AI resulted in a marked enhancement in adherence to medication. The integration of pharmacists with AI tools also led to a 22% reduction in the risk of hospital readmissions. A moderate level of heterogeneity was noted (I² = 40-52%). The average reduction in HbA1c among diabetic populations was -0.44%. Quality evaluations indicated that 7 out of 9 studies received a high rating on the NOS.
CONCLUSIONS: Tools for adherence monitoring powered by AI, when combined with care models led by pharmacists, greatly enhance medication adherence and clinical results. These technologies provide scalable solutions applicable to real-world scenarios that bolster collaborative care and should be emphasized in upcoming digital health initiatives
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
MT3
Topic
Clinical Outcomes, Medical Technologies, Real World Data & Information Systems
Topic Subcategory
Digital Health
Disease
Diabetes/Endocrine/Metabolic Disorders (including obesity), No Additional Disease & Conditions/Specialized Treatment Areas