ArticleMedical care2015
Using machine learning to examine medication adherence thresholds and risk of hospitalization.
Article in Medical care, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 4 of them syntheses that pooled it.
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Who cites it
36 citing papers in PubMed, 4 syntheses or guidelines pooled it, 78 citations in OpenAlex.
- Adherence to Lipid-Lowering Therapies and Cardiovascular Outcomes in Patients With Atherosclerotic Cardiovascular Disease: A Systematic Review and Meta-Analysis.Journal of the American Heart Association · 2025 · on this mapPooled it
- Adherence to and persistence with antidiabetic medications and associations with clinical and economic outcomes in people with type 2 diabetes mellitus: A systematic literature review.Diabetes, obesity & metabolism · 2022Pooled it
- Refill Adherence Measures and Its Association with Economic, Clinical, and Humanistic Outcomes Among Pediatric Patients: A Systematic Review.International journal of environmental research and public health · 2020Pooled it
- Artificial Intelligence in Pharmacoepidemiology: A Systematic Review. Part 1-Overview of Knowledge Discovery Techniques in Artificial Intelligence.Frontiers in pharmacology · 2020Pooled it
- Effectiveness of Targeted Insulin-Adherence Interventions for Glycemic Control Using Predictive Analytics Among Patients With Type 2 Diabetes: A Randomized Clinical Trial.JAMA network open · 2019Trial
- Predicting Treatment Failure With Sodium-Glucose Cotransporter-2 Inhibitors in People With Type 2 Diabetes: Novel Artificial Intelligence and Machine Learning Approach.JMIR diabetes · 2026Article
- Advancing drug delivery research: sustainable strategies for innovation and translation.Drug delivery and translational research · 2025Review
- Artificial intelligence-driven transformations in diabetes care: a comprehensive literature review.Annals of medicine and surgery (2012) · 2024Review
- Artificial intelligence for optimizing benefits and minimizing risks of pharmacological therapies: challenges and opportunities.Frontiers in drug safety and regulation · 2024Review
- Adherence to Oral Antidiabetic Drugs in Patients with Type 2 Diabetes: Systematic Review and Meta-Analysis.Journal of clinical medicine · 2023Review
- Identification of high-risk patients for referral through machine learning assisting the decision making to manage minor ailments in community pharmacies.Frontiers in pharmacology · 2023Article
- Medication Adherence and Cardiometabolic Control Indicators Among American Indian Adults Receiving Tribal Health Services: Protocol for a Longitudinal Electronic Health Records Study.JMIR research protocols · 2022Article
- A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training.Information processing & management · 2022Article
- SANE (Easy Gait Analysis System): Towards an AI-Assisted Automatic Gait-Analysis.International journal of environmental research and public health · 2022Article
- Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device.BMC medical informatics and decision making · 2022Article
- Predicting Parkinson's Disease Progression: Evaluation of Ensemble Methods in Machine Learning.Journal of healthcare engineering · 2022Article
- Using Machine Learning to Predict Early Preparation of Pharmacy Prescriptions at PSMMC - a Comparison of Four Machine Learning Algorithms.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2021Article
- Measuring the multiple domains of medication nonadherence: findings from a Delphi survey of adherence experts.Translational behavioral medicine · 2021Article
- The Need for Ethnoracial Equity in Artificial Intelligence for Diabetes Management: Review and Recommendations.Journal of medical Internet research · 2021Review
- Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases.Frontiers in digital health · 2021Review
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundQuality improvement efforts are frequently tied to patients achieving ≥80% medication adherence. However, there is little empirical evidence that this threshold optimally predicts important health outcomes.
objectiveTo apply machine learning to examine how adherence to oral hypoglycemic medications is associated with avoidance of hospitalizations, and to identify adherence thresholds for optimal discrimination of hospitalization risk.
methodsA retrospective cohort study of 33,130 non-dual-eligible Medicaid enrollees with type 2 diabetes. We randomly selected 90% of the cohort (training sample) to develop the prediction algorithm and used the remaining (testing sample) for validation. We applied random survival forests to identify predictors for hospitalization and fit survival trees to empirically derive adherence thresholds that best discriminate hospitalization risk, using the proportion of days covered (PDC). OUTCOMES: Time to first all-cause and diabetes-related hospitalization.
resultsThe training and testing samples had similar characteristics (mean age, 48 y; 67% female; mean PDC=0.65). We identified 8 important predictors of all-cause hospitalizations (rank in order): prior hospitalizations/emergency department visit, number of prescriptions, diabetes complications, insulin use, PDC, number of prescribers, Elixhauser index, and eligibility category. The adherence thresholds most discriminating for risk of all-cause hospitalization varied from 46% to 94% according to patient health and medication complexity. PDC was not predictive of hospitalizations in the healthiest or most complex patient subgroups.
conclusionsAdherence thresholds most discriminating of hospitalization risk were not uniformly 80%. Machine-learning approaches may be valuable to identify appropriate patient-specific adherence thresholds for measuring quality of care and targeting nonadherent patients for intervention.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.