ArticleHealth services research2016
Observing versus Predicting: Initial Patterns of Filling Predict Long-Term Adherence More Accurately Than High-Dimensional Modeling Techniques.
Article in Health services research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence in Pharmacoepidemiology: A Systematic Review. Part 1-Overview of Knowledge Discovery Techniques in Artificial Intelligence.Frontiers in pharmacology · 2020Pooled it
- Effect of Reminder Devices on Medication Adherence: The REMIND Randomized Clinical Trial.JAMA internal medicine · 2017Trial
- Effect of the initial combination approach vs initial monotherapy approach on 1-year trajectories of adherence in drug-naive patients with type 2 diabetes.Journal of managed care & specialty pharmacy · 2026Article
- Artificial intelligence approaches to predicting treatment non-adherence in chronic diseases: a narrative review.Frontiers in digital health · 2026Review
- Machine learning approaches to predicting medication nonadherence: a scoping review.International journal of medical informatics · 2025Article
- The association of distress and depression screening measures and other electronic health record information with adjuvant endocrine therapy persistence.Breast cancer research and treatment · 2025Article
- Association of Baseline Adherence to Antihypertensive Medications With Adherence After Shelter-in-Place Guidance for COVID-19 Among US Adults.JAMA network open · 2022Article
- A prediction model for nonpersistence or nonadherence to direct oral anticoagulants in hospitalized patients with atrial fibrillation.Journal of managed care & specialty pharmacy · 2022Article
- Prediction of treatment nonadherence among older adults with chronic obstructive pulmonary disease using Medicare real-world data.Journal of managed care & specialty pharmacy · 2022Article
- Machine Learning and Medication Adherence: Scoping Review.JMIRx med · 2021Article
- Predicting medication adherence using ensemble learning and deep learning models with large scale healthcare data.Scientific reports · 2021Article
- Identifying adherent patients to newly initiated statins using previous adherence to chronic medications.Journal of managed care & specialty pharmacy · 2021Article
- Intersections of machine learning and epidemiological methods for health services research.International journal of epidemiology · 2021Article
- The Impact of Adherence to Disease-Modifying Therapies on Functional Outcomes in Veterans with Multiple Sclerosis.Journal of central nervous system disease · 2021Article
- Use of Data-Driven Methods to Predict Long-term Patterns of Health Care Spending for Medicare Patients.JAMA network open · 2020Article
- Not there yet: using data-driven methods to predict who becomes costly among low-cost patients with type 2 diabetes.BMC endocrine disorders · 2020Article
- Social Risk Factors for Medication Nonadherence: Findings from the CARDIA Study.American journal of health behavior · 2020Article
- The association of pharmacy fill synchronization with breast cancer endocrine therapy adherence.Cancer · 2019Article
- Trajectories of adherence to mood stabilizers in patients with bipolar disorder.International journal of bipolar disorders · 2019Article
- Quantifying Social Reinforcement Among Family Members on Adherence to Medications for Chronic Conditions: a US-Based Retrospective Cohort Study.Journal of general internal medicine · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveDespite the proliferation of databases with increasingly rich patient data, prediction of medication adherence remains poor. We proposed and evaluated approaches for improved adherence prediction. DATA SOURCES: We identified Medicare beneficiaries who received prescription drug coverage through CVS Caremark and initiated a statin. STUDY
designA total of 643 variables were identified at baseline from prior claims and linked Census data. In addition, we identified three postbaseline predictors, indicators of adherence to statins during each of the first 3 months of follow-up. We estimated 10 models predicting subsequent adherence, using logistic regression and boosted logistic regression, a nonparametric data-mining technique. Models were also estimated within strata defined by the index days supply.
resultsIn 77,703 statin initiators, prediction using baseline variables only was poor with maximum cross-validated C-statistics of 0.606 and 0.577 among patients with index supply ≤30 days and >30 days, respectively. Using only indicators of initial statin adherence improved prediction accuracy substantially among patients with shorter initial dispensings (C = 0.827/0.518), and, when combined with investigator-specified variables, prediction accuracy was further improved (C = 0.842/0.596).
conclusionsObserved adherence immediately after initiation predicted future adherence for patients whose initial dispensings were relatively short.
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