ArticleJournal of the American Medical Informatics Association : JAMIA
Surveillance of medication use: early identification of poor adherence.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
What it found
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The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.
- A systematic review of medication exposure assessment in prospective cohort studies of community dwelling older australians.PloS one · 2015Pooled it
- Assessing medication adherence: options to consider.International journal of clinical pharmacy · 2014Pooled it
- The Over-the-Counter Medicines Market in Poland.International journal of environmental research and public health · 2022Article
- Community Pharmacies in Poland-The Journey from a Deregulated to a Strictly Regulated Market.International journal of environmental research and public health · 2020Review
- Towards an understanding of the burdens of medication management affecting older people: the MEMORABLE realist synthesis.BMC geriatrics · 2020Article
- Proximal Predictors of Long-Term Discontinuance with Noninsulin Antihyperglycemic Agents.Journal of managed care & specialty pharmacy · 2016Article
- Observational
- Comprehensive electronic medical record implementation levels not associated with 30-day all-cause readmissions within Medicare beneficiaries with heart failure.Applied clinical informatics · 2014Article
- Scalable decision support at the point of care: a substitutable electronic health record app for monitoring medication adherence.Interactive journal of medical research · 2013Article
- Early detection of poor adherers to statins: applying individualized surveillance to pay for performance.PloS one · 2013Article
- Clinical research informatics: a conceptual perspective.Journal of the American Medical Informatics Association : JAMIA · 2012Article
- The roles of past behavior and health beliefs in predicting medication adherence to a statin regimen.Patient preference and adherence · 2012Article
- The SMART Platform: early experience enabling substitutable applications for electronic health records.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundWe sought to measure population-level adherence to antihyperlipidemics, antihypertensives, and oral hypoglycemics, and to develop a model for early identification of subjects at high risk of long-term poor adherence.
methodsPrescription-filling data for 2 million subjects derived from a payor's insurance claims were used to evaluate adherence to three chronic drugs over 1 year. We relied on patterns of prescription fills, including the length of gaps in medication possession, to measure adherence among subjects and to build models for predicting poor long-term adherence.
resultsAll prescription fills for a specific drug were sequenced chronologically into drug eras. 61.3% to 66.5% of the prescription patterns contained medication gaps >30 days during the first year of drug use. These interrupted drug eras include long-term discontinuations, where the subject never again filled a prescription for any drug in that category in the dataset, which represent 23.7% to 29.1% of all drug eras. Among the prescription-filling patterns without large medication gaps, 0.8% to 1.3% exhibited long-term poor adherence. Our models identified these subjects as early as 60 days after the first prescription fill, with an area under the curve (AUC) of 0.81. Model performance improved as the predictions were made at later time-points, with AUC values increasing to 0.93 at the 120-day time-point.
conclusionsDispensed medication histories (widely available in real time) are useful for alerting providers about poorly adherent patients and those who will be non-adherent several months later. Efforts to use these data in point of care and decision support facilitating patient are warranted.
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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.