ArticleProceedings of the ... International Florida AI Research Society Conference. Florida AI Research Symposium2016
Examining Healthcare Utilization Patterns of Elderly Middle-Aged Adults in the United States.
Article in Proceedings of the ... International Florida AI Research Society Conference. Florida AI Research Symposium, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
30 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Effectiveness of Digital Interventions to Increase Preventive Care Uptake in Older Adults: Systematic Review.JMIR aging · 2026Pooled it
- Interventions to Reduce Hospital Readmissions in Older African Americans: A Systematic Review of Studies Including African American Patients.Journal of racial and ethnic health disparities · 2023Pooled it
- Patient and System Factors Associated with Second-generation Antipsychotic Metabolic Lab Monitoring, a Retrospective Cohort Study.Community mental health journal · 2026Article
- Maximizing benefits from evidence-based psychological treatments: Memory support and habit formation as key strategies.Behaviour research and therapy · 2025Review
- Accuracy of Artificial Intelligence for Gatekeeping in Referrals to Specialized Care.JAMA network open · 2025Article
- Healthcare utilisation patterns and contributory factors among middle-aged adults: a scoping review.Journal of health, population, and nutrition · 2024Article
- Article
- Health care utilization and behavior changes after workplace genetic testing at a large US health care system.Genetics in medicine : official journal of the American College of Medical Genetics · 2024Article
- Understanding categories of postpartum care use among privately insured patients in the United States: a cluster-analytic approach.Health affairs scholar · 2023Article
- Subtypes of the psychedelic experience have reproducible and predictable effects on depression and anxiety symptoms.Journal of affective disorders · 2023Article
- Geriatric Telehealth: A Standardized Patient Case for Medical Students.MedEdPORTAL : the journal of teaching and learning resources · 2023Article
- Identifying common patterns of health services use: a longitudinal study of older Swiss adults' care trajectories.BMC health services research · 2022Article
- Potentially Inappropriate Medication Use in Patients with Dementia.International journal of environmental research and public health · 2022Article
- Development of dynamic health care delivery heatmaps for end-of-life cancer care: a cohort study.BMJ open · 2022Article
- Clinician knowledge and behaviors related to the 4Ms framework of Age-Friendly Health Systems.Journal of the American Geriatrics Society · 2022Article
- Undiagnosed Dementia Is Associated with Poor Physical Function in Older Adults.Journal of Alzheimer's disease : JAD · 2022Article
- Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data.JMIR medical informatics · 2021Article
- Personal Health Information Management Among Older Adults: Scoping Review.Journal of medical Internet research · 2021Article
- Article
- Older adults' personal health information management: The role and perspective of various healthcare providers.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Elderly patients, aged 65 or older, make up 13.5% of the U.S. population, but represent 45.2% of the top 10% of healthcare utilizers, in terms of expenditures. Middle-aged Americans, aged 45 to 64 make up another 37.0% of that category. Given the high demand for healthcare services by the aforementioned population, it is important to identify high-cost users of healthcare systems and, more importantly, ineffective utilization patterns to highlight where targeted interventions could be placed to improve care delivery. In this work, we present a novel multi-level framework applying machine learning (ML) methods (i.e., random forest regression and hierarchical clustering) to group patients with similar utilization profiles into clusters. We use a vector space model to characterize a patient's utilization profile as the number of visits to different care providers and prescribed medications. We applied the proposed methods using the 2013 Medical Expenditures Panel Survey (MEPS) dataset. We identified clusters of healthcare utilization patterns of elderly and middle-aged adults in the United States, and assessed the general and clinical characteristics associated with these utilization patterns. Our results demonstrate the effectiveness of the proposed framework to model healthcare utilization patterns. Understanding of these patterns can be used to guide healthcare policy-making and practice.
Identifiers
27430035PMC4946167What OpenQuestion holds
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.