Observational studyJournal of general internal medicine2019
Subgroups of High-Cost Medicare Advantage Patients: an Observational Study.
Observational study in Journal of general internal medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Characterizing Cross-Provincial High-Cost Patients in Rural China: Cross-Sectional Study.JMIR public health and surveillance · 2025Article
- Subgroups of High-Cost Patients and Their Preventable Inpatient Cost in Rural China.International journal of health policy and management · 2024Article
- Finding social need-les in a haystack: ascertaining social needs of Medicare patients recorded in the notes of care managers.BMC health services research · 2023Article
- Two-year change in latent classes of comorbidity among high-risk Veterans in primary care: a brief report.BMC health services research · 2022Article
- Temporal Patterns of High-Spend Subgroups Can Inform Service Strategy for Medicare Advantage Enrollees.Journal of general internal medicine · 2022Article
- Exploring Patient Multimorbidity and Complexity Using Health Insurance Claims Data: A Cluster Analysis Approach.JMIR medical informatics · 2022Article
- Characterizing Potentially Preventable Hospitalizations of High-Cost Patients in Rural China.Frontiers in public health · 2022Article
- High-cost high-need patients in Medicaid: segmenting the population eligible for a national complex case management program.BMC health services research · 2021Article
- Simulation-derived best practices for clustering clinical data.Journal of biomedical informatics · 2021Article
- Clustering Complex Chronic Patients: A Cross-Sectional Community Study From the General Practitioner's Perspective.International journal of integrated care · 2021Article
- Article
- Use of Latent Class Analysis and k-Means Clustering to Identify Complex Patient Profiles.JAMA network open · 2020Article
- Potentially Preventable Spending Among High-Cost Medicare Patients: Implications for Healthcare Delivery.Journal of general internal medicine · 2020Article
- 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
- High-Need Phenotypes in Medicare Beneficiaries: Drivers of Variation in Utilization and Outcomes.Journal of the American Geriatrics Society · 2020Article
- Defining 'actionable' high- costhealth care use: results using the Canadian Institute for Health Information population grouping methodology.International journal for equity in health · 2019Article
- High burden of drug therapy in adult congenital heart disease: polypharmacy as marker of morbidity and mortality.European heart journal. Cardiovascular pharmacotherapy · 2019Article
- Applying Machine Learning Algorithms to Segment High-Cost Patient Populations.Journal of general internal medicine · 2019Article
- Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is a growing focus on improving the quality and value of health care delivery for high-cost patients. Compared to fee-for-service Medicare, less is known about the clinical composition of high-cost Medicare Advantage populations.
objectiveTo describe a high-cost Medicare Advantage population and identify clinically and operationally significant subgroups of patients.
designWe used a density-based clustering algorithm to group high-cost patients (top 10% of spending) according to 161 distinct demographic, clinical, and claims-based variables. We then examined rates of utilization, spending, and mortality among subgroups.
participantsSixty-one thousand five hundred forty-six Medicare Advantage beneficiaries. MAIN MEASURES: Spending, utilization, and mortality. KEY
resultsHigh-cost patients (n = 6154) accounted for 55% of total spending. High-cost patients were more likely to be younger, male, and have higher rates of comorbid illnesses. We identified ten subgroups of high-cost patients: acute exacerbations of chronic disease (mixed); end-stage renal disease (ESRD); recurrent gastrointestinal bleed (GIB); orthopedic trauma (trauma); vascular disease (vascular); surgical infections and other complications (complications); cirrhosis with hepatitis C (liver); ESRD with increased medical and behavioral comorbidity (ESRD+); cancer with high-cost imaging and radiation therapy (oncology); and neurologic disorders (neurologic). The average number of inpatient days ranged from 3.25 (oncology) to 26.09 (trauma). Preventable spending (as a percentage of total spending) ranged from 0.8% (oncology) to 9.5% (complications) and the percentage of spending attributable to prescription medications ranged from 7.9% (trauma and oncology) to 77.0% (liver). The percentage of patients who were persistently high-cost ranged from 11.8% (trauma) to 100.0% (ESRD+). One-year mortality ranged from 0.0% (liver) to 25.8% (ESRD+).
conclusionsWe identified clinically distinct subgroups of patients within a heterogeneous high-cost Medicare Advantage population using cluster analysis. These subgroups, defined by condition-specific profiles and illness trajectories, had markedly different patterns of utilization, spending, and mortality, holding important implications for clinical strategy.
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