ArticleJournal of general internal medicine2017
High-Cost Patients: Hot-Spotters Don't Explain the Half of It.
Article in Journal of general internal medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.
What it found
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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
39 citing papers in PubMed, 1 synthesis or guideline pooled it, 82 citations in OpenAlex.
- Pooled it
- Impact of Referring High-Risk Patients to Intensive Outpatient Primary Care Services: A Propensity Score-Matched Analysis.Journal of general internal medicine · 2025Trial
- Lessons learned from a trial on integrated and proactive care for patients with complex needs (Hotspotters project): a process evaluation.medRxiv : the preprint server for health sciences · 2026Article
- The perceptions of Dutch general practitioners on the implementation of a proactive integrated care approach for patients with complex needs: a pilot survey.BMC primary care · 2026Article
- Performance of 2-stage health-related social needs screening using area-level measures.The American journal of managed care · 2025Article
- Article
- 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
- Characterizing hospitalization trajectories in the high-need, high-cost population using electronic health record data.Health affairs scholar · 2023Article
- Cluster Analysis of the Highest Users of Medical, Behavioral Health, and Social Services in San Francisco.Journal of general internal medicine · 2023Article
- Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets.Health economics review · 2023Article
- Analysis of Emergency Department Encounters Among High Users of Health Care and Social Service Systems Before and During the COVID-19 Pandemic.JAMA network open · 2022Article
- Improving the Prediction of Persistent High Health Care Utilizers: Retrospective Analysis Using Ensemble Methodology.JMIR medical informatics · 2022Article
- Optimizing care coordination to address social determinants of health needs for dual-use veterans.BMC health services research · 2022Article
- Characteristics and resource utilization of high-cost users in the intensive care unit: a population-based cohort study.BMC health services research · 2021Article
- Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data.JMIR medical informatics · 2021Article
- Outcomes of a randomized quality improvement trial for high-risk Veterans in year two.Health services research · 2021Article
- Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management.JAMIA open · 2021Article
- Super fragmented: a nationally representative cross-sectional study exploring the fragmentation of inpatient care among super-utilizers.BMC health services research · 2021Article
- Predicting Individual Risk of Emergency Hospital Admissions - A Retrospective Validation Study.Risk management and healthcare policy · 2021Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundUnderstanding resource utilization patterns among high-cost patients may inform cost reduction strategies.
objectiveTo identify patterns of high-cost healthcare utilization and associated clinical diagnoses and to quantify the significance of hot-spotters among high-cost users.
designRetrospective analysis of high-cost patients in 2012 using data from electronic medical records, internal cost accounting, and the Centers for Medicare and Medicaid Services. K-medoids cluster analysis was performed on utilization measures of the highest-cost decile of patients. Clusters were compared using clinical diagnoses. We defined "hot-spotters" as those in the highest-cost decile with ≥4 hospitalizations or ED visits during the study period. PARTICIPANTS AND EXPOSURE: A total of 14,855 Medicare Fee-for-service beneficiaries identified by the Medicare Quality Resource and Use Report as having received 100 % of inpatient care and ≥90 % of primary care services at Cleveland Clinic Health System (CCHS) in Northeast Ohio. The highest-cost decile was selected from this population. MAIN MEASURES: Healthcare utilization and diagnoses. KEY
resultsThe highest-cost decile of patients (n = 1486) accounted for 60 % of total costs. We identified five patient clusters: "Ambulatory," with 0 admissions; "Surgical," with a median of 2 surgeries; "Critically Ill," with a median of 4 ICU days; "Frequent Care," with a median of 2 admissions, 3 ED visits, and 29 outpatient visits; and "Mixed Utilization," with 1 median admission and 1 ED visit. Cancer diagnoses were prevalent in the Ambulatory group, care complications in the Surgical group, cardiac diseases in the Critically Ill group, and psychiatric disorders in the Frequent Care group. Most hot-spotters (55 %) were in the "frequent care" cluster. Overall, hot-spotters represented 9 % of the high-cost population and accounted for 19 % of their overall costs.
conclusionsHigh-cost patients are heterogeneous; most are not so-called "hot-spotters" with frequent admissions. Effective interventions to reduce costs will require a more multi-faceted approach to the high-cost population.
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