BACKGROUND: Most healthcare costs are concentrated in a small proportion of individuals with complex social, medical, behavioral, and clinical needs that are poorly met by a fee-for-service healthcare system. Efforts to reduce cost in the top decile have shown limited effectiveness. Understanding patient subgroups within the top decile is a first step toward designing more effective and targeted interventions. OBJECTIVE: Segment the top decile based on spending and clinical characteristics and examine the temporal movement of individuals in and out of the top decile. DESIGN: Retrospective claims data analysis. PARTICIPANTS: UnitedHealthcare Medicare Advantage (MA) enrollees (N = 1,504,091) continuously enrolled from 2016 to 2019. MAIN MEASURES: Medical (physician, inpatient, outpatient) and pharmacy claims for services submitted for third-party reimbursement under Medicare Advantage, available as International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and National Drug Codes (NDC) claims. KEY RESULTS: The top decile was segmented into three distinct subgroups characterized by different drivers of cost: (1) Catastrophic: acute events (acute myocardial infarction and hip/pelvic fracture), (2) persistent: medications, and (3) semi-persistent chronic conditions and frailty indicators. These groups show different patterns of spending across time. Each year, 79% of the catastrophic group dropped out of the top decile. In contrast, 68-70% of the persistent group and 36-37% of the semi-persistent group remained in the top decile year over year. These groups also show different 1-year mortality rates, which are highest among semi-persistent members at 17.5-18.5%, compared to 12% and 13-14% for catastrophic and persistent members, respectively. CONCLUSIONS: The top decile consists of subgroups with different needs and spending patterns. Interventions to reduce utilization and expenditures may show more effectiveness if they account for the different characteristics and care needs of these subgroups.
BACKGROUND: Most healthcare costs are concentrated in a small proportion of individuals with complex social, medical, behavioral, and clinical needs that are poorly met by a fee-for-service healthcare system. Efforts to reduce cost in the top decile have shown limited effectiveness. Understanding patient subgroups within the top decile is a first step toward designing more effective and targeted interventions. OBJECTIVE: Segment the top decile based on spending and clinical characteristics and examine the temporal movement of individuals in and out of the top decile. DESIGN: Retrospective claims data analysis. PARTICIPANTS: UnitedHealthcare Medicare Advantage (MA) enrollees (N = 1,504,091) continuously enrolled from 2016 to 2019. MAIN MEASURES: Medical (physician, inpatient, outpatient) and pharmacy claims for services submitted for third-party reimbursement under Medicare Advantage, available as International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and National Drug Codes (NDC) claims. KEY RESULTS: The top decile was segmented into three distinct subgroups characterized by different drivers of cost: (1) Catastrophic: acute events (acute myocardial infarction and hip/pelvic fracture), (2) persistent: medications, and (3) semi-persistent chronic conditions and frailty indicators. These groups show different patterns of spending across time. Each year, 79% of the catastrophic group dropped out of the top decile. In contrast, 68-70% of the persistent group and 36-37% of the semi-persistent group remained in the top decile year over year. These groups also show different 1-year mortality rates, which are highest among semi-persistent members at 17.5-18.5%, compared to 12% and 13-14% for catastrophic and persistent members, respectively. CONCLUSIONS: The top decile consists of subgroups with different needs and spending patterns. Interventions to reduce utilization and expenditures may show more effectiveness if they account for the different characteristics and care needs of these subgroups.
Authors: Brian W Powers; Jiali Yan; Jingsan Zhu; Kristin A Linn; Sachin H Jain; Jennifer L Kowalski; Amol S Navathe Journal: J Gen Intern Med Date: 2018-12-03 Impact factor: 5.128
Authors: Martin A Makary; Dorry L Segev; Peter J Pronovost; Dora Syin; Karen Bandeen-Roche; Purvi Patel; Ryan Takenaga; Lara Devgan; Christine G Holzmueller; Jing Tian; Linda P Fried Journal: J Am Coll Surg Date: 2010-04-28 Impact factor: 6.113
Authors: Peter May; Melissa M Garrido; J Brian Cassel; Amy S Kelley; Diane E Meier; Charles Normand; Lee Stefanis; Thomas J Smith; R Sean Morrison Journal: Health Aff (Millwood) Date: 2016-01 Impact factor: 6.301
Authors: Francesco Gilardi; Paola Scarcella; Maria Grazia Proietti; Giovanni Capobianco; Gennaro Rocco; Alessandra Capanna; Sandro Mancinelli; Maria Cristina Marazzi; Leonardo Palombi; Giuseppe Liotta Journal: Eur J Public Health Date: 2018-10-01 Impact factor: 3.367