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Characteristics and healthcare utilisation patterns of high-cost beneficiaries in the Netherlands: a cross-sectional claims database study

OBJECTIVE: To determine medical needs, demographic characteristics and healthcare utilisation patterns of the top 1% and top 2%–5% high-cost beneficiaries in the Netherlands. DESIGN: Cross-sectional study using 1 year claims data. We broke down high-cost beneficiaries by demographics, the most cost-...

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Detalles Bibliográficos
Autores principales: Wammes, Joost Johan Godert, Tanke, Marit, Jonkers, Wilma, Westert, Gert P, Van der Wees, Philip, Jeurissen, Patrick PT
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5695517/
https://www.ncbi.nlm.nih.gov/pubmed/29133323
http://dx.doi.org/10.1136/bmjopen-2017-017775
Descripción
Sumario:OBJECTIVE: To determine medical needs, demographic characteristics and healthcare utilisation patterns of the top 1% and top 2%–5% high-cost beneficiaries in the Netherlands. DESIGN: Cross-sectional study using 1 year claims data. We broke down high-cost beneficiaries by demographics, the most cost-incurring condition per beneficiary and expensive treatment use. SETTING: Dutch curative health system, a health system with universal coverage. PARTICIPANTS: 4.5 million beneficiaries of one health insurer. MEASURES: Annual total costs through hospital, intensive care unit use, expensive drugs, other pharmaceuticals, mental care and others; demographics; most cost-incurring and secondary conditions; inpatient stay; number of morbidities; costs per ICD10-chapter (International Statistical Classification of Diseases, 10th revision); and expensive treatment use (including dialysis, transplant surgery, expensive drugs, intensive care unit and diagnosis-related groups >€30 000). RESULTS: The top 1% and top 2%–5% beneficiaries accounted for 23% and 26% of total expenditures, respectively. Among top 1% beneficiaries, hospital care represented 76% of spending, of which, respectively, 9.0% and 9.1% were spent on expensive drugs and ICU care. We found that 54% of top 1% beneficiaries were aged 65 years or younger and that average costs sharply decreased with higher age within the top 1% group. Expensive treatments contributed to high costs in one-third of top 1% beneficiaries and in less than 10% of top 2%–5% beneficiaries. The average number of conditions was 5.5 and 4.0 for top 1% and top 2%–5% beneficiaries, respectively. 53% of top 1% beneficiaries were treated for circulatory disorders but for only 22% of top 1% beneficiaries this was their most cost-incurring condition. CONCLUSIONS: Expensive treatments, most cost-incurring condition and age proved to be informative variables for studying this heterogeneous population. Expensive treatments play a substantial role in high-costs beneficiaries. Interventions need to be aimed at beneficiaries of all ages; a sole focus on the elderly would leave many high-cost beneficiaries unaddressed. Tailored interventions are needed to meet the needs of high-cost beneficiaries and to avoid waste of scarce resources.