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Using exogenous organizational and regional hospital attributes to explain differences in case-mix adjusted hospital costs.
Havranek, Michael M; Ondrej, Josef; Widmer, Philippe K; Bollmann, Stella; Spika, Simon; Boes, Stefan.
Afiliação
  • Havranek MM; Competence Center for Health Data Science, Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland.
  • Ondrej J; Competence Center for Health Data Science, Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland.
  • Widmer PK; Spital Limmattal Zurich, Zurich, Switzerland.
  • Bollmann S; Competence Center for Health Data Science, Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland.
  • Spika S; University Hospital Zurich, Zurich, Switzerland.
  • Boes S; Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland.
Health Econ ; 32(8): 1733-1748, 2023 Aug.
Article em En | MEDLINE | ID: mdl-37057301
Diagnosis-related group (DRG) hospital reimbursement systems differentiate cases into cost-homogenous groups based on patient characteristics. However, exogenous organizational and regional factors can influence hospital costs beyond case-mix differences. Therefore, most countries using DRG systems incorporate adjustments for such factors into their reimbursement structure. This study investigates structural hospital attributes that explain differences in average case-mix adjusted hospital costs in Switzerland. Using rich patient and hospital-level data containing 4 million cases from 120 hospitals across 3 years, we show that a regression model using only five variables (number of discharges, ratio of emergency/ambulance admissions, rate of DRGs to patients, expected loss potential based on DRG mix, and location in large agglomeration) can explain more than half of the variance in average case-mix adjusted hospital costs, capture all cost variations across commonly differentiated hospital types (e.g., academic teaching hospitals, children's hospitals, birth centers, etc.), and is robust in cross-validations across several years (despite differing hospital samples). Based on our findings, we propose a simple practical approach to differentiate legitimate from inefficiency-related or unexplainable cost differences across hospitals and discuss the potential of such an approach as a transparent way to incorporate structural hospital differences into cost benchmarking and payment schemes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation / Prognostic_studies Limite: Child / Humans País/Região como assunto: Europa Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation / Prognostic_studies Limite: Child / Humans País/Região como assunto: Europa Idioma: En Ano de publicação: 2023 Tipo de documento: Article