PuSH - Publikationsserver des Helmholtz Zentrums München: Risk-adjusted capitation payments: How well do principal inpatient diagnosis-based models work in the German situation? Results from a large data set.

Informationen

Hinweise zu Qualitätskriterien von Zeitschriften

Open-Access-Richtlinie der Helmholtz-Gemeinschaft 2016

CC Licencences

Metriken für Publikationen

Navigation

Startseite

English

EVA: Veröffentlichen

Neuer EVA Antrag

Recherche

Erweiterte Suche

Durchblättern nach ...

... HMGU-Autoren/Konsortien

... Organisationsstruktur

... Zeitschriften

... Publikationstypen

... Forschungsdaten

... Arbeitsgruppen

... Erscheinungsjahr

Publikationen im Überblick

Statistik

HGF Fortschrittsbericht

OA Publikationen

Eintragen

Neue Publikation eintragen

Neue Publikation holen aus...

...EVA

Fehlende Publikation melden

Highlights

Suche

Hilfe & Kontakt

Ansprechpartner

Hilfe

Datenschutz

Helmholtz Open Science

Bibliometrische Indikatoren

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

Behrend, C. ; Buchner, F.* ; Happich, M. ; Holle, R. ; Reitmeir, P. ; Wasem, J.*

Risk-adjusted capitation payments: How well do principal inpatient diagnosis-based models work in the German situation? Results from a large data set.

Eur. J. Health Econ. 8, 31-39 (2007)

DOI

PMC

Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.

Abstract
Metriken
Zusatzinfos

Five models of risk adjusters were tested as a (proxy) measure for health status with data from a large German sickness fund. The first two models use standard demographic and socio-demographic variables. One model incorporates a simple binary indicator for hospitalization and the last two are based on the hierarchical coexisting conditions (HCCs: DxCG® Risk Adjustment Software Release 6.1) using in-patient diagnoses. Special investigations were done on the subgroups of insurees who left, joined or stayed with the fund over the observation period. Age and gender grouping accounted for 3.2% of the variation in total expenditure for concurrent as well as prospective models. The current German risk adjusters age, sex, and invalidity status account for 5.1 and 4.5% of the variance in the concurrent and prospective models, respectively. Age, gender, invalidity status and in-patient HCC covariates explain about 37% of the variations of the total expenditures in a concurrent model and roughly 12% of the variations of total expenditures in a prospective model. Only modest improvement can be achieved with the long-term-care (LTC) indicator. For high-risk (cost) groups, substantial under-prediction remains; conversely, for the low-risk group, represented by enrolees who did not show any health care expense in the base year, all of the models over-predict expenditure. Special investigations were done on the subgroups of insurees who left, joined or stayed with the fund over the observation period.

Impact Factor

Scopus SNIP

Scopus
Cited By

Altmetric

0.200

0.000