Ressourcenverbrauch stationärer Episoden bei depressiven Störungen. Eine Analyse aus Sicht der Krankenkassen
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Ressourcenverbrauch stationärer Episoden bei depressiven Störungen. Eine Analyse aus Sicht der Krankenkassen. / Stamm, K; Salize, H J; Härter, M; Brand, S; Sitta, P; Berger, M; Gaebel, W; Schneider, F.
In: NERVENARZT, Vol. 78, No. 6, 06.2007, p. 665-71.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Ressourcenverbrauch stationärer Episoden bei depressiven Störungen. Eine Analyse aus Sicht der Krankenkassen
AU - Stamm, K
AU - Salize, H J
AU - Härter, M
AU - Brand, S
AU - Sitta, P
AU - Berger, M
AU - Gaebel, W
AU - Schneider, F
PY - 2007/6
Y1 - 2007/6
N2 - BACKGROUND: Inpatient treatment is the most costly sector of treatment for depressive disorders in Germany. However, little is known about which patient and hospital characteristics contribute to costs of inpatient episodes.PATIENTS AND METHODS: To take part in this study, patients had to fullfill criteria for ICD-10 diagnosis of F31.3-F31.5, F32, F33, F34.1, F43.20, or F43.21. Episodes were recorded between September 9 2001 and March 3 2003 in ten hospitals in three German states. Inpatient records of 1,202 persons were analysed. Multiple regression analysis was performed to identify significant patient predictors of cost per inpatient episode, and the predictive function of hospital characteristics was analysed by applying hierarchical linear modeling.RESULTS: Patient characteristics at admission could not explain a substantial part of the variance in episode costs. Better prediction was possible including variables from the whole treatment process. Also, conditions for admission and patient-related factors did not well explain cost differences between hospitals, but characteristics of the whole treatment were.CONCLUSION: For predicting costs of inpatient depressive episodes, the complete course treatment has to be considered. As in the physiologic sector, therapeutic and diagnostic procedures have a great effect on cost prediction.
AB - BACKGROUND: Inpatient treatment is the most costly sector of treatment for depressive disorders in Germany. However, little is known about which patient and hospital characteristics contribute to costs of inpatient episodes.PATIENTS AND METHODS: To take part in this study, patients had to fullfill criteria for ICD-10 diagnosis of F31.3-F31.5, F32, F33, F34.1, F43.20, or F43.21. Episodes were recorded between September 9 2001 and March 3 2003 in ten hospitals in three German states. Inpatient records of 1,202 persons were analysed. Multiple regression analysis was performed to identify significant patient predictors of cost per inpatient episode, and the predictive function of hospital characteristics was analysed by applying hierarchical linear modeling.RESULTS: Patient characteristics at admission could not explain a substantial part of the variance in episode costs. Better prediction was possible including variables from the whole treatment process. Also, conditions for admission and patient-related factors did not well explain cost differences between hospitals, but characteristics of the whole treatment were.CONCLUSION: For predicting costs of inpatient depressive episodes, the complete course treatment has to be considered. As in the physiologic sector, therapeutic and diagnostic procedures have a great effect on cost prediction.
KW - Adolescent
KW - Adult
KW - Aged
KW - Aged, 80 and over
KW - Costs and Cost Analysis
KW - Depressive Disorder
KW - Episode of Care
KW - Female
KW - Germany
KW - Health Care Costs
KW - Health Resources
KW - Hospitalization
KW - Humans
KW - Linear Models
KW - Male
KW - Middle Aged
KW - National Health Programs
KW - Statistics as Topic
KW - Total Quality Management
KW - English Abstract
KW - Journal Article
U2 - 10.1007/s00115-006-2115-x
DO - 10.1007/s00115-006-2115-x
M3 - SCORING: Zeitschriftenaufsatz
C2 - 16821064
VL - 78
SP - 665
EP - 671
JO - NERVENARZT
JF - NERVENARZT
SN - 0028-2804
IS - 6
ER -