Risk-adjusted capitation payments: how well do principal inpatient diagnosis-based models work in the German situation? Results from a large data set
The Risk Adjustment Reform Act of 2001 mandates that a health-status-based risk adjustment mechanism has to be implemented in Germany's Statutory Health Insurance system by January 1, 2007. German parliament decided this as with the existing demographic risk adjustment model, that means there is cream skimming and sickness funds hesitate to engage in managing care for the chronical ill. Four approaches were used to test the feasibility of incorporating use of diagnosis as a proxy measure for health status in a German risk adjustment formula. The first two models used standard demographic and socio-demographic variables. The other two models are separately incorporating a simple binary indicator for hospitilization and Hierarchical Coexisting Conditions (HCCs: DxCG® Risk Adjustment Software Release 6.1) using inpatient diagnosis. Age and gender grouping accounted for 3.2% of the variation in total expenditures 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. There are substantial increases in explanatory power, however, when HCCs are added. Age, gender, invalidity status and 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. For high-risk (cost) groups, substantial underprediction 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.
(This abstract was borrowed from another version of this item.)
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 8 (2007)
Issue (Month): 1 (March)
|Contact details of provider:|| Web page: http://www.springer.com|
|Order Information:||Web: http://www.springer.com/medicine/health+informatics/journal/10198/PS2|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Buchner, Florian & Wasem, Jurgen, 2003. "Needs for further improvement: risk adjustment in the German health insurance system," Health Policy, Elsevier, vol. 65(1), pages 21-35, July.
When requesting a correction, please mention this item's handle: RePEc:spr:eujhec:v:8:y:2007:i:1:p:31-39. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Rebekah McClure)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.