TMPM.ado: The Trauma Mortality Prediction Model is Robust to ICD-9 and AIS Coding Lexicons
AbstractMany methods have been developed to predict mortality following trauma. Two classification systems are used to provide a taxonomy for diseases, including injuries. The ICD-9 is the classification system for administrative data in the U.S.A. AIS was developed for characterization of injuries alone. The Trauma Mortality Prediction Model (TMPM) is based on empiric estimates of severity for each injury in the ICD-9 and AIS lexicons. Each probability of mortality (POD) is estimated from the five worst injuries per patient. TMPM has been rigorously tested against other mortality prediction models using ICD-9 and AIS data and found superior. The TMPM.ado command allows Stata users to efficiently apply TMPM to data sets using ICD-9 or AIS. The command makes use of model-averaged regression coefficients (MARC) that assign empirically derived severity measures for each of the 1,322 AIS codes and 1,579 ICD-9 injury codes. The injury codes are sorted into body regions then merged with the MARC table to assemble a set of regression coefficients. A logit model is generated to calculate the probability of death. TMPM.ado accommodates either AIS or ICD-9 lexicons from a single command and adds the POD for each patient to the original dataset as a new variable.
Download InfoIf 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.
Bibliographic InfoPaper provided by Stata Users Group in its series SAN12 Stata Conference with number 20.
Date of creation: 01 Aug 2012
Date of revision:
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Christopher F Baum).
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.