SAS Code and associated documents for calculating the PMCA.
Reference: Pediatric Medical Complexity Algorithm: A New Method to Stratify Children by Medical Complexity, Tamara D. Simon, Mary Lawrence Cawthon, Susan Stanford, Jean Popalisky, Dorothy Lyons, Peter Woodcox, Margaret Hood, Alex Y. Chen and Rita Mangione-Smith, Pediatrics; originally published online May 12, 2014; DOI: 10.1542/peds.2013-3875
As of release v3.2.0, this repo contains an implementation of the PMCA in R. It is important to know that this code:
- has not been validated
- was not tested by me (@kaiser-roy), and
- has thus far not been updated since v3.2.0
Please get in touch with the author listed in that file's header for support.
(Mostly a note-to-self)
Rita will occasionally send an xlsx of new dx codes, along with yes-or-no include decisions, body systems & progressive-or-not information. When that happens, the steps for updating the %pmca macro are:
- copy the
%classify_dx
macro out of pmca.sas and into classify_dx.sas (to make absolutely sure you're working with the most recent version). - Take the no-diagnoses and append them to the end of the
s.dont_want
input datastep in test_classify_dx.sas. - Take the yes-diagnoses and append those to the end of
s.do_want
. - Run test_classify_dx.sas and note the deficiencies listed in the test_classify_dx.html output.
- Edit classify_dx.sas until there are no more deficiencies
- Copy
%classify_dx
out of classify_dx.sas and paste it over top of the one in pmca.sas - Commit/tag/push & inform Rita the update is done.