Population:

1
Population Pull all DM ICD9s 2 Visit
criteria for initial DM population That reside in
11county Zip w/research authorization flag
Centerphase Project
Data Quality Project
Filter on ICD9 codes for T2D
Pull anyone with a capillary glucose in last two
years with two inpatient visits. abnormal lab
(serum, fasting, random or HbA1c or existence of
capillary (not a glucose tolerance test nor
part of a pregnancy screen) blood serum as well
as capillary glucose level gt200 mg/dL OR
fasting blood glucose level gt 125 mg/dL OR
(glyco) hemoglobin A1c gt 6.5
Run 500 Sample where age is gt18
Study Coordinator gets list of 500 Clinic Numbers
A/P (Kevin) takes list of 500 Clinic Numbers run
criteria in stages from EMR
Filter out over age 75
Filter out over age 75
Inclusion of Problem list for diabetes
Examine Medications
Have NLP run Medications inc/exc
Inclusion of Medication criteria
Categorize based on Lab Values
Categorize based on Lab Values
Pull all ICD9 Codes (pull all of the coded
problem lists) for this population
Care Manager takes red category and seeks
appointment information
Run compare for red category w/ appt information
From Population Run EDT Query to populate full
data dictionary
Demographics Diagnosis Medications Labs Problem
List
Data available for Data Quality Study
Time Measures Discrepancies
Time Measures Discrepancies
Run compare for 500 Clinic Numbers
Analysis manual vs. EMR electronic method
Gap analysis EMR electronic staged method vs. EDT
1 algorithm method (more like SHARPn)