Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records
Table 1
List of features and their descriptions in the initial dataset (the dataset is also available at the website of Data Mining and Biomedical Informatics Lab at VCU (http://www.cioslab.vcu.edu/)).
Feature name
Type
Description and values
% missing
Encounter ID
Numeric
Unique identifier of an encounter
0%
Patient number
Numeric
Unique identifier of a patient
0%
Race
Nominal
Values: Caucasian, Asian, African American, Hispanic, and other
Integer identifier corresponding to 9 distinct values, for example, emergency, urgent, elective, newborn, and not available
0%
Discharge disposition
Nominal
Integer identifier corresponding to 29 distinct values, for example, discharged to home, expired, and not available
0%
Admission source
Nominal
Integer identifier corresponding to 21 distinct values, for example, physician referral, emergency room, and transfer from a hospital
0%
Time in hospital
Numeric
Integer number of days between admission and discharge
0%
Payer code
Nominal
Integer identifier corresponding to 23 distinct values, for example, Blue Cross/Blue Shield, Medicare, and self-pay
52%
Medical specialty
Nominal
Integer identifier of a specialty of the admitting physician, corresponding to 84 distinct values, for example, cardiology, internal medicine, family/general practice, and surgeon
53%
Number of lab procedures
Numeric
Number of lab tests performed during the encounter
0%
Number of procedures
Numeric
Number of procedures (other than lab tests) performed during the encounter
0%
Number of medications
Numeric
Number of distinct generic names administered during the encounter
0%
Number of outpatient visits
Numeric
Number of outpatient visits of the patient in the year preceding the encounter
0%
Number of emergency visits
Numeric
Number of emergency visits of the patient in the year preceding the encounter
0%
Number of inpatient visits
Numeric
Number of inpatient visits of the patient in the year preceding the encounter
0%
Diagnosis 1
Nominal
The primary diagnosis (coded as first three digits of ICD9); 848 distinct values
0%
Diagnosis 2
Nominal
Secondary diagnosis (coded as first three digits of ICD9); 923 distinct values
0%
Diagnosis 3
Nominal
Additional secondary diagnosis (coded as first three digits of ICD9); 954 distinct values
1%
Number of diagnoses
Numeric
Number of diagnoses entered to the system
0%
Glucose serum test result
Nominal
Indicates the range of the result or if the test was not taken. Values: “>200,” “>300,” “normal,” and “none” if not measured
0%
A1c test result
Nominal
Indicates the range of the result or if the test was not taken. Values: “>8” if the result was greater than 8%, “>7” if the result was greater than 7% but less than 8%, “normal” if the result was less than 7%, and “none” if not measured.
0%
Change of medications
Nominal
Indicates if there was a change in diabetic medications (either dosage or generic name). Values: “change” and “no change”
0%
Diabetes medications
Nominal
Indicates if there was any diabetic medication prescribed. Values: “yes” and “no”
0%
24 features for medications
Nominal
For the generic names: metformin, repaglinide, nateglinide, chlorpropamide, glimepiride, acetohexamide, glipizide, glyburide, tolbutamide, pioglitazone, rosiglitazone, acarbose, miglitol, troglitazone, tolazamide, examide, sitagliptin, insulin, glyburide-metformin, glipizide-metformin, glimepiride-pioglitazone, metformin-rosiglitazone, and metformin-pioglitazone, the feature indicates whether the drug was prescribed or there was a change in the dosage. Values: “up” if the dosage was increased during the encounter, “down” if the dosage was decreased, “steady” if the dosage did not change, and “no” if the drug was not prescribed
0%
Readmitted
Nominal
Days to inpatient readmission. Values: “<30” if the patient was readmitted in less than 30 days, “>30” if the patient was readmitted in more than 30 days, and “No” for no record of readmission.
