Abstract
Aims: This study validated enterprise data warehouse (EDW) data for a cohort of hospitalized patients with a primary diagnosis of diabetic ketoacidosis (DKA). Methods: 247 patients with 319 admissions for DKA (ICD-9 code 250.12, 250.13, or 250.xx with biochemical criteria for DKA) were admitted to Northwestern Memorial Hospital from 1/1/2010 to 9/1/2013. Validation was performed by electronic medical record (EMR) review of 10% of admissions (N = 32). Classification of diabetes type (Type 1 vs. Type 2) and DKA clinical status were compared between the EMR review and EDW data. Results: Key findings included incorrect classification of diabetes type in 5 of 32 (16%) admissions and indeterminable classification in 5 admissions. DKA was not present, based on the review, in 11 of 32 (34%) admissions. DKA was not present, based on biochemical criteria, in 15 of 32 (47%) admissions. Conclusions: This study found that EDW data have substantial errors. Some discrepancies can be addressed by refining the EDW query code, while others, related to diabetes classification and DKA diagnosis, cannot be corrected without improving clinical coding accuracy, consistency of medical record documentation, or EMR design. These results support the need for comprehensive validation of data for complex clinical populations obtained through data repositories such as the EDW.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 650-654 |
| Number of pages | 5 |
| Journal | Journal of Diabetes and Its Complications |
| Volume | 32 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 1 2018 |
Fingerprint
Keywords
- Diabetes mellitus
- Diabetic ketoacidosis
- Electronic medical record
- Enterprise data warehouse
- Medical informatics
ASJC Scopus subject areas
- Internal Medicine
- Endocrinology, Diabetes and Metabolism
- Endocrinology
Cite this
}
Validation of data from electronic data warehouse in diabetic ketoacidosis : Caution is needed. / VanderWeele, Jennifer; Pollack, Teresa; Oakes, Diana Johnson; Smyrniotis, Colleen; Illuri, Vidhya; Vellanki, Priyathama; O'Leary, Kevin John; Holl, Jane Louise; Aleppo, Grazia; Molitch, Mark E; Wallia, Amisha.
In: Journal of Diabetes and Its Complications, Vol. 32, No. 7, 01.07.2018, p. 650-654.Research output: Contribution to journal › Article
TY - JOUR
T1 - Validation of data from electronic data warehouse in diabetic ketoacidosis
T2 - Caution is needed
AU - VanderWeele, Jennifer
AU - Pollack, Teresa
AU - Oakes, Diana Johnson
AU - Smyrniotis, Colleen
AU - Illuri, Vidhya
AU - Vellanki, Priyathama
AU - O'Leary, Kevin John
AU - Holl, Jane Louise
AU - Aleppo, Grazia
AU - Molitch, Mark E
AU - Wallia, Amisha
PY - 2018/7/1
Y1 - 2018/7/1
N2 - Aims: This study validated enterprise data warehouse (EDW) data for a cohort of hospitalized patients with a primary diagnosis of diabetic ketoacidosis (DKA). Methods: 247 patients with 319 admissions for DKA (ICD-9 code 250.12, 250.13, or 250.xx with biochemical criteria for DKA) were admitted to Northwestern Memorial Hospital from 1/1/2010 to 9/1/2013. Validation was performed by electronic medical record (EMR) review of 10% of admissions (N = 32). Classification of diabetes type (Type 1 vs. Type 2) and DKA clinical status were compared between the EMR review and EDW data. Results: Key findings included incorrect classification of diabetes type in 5 of 32 (16%) admissions and indeterminable classification in 5 admissions. DKA was not present, based on the review, in 11 of 32 (34%) admissions. DKA was not present, based on biochemical criteria, in 15 of 32 (47%) admissions. Conclusions: This study found that EDW data have substantial errors. Some discrepancies can be addressed by refining the EDW query code, while others, related to diabetes classification and DKA diagnosis, cannot be corrected without improving clinical coding accuracy, consistency of medical record documentation, or EMR design. These results support the need for comprehensive validation of data for complex clinical populations obtained through data repositories such as the EDW.
AB - Aims: This study validated enterprise data warehouse (EDW) data for a cohort of hospitalized patients with a primary diagnosis of diabetic ketoacidosis (DKA). Methods: 247 patients with 319 admissions for DKA (ICD-9 code 250.12, 250.13, or 250.xx with biochemical criteria for DKA) were admitted to Northwestern Memorial Hospital from 1/1/2010 to 9/1/2013. Validation was performed by electronic medical record (EMR) review of 10% of admissions (N = 32). Classification of diabetes type (Type 1 vs. Type 2) and DKA clinical status were compared between the EMR review and EDW data. Results: Key findings included incorrect classification of diabetes type in 5 of 32 (16%) admissions and indeterminable classification in 5 admissions. DKA was not present, based on the review, in 11 of 32 (34%) admissions. DKA was not present, based on biochemical criteria, in 15 of 32 (47%) admissions. Conclusions: This study found that EDW data have substantial errors. Some discrepancies can be addressed by refining the EDW query code, while others, related to diabetes classification and DKA diagnosis, cannot be corrected without improving clinical coding accuracy, consistency of medical record documentation, or EMR design. These results support the need for comprehensive validation of data for complex clinical populations obtained through data repositories such as the EDW.
KW - Diabetes mellitus
KW - Diabetic ketoacidosis
KW - Electronic medical record
KW - Enterprise data warehouse
KW - Medical informatics
UR - http://www.scopus.com/inward/record.url?scp=85048264427&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048264427&partnerID=8YFLogxK
U2 - 10.1016/j.jdiacomp.2018.05.004
DO - 10.1016/j.jdiacomp.2018.05.004
M3 - Article
VL - 32
SP - 650
EP - 654
JO - Journal of Diabetes and its Complications
JF - Journal of Diabetes and its Complications
SN - 1056-8727
IS - 7
ER -