Validation of data from electronic data warehouse in diabetic ketoacidosis

Caution is needed

Jennifer VanderWeele, Teresa Pollack, Diana Johnson Oakes, Colleen Smyrniotis, Vidhya Illuri, Priyathama Vellanki, Kevin John O'Leary, Jane Louise Holl, Grazia Aleppo, Mark E Molitch, Amisha Wallia*

*Corresponding author for this work

Research output: Contribution to journalArticle

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 languageEnglish (US)
Pages (from-to)650-654
Number of pages5
JournalJournal of Diabetes and Its Complications
Volume32
Issue number7
DOIs
StatePublished - Jul 1 2018

Fingerprint

Diabetic Ketoacidosis
Electronic Health Records
International Classification of Diseases
Medical Electronics
Clinical Coding
Documentation
Medical Records
Population

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

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. / Validation of data from electronic data warehouse in diabetic ketoacidosis : Caution is needed. In: Journal of Diabetes and Its Complications. 2018 ; Vol. 32, No. 7. pp. 650-654.
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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.",
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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 journalArticle

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.

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KW - Diabetes mellitus

KW - Diabetic ketoacidosis

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KW - Enterprise data warehouse

KW - Medical informatics

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