Development and validation of a structured query language implementation of the Elixhauser comorbidity index.
OBJECTIVE
Comorbidity adjustment is often performed during outcomes and health care resource utilization research. Our goal was to develop an efficient algorithm in structured query language (SQL) to determine the Elixhauser comorbidity index.


METHODS
We wrote an SQL algorithm to calculate the Elixhauser comorbidities from Diagnosis Related Group and International Classification of Diseases (ICD) codes. Validation was by comparison to expected comorbidities from combinations of these codes and to the 2013 Nationwide Readmissions Database (NRD).


RESULTS
The SQL algorithm matched perfectly with expected comorbidities for all combinations of ICD-9 or ICD-10, and Diagnosis Related Groups. Of 13 585 859 evaluable NRD records, the algorithm matched 100% of the listed comorbidities. Processing time was ∼0.05 ms/record.


CONCLUSIONS
The SQL Elixhauser code was efficient and computationally identical to the SAS algorithm used for the NRD.


CONCLUSIONS
This algorithm may be useful where preprocessing of large datasets in a relational database environment and comorbidity determination is desired before statistical analysis. A validated SQL procedure to calculate Elixhauser comorbidities and the van Walraven index from ICD-9 or ICD-10 discharge diagnosis codes has been published.
Department of Anesthesiology, Perioperative Medicine and Pain Management, University of Miami, Miami, FL, USA.
Richard H
RH
Epstein
Division of Management Consulting, Department of Anesthesia, University of Iowa, Iowa City, IA, USA.
Franklin
F
Dexter
D000465:Algorithms; D015897:Comorbidity; D019992:Databases as Topic; D006760:Hospitalization; D006801:Humans; D011381:Programming Languages; D012984:Software
algorithms; comorbidity; computing methodologies; software validation