Appl Clin Inform 2015; 06(03): 565-576
DOI: 10.4338/ACI-2015-03-RA-0026
Research Article
Schattauer GmbH

Retrospective Derivation and Validation of an Automated Electronic Search Algorithm to Identify Post operative Cardiovascular and Thromboembolic Complications

M. Tien
1   Mayo Clinic, College of Medicine, Rochester, MN, United States
,
R. Kashyap
2   Mayo Clinic, Department of Anesthesiology, Rochester, MN, United States
,
G. A. Wilson
3   Mayo Clinic, Division of Pulmonary and Critical Care Medicine, Rochester, MN, United States
,
V. Hernandez-Torres
2   Mayo Clinic, Department of Anesthesiology, Rochester, MN, United States
,
A. K. Jacob
2   Mayo Clinic, Department of Anesthesiology, Rochester, MN, United States
,
D. R. Schroeder
4   Mayo Clinic, Health Sciences Research - Biomedical Statistics and Informatics, Rochester, MN, United States
,
C. B. Mantilla
2   Mayo Clinic, Department of Anesthesiology, Rochester, MN, United States
› Author Affiliations
Financial Support and Disclosure The Department of Anesthesiology and Division of Pulmonary and Critical Care Medicine at Mayo Clinic, Rochester, Minnesota supported this work with no direct financial support.
Further Information

Publication History

received: 10 March 2015

accepted in revised form: 28 August 2015

Publication Date:
19 December 2017 (online)

Summary

Background: With increasing numbers of hospitals adopting electronic medical records, electronic search algorithms for identifying postoperative complications can be invaluable tools to expedite data abstraction and clinical research to improve patient outcomes.

Objectives: To derive and validate an electronic search algorithm to identify postoperative thromboembolic and cardiovascular complications such as deep venous thrombosis, pulmonary embolism, or myocardial infarction within 30 days of total hip or knee arthroplasty.

Methods: A total of 34 517 patients undergoing total hip or knee arthroplasty between January 1, 1996 and December 31, 2013 were identified. Using a derivation cohort of 418 patients, several iterations of a free-text electronic search were developed and refined for each complication. Subsequently, the automated search algorithm was validated on an independent cohort of 2 857 patients, and the sensitivity and specificities were compared to the results of manual chart review.

Results: In the final derivation subset, the automated search algorithm achieved a sensitivity of 91% and specificity of 85% for deep vein thrombosis, a sensitivity of 96% and specificity of 100% for pulmonary embolism, and a sensitivity of 100% and specificity of 95% for myocardial infarction. When applied to the validation cohort, the search algorithm achieved a sensitivity of 97% and specificity of 99% for deep vein thrombosis, a sensitivity of 97% and specificity of 100% for pulmonary embolism, and a sensitivity of 100% and specificity of 99% for myocardial infarction.

Conclusions: The derivation and validation of an electronic search strategy can accelerate the data abstraction process for research, quality improvement, and enhancement of patient care, while maintaining superb reliability compared to manual review.

Citation: Tien M, Kashyap R, Wilson GA, Hernandez-Torres V, Jacob AK, Schroeder DR, Mantilla CB. Retrospective Derivation and Validation of an Automated Electronic Search Algorithm to Identify Postoperative Thromboembolic and Cardiovascular Complications. Appl Clin Inform 2015; 6: 565–576

http://dx.doi.org/10.4338/ACI-2015-03-RA-0026