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 Post Operative Cardiovascular and Thromboembolic Complications.
Appl Clin Inform 2015;
6:565-76. [PMID:
26448798 DOI:
10.4338/aci-2015-03-ra-0026]
[Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2015] [Accepted: 07/28/2015] [Indexed: 12/15/2022] Open
Abstract
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.
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