Validating International Classification of Diseases Code 10th Revision algorithms for accurate identification of pulmonary embolism

Behnood Bikdeli; Candrika D Khairani; Antoine Bejjani; Ying-Chih Lo; Shiwani Mahajan; César Caraballo; Jose Victor Jimenez; Darsiya Krishnathasan; Mehrdad Zarghami; Sina Rashedi; David Jimenez; Stefano Barco; Eric A Secemsky; Frederikus A Klok; Andetta R Hunsaker; Ayaz Aghayev; Alfonso Muriel; Mohamad A Hussain; Abena Appah-Sampong; Yuan Lu; Zhenqiu Lin; Hamid Mojibian; Sanjay Aneja; Rohan Khera; Stavros Konstantinides; Samuel Z Goldhaber; Liqin Wang; Li Zhou; Manuel Monreal; Gregory Piazza; Harlan M Krumholz; PE-EHR+ Investigators

doi:10.1016/j.jtha.2024.10.013

Validating International Classification of Diseases Code 10th Revision algorithms for accurate identification of pulmonary embolism

J Thromb Haemost. 2024 Nov 4:S1538-7836(24)00620-2. doi: 10.1016/j.jtha.2024.10.013. Online ahead of print.

Authors

Behnood Bikdeli¹, Candrika D Khairani², Antoine Bejjani³, Ying-Chih Lo⁴, Shiwani Mahajan⁵, César Caraballo⁶, Jose Victor Jimenez⁷, Darsiya Krishnathasan², Mehrdad Zarghami⁸, Sina Rashedi², David Jimenez⁹, Stefano Barco¹⁰, Eric A Secemsky¹¹, Frederikus A Klok¹², Andetta R Hunsaker¹³, Ayaz Aghayev¹³, Alfonso Muriel¹⁴, Mohamad A Hussain¹⁵, Abena Appah-Sampong¹⁵, Yuan Lu⁷, Zhenqiu Lin⁷, Hamid Mojibian¹⁶, Sanjay Aneja¹⁷, Rohan Khera⁶, Stavros Konstantinides¹⁸, Samuel Z Goldhaber¹⁹, Liqin Wang⁴, Li Zhou⁴, Manuel Monreal²⁰, Gregory Piazza¹⁹, Harlan M Krumholz²¹; PE-EHR+ Investigators

Affiliations

¹ Cardiovascular Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; Thrombosis Research Group, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; YNHH/Yale Center for Outcomes Research and Evaluation, New Haven, Connecticut, USA. Electronic address: [email protected].
² Thrombosis Research Group, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
³ Thrombosis Research Group, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; Department of Internal Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
⁴ Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
⁵ YNHH/Yale Center for Outcomes Research and Evaluation, New Haven, Connecticut, USA; Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
⁶ YNHH/Yale Center for Outcomes Research and Evaluation, New Haven, Connecticut, USA; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
⁷ YNHH/Yale Center for Outcomes Research and Evaluation, New Haven, Connecticut, USA.
⁸ Division of Allergy and Clinical Immunology and Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
⁹ Respiratory Department, Hospital Ramón y Cajal and Medicine Department, Universidad de Alcalá (Instituto de Ramón y Cajal de Investigación Sanitaria), Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Madrid, Spain.
¹⁰ Department of Angiology, University Hospital Zurich, Zurich, Switzerland; Center for Thrombosis and Hemostasis, Johannes Gutenberg University Mainz, Mainz, Germany.
¹¹ Department of Medicine, Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA; Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
¹² Department of Medicine - Thrombosis & Hemostasis, Leiden University Medical Centre, Leiden, The Netherlands.
¹³ Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
¹⁴ Biostatistics Department, Hospital Ramón y Cajal, and Universidad de Alcalá, Madrid, Spain; CIBER de Epidemiología y Salud Pública, Madrid, Spain.
¹⁵ Department of Surgery, Division of Vascular and Endovascular Surgery, Brigham and Women's Hospital/Harvard Medical School, Boston, Massachusetts, USA; Department of Surgery, Center for Surgery and Public Health, Brigham and Women's Hospital/Harvard Medical School, Boston, Massachusetts, USA.
¹⁶ Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, USA.
¹⁷ YNHH/Yale Center for Outcomes Research and Evaluation, New Haven, Connecticut, USA; Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut, USA.
¹⁸ Center for Thrombosis and Hemostasis, Johannes Gutenberg University Mainz, Mainz, Germany; Department of Cardiology, Democritus University of Thrace, Alexandroupolis, Greece.
¹⁹ Cardiovascular Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; Thrombosis Research Group, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
²⁰ Cátedra de Enfermedad Tromboembólica, Universidad Católica de Murcia, Murcia, Spain.
²¹ YNHH/Yale Center for Outcomes Research and Evaluation, New Haven, Connecticut, USA; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA; Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, USA.

PMID: 39505153
DOI: 10.1016/j.jtha.2024.10.013

Abstract

Background: Many research investigations for pulmonary embolism (PE) rely on the International Classification of Diseases 10th Revision (ICD-10) codes for analyses of electronic databases. The validity of ICD-10 codes in identifying PE remains uncertain.

Objectives: The objective of this study was to validate an algorithm to efficiently identify pulmonary embolism using ICD-10 codes.

Methods: Using a prespecified protocol, patients in the Mass General-Brigham hospitals (2016-2021) with ICD-10 principal discharge codes for PE, those with secondary codes for PE, and those without PE codes were identified (n = 578 from each group). Weighting was applied to represent each group proportionate to their true prevalence. The accuracy of ICD-10 codes for identifying PE was compared with adjudication by independent physicians. The F1 score, which incorporates sensitivity and positive predictive value (PPV), was assessed. Subset validation was performed at Yale-New Haven Health System.

Results: A total of 1712 patients were included (age: 60.6 years; 52.3% female). ICD-10 PE codes in the principal discharge position had sensitivity and PPV of 58.3% and 92.1%, respectively. Adding secondary discharge codes to the principal discharge codes improved the sensitivity to 83.2%, but the PPV was reduced to 79.1%. Using a combination of ICD-10 PE principal discharge codes or secondary codes plus imaging codes for PE led to sensitivity and PPV of 81.6% and 84.7%, respectively, and the highest F1 score (83.1%; P < .001 compared with other methods). Validation yielded largely similar results.

Conclusion: Although the principal discharge codes for PE show excellent PPV, they miss 40% of acute PEs. A combination of principal discharge codes and secondary codes plus PE imaging codes led to improved sensitivity without severe reduction in PPV.

Keywords: International Classification of Diseases; accuracy; administrative claims; electronic health records; pulmonary embolism.