Operational Definition Identifying Osteoporotic Vertebral Fractures in the Claims Database
10.3346/jkms.2022.37.e249
- Author:
Min Heui YU
1
;
Namki HONG
;
Seunghyun LEE
;
Ha-Young KIM
;
Hye-Sun PARK
;
Sang-Min PARK
;
Young-Kyun LEE
;
Tae-Young KIM
;
Yong-Chan HA
;
Yumie RHEE
;
Kyung-Hoi KOO
Author Information
1. Department of Internal Medicine, Endocrine Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
- Publication Type:Original Article
- From:Journal of Korean Medical Science
2022;37(32):e249-
- CountryRepublic of Korea
- Language:English
-
Abstract:
Background:We analyzed the International Classification of Diseases, 10th edition (ICD-10) diagnostic codes, procedure codes, and radiographic image codes for vertebral fracture (VF) used in the database of Health Insurance Review and Assessment Service (HIRA) of Korea to establish a validated operational definition for identifying patients with osteoporotic VF in claims data.
Methods:We developed three operational definitions for detecting VFs using 9 diagnostic codes, 5 procedure codes and 4 imaging codes. Medical records and radiographs of 2,819 patients, who had primary and subordinated codes of VF between January 2016 and December 2016 at two institutions, were reviewed to detect true vertebral fractures. We evaluated the sensitivity and positive predictive value (PPV) of the operational definition in detecting true osteoporotic VF and obtained the receiver operating characteristic (ROC) curve.
Results:Among the 2,819 patients who had primary or secondary diagnosis codes for VF, 995 patients satisfied at least one of the criteria for the operational definition of osteoporotic VF. Of these patients, 594 were judged as having true fractures based on medical records and radiographic examinations. The sensitivity and PPV were 62.5 (95% confidence interval [CI], 59.4–65.6) and 59.7(95% CI, 56.6–62.8) respectively. In the receiver operating characteristic analysis, area under the curve (AUC) was 0.706 (95% CI, 0.688–0.724).
Conclusion:Our findings demonstrate the validity of our operational definitions to identify VFs more accurately using claims data. This algorithm to identify VF is likely to be useful in future studies for diagnosing osteoporotic VF.
