Operational Definition Identifying Osteoporotic Vertebral Fractures in the Claims Database

Vertebral fracture (VF) is the most common osteoporotic fracture, that occurs in 30–50% of people aged over 50 years.1, 2, 3, 4, 5 Patients with VF experience marked impairment in mobility and increased mortality; this impairs the patients’ quality-of-life and poses a serious socioeconomic burden on the healthcare system, especially among older adults.4, 6, 7, 8, 9, 10 VF can present with non-specific symptoms or be asymptomatic, thus making clinical detection difficult. The diagnosis of VFs requires spine imaging by lateral radiography. However, it may also be diagnosed by chance on an X-ray requested for other reasons.

Recently, large-scale medical databases have been used for big data research worldwide.5, 6, 11, 12, 13 Medical databases are powerful tools that support clinical and epidemiologic studies of disease burden and treatment outcomes.14, 15, 16, 17, 18, 19, 20, 21, 22 Specifically, a claims database can provide large-scale nationwide information for analysis while also preventing selection bias.14, 15, 17, 23, 24 When properly used, this information allows researchers to simulate predictive scenarios through the use of artificial intelligence such as machine learning and deep learning.25, 26 However, claims databases were established for financial reimbursement and not medical research; therefore, analysis using claims data may be limited due to potential lack of clinical information and possibility of coding errors.5, 20, 27, 28, 29, 30, 31, 32

The lack of details on individual cases, such as VF injury mechanism (i.e., trauma type, osteoporosis), radiographs, and bone mineral density results,20, 28, 29 poses significant limitations on conclusions that may be drawn through analysis using claims database. Among previous studies, osteoporotic VF has had varied definitions when using large-scale medical claim data; there is no standard operational definition for osteoporotic VFs.33, 34, 35 Therefore, researchers should develop algorithms to identify osteoporotic VF prior to the study to reliably validate their operational definitions.23, 36, 37 For this reason, establishing and validating the operational definition of osteoporotic VF is necessary, especially when conducting research using national health claim data.

Here, we analyzed the International Classification of Diseases, 10th edition (ICD-10) diagnostic codes, procedure codes, and radiographic image codes for VF used in the database of Health Insurance Review and Assessment Service (HIRA) of South Korea to establish a validated operational definition for identifying patients with osteoporotic VF in claims data.

This study demonstrated the diagnostic validity of three operational definitions of VFs that were developed to identify osteoporosis-related VFs from the HIRA claims database. The VF operational definitions were based on a combination of diagnosis, procedure and imaging codes from the medical records. And we demonstrated theses operational definitions based on medical records and radiographs. Our operational definition identified patients with osteoporosis-related VF with a high accuracy by combining diagnosis, procedure, and imaging codes.

In our country, the diagnosis code of claim data is assigned according to the importance of treatment or examination during the treatment period. A primary diagnosis is the condition that consumes the most medical resources, especially for newly diagnosed diseases. Secondary, or subordinated, diagnostic codes imply the use of fewer medical resources than those needed for primary diagnoses. For this reason, the order of diagnostic codes is often used as a criterion for developing operational definitions using claims data,39, 40 and classifying the codes as primary or secondary. Additionally, imaging and procedure codes were used along with diagnostic codes to increase the accuracy of the operational definitions.35 Here, we analyzed the operational definition developed using these codes.

To date, various operational definitions have been proposed for the identification of patients with osteoporotic fractures including VF, hip fracture and distal radius fracture.35, 40, 41 Unlike other osteoporotic fractures,40, 41 identification of patients with osteoporosis-related VFs in claims data is challenging because the claims database does not include data on injury mechanism or bone mineral density. Moreover, the patient’s condition often improves with simple conservative treatments, such as prescription pain relievers, precluding the need for specialty treatments such as vertebroplasty or fusion surgery. Moreover, multiple diagnostic codes assigned during follow-up evaluations after the VF are problematic in accurate diagnostic identification though medical records.

Most osteoporotic VFs are treated conservatively, and there is a wide variation in the therapeutic options used and treatment lengths followed by different physicians. Therefore, previous claims database studies, which mainly used diagnosis codes and/or procedure codes, reported inconsistent incidence rates of osteoporotic VFs.18, 28, 35 Thus, diagnostic, imaging, and procedural codes should be combined to enable accurate identification of cases of osteoporotic VF. Furthermore, prior medical history of VF leads to further inconsistency between the true VF rate and the rate of VFs detected by currently used operational definitions; in the currently available literature, most (99.9%) patients who did not have incident VF but had primary or subordinated codes of VF had a previous history of VF (Table 1). In a previous study, the PPV of incident VF using only the diagnostic code was relatively low by 46%; however, it slightly increased to 61% in this study owing to the inclusion of imaging codes.39

There were some limitations to this study. First, we sourced our data from a tertiary referral center, and a substantial number of the selected patients had comorbidities. If patient populations from other institutions were studied, the results could be inconsistent. Therefore, a multi-institutional study that combines a larger population data set from various databases should be conducted in the future to corroborate our results. Second, our operational definitions cannot be generalized to other countries that use different coding systems. Hence, although further validation is needed to translate our approach to other coding systems and study the populations of different countries, our results may serve as a foundation for such studies. Third, the PPV of our operational definition for VF was lower than those reported for hip fracture (59.1–77.4%)41 and wrist fracture (95.6–98.2%).40 Most patients with VF are treated conservatively and visit the outpatient clinic several times during the treatment course; this unique clinical feature may account for this difference.

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. Although the use of three operational definitions could misclassify incident VF, these results may be useful for future observational studies. Additional validation studies that can reduce the effect of confounding factors with improved algorithms and larger datasets should be conducted to corroborate and expand on our findings.