COMPARISON OF DIAGNOSIS CODE-BASED DEFINITION AND A CLAIMS-BASED ALGORITHM FOR IDENTIFYING OPIOID USE DISORDER IN KOREA
Author(s)
Yoonjin Lee, BS1, Siin Kim, MS, PharmD, PhD2, Miryoung Kim, PhD3, Hae Sun Suh, MA, MS, PhD4.
1Department of Regulatory Science, Graduate School, Kyunghee university, Seoul, Korea, Republic of, 2College of Pharmacy, Kyungsung University, Busan, Korea, Republic of, 3College of Pharmacy, Sunchon National University, Suncheon-si, Korea, Republic of, 4College of Pharmacy, Kyung Hee University, Seoul, Korea, Republic of.
1Department of Regulatory Science, Graduate School, Kyunghee university, Seoul, Korea, Republic of, 2College of Pharmacy, Kyungsung University, Busan, Korea, Republic of, 3College of Pharmacy, Sunchon National University, Suncheon-si, Korea, Republic of, 4College of Pharmacy, Kyung Hee University, Seoul, Korea, Republic of.
OBJECTIVES: To compare a diagnosis code-based definition with a claims-based algorithm for identifying opioid use disorder (OUD) and examine temporal relationships and subsequent serious adverse events in Korea.
METHODS: A nationwide population-based retrospective cohort study was conducted using the National Health Insurance Service (NHIS) claims database from 2018 to 2024. Patients with opioid prescriptions during the study period were included. OUD was identified using two approaches: ICD-10 F11 diagnosis codes and a claims-based algorithm based on high-risk opioid utilization patterns. The algorithm included shopping, defined as visiting ≥4 different hospitals for opioid prescription within 90 days, and overlap, defined as consecutive prescriptions of the same opioid with ≥25% overlap in days supplied. Serious adverse events included opioid/narcotic poisoning, accidental poisoning, and respiratory failure defined by ICD-10 codes. Among patients identified by both approaches, temporal ordering was assessed using the first F11 diagnosis date and the first date meeting the algorithm.
RESULTS: A total of 483 patients were identified using an F11 diagnosis code, while 377,592 patients met claims-based algorithm during the study period. Among 225 patients identified by both approaches, the algorithm preceded F11 diagnosis in 184 patients, F11 diagnosis preceded in 35 patients, and both occurred on the same date in 6 patients. The mean interval between F11 diagnosis and algorithm date was 546.3 days, indicating earlier identification by the algorithm. Serious adverse events occurred in 35 patients in F11 group (7.2%) and 22,797 patients in the algorithm group (6.0%). The mean interval from OUD detection to serious adverse event was 234 days for the F11 group and 389 days for the algorithm group.
CONCLUSIONS: An F11 diagnosis code identified a much smaller subset of patients than claims-based algorithm. High-risk opioid utilization patterns generally preceded F11 diagnosis, suggesting that claims-based approaches may complement diagnosis-based identification by capturing OUD before formal diagnostic coding.
METHODS: A nationwide population-based retrospective cohort study was conducted using the National Health Insurance Service (NHIS) claims database from 2018 to 2024. Patients with opioid prescriptions during the study period were included. OUD was identified using two approaches: ICD-10 F11 diagnosis codes and a claims-based algorithm based on high-risk opioid utilization patterns. The algorithm included shopping, defined as visiting ≥4 different hospitals for opioid prescription within 90 days, and overlap, defined as consecutive prescriptions of the same opioid with ≥25% overlap in days supplied. Serious adverse events included opioid/narcotic poisoning, accidental poisoning, and respiratory failure defined by ICD-10 codes. Among patients identified by both approaches, temporal ordering was assessed using the first F11 diagnosis date and the first date meeting the algorithm.
RESULTS: A total of 483 patients were identified using an F11 diagnosis code, while 377,592 patients met claims-based algorithm during the study period. Among 225 patients identified by both approaches, the algorithm preceded F11 diagnosis in 184 patients, F11 diagnosis preceded in 35 patients, and both occurred on the same date in 6 patients. The mean interval between F11 diagnosis and algorithm date was 546.3 days, indicating earlier identification by the algorithm. Serious adverse events occurred in 35 patients in F11 group (7.2%) and 22,797 patients in the algorithm group (6.0%). The mean interval from OUD detection to serious adverse event was 234 days for the F11 group and 389 days for the algorithm group.
CONCLUSIONS: An F11 diagnosis code identified a much smaller subset of patients than claims-based algorithm. High-risk opioid utilization patterns generally preceded F11 diagnosis, suggesting that claims-based approaches may complement diagnosis-based identification by capturing OUD before formal diagnostic coding.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
RWD48
Topic
Epidemiology & Public Health, Methodological & Statistical Research, Real World Data & Information Systems
Topic Subcategory
Health & Insurance Records Systems
Disease
Injury & Trauma, Mental Health (including addiction)