Study Protocol of a Korean Patient-Centered Shared Decision-Making Model for Management of Severe Knee Osteoarthritis: A Multicenter Pragmatic Clinical Trial (K-SDM-KOA)

Severe knee osteoarthritis (KOA) involves complex, preference-sensitive treatment decisions, ranging from non-operative to surgical options. However, despite the preference-sensitive nature of KOA, existing shared decision-making (SDM) processes often lack clarity in effectively incorporating patients' values and preferences into treatment decisions. Moreover, most SDM models have been developed in western contexts, which may limit their applicability in other cultural settings. To address these limitations, a Korean Shared Decision-Making Model for KOA (K-SDM-KOA) has been developed using a culturally adapted, five-step framework that integrates a web-based decision-support platform and age-friendly educational media. The K-SDM-KOA model is designed to support preference-sensitive decision-making through a pragmatic, multicenter cohort framework involving 1,300 patients with Kellgren-Lawrence grade 3-4 across five hospitals. Within this framework, patients receive either standard care or the K-SDM-KOA intervention, which combines pre-consultation preparation (step 1-3) with in-clinic deliberation and decision-making (step 4-5). The primary outcome is patient-perceived SDM measured using the Korean-validated 9-item Shared Decision Making Questionnaire, reported on a 0-100 scale, with higher scores indicating greater SDM. Secondary outcomes include patients' preferred role in decision-making, decisional conflict, decision regret, and knowledge gain related to KOA. Additionally, a nested cohort of 50 patients undergoing contralateral total knee arthroplasty will provide paired analyses of early pain and function (visual analogue scale, Western Ontario and McMaster Universities Osteoarthritis Index, Knee Society Score) at baseline, 3 months, and 12 months. Analyses will follow an intention-to-treat principle and employ linear mixed-effect models and appropriate statistical tests to assess between group differences. This article presents a culturally tailored, technology-supported SDM model designed to enhance decision quality and early patient-reported outcomes in severe KOA. Findings may provide a foundation for future empirical studies and support the broader adoption of structured SDM in Korea's healthcare system.

Authors

Institutions

Publication Details

Journal
Journal of Korean Medical Science
Published
2026-01-01
DOI
https://doi.org/10.3346/jkms.2026.41.e40
Primary Topic
Patient-Provider Communication in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study Protocol of a Korean Patient-Centered Shared Decision-Making Model for Management of Severe Knee Osteoarthritis: A Multicenter Pragmatic Clinical Trial (K-SDM-KOA)

Do Weon Lee, BI Choi, Moon Jong Chang, Joong Il Kim et al.
Journal of Korean Medical Science
Patient-Provider Communication in Healthcare
article

Study Protocol of a Korean Patient-Centered Shared Decision-Making Model for Management of Severe Knee Osteoarthritis: A Multicenter Pragmatic Clinical Trial (K-SDM-KOA)

Do Weon Lee, BI Choi, Moon Jong Chang, Joong Il Kim, Du hyun Ro, Hyuk-Soo Han, Hyoseon Choi, Sujin Seo, Seong Hwan Kim
article en

Abstract

Severe knee osteoarthritis (KOA) involves complex, preference-sensitive treatment decisions, ranging from non-operative to surgical options. However, despite the preference-sensitive nature of KOA, existing shared decision-making (SDM) processes often lack clarity in effectively incorporating patients' values and preferences into treatment decisions. Moreover, most SDM models have been developed in western contexts, which may limit their applicability in other cultural settings. To address these limitations, a Korean Shared Decision-Making Model for KOA (K-SDM-KOA) has been developed using a culturally adapted, five-step framework that integrates a web-based decision-support platform and age-friendly educational media. The K-SDM-KOA model is designed to support preference-sensitive decision-making through a pragmatic, multicenter cohort framework involving 1,300 patients with Kellgren-Lawrence grade 3-4 across five hospitals. Within this framework, patients receive either standard care or the K-SDM-KOA intervention, which combines pre-consultation preparation (step 1-3) with in-clinic deliberation and decision-making (step 4-5). The primary outcome is patient-perceived SDM measured using the Korean-validated 9-item Shared Decision Making Questionnaire, reported on a 0-100 scale, with higher scores indicating greater SDM. Secondary outcomes include patients' preferred role in decision-making, decisional conflict, decision regret, and knowledge gain related to KOA. Additionally, a nested cohort of 50 patients undergoing contralateral total knee arthroplasty will provide paired analyses of early pain and function (visual analogue scale, Western Ontario and McMaster Universities Osteoarthritis Index, Knee Society Score) at baseline, 3 months, and 12 months. Analyses will follow an intention-to-treat principle and employ linear mixed-effect models and appropriate statistical tests to assess between group differences. This article presents a culturally tailored, technology-supported SDM model designed to enhance decision quality and early patient-reported outcomes in severe KOA. Findings may provide a foundation for future empirical studies and support the broader adoption of structured SDM in Korea's healthcare system.

Journal of Korean Medical ScienceVol. 41(4)
Seoul National University (KR), Hallym University (KR), Chosun University (KR), Seoul Metropolitan Government (KR), Hallym University Kangnam Sacred Heart Hospital (KR), Dongguk University Ilsan Hospital (KR), Chung-Ang University Hospital (KR)
Peace, Justice and strong institutions
Openalex Percentile: Top 94%
Patient-Provider Communication in Healthcare
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.