Current status and prospects of shared decision-making for severe knee osteoarthritis in Korea: a narrative review

Shared decision-making in severe knee osteoarthritis

Article information

J Korean Med Assoc. 2025;68(9):583-592

Publication date (electronic) : 2025 September 10

doi : https://doi.org/10.5124/jkma.25.0093

Byung Sun Choi, MD ¹

, Du Hyun Ro, MD ¹

, Hyoseon Choi, PhD^,²

, Hyuk-Soo Han, MD, PhD^,¹

¹Department of Orthopedic Surgery, Seoul National University College of Medicine, Seoul, Korea

²Department of Medical Education, Kyung Hee University College of Medicine, Seoul, Korea

Corresponding author: Hyuk-Soo Han E-mail: oshawks7@snu.ac.kr

Corresponding author: Hyoseon Choi E-mail: hyoseon.choi@gmail.com

Received 2025 July 7; Accepted 2025 July 29.

Abstract

Purpose

The treatment of severe knee osteoarthritis (KOA) represents a preference-sensitive decision in which the traditional informed consent model is insufficient, particularly within South Korea’s time-constrained clinical setting. This review examines the current status of shared decision-making (SDM) and proposes a strategic framework for a Korean-specific model to strengthen patient-centered care.

Current Concepts

Globally, SDM has been incorporated into healthcare policy and is clinically demonstrated to enhance patient quality of life, satisfaction, and functional outcomes while reducing decision regret. Patient decision aids (PtDAs) are essential evidence-based tools for implementation. A key advancement is the Korean Shared Decision-Making Model for Severe KOA (K-SDM-KOA), which follows a 5-step process and incorporates a pre-consultation web-based PtDA designed to empower patients and optimize limited clinician–patient interaction.

Discussion and Conclusion

Substantial barriers to SDM adoption in Korea remain, including the absence of reimbursement mechanisms, the persistence of a traditionally paternalistic medical culture, and limited clinician training. Addressing these obstacles requires a multi-pronged approach: clinically validating culturally adapted models such as the K-SDM-KOA, integrating SDM training into medical education, establishing reimbursement policies, and applying technologies such as artificial intelligence to create personalized PtDAs. Embedding SDM into clinical practice for severe KOA would mark a paradigm shift from information delivery to genuine partnership, ultimately improving health outcomes and achieving truly patient-centered care.

Keywords: Decision support techniques; Health policy; Knee osteoarthritis; Quality of life; Shared decision-making

Introduction

1. Background

Shared decision-making (SDM) plays a crucial role in the treatment of severe knee osteoarthritis (KOA) because the condition is “preference-sensitive,” meaning that no single treatment option is universally optimal. Choosing between surgical and non-surgical strategies depends on a patient’s individual values, lifestyle, and tolerance for the risks and benefits of each option. The traditional “informed consent” model, where patients passively endorse a physician’s recommendation, is insufficient to safeguard autonomy and ensure satisfaction. By contrast, SDM enables patients to engage actively in the process, aligning treatment decisions with personal preferences and life circumstances.

2. The growing challenge of KOA in an aging society

Korea is rapidly evolving into a super-aged society, which has resulted in a rising prevalence of degenerative diseases and a growing socioeconomic burden [1]. KOA constitutes a major public health issue, with approximately 4 million affected patients reported in 2019. Radiographic signs of KOA are present in 48% of individuals aged 65 years and older [2,3]. The associated pain and functional limitations substantially reduce quality of life while generating high socioeconomic costs through both direct medical expenditures and productivity loss [4].

3. The need for a new decision-making paradigm

The treatment of severe KOA is especially complex because no universally superior option exists, creating the need for a new decision-making approach [5–9]. Broadly, management strategies include non-surgical interventions—such as pharmacologic therapy, intra-articular injections, and physical therapy—and surgical procedures, including osteotomy, unicompartmental knee arthroplasty, and total knee arthroplasty (TKA) [10]. While TKA provides effective pain relief and functional recovery, it is associated with risks such as infection, thrombosis, and anesthesia-related complications [11]. It also requires postoperative rehabilitation, and implant longevity is finite, raising the possibility of revision surgery [12]. Conversely, non-surgical treatments are generally safer but often provide only partial or temporary symptom control [13].

This clinical landscape makes KOA treatment inherently preference-sensitive [10,14]. The optimal choice hinges on patient-specific priorities, such as valuing the definitive pain relief of surgery versus avoiding surgical risks and recovery time [15,16]. Additionally, lifestyle, occupation, family support, and financial resources critically shape treatment decisions [17,18].

4. Limitations of traditional informed consent

The conventional informed consent model proves inadequate in these preference-sensitive scenarios [19]. Although it fulfills legal and ethical obligations for physicians to provide information and for patients to sign a consent form, it does not ensure comprehension or active involvement [20]. Patients often struggle with complex terminology and statistical information, and entrenched power imbalances may lead them to follow physician recommendations passively rather than assert their preferences [19,21]. These limitations are amplified in Korea, where a hierarchical medical culture and “3-minute consultations” are common [22,23]. In such conditions, patients may hesitate to ask questions, defer to medical authority, and risk undermining their right to self-determination, resulting in dissatisfaction or regret with the chosen treatment.

To move beyond the limitations of formal informed consent, a new paradigm is urgently needed: SDM, which places the patient at the center of the decision process.

5. Objectives

This article re-examines the importance of SDM in managing severe KOA and outlines a path toward establishing a Korea-specific SDM model. We critically evaluate policies and clinical practices, analyze the development and effectiveness of patient decision aids (PtDAs), and discuss the clinical, political, and technological challenges that must be overcome to advance a Korean-style SDM framework.

Methods

This study is a narrative review that synthesizes key literature on SDM in the treatment of severe KOA. We performed a literature search across major academic databases, including PubMed, Google Scholar, and Scopus. The search covered publications from 2003 to 2025, using a combination of keywords such as “knee osteoarthritis,” “shared decision-making,” “patient decision aids,” and “preference-sensitive care.”

Inclusion criteria were structured to enable a multi-dimensional and comprehensive analysis. We included: (1) Studies on SDM models and policies related to KOA; (2) Research on the development and effectiveness of PtDAs; (3) Major reviews, clinical trials, and guidelines concerning the clinical application and barriers to SDM.

Policy and Model Developments for SDM in Severe KOA

The growing global interest in SDM has led to the development of various policies and clinical studies in orthopedics, particularly for KOA.

1. SDM policy implementation in KOA

Many countries, including the United Kingdom (UK) and Germany, have adopted policies to promote SDM in healthcare.

1) United Kingdom

The UK’s National Health Service constitution enshrines the right of patients to be involved in all decisions regarding their care. The National Institute for Health and Care Excellence (NICE) has integrated SDM into its clinical guidelines, providing specific recommendations for its use in orthopedic procedures such as knee, hip, and shoulder arthroplasty [24]. NICE guidelines require clinicians to discuss not only the potential benefits and risks of joint replacement but also alternative treatments, the possibility of future surgeries, and details concerning anesthesia and pain management [24].

2) Germany

Germany has also institutionalized SDM policies through legal protections of patients’ rights to autonomous choice. The Innovationsfonds (Innovation Fund) has strongly supported SDM initiatives. A leading example is the “Share to Care” program at Schleswig-Holstein University Hospital (UKSH), which established SDM across the institution. In this program, physicians, nurses, patients, psychologists, and researchers collaboratively created more than 80 PtDAs and developed educational programs for both patients and providers. The program, which includes SDM for KOA, has since been scaled to other regions. Furthermore, the EDELL project piloted the systematic incorporation of SDM elements into 12 to 15 clinical guidelines. These international developments illustrate a global movement toward patient-centered and participatory healthcare.

2. SDM models for KOA

Multiple SDM models have been designed and applied in orthopedics, each offering a distinct framework.

1) Three-talk model

The three-talk model, developed by Elwyn et al. [25], is widely used in orthopedic practice. One study conducted a stepped-wedge clinical trial using the Option Grid, a tool based on this model, to evaluate its effectiveness. In this trial, physical therapists first educated patients with KOA before their physician consultation. Results demonstrated improved observer ratings of decision-making quality (Observer Option scores) and higher patient knowledge scores, with no increase in consultation time. These findings confirm the model’s efficiency and practicality in clinical care.

2) Four-step model

An advanced four-step SDM model, based on Stiggelbout’s work, has been employed in pediatric orthopedics. One study applied this model to young patients with malignant bone tumors of the knee by developing PtDAs and tailored clinical protocols. The modified model enhanced patient participation and reduced decision regret [26].

3) SHARE approach

The SHARE approach, developed by the Agency for Healthcare Research and Quality (AHRQ) in the United States, is another implementation framework designed for use in clinical practice, similar to the three-talk and four-step models. An AHRQ-funded study tested the SHARE model in 2 hospitals to validate its clinical effectiveness. By integrating patient-reported outcome data with patient interviews (n=201), researchers created a machine learning-based predictive tool. When combined with the SHARE model, this approach further enhanced the personalization of care [27].

PtDAs for Severe KOA

PtDAs are an effective and essential tool for facilitating SDM. They are evidence-based resources, such as brochures, videos, and web or mobile applications, designed to support patients in making informed decisions aligned with their personal values [28]. Unlike basic informational leaflets, PtDAs guide patients through a structured process: clarifying the decision at hand, presenting unbiased advantages and disadvantages of all treatment options, and helping patients articulate which outcomes they value most [29].

1. Evidence of PtDA effectiveness

A Cochrane systematic review of 209 randomized controlled trials (RCTs), encompassing more than 30,000 participants, confirmed the effectiveness of PtDAs [30]: (1) Improved knowledge: Patients using PtDAs gained a greater understanding of their condition and treatment options; (2) Accurate risk perception: They estimated potential benefits and risks more accurately; (3) Active participation: They were more likely to engage actively in decision-making; (4) Value-aligned choices: Their treatment decisions more closely reflected their personal values; (5) Reduced decision conflict: They reported lower uncertainty and less internal conflict about treatment choices.

These findings underscore PtDAs as powerful tools for reducing the information asymmetry between clinicians and patients. In Korea’s context of “3-minute consultations,” distributing PtDAs before appointments may offer a practical and efficient means of incorporating SDM into clinical practice [31].

2. Standards and next-generation PtDAs

For a PtDA to be effective, it must meet high standards of quality. The International Patient Decision Aid Standards (IPDAS) collaboration provides rigorous criteria to ensure this quality [32,33]. The IPDAS checklist defines 3 main categories: (1) qualifying: clearly defining the decision, options, and their advantages and disadvantages; (2) certification: transparently disclosing balanced information, evidence sources, and funding; (3) quality: using plain language and keeping the information up-to-date.

Following these criteria, several PtDAs for KOA have been developed and adopted internationally. In the United States, Healthwise created a web-based PtDA that allows patients to compare surgical and non-surgical treatments while ranking outcomes most important to them, such as pain relief or recovery time [34,35]. More advanced PtDAs, such as WiserCare, incorporate artificial intelligence (AI) and machine learning to provide personalized predictive analyses [36]. These tools integrate patient-specific clinical data, health status, and personal preferences to forecast likely functional outcomes or pain reduction with and without surgery. By shifting the focus from generalized averages to individualized predictions, such PtDAs substantially enhance the precision and quality of SDM.

3. Principles for developing a Korean PtDA model

In Korea, the development of KOA PtDAs remains at an early stage and must take into account the distinctive features of the healthcare system, patient literacy levels, and the high proportion of elderly patients. Four guiding principles should inform the design of a successful Korean PtDA:

1) Support pre-consultation review

The PtDA should provide clear information about available treatment options—including benefits and risks—that patients can review with their family or friends before the consultation.

2) Facilitate patient preparation

The PtDA should include functions that help patients prepare for the consultation, such as generating a personalized list of questions for their physician.

3) Offer diverse educational formats

Given the wide variation in digital literacy and health knowledge, especially among older adults, the PtDA should provide multiple formats, including infographics, short videos, and audio support, to improve comprehension.

4) Capture patient preferences

To overcome the limitations of short consultation times, the PtDA should allow patients to record their preferences regarding involvement in decision-making, expectations for treatment, and primary concerns about risks and benefits. This information can then be shared with the physician during the appointment to facilitate a more focused and efficient consultation.

Korean Shared Decision-Making Model for Severe Knee Osteoarthritis (K-SDM-KOA) and PtDA Development

The Korean Shared Decision-Making Model for Severe Knee Osteoarthritis (K-SDM-KOA) was developed specifically to address the challenges of Korea’s healthcare environment (Figure 1). Unlike Western-developed models, the K-SDM-KOA explicitly accounts for short consultation times and the cultural tendency for families to participate in medical decisions.

Figure 1.

Overview of the Korean Shared Decision-Making Model for Severe Knee Osteoarthritis. Steps 1 to 3 occur before the clinic visit: patients use a web-based decision aid, clarify their values and preferences through an electronic checklist, and review educational materials accompanied by an individualized risk-benefit estimate. Steps 4 and 5 unfold during the consultation, where the patient and clinician collaboratively discuss the previously identified preferences and sensitivities. SDM, shared decision-making.

1. The K-SDM-KOA 5-step model

The K-SDM-KOA model is designed to prepare patients ahead of their clinical visit, thereby maximizing the effectiveness of the limited time available during consultation. Its 5 steps are as follows.

1) Choice

Before the consultation, the patient accesses a web-based tool to learn about SDM and the importance of their active role in the process.

2) Preference & value

Using the tool, the patient reflects on and records their values and treatment preferences.

3) Option

The patient reviews the benefits and risks of all available treatments and prepares a list of questions for the physician.

4) Preference & sensitivity

During the consultation, the physician and patient review the patient’s pre-submitted preferences and values from the web tool.

5) Decision

The patient and physician make a final treatment decision together or agree to defer the decision until a future appointment.

This model represents a culturally adapted approach. By moving the information-gathering and initial reflection outside the consultation, the limited in-clinic time can instead be used for an in-depth discussion of the patient’s priorities. It also acknowledges the cultural significance of family involvement in medical decision-making and ensures that patients can prepare their thoughts in advance. The web-based tool provides a practical solution to the constraints of short consultation times and secures the patient’s role as an engaged partner in their care.

Application and Effectiveness of SDM for KOA

The application of SDM in clinical practice for KOA has been shown to improve patient outcomes. Research in this area has steadily increased (Table 1) [36–41], with RCTs providing robust evidence.

Table 1.

Summary of studies on shared decision-making for patients with knee osteoarthritis

1. Evidence from clinical studies

A 2013 RCT involving 123 patients with hip or KOA compared outcomes between an SDM group and a control group [42]. The SDM group received educational materials, including a video and booklet, and worked with a health coach to prepare questions for their physician. (1) Patients in the SDM group reported feeling more informed and confident in their decisions than those in the control group; (2) The proportion of patients choosing surgery was similar between the groups; (3) However, patients in the SDM group asked more appropriate questions and reported higher satisfaction with their care.

Another RCT, the “DECIDE-OA” project, further supported these findings [37]. Patients who made informed, patient-centered decisions through SDM demonstrated significantly higher quality of life, improved knee function scores, greater pain relief, and higher treatment satisfaction at 6 months compared to controls. Importantly, they also reported less decision regret [37].

2. How SDM improves outcomes

These studies indicate that SDM enhances clinical outcomes by aligning treatment decisions with patients’ personal values [37,43]. When patients perceive their choices as respected, they are more likely to engage actively in their care, adhere to treatment plans, hold realistic expectations about outcomes, and experience greater overall satisfaction. This alignment contributes to better clinical results.

For orthopedic surgeons, SDM is an essential clinical competency. Establishing an environment that supports SDM is critical. In Korea, efforts such as the development and validation of the K-SDM-KOA model are intended to provide surgeons with the necessary training and tools to integrate SDM effectively. These initiatives are expected to enhance not only decision quality but also patients’ psychological well-being.

Limitations of SDM in the Korean Healthcare System

Despite growing recognition of its importance, the Korean healthcare system faces substantial barriers to SDM implementation for chronic conditions such as severe KOA. While many physicians believe they already practice SDM, a significant number acknowledge that their approach is inadequate, largely due to a lack of formal training [31]. Barriers can be grouped into 3 domains [44].

1. Institutional factors

The reimbursement system does not adequately compensate for the time and effort required for SDM. Extremely short consultation times further hinder meaningful discussions.

2. Organizational and cultural factors

A hierarchical, physician-centered culture and passive patient attitudes create obstacles. Additionally, most hospitals lack infrastructure and specialized staff to systematically support SDM implementation [45].

3. Individual factors

Many clinicians lack sufficient knowledge of SDM principles and the communication skills required to conduct collaborative discussions with patients.

Conclusion

1. Prospects and development directions for Korean SDM in severe KOA

SDM is a vital, patient-centered strategy that improves treatment satisfaction and clinical outcomes in severe KOA. It is particularly valuable in preference-sensitive decisions where no single “right answer” exists. However, Korea faces persistent challenges to implementation, including short consultation times, inadequate reimbursement mechanisms, and entrenched hierarchical medical culture. To successfully embed SDM into the Korean healthcare system, a comprehensive and multifaceted approach is required.

2. Overcoming barriers and advancing a Korean model

To overcome existing barriers and establish a successful Korean SDM model, efforts are needed in 3 critical domains:

1) First, clinical development

Developing and implementing SDM models and PtDAs that reflect the realities of Korean patients and the healthcare system is essential. Ongoing research, such as the K-SDM-KOA project, plays a pivotal role in empirically demonstrating clinical effectiveness. In parallel, formal training in SDM principles and communication skills—such as role-playing exercises and peer feedback—should be incorporated into medical school curricula, residency training, and continuing education programs for specialists.

2) Second, policy reform

Policy-level reforms are required to create a supportive institutional framework for SDM. Financial compensation represents the strongest incentive for providers. Thus, a dedicated reimbursement code should be established to compensate clinicians for the time and effort devoted to SDM. A relevant benchmark is the Center for Medicare & Medicaid Services Innovation in the United States, which incentivizes institutions to implement SDM for selected conditions [46]. In addition, SDM performance and patient experience should be integrated into hospital accreditation standards and national quality assessment metrics to encourage continuous system-wide improvement.

3) Third, technological innovation

Leveraging advanced technology is key to improving the quality and efficiency of SDM. AI and machine learning tools that analyze patient data, including electronic health records, genomic profiles, and lifestyle information, can generate precise prognostic predictions and recommend optimal treatment pathways [47]. This capability elevates personalized SDM to a new standard. Integrating such PtDAs into hospital electronic medical record systems and patient-facing mobile health applications will ensure seamless accessibility for both patients and clinicians, forming a critical component of the infrastructure required for widespread adoption.

3. Shifting the paradigm

Successfully integrating SDM into the treatment of severe KOA represents more than a refinement in communication; it constitutes a fundamental paradigm shift in healthcare. SDM ensures patients’ rights to self-determination, enhances satisfaction, and promotes treatment adherence, ultimately improving both outcomes and quality of life. The development and validation of models such as the K-SDM-KOA mark the first step. The next stage involves demonstrating their effectiveness and extending their application beyond KOA to primary care, other orthopedic conditions, and a wide range of chronic diseases. This expansion would represent a meaningful advancement toward genuine patient-centered care, a more sustainable healthcare system, and improved public health.

Notes

Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Funding

This research was supported by a Korea Health Technology R&D Project grant through the Patient-Doctor Shared Decision Making Research Center (PDSDM), funded by the Ministry of Health and Welfare, South Korea (grant number: RS-2023-KH142246). The funding body had no role in the study design; data collection, analysis, or interpretation; manuscript preparation; or the decision to submit the work for publication.

Data Availability

Not applicable.

References

1. Baek JY, Lee E, Jung HW, Jang IY. Geriatrics fact sheet in Korea 2021. Ann Geriatr Med Res 2021;25:65–71. 10.4235/agmr.21.0063. 34187140.

2. Hong JW, Noh JH, Kim DJ. The prevalence of and demographic factors associated with radiographic knee osteoarthritis in Korean adults aged ≥ 50 years: the 2010-2013 Korea National Health and Nutrition Examination Survey. PLoS One 2020;15e0230613. 10.1371/journal.pone.0230613. 32196540.

3. Yin X, Deng T, Ma R, et al. Burden, trends, and predictions of five major musculoskeletal disorders in China, Japan, and South Korea: analysis based on the Global Burden of Disease Study 2021. Front Public Health 2025;13:1582618. 10.3389/fpubh.2025.1582618. 40584541.

4. Kloppenburg M, Namane M, Cicuttini F. Osteoarthritis. Lancet 2025;405:71–85. 10.1016/s0140-6736(24)02322-5. 39755397.

5. Kolasinski SL, Neogi T, Hochberg MC, et al. 2019 American College of Rheumatology/Arthritis Foundation Guideline for the management of osteoarthritis of the hand, hip, and knee. Arthritis Care Res (Hoboken) 2020;72:149–162. 10.1002/acr.24131. 31908149.

6. Hunter DJ, Bierma-Zeinstra S. Osteoarthritis. Lancet 2019;393:1745–1759. 10.1016/s0140-6736(19)30417-9. 31034380.

7. Gibbs AJ, Gray B, Wallis JA, et al. Recommendations for the management of hip and knee osteoarthritis: a systematic review of clinical practice guidelines. Osteoarthritis Cartilage 2023;31:1280–1292. 10.1016/j.joca.2023.05.015. 37394226.

8. Bannuru RR, Osani MC, Vaysbrot EE, et al. OARSI guidelines for the non-surgical management of knee, hip, and polyarticular osteoarthritis. Osteoarthritis Cartilage 2019;27:1578–1589. 10.1016/j.joca.2019.06.011. 31278997.

9. Arden NK, Perry TA, Bannuru RR, et al. Non-surgical management of knee osteoarthritis: comparison of ESCEO and OARSI 2019 guidelines. Nat Rev Rheumatol 2021;17:59–66. 10.1038/s41584-020-00523-9.

10. Gökçe Kutsal Y, Eyigör S, Karahan S, et al. Incorporating patient preferences into osteoarthritis treatment. Arch Rheumatol 2021;36:577–586.

11. de Mik SM, Stubenrouch FE, Balm R, Ubbink DT. Systematic review of shared decision-making in surgery. Br J Surg 2018;105:1721–1730. 10.1002/bjs.11009.

12. Konnyu KJ, Thoma LM, Cao W, et al. Rehabilitation for total knee arthroplasty: a systematic review. Am J Phys Med Rehabil 2023;102:19–33. 10.1097/phm.0000000000002008. 35302953.

13. Primorac D, Molnar V, Rod E, et al. Knee osteoarthritis: a review of pathogenesis and state-of-the-art non-operative therapeutic considerations. Genes (Basel) 2020;11:854. 10.3390/genes11080854. 32722615.

14. van der Sluis G, Jager J, Punt I, et al. Current status and future prospects for shared decision making before and after total knee replacement surgery: a scoping review. Int J Environ Res Public Health 2021;18:668. 10.3390/ijerph18020668. 33466879.

15. Barker KL, Toye F, Seers K. A synthesis of qualitative research to understand the complexity behind treatment decision-making for osteoarthritis. Osteoarthr Cartil Open 2023;5:100355. 10.1016/j.ocarto.2023.100355. 37020788.

16. Hutyra CA, Gonzalez JM, Yang JC, et al. Patient preferences for surgical treatment of knee osteoarthritis: a discrete-choice experiment evaluating total and unicompartmental knee arthroplasty. J Bone Joint Surg Am 2020;102:2022–2031.

17. Wang CC, Huang KC, Ku MC, et al. Factors influencing the decision to receive total knee replacement among patients with severe knee osteoarthritis under universal health insurance coverage. Sci Rep 2024;14:30028. 10.1038/s41598-024-81852-7. 39627381.

18. Nicolson PJA, Holden MA. Patient preferences and osteoarthritis care: what do we know about what patients want from osteoarthritis treatment? Curr Treat Options in Rheum 2023;9:120–131. 10.1007/s40674-023-00208-w.

19. Glaser J, Nouri S, Fernandez A, et al. Interventions to improve patient comprehension in informed consent for medical and surgical procedures: an updated systematic review. Med Decis Making 2020;40:119–143. 10.1177/0272989x19896348. 31948345.

20. Whitney SN, McGuire AL, McCullough LB. A typology of shared decision making, informed consent, and simple consent. Ann Intern Med 2004;140:54–59. 10.7326/0003-4819-140-1-200401060-00012.

21. Scherer KA, Büdenbender B, Blum AK, et al. Power asymmetry and embarrassment in shared decision-making: predicting participation preference and decisional conflict. BMC Med Inform Decis Mak 2025;25:120. 10.1186/s12911-025-02938-4.

22. Choi IS, Choi EY, Lee IH. Challenges in informed consent decision-making in Korean clinical research: a participant perspective. PLoS One 2019;14e0216889. 10.1371/journal.pone.0216889. 31120918.

23. Sohn KH, Nam S, Joo J, Kwon YJ, Yim JJ. Patient-centeredness during in-depth consultation in the outpatient clinic of a tertiary hospital in Korea: paradigm shift from disease to patient. J Korean Med Sci 2019;34e119. 10.3346/jkms.2019.34.e119. 31001936.

24. Carmona C, Crutwell J, Burnham M, Polak L. Shared decision-making: summary of NICE guidance. BMJ 2021;373:n1430. 10.1136/bmj.n1430. 34140279.

25. Elwyn G, Pickles T, Edwards A, et al. Supporting shared decision making using an Option Grid for osteoarthritis of the knee in an interface musculoskeletal clinic: a stepped wedge trial. Patient Educ Couns 2016;99:571–577. 10.1016/j.pec.2015.10.011. 26566194.

26. Blom KJ, Bekkering WP, Fiocco M, et al. Shared decision making in primary malignant bone tumour surgery around the knee in children and young adults: protocol for a prospective study. J Orthop Surg Res 2024;19:714. 10.1186/s13018-024-05192-y. 39487545.

27. Lin E, Uhler LM, Finley EP, et al. Incorporating patient-reported outcomes into shared decision-making in the management of patients with osteoarthritis of the knee: a hybrid effectiveness-implementation study protocol. BMJ Open 2022;12e055933. 10.1136/bmjopen-2021-055933. 35190439.

28. Chen O, Ji J, Zeng C, Yang H, Lu Q. Patient decision aids for hip and knee arthroplasty decision-making: a scoping review protocol. BMJ Open 2025;15e089305. 10.1136/bmjopen-2024-089305. 40180380.

29. Coulter A, Stilwell D, Kryworuchko J, et al. A systematic development process for patient decision aids. BMC Med Inform Decis Mak 2013;13 Suppl 2:S2. 10.1186/1472-6947-13-s2-s2. 24625093.

30. O'Connor AM, Stacey D, Entwistle V, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2003;(1):CD001431.

31. Yu BC, Han M, Ko GJ, et al. Effect of shared decision-making education on physicians' perceptions and practices of end-of-life care in Korea. Kidney Res Clin Pract 2022;41:242–252. 10.23876/j.krcp.21.071. 34974652.

32. Rahn AC, Jull J, Boland L, et al. Guidance and/or decision coaching with patient decision aids: scoping reviews to inform the International Patient Decision Aid Standards (IPDAS). Med Decis Making 2021;41:938–953. 10.1177/0272989x21997330. 33759626.

33. Stacey D, Volk RJ. The International Patient Decision Aid Standards (IPDAS) collaboration: evidence update 2.0. Med Decis Making 2021;41:729–733. 10.1177/0272989x211035681.

34. Betz ME, Fowler NR, Meza K, et al. "You just have to be careful how you do it": a qualitative study of the Healthwise decision aid for older drivers. Traffic Inj Prev 2024;25:781–787. 10.1080/15389588.2024.2351203. 38860882.

35. Stacey D, Lewis KB, Smith M, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2024;1:CD001431. 10.1002/14651858.cd001431.pub3.

36. Jayakumar P, Moore MG, Furlough KA, et al. Comparison of an artificial intelligence-enabled patient decision aid vs educational material on decision quality, shared decision-making, patient experience, and functional outcomes in adults with knee osteoarthritis: a randomized clinical trial. JAMA Netw Open 2021;4e2037107. 10.1001/jamanetworkopen.2020.37107.

37. Sepucha KR, Vo H, Chang Y, et al. Shared decision-making is associated with better outcomes in patients with knee but not hip osteoarthritis: the DECIDE-OA randomized study. J Bone Joint Surg Am 2022;104:62–69. 10.2106/JBJS.21.00064. 34437308.

38. Karunaratne S, Horsley M, Solomon M, et al. A Codesigned Patient Decision Aid Supports the Decision Quality of Patients Considering Total Knee Arthroplasty: A Randomized Controlled Trial. J Arthroplasty 2025:S0883-5403(25)00619-9. 10.1016/j.arth.2025.05.104.

39. Lutzner J, Deckert S, Beyer F, et al. Evaluation of a Digital Decision Aid for Knee Replacement Surgery. Dtsch Arztebl Int 2024;121:566–572. 10.3238/arztebl.m2024.0152. 39109409.

40. Bansback N, Trenaman L, MacDonald KV, et al. An online individualised patient decision aid improves the quality of decisions in patients considering total knee arthroplasty in routine care: a randomized controlled trial. Osteoarthr Cartil Open 2022;4:100286. 10.1016/j.ocarto.2022.100286. 36474942.

41. Rivero-Santana A, Torrente-Jimenez RS, Perestelo-Perez L, et al. Effectiveness of a decision aid for patients with knee osteoarthritis: a randomized controlled trial. Osteoarthritis Cartilage 2021;29:1265–1274. 10.1016/j.joca.2021.06.005. 34174455.

42. Bozic KJ, Belkora J, Chan V, et al. Shared decision making in patients with osteoarthritis of the hip and knee: results of a randomized controlled trial. J Bone Joint Surg Am 2013;95:1633–1639. 10.2106/JBJS.M.00004. 24048550.

43. Sepucha K, Bedair H, Yu L, et al. Decision support strategies for hip and knee osteoarthritis: less is more: a randomized comparative effectiveness trial (DECIDE-OA Study). J Bone Joint Surg Am 2019;101:1645–1653.

44. Kim CN, Yoon SJ. Reinforcing primary care in Korea: policy implications, data sources, and research methods. J Korean Med Sci 2025;40e109. 10.3346/jkms.2025.40.e109. 40034094.

45. Yu SY, Lee YE, Shin SJ, et al. Navigating shared decision-making after the life-sustaining treatment decision act: a qualitative study of in-depth interviews with terminal cancer patients, families, and healthcare professionals. Support Care Cancer 2024;32:796. 10.1007/s00520-024-08975-5. 39549104.

46. Matlock DD, Fukunaga MI, Tan A, et al. Enhancing success of Medicare’s shared decision making mandates using implementation science: examples applying the Pragmatic Robust Implementation and Sustainability Model (PRISM). MDM Policy Pract 2020;5:2381468320963070. 10.1177/2381468320963070. 33117890.

47. Kumar V, Patel S, Baburaj V, et al. Current understanding on artificial intelligence and machine learning in orthopaedics: a scoping review. J Orthop 2022;34:201–206. 10.1016/j.jor.2022.08.020. 36104993.

Article information Continued

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Study	Year	Country	Study design	Participants	Intervention	Comparison	Primary outcomes	Key findings
Karunaratne et al. [38]	2025	Australia	Double-blind RCT	216 (total), 173 (analyzed)	Co-designed printed PtDA before consultation	Standard care	Decision quality	OR 3.72 for high-quality decision; less decision conflict; patients felt better informed
Karunaratne et al. [38]	2025	Australia	Double-blind RCT	216 (total), 173 (analyzed)	Co-designed printed PtDA before consultation	Standard care	Decisional conflict
Lutzner et al. [39]	2024	Germany	Stepped-wedge, cluster RCT	1,055	App-based digital decision aid (EKIT tool)+surgeon training	Standard care	Decision quality	86% (vs. 67%) decision quality
Bansback et al. [40]	2022	Canada	Pragmatic RCT	163 (total), 155 (analyzed)	Online, individualized PtDA+surgeon one-page report	Standard care	Decision quality	PtDA group higher decision quality (OR, 2.08)
Sepucha et al. [37]	2022	USA	2×2 multicenter RCT	854 (total), 562 (knee OA)	Video/booklet decision aids+surgeon preference report	Decision aid without report	IPC decision	Knee OA: high IPC decision; better KOOS; higher satisfaction; less regret
Rivero-Santana et al. [41]	2021	Spain	Multicenter RCT	193	Paper PtDA	Standard care	Decisional conflict	Less conflict
Jayakumar et al. [36]	2021	USA	RCT	129	AI-enabled PtDA	Interactive educational video	Decision quality	AI PtDA: better decision quality; higher satisfaction; improved function (KOOS)