Dataset Information

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.

ABSTRACT:

Importance

Decision aids can help inform appropriate selection of total knee replacement (TKR) for advanced knee osteoarthritis (OA). However, few decision aids combine patient education, preference assessment, and artificial intelligence (AI) using patient-reported outcome measurement data to generate personalized estimations of outcomes to augment shared decision-making (SDM).

Objective

To assess the effect of an AI-enabled patient decision aid that includes education, preference assessment, and personalized outcome estimations (using patient-reported outcome measurements) on decision quality, patient experience, functional outcomes, and process-level outcomes among individuals with advanced knee OA considering TKR in comparison with education only.

Design, setting, and participants

This randomized clinical trial at a single US academic orthopedic practice included 129 new adult patients presenting for OA-related knee pain from March 2019 to January 2020. Data were analyzed from April to May 2020.

Intervention

Patients were randomized into a group that received a decision aid including patient education, preference assessment, and personalized outcome estimations (intervention group) or a group receiving educational material only (control group) alongside usual care.

Main outcomes and measures

The primary outcome was decision quality, measured using the Knee OA Decision Quality Instrument (K-DQI). Secondary outcomes were collaborative decision-making (assessed using the CollaboRATE survey), patient satisfaction with consultation (using a numerical rating scale), Knee Injury and Osteoarthritis Outcome Score Joint Replacement (KOOS JR) score, consultation time, TKR rate, and treatment concordance.

Results

A total of 69 patients in the intervention group (46 [67%] women) and 60 patients in the control group (37 [62%] women) were included in the analysis. The intervention group showed better decisional quality (K-DQI mean difference, 20.0%; SE, 3.02; 95% CI, 14.2%-26.1%; P?Conclusions and relevanceIn this randomized clinical trial, an AI-enabled decision aid significantly improved decision quality, level of SDM, satisfaction, and physical limitations without significantly impacting consultation times, TKR rates, or treatment concordance in patients with knee OA considering TKR. Decision aids using a personalized, data-driven approach can enhance SDM in the management of knee OA.

Trial registration

ClinicalTrials.gov Identifier: NCT03956004.

SUBMITTER: Jayakumar P

PROVIDER: S-EPMC7893500 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

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.

Jayakumar Prakash P Moore Meredith G MG Furlough Kenneth A KA Uhler Lauren M LM Andrawis John P JP Koenig Karl M KM Aksan Nazan N Rathouz Paul J PJ Bozic Kevin J KJ

JAMA network open 20210201 2

<h4>Importance</h4>Decision aids can help inform appropriate selection of total knee replacement (TKR) for advanced knee osteoarthritis (OA). However, few decision aids combine patient education, preference assessment, and artificial intelligence (AI) using patient-reported outcome measurement data to generate personalized estimations of outcomes to augment shared decision-making (SDM).<h4>Objective</h4>To assess the effect of an AI-enabled patient decision aid that includes education, preferenc ...[more]

PMID: 33599773

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Project description:BackgroundResearch shows that people with stable angina need decision support when considering elective treatments. Initial treatment is with medicines but patients may gain further benefit with invasive percutaneous coronary intervention (PCI). Choosing between these treatments can be challenging for patients because both confer similar benefits but have different risks. Patient decision aids (PtDAs) are evidence-based interventions that support shared decision-making (SDM) when making healthcare decisions. This study aimed to develop and user-test a digital patient decision aid (CONNECT) to facilitate SDM for people with stable angina considering invasive treatment with elective PCI.MethodsA multi-phase study was conducted to develop and test CONNECT (COroNary aNgioplasty dECision Tool) using approaches recommended by the International Patient Decision Aid Standards Collaboration: (i) Steering Group assembled, (ii) review of clinical guidance, (iii) co-design workshops with patients and cardiology health professionals, (iv) first prototype developed and 'alpha' tested (semi-structured cognitive interviews and 12-item acceptability questionnaire) with patients, cardiologists and cardiac nurses, recruited from two hospitals in Northern England, and (v) final PtDA refined following iterative user-feedback. Quantitative data were analysed descriptively and qualitative data from the interviews analysed using deductive content analysis.ResultsCONNECT was developed and user-tested with 34 patients and 29 cardiology health professionals. Findings showed that CONNECT was generally acceptable, usable, comprehensible, and desirable. Participants suggested that CONNECT had the potential to improve care quality by personalising consultations and facilitating SDM and informed consent. Patient safety may be improved as CONNECT includes questions about symptom burden which can identify asymptomatic patients unlikely to benefit from PCI, as well as those who may need to be fast tracked because of worsening symptoms.ConclusionsCONNECT is the first digital PtDA for people with stable angina considering elective PCI, developed in the UK using recommended processes and fulfilling international quality criteria. CONNECT shows promise as an approach to facilitate SDM and should be evaluated in a clinical trial. Further work is required to standardise the provision of probabilistic risk information for people considering elective PCI and to understand how CONNECT can be accessible to underserved communities.

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Dataset Information

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.

Importance

Objective

Design, setting, and participants

Intervention

Main outcomes and measures

Results

Trial registration

Publications

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.

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