Background: Total knee replacement (TKR) is one of the most commonly performed routine procedures in the world. Prognostic studies indicate that the number of TKR will further increase constituting growing burden on healthcare systems. There is also substantial regional heterogeneity in TKR rates within and between countries. Despite the known therapeutic effects, a subset of patients undergoing TKR does not benefit from the procedure as intended. To improve the appropriateness of TKR indication, the EKIT initiative ("evidence and consensus based indication critera for total arthroplasty") developed a clinical guideline for Germany on the indication of TKR. This guideline is the basis for a digital medical decision aid (EKIT tool) to facilitate shared decision making (SDM) in order to improve decision quality for elective surgery. The aim of this cluster randomized trial is to investigate the effectiveness of the EKIT tool on decision quality.

Methods: The Value-based TKR study is a prospective pragmatic multi-center, stepped wedge, cluster randomized controlled trial (SW-RCT). The EKIT tool provides (1) a systematic presentation of individual patient and disease-specific information (symptoms, expectations), (2) the fulfillment of the indication criteria and (3) health information about safety and effectiveness of TKR. All study sites will follow routine care as control clusters until the start of the intervention. In total, there will be 10 clusters (study sites) and 6 sequential steps over 16 month, with clusters receiving the intervention with a minimum 2 months of standard routine care. The primary outcome is patients' decision quality measured with the Decision Quality Instrument (DQI)-Knee Osteoarthritis questionnaire. Furthermore, we will collect information on global patient satisfaction, patient reported outcome measures and the fulfilment of the individual expectations 12 months after SDM. The power calculation yielded an estimated power of 89% using robust Poisson regression under the following assumptions: 10 study sites with a total of N=1,080 patients (including a dropout rate of 11%), a 10% increase in decision quality due to the use of the EKIT tool, and a significance level of 5%.

Discussion: There is a high potential for transferring the intervention into routine practice if the evaluation is positive.

Trial Registration: ClinicalTrials.gov: NCT04837053 . Registered on 08/04/2021.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8436461PMC
http://dx.doi.org/10.1186/s12891-021-04546-5DOI Listing

Publication Analysis

Top Keywords

ekit tool
16
decision quality
16
tkr study
12
cluster randomized
12
study sites
12
tkr
9
decision aid
8
total knee
8
knee replacement
8
value-based tkr
8

Similar Publications

Background: We studied whether an individualized digital decision aid can improve decision-making quality for or against knee arthroplasty.

Methods: An app-based decision aid (EKIT tool) was developed and studied in a stepped-wedge, cluster-randomized trial. Consecutive patients with knee osteoarthritis who were candidates for knee replacement were included in 10 centers in Germany.

View Article and Find Full Text PDF

Background: Total knee replacement (TKR) is one of the most commonly performed routine procedures in the world. Prognostic studies indicate that the number of TKR will further increase constituting growing burden on healthcare systems. There is also substantial regional heterogeneity in TKR rates within and between countries.

View Article and Find Full Text PDF

To end the largest known outbreak of Ebola virus disease (EVD) in West Africa and to prevent new transmissions, rapid epidemiological tracing of cases and contacts was required. The ability to quickly identify unknown sources and chains of transmission is key to ending the EVD epidemic and of even greater importance in the context of recent reports of Ebola virus (EBOV) persistence in survivors. Phylogenetic analysis of complete EBOV genomes can provide important information on the source of any new infection.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!