IntroductionShared decision-making (SDM) is not yet widely used when making decisions in German hospitals. Making SDM a reality is a complex task. It involves training healthcare professionals in SDM communication and enabling patients to actively participate in communication, in addition to providing sound, easy to understand information on treatment alternatives in the form of evidence-based patient decision aids (EbPDAs). This project funded by the German Innovation Fund aims at designing, implementing and evaluating a multicomponent, large-scale and integrative SDM programme—called SHARE TO CARE (S2C)—at all clinical departments of a University Hospital Campus in Northern Germany within a 4-year time period.Methods and analysisS2C tackles the aforementioned components of SDM: (1) training physicians in SDM communication, (2) activating and empowering patients, (3) developing EbPDAs in the most common/relevant diseases and (4) training other healthcare professionals in SDM coaching. S2C is designed together with patients and providers. The physicians’ training programme entails an online and an in situ training module. The decision coach training is based on a similar but less comprehensive approach. The development of online EbPDAs follows the International Patient Decision Aid Standards and includes written, graphical and video-based information. Validated outcomes of SDM implementation are measured in a preintervention and postintervention evaluation design. Process evaluation accompanies programme implementation. Health economic impact of the intervention is investigated using a propensity-score-matched approach based on potentially preference-sensitive hospital decisions.Ethics and disseminationEthics committee review approval has been obtained from Medical Ethics Committee of the Medical Faculty of the Christian-Albrechts-University Kiel. Project information and results will be disseminated at conferences, on project-hosted websites at University Hospital Medical Center Schleswig Holstein and by S2C as well as in peer-reviewed and professional journals.

Objective: The aim of the study was to perform a systematic assessment of disease-free survival (DFS), overall survival, and morbidity rates after open radical hysterectomy (ORH) and minimally invasive surgery (MIS) for early-stage cervical cancer and discuss with experts the consequences of the LACC trial (published by Ramirez et al. in 2018) on clinical routine. Methods: A total of 5428 records were retrieved. After exclusion based on text screening, four records were identified for inclusion. Five experts from three independent large-volume medical centers in Europe were interviewed for their interpretation of the LACC trial. Results: The LACC trial showed a significantly higher risk of disease progression with MIS compared to ORH (HR 3.74, 95% CI 1.63 to 8.58). This was not seen in one epidemiological study and was contradicted by one prospective cohort study reported by Greggi et al. A systematic review by Zhang et al. mentioned a similar DFS for robot-assisted radical hysterectomy (RRH) and LRH. Recurrence rates were significantly higher with MIS compared to ORH in the LACC trial (HR 4.26, 95% CI 1.44 to 12.60). In contrast, four studies presented by Greggi reported no significant difference in recurrence rates between LRH/RRH and ORH, which concurred with the systematic reviews of Zhang and Zhao. The experts mentioned various limitations of the LACC trial and stated that clinicians were obliged to provide patients with detailed information and ensure a shared decision-making process. Conclusions: The surgical treatment of early-stage cervical cancer remains a debated issue. More randomized controlled trials (RCT) will be needed to establish the most suitable treatment for this condition.

Background Recent publications reveal shortcomings in evidence review and summarization methods for patient decision aids. In the large-scale “Share to Care (S2C)” Shared Decision Making (SDM) project at the University Hospital Kiel, Germany, one of 4 SDM interventions was to develop up to 80 decision aids for patients. Best available evidence on the treatments’ impact on patient-relevant outcomes was systematically appraised to feed this information into the decision aids. Aims of this paper were to (1) describe how PtDAs are developed and how S2C evidence reviews for each PtDA are conducted, (2) appraise the quality of the best available evidence identified and (3) identify challenges associated with identified evidence. Methods The quality of the identified evidence was assessed based on GRADE quality criteria and categorized into high-, moderate-, low-, very low-quality evidence. Evidence appraisal was conducted across all outcomes assessed in an evidence review and for specific groups of outcomes, namely mortality, morbidity, quality of life, and treatment harms. Challenges in evidence interpretation and summarization resulting from the characteristics of decision aids and the type and quality of evidence are identified and discussed. Results Evidence reviews assessed on average 25 systematic reviews/guidelines/studies and took about 3 months to be completed. Despite rigorous review processes, nearly 70% of outcome-specific information derived for decision aids was based on low-quality and mostly on non-directly comparative evidence. Evidence on quality of life and harms was often not provided or not in sufficient form/detail. Challenges in evidence interpretation for use in decision aids resulted from, e.g., a lack of directly comparative evidence or the existence of very heterogeneous evidence for the diverse treatments being compared. Conclusions Evidence reviews in this project were carefully conducted and summarized. However, the evidence identified for our decision aids was indeed a “scattered landscape” and often poor quality. Facing a high prevalence of low-quality, non-directly comparative evidence for treatment alternatives doesn’t mean it is not necessary to choose an evidence-based approach to inform patients. While there is an urgent need for high quality comparative trials, best available evidence nevertheless has to be appraised and transparently communicated to patients.

Background Numerous articles and reviews discussed the effects of shared decision making (SDM) on concept-specific and direct outcomes, showing great variety in methodology and results. Objectives This scoping review accentuates effects of shared decision making interventions on more distal and distant outcomes related to the healthcare experience of patients and physicians, the economy and treatment parameters. Eligibility criteria The search considered randomized controlled trials (RCTs), their secondary analyses and follow-up reports comparing shared decision making interventions against control conditions. Sources of evidence MEDLINE (through PubMed) and reference lists of included articles were systematically appraised. Charting methods First, relevant outcome effects were extracted following the authors’ conclusions. Second, all outcomes were sorted into one of five different effect levels: individual, interactional, organizational, systemic and clinical. Results The search process identified 120 eligible reports, representing 116 randomized controlled trials and four follow-up reports with a variety in research topics, intervention types, outcome measurements and effects. Most of the 298 extracted outcomes were reported as not affected by shared decision making (204). While some outcomes improved at least slightly (83), few tended to decline (9) or revealed mixed results (2). Considering the five outcome effect levels, individual and clinical outcomes were reported more frequently than interactional, organizational and systemic ones. However, many individual outcomes could be counted as systemic and vice versa. Conclusions Shared decision making can improve distal and distant outcomes depending on the healthcare context. Individual, systemic and clinical outcomes have been more frequently appraised than interactional and organizational ones. Single database search and limited assessment of articles’ risk of bias and effect size narrow reliability of our results.

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