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The systematic use of evidence-based methodologies and technologies enhances shared decision-making in the 2018 International Consensus Conference on Patient Blood Management.

ABSTRACT: BACKGROUND AND OBJECTIVES:Patient Blood Management (PBM) aims to optimize the care of patients who might need a blood transfusion. The International Consensus Conference on PBM (ICC-PBM) aimed to develop evidence-based recommendations on three topics: preoperative anaemia, red blood cell transfusion thresholds and implementation of PBM programmes. This paper reports how evidence-based methodologies and technologies were used to enhance shared decision-making in formulating recommendations during the ICC-PBM. MATERIALS & METHODS:Systematic reviews on 17 PICO (Population, Intervention, Comparison, Outcomes) questions were conducted by a Scientific Committee (22 international topic experts and one methodologist) according to GRADE (Grades of Recommendation, Assessment, Development and Evaluation) methodology. Evidence-based recommendations were formulated using Consensus Development Conference methodology. RESULTS:We screened 17 607 references and included 145 studies. The overall certainty in the evidence of effect estimates was generally low or very low. During the ICC, plenary sessions (100-200 stakeholders from a range of clinical disciplines and community representatives) were followed by closed sessions where multidisciplinary decision-making panels (>50 experts and patient organizations) formulated recommendations. Two chairs (content-expert and methodologist) moderated each session and two rapporteurs documented the discussions. The Evidence-to-Decision template (GRADEpro software) was used as the central basis in the process of formulating recommendations. CONCLUSION:This ICC-PBM resulted in 10 clinical and 12 research recommendations supported by an international stakeholder group of experts in blood transfusion. Systematic, rigorous and transparent evidence-based methodology in a formal consensus format should be the new standard to evaluate (cost-) effectiveness of medical treatments, such as blood transfusion.

SUBMITTER: Van Remoortel H

PROVIDER: S-EPMC7004058 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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The systematic use of evidence-based methodologies and technologies enhances shared decision-making in the 2018 International Consensus Conference on Patient Blood Management.

Van Remoortel Hans H Aranko Kari K Mueller Markus M MM De Buck Emmy E Devine Dana D Folléa Gilles G Meybohm Patrick P Tiberghien Pierre P Wood Erica M EM Vandekerckhove Philippe P Seifried Erhard E

Vox sanguinis 20191110 1

<h4>Background and objectives</h4>Patient Blood Management (PBM) aims to optimize the care of patients who might need a blood transfusion. The International Consensus Conference on PBM (ICC-PBM) aimed to develop evidence-based recommendations on three topics: preoperative anaemia, red blood cell transfusion thresholds and implementation of PBM programmes. This paper reports how evidence-based methodologies and technologies were used to enhance shared decision-making in formulating recommendation ...[more]

PMID: 31709562

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Project description:BackgroundShared decision-making (SDM) is widely recommended and required by the Centers for Medicare and Medicaid for patients considering lung cancer screening (LCS).ObjectiveWe examined clinicians' communication practices and perceived barriers of SDM for LCS at three medical centers with established screening programs.DesignMulticenter qualitative study of clinicians participating in LCS.ApproachWe performed semi-structured interviews, which were transcribed and analyzed using directed content analysis, guided by a theoretical model of patient-clinician communication.ParticipantsWe interviewed 24 clinicians including LCS coordinators (2), pulmonologists (3), and primary care providers (17), 4 of whom worked for the LCS program, a thoracic surgeon, and a radiologist.ResultsAll clinicians agreed with the goal of SDM, to ensure the screening decision was congruent with the patient's values. The depth and type of information presented by each clinician role varied considerably. LCS coordinators presented detailed information including numeric estimates of benefit and harm. Most PCPs explained the process more generally, focusing on logistics and the high rate of nodule detection. No clinician explicitly elicited values or communication preferences. Many PCPs tailored the conversation based on their implicit understanding of patients' values and preferences, gained from past experiences. PCPs reported that time, lack of detailed personal knowledge of LCS, and patient preferences were barriers to SDM. Many clinicians perceived that a significant proportion of patients were not interested in specific percentages and preferred to receive a clinician recommendation.ConclusionsOur results suggest that clinicians support the goal of SDM for LCS decisions but PCPs may not perform some of its elements. The lack of completion of some elements, such as PCPs' lack of in-depth information exchange, may reflect perceived patient preferences for communication. As LCS is implemented, further research is needed to support a personalized, patient-centered approach to produce better outcomes.

Project description:Background. Accurate diagnosis of patients' preferences is central to shared decision making. Missing from clinical practice is an approach that links pretreatment preferences and patient-reported outcomes. Objective. We propose a Bayesian collaborative filtering (CF) algorithm that combines pretreatment preferences and patient-reported outcomes to provide treatment recommendations. Design. We present the methodological details of a Bayesian CF algorithm designed to accomplish 3 tasks: 1) eliciting patient preferences using conjoint analysis surveys, 2) clustering patients into preference phenotypes, and 3) making treatment recommendations based on the posttreatment satisfaction of like-minded patients. We conduct a series of simulation studies to test the algorithm and to compare it to a 2-stage approach. Results. The Bayesian CF algorithm and 2-stage approaches performed similarly when there was extensive overlap between preference phenotypes. When the treatment was moderately associated with satisfaction, both methods made accurate recommendations. The kappa estimates measuring agreement between the true and predicted recommendations were 0.70 (95% confidence interval = 0.052-0.88) and 0.73 (0.56-0.90) under the Bayesian CF and 2-stage approaches, respectively. The 2-stage approach failed to converge in settings in which clusters were well separated, whereas the Bayesian CF algorithm produced acceptable results, with kappas of 0.73 (0.56-0.90) and 0.83 (0.69-0.97) for scenarios with moderate and large treatment effects, respectively. Limitations. Our approach assumes that the patient population is composed of distinct preference phenotypes, there is association between treatment and outcomes, and treatment effects vary across phenotypes. Findings are also limited to simulated data. Conclusion. The Bayesian CF algorithm is feasible, provides accurate cluster treatment recommendations, and outperforms 2-stage estimation when clusters are well separated. As such, the approach serves as a roadmap for incorporating predictive analytics into shared decision making.

Project description:On November 9 and 10, 2015, the International Conference on Mesothelioma in Populations Exposed to Naturally Occurring Asbestiform Fibers was held at the University of Hawaii Cancer Center in Honolulu, Hawaii. The meeting was cosponsored by the International Association for the Study of Lung Cancer, and the agenda was designed with significant input from staff at the U.S. National Cancer Institute and National Institute of Environmental Health Sciences. A multidisciplinary group of participants presented updates reflecting a range of disciplinary perspectives, including mineralogy, geology, epidemiology, toxicology, biochemistry, molecular biology, genetics, public health, and clinical oncology. The group identified knowledge gaps that are barriers to preventing and treating malignant mesothelioma (MM) and the required next steps to address barriers. This manuscript reports the group's efforts and focus on strategies to limit risk to the population and reduce the incidence of MM. Four main topics were explored: genetic risk, environmental exposure, biomarkers, and clinical interventions. Genetics plays a critical role in MM when the disease occurs in carriers of germline BRCA1 associated protein 1 mutations. Moreover, it appears likely that, in addition to BRCA1 associated protein 1, other yet unknown genetic variants may also influence the individual risk for development of MM, especially after exposure to asbestos and related mineral fibers. MM is an almost entirely preventable malignancy as it is most often caused by exposure to commercial asbestos or mineral fibers with asbestos-like health effects, such as erionite. In the past in North America and in Europe, the most prominent source of exposure was related to occupation. Present regulations have reduced occupational exposure in these countries; however, some people continue to be exposed to previously installed asbestos in older construction and other settings. Moreover, an increasing number of people are being exposed in rural areas that contain noncommercial asbestos, erionite, and other mineral fibers in soil or rock (termed naturally occurring asbestos [NOA]) and are being developed. Public health authorities, scientists, residents, and other affected groups must work together in the areas where exposure to asbestos, including NOA, has been documented in the environment to mitigate or reduce this exposure. Although a blood biomarker validated to be effective for use in screening and identifying MM at an early stage in asbestos/NOA-exposed populations is not currently available, novel biomarkers presented at the meeting, such as high mobility group box 1 and fibulin-3, are promising. There was general agreement that current treatment for MM, which is based on surgery and standard chemotherapy, has a modest effect on the overall survival (OS), which remains dismal. Additionally, although much needed novel therapeutic approaches for MM are being developed and explored in clinical trials, there is a critical need to invest in prevention research, in which there is a great opportunity to reduce the incidence and mortality from MM.

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The systematic use of evidence-based methodologies and technologies enhances shared decision-making in the 2018 International Consensus Conference on Patient Blood Management.

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The systematic use of evidence-based methodologies and technologies enhances shared decision-making in the 2018 International Consensus Conference on Patient Blood Management.

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