Objective To summarize the classic and latest treatment techniques for localized knee cartilage lesions in clinical practice and create a new comprehensive clinical decision-making process. Methods The advantages and limitations of various treatment methods for localized knee cartilage lesions were summarized by extensive review of relevant literature at home and abroad in recent years. Results Currently, there are various surgical methods for treating localized knee cartilage injuries in clinical practice, each with its own pros and cons. For patients with cartilage injuries less than 2 cm2 and 2-4 cm2 with bone loss are recommended to undergo osteochondral autograft (OAT) and osteochondral allograft (OCA) surgeries. For patients with cartilage injuries less than 2 cm2 and 2-4 cm2 without bone loss had treatment options including bone marrow-based techniques (micro-fracture and ogous matrix induced chondrogenesis), autologous chondrocyte implantation (ACI)/matrix-induced ACI, particulated juvenile allograft cartilage (PJAC), OAT, and OCA. For patients with cartilage injuries larger than 4 cm2 with bone loss were recommended to undergo OCA. For patients with cartilage injuries larger than 4 cm2 without bone loss, treatment options included ACI/matrix-induced ACI, OAT, and PJAC. Conclusion There are many treatment techniques available for localized knee cartilage lesions. Treatment strategy selection should be based on the size and location of the lesion, the extent of involvement of the subchondral bone, and the level of evidence supporting each technique in the literature.
Decision-making is often a complex and hard-to-routinize process. Based on the decision-making experience of fighting COVID-19, policymakers have gradually realized that climate action, quality education, and other societal challenges, as well as the sustainable development goals (SDGs) need to be addressed with the best available evidence using an evidence-informed decision-making (EIDM) approach. The Global Commission on Evidence was established in 2021. In addition, the Evidence Commission issued reports in 2022 and 2023. A systematic methodology to address societal challenges with EIDM has been constructed in the report. Five types of domestic evidence (data analytics, evaluation, modeling, qualitative insights, and behavioural/implementation research) and four steps in decision-making process (understanding a problem and its causes, selecting an option for addressing the problem, identifying implementation considerations, and monitoring implementation and evaluating impacts) were used to support four types of decision-makers (government policymakers, organizational leaders, professionals and citizens) in EIDM, as demonstrated by the reports. To further disseminate the concept and methodology of EIDM globally, the secretariat works with 25 Evidence Commissioners to write the report, and continues to cooperate with Country Leads Group from 12 countries to conduct rapid evidence-support system assessments (RESSAs), and collaborates with Evidence Commission Implementation Council to accelerate the implementation of 24 recommendations. The main history, core methodology, and latest developments of the Global Committee on Evidence were systematically reviewed in this paper. We aimed to show decision-makers a new version of how to scientifically address the societal challenges of EIDM.
This article explores the application and research progress of shared decision-making (SDM) tools in ultra-early vascular recanalization therapy for ischemic stroke, focusing on analyzing the functional characteristics and advantages and disadvantages of various tools. Based on functional goals, SDM tools can be divided into four categories: brief decision aids, risk communication tools, patient information tools, and prognosis assessment tools. These tools can assist patients and doctors in making informed treatment decisions quickly in time-sensitive situations, providing a reference for optimizing stroke revascularization treatment. Additionally, SDM tools can facilitate communication between doctors and patients, enabling patients to better understand the risks and benefits of treatment options, leading to choices more aligned with personal preferences and values. Through an in-depth study of these SDM tools, it is expected to improve the diagnostic and treatment efficiency for stroke patients, reduce decision conflicts, promote collaboration between doctors and patients, and provide new ideas and methods for stroke treatment and management.
Objective To establish a cooperative decision-making model of county-level public hospitals, so as to freely select the best partner in different decision-making units and promote the optimal allocation of medical resources. Methods The input and output data of 10 adjacent county-level public hospitals in Henan province from 2017 to 2019 was selected. Based on the traditional data envelopment analysis (DEA) model, a generalized fuzzy DEA cooperative decision-making model with better applicability to fuzzy indicators and optional decision-making units was constructed. By inputting index information such as total number of employees, number of beds, annual outpatient and emergency volume, number of discharged patients, total income and hospital grade evaluation, the cooperation efficiency intervals of different hospitals were calculated to scientifically select the best partner in different decision-making units.Results After substituting the data of 10 county-level public hospitals in H1-H10 into the model, taking H2 hospital as an example to make cooperative decision, among the four hospitals in H1, H2, H7 and H10 of the same scale, under optimistic circumstances, the best partner of H2 hospital was H7 hospital, and the cooperation efficiency value was 1.97; in a pessimistic situation, the best partner of H2 hospital was H10 hospital, and the cooperation efficiency value was 0.98. The model had good applicability in the cooperative decision-making of county-level public hospitals. Conclusion The generalized fuzzy DEA model can better evaluate the cooperative decision-making analysis between county-level public hospitals.
Compared with traditional HTA, the most fundamental feature of HB-HTA is “organizational perspective”, which is based on the actual situation of the hospital and supports hospital management decision-making. The new health care reform has set higher goals and requirements for hospitals. HB-HTA has management, economic and technical functions, and it can provide methodological support for health care policy management and decision-making based on the current optimal evidence, and promote the transformation of hospital from administrative decision-making to evidence informed decision-making. As an integral part of HTA network, HB-HTA plays a role in health technology networks through vertical cooperation mechanism and horizontal diffusion mechanism. It can interact and cooperate with national and regional HTA, as well as spread based on a specific medical field.
In recent years, the concept of population medicine has emerged as a research field that has important implications for healthcare practice and policy decision-making. It specifically aims to improve overall health of patient populations and safety, quality and efficiency of healthcare system. This paper descried the background, definition and characteristics of population medicine, discussed relationship between population medicine and population health and evidence-based medicine. It also introduced Department of Population Medicine at Harvard Medical School as a world-class model in the field of population medicine, discussed the needs and potential strategies for developing population medicine research in China, and briefly outlined the current development of population medicine in China.
Objective To explore the factors which affect shared decision-making and develop strategies to get patients actively involved in clinical decision-making. Methods We conducted a survey on 566 patients of a Class A Hospital in Sichuan with group random sampling method. The data were collected by the use of anonymous selfadministered questionnaires. We used SPSS 10.0 to analyse the data. Results A total of 600 questionnaires were distributed at random, of which 565 were completed. There were 68% patients who had some knowledge of the disease, and 93% who were willing to participate in clinical decision-making. The patients’ biggest concerns were: treatment effect, cost and doctors’ skills. The biggest difficulties that patients worried about were: long-time waiting in out-patient departments and limited time to communicate with doctors. Conclusion As more and more patients would like to involve in shared decision-making, doctors need to provide patients with more choices and help them make a right decision in their treatment.