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.
Objective To evaluate the effectiveness of the shared decision-making scheme in postoperative out-of-hospital extended care for patients with total hip/knee arthroplasty (THA/TKA). Methods Patients who underwent THA/TKA in the Department of Orthopedic Surgery at West China Hospital of Sichuan University between October 2023 and April 2024 were included using convenience sampling. Patients were divided into the control group (odd-numbered dates) and the intervention group (even-numbered dates) based on the surgical dates. The intervention group was received care guided by a shared decision-making protocol, whereas the control group was followed the standard post-arthroplasty follow-up procedures. Differences between the two groups were compared in terms of decision-making capacity, decision satisfaction, and hip/knee function at the following time points: on the day of discharge, 3 weeks after discharge, 2 months after discharge, and 3 months after discharge. Results A total of 118 patients were included, with 59 cases in each group. There were no significant differences in demographic and clinical characteristics between the two groups (P>0.05). In terms of decision-making, compared with the control group, the experimental group had stronger decision-making ability, lower decision-making conflict, and more satisfaction with the decision-making process (P<0.05). In terms of joint function, the experimental group showed better joint function than the control group at 3 weeks, 2 months, and 3 months after surgery (P<0.05). There was no significant difference in the pain dimension of the Western Ontario and McMaster Universities Osteoarthritis index between the two groups (P=0.199). Conclusions Compared with the traditional follow-up protocol, the shared decision-making protocol can enhance patient engagement in medical decision-making, reduce decisional conflict, improve satisfaction with the decision-making process, and simultaneously promote joint functional recovery and expedite the rehabilitation process.
Rare diseases are characterized by low incidence rates, high heterogeneity, and significant genetic relevance, posing global challenges in clinical diagnosis and treatment, including delayed diagnosis and a scarcity of therapeutic options. Artificial intelligence (AI) technology offers novel solutions to address these challenges in the field of rare diseases. This paper explores the advancements in AI applications for rare diseases from two perspectives: auxiliary diagnosis and treatment decision-making. In terms of auxiliary diagnosis, AI can integrate superficial features, electronic health records, genomic data, and multi-modal data to achieve early and precise diagnosis. Regarding treatment decision-making, AI facilitates drug target discovery, drug repurposing, and the design of gene therapy vectors, thereby promoting the development and application of new treatments. Furthermore, this paper analyzes the challenges of AI in rare disease diagnosis and treatment concerning data, technical algorithms, and clinical application, and proposes future directions, including the construction of a collaborative data ecosystem, enhancement of algorithm interpretability, and improvement of regulatory frameworks.
Objective To provide scientific evidence for the establishment of medical specialist system in China by investigating the history, current situation, problems and countermeasures of medical specialties training at home and aboard. Method The principle and theroy of evidence-based medicine were adopted. The information before Dec. 31, 2003 of Pubmed, CBM, official website, some journals, most frequently used search engines and medical monograph were systematically reviewed. Included literatures were assessed and graded according to the pre-defined criterias. Results A total of 1 319 studies (1 298 in English, 21 in Chinese) were included, among which only 6 were related to the classification of medical specialties. Based on the information from official website of USA, Canada, UK, Singapore, Australia and China (including HK and Taiwan), it showed that China has the largest number of medical specialties, followed by that of USA. In China, the number of medical specialties has more than that of the disciplines in clinical field, which was followed by resident training programs. Some specialties were duplicate, or not international standardized. Conclusions The classification of medical specialties should be developed consecutively, which comprehensively considered the international trend, characteristics of doctor training and the current situation. Specialties whose training program are well-established and developed should initiate firstly. Others will be put into practice gradually after being fully exprienced.
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 clarify the views of healthcare providers on the current vascular access shared decision-making model under the daytime chemotherapy mode, and to determine improvement measures to promote the conventional implementation of the daytime chemotherapy vascular access shared decision-making model. Methods Based on the SWOT model, an interview outline was developed. Using purposive sampling method, 7 doctors and 6 intravenous therapy nurses working at Tianjin Medical University Cancer Institute & Hospital from April to June 2023 were selected for semi-structured interviews, and content analysis method was used for data analysis. Results Four themes were extracted for internal advantages: alleviating the pressure of diagnosis and treatment and decision-making for doctors, ability and willingness of specialized intravenous therapy nurses to implement, promoting the rational selection of vascular pathways, enhancing the recognition of vascular pathways in daytime chemotherapy patients, and enhancing communication stickiness between nurses and patients. Four themes were extracted for internal weaknesses: increased workload, impractical decision support tools, unsmooth implementation processes, and incomplete informatization. Three themes were extracted for external opportunities: national policy support, willingness of daytime chemotherapy patients to participate in decision-making, and sufficient evidence-based evidence. Three themes were extracted for external threats: poor communication between healthcare providers under daytime chemotherapy mode, cognitive differences related to intravenous therapy among healthcare providers, and insufficient confidence in nurse leadership. Conclusions The vascular pathway shared decision-making led by intravenous therapy nurses has certain advantages in the daytime chemotherapy mode. In the future, we should seize existing opportunities, avoid our own weaknesses, face external threats, and develop a standardized vascular access shared decision-making model led by intravenous therapy nurses under the daytime chemotherapy mode, promoting the best evidence-based practice for vascular access decision-making during daytime chemotherapy.
With the change of coronavirus disease 2019 (COVID-19) prevention and control strategy in China, the number of COVID-19 cases has increased significantly recently, which has also brought new challenges to the perioperative risk control of thoracic surgery. This paper puts forward several suggestions, aiming to standardize the preoperative screening and evaluation during the COVID-19 period, strictly grasp the indications and timing of surgery, optimize the medical management process, individualize surgical decision-making, and minimize the risk of COVID-19 infection to surgery.