Objective To evaluate the efficacy of the DrCloudme platform in follow-ups of intracranial aneurysm(IA)patients.Methods A randomized controlled trial was conducted with 120 IA patients treated at Hechi People's Hospital from July 2021 to June 2024.Participants were equally allocated via random number table method into two groups:The control group(n=60)received conventional telephone follow-up post interventional embolization,while the intervention group(n=60)uti-lized the DrCloudme platform for digital follow-up management.Outcome measures included medical compliance,social functio-ning(assessed by Social Disability Screening Schedule,SDSS),quality of life(evaluated using Quality of Life Instrument for Head and Neck Cancer,QLICP-HN),follow-up completion rates,and patient satisfaction.Results The observation group dem-onstrated significantly higher medical compliance,follow-up completion rate,and follow-up patient satisfaction compared to the control group(P＜0.05).Additionally,the observation group had lower SDSS scores and higher QLICP-HN scores,indicating better social function and quality of life(P＜0.05).Conclusion The DrCloudme platform can not only improve the follow-up completion rate for healthcare providers,but also enhance medical compliance,social functioning,and quality of life among dis-charged IA patients.Moreover,it significantly boosts patient satisfaction with follow-ups.

Objective:To explore the relationship of metacognitive regulation, self-efficacy, and motivation regulation with learning engagement among medical students in military academies.Methods:A total of 439 students from the Air Force Medical University were selected by convenience sampling in March to April 2023. The Metacognitive Self-Regulation Scale, Self-Efficacy Scale, Learning Engagement Scale, and Motivation Regulation Questionnaire were adopted for investigation. SPSS 25.0 was used for Pearson correlation analysis, and the Process procedure for analysis and testing of mediating effects.Results:A total of 436 usable questionnaires were collected. Metacognitive regulation, self-efficacy, motivation regulation, and learning engagement were significantly positively correlated ( r>0.477, P<0.01). The mediating effect of self-efficacy and motivation regulation and the chain mediating effect of self-efficacy-motivation regulation were significant between metacognitive regulation and learning engagement, and the effect sizes were 0.449, 0.244, and 0.130, accounting for 44.37%, 24.11%, and 12.85% of the total effect, respectively. The proportion of the total indirect effect was 81.32%. Conclusions:The metacognitive regulation of medical students in military academies directly affects learning engagement, which is also indirectly affected through the independent mediating effect of self-efficacy and motivation regulation or the chain mediating effect of self-efficacy-motivation regulation.

Objective:The influencing factors of intraoperative hypoxemia in patients with benign central airway stenosis were investigated by machine learning algorithm, and the prediction model of hypoxemia was constructed and verified.Methods:A case-control study was used in this study. The clinical data of 650 patients with benign central airway stenosis who who received surgical treatment in the First Affiliated Hospital of PLA Naval Medical University from June 2022 to April 2024 were retrospectively analyzed. And they were divided into a training set ( n=455) and a test set ( n=195) according to 7:3. The training set was used for establishing Logistic regression model and conducting internal verification, and the test set was used for external verification. The least absolute shrinkage and selection operator (LASSO) regression and Boruta algorithm were used to select the factors affecting intraoperative hypoxemia in patients with benign central airway stenosis. A Logistic regression prediction model was constructed, and the model was evaluated using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA) and calibration curve. Shapley additive interpretation (SHAP) were used to analyze the importance of influencing factors. Results:Among 650 patients, 279 were males and 371 were females, aged (37.86 ± 8.82) years. Nine feature variables were screened by LASSO regression, while 7 feature variables were screened by Boruta algorithm, the intersection of the two was operation time, complications, degree of airway stenosis, thermal ablation therapy, balloon dilation, and airway stent, respectively, based on this, a logistic regression prediction model was constructed.The AUC values of the training set, validation set and test set of the model were 0.928 (95% CI 0.903-0.954), 0.922 (95% CI 0.843-0.995) and 0.919 (95% CI 0.872-0.965), respectively. The calibration curve showed that the predicted results of the model were in good agreement with the actual results, and the DCA curve showed that the model had clinical application value. SHAP analysis showed that the importance of variables affecting intraoperative hypoxemia in benign central airway stenosis patients was ranked as operation time, thermal ablation therapy, degree of airway stenosis, comorbidification, balloon dilation, and airway stent. Conclusions:The Logistic regression prediction model of intraoperative hypoxemia built based on machine learning algorithm has good prediction efficiency, which is helpful to early identification of risk groups and prevention of hypoxemia.

Objective:To analyze the current situation and influencing factors of information need for cardiac rehabilitation of urban and rural patients with coronary heart disease, and explore the inequality of information need for cardiac rehabilitation among urban and rural patients with coronary heart disease and its influencing factors, so as to provide a scientific reference for formulating targeted cardiac rehabilitation programs.Methods:From June to July 2024, hospitalized patients with coronary heart disease from a Class A tertiary hospital in Suzhou City were selected by convenience sampling as the study subjects. A General Information Questionnaire, Information Need in Cardiac Rehabilitation Hospital Anxiety and Depression Scale, Health Literacy Management Scale, and Coronary Artery Disease Self-Management Scale were used to conduct a questionnaire survey. Multiple linear regression was used to analyze the influencing factors of the cardiac rehabilitation information needs and the oaxaca-blinder model was used to analyze the causes of unequal information needs in urban and rural patients.Results:A total of 254 hospitalized patients with coronary heart disease who met the inclusion and exclusion criteria were surveyed, included 127 males and 127 females, 182 of them were aged 60 years or older. The total cardiac rehabilitation information needs score of rural and urban patients with coronary heart disease were 168.00 (115.50, 255.00) and 213.00 (132.00, 255.00), respectively, the difference was significant ( U = 5 389.50, P<0.05). Multiple regression analysis showed that health literacy ( β = 0.871, P<0.05) was the influencing factor of cardiac rehabilitation information needs of rural coronary heart disease patients, and depression ( β = 0.719, P<0.05) and living status ( β = -0.186, P<0.05) was the influencing factor of cardiac rehabilitation information needs of urban coronary heart disease patients. Average monthly household income per capita (C = 14.50%) and health literacy (C = 88.30%) were the main causes of the difference in cardiac rehabilitation information needs between urban and rural patients with coronary heart disease. Conclusions:The information demand for cardiac rehabilitation of patients with coronary heart disease in rural area is lower than that in urban areas in Suzhou, mainly due to health literacy and monthly income. It is recommended to narrow the urban-rural gap by improving rural health literacy, optimizing medical insurance policies, and promoting a multi-level rehabilitation service network.

Metering unit is important component of medical service items and also serve as significant bases for scientifically estimating the costs of medical services.National Technical Specification of Medical Service Items(2023 Edition)has set up elements such as"metering unit"and"adjustment coefficient for resource consumption in special circumstances",which clearly stipulate the metering units of each medical service item and the multiples for discretionary increases or decreases in the overall resource consumption when special circumstances occur.These two elements are important references for the cost accounting in medical institutions.The project team has elaborated on the definitions,establishment principles and special circumstances of these two types of elements,namely"metering units"and"adjustment coefficient for resource consumption in special circumstances",providing references for the application of relevant governments and healthcare institutions.

The relative value of human resource consumption is a relative value scale of the workload and difficulty of medical personnel needed to provide medical service items.Based on"basic human resource consumption and time consumption","technical difficulty"and"risk level"of the medical service items,it is comprehensively calculated by"relative value indicator standardization","relative value indicator weight setting","relative value indicator calculation model construction",and"relative value indicator expert verification".By formulating the relative value of human resource consumption,it could be used in rationalizing the relative value scale of medical service items,promoting cost accounting in hospitals,and establishing a scientific and reasonable performance evaluation system as technical tools.

In September 2023,the issues of National Technical Specification of Medical Service Items(Version 2023)and Financial Classification of Medical Service Items provide national-level standards and guidance for regulating healthcare facilities'charging practices and economic operation management.It highlights the overarching design principles,structural frameworks,and practical implementation approaches of National Technical Specification of Medical Service Items(Version 2023),in order to provide comprehensive support and directional guidance for fee regulation,cost accounting,performance evaluation,and other critical areas.

As an important indicator to assess the revenue structure of hospitals,healthcare service revenue can truly reflect the labor value of medical personnel.A unified financial classification is the premise of accurate calculation of revenue structure.Meeting the needs of financial management of medical institutions through mapping with current healthcare service items in various regions,Financial Classification of Medical Service Items has unified the financial classification from the aspects of bill classification,accounting subject and expense classification in medical record.

The assignment of the"item code"element in National Technical Specification of Medical Service Items(Version 2023)continues the classification framework and coding rules of National Specification of Medical Service Price Items(Version 2012).The project team experts are members of the WHO-Family of International Classifications(WHO-FIC)China Classification,Terminology and Standards Collaborating Center.The design concept of project coding is the same as that of the International Classification of Health Interventions(ICHI).Both adopt an alphanumeric characters hybrid coding classification method based on multi-axis classification,clarified the definition and scope of these four key classification axis which including anatomy system,anatomical site,surgical procedure and surgical approach,and optimize and update item property,sub-classifications and coding.Unified medical service item code can make contribution to the comparability of statistics related to health care items across regions,promote cross-regional healthcare and healthcare insurance settlement at the national level;improve its refined management level in hospital,and play an important role in performance management and data statistical analysis.

It introduces the setting scope,principles and codes of disposable medical consumables in National Technical Specification of Medical Service Items(Version 2023)in detail to provide a basis to strengthen medical consumables management,standardize clinical charging behavior,and promote the cost accounting of medical service items for relevant governments and medical institutions.