With the increasing burden of chronic diseases, the issue of comorbidities has become increasingly important. In practice, patients with comorbidity of chronic diseases struggle to access continuous and integrated healthcare experiences. This article introduces the construction of the referral management system for comorbidity of chronic diseases based on “internet plus” in West China Hospital of Sichuan University. By formulating a standardized and convenient referral process and using artificial intelligence to optimize the referral platform, it creates a referral system for comorbidity of chronic diseases suitable for the hospital’s clinical workflows, makes reasonable use of the resources of the return pool, and improves the referral efficiency. After the implementation of the comorbidity referral system, patient satisfaction has increased, providing new ideas and reference experience for the management of comorbidity of chronic diseases for other medical institutions.
Patients with chronic diseases usually face severe challenges during their transition from hospital to home, such as poor discharge preparation, the increased incidence of medical errors, insufficient self-care capability, and poor participation in healthcare decision, which can result in increased readmission and poor patient safety. This paper reviews the definition of transitional care, single-element transitional care intervention strategy, and multiple-element transitional care intervention strategy, in order to provide new insights into the development of effective and safe transitional care strategies in China.
This paper introduces the background and research design (including site of investigation, study population, baseline survey and follow-up monitoring), which belongs to the Precision Medicine Project of the National Key Research and Development Program of China.
The prevention and control of chronic diseases is a major need that urgently needs to be solved in China. Traditional Chinese medicine has unique advantages in preventing and treating chronic diseases. However, insufficient patient engagement may be found in the selection and evaluation of traditional Chinese medicine for the prevention and treatment of chronic diseases. In recent years, patient-centered clinical research has become a hot topic. A patient-centered methodological framework is proposed for the selection and evaluation of traditional Chinese medicine for preventing and treating chronic diseases. It incorporates some patient-centered studies based on the evidence-based medicine practice model, and will provide a scientific basis for screening traditional Chinese medicine for preventing and treating chronic diseases, improving the efficiency of traditional Chinese medicine services, improving price policies, and updating medical insurance catalogs.
At present, the health management of chronic diseases in China is still in its infancy. In the face of an increasingly large group of patients with chronic diseases, large general public hospitals often lack a systematic and standardized chronic disease continuity management system. In order to solve the problem of patients’ medical difficulties, popularize the hospitals’ innovative medical services, and promote the professional development of clinical departments, taking the continuous health management model of chronic diseases constructed by West China Hospital of Sichuan University as an example, this paper introduces the background, organizational structure and service process of the system construction in turn. The purpose is to build a new health service model of “smart hospital”, and also provide a reference for the construction of standardized chronic disease management system in hospitals, which will lay a foundation for further constructing a top-down chronic disease whole process system linked with communities and hospitals in the later stage.
ObjectiveTo systematically review the efficacy of discharge preparation service in elderly patients with chronic diseases.MethodsCNKI, WanFang Data, VIP, Web of Science, The Cochrane Library, PubMed and EMbase databases were electronically searched to collect randomized controlled trails (RCTs) on the discharge preparation service for elderly patients with chronic diseases from January, 2000 to January, 2019. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies, then, meta-analysis was performed by using RevMan 5.3 software.ResultsA total of 7 RCTs, involving 884 patients were included. The results of meta-analysis showed that: after the hospitalization preparation service, the incidence of acute complication (RR=0.38, 95%CI 0.15 to 0.98, P=0.04), patient compliance behavior (SMD=0.54, 95% CI 0.25 to 0.83, P=0.000 3), exercise capacity (SMD=2.65, 95%CI 0.25 to 5.04, P=0.03), and nursing satisfaction (SMD=0.71, 95%CI 0.10 to 1.33, P=0.02) significantly improved. However, there were no significant differences in emergency hospital admission for acute complications (RR=0.25, 95%CI 0.06 to 1.11, P=0.07), self-care ability (SMD=2.18, 95%CI ?1.02 to 5.38, P=0.18), activity of daily living (ADL) (SMD=0.56, 95%CI ?0.47 to 1.59, P=0.28).ConclusionsThe current evidence shows that after implementation of the discharge preparation service, the incidence of acute complication, compliance behavior, exercise ability, and service satisfaction of the elderly patients with chronic diseases are significantly improved. Due to limited quality and quantity of the included studies, more high-quality studies are required to verify above conclusion.
Objective This study aims to systematically review the current application status of sequential multiple assignment randomized trials (SMART) in the past decade. The goal is to clarify the research fields, research objectives, design elements, and data analysis methods of SMART clinical reports, and to provide evidence-based references for the subsequent standardized design and reporting of SMART. Methods The PubMed, Embase, Web of Science, APA PsychInfo, Scopus, CNKI, WanFang Data, VIP databases were electronically searched to collect studies on SMART-related clinical studies published from 2015 to 2025. Descriptive statistics and inductive thematic analysis methods were used to summarize and analyse the extracted data. Results A total of 153 articles were included. The results showed that the number of publications has been increasing year by year; the research was mainly concentrated in the United States (n=133), followed by China (n=11). The research fields were mainly in psychology and psychiatry (42%), endocrinology (12%), and cancer (11%). The research goals were diverse, with the comparison of dynamic treatment strategies (14%) being the most common. In terms of trial design, the initial grouping was mostly two groups, with a 1: 1 ratio between groups being the most common; two-stage multiple randomizations were mostly used, ultimately forming 4-8 subgroups; sample sizes were mostly between 100 and 500 cases (48%). Data analysis methods were diverse, depending on the research purpose, data characteristics, and design type. Longitudinal data analysis mainly used linear mixed-effects models (66 times) and generalized estimating equations (31 times), and Q-learning (16 times) was the mainstream method for constructing optimal decision rules. Additionally, the study found that the detail related to data processing was generally underreported. Conclusion As a primary method for evaluating clinical dynamic treatment strategies, SMART has issues such as imbalanced geographical and disciplinary distribution, incomplete reporting of design elements, and insufficient standardization of data processing. In the future, it is necessary to promote the expansion of international reporting standards, strengthen methodological research, and encourage the validation of its extrapolation and clinical translation value in a wider range of disease fields and regions.
