ObjectiveTo analyze the surgical treatment patterns for newly diagnosed colorectal cancer (CRC) patients based on hospital registry data in Sichuan Province (2020–2023). MethodsBased on the hospitalization records of CRC inpatients from all secondary and tertiary hospitals in Sichuan Province (2015–2024), the newly diagnosed CRC patients admitted during 2020–2023 and evaluated rates of primary lesion resection, neostomy, and stoma reversal procedures were identified. Then stratified analyses by gender, age, tumor location, and organ metastasis at diagnosiswere analyzed (One-sided test with α=0.025). ResultsBased on hospitalization records of 118 787 newly diagnosed CRC inpatients in Sichuan Province (2020–2023), the cohort had a mean age of (66.4±12.3) years, with 70 756 s (59.6%) male, 64 646 (54.4%) rectal cancer cases, and 16 418 (13.8%) cases exhibiting synchronous organ metastasis at diagnosis. Within one year post-diagnosis, 84 634 (71.2%) patients underwent primary tumor resection and 26 514 (22.3%) received neostomy procedures, both demonstrating significantly increasing annual trends (resection: χ2trend=72.2, P<0.001; ostomy: χ2trend=70.6, P<0.001) while showing inverse correlations with advancing age (resection: χ2trend=4 096.0, P<0.001; ostomy: χ2trend=56.3, P<0.001). Stratified analyses revealed significantly lower resection rates among females vs. males, rectal vs. colon cancer, and metastatic vs. non-metastatic patients (all P<0.001), whereas ostomy rates were higher in females and rectal cancer patients but lower in metastatic cases (all P<0.001). Among 26 514 ostomy patients, 11 288 (42.6%) underwent stoma reversal after a median (interquartile range) interval of 123 d (95 d, 188 d), with 8 187 reversals (72.5%) within 6 months, 2 700 (23.9%) during 6–12 months, and 401 (3.6%) after 12 months. Reversal rates increased temporally (χ2trend=80.0, P<0.001) but decreased with advancing age (χ2trend=1 072.3, P<0.001). ConclusionIn Sichuan province, rising trends are observed in the hospitalization burdern of newly diagnosed CRC and rates of primary tumor resection and neostomy.
ObjectivePublic health information collection is critical in improving the capacity of basic public health services. Our study took the "Wei Jian E Tong" APP as an example to evaluate the willingness and influencing factors of rural public health service personnel to continue using such APPs.MethodsWe applied exploratory sequential design in mixed-method research and chose Renshou county in Sichuan province as the representative region. Firstly, we used the personal in-depth interview to initially explore the status quo, applicability, continued willingness to use APP and other issues. Secondly, we used unified theory of acceptance and use of technology (UTAUT) and expectation confirmation theory (ECT) to construct a hypothetical model of influencing factors of user satisfaction. We then designed a structured questionnaire covering 7 measurement dimensions to survey all users of the APP at the survey site. Finally, we used structural equation model to verify the research hypothesis.ResultsA total of 21 individuals were interviewed in this survey, including leaders of township health centers, public health doctors, and rural doctors. Qualitative results showed the major defects were insufficient funds and policy support in the promotion and application, additionally lack of software functionalities and system incompatibility. A total of 593 valid questionnaires were collected from the quantitative survey on the satisfaction of township doctors and village doctors. Structural equation model results showed that seven direct hypotheses were established, of which compatibility had the largest effect value user satisfaction with a total effect value of 0.617, followed by facilitating condition (r=0.211), performance expectancy (r=0.137), effort expectancy (r=0.091) and social influence (r=0.068).ConclusionsTo promote the application of information collection apps in primary public health services and improve user satisfaction, the focus should be on solving software incompatibility and create interconnection among all levels of medical systems. At the same time, it is necessary to solve funding problems as a whole, optimize software functions, improve the performance evaluation system, and improve software training and promotion.
ObjectiveTo establish a hypertension prediction model for middle-aged and elderly people in China and to use the basic public health service database for performance validation. MethodsThe literature related to hypertension was retrieved from the internet. Using meta-analysis to assess the effect value of influencing factors. Statistically significant factors, which were also combined in the database, were extracted as the predictors of the models. The predictors’ effect values were logarithmarithm-transformed as the parameters of the Logit function model and the risk score model. Participants who were never diagnosed with hypertension at the physical examination of health service project of Hongguang Town Health Center in Pidu District of Chengdu from January 1, 2017, to January 1, 2022, were considered as the external validation group. ResultsA total of 15 original studies were involved in the meta-analysis and 11 statistically significant influencing factors for hypertension were identified, including age, female, systolic blood pressure, diastolic blood pressure, BMI, central obesity, triglyceride, smoking, drinking, history of diabetes and family history of hypertension. Of 4997 qualified participants, 684 individuals were identified with hypertension during the five-years follow-up. External validation indicated an AUC of 0.571 for the Logit function model and an AUC of 0.657 for the risk score model. ConclusionIn this study, we developed two different prediction models based on the results of meta-analysis. National basic public health service database is used to verify the models. The risk score model has a better prediction performance, which may help quickly stratify the risk class of the community crowd and strengthen the primary-level assistance system.
Against the backdrop of medical digital transformation, West China Hospital of Sichuan University has conducted a 30-year exploration and practice of colorectal cancer data engineering. This study focuses on the integration of special disease digitization and value-based healthcare, achieving standardized management and in-depth mining of colorectal cancer diagnosis and treatment data through constructing a full-life cycle data governance system, multi-center data platform, and intelligent application scenarios (such as clinical decision support systems). The practical results show that this data engineering has formed a specialized disease database containing more than 9 500 cases of structured data, and promoted the collaborative development of the entire chain of “production–study–research–business–government”, providing a learnable digital paradigm for improving diagnostic and treatment accuracy and optimizing medical resource allocation. The study indicates that special disease digitization is a key path to achieving value-based healthcare, and its experience in data standardization and medical-engineering cross-innovation is of reference significance for other disease fields.