To conduct a systematic analysis of a clinical surgery theoretical examination based on knowledge points, thereby providing a reference for establishing a scientific and comprehensive test paper analysis system.

Using the difficulty coefficient (P-value) and discrimination index (D-value) as indicators, a detailed evaluation was performed on 6 question types and 40 knowledge points from the Clinical Comprehensive Course: Surgery examination for the 2023 clinical medicine pilot class at Peking Union Medical College. Data were visualized using frequency distribution charts, radar charts, and scatter plots.

A total of 23 examination papers were collected. The students' average score was 78.63±7.58, with a pass rate of 100%. The overall examination difficulty was relatively low (P=0.79), and the overall discrimination was poor (D=0.15). Among the 40 knowledge points, 2 (5.0%) were difficult, 9 (22.5%) were moderately difficult, and 29 (72.5%) were relatively easy. Regarding discrimination, 3 (7.5%) knowledge points showed excellent discrimination, 8 (20.0%) demonstrated good or acceptable discrimination, and 29 (72.5%) had relatively poor discrimination. Some knowledge points [e.g., "Benign Prostatic Hyperplasia" (P=0.26, D=-0.17)] presented issues of high difficulty coupled with poor discrimination. A considerable number of knowledge points require corresponding adjustments.

Knowledge-point-based test paper analysis can provide references for optimizing question type design, thereby enhancing the scientific nature of assessments and offering a basis for teaching improvements.

To explore the establishment, implementation, and outcomes of an integrated physician-nurse team-based comprehensive management model for breast cancer chemotherapy outpatients, aiming to provide a reference for standardized patient care.

In January 2019, the Breast Surgery Department of Peking Union Medical College Hospital developed an integrated physician-nurse team and established a full-cycle management pathway covering the pre-chemotherapy, chemotherapy, and inter-cycle phases. This model featured appointment-based scheduling, time-segmented visits, and closed-loop patient management. Key performance indicators-including healthcare efficiency, chemotherapy safety, staffing ratios, and satisfaction levels among patients and healthcare providers-were compared between pre-implementation(2018) and post-imple-mentation (2019) periods.

Before implementation, patient waited times ranged from 30 to 120 (75.40±20.97) minutes, with an annual chemotherapy volume of 8715 cases. Two ward nurses were routinely redeployed daily to support the chemotherapy clinic. Post-implementation, patients received timely chemotherapy per scheduled appointments without delays, annual chemotherapy volume increased to 10101 cases, and staffing between two chemotherapy units became flexibly adjustable. Ward nurses transitioned from an on-call to a reserve role. Adverse events (chemotherapy-related, catheter-related, and nursing incidents) remained at 0, consistent with pre-implementation levels. Both patient and staff satisfaction scores significantly improved across all domains (all P < 0.05).

The integrated physician-nurse team-based chemotherapy management model enhances service efficiency, ensures treatment safety, optimizes workforce allocation, and improves satisfaction among patients and healthcare providers.