ABSTRACT
The assessment of physicians'clinical competence is pivotal for fostering their professional growth and enhancing the quality of healthcare services.Despite this,a universally recognized and standardized system for as-sessing physicians'clinical competence remains to be established in China.Drawing on international practices in clini-cal competence assessment,provided a summary of the commonly utilized tools and methods for evaluating physi-cians'clinical competence.It also proposed recommendations for the development of a clinical competence assess-ment system in China.In the current practice of assessing physicians'clinical competence in China.It advocated for the establishment of a unified framework for clinical competence assessment,encouraging graded and classified as-sessments and a patient-centered,quality-improvement-oriented system for evaluating clinical competence.The uti-lization of big data will bring new opportunities for the assessment of healthcare personnel and the overall quality of medical services in China.
ABSTRACT
Objective It combines medical big data and machine learning techniques to explore clinical outcomes based clinical physician performance evaluation method.Methods The non-negative principal component analysis(NPCA)was used in cases.Based on the non-negative sparse principal component analysis(NSPCA),a comprehen-sive index fitting was performed on 11 clinical performance indicators of 170 clinicians treating cardiovascular diseases.At the same time,confidence intervals were constructed based on root cause assessment techniques to calculate the range of indicators for each clinician.Results The coincidence rate of outpatient discharge diagnosis,the rate of grade A healing of surgical incision,the proportion of surgical patients,the rate of 3-day diagnosis,the proportion of third-grade and fourth-grade surgery,the completion of surgery and the number of operations were significant in dis-tinguishing the work performance of clinicians.However,the average length of hospital stays before surgery,the rate of unplanned readmission within 30 days,the average length of hospital stays of discharged patients,the main diag-nosis and cure/improvement,and the number of patients admitted were not significant in distinguishing the clinical work performance of clinicians.The overall work performance of all clinicians can be ranked through comprehensive index fitting,and the further evaluation of high,middle and low performance of each specific index can reveal the potential reconstruction dimensions of each clinician.Conclusion It utilizes machine learning techniques to achieve a comprehensive evaluation of clinical performance,utilizing medical big data as the foundation.It holds the potential to provide important support for a more scientific and objective assessment of clinical performance.
ABSTRACT
Objective Focusing on the evaluation system of senior health professional titles in Shanghai,it discusses the rationality of the existing policies from the perspective of clinicians who plan to participate in the promotion,and put forward suggestions for optimizing the content and form of the evaluation.Methods Online questionnaire surveys had been conducted for all clinicians who participated in the application for Shanghai's senior health professional titles in 2020 to collect the personal information and their attitudes towards the professional title review system.R 4.0.2 soft-ware was used to conduct statistical description,cluster analysis,chi-square test,non-parametric test,etc.Results A to-tal of 1,674 people from 32 clinical specialties were surveyed.According to the two factors of growth space and growth speed,the participating subjects are divided into four different categories of groups,which are named according to the sample characteristics:Stars,Mainstay and Veteran.There are no differences among the three groups in the familiarity,and difficulty evaluation of clinical indicators for the senior health professional title evaluation system.The proportion of Veteran considered unreasonable is relatively high.There are differences among the three groups in overall difficulty level,scientific research difficulty and qualification difficulty.Conclusion The incentive attribute of the health technical person-nel senior title evaluation system should be continuously strengthened,and the differentiated characteristics of the de-velopment of health talents should be paid attention to.Big data can be used to highlight the quantification and differen-tiation of clinical competency evaluation indicators,which can effectively improve the scientific level of professional title evaluation.
ABSTRACT
Small cell lung cancer (SCLC) is a neuroendocrine tumor with fast progression, high malignancy, easy recurrence, and extremely poor prognosis. In the past 30 years, the clinical treatment strategy of SCLC has been mainly chemotherapy and radiotherapy, but the curative effect is not significant; the current immunotherapy of SCLC has gradually entered the clinic and has made certain progress. Tumor immunotherapy includes immune checkpoint inhibitors, tumor vaccines, cytokines, chimeric antigen receptor T-cell immunotherapy (CAR-T) therapy, etc. Currently, immune checkpoint inhibitors are the most widely used. This article summarizes the principles of immune checkpoint inhibitors and related drugs, summarizes their domestic and foreign clinical trials progress in SCLC treatment, reviews the biomarkers used in the therapy, and discusses its future development direction. .