Objective To review main obstacles to health care professionals' adherence to clinical practice guidelines (CPGs) by employing the scoping review method and a determinants framework, and to explore the effect of implementation strategies in intervention researches on guideline adherence. Methods The articles published from January 1, 2011 to June 10, 2023 were retrieved from the PubMed, CINAHL, MEDLINE, Embase, Scopus, Cochrane Library, SinoMed, CNKI, WanFang Data and VIP databases. The original literature on the CPGs implementation obstacles and strategies was included, and the primary and secondary screening of the literature were completed by four researchers according to the inclusion and exclusion criteria. The basic characteristics of the literature, the factors affecting the implementation of the CPGs, and the strategies used were extracted. The results were analyzed and summarized using qualitative and quantitative methods. Results A total of 61 articles were included in the scoping review. The factors affecting the implementation of CPGs could be divided into five categories: guidelines themselves, external factors, internal factors, individual factors, and implementation process. The most common implementation obstacles were insufficient knowledge or skills of professionals regarding guidelines (n=21, 34.4%), insufficient necessity of using guidelines according to doctors (n=17, 27.9%), and unreasonable factors within hospital (n=16, 26.2%). The factors that promoted the implementation of CPGs included guidelines based on high-quality evidence (n=5, 8.2%), good department or hospital culture (n=4, 6.6%), convenient accessibility of guideline knowledge and information (n=4, 6.6%), and doctors’ excellent professional ability (n=4, 6.6%). The overall effectiveness of the guideline implementation strategy was 50%. Clinical decision support system (CDSS) could improve the adherence of CPGs. Guideline education or training was one of the most commonly used methods, but the effect of improving guideline compliance was unstable. Conclusion The primary challenges in implementing guidelines include inadequate professional capacity and demand, suboptimal hospital infrastructure and limited resources. However, the obstacles are not absolute. It is recommended to use implementation strategies to improve the absorption and implementation of guidelines, among which CDSS is an effective measure for promoting guideline adherence.
ObjectiveTo explore the parameter selection of different sample size estimation methods and the differences in estimation results in single-group target value clinical trials with rate as the outcome evaluation index. MethodsWe conducted a literature review to assess the method of target value selection for single-group target value clinical trials. Then, different values of target value (P0), clinical expected value (P1), and class II error level (β) were set through numerical simulation. Sample size results estimated using different sample size estimation methods were obtained using PASS software. The coefficient of variation, range/mean, analysis of variance and other methods were used to compare the differences between different methods. ResultsAnalysis of the data simulation results showed: when the expected value P1 was fixed, the sample size first decreased rapidly and then decreased slowly along with the increase or decrease of the targeted value P0 on both sides of the sample size limit value. When the difference between P0 and P1 was within 0.15, the ratio before and after correction could be controlled within 0.9. When the difference between P0 and P1 was more than 0.6, the ratio before and after correction approached 0.5. When P0+P1≈1, the ratio of different standard error choices (Sp0 or Sp1) to the estimated sample size was close to 1. When 0.65<P0+P1<1.35, the ratio of different standard error choices (Sp0 or Sp1) to the estimated sample size was about 3:1. When the confidence was 0.8, P0 and P1 were between 0.25 and 0.75 and between 0.20 and 0.80, respectively. We found little difference among the sample sizes estimated using these five methods (CV<0.10, range/mean<0.2). ConclusionThere are some differences among different sample size estimation methods, however, when P0 and P1 values are around 0.5, the differences between different methods are small, suggesting that appropriate methods should be selected for sample size estimation.
The level of evidence in randomized controlled studies is high. However, it cannot be widely applied due to its high cost, external authenticity, ethics and other reasons. The traditional observational studies reduce the internal authenticity due to various confounding factors, and the level of evidence is low. Regression discontinuity design (RDD) is a design that observes and compares outcome of object around the threshold under practical clinical conditions. Its capability to adjust confounding factors is second only to that of randomized control studies. It can be used in cases where the intervention (or exposure) is directly related to the value of a continuous variable. For instance, whether an HIV patient needs antiretroviral treatment mainly depends on whether the CD4 cell count is lower than 200/μL. Because the measurement of continuous variables has random error, whether intervention is given near the threshold or is close to random, the baseline of patients in the intervention group and non-intervention group near the threshold should be balanced and comparable. Based on this assumption, the causal effect of intervention (or exposure) and outcome can be estimated by comparing the outcomes of populations near the threshold. RDD is mainly applicable to the study of classification outcomes in medicine, among which two-stage least square method, likelihood ratio based estimation method and Bayesian method are more commonly used model estimation methods. However, the application conditions of RDD and the requirement of sample size limit its extensive application in medicine. With the improvement of data accessibility and the development of real world research, RDD will be more widely used in clinical research.
Mixed methods research (MMR) is the third research paradigm that combines quantitative and qualitative research. MMR can overcome limitations of qualitative and quantitative methods by integrating the advantages of these two. The environment of real world research is complicated. When using real world data to assess the health status of patients, process of treatment, outcomes of prevention and treatment, prognosis and prediction, and support for medical policy development, MMR can be applied to tackle research questions more comprehensively for the quality of research.
Currently, the recommendations of the clinical practice guidelines related to acupuncture in China and abroad are opaque to the source of the acupuncture prescription, there is a lack of comprehensive evaluation of the rationality of the acupuncture prescription, and the standards for the selection of the acupuncture prescription are opaque and nonstandard, and the writing and reporting details are insufficient, thus affecting the clinical applicability of the guidelines. To a certain extent, the utilization rate of the recommendations of the guidelines is low. This paper discusses the origin, rationality comprehensive evaluation, priority selection, writing and reporting of acupuncture prescriptions, and puts forward detailed methodological suggestions, to provide guidance makers of methodological optimization thoughts and suggestions for the evaluation, selection and writing of acupuncture prescriptions in the recommendations.
ObjectiveThe purpose of this study was to translate the U-CEP scale into Chinese, and evaluate the reliability and validity of the Chinese version of the U-CEP, in order to provide a measurement and evaluation tool for clinical epidemiology education and research. MethodsThe U-CEP scale was translated and adapted using the Brislin translation model. A nationwide survey of clinicians was conducted using the Chinese version of the U-CEP. Item analysis, reliability analysis, and validity analysis were performed using SPSS 26.0 software. ResultsThe discriminant validity analysis showed that except for item 4, the critical value (CR) of the other twenty-four items differed significantly between high and low groups (P<0.01), with CR values ranging from 2.902 to 14.609. The ITCs of the 25 items were all positive, with 5 items having an ITC<0.15(20%), 2 items having ITC≥0.15~0.20 (8%), 6 items having ITC≥0.20~0.40 (24%) and 12 items having ITC≥0.40 (48%). In terms of reliability, the overall Cronbach’s α coefficient of the Chinese version of the U-CEP was 0.80, with Cronbach’s α coefficient ranging from 0.752 to 0.805 when deleting each item one by one. The test-retest reliability was 0.848 (P<0.001). The alternative-form reliability was 0.838 (P<0.001). In terms of validity, expert analysis showed that the content validity of the Chinese version of the U-CEP was good. The construct validity analysis showed that the cumulative contribution rate of the 25 items was 57.50%. No respondent scored full marks or zero marks, indicating that no ceiling or floor effects were found. There were statistically significant differences in the total scores among clinicians with different educational backgrounds or with or without systematic learning of relevant knowledge (P<0.05). ConclusionThe Chinese version of the U-CEP has good reliability and validity, as well as good cultural adaptability. It can effectively assess a physician's knowledge of clinical epidemiology.
In the process of formation of recommendations of clinical practice guidelines, experts have many difficult problems of lack of transparency and high subjectivity in making final decisions, such as incomplete comprehensive consideration of dimensions and great heterogeneity in the evaluation of importance between dimensions, etc. As a decision-making tool, multi-criterion decision analysis improves the decision-making level of recommendation by adding the combination of qualitative and quantitative methods. By analyzing the challenges facing the formation of recommendations, this paper introduces the decision assistance of multi-criterion decision, and analyzes and summarizes the advantages and methods of the application of multi-criterion decision, so as to provide reference and guidance for guide makers to solve the difficulties in the formation of recommendations.
In the process of formulation, traditional Chinese medicine clinical practice guidelines are often faced with the dilemma of lack of evidence. Guidelines development groups tend to make final decisions based on expert experience or expert opinion, but the limitations of cognitive bias reduce the credibility and transparency of the guidelines. By clarifying the difference between the expert experience and expert opinion and expert evidence, the expert evidence of traditional Chinese medicine discipline advantages and necessity, providing the recommendation form link using expert evidence methodology design and implementation details, retaining the empirical characteristics of traditional Chinese medicine and improving the lack of evidence, has certain practical application value.