Education, Science, Technology, Innovation and Life
Open Access
Sign In

Processing of Real World Data in Traditional Chinese Medicine

Download as PDF

DOI: 10.23977/phpm.2023.030201 | Downloads: 10 | Views: 477

Author(s)

Yujia Li 1, Jun Li 1

Affiliation(s)

1 Public Health School, Shaanxi University of Chinese Medicine, Xi'an, Shaanxi, 712046, China

Corresponding Author

Jun Li

ABSTRACT

Traditional Chinese medicine (TCM) is a unique traditional medicine in China and has been passed down to the present day with its unique theoretical basis and treatment model. The introduction of the concept of evidence-based medicine into traditional Chinese medicine and the scientific evaluation of its clinical efficacy are essential for the better development and transmission of TCM. Randomised controlled trials have always been the "gold standard" of clinical trial evidence due to their strict inclusion and exclusion criteria and strict control of the data collection process, but the specificity of the TCM treatment model, the holistic, ambiguous, diverse and complex nature of the data, and the concomitant events in the research process make it difficult to conduct randomized ontrolled trials in TCM. Real World Study (RWS), which is conducted in actual clinical settings with broad inclusion and exclusion criteria to obtain treatment effects and long-term clinical outcomes as endpoints, can be used for long-term evaluation of treatment measures based on patients' preference. Real world studies allow for the long-term evaluation of treatment measures based on patients' preference, and are able to evaluate the overall effects, adapting to the holistic concept of Chinese medicine and the characteristics of evidence-based treatment. This paper summaries the data characteristics and data processing methods of real world studies in TCM, with a view to providing a reference for real world studies in TCM.

KEYWORDS

Chinese medicine; real-world research; Chinese medicine data characteristics; Chinese medicine data processing

CITE THIS PAPER

Yujia Li, Jun Li, Processing of Real World Data in Traditional Chinese Medicine. MEDS Public Health and Preventive Medicine (2023) Vol. 3: 1-6. DOI: http://dx.doi.org/10.23977/phpm.2023.030201.

REFERENCES

[1] Sherman R E, Anderson S A, Dal Pan G J, et al. Real-World Evidence - What Is It and What Can It Tell Us? [J]. N Engl J Med, 2016, 375(23):2293-2297.
[2] Austin PC. Assessing balance in measured baseline covariates when using many-to-one matching on the propensity-score. Pharmacoepidemiology and Drug Safety 2008; 17:1218–1225.
[3] Austin PC. Goodness-of-fit diagnostics for the propensity score model when estimating treatment effects using covariate adjustment with the propensity score. Pharmacoepidemiology and Drug Safety 2008; 17:1202–1217.
[4] Bradley E. Overlapping coefficient. Encyclopedia ofStatistical Sciences 1985; 6:546–547.
[5] Inman HF, Bradley EL. The overlapping coefficient as a measure of agreement between probability distributions and point estimation of the overlap of two normal densities. Communications in Statistics-Theory and Methods 1989; 18: 3851–3874.
[6] Stephens MA. Use of the Kolmogorov-Smirnov, Cramer-Von Mises and related statistics without extensive tables. Journal ofthe Royal Statistical Society, Series B 1970; 32:115–122.
[7] Pestman WR. Mathematical Statistics: An Introduction. Walter De Gruyter Inc: Berlin, 1998.

Downloads: 1923
Visits: 86639

Sponsors, Associates, and Links


All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.