Measuring the effect of clinical guidelines on patient outcomes

Citation
Da. Marshall et al., Measuring the effect of clinical guidelines on patient outcomes, INT J TE A, 16(4), 2000, pp. 1013-1023
Citations number
28
Categorie Soggetti
Health Care Sciences & Services
Journal title
INTERNATIONAL JOURNAL OF TECHNOLOGY ASSESSMENT IN HEALTH CARE
ISSN journal
02664623 → ACNP
Volume
16
Issue
4
Year of publication
2000
Pages
1013 - 1023
Database
ISI
SICI code
0266-4623(200023)16:4<1013:MTEOCG>2.0.ZU;2-R
Abstract
Objectives: To identify and examine the methodologic issues related to eval uating the effectiveness of treatment adherence to clinical guidelines. The example of antiretroviral therapy guidelines for human immunodeficiency vi rus (HIV) disease is used to illustrate the points. Methods: Regression analysis was applied to observational HIV clinic data f or patients with CD4+ cell counts less than 500 per muL and greater than 50 per muL at baseline (n = 704), using Cox proportional hazards time-varying covariates models controlling for baseline risk. The results are compared with simpler models (Cox model [without time-varying covariates] and logist ic regression). In addition, the effect of including a measure of exposure to antiretroviral guidelines in the model is explored. Results: This study has three implications for modeling clinical guideline effectiveness. To capture events that are time-sensitive, a duration model should be used, and covariates that are time-varying should be modeled as t ime-varying. Thirdly, incorporating a threshold measure of exposure to refl ect the minimum period of time for guideline adherence required for a measu rable effect on patient outcome should be considered. Conclusions: The methods proposed in this paper are important to consider i f guidelines are to evolve from being a tool for summarizing and transferri ng the results of research from the literature to clinicians into a practic al tool that influences clinical practice patterns. However, the methodolog y tested in this study needs to be validated using additional data on simil ar patients and using data on patients with other diseases.