Resources for Causal Reasoning in Health Services Research

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Over the past decades, health services research has informed policy about the most effective options for improving the delivery of medical care. However, the link between the organization and the outcomes of health services is rarely tested empirically because of ethical and methodological constraints on conducting experimental research in the patient care setting. As a result, the current state of knowledge offers limited insights into how changes in the organization and management of a health system may affect the quality of the health services provided. Increasingly, health services researchers are seeking new approaches to evaluating the causal effects of policy alternatives. More

Causal reasoning requires certain extensions in the standard statistical inference, including: (i) graphical models, (ii) nonparametric structural equations, (iii) probabilistic models, and (iv) counterfactual analysis.

We created this website having in mind colleagues from 4 professional groups who could find the website useful for putting together their causal reasoning library:

1. health services researchers
2. methodologists in structural equation modeling
3. statisticians working in causal inference
4. health care policy makers

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