Extracting Evidence from Health IT Studies to Populate Logic Models

Area of Science:

• Health Informatics
• Systems Science
• Program Evaluation

Background:

• Logic models visually map the components and underlying assumptions of programs.
• They are proposed as a method to describe complex socio-technical health IT interventions.
• Understanding program logic is crucial for evaluating intervention effectiveness.

Purpose of the Study:

• To evaluate the applicability of logic models for depicting cause-effect relationships in health IT.
• To determine if logic models can adequately represent the evidence base for health IT impacts.

Main Methods:

• An integrative review was conducted on the impact of patient portals on patient outcomes.
• Key logic model elements (resources, activities, output, outcome, impact) were extracted from reviewed publications.
• Extracted elements were used to populate logic models, creating structured graphical representations of evidence.

Main Results:

• All evidence reviewed to date has successfully been incorporated into logic models.
• Logic models demonstrated flexibility in accommodating diverse types of evidence related to health IT.
• The graphical representation provided a structured overview of the evidence.

Conclusions:

• Logic models appear suitable for representing evidence concerning the impact of health IT.
• The study supports the use of logic models in understanding and evaluating health IT interventions.