Principal Investigator: Jinying Chen, PhD
Co-investigators: Drs. Houston, Cutrona, Dharod
Monitoring implementation processes, including fidelity, is crucial for understanding implementation, adapting implementation programs, and comparing effectiveness of implementation strategies. Common approaches for assessing implementation fidelity often rely on self-report data or observational data collected by direct observation or audio/video recording. These approaches are difficult to scale for large implementation efforts. Technology-enabled fidelity measures have the potential to address this challenge.
This methods pilot study builds on Dr. Chen’s expertise in machine learning and her recent trainings in implementation research through the NCI-funded PRACCTIS post-doctoral fellowship at UMMS. The Specific Aims are:
Aim 1: Monitoring Intended, Direct Effects of Implementation: Using EHR access and audit logs, develop automatic metrics that measure the fidelity of implementation. As a demonstration of the methods, we will take advantage of the implementation, in 2019, of a new detailed smoker status assessment with automated clinical alerts to clinical providers in the Wake Forest Comprehensive Cancer Center.
Aim 2: Monitoring Overall patterns of clinical team-EHR activity: Develop methods to classify overall patterns of use, and Compare EHR use patterns before and after the launch of an implementation program that promotes the completion of smoking screening during clinic visits. This is an exploratory aim with the goal of identifying latent patterns of change in use of the EHR that can be used to monitor implementation, and can be adapted to any implementation program.