142nd APHA Annual Meeting and Exposition

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Logic modeling for measuring performance in clinical research programs

142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014): http://www.apha.org/events-and-meetings/annual
Wednesday, November 19, 2014 : 9:30 AM - 9:50 AM

Susanna Weiss, Ph.D., J.D., CEP , Office of Planning and Operations Support -- Division of Clinical Research, National Institute of Allergy and Infectious Diseases -- National Institutes of Health, Bethesda, MD
Logic modeling forms the foundation of evaluation, and one of the prerequisites for measuring outcome is a reliable, valid and appropriate system of performance measurement.  This logic model provides an integrated design to help evaluators visualize a framework for developing performance measures to improve productivity and accountability.  The journey towards developing an appropriate logic model started with strategic planning, involving goals and objectives for each administrative branch and project.  Optimal measures are being sought to accurately and fairly reflect the performance of employees as well as understand the reasons why goals sometimes may not be met.  It is important to develop a logic model that encompasses strategies to capture the complexity and nuances of the multi-factorial, collaborative productivity that each component of the system brings to the facilitation of clinical research.  Part of those strategies involve the commission of a full-scale study yielding quantitative and qualitative data to validate the selection of the KPIs, target metrics, and reporting systems to uncover the full, contextual performance story. Hopefully, this logic model will provide key insights and a useful roadmap for the in-depth research that needs to take place before performance measures can be implemented in a government clinical research environment. The model incorporates comparison measures against which performance can be assessed.  Reference points may include prior measures of performance (baseline) as well as recognized standards of industry performance (benchmarks).  The model will be enriched with data gathered from several sources, using a variety of appropriate collection methods and instruments.  The logic model will hopefully provide practical assistance to similarly situated government and non-profit entities seeking to develop performance measures and systems that can subsequently be utilized for full-scale performance evaluations and outcome assessments. 

Learning Areas:

Administration, management, leadership
Program planning
Public health administration or related administration
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
Explain logic modeling as a necessary precursor to performance measurement, including conceptual and methodological techniques for developing logic models, and their application to strategic planning, quality improvement, performance management, and program evaluation. Identify examples of logic models applicable to performance metrics, which may include process effectiveness outcomes, leadership outcomes, and workforce-focused outcomes. Describe components of logic models that can be used in scientific research, including pathways to collection of quantitative and qualitative data via focus group and survey methodologies, and multifactorial analysis that will be used to identify appropriate performance indicators. Identify comparison measures against which the performance of a program can be assessed. Comparison reference points may include prior measures of performance (baseline) and recognized standards of industry performance (benchmarking). Discuss efforts to develop logic models that can identify objective Key Performance Indicators (KPIs) and provide quantifiable data that will enable leadership to prioritize, and optimally align/utilize resources. Explain why logic models should include, and be enriched with, data gathered from several sources, using a variety of appropriate collection methods and instruments. Demonstrate how an effective logic model should produce metrics that provide data-driven assessments of performance and productivity and information about contextual factors to answer the “Why” and “How” questions that should accompany routine performance measurement. Discuss the need for computer software that can automate and expedite logic modeling, and the need for expertise in adapting existing software to an organization’s specific needs.

Keyword(s): Evaluation, Clinical Trials

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: Among my scientific interests and areas of scholarship and practice are program development, performance measurement, and evaluation practice. I am the lead author of an evaluation protocol for the development of performance measures for diverse clinical research programs and networks in domestic and global settings. I hold a Certificate in Evaluation Practice from The Evaluators' Institute at George Washington University.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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