Developing a Reliable, Valid, and Feasible Plan for Quality-of-Care Measurement for Cancer

How Should We Measure?

Published in: Medical Care, v. 40, no. 6, suppl., June 2002, p. III-73- III-85

Posted on RAND.org on December 31, 2001

by Katherine L. Kahn, Jennifer Malin, John L. Adams, Patricia A. Ganz

Read More

Access further information on this document at www.lww-medicalcare.com

This article was published outside of RAND. The full text of the article can be found at the link above.

BACKGROUND. Recent changes in the US health care delivery system have raised expectations that the medical marketplace will compete on quality and cost of care. This effort will require a systematic evaluation of the measurement of quality of care as it applies to cancer and other critical conditions. OBJECTIVES. To articulate the components of the design of quality-of-care measurement systems that must be considered and optimally manipulated to generate feasible, reliable, and valid data pertinent to patients with cancer. RESEARCH DESIGN. A synthesis of information obtained from literature reviews and experience. MEASURES. Four key areas of design that influence quality-of-care measurement scores are discussed: case identification, data source, data-collection strategies, and the quality of the care-measurement model. RESULTS. Challenges associated with these design and measurement strategies are defined and discussed. CONCLUSIONS. Policy analyses vary as a function of measurement domains. The design of a quality-of-care measurement system should consider trade-offs between validity and burden by considering the intricate relations between domains of measurement.

This report is part of the RAND Corporation external publication series. Many RAND studies are published in peer-reviewed scholarly journals, as chapters in commercial books, or as documents published by other organizations.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.