Using an empirical method for establishing clinical outcome targets in disease management programs.
The disease management (DM) industry is being scrutinized now more than ever before, with programs being asked to demonstrate improvement in clinical quality in addition to the expected reduction in medical costs. In healthcare, clinical improvement targets are often set at levels considered to be clinically meaningful. This difference may or may not be statistically significant. The term "effect size" refers to the smallest difference that could be detected statistically. This paper proposes a simple empirical method for determining the minimum expected improvement level for DM clinical outcome measures in which two proportions are being compared. This method is useful in situations where the outcome measure does not lend itself to be determined by the subjective judgment of medical expertise. Graphical displays are provided for the reader to use to help determine appropriate effect sizes for studies in lieu of, or in addition to, the statistical calculations.
Linden
Ariel
A
Linden Consulting Group, Portland, Oregon, USA. ariellinden@yahoo.com
Adams
John L
JL
Roberts
Nancy
N
D003363:Cost Control; D019468:Disease Management; D036262:Empirical Research; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000592:standards*; D015397:Program Evaluation; D011785:Quality Assurance, Health Care; D014481:United States