International Journal of Technology Assessment in Health Care



ASSESSING THE LEARNING CURVE EFFECT IN HEALTH TECHNOLOGIES

(Lessons From The Nonclinical Literature)


Craig R. Ramsay a1c1, Sheila A. Wallace a1c1, Paul H. Garthwaite a2c1, Andrew F. Monk a3c1, Ian T. Russell a3c1 and Adrian M. Grant a4c1
a1 University of Aberdeen
a2 Open University
a3 University of York
a4 University of Aberdeen

Abstract

Introduction: Many health technologies exhibit some form of learning effect, and this represents a barrier to rigorous assessment. It has been shown that the statistical methods used are relatively crude. Methods to describe learning curves in fields outside medicine, for example, psychology and engineering, may be better.

Methods: To systematically search non–health technology assessment literature (for example, PsycLit and Econlit databases) to identify novel statistical techniques applied to learning curves.

Results: The search retrieved 9,431 abstracts for assessment, of which 18 used a statistical technique for analyzing learning effects that had not previously been identified in the clinical literature. The newly identified methods were combined with those previously used in health technology assessment, and categorized into four groups of increasing complexity: a) exploratory data analysis; b) simple data analysis; c) complex data analysis; and d) generic methods. All the complex structured data techniques for analyzing learning effects were identified in the nonclinical literature, and these emphasized the importance of estimating intra- and interindividual learning effects.

Conclusion: A good dividend of more sophisticated methods was obtained by searching in nonclinical fields. These methods now require formal testing on health technology data sets.


Key Words: Learning; Clinical competence; Technology assessment; Biomedical; Models; Statistical.

Correspondence:
c1 This project was funded by the UK NHS R&D Health Technology Assessment Programme. The Health Services Research Unit is funded by the Chief Scientist Office of the Scottish Executive Health Department. The views expressed are those of the authors.