Skip to main content
    • Aa
    • Aa


  • Craig R. Ramsay (a1), Sheila A. Wallace (a1), Paul H. Garthwaite (a2), Andrew F. Monk (a3), Ian T. Russell (a3) and Adrian M. Grant (a4)...
    • Published online: 20 May 2002

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.

Corresponding author
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.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

International Journal of Technology Assessment in Health Care
  • ISSN: 0266-4623
  • EISSN: 1471-6348
  • URL: /core/journals/international-journal-of-technology-assessment-in-health-care
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 0
Total number of PDF views: 11 *
Loading metrics...

Abstract views

Total abstract views: 96 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 23rd September 2017. This data will be updated every 24 hours.