Pseudo-understanding: an analysis of the dilution of value in healthcare

BMJ Qual Saf. 2015 Jul;24(7):451-7. doi: 10.1136/bmjqs-2014-003803. Epub 2015 May 14.


Background: Management concepts cycle through healthcare in trends lasting 3-5 years. This may hinder policy-makers, healthcare managers, researchers and clinicians from grasping the intricacies of a management concept and prevent organisations from realising the potential of these concepts. We, therefore, sought to characterise how the newest management concept, value-based healthcare (VBHC), is used and understood in the scientific literature.

Methods: We developed a novel five-step approach: (1) identification of a trend-starting article, (2) identification of key conceptual aspects in the trend-starting article, (3) collection of citing articles and identification of citing text, (4) categorisation of citing text to evaluate which aspects were used and (5) categorisation of citing text according to the structure of observed learning outcomes (SOLO) taxonomy to evaluate understanding.

Results: We identified four aspects in the trend-starting article, 'What is value in healthcare', of which value and outcomes were the most cited. More than one-quarter of the citing texts demonstrated no understanding of the aspect referred to; most demonstrated a superficial understanding. Level of understanding was inversely related to journal impact factor (IF), and did not change significantly over time. A deeper understanding was demonstrated in those articles that repeatedly cited the trend-starting article.

Conclusions: None of the four aspects were understood at a level required to develop the management concept of VBHC. VBHC may be undergoing a process of dilution rather than diffusion. To break the cycle of management trends, we encourage a deeper reflective process about the translation of management concepts in healthcare.

Keywords: Evaluation methodology; Health services research; Healthcare quality improvement; Management.

MeSH terms

  • Bibliometrics
  • Diffusion of Innovation
  • Health Services Administration / statistics & numerical data*
  • Humans