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Related Concept Videos

Reason and Intuition01:37

Reason and Intuition

The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the brain can only use...
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Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
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Related Experiment Video

Updated: Jul 14, 2026

Design and Optimization Strategies of a High-Performance Vented Box
14:23

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

Optimisation or Restriction? Unpacking the Logic Behind NICE Decisions.

Nadine Henderson1, Brittany Darrow2, Phill O'Neill2

  • 1Office of Health Economics, London, UK. nhenderson@ohe.org.

Pharmacoeconomics
|July 13, 2026
PubMed
Summary

Half of National Institute for Health and Care Excellence (NICE) technology appraisals (TAs) are optimized, restricting patient access to one-third of licensed medicines. Understanding these optimization drivers is crucial for patient equity.

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Last Updated: Jul 14, 2026

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Published on: July 22, 2025

Area of Science:

  • Health Technology Assessment
  • Health Economics
  • Pharmaceutical Policy

Background:

  • National Institute for Health and Care Excellence (NICE) technology appraisals (TAs) often recommend medicines for a subset of their licensed population.
  • These optimized recommendations significantly impact patient access to treatments, but the reasons and consequences are not well understood.

Purpose of the Study:

  • To analyze the drivers and implications of optimized NICE TA recommendations.
  • To quantify the extent of patient access restricted by these optimized decisions.

Main Methods:

  • Mixed-methods analysis of NICE TAs from 2023-2024.
  • Qualitative assessment of committee documents (n=56).
  • Quantitative estimation of patient access using the M-score method (n=30).

Main Results:

  • 50% of positive NICE decisions in 2023-2024 were optimized.
  • Key drivers include alignment with clinical trial data, NHS practice, prior NICE guidance, and cost-effectiveness in specific subgroups.
  • The mean M-score was 31%, indicating average access for only one-third of the licensed population; 77% of optimized decisions granted access to less than half of eligible patients.

Conclusions:

  • Optimized NICE recommendations represent a significant portion of positive appraisals, frequently imposing substantial restrictions compared to marketing authorizations.
  • Understanding the complex drivers of optimization is vital for assessing patient access and equity implications.