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Assessing the national essential medicines list selection processes: Instrument development and testing

Author

Listed:
  • Ekanki Saxena
  • Jillian C Kohler
  • Kevin E Thorpe
  • Nav Persaud

Abstract

Background: National Medicines Policies use the National Essential Medicines Lists (NEML) to improve equitable access to medications. An effective list selection process should address a country’s priority healthcare needs and be aligned with WHO guidelines. Objective: The purpose of this study was to develop and test an instrument to measure the effectiveness of NEML selection process design. Methods: An instrument consisting of 16 items, along with an associated rating scheme, was created through a literature review and consultation with subject matter experts. Reliability was assessed using intraclass correlation coefficients (ICCs) for absolute agreement and consistency. Validity was evaluated by comparing instrument scores with two proxy measures of NEML selection process effectiveness. Results: The total score for NEML selection process design effectiveness, based on ratings from 5 raters across 4 countries, demonstrated an absolute agreement ICC of 0.98 (95% confidence interval 0.91 to 0.99) and a consistency ICC of 0.97 (95% confidence interval 0.88 to 0.99). Instrument scores varied correspondingly with two proxy measures of NEML selection process effectiveness, indicating good validity. Conclusion: The instrument developed in this study measures the construct of NEML selection process design effectiveness, which essentially evaluates the alignment of national policy content with policy intent. The instrument demonstrated good validity and excellent reliability.

Suggested Citation

  • Ekanki Saxena & Jillian C Kohler & Kevin E Thorpe & Nav Persaud, 2026. "Assessing the national essential medicines list selection processes: Instrument development and testing," PLOS ONE, Public Library of Science, vol. 21(2), pages 1-17, February.
    • Handle: RePEc:plo:pone00:0342750
    DOI: 10.1371/journal.pone.0342750
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