Good or best practice statements: proposal for the operationalisation and implementation of GRADE guidance

BMJ Evid Based Med. 2023 Jun;28(3):189-196. doi: 10.1136/bmjebm-2022-111962. Epub 2022 Apr 15.

Abstract

An evidence-based approach is considered the gold standard for health decision-making. Sometimes, a guideline panel might judge the certainty that the desirable effects of an intervention clearly outweigh its undesirable effects as high, but the body of supportive evidence is indirect. In such cases, the application of the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach for grading the strength of recommendations is inappropriate. Instead, the GRADE Working Group has recommended developing ungraded best or good practice statement (GPS) and developed guidance under which circumsances they would be appropriate.Through an evaluation of COVID-1- related recommendations on the eCOVID Recommendation Map (COVID-19.recmap.org), we found that recommendations qualifying a GPS were widespread. However, guideline developers failed to label them as GPS or transparently report justifications for their development. We identified ways to improve and facilitate the operationalisation and implementation of the GRADE guidance for GPS.Herein, we propose a structured process for the development of GPSs that includes applying a sequential order for the GRADE guidance for developing GPS. This operationalisation considers relevant evidence-to-decision criteria when assessing the net consequences of implementing the statement, and reporting information supporting judgments for each criterion. We also propose a standardised table to facilitate the identification of GPS and reporting of their development. This operationalised guidance, if endorsed by guideline developers, may palliate some of the shortcomings identified. Our proposal may also inform future updates of the GRADE guidance for GPS.

Keywords: COVID-19; Evidence-Based Practice.

MeSH terms

  • COVID-19*
  • Evidence-Based Medicine*
  • Humans
  • Research Design