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Consultation: Revised accreditation framework for prevocational medical training

Our consultation regarding the strengthening of the accreditation framework for prevocational medical training is now open. We invite your feedback.

Te Kaunihera Rata o Aotearoa | the Medical Council of New Zealand’s (the Council) prevocational medical training accreditation framework has been updated to ensure it is appropriate for the new Te Whatu Ora | Health New Zealand (HNZ) environment. 

Thea new model for prevocational medical training identifies accountabilities at:

  • district level
  • regional level
  • national level. 

We have also revised our accreditation standards to assign accountability for each standard to these three levels. 

We have been engaging with HNZ and those involved in prevocational medical training. The model has been informed by recent accreditation site visits, changes in the structure of HNZ and meetings with those involved in prevocational medical training. 

This consultation provides an overview of the need for change, the process undertaken and the proposed changes to be made to the accreditation framework for prevocational training.

Your feedback is very important to us. This will be considered carefully before we make any decisions.

Please provide written submissions and responses to the questions in the consultation paper online  . Alternatively, you can email your submission to education@mcnz.org.nz.

We look forward to receiving your feedback. The consultation closes on 22 September 2025.

Consultation document
Download here [PDF, 326 KB] [PDF, 329 KB]

 

The new model for prevocational medical training identifies accountabilities sitting at:

  • district level
  • regional level
  • inational level.

Revised standards
Download here [PDF, 187 KB]
 

We have revised our accreditation standards to assign accountability for each standard to these three levels. 

Explanatory resources
Download here [PDF, 442 KB]
 

Explanatory resources which include diagrams of the new model and examples of scenarios which show how this model would work.