The Model of Care Data Set (MoC DS) is a national maternity service-based data collection that contains data about the maternity Models of Care offered by maternity services.
The data elements within this dataset reflect the characteristics of 11 major models of care, under which women would be cared for by a health professional. The MoC DS reflect maternity plans at the population level, not the individual. As such no individual unit record data is held in this collection.
from 1/1/2018 to 30/4/2021
National and State
Unit records are not available.
The Maternity model of care (MoC) National best practice data set (NBPDS) is not mandated for collection. This data set enables maternity care providers to classify models of care using the Maternity Care Classification System (MaCCS).
The scope of the data set is all models of maternity care available to pregnant and birthing women.
The MaCCS, utilising the NBPDS provides a standardised nomenclature and descriptive data for maternity models of care. National collation of these data enables meaningful analysis and comparisons of maternal and perinatal outcomes between differing models of care. The data elements in the NBPDS describe the different characteristics of models of maternity care based on three domains:
The development of the MaCCS and the MoC NBPDS was undertaken as part of the National Maternity Data Development Project under the guidance of an expert advisory group and included wide-reaching consultation with relevant stakeholder groups around the country.
Metadata information and data quality statement (DQS)
See Maternity model of care (MoC) National best practice data set (NBPDS).
External links and information
Nomenclature for models of maternity care: a consultation report
Maternity Care Classification System: Maternity Model of Care Data Set Specification national pilot report November 2014
We'd love to know any feedback that you have about the AIHW website, its contents or reports.
The browser you are using to browse this website is outdated and some features may not display properly or be accessible to you. Please use a more recent browser for the best user experience.