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NSW Health is using AI to recommend how staff job categories should map to roles in its new Single Digital Patient Record (SDPR). Implementation specialists review every recommendation; the reported process does not have AI independently granting access or making final access decisions. For the first rollout tranche, NSW Health says the AI-assisted work cut an estimated 30 days of intensive manual mapping to days.
What the AI does—and what it does not do
As staff join the SDPR, their varied job titles and workforce structures must be matched to the system’s access roles. NSW Health’s reported workflow analyses workforce records and recommends job categories that correspond to SDPR roles. Implementation specialists review each recommendation because staff need appropriate access when a site goes live.
Marc Pelusi, associate director of portfolio and AI delivery at the NSW Health SDPR Implementation Authority, put the accountability boundary plainly: “So, the AI recommends, and people remain accountable.” The report describes AI-assisted role mapping, not a clinical decision tool, and does not say AI independently assigns permissions.
The workflow uses Amazon Bedrock within NSW Health’s AWS tenancy in the Sydney region. Epic Systems supplies the core SDPR technology, hosted in AWS.
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How much time did AI save mapping SDPR roles?
For tranche A, 6,000 roles had to be mapped. Pelusi told iTnews that intensive manual work would have taken roughly 30 days, while AI assistance reduced the task to days—an estimated improvement of about 80 percent. These are program-representative estimates reported in October 2026, not independently audited performance results.
Pelusi also cited a 178,000-person NSW Health workforce as context for the broader scale of the access challenge. That is not the number of roles mapped for tranche A.
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What the Single Digital Patient Record brings together
The SDPR is a statewide integration of electronic medical records (eMR), laboratory information management systems (LIMS), and patient administration systems (PAS), intended to bring patient information together across NSW Health services. Before integration, NSW Health had 9 eMRs, 10 PAS, and 5 LIMS, according to its staff SDPR information page.
The rollout is phased. The system went live in March 2026 for Justice Health and Forensic Mental Health Network and the John Hunter Hospital laboratory. In May 2026, it went live across Hunter New England Local Health District and associated NSW Health Pathology sites. NSW Health names Epic Systems as the core technology supplier, AWS as cloud host, and RLDatix Galen as provider of the statewide data archive.
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Planned statewide footprint
Digital NSW describes the program’s planned reach as 228 public hospitals, more than 600 community health centres, 60 pathology laboratories, and more than 150 pathology collection centres. Implementation is expected to complete by 2028; these figures describe the planned footprint, not sites already live.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the reported result does—and does not—show
The reported time reduction suggests AI can speed up a laborious administrative mapping task. It does not establish that access assignments became more accurate or safer, or that patient outcomes improved. The October 2026 report does not publish model accuracy, error or false-assignment rates, bias testing, audit results, or a detailed process for correcting recommendations.
NSW Health’s February 2026 Artificial Intelligence Framework sets a risk-based approach guided by consumer-centred care, transparency, accountability, and trust. It identifies workforce, privacy and security, governance and regulation, and safety, ethics and quality as priority areas. That framework provides governance context; the cited sources do not establish a publicly available project-level risk assessment or audit for this specific role-mapping workflow.
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