Capability Uplift for Linked Data Policy Analysis

⁠⁠⁠We are seeking a 3-day, in-person short training course on the use of large, linked administrative datasets to address health, disability and ageing policy relevant questions. This is part of a larger capability uplift for analysts to integrate PLIDA (1 day) and in particular BLADE (2 days) data assets into advice provided to the Department. We are seeking to apply emerging methods in applied microeconometrics within the PLIDA-BLADE environment.

This will focus primarily on the integration and interpretation of BLADE data into relevant policy issues as this is historically not a data asset with which health analysts are familiar. The course should provide instruction on developing policy relevant research questions, as well as technical methods and approaches to answering those questions using large linked administrative datasets. Course material and content should be directed to answering real world policy questions and scenarios- particularly those that are relevant or adjacent to the health, disability and ageing policy context. The course should include a mix of lectures, case studies, and worked examples. Seminars may be recorded to facilitate knowledge transfer and capture. The course may include recommendations and instruction on using AI to conduct policy-relevant research using large administrative datasets. Relevant worked examples, code, course, and lecture materials should be provided to attendees to facilitate knowledge transfer.

The course presenter should agree to make themselves available to answer questions about the course subject matter for a period of one month preceding and two months post-seminar delivery. Expected attendance will be approximately 10 experienced analysts. An objective of the course is that attendees should have specific ideas/ proposals for relevant analysis that can be pitched to leaders.