MAPPING THE TERRAIN: A MOSAIC APPROACH TO SMALL AREA ANALYSIS OF NEED IN QUEENSLAND Spatial Sciences Institute Biennial International 28 September to 2 October 2009, Adelaide For more information please contact Dr Kate Liley | Evidence and Modelling | Department of Communities t: (07) 323 41506 | e: Kate.Liley@communities.qld.gov.au

This presentation will: OUTLINE: Evidence Based Management (EBM) and its application to small area analysis of need SHOW the OUTPUT: Mapping diverse data with GIS (synthesising quantitative and qualitative data make sense to a potentially shifting and lay audience) 2

What is Evidence Based Management (EBM)? Evidence Based Management is a means for the Queensland Department of Communities to match human services to priority community needs. This means that planning decisions and funding allocation are based on evidence of need so that resources will be allocated on an effective and efficient basis.

A ‘Mosaic’ approach Mosaic is not an acronym, it's the dictionary meaning of the word - a fusion of art and science (or qualitative and quantitative) using many small elements to make a picture that tells a story about an at risk population or specific issue

EBM Tools Tool 2 Tool 1 Tool 3 Tool 4 Rigorous process to identify high risk – high need population-locations. This involves participation of external stakeholders (academics, community reps) in the interpretation of data (‘Evidence’ or project group activity) Tool 1 Definitions, common standards and systems Tool 3 Outline of what needs to be done by who in planning to meet priority need (E.g. E&M - Statistical Assessment, Regional officers – validation) Tool 4 COMSIS

COMSIS COMSIS is the Community Services Information System and is availably publicly at https://statistics.oesr.qld.gov.au/comsis is built and maintained by the Office of Economic and Statistical Research (OESR – a portfolio office of Queensland Treasury) for the Department of Communities. is a key tool in establishing a core set of common standards and information across Queensland for identifying disadvantage need and risk. Data presented at SLA, LGA and DoC region level and includes specific administrative data from other agencies COMSIS delivers regional profiles and access to automatically updated data from over 200 datasets for localities and population groups. is a key part of Evidence Based Management COMSIS is the Communities Statistical Information System COMSIS is built and maintained by OESR for the department of Communities. COMSIS is a key tool in establishing a core set of common standards and information across Queensland for identifying disadvantage need and risk. COMSIS delivers 10 Regional Profiles, 1 Statewide Profile and access to automatically updated data from over 200 datasets for localities and population groups. COMSIS is a key part of the needs based planning and resource allocation framework. COMSIS is not a de facto data warehouse but the Department of Communities Interface with larger data sets such as QSIRS and the ABS. In this way it is not a discerete system but a planning tool for manipulating selected data sets to the Departments prioritisation of need.

Key Steps in EBM STEP 1: CONSTANT UPDATE OF COMSIS & REGIONAL PROFILES, DEPARTMENTAL RESEARCH AND EVIDENCE GATHERING STEP 2a: NEEDS IDENTIFICATION AND ANALYSIS Identification of need, risk and protective factors for DNR Ranking STEP 2b: REGIONAL VALIDATION OF NEEDS ANALYSIS DNR Ranking matched to regional experience STEP 3: SERVICE SYSTEM ANALYSIS Includes Service System Analysis (Mapping of need against service locations, service capacity, catchments, service continuum and community capacity) STEP 5: IMPLEMENTATION, MONITORING AND REVIEW STEP 4: DECISION MADE and FINALISATION OF DEPARTMENTAL PLAN DNR Ranking

Now we have all the data, what do we do with it and how do we put it together?? 8

The usefulness of GIS Layering of : basic map of Queensland and SLAs thematic layer (such as disadvantage or DNR rank for a program area) Dot density of Target Population community capacity analysis service system and other relevant services Cost and benefit analysis (coming soon) Service system network analysis (coming soon) 9

‘Corridor' of Disadvantage CCD IRSED

‘Corridor' of Disadvantage Main roads

‘Corridor' of Disadvantage DoC Services

Key Points COMSIS (or an Agency equivalent) is a is a key tool in establishing a core set of common standards and information for identifying need. A statistical database best sits within a robust framework to ensure a standards based use of data, research and regional intelligence. Implementation and training is a key component in ensuring that agency staff understand and adopt the practices of EBM - ensuring consistency, transparency and defensibility of planning and resource allocation decisions at an executive level. 13

MAPPING THE TERRAIN: A MOSAIC APPROACH TO SMALL AREA ANALYSIS OF NEED IN QUEENSLAND For more information please contact Dr Kate Liley | Evidence and Modelling | Department of Communities t: (07) 323 41506 | e: Kate.Liley@communities.qld.gov.au

Disadvantage, Need, Risk Ranking or ‘DNR ranking’ A DNR (Demand, Need and Risk) rank is a ranking of need across all SLAs in Queensland for a particular Issue or population DNR(SLA) = Comparative Disadvantage (A) + Relative Need (B¹) + ’Sentinel Indicator’(B²) + Risk (C) A = Comparative Disadvantage - The SEIFA index of disadvantage (Socio-economic index for areas) for each SLA is converted to a SEIFA Reference Value. This is calculated thus: SEIFA Reference Value = (QLD Average SEIFA - SEIFA Index Value) + QLD SEIFA Average). B¹and B²= Relative Need - Relative need (B¹) and the Sentinel indicator (B²). Relative need in the absence of definitive data is measured by use of a proxy variable. On their own proxy variables are considered weak unless used in conjunction with other variables (such as a sentinel indicator), when they become sufficiently powerful to create statistical meaning for a given population or issue. program area. Sentinel indicators are developed by the Evidence Groups for each program area in partnership with the office of Economic and Statistical Research (OESR). Sentinel indicators are products of a Multivariate Classification Tree Analysis and are statistically robust enough to produce DNR scores that ‘begin a conversation’ with qualitative data sources in pursuit of a holistic perspective for a high need, high risk location-population. C = Proportion of target population (such as children, youth) per SLA Back