Big Data 2014 : Melbourne
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1 Big Data 2014 : Melbourne >
2 > Topic: Data driven Rapid insights > Healthfirst Global into Population Health Status & Needs Introducing the Population Health Commissioning Atlas (PHCAtlas) Population Health Solutions >
3 > Who are we? > Healthfirst Network is a national not for profit organisation focussed on supporting population health and primary health care providers. > Healthfirst Global > We have over 20 years experience in the Primary Health Care sector - servicing general practice teams, allied health, regional health authorities (Divisions, Medicare Locals & local health networks), aged care sector, community services organisations. > The three core areas of activity: 1. Healthfirst Care include aged care, mental health and chronic disease management (eg National Diabetes Care Pilot). 2. Healthfirst Training Australia, our nationally accredited Registered Training Organisation (RTO) e.g. Diploma Population Health. 3. Healthfirst Global : e-health solutions and Tele-health; GP data analytics (Practice Health Atlas); population health intelligence, research and rapid reviews (Population Health Commissioning Atlas);. Population Health Solutions >
4 > Population Health Commissioning Atlas TM (PHCAtlas) Provides a data driven rapid insight into the health status & needs of a regional population. For PHC Organisations: MLs, LGAs, ATSI + LHNs. > Healthfirst Global A key focus on social determinants, Chronic Disease continuum & National KPIs A Narrative for story-telling & engagement (start of a journey of discovery) Primarily a resource for decision makers at regional level (e.g. population health planners, commissioners, and board directors) Why? - to inform rational resource allocation to optimise health outcomes & equity in a population Population Health Solutions >
5 > Population Health Commissioning Atlas TM (PHCAtlas) > Healthfirst Global Process: Engage CEO, Senior Executive and Population Health planners from the start - manage expectations Developed interactively with the regional organisation Workshops (x 2): community & stakeholders Optional workshop with academic community + Optional International reviewer Aim for a rapid turn-around 2 to 3 months Ensure Information rich product with lots of data visualization aids maps/tables Key themes / challenges emerging from the analysis are highlighted High level recommendations to inform rational resource allocation to optimise health outcomes and equity Population Health Solutions >
6 Population Health Commissioning Atlas & Chronic Disease Continuum >
7 > Population Health Commissioning Atlas TM (PHCAtlas) PHCA Key components (for MLs) > Healthfirst Global At the core of the PHCAtlas is a matrix across seven health domains that allows an ML to benchmark against NHPA KPIs and other locally important indicators, as well as a SLA variation analysis within the ML region. Based on the above and purchaser requirements Critical data (public & private) and other supporting evidence is sourced, analysed, interpreted and presented in a lean but information rich visual format that provides timely intelligence. Final section provides independent, evidence based set of recommendations around key emerging themes for regional prioritisation, further in-depth analyses and planning. Population Health Solutions >
8 > Population Health Commissioning Atlas TM (PHCAtlas) > Healthfirst Global PHCA Key public data sources AIHW ABS Census (2011), SEIFA, National Health Surveys data PHIDU (Synthetic data) State Cancer Registries ED, Hospital Separations & Avoidance Regional/Local data collections / surveys Medicare: MBS, PBS, ACIR data Workforce data sets (HWA) Australian Indigenous (HealthInfoNet) General Practice Data (Public & Private) **Data qualification statement Population Health Solutions >
9 PHC Atlas Structure > Overview region at a glance Demographics - SEIFA Workforce / Facilities locations Service Utilisation Data + Hosp Avoidance Population Health Profiling social determinants, risk factors screening, chronic disease, etc Health Domains (x7) Matrix: - ML Benchmarking (National KPIs) & SLA variation analysis Vulnerable sub-populations / needs Priority Needs Assessment based on domains, SLA variation and specific subpopulations - key emerging themes Commissioning approach & initial recommendations for areas of intervention
10 PHC Atlas Domains & ML KPIs + SLA variation > The 7 domains are: Access & Service Utilisation Lifestyle & Prevention Chronic Disease Management Screening Child Health Mental Health Aged care ML Benchmarking: Quintiles NPHA National Performance KPIs for MLs (where data available) SLA Analysis: selected indicators Variation and patterns within the ML region (clustering)
11 PHC Atlas Sub-populations > Vulnerable populations (nongeographic) analysis: ATSI (Indigenous) Homeless Refugees / New Arrivals Veterans Aged in RACFs People with disabilities CALD Children < 5 years Maternal health Young people / students Fly in / Fly out Prison population etc
12 CAH Medicare Local: Overview & SEIFA: Population Health Commissioning Atlas > At a glance: Population: 504,508 (1/3 of SA) GPs: 873; PNs: 199 Practices: 213 RACFs: 98 (Beds: 5735) SEIFA across 26 SLAs in ML (number, rank & quintiles) and
13 Medicare Local Benchmarking: starting point Population Health Commissioning Atlas > > ML Quintile range: Darker colour = greatest need
14 SLA variation & patterns within Medicare Local: Population Health Commissioning Atlas > > Indicator range for SLAs within an ML beyond averages SLAs with greatest needs form clusters across multiple indicators
15 Medicare Local GPs (&PNs) + Allied Health: Population Health Commissioning Atlas > >
16 Medicare Local RACFs and 65 yr old % : Population Health Commissioning Atlas > >
17 Medicare Local Social Determinants (variation) Population Health Commissioning Atlas > >
18 Medicare Local GP data: PHC Atlas> > Diabetes Profiling: Including CV risk and Multi-morbidity Using GP Sentinel Data (CAHML only)
19 > GP Sentinel Data Program > Healthfirst Global > Provides rich local intelligence to inform regional population health status and needs using GP data. GP practices are selected on the basis of location in an area of identified need & who can provide high quality de-identified data. Involves the aggregation of de-identified individual practice PHA data that is mapped to a geography or region of interest (eg postcode, SA2/SLA via geo-tagging). Participating practices funded & also commit to ongoing CQI re data quality & coding. Supported by ML staff around targeted PDSAs to address specific population (via practice) needs & health outcomes. Linked into progress with regional population health impact evaluations. Population Health Solutions >
20 Sentinel General Practice: Multi-morbidity matrix > Table 16. Multi-morbidity Matrix: Number of Patients Diabetes Asthma Hypertension Mental Health COPD CHD Stroke CRD/I Osteoporosis Dementia Osteoarthritis Diabetes Asthma Hypertension Mental Health 6, COPD CHD 2, Stroke CRD/I Osteoporosis Dementia Osteoarthritis 4941 Table 17. Multi-morbidity Matrix: Percentage of Patients Diabetes Asthma Hypertension Mental Health COPD CHD Stroke CRD/I Osteoporosis Dementia Osteoarthritis Diabetes 100.0% 10.7% 61.5% 22.1% 5.7% 20.2% 6.4% 4.4% 15.7% 2.5% 30.4% Asthma 100.0% 21.7% 20.2% 5.7% 6.1% 1.9% 0.9% 9.4% 0.7% 15.9% Hypertension 100.0% 21.5% 5.4% 22.0% 6.3% 3.6% 18.8% 2.6% 31.0% Mental Health 100.0% 3.5% 7.7% 3.4% 0.5% 12.1% 1.9% 21.2% COPD 100.0% 31.8% 7.2% 4.2% 27.5% 4.2% 8.1% CHD 100.0% 34.8% 6.9% 21.1% 4.5% 33.7% Stroke 100.0% 6.5% 26.7% 7.2% 38.2% CRD/I 100.0% 24.0% 4.5% 39.3% Osteoporosis 100.0% 4.2% 41.1% Dementia 100.0% 38.7% Osteoarthritis 100.0%
21 Sentinel General Practice: CV Event risk >
22 PHCAtlas outcomes > > PHCA recommendations Summary of outcomes of the data analysis, stakeholder engagement & service needs Highlights key emerging themes and challenges to address (eg areas of greatest need or unwarranted variation) Creates a set of interim recommendations for the board and planners to consider and prioritise
23 PHCA Uses > 1. Creates a local health agenda with context : Key messages / narrative (story-telling) Transparency, accountability & equity 2. Engagement tool with : Members; Stakeholders & Community groups; Funders & Researchers 2. Highlights areas for in-depth analyses / review of services 3. Assists with partnerships & joint planning (eg ML and LHNs / LGAs) Aligned prioritisation & Integration of Population Care interventions 4. Completes most of first stage of Commissioning Cycle (Assess) Input to options appraisal, business cases and funding streams 5. Highlights gaps in data for better population health intelligence 5. Background for funding / grant proposals
24 Medicare Locals & LGA PHCAs completed > ML PHCAs x5 : CAHML (SA); ACTML; WBML & LHN (Qld); KPML (WA) & NTML. LGA PHA x 1: Unley & Mitcham Councils (SA) ATSI PHCA Addendum: NTML and KPML
25 PHCA Feedback & Evaluation > 1. Formal evaluation of PHCA by MLs: CAHML commenced, others in planning phase 2. International reviewers & commentary (UK) 3. National Symposium (15 October 2013): Critical Success factors for Population Health Planning Key note speakers: Prof Vivian Lin and Prof John Glover 4. Qualitative Feedback (from ML CEOs and Boards)
26 National Symposium (1) Data sources and quality Data definitions & coding (variable and change over time) Access to routine data collections: ABS, Medicare, ACIR State registries vs National (eg cancer) Age of source data, completeness, validity & reliability Synthetic Data (PHIDU) limitations: estimates of prevalence Public and private data / inter-sectoral collaboration Additional new data collections to fill in gaps Granularity of data sources (National/State only vs SLA)
27 National Symposium (2) Methodology and benchmarking Sampling methodologies and generalisation KPIs with no existing or reliable data source Longitudinal data linkage issues ABS Boundaries and jurisdictions not aligned ABS change from SLA to SA2 (different boundaries) Clustering of SLAs : CAHML x 26 SLAs 500K population vs ACTML 100+ SLAs 370K population (21 SLA clusters)
28 National Symposium (3) Data interpretation & presentation Data visualisation including info-graphics Case studies, narratives Privacy Limitations due to privacy concerns vs public health benefits Data suppression or aggregation upwards De-identified aggregated data & longitudinal data linkages Data governance, training and research Roles of PHIDU, PHCRIS, AIHW and NPHA Supporting clnicians quality data coding (eg RACGP, AGPAL) Role of PCEHR (data quality and safety) Population health training for ML Boards & staff Research and Development (ANU Geo-Medicine)
29 PHCA Qualitative feedback > The PHCAtlas provided a very useful population health profile of the ACT region which helped inform ACTML s Population Health Interim Needs Assessment and priority setting. This was the first time that data/information has been used by ACTML to provide a visual document which highlighted variations in health status at an SLA level. Leanne Wells, CEO, ACT Medicare Local This is a powerful document which provides us with lifestyle risk and disease prevalence data across our region including heat maps and data interpretation, comparative analysis against other Medicare Locals and recommendations for prioritisation of effort. Healthfirst Network are tremendous to work with, know the primary health care sector and met our tight deliverables schedule. Chris Pickett, CEO, Kimberley Pilbara Medicare Local Having a comprehensive PHCAtlas produced by Healthfirst Network has helped Central Adelaide and Hills Medicare Local define its priorities down to sub regional locations. The Population Health Commissioning Atlas clearly displays demographic information layered with prevalence data aligned and benchmarked to the Medicare Local Performance Accountability Framework. Healthfirst Network has produced very high quality publication that not only aids our health service planning but also our marketing strategy. Chris Seiboth, CEO, Central Adelaide and Hills Medicare Local
30 Harness Local Intelligence & Intuition... You can use all the quantitative data you can get, but you still have to distrust it and use your own intelligence and judgment. Alvin Toffler Any Questions?
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