Predicting who will need costly care Ray Beatty Care Services Efficiency Delivery Programme

CSED Introduction ■CSED set up by DH to help councils meet Gershon targets in Adult Social Care – Deliver evidence-based, pragmatic, practical efficiency improvement solutions to councils - by March 2008 – DH decision to extend CSED activity into the CSR07 timeframe ■Demand forecasting and planning one of 6 CSED workstreams has delivered: – POPPI web-accessed forecasting solution with ONS population projections, characteristics and prevalence from census and research – FLoSC – Forecasting Length of Stay and Cost – Toolkits for consultation and joint health/care service opportunities – Methodology briefs ■Regional teams working with councils on process improvements

Care Services Efficiency Delivery Programme Why Predictive Modelling? ■Kaiser Permanente in California seemed to provide higher quality healthcare than NHS at lower cost * Getting more for their dollar: a comparison of the NHS with California's Kaiser Permanente BMJ 2002;324: ■Kaiser identify high risk people in their population and manage them intensively to avoid admissions – Unplanned hospital admissions undesirable, costly - some avoidable ■PARR [Patients at Risk of Re-admission] developed by King’s Fund with NYU and Health Dialog for NHS - results better than: – Clinician referrals – Threshold approaches (e.g. aged >65 with 2+ admissions) ■PARR++ and Combined Model available to PCTs 2007 ■King’s Fund commissioned by CLG to explore how PARR could be extended to include social care

Care Services Efficiency Delivery Programme Inpatient data A&E dataGP Practice data Social Services data Outpatient data PARR Patterns in routine data Combined Model Census data

Care Services Efficiency Delivery Programme J7KA Encrypted, linked data Decrypted data with risk score attached  Inpatient  Outpatient  A&E  GP Name, Address, DOB

Care Services Efficiency Delivery Programme 10 Million Patient-Years of Data 5 Million Patient-Years of Data 5 Million Patient-Years of Data DevelopmentValidation Predictive Model Randomised

Care Services Efficiency Delivery Programme Very High (0 – 0.5%) High (0.5 – 5%) Moderate (5 – 20%) Low (20 – 100%) Risk Segmentation Kaiser pyramid divides into 4 segments: 20% 80% Top three segments combined make up the top quintile Bottom segment represents the bottom four quintiles combined Distribution of Future Utilisation is Exponential

Care Services Efficiency Delivery Programme Very High (0 – 0.5%) High (0.5 – 5%) Moderate (5 – 20%) Low (20 – 100%) NUMBER OF PATIENTS FUTURE UTILISATION Individuals at very high risk will use disproportionately large amounts of resources each But the bulk of future utilisation for the population comes from the rest of the top quintile

Care Services Efficiency Delivery Programme Predictions based on routine data ■Evidence that certain preventative interventions are effective at avoiding or delaying care home admission – but only cost-effective if offered to people at high risk ■Many factors predictive of care home admission – face-to-face tools have been built using these factors ■Predictions based on routine data – less labour intensive so can stratify the population systematically and repeatedly – avoid “non-response bias” – can identify people with lower, emerging, risk – less susceptible to the inverse care law – can be used for resource allocation – potential use as a performance assessment tool

Care Services Efficiency Delivery Programme Issues ■Issues of confidentiality and consent to consider [PIAG] – Decryption by patients GP ■Linking data sources at individual level across health and social care is particularly problematic ■The tools are not 100% accurate – probability – False positive/negatives occur ■Data may be missing from routine databases – NHS and GP data needed for coverage ■Evidence base for ‘upstream’ interventions needs to be developed – Intervention modes and costs for implementation ■Investments/returns to NHS and councils uncertain – Issues with joint or cross funding, self-payers, IB/DP

Care Services Efficiency Delivery Programme Status and next steps ■DH contract with Nuffield Trust for model development – PARR team involvement – Reference Group for project direction – CSED in DH client role ■4-5 pilot sites (Whole System Demonstrators) – Identify data sources – Accessibility of individual level data – Data linkage & confidentiality ■Build & test predictive models – Optimise predictive power ■Research project – If successful, software tool development 2009 ■Implementation by local health/care communities