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Predictive Models and data linkage
This document discusses using predictive models and linking different types of healthcare data to improve quality and efficiency. It provides examples of predictive models being used in the UK to identify high-risk patients and assess their future healthcare costs. The document also outlines how linking data from various sources, like medical records, hospital data, and social care, can provide a more comprehensive view of patients' care over time. Evaluating the impact of interventions using retrospective analyses with matched controls is discussed. Protecting patient privacy when linking personal data is also addressed.
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Predictive Models and data linkage
- 1. Predictive Models andData Linkage Sharing international experience: Linking disease registry information and predictive modelling to improve quality and efficiency September 2012 Martin Bardsley Head of Research The Nuffield Trust © Nuffield Trust
- 2. Applications of predictiverisk in the UK • Case finding for people at high risk of admission seen as increasingly important for people with LTCs and complex conditions • Examples of predicting across health and social care • Scope to make the most of linked data sets in describing care pathways • Evaluation and risk adjustment © Nuffield Trust
- 3. Predictive risk andcase finding © Nuffield Trust
- 4. Predictive modelling inUK • BMJ in paper* in 2002 showed Kaiser Permanente in California seemed to provide higher-quality healthcare than the NHS at a lower cost. Kaiser identify high risk people in their population and manage them intensively to avoid admissions • • Modelling aims to identify people at risk of high costs in future • Relies on exploiting existing information +ve: systematic; not costly data collections; fit into existing systems -ve: information collected may not be predictive • *Getting more for their dollar: a comparison of the NHS with California's Kaiser Permanente BMJ 2002;324:135- 143 © Nuffield Trust
- 5. Predictive Models Identifywho will be where on next year’s Kaiser Pyramid © Nuffield Trust
- 6. Regression to themean: Change in average number of emergency bed days Predictive models try to identify people here © Nuffield Trust
- 7. Extending models beyondhealthcare © Nuffield Trust
- 8. Information flows © Nuffield Trust
- 9. Protecting individuals identities © Nuffield Trust
- 10. Looking at andindividuals history of care One person’s story © Nuffield Trust
- 11. Typical accuracy modelscurrently used to predict hospital admission Model Risk threshold PPV (%) Sensitivity (%) PARR (England) 50 65.3 54.3 70 77.4 17.8 80 84.3 8.1 SPARRA (Scotland) 50 59.4 18.0 70 76.1 3.3 S Care model 50 55 19 (Pooled £1K) 70 60 10 © Nuffield Trust
- 12. Range of casefinding models available SPARRA PARR (++) SPARRA MD Combined Predictive Model PRISM PEONY AHI Risk adjuster LACE ACGs (John Hopkins) MARA (Milliman Advanced Risk Adjuster) DxCGs (Verisk) Dr Foster Intelligence SCOPE RISC (United Health Group) Variants on basic admission/readmission predictions: Short term readmissions Social care costs Condition specific tools © Nuffield Trust
- 13. Wider applications oflinked data © Nuffield Trust
- 14. Using the dataavailable © Nuffield Trust
- 15. Testing for gapsin care © Nuffield Trust
- 16. North West e-lab © Nuffield Trust
- 17. Relative size ofdata sets collected For one WSD area Accident and Outpatients Inpatients Social care Community GPs emergency 1,680,000 records 360,000 records 240,000 records matrons 60 practices 350,000 records 20,000 records 48.5 million records March 2011 © Nuffield Trust
- 18. Data linkage Social &secondary care interface © Nuffield Trust
- 19. Inpatient and SocialCare costs per person in final year of life by age band over two lines £12,000 £10,000 £8,000 £6,000 Social care £4,000 Hospital IP care £2,000 SC+ Hosp £0 40 50 60 70 80 90 100 Age Band © Nuffield Trust
- 20. Number of inpatientadmissions (with 95% confidence intervals) per person by age according to type of social care received Bardsley M, Georghiou T, Chassin L, Lewis G, Steventon A, and Dixon J. Overlap of hospital use and social care in older people in England J Health © Nuffield Trust Serv Res Policy jhsrp.2011.010171; published ahead of print 23 February 2012,
- 21. Describing patterns ofsocial care around cancer diagnosis. Linkage to cancer registry © Nuffield Trust
- 22. What was theaverage cost of hospital care? © Nuffield Trust
- 23. GP visits aroundcancer diagnosis © Nuffield Trust
- 24. Risk adjustment andEvaluation a. Prospective Trials b. Retrospective evaluations © Nuffield Trust
- 25. Using risk scoreswithin a randomised trial Ensuring even mix of patients Analysis by risk subgroup March 2011 © Nuffield Trust
- 26. Information flows forthis analysis Local Secondary Uses Service Encrypted client-event Link to create Combined Nuffield operational based Model Trust systems GP Encrypted client-event based Linked Hospital Encrypted datasets Episodes client-event Statistics based HES-ONS Encrypted mortality data client-event based Community Encrypted systems client-event based Social care Encrypted client-event based © Nuffield Trust
- 27. Distribution of CombinedModel risk scores Importance of risk adjustment Very high risk Top 0.5% Top 10% High risk Moderate risk 0.5% - 5% Low risk 5% - 20% 10% - 45% 20% - 100% 45% - 85% 85% - 100% General population WSD participants © Nuffield Trust
- 28. Exploiting admin datawithin an RCT- trends in emergency hospital admissions Start of trial Able to chart hospital use before recruitment © Nuffield Trust
- 29. Linked data inRCTS • Enables larger sample sizes as its relatively cheap information • Able to generate multiple outcome measures • Track patient histories before baseline – and inform risk adjustment • Generate intermediate points • BUT • Constrained by type of information collected and quality • May exclude care from some sectors © Nuffield Trust
- 30. Retrospective evaluations The Partnershipfor Older People Projects (POPPs) •£60m investment by DH with aim to: “shift resources and culture away from institutional and hospital- based crisis care” •146 interventions piloted in 29 sites. •National evaluation of whole programme found £1.20 saving in bed days per £1 “We recommend expanding the spent. Partnerships for Older People Projects (POPPs) approach to prevention across all local authorities and PCTs.” © Nuffield Trust
- 31. From the 146interventions offered under POPP, we selected 8 for an in-depth study of hospital use Support workers for community matrons Intermediate care service with generic workers Integrated health and social care teams Out-of-hours and daytime response service + 4 different short term assessment and signposting services © Nuffield Trust
- 32. Our preferred optionfor this evaluation: link participants to HES through a trusted third party Collate files and add NHS Participating sites numbers Information Collate patient lists Centre Derive HES ID Nuffield Trust Patient identifiers Trial information (e.g. Non-patient identifiable keys (e.g. NHS number) start and end date) (e.g. HES ID, pseudonymised © Nuffield Trust NHS number) March 2011
- 33. Prevalence of healthdiagnoses categories in intervention and control groups © Nuffield Trust
- 34. Overcoming regression tothe mean using a control group Intervention 0.3 Start of intervention Number of emergency hospital admissions per head per month 0.2 0.1 0.0 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 11 12 Month March 2011 © Nuffield Trust
- 35. Overcoming regression tothe mean using a control group Intervention 0.3 Start of intervention Number of emergency hospital admissions per head per month 0.2 0.1 0.0 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 11 12 Month March 2011 © Nuffield Trust
- 36. Overcoming regression tothe mean using a control group Intervention 0.3 Start of intervention Number of emergency hospital admissions per head per month 0.2 0.1 0.0 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 11 12 Month March 2011 © Nuffield Trust
- 37. Overcoming regression tothe mean using a control group Control Intervention 0.3 Start of intervention Number of emergency hospital admissions per head per month 0.2 0.1 0.0 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 11 12 Month March 2011 © Nuffield Trust
- 38. Impact of eightdifferent interventions on hospital use © Nuffield Trust
- 39. Summary • Predictive modellingpractical case finding tool for identifying high risk patients • Possible to screen large populations using existing data • Scope to extend linkage over time and across data sets to give a broader view of patients’ journey • Large data sets can be used in both prospective studies (RCTs) and enable retrospective analyses using matched controls • Biggest weakness with existing administrative data is the limited level of clinical information – yet greater use of clinical records, audits and registries is possible © Nuffield Trust
- 40. www.nuffieldtrust.org.uk Sign-up for ournewsletter www.nuffieldtrust.org.uk/newsletter Follow us on Twitter (http://twitter.com/NuffieldTrust) © Nuffield Trust © Nuffield Trust