2. t : 020 7631 8450 e : info@nuffieldtrust.org.uk www.nuffieldtrust.org.uk The Nuffield Trust
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5. Frequently-admitted patients 0 5 10 15 20 25 30 35 40 45 50 - 5 - 4 - 3 - 2 - 1 Intense year + 1 + 2 + 3 + 4 Average number of emergency bed days
6. Regression to the mean 0 5 10 15 20 25 30 35 40 45 50 Average number of emergency bed days - 5 - 4 - 3 - 2 - 1 Intense year + 1 + 2 + 3 + 4
7. Emerging Risk 0 5 10 15 20 25 30 35 40 45 50 Average number of emergency bed days - 5 - 4 - 3 - 2 - 1 Intense year + 1 + 2 + 3 + 4
8. Kaiser Pyramid The Pyramid represents the distribution of risk across the population Small numbers of people at very high risk Large numbers of people at low risk [Size of shape is proportional to number of patients]
9. Inpatient data A&E data GP Practice data Outpatient data PARR Patterns in routine data Combined Model Census data
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11. J7KA42 J7KA42 J7KA42 J7KA42 J7KA42 J7KA42 76.4 131178 76.4 Encrypted, linked data Decrypted data with risk score attached 131178 131178 131178 131178 Inpatient Outpatient A&E GP Name, Address, DOB Name, Address, DOB Name, Address, DOB Name, Address, DOB
12. 10 Million Patient-Years of Data 5 Million Patient-Years of Data 5 Million Patient-Years of Data Development Validation
13. J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R Year 1 Year 2 Year 3 Development Sample Inpatient Outpatient A&E GP
14. J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R Development Sample Year 1 Year 2 Year 3 Inpatient Outpatient A&E GP
15. J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R J7KA42 YH8TPP G8HE9F 3LWZ67 2NX632 LG5DSD 3V9D54R Development Sample Year 1 Year 2 Year 3 Inpatient Outpatient A&E GP
17. A89KP5 833TY6 I9QA44 85H3D 6445JX 233UMB RF02UH A89KP5 833TY6 I9QA44 85H3D 6445JX 233UMB RF02UH Using the Model Last Year This Year Next Year Inpatient Outpatient A&E GP
18. Distribution of Future Utilisation £0 £500 £1,000 £1,500 £2,000 £2,500 £3,000 £3,500 £4,000 £4,500 0 10 20 30 40 50 60 70 80 90 Predicted Risk (centile rank) Actual Average cost per patient
35. Trend Model predicts: Cost Details Model predicts which patients will become high-cost over next 6 or 12 months Examples Low-cost patient this year will become high-cost next year
36. Trend Model predicts: Cost Event Details Model predicts which patients will become high-cost over next 6 or 12 months Model predicts which patients will have an event that can be avoided Examples Low-cost patient this year will become high-cost next year Patient will be hospitalized Patient will have diabetic ketoacidosis
37. Trend Model predicts: Cost Event Actionability Details Model predicts which patients will become high-cost over next 6 or 12 months Model predicts which patients will have an event that can be avoided Model predicts which patients have features that can readily be changed Examples Low-cost patient this year will become high-cost next year Patient will be hospitalized Patient will have diabetic ketoacidosis Patient has angina but is not taking aspirin Patient does not have pancreatic cancer (Ambulatory Care Sensitive)
38. Trend Model predicts: Cost Event Actionability Readiness to engage Details Model predicts which patients will become high-cost over next 6 or 12 months Model predicts which patients will have an event that can be avoided Model predicts which patients have features that can readily be changed Model predicts which patients are most likely to engage in upstream care Examples Low-cost patient this year will become high-cost next year Patient will be hospitalized Patient will have diabetic ketoacidosis Patient has angina but is not taking aspirin Patient does not have pancreatic cancer (Ambulatory Care Sensitive) Patient does not abuse alcohol Patient has no mental illness Patient previously compliant
39. Trend Model predicts: Cost Event Actionability Readiness to engage Receptivity Details Model predicts which patients will become high-cost over next 6 or 12 months Model predicts which patients will have an event that can be avoided Model predicts which patients have features that can readily be changed Model predicts which patients are most likely to engage in upstream care Model predicts what mode and form of intervention will be most successful for each patient Examples Low-cost patient this year will become high-cost next year Patient will be hospitalized Patient will have diabetic ketoacidosis Patient has angina but is not taking aspirin Patient does not have pancreatic cancer (Ambulatory Care Sensitive) Patient does not abuse alcohol Patient has no mental illness Patient previously compliant Patient prefers email rather than telephone Patient prefers male voice rather than female Readiness to change
