Predicting who will use intensive social care: case finding tools based on linked health and social care data.
BACKGROUND
the costs of delivering health and social care services are rising as the population ages and more people live with chronic diseases.


OBJECTIVE
to determine whether predictive risk models can be built that use routine health and social care data to predict which older people will begin receiving intensive social care.


METHODS
analysis of pseudonymous, person-level, data extracted from the administrative data systems of local health and social care organisations.


METHODS
five primary care trust areas in England and their associated councils with social services responsibilities.


METHODS
people aged 75 or older registered continuously with a general practitioner in five selected areas of England (n = 155,905).


METHODS
multivariate statistical analysis using a split sample of data.


RESULTS
it was possible to construct models that predicted which people would begin receiving intensive social care in the coming 12 months. The performance of the models was improved by selecting a dependent variable based on a lower cost threshold as one of the definitions of commencing intensive social care.


CONCLUSIONS
predictive models can be constructed that use linked, routine health and social care data for case finding in social care settings.
The Nuffield Trust, 59 New Cavendish Street, London W1G 7LP, UK.
Martin
M
Bardsley
John
J
Billings
Jennifer
J
Dixon
Theo
T
Georghiou
Geraint Hywel
GH
Lewis
Adam
A
Steventon
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D000465:Algorithms; D000553:Ambulatory Care / Q000706:statistics & numerical data; D004739:England; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data; D006299:Health Services for the Aged / Q000191:economics / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data; D008297:Male; D015233:Models, Statistical; D011320:Primary Health Care / Q000191:economics / Q000706:statistics & numerical data*; D018570:Risk Assessment; D012307:Risk Factors; D012947:Social Work / Q000191:economics / Q000706:statistics & numerical data*