Using Information to Support health and social care Lorna Jackson Head of Programme

Content Scene setting –Illness/care and evolution of policy Three key uses of information –Understanding the local context –Predicting need –Service use/resource allocation

The landscape of illness/care Range of long and short term conditions Progression of care settings through: home/self carepublic health messages support in own homegroup based, anticipatory care/tele care case management care home NHS continuing care

Policy Background Pre- ‘Kerr Report’ Recognition of pressures on Acute system Rates of emergency admission rising steadily 5% of inpatients account for 43% of total inpatient days These are mainly older people who experience more than one admission Projections - population is getting/will get older

Match complexity of condition/care need with appropriate level of care/intervention

Pre Better Health/ Better Care: Kerr / Delivering for Health (2005) Current model New model of care Geared towards acute conditionsGeared towards long-term conditions Hospital centredLocally responsive Doctor dependent Team based Episodic careContinuous care Disjointed care Integrated care Reactive carePreventative care Patient as passive recipient Patient as partner Self care tolerated Self care encouraged and facilitated Carers undervaluedCarers supported as partners

Concept of a ‘Mutual NHS' –Partnerships between patients and professionals, NHS and LA, housing, voluntary sector etc –Patients at the centre but not just ‘consumers’ but partners/owners with both ‘rights’ and ‘responsibilities’ –‘Building resilience’ and ‘capacity’ of communities and individuals to improve health –Positive health behaviours, better self care and support for carers Better health, Better Care (2007)

Key policy aspects ‘Shifting the balance’ –from acute hospitals to community based care/settings –from care homes to care at home Increasing partnership working, health, social work, housing Person centred assessments/information provision Emphasis on patients as partners with Individual responsibility

How can we use information to support these processes? What is the local context? -demographics -local service configuration Can we predict the people who are likely to need care/support? Are the right people getting the right services?

The local context: ScotPHO CHP profiles To be distributed to all CHPs (June 08) Contains 60 indicators drawn from various sources Information grouped under 10 headings

1.Population profile 2.Mortality 3.Substance use 4.Ill health and injury 5.Mental health 6.Social care and housing 7.Education and employment 8.Crime 9.Environment 10.Child and maternity health

Risk prediction What is SPARRA? Scottish Patients At Risk of Readmission and Admission

A bit more detail To estimate a patient’s risk the algorithm uses the patient’s demographics (age, sex, deprivation) and factors from their history of hospital admission over the 3 years prior to the year of interest Number of previous emergency admissions Time since last emergency admission Total bed days accumulated in the 3 years Principal diagnosis (last emergency admission) Co-morbidity – number of diagnostic groups Number of Elective admissions Predictor variables Outcome year Historic Period 2005/6 2006/7 2007/8 2008/9

SPARRA coverage Match complexity of condition/care need with appropriate level of care/intervention

Scotland SPARRA ‘scores’ – Scotland The SPARRA cohort: Those aged over 65 with at least one emergency admission in the previous three years. About 25% of the 65 and over population.

SPARRA the ISD service Customers at Board, CHP & practice level receiving data relating to their populations Aggregated –Distribution of risk scores –Characteristics of risk categories Patient-level –Patient listing with ID, risks scores & factor values –Threshold option Use of SystemWatch / CHI index to ensure up-to-date data Quarterly updates –NHS /encrypted /CD

Actual Output Identifiable (60% and over). These records must always be checked against up to date data on local operational systems (especially to check that patients are still alive).

1.Better understanding of what SPARRA is being used for & extent: (questionnaire, user feedback) 2.SPARRA ‘All ages’ – (BHBC commitment by June 2008) - Report to be published on ISD Online 24 th June 3.Mental Health SPARRA – (August 2008) 4.‘Medium Risk SPARRA -(BHBC commitment by Dec 2008) –a comprehensive risk-stratification tool –a greater focus on those yet to enter the cycle of repeat emergency admission SPARRA Development

Indicator of Relative Need SSA-IoRN Clients grouped according to their level of need primarily for social care: –activities of daily living and mobility –personal care –food and drink preparation –mental well-being and behaviour –bowel management Groupings are ‘a-i’ with group ‘i’ requiring most support ISD do not receive IoRN data

Predicting people who may need increasing social care support? SPARRA and IoRN have developed separately but they could be linked locally There may be other social care data held locally which could be used to aid prediction of increasing need – informal support, accommodation?

CH(C)P demonstration projects ISD staff spending time to understand how CH (c) Ps are evolving Working in partnership with CH (C) Ps to understand information needs and solve problems identified locally SW Glasgow, Renfrewshire, Perth, Highland, West Lothian

Understanding patterns of service up-take: SW Glasgow example Use SPARRA model to identify people at high risk, medium risk and low risk of hospital admission. Link to local data systems – primary care (GPASS), social care (Carefirst), community mental health (PIMS)

SW Glasgow project (2) Are those most in need/ at risk of emergency admission receiving the most intensive care services? How does the ‘tiered services’ model work in practice, which clients receive which services? What are the triggers/factors that lead to emergency admissions?

West Lothian CHCP: using SPARRA within health service research How effective is local anticipatory care been? –calculate SPARRA scores for patients who were part of anticipatory service –create a ‘control group’ of case adjusted patients who did not receive the anticipatory service (ie from similar area, or previous time period)

Summary Often we are data rich but information poor Information can be used productively to –understand the local context –identify those in need of support/care –understand where resources are being used and make informed choices about service provision

Challenges Sharing information between health and social care partners –IT systems –Professional cultures –Information governance Making time – stepping back from the coal face