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SPARRA MD

Mike Muirhead, ISD ScotlandMike Muirhead, ISD Scotland

SPD Network conference. SPD Network conference. 44thth September, 2008 September, 2008

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SPARRA

SScottish cottish PPatients atients AAt t RRisk of isk of RRe-e-admission and admission and AAdmissiondmission

( cf PARR model – King’s Fund)

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Aim of SPARRA MD

• Identify those individuals most at risk of Identify those individuals most at risk of psychiatric re-admission to hospital in psychiatric re-admission to hospital in next twelve monthsnext twelve months

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Aim of SPARRA MD

• Identify those individuals most at risk of Identify those individuals most at risk of psychiatric re-admission to hospital in psychiatric re-admission to hospital in next twelve monthsnext twelve months

• Re-admission Re-admission notnot admission admission

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Personality Disorder – some inpatient stats

..

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Personality Disorder – some inpatient stats

• 4.0% of patients admitted in 06/07 were for PD4.0% of patients admitted in 06/07 were for PD

• 4.8% of total episodes in 06/07 were for personality 4.8% of total episodes in 06/07 were for personality disorder. disorder.

• Frequency of admissionFrequency of admission– 72 % patients admitted once– 15% patients admitted twice– 13% patients admitted 3 or more times

• 2.5% of total beddays were for PD.2.5% of total beddays were for PD.

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PD hospital episodes (06/07); rate/1000 pop by age

0.0

2.0

4.0

6.0

8.0

10.0

12.0

<15 15-24 25-44 45-64 65-74 75+

rate

/ 1

00

0 p

op

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Two separate models

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Two separate models

1. Psychiatric inpatient admission based 1. Psychiatric inpatient admission based on SMR04 recordson SMR04 records

2. Psychiatrically related emergency 2. Psychiatrically related emergency admission to acute hospital based on admission to acute hospital based on SMR01 records SMR01 records

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Two separate models

1. Psychiatric inpatient admission based 1. Psychiatric inpatient admission based on SMR04 recordson SMR04 records

2. Psychiatrically related emergency 2. Psychiatrically related emergency admission to acute hospital based on admission to acute hospital based on SMR01 records SMR01 records

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1st April 2006

Predictor variablesOutcome year

Developing the predictive model

Time Period

2003 2004 2005 2006

Model is based on previous 3 years of hospital admissions

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1st April 2006

Predictor variablesOutcome year

Developing the predictive model

Time Period

2003 2004 2005 2006

Model is based on previous 3 years of hospital admissions

38,000 patients (15=+)38,000 patients (15=+)

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SMR04 model: significant predictor variables

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SMR04 model: significant predictor variables

AgeAge (risk tails off after age 50)(risk tails off after age 50)Previous admissionsPrevious admissions (powerful effect) (powerful effect)Recency of admissionRecency of admission (powerful effect) (powerful effect)Total bed daysTotal bed days (moderate effect) (moderate effect)Most recent diagnosisMost recent diagnosis (moderate effect) (moderate effect)Urban / ruralUrban / rural (slight effect) (slight effect)

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SMR04 model: significant predictor variables

AgeAge (risk tails off after age 50)(risk tails off after age 50)Previous admissionsPrevious admissions (powerful effect) (powerful effect)Recency of admissionRecency of admission (powerful effect) (powerful effect)Total bed daysTotal bed days (moderate effect) (moderate effect)Most recent diagnosisMost recent diagnosis (moderate effect) (moderate effect)Urban / ruralUrban / rural (slight effect) (slight effect) Not significantNot significant: deprivation, NHS Board, gender, : deprivation, NHS Board, gender,

formal admission, number of different formal admission, number of different diagnosesdiagnoses

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Relationship between diagnosis and likelihood of admission

0.50.60.70.80.9

11.11.2

rela

tive

ris

k

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SMR04 model: distribution of probabilities of admission in 2005

2705

15711028

717 472

12300

13366

5606

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

0-10% 10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70+%

Predicted risk

Nu

mb

er

of

ca

se

s

50% and over 2217

5% of cohort

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Age group make up of SPARRA risk categories

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-10% 10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70-80% 80-90% 90% andover

Total

Risk Probability Group

Per

cent

age

(%) 65+

45-64

15-44

Age Group

Scotland

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Number of Admissions by SPARRA Mental Disorders risk categories

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-10% 10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70-80% 80-90% 90% andover

Risk Probability Group

Per

cent

age

(%)

6 or moreadmissions5 admissions

4 admissions

3 admissions

2 admissions

1 admission

Admissions

Scotland

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Most recent Diagnosis group by SPARRA Mental Disorders risk categories

0%

20%

40%

60%

80%

100%

0-10% 10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70-80% 80-90% 90% andoverRisk Probability Group

Per

cent

age

(%)

Childhood/adolescent onset

Disorders of psychologicaldevelopment

Mental retardation

Disorders of personality andbehaviour

Eating disorders etc

Neurotic, stress-related,anxiety etc.

Bipolar disorder

Mood (affective) disorders(manic depression)

Schizophrenia etc.

Psychoactive substanceabuse related (alcohol anddrug misuse) Organic (includes dementia)

Other

Most recent Diagnosis groupScotland

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SPARRA model: Example I

Very high risk (78%).Very high risk (78%).

• Male aged 25-29 Male aged 25-29 • 6+ admissions.6+ admissions.• 120 bed days. 120 bed days. • Most recent diagnosis: Personality Most recent diagnosis: Personality

disorderdisorder

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SPARRA model: Example II

High risk (65%).High risk (65%).

• Female aged 40-44Female aged 40-44• 6+ admissions. 6+ admissions. • 60 bed days. 60 bed days. • Diagnosis: schizophreniaDiagnosis: schizophrenia..

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SPARRA model: Example III

Low risk (20%)Low risk (20%)

• Female aged 37. Female aged 37. • 1 admission.1 admission.• 15 days.15 days.• Diagnosis: mood affective disorder.Diagnosis: mood affective disorder.

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What’s next?

• Piloting and evaluation of model– Is it helpful?– Does it add anything?

• Offer to all NHS boards

• Ensure integration with “classic” SPARRA

• Address data completeness/timeliness issues

• Extend the model – prescribing data & primary care (longer term)

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Total number of Psychiatric Bed days by SPARRA Mental Disorders risk categories

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-10% 10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70-80% 80-90% 90% andover

Risk Probability Group

Per

cent

age

(%)

Greater than 100days

Between 51-100days

Between 32-50days

Between 11-31days

Between 0-10days

Bed days

Scotland

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Personality disorders

• F60 Specific personality disorders F60 Specific personality disorders

• F61 Mixed and other personality disordersF61 Mixed and other personality disorders

• F62 Enduring personality changes, not attributable to brain damage and F62 Enduring personality changes, not attributable to brain damage and disease disease

• F63 Habit and impulse disordersF63 Habit and impulse disorders

• F64 Gender identity disorders F64 Gender identity disorders

• F65 Disorders of sexual preference F65 Disorders of sexual preference

• F66 Psychological and behavioural disorders associated with sexual F66 Psychological and behavioural disorders associated with sexual development and orientationdevelopment and orientation

• F68 Other disorders of adult personality and behaviourF68 Other disorders of adult personality and behaviour

• F69 Unspecified disorder of adult personality and behaviourF69 Unspecified disorder of adult personality and behaviour