linkage between sscas data and mortality data

Linkage between SSCAS data and mortality data

Patients’ outcome

Determined by:

• Prior health and personal characteristics

• Severity of illness

• Effectiveness of treatment

• Chance

Previous analyses by ISD

• Used routinely collected hospital discharge data – SMR01 to identify cases

• Linked these to death certificate data from General Register Office

• Focused on case fatality by 30 days from admission

• Was limited in ability to adjust for casemix (age, sex and deprivation by postcode)

Stroke Outcomes 1990-93

Scottish Stroke Outcomes Study

WGHVHK GRI LAW Falk

Unadjusted 6 month case fatality

20 30 40 50Case fatality % (95% CI)

VHK

GRI

Law

WGH

Falkirk

6 month case fatality


VHK

GRI

Law

WGH

Falkirk

Adjusted for •age•pre-stroke independence•can walk?•can talk & not confused?•can lift both arms?


VHK

GRI

Law

WGH

Falkirk

Unadjusted

Methods of current linkage

• All MCNs gave permission to export individual patient data

• All centres have exported individual patient data to Mike McDowall (ISD contract)

• Linked these records with those held by ISD• Preliminary analyses to look at

– Data completeness by MCN and hospital– 6 month case fatality by MCN and hospital– 6 month case fatality adjusted for casemix

Patient included in analysesAll cases on SSCAS (n= 18831)

Linked to existing patient in ISD data (n= 17344)

Data available for casemix adjustment & included in analyses (n= 10018)

Survival data available for 6 months post admission (11507)

Restricted to stroke patients only (14421)

% of casemix data missingAge Lived

Alone?

Indepen-dent

Before?

Can

talk?

Lift

both

arms?

Can

walk?

Overall 0.0 2.5 4.4 4.1 5.7 5.3

Lowest 0.0 0.1 0.0 0.0 0.0 0.0

Highest 0.7 6.5 9.1 6.6 19.8 8.0

Excluding Island HBs with very small numbers

Factors likely to influence % of missing data in SSCAS

• Completeness of medical records

• Use of proforma or ICP

• Explicit collection of casemix variables

• Training & expertise of data extractor

• ? Willingness to best guess

• Amount of clinical support available

• Frequency of missing data checks

% dead at 6 months by Health Board

101520253035404550

Ayr

shir

e &

Arr

an

Bor

ders

Arg

yl &

Cly

de

Fif

e

Gre

ater

Gla

sgow

Hig

hlan

d

Lan

arks

hire

Gra

mpi

an

Ork

ney

Lot

hian

Tay

side

For

th V

alle

y

Wes

tern

Isl

es

Dum

frie

s &

Gal

low

ay

Shet

land

% surviving at 6 months by Health Board

40

50

60

70

80

90

100

Ayr

shir

e &

Arr

an

Bor

ders

Arg

yl &

Cly

de

Fif

e

Gre

ater

Gla

sgow

Hig

hlan

d

Lan

arks

hire

Gra

mpi

an

Ork

ney

Lot

hian

Tay

side

For

th V

alle

y

Wes

tern

Isl

es

Dum

frie

s &

Gal

low

ay

Shet

land

But these crude data do not take account of casemix and chance

• Need to adjust for differences in factors which are associated with case fatality

• Need to produce 95% confidence intervals to indicate precision of estimate

• Adjusted survival data should minimise the affect that poor case ascertainment has on results e.g. if you missed all severe strokes then your casemix would be mild.

Mean Age

68

70

72

74

76

78

80

Mea

n A

ge

Health Board Scotland

Younger than average

% Cases Independent

0

20

40

60

80

100

120

% C

ases


Odd

% Cases Living Alone

01020304050607080

% C

ases


% Cases Able to Lift Arms

01020304050607080

% C

ases


More severe Milder

% Cases Able to Walk

0

10

20

30

40

50

60

% C

ases


% Cases Able to Talk

0102030405060708090

% C

ases


% of total who showed haemorrhage on scan

0

5

1015

20

25

3035

40

45

% C

ases


Why might casemix vary between Health Boards?

• Different populations• Different admission criteria – e.g. do patients with

minor stroke in Fife and D & G stay at home or are treated in clinic?

• Were mild or severe cases missed by SSCAS?• Was casemix data missing for particular severity

of stroke patient in some places and therefore excluded from analyses?

W score explained

• Observed number of patients surviving at 6 months

• Predicted number of patients surviving at 6 months based on– Average survival for Scotland– Modelled using 6 casemix factors

• W is excess no. of survivors at 6 months per 100 admissions over that predicted (+ values good) with 95% confidence intervals

Unadjusted

-60

-50

-40

-30

-20

-10

0

10

20

30A

&A

Bor

ders

A&

C

Fife

GG

Hig

hlan

d

Lana

rk.

Gra

mp.

Ork

ney

Loth

ian

Tay

side

FV

W Is

les

D&

G

She

tland

W s

core

Good

Bad

Good

Bad

Adjusted with 6 variable model

-60

-50

-40

-30

-20

-10

0

10

20

30A

&A

Bor

ders

A&

C

Fife

GG

Hig

hlan

d

Lana

rk.

Gra

mp.

Ork

ney

Loth

ian

Tay

side

FV

W Is

les

D&

G

She

tland

W s

core

Good

Bad

Unadjusted

-30

-20

-10

0

10

20

30

40

50

AR

I

WG

H

ER

I

ST

J

DG

RI

New

ER

I

Wis

haw

RA

H

Mon

klan

ds

Fal

kirk

RI

Cro

ssho

use

PR

I

Ayr

Inve

rcly

de

VH

K

SR

I

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t In

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Wes

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/Gar

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Bor

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Sto

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Lorn

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Roy

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ic

Hai

rmyr

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Inch

keith

Gilb

ert B

ain

W s

core

Good

Bad

Adjusted with 6 Variable model

-30

-20

-10

0

10

20

30

40

50A

RI

WG

H

ER

I

ST

J

DG

RI

New

ER

I

Wis

haw

RA

H

Mon

klan

ds

Fal

kirk

RI

Cro

ssho

use

PR

I

Ayr

Inve

rcly

de

VH

K

SR

I

Vic

t In

Rai

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QM

H

Wes

tern

/Gar

t

Sou

th G

en

Nin

ewel

ls

Bor

ders

GR

I

Sto

bhill

Wes

t Isl

es

Lorn

Val

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Roy

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ic

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Gilb

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ain

W s

core

Stroke Unit Trialist CollaborationMeta-analysis of trials of

stroke unit care

Absolute outcomes

Organised (SU) care

Conventional care

Risk Diff (95%CI)

Dead 22% 26% -3 (-6,-1)

Conclusions

• There are large variations in crude 6 month survival between health boards

• Most of these are due to variation in age and severity of stroke patient admitted

• Having adjusted for casemix and having taken chance into account, differences are small

Planned analyses

• Explore relationship between case fatality and process of care– Admission to stroke unit– Brain scanning– Aspirin– Discharge on secondary prevention

• Look at agreement between diagnostic codes in SSCAS and SMR01 by hospital

Discussion

• Are you happy to include these sorts of data in National Report?

• Is the process of pooling data from each Health Board satisfactory?

• Should we be making more use of these data in research?

• How could efforts of contributors be appropriately acknowledged?

linkage between sscas data and mortality data

Documents