Avoidable Injuries

How can we monitor them effectively?

Carol WilliamsPublic Health AnalystNorthamptonshire Teaching PCT

Why is it a priority?

Part of Local Area Agreements

Not part of LDP or PSA targets

Routine Data Sources

Mortality Data Hospital Admissions A&E Attendances Ambulance Calls Other e.g. Police, Fire etc

Which codes to use? ICD-10 primary diagnosis in the range

S00 through T98X and external cause code in the following ranges: V01-V99, W00-X59, Y40-Y84

Includes complications of medical & surgical care

Mortality Data Issues Falls under recording:

Fractures with cause unspecified (E887 ICD9)

Now coded in ICD 10 as X59 (accidental exposure to unspecified factor)

East Midlands had a relatively high number

Include fractures with unspecified external cause

Include deaths with diag. of osteoporosis (Health Statistics Quarterly Winter 2006)

Levers for change?

National guidance for monitoring deaths from falls

NCHOD need to reflect this issue for deaths from accidental falls

Hospital Admission Data Lack of timely comparative data –

NCHOD 2004/2005 Serious Accidental Injury (LOS > 3

days) No further breakdown by accident

type Lack of specific external cause code

for some hospitals

Avoidable Injury Admissions

Directly aged standardised hospital admission rates for avoidable injury - all agesby local authority of residence in the East Midlands (2001/02 to 2005/06)

0.0

200.0

400.0

600.0

800.0

1000.0

1200.0

Oadby

& W

igsto

n

Charn

wood

Rushc

liffeBlab

y

Hinck

ley &

Bos

worth

Harbo

roug

h

Broxto

we

Melt

on

Kette

ring

South

Nor

tham

pton

shire

Well

ingbo

roug

h

East N

orth

ampt

onsh

ire

Gedlin

g

Daven

try

North

Wes

t Leic

este

rshir

e

Rutlan

d

South

Der

bysh

ire

Leice

ster

South

Holl

and

North

Eas

t Der

bysh

ire

EAST MID

LANDS

South

Kes

teve

n

ENGLAND

High

Peak

East L

indse

y

Newar

k & S

herw

ood

Ambe

r Vall

ey

Cheste

rfield

Erewas

h

North

Kes

teve

n

North

ampt

on

Derby

shire

Dale

s

Bosto

n

Corby

Nottin

gham

Ashfie

ld

Wes

t Lind

sey

Derby

Bolsov

er

Basse

tlaw

Man

sfield

Linco

ln

local authority

Dir

ectl

y ag

ed s

tan

dar

dis

ed r

ate

per

100

,000

Lack of specific codes

Percentage of admissions for accidental injury (ICD10 codes V01 to X59) where cause code is unspecified (X59) - 2005/06

V01 to X59 X59

RCS NOTTINGHAM CITY HOSPITAL NHS TRUST 1726 90 5%RFK QUEEN'S MEDICAL CENTRE, NOTTINGHAM UNIVERSITY HOSPITALS NHS TRUST 5947 208 3%RFS CHESTERFIELD ROYAL HOSPITAL NHS FOUNDATION TRUST 3127 114 4%RK5 SHERWOOD FOREST HOSPITALS NHS TRUST 3449 72 2%RNQ KETTERING GENERAL HOSPITAL NHS TRUST 2825 1431 51%RNS NORTHAMPTON GENERAL HOSPITAL NHS TRUST 3555 735 21%RTG DERBY HOSPITALS NHS FOUNDATION TRUST 5878 252 4%RWD UNITED LINCOLNSHIRE HOSPITALS NHS TRUST 6834 202 3%RWE UNIVERSITY HOSPITALS OF LEICESTER NHS TRUST 10176 1831 18%ALL TOTAL OF THE ABOVE 43517 4935 11%

Source: Department of Health, Hospital Episode Statistics (HES).

Trust code NHS TrustExternal cause codes

%

Effect on cause-specific rates

Directly aged standardised hospital admission rates for road traffic accidents - all agesby local authority of residence in the East Midlands (2001/02 to 2005/06)

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

Corby

Kette

ring

Oadby

& W

igsto

n

Well

ingbo

roug

h

East N

orth

ampt

onsh

ireBlab

y

Harbo

roug

h

Leice

ster

Charn

wood

Rushc

liffe

Hinck

ley &

Bos

worth

Daven

try

North

ampt

on

Broxto

we

ENGLAND

Melt

on

South

Der

bysh

ire

South

Nor

tham

pton

shire

Gedlin

g

North

Eas

t Der

bysh

ire

High

Peak

EAST MID

LANDS

Derby

Rutlan

d

Cheste

rfield

North

Wes

t Leic

este

rshir

e

Erewas

h

Nottin

gham

Ambe

r Vall

ey

South

Kes

teve

n

Derby

shire

Dale

s

Ashfie

ld

Newar

k & S

herw

ood

Man

sfield

Bolsov

er

North

Kes

teve

n

Wes

t Lind

sey

Linco

ln

East L

indse

y

Basse

tlaw

South

Holl

and

Bosto

n

local authority

Dir

ectl

y ag

ed s

tan

dar

dis

ed r

ate

per

100

,000

Effect on cause-specific rates

Directly aged standardised hospital admission rates for accidental falls - patients aged 15 to 64 by local authority of residence in the East Midlands (2001/02 to 2005/06)

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

local authority

Dir

ectl

y a

ged

sta

nd

ard

ised

rate

per

100,0

00

Levers for change? Payment by Results – probably not

Coding Standards – is there any process such as Data Accreditation?

Information Agreement – not enough on its own

Other National Initiatives?

A&E attendances Not part of SUS – no global data to

set quality standards A&E mds has limited use

Payment by Results only gives Low, Medium, High bandings

No Accident Type field (except Patient Group)

No detailed Incident Location CAER codes only relate to type of

injury and treatment

Levers for change

Informing Healthier Choices SUS user group

A&E data part of SUS

Development of national A&E mds

Accident monitoring initiatives NWPHO – Trauma and Injury Intelligence

Group (TIIG) – additional data such as Injury Group, Accident Location

West Midlands Accident Surveillance Centre (Bgm Uni) – based on A&E mds

Cardiff University – All Wales Injury Surveillance System

Dr Foster – Smart Risk

Other initiatives

Use of other data sets e.g. Ambulance (can give location of accidents)

Examples of special data collections?

Other?