aihw national injury surveillance unit research centre for injury studies flinders university -...

AIHW National Injury Surveillance UnitResearch Centre for Injury Studies

Flinders University - Adelaide - South Australia

Injury indicators: purposes, progress, prognosis

James Harrison

AIHW National Injury Surveillance Unit

Research Centre for Injury Studies, Flinders University

Overview

• Injury indicators– Purposes: Why have indicators?– Principles: Concepts, definitions & standards– Progress: Where are we up to?– Problems: Constraints– Prognosis: Next steps…



Purposes: Why have indicators?

Information to support injury prevention & control

• Support planning and policy-making

• Guide targeting and priority-setting

by• Measuring and monitoring injury, its consequences,

injury risk-factors and exposure to them

• (Contributing to) evaluation of interventions



Operator

Steam-

engine

Pressure-

time

indicator

Control

valves

Purposes: Origin of indicators



Injury

prevention

practitioners

Injury

prevention

program

Injury

indicator

Start or alter

prevention

program

Purposes: Origin of indicators



What to indicate?

Steam-engine– Risk of explosion

– Efficiency

– Effect of altered settings

Injury prevention– Burden of injury

– Risk exposure

– Effect of intervention

Things worth knowing

…especially if not directly observable



How to indicate it?

Steam-engine– Pressure-time relationship

Injury prevention– Injury incidence

– Prevalence of risk exposure

– Reach of an intervention

A. Identify and specify another thing, which: 1. Can be measured

2. Varies with the ‘thing worth knowing’

B. Make a device / information system able to provide measured values of A.

Steam-engine indicator Injury indicator



What is a good indicator?

• Steam-engine indicator– Varies predictably with time-

pressure– Not much influenced by

other things– Sensitive enough to show

important changes – Timely enough to allow good

control of engine

• Injury prevention indicator– Varies predictably with injury

occurrence– Not much influenced by other

things– Sensitive enough to show

important changes– Timely enough to allow effective

response to findings– Well-defined– Comparable (esp. over time)

One with attributes suitable for its purpose



What is a good indicator?

IInformation objective Assessment as topic for indicator

Trends in total burden of injury

• Broad scope is appealing

• Lack information for reliable measurement, especially over time

Trends in incidence of fatal and severe injury

• Narrower scope: may not be a reliable guide to (eg) trends in burden of total

• Measurement is feasible



Principles: concepts, definitions, standardsIndicators require data

• Necessary but not sufficient• Must be COMPARABLE

Foundations for comparability• Clear meaning for key concepts: eg. ‘injury’, ‘severity’, ‘outcome’ • Classifications

– eg. ICD-10, ICD-10-AM, ICECI• Operational definitions

– eg. STIPDA Consensus Recommendations for using hospital discharge data for Injury Surveillance

• Reporting standards – eg. Recommended Framework for reporting injury mortality data

• Derived measures – eg. ICISS severity, remoteness, Socio-Economic Status

• Institutional arrangements – eg. WHO-FIC, Injury ICE, STIPDA



Injury outcome indicators

• Consensus criteria (ICE on Injury Statistics)

– Define in terms of anatomical/physiological damage

– Serious injury

– Case ascertainment independent of extraneous factors

– Representative of target population

– Available data

– Well-documented (definitions, methods, etc)(Cryer, Langley, et al

2005)



Progress: Where are we up to?

Australia as an example

Focus on trends in severe & fatal injury• c. 10 years at national level

• Deaths and hospitalised injury

• Onion metaphor: layers of work (iterative)– Getting, understanding, ‘cleaning’ & documenting data

– Scope: defining and operationalising definition of ‘injury’

– Methods to avoid multiple counting

– Methods to assess & control changing sample fraction



Full specification can be complex

Fatal cases Deaths occurring in Australia during the year from 1 July 2002 and registered within six months of the end of that year where any Multiple Cause of Death code is in the range S00-T75 or T79 and Underlying Cause of Death is in the range V01-V98. If Underlying Cause is not an External Cause, then include if (any) (first-mentioned external cause) Multiple Cause of Death code is in the range V01-V98 and the person was a resident of Australia.

Non-fatal high-threat to life cases

Episodes of admitted patient (acute) care in any acute-care hospital that (commenced) (ended) during the year from 1 July 2002 where (principal) (any) diagnosis code is in the range S00-T75 or T79 and (any) (the corresponding) external cause code is in the range V01-V75 or V79 and the person was not admitted following transfer from an acute care hospital and the (all injuries multiplicative) (worst injury) ICISS severity score is < 0.941 and the person is recorded as residing in Australia and the episode ended with the patient alive.

Population Estimated resident population at 31 December 2000.

Rates Numerator values are sums of fatal cases and the non-fatal instances of types of injury that pose high threat to life. Rates are adjusted for age by the direct method using the Australian population in 2001 as the reference (and stratified or adjusted for remoteness of place of residence and Indigenous status).

Incident fatal and severe injury due to Transport



…but different methods can give very different values

‘Underlying cause of death’ coded to Accidental Falls (W00-W79) 629

‘Underlying cause of death’ coded to Unspecified cause (X59)

with a fracture as an ‘additional cause’ Mostly falls by people aged 75 and older at death

Cause unspecified mainly because ABS does not seek one at this age

888

‘Underlying cause of death’ coded to Natural cause (i.e. not injury)

with additional cause codes for injury condition(s)

and for fall as external cause of injury ‘Underlying cause’ is coded to circulatory disease in 49%

Small differences in wording on death certificates affect whether coded as injury deaths.

1,518

How many deaths following injury due to a fall are recognised as such?

Of deaths registered in Australia in 2002:



Injury all ages (NHPA indicator 1.2) Australia 1993-94 to 2002-03

0

200

400

600

800

1,000

1,200

1,400

1993

-94

1994

-95

1995

-96

1996

-97

1997

-98

1998

-99

1999

-00

2000

-01

2001

-02

2002

-03

Year of separation

case

s/10

0,00

0 po

p

all separations

Excl transfers from acute hospitals

Excl transfers to acute hospitals

…even if differences are subtle

Age-adjusted rates



Falls ages 75+ (NHPA indicator 1.2) Australia 1993-94 to 2002-03

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

1993

-94

1994

-95

1995

-96

1996

-97

1997

-98

1998

-99

1999

-00

2000

-01

2001

-02

2002

-03

Year of separation

case

s/10

0,00

0 po

p

all separations

Excl transfers from acute hospitals

Excl transfers to acute hospitals

Has the age-adjusted rate risen?

Age-adjusted rates



Aspects of burden of hospitalised injury

0

10,000

20,000

30,000

40,000

50,000

60,000

70,00019

95-9

6

1996

-97

1997

-98

1998

-99

1999

-00

2000

-01

2001

-02

2002

-03

Cas

es

0

500

1,000

1,500

2,000

2,500

Cas

es/1

00,0

00 p

opul

atio

n

Cases

Crude rate

Adj. Rate

Hospitalisation due to Accidental Falls ages 65 and older, Australia 1995-6 to 2002-3



Aspects of burden of hospitalised injuryHospitalisation due to Accidental Falls ages 65 and older, Australia 1995-6 to 2002-3

0

200,000

400,000

600,000

800,000

1,000,000

1,200,00019

95-9

6

1996

-97

1997

-98

1998

-99

1999

-00

2000

-01

2001

-02

2002

-03

Bed

-day

s

No injury Dx; Fall ext. cause

Other (AdDx injury)

Rehabilitation (AdDx injury)

Injury (PrDx)



Problems: Constraints

• Data quality (incl timeliness)– Variation in % of cases incident in population admitted to hospital?

(Especially for low severity injuries?)• Difficulty and costliness of validation studies

– special studies; WA linked data• Data (mostly) not person-linked

– >episode (ie record) / incident case of admitted injury: tricky to allow for this source of multiple counting of cases

– hospital data and deaths data: do in-hospital ‘injury deaths’ appear as ‘injury deaths’ in national deaths data collection?

• Access (administrative issues, privacy)• Complexity (esp for ‘clever data cleaning’)• Classification

– Australian clinical modification of ICD-10 (ICD-10-AM)– revisions (each 2y) allow useful enhancement of Injury & External Cause codes– … but (so far) the revised codes are not used for routine mortality data



Signal & noise: example 1Nature Injury (principal diagnosis) All 1993-94 to 2002-03

75 years and older

0.0

1000.0

2000.0

3000.0

4000.0

5000.0

6000.0

1993

-94

1994

-95

1995

-96

1996

-97

1997

-98

1998

-99

1999

-00

2000

-01

2001

-02

2002

-03

rate

(/1

00,0

00 p

op

)

1.0

10.0

rati

o (

seri

es 1

:2)

Australia separations

Australia cases (est.)

sub-area A cases (est.)

ratio [1:2]

Age-adjusted rates



Signal & noise: example 2M echanism Injury (principal diagnosis) M otorcyclist 1993-94 to 2002-03 Australia 0-4 years and older (cases (est.))

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

1993

-94

1994

-95

1995

-96

1996

-97

1997

-98

1998

-99

1999

-00

2000

-01

2001

-02

2002

-03

rate

(/1

00,0

00 p

op

)

NSW, Vic, ACT & NT

Qld, SA, WA & Tas

Age-adjusted rates



Prognosis: Next steps…

• What?– Broader scope: of burden (eg rehab, late care)– Broader scope: of severity (eg ED)– Broader scope: exposures as well as outcomes– Prediction of non-fatal outcomes– Better denominators– Shorter lag (+/- model-based prediction)

• How?– Standards (more, better, more widely used)– Linkage– Incremental system improvements



Summary– Purposes: Why have indicators?

• To estimate trends (and differences) in important phenomena, which are not directly observable

– Principles: concepts, definitions & standards• The technical foundation; essential for comparability

– Progress: • Coming together… quite good trends data for serious injury

– Problems:• Constraints are real, tricky but generally manageable

– Prognosis:• Exciting times (nb linkage)• Grail: ICISS-like measure(s) for important non-fatal

outcomes



After dinner…?



Understanding the issue

• Demographics of injured people

• Types of injury

• Severity and outcomes

• Risk factors and exposure

• Effectiveness and use of interventions



Targeting and priority-setting

• (potential) topics for indicators– Frequency– Risk– Burden– Potential for improvement



Approaches• Opportunistic

• Using existing data and other resources

• Making the most of them for injury surveillance– Understanding, creative use, incremental enhancements

• Purposive / strategic• Data sources and other components of injury

surveillance developed specially to serve this purpose



Approaches

Opportunistic Purposive

Case data sources ABS mortality

NHMD

VEMD NCIS

QISU-ED

Trauma registers ASCIR

Classifications ICD (‘vanilla’) ICD-10-AM

ICECI

Concepts, definitions ICD, NHDD ICE on Injury Statistics



StatusFatal and serious injury

• Hospital separations and deaths• Cross-sectional and trends • Better understanding of data -> better use• Good useable system

– Will benefit from further validation, etc

• Basis for – Reporting of indicators– Numerous analyses of specific topics – Use with cost-models for good injury costings– Use in GBD models– …



StatusOccurrence

– Incident fatal & severe injury– Characterised in terms of ICD-10-AM, LoS, threat to life,

demographic characteristics etc.– Period: deaths - many years, hospitalised – c. 10 years– 1-2 year lag (2-3 y latency for system changes)

Risks and burden– Population-based rates

• Age/sex/remoteness/SEIFA/CoB/etc (+/- indigenous status)

– Other denominators• Potentially diverse; patchy availability

– Other units• Cost, DALYs



StatusChange in occurrence (trends)

• Challenges:– Hospital data

• (largely) not person-linked: multiple counting

• differences in admission/recording: variable sample

• variations in data quality

– Deaths

• ‘Injury death’ vs UCoD External Cause

• changes in coding some types of death

• Manageablewith care …



Future?

• Technical developments

• Maintenance

• Operational links



Future? Technical developments1. Standards

For comparable & meaningful data…

2. OutcomesMeasure & describe outcomes of injury (in addition to death)

3. LinkageIllness service utilisation data, case data/event data, case

data/population data

4. Denominators / exposure dataBetter population data (nb Indigenous); other denominators

5. Knowledge, attitudes, behaviour…of Australians concerning injury, injury prevention, interventions



1. StandardsNeeded for comparable & meaningful data

– Including:• Operational definition(s) of ‘injury’

– For deaths, hospital data, other sources

– Australia: Technical Review & Revision of injury indicators

– International: ICE on Injury Statistics; ICECI

• Classifications– ICD-10, ICD-10-AM, ICECI

• Data standards / minimum data sets– NDS-IS, NCIS data set

• Survey questions

– Opportunities:• Consideration/contribution to/adoption of international standards

• Further development & updating of Australian standards



2. Outcomes

Measure & describe outcomes of injury– Overview:

• Fairly good methods to measure threat to life of injury– AIS & derivatives, GCS etc, ICISS

• Much of burden of injury is due to consequences other than death

• Methods to measure ‘threat to health’ of injury are immature

• Progress is likely to require large and expensive prospective studies

– Opportunities:• Collaborative project(s), national or international



3. Linkage

Potential for more information from existing data– May include:

• Person-based linkage of illness service utilisation data, etc

• Linking case data to event data (eg hospital / crash)

• Linking case data to population data (eg enhanced census)

• Linking special injury register data to any of these

– Opportunities:• Collaborative projects using WA Linked Health Data

• Advocacy for similar capabilities elsewhere

• National developments



4. Denominators/exposure dataPotential for more information from existing case data

– Types of denominators:• Better population data

– nb reliable estimates of Indigenous population

• Injury risk factor / exposure data– Eg. more specific sports-participation data, alcohol use data,

travel/vehicle use data

• Injury protective factor / intervention – Eg participation by older persons in specified exercise activities

– Opportunities: • Diverse



5. Knowledge, attitudes, behaviourKnowledge, attitudes, behaviour

• …of Australians concerning injury, injury prevention, interventions

– Themes:• Knowledge

– What is the extent, distribution and reliability of knowledge about injury occurrence, consequences and potential for prevention.

• Attitudes– What is the direction (positive or negative) and strength of attitudes

towards injury prevention generally and to specific interventions.

• Behaviour – What are the population patterns of certain behaviours that increase or

decrease injury risk

– Opportunities: • CATI surveys



Future? Maintenance– Maintain current data sources & quality

• eg loss of items from ABS mortality data

• eg signs of possible deterioration of injury coding in some hospital records

– Ensure good understanding of data • Validation studies (eg ARC project)

– Continue to tap value from existing sources• Novel analytic methods (eg ICISS)

• More efficient analysis & access (cf US WISQARS)

• Minor changes (eg ICD-10-AM biennial revisions)



Future? Operational links – Better understanding of uses and users

• Governments, researchers, industry, community– Consult, discuss, seek feedback

• Look for lessons in related activities– Other public health surveillance ane information activities– Injury surveillance elsewhere

– Close liaison with policy-makers• Individually and though national forums• Health and other sectors

– Seek two-way connection with policy• … in which surveillance information

– helps shape policy– supports its implementation and monitoring



ReviewInjury surveillance systems & information

PurposesInformation to support injury prevention & control

ApproachesOpportunistic and purposive

StatusGood system for severe and fatal injury

Future– Standards; Outcomes; Linkage; Denominators/exposure data;

Knowledge, attitudes, behaviour– Maintenance– Operational links and relationships



Why better now?• Ten year series of data

• Quality fairly good and has generally improved

• Completeness

• Similarity between jurisdictions

• Better understanding• Of data strengths and limitations

• Development of concepts and methods• Eg severity measures, injury definitions



Trends in injury incidence: issues• Records are for inpatient episodes, not

persons injured

• Proportion of incident injury cases resulting in admission might change over time.

• Identifiability of separation records as relating to an “injury” might change over time



Burden of hospitalised injury

0

10,000

20,000

30,000

40,000

50,000

60,000

70,00019

95-9

6

1996

-97

1997

-98

1998

-99

1999

-00

2000

-01

2001

-02

2002

-03

Cas

es

0

500

1,000

1,500

2,000

2,500

Cas

es/1

00,0

00 p

opul

atio

n

Cases

Crude rate

Adj. Rate

Hospitalisation due to Accidental Falls ages 65 and older, Australia 1995-6 to 2002-3



SCI: trends and prioritiesPersisting Spinal Cord Injury due to motor vehicle accidents,

ages 15y and older, Australia 1995-6 to 2003-4

0

2

4

6

8

10

1995-9

6

1996-9

7

1997-9

8

1998-9

9

1999-0

0

2000-0

1

2001-0

2

2002-0

3

2003-0

4

Year of injury

Cases/1

00,0

00 p

opula

tion

Motorcyclists

Other MVTA

M/cyclists, 15-34y



Improvements• Understanding the data

• Estimating incident cases• Comparability over time & between places• Coding validation (ARC project)• Completeness (external cause codes, activity, etc)

• New uses of the data• ICD-based severity measures

• Classification• ICD-10-AM 3rd • ICD-10-AM 5th



Classification• ICECI

• Development was prompted by dissatisfaction with ICD External Causes classification:– Lagged behind theory (eg energy transfer concept)– Technical defects (eg not multi-axial)

• Developed by international collaborative group• Challenges:

– Enable refinement– Keep current– Translation (concepts as well as language)– Minimise burden of maintenance

aihw national injury surveillance unit research centre for injury studies flinders university -...

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