Population-based injury data in Population-based injury data in OntarioOntario

Presentation for ICE meetingPresentation for ICE meeting

Washington, September 7, 2006Washington, September 7, 2006

Alison K. Macpherson, PhDAlison K. Macpherson, PhD

Assistant Professor Assistant Professor

School of Kinesiology and Health ScienceSchool of Kinesiology and Health Science

York UniversityYork University

Sources of data

1. National ambulatory care reporting system (NACRS) database

• Includes all patients reporting to ED in Ontario • Reporting required by government in the

context of a one-party payment system (universal healthcare)

• Coded by nosologists using a standardized process

• Uses international classification system (ICD-10-CA)

• Includes unique identifier (scrambled OHIP number)

1. National ambulatory care reporting system (NACRS) database

• Includes all patients reporting to ED in Ontario • Reporting required by government in the

context of a one-party payment system (universal healthcare)

• Coded by nosologists using a standardized process

• Uses international classification system (ICD-10-CA)

• Includes unique identifier (scrambled OHIP number)

Sources of data (2)

2. Discharge Abstract Database (DAD)• Includes all patients hospitalized in Ontario • Can be linked to NACRS by unique identifier• Uses international classification system (ICD-

10)• Both datasets include:

– mechanism of injury – geographic indicators– Diagnoses (ICD-10)– sociodemographic information

2. Discharge Abstract Database (DAD)• Includes all patients hospitalized in Ontario • Can be linked to NACRS by unique identifier• Uses international classification system (ICD-

10)• Both datasets include:

– mechanism of injury – geographic indicators– Diagnoses (ICD-10)– sociodemographic information

Injuries in Ontario: An ICES Research Atlas

• Objective: To describe the injury problem in Ontario, paying special attention to variation by:

• Age• Gender• SES• Geographic location• Mechanism of injury

Methods

• National ambulatory care reporting system (NACRS) database linked with Discharge Abstract Database (DAD)

• One year (2002-2003)• All patients reporting to ED in Ontario • Grouped by

– county (49 in Ontario)– SES based on average family income in the

residential census tract

• National ambulatory care reporting system (NACRS) database linked with Discharge Abstract Database (DAD)

• One year (2002-2003)• All patients reporting to ED in Ontario • Grouped by

– county (49 in Ontario)– SES based on average family income in the

residential census tract

Variable definition

• Injury variable- Diagnosis (ICD-10 codes)- Visits with an e-code and a trauma diagnosis included

• Grouped according to ICE categories for cause:– Falls – Motor vehicle crashes– Bicycle-related injuries– Pedestrian injuries– Overexertion– Drowning– -etc….

• Injury variable- Diagnosis (ICD-10 codes)- Visits with an e-code and a trauma diagnosis included

• Grouped according to ICE categories for cause:– Falls – Motor vehicle crashes– Bicycle-related injuries– Pedestrian injuries– Overexertion– Drowning– -etc….

12,068,30012,068,300

4,921,0854,921,085

1,211,5501,211,550

Population of Ontario

Number of ED visits

ED visits for injury (25% of ED visits)

ResultsResults

• 1.2 million ED visits for an injury in one year

• 13,678/100,000 injury rate

• 62,377 (2.6%) admitted to hospital

• 2700 (0.02%) died in hospital

• 1.2 million ED visits for an injury in one year

• 13,678/100,000 injury rate

• 62,377 (2.6%) admitted to hospital

• 2700 (0.02%) died in hospital

How do NACRS and DAD compare for all

injury admissions?Agree perfectly(same code for ED and hospitalization)

N (%)

Do not agree perfectly

N (%)

Primary diagnosis

25216 (40%) 37161 (60%)

Cause of injury 32947 (53%) 29430 (47%)

Intent (unintentional/unknown, self inflicted, assault)

51106 (82%) 11271 (18%)

How do NACRS and DAD compare for

injury admissions > 3 days?Agree perfectly(same code for ED and hospitalization)

N (%)

Do not agree perfectly

N (%)

Primary diagnosis

13478 (37%) 23385 (63%)

Cause of injury 18636 (51%) 18227 (49%)

Intent (unintentional/unknown, self inflicted, assault)

29682 (81%) 7181 (19%)

Strengths and Limitations of Ontario injury data

StrengthsStrengths• Population-based study • Linked data• Coded using standardized practices

LimitationsLimitations• Administrative data • Possibility of coding errors• Variation in injury rates may partially reflect

variation in ED visits

StrengthsStrengths• Population-based study • Linked data• Coded using standardized practices

LimitationsLimitations• Administrative data • Possibility of coding errors• Variation in injury rates may partially reflect

variation in ED visits

Conclusions

• Ontario has rich sources of injury dataOntario has rich sources of injury data

• Can be used for local planning and Can be used for local planning and international comparisonsinternational comparisons

• Linkable data can help with validation for Linkable data can help with validation for ICE injury projectsICE injury projects

• Atlas exhibits available at Atlas exhibits available at www.ices.on.ca under publications