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National Violent DeathReporting System (NVDRS): Data

Management Challenges and Solutions

December 12, 2005

Malinda Steenkamp, M.Phil;Nikolay Lipskiy, Dr.PH (presenter);

Division of Violence Prevention National Center for Injury Prevention and Control

Centers for Disease Control and Prevention

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NVDRS Vision:

Reduce and prevent the occurrence of violent deaths in the US through the provision of accurate, timely and comprehensive

surveillance data.

NVDRS Goals:• Collect and analyze timely, high-quality data for monitoring the magnitude and characteristics of violent

deaths at the national, state, and local levels• Ensure that violent death data are routinely and expeditiously disseminated to public health officials, law

enforcement officials, policy makers and the public• Provide data for developing, implementing and evaluating strategies, programs and policies designed to

prevent violent deaths and injuries at the national, state and local levels• Build and strengthen partnerships with organizations and communities at the national, state, and local levels

to ensure that data are collected and used to reduce and prevent violent deaths and injuries• Expand the National Violent Death Reporting System into all 50 states, the District of Columbia and US

territories

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NVDRS States as of July, 2005

FY 02 (6 states)

FY 03 (7 states)

FY 04 (4 states)

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NVDRS Data Sources• Primary sources:

– Death Certificates (DC)– Coroner/Medical Examiner (C/ME) Records– Police Records (PR)– Crime Lab Data (Lab)

• Secondary, optional sources:– Child Fatality Review Team Data (CFR)– Supplementary Homicide Reports (SHR)– Hospital (HOSP) Data– Emergency Department (ED) Data– Alcohol Tobacco, Firearms and Explosives (ATF)

Trace Information on Firearms

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National Violent Death Reporting System

NVDRS collects data on all violent deaths• Suicides (including terrorism-related deaths)

• Homicides (including terrorism-related deaths)

• Legal intervention• Some others:

– Deaths of undetermined intent– Deaths due to unintentional firearm injury

• Excluded: acts of war and legal executionsCase initiation: Abstractors initiate cases through analysis of the source

specific manners of deaths, w/o ICD-10 codes

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Operational Definition: ICD-10 Codes that Define NVDRS Cases

Manner of

Death

Death <1 yr

after Injury

Death >1 yr

after Injury

Intentional self harm X60-X84 Y87.0

Assault X85-X99, Y00-Y09 Y87.1

Undetermined intent Y10-Y34 Y87.2, Y89.9

Unintentional firearm W32-W34 Y86 (guns)

Legal intervention Y35.0-Y35.7

except Y35.5

Y89.0

Terrorism *U01, *U03 *U02

Excluded: acts of war and legal executions

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NVDRS: Case Initiation and ICD-10 Codes

A. Suicide Incidents* B. Homicide Incidents*

ICD-10 categorization

Manner_C (YPMANNEA /CME/DP), % ICD-10 categorization

Manner_C (YPMANNEA /CME/DP), %

(1) Suicide, incl terrorism

(2) Homicide, incl terrorism

(1) Suicide 94.3% (1) Suicide 0.2%

(2) Homicide 0.2% (2) Homicide 94.6%

(3) Unintentional firearm deaths 0.3% (3) Unintentional firearm deaths 0.5%

(5) Injury diagnosis deaths 0.1% (5) Injury diagnosis deaths 0.1%

(6) Legal intervention deaths 0.0% (6) Legal intervention deaths 0.1%

(7) Mental and behavioral disorders 0.1% (7) Mental and behavioral disorders 0.0%

(8) Other external causes of deaths 0.4% (8) Other external causes of deaths 0.6%

(9) Undetermined intent 1.7% (9) Undetermined intent 0.4%

(10) Other non-injury related deaths 1.2% (10) Other non-injury related deaths 1.2%

(99) Unknown 0.0% (99) Unknown 0.1%

Total 100.0% Total 100.0%* 2004 deaths as of May 2005 * 2004 deaths as of May 2005

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How Does NVDRS Work?

Med. Exam/Coroner

Software contractor

Disseminate findings and data in various ways

Law enforcement

(Police reports)

(SHR + NIBRS)

CrimeLab

Case Info(- identifiers)

Vital Records

(Death certificate)

NVDRS (CDC)

State VDRS(17 states)

Other

Also back to providers

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What Data Are Collected?

Incident(# of persons, mechanisms, PR/CME narratives)

Persons:•Victims •Alleged perpetrators

Victim-Perpetrator Relationships

MechanismsPerson-Mechanism

Relationships

Victims:

•Demographics

•Other personal data (residence, marital status, pregnant, occupation)

•Injury event (location, county)

•Death (location, manner, cause)

•Related factors (toxicology)

•Circumstances:

- Suicide/Undetermined deaths

- Homicide

- Unintentional firearms

Alleged perpetrators:

•Demographics

•Mechanism type

- Firearm

- Poisonings

- Hanging, strangulation, suffocation

•History of abuse

•Caretaker

•V-P relationship (for all pairs)

•Person used this weapon to kill

•Weapon killed this person

•First purchaser

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Screen Shot of NVDRS Software

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Incident tables

Document table

SV relationship

PW relationship

Person tables

Weapon tables

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NVDRS’ PUD Structure

Incidents Deaths Suspects

•State reporting incident

•Resident incident

•Incident type

•# of persons in incident

•# of weapons

•# of deaths

•# of suspects

•Person type

•Demographics

•Pregnancy status

•Homeless status

•State reporting incident

•Type of location where injured

•Injured at home/work

•Manner of death

•ICD-10 manner of death

•358/113/39 cause of death recode

•Person attempted suicide after incident

•History of abuse

•Caretaker of victim

•Victim to suspect relationship

•Weapon type

•Firearm type

•Poison type

•State reporting incident

•Person type

•Record type

•Demographics

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Approach To Analyze NVDRS Data

• Created 6 data analysis files based on six entities:– Incident

– Person (Victims, Suspect/Victims, Suspects)

– Weapon

– Victim – Suspect Relationship

– Person – Weapon Relationship

– Document

• All files includes linking variables– Site ID, Incident ID

– Will also include person ID in future

• Files can be combined/merged as needed

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Analyzing NVDRS Data

• Different ways to identify cases– 5 manners of death

(DC, CME, Abstractor, ICD-10, CDC Manner)

• At different points in time – completion rates for manner differ (ICD-10 more incomplete for longer)

• Abstractor assigned manner is a gateway variable

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Analyzing NVDRS Data (cont.)

• Need to know that there are gateway variables– Abstractor assigned manner

– Person type

– Circumstances known

– Weapon type (not discussed today)

• Need to know how to use these:– Person type

• When looking at deaths - Select person types 1 (Victim) and 3 (Suspect/Victim)

(Person type 2 = live suspects)

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CDC Analysis Variables

• Similar variables – multiple sources – combine

• Example for sex data element:– Variable comes from four data sources

• DC, CME, SHR, PR,

– Rule of primacy• Created a CDC analysis variable

(combined variable)

• Identified by _c (e.g. Sex_C)

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Preliminary NVDRS Data:First and Second Data Year

Frequency2003

(June 05)

2004(June 05)

# of States 7 13

Months collecting 27 15

# of Incidents 7,553 13,850

# of Deaths 7,736 13,923

# of Live Suspects 2,034 3,027

*Six states were funded to start data collection in 2003, Alaska was funded to start data collection in 2004, but they chose to go back and also collect data on 2003.

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Data element and categoriesSuicide(n=3,564)

Homicide (N=2,009)

Place of injury House/apartment

Street/road

Natural area

Motor vehicle

72.4%

1.7%

6.0%

4.5%

41.0%

30.8%

2.0%

4.0%

At/during work Yes 1.5% 3.7%

Alcohol use suspected Yes 34.4% 33.3%

CME Circumstances known

Yes 81.1% 49.3%

Preliminary NVDRS Results: Injury Event; 2003; 7 States

NVDRS, as of March 2005

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Preliminary Homicide Results:Victim to Suspect Relationship; 2003; 7

States

67.6

32.4

Relationship unknown

Relationship knownV-S Relationship Percent

Intimate partner 28.1

Parent 4.6

Child 6.8

Other family/caretaker 8.0

Friend/other known person

32.0

Stranger 7.8

Other 12.8

NVDRS, as of March 2005

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Next Steps

• Develop strategic planning process incorporating data management tasks

• Develop and release 2003 and 2004 PUDs• Incorporate NVDRS into Public Health Information

Network (PHIN/NEDSS)• Continue to work on a data aggregation model• Use NVDRS data to guide and enhance violence

prevention efforts

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Summary

NVDRS improves quality and completeness of violent death data through the timely collection and aggregation of multi-source information

Major pitfalls data collection and management: - Involvement of different agencies

- Need a standardization of data element definitions across all agencies

- The development and implementation of QA methods for data collection and management, from a multi-source perspective, is a complex problem

Major data management challenges: - development of a data management model for the population-based

violent death surveillance system - development of a reliable violent death data source for the public

health - to grow towards becoming a comprehensive public health

measurement tool

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For Additional Information, Contact:

Malinda Steenkamp, M.PhilNVDRS Senior Advisor

(770) 488-4476Email: Msteenkamp@cdc.gov

Nikolay Lipskiy, MPH, MBA, DrPHNVDRS Epidemiologist

(770) 488-1306Email: dgz1@cdc.gov