1

 Roadway Safety Data Program

MARYLAND’S DATA LINKAGE AND ANALYSIS TO

SUPPORT DECISION MAKING

ROADWAY SAFETY DATA AND ANALYSIS

CASE STUDY

FHWA-SA-16-049

Federal Highway Administration Office of Safety

Roadway Safety Data Program

http://safety.fhwa.dot.gov/rsdp/

 

September 22, 2016
Notice

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MARYLAND’S DATA LINKAGE AND ANALYSIS TO SUPPORT DECISION MAKING

iii

TECHNICAL DOCUMENTATION PAGE

1. Report No. 2. Government Accession 3. Recipient's Catalog No.

FHWA-SA-16-049 No.

4. Title and Subtitle 5. Report Date

Maryland’s Data Linkage and Analysis to Support Decision Making: Roadway September 2016

Safety Data and Analysis Case Study 6. Performing Organization Code

7.Author(s) 8. Performing Organization Report No.

Robert A. Scopatz and Elissa Goughnour

9. Performing Organization Name and Address

VHB

8300 Boone Blvd., Suite 700

10. Work Unit No.

11. Contract or Grant No.

DTFH61-10-D-00022

Vienna, VA 22182-2626 

12. Sponsoring Agency Name and Address 13. Type of Report and Period

Case study 2016

Federal Highway Administration Office of Safety 

1200 New Jersey Ave., SE

Washington, DC 20590 14. Sponsoring Agency Code

FHWA

15. Supplementary Notes

The contract manager for this report was Esther Strawder, Office of Safety

16. Abstract

Highway traffic safety analysis is a multi-dimensional process involving roadway characteristics, volumes, and crash data. 

State agencies may encounter difficulties sharing data between agencies and integrating the multiple data sources into a 

single safety analysis. The University of Maryland’s National Study Center for Trauma and Emergency Medical Services 

(NSC) receives data from several State agencies and provides integrated data analysis using the Crash Outcome Data 

Evaluation System (CODES) methodology. CODES helps States develop data linkage programs as crash data alone do not 

capture the full consequences of motor vehicle crashes. The intent of the CODES program was to provide a more 

comprehensive understanding of motor vehicle crashes by linking crash, vehicle, and behavior characteristics to their 

specific medical and financial outcomes.

17. Key Words: 18. Distribution Statement

safety data, data linkage, safety analysis, crash No restrictions.

data, hospital data, EMS data, data sharing

19. Security Classif. (of this report) 20. Security Classif. (of this 21. No. of Pages 22. Price

Unclassified page) Unclassified 13

Form DOT F 1700.7 (8-72) Reproduction of Completed Pages authorized
MARYLAND’S DATA LINKAGE AND ANALYSIS TO SUPPORT DECISION MAKING 

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TABLE OF CONTENTS 

INTRODUCTION ............................................................................................................. 2

AUDIENCE ..................................................................................................................... 2

BACKGROUND............................................................................................................. 2

SPECIFIC GUIDELINES AND PRACTICES .................................................................. 3

BENEFITS........................................................................................................................... 4

SUMMARY..........................................................................................................................5

FUNDING: ...................................................................................................................... 5

MARYLAND PROGRAMS AND PROCESSES USING DATA LINKAGE AND 

ANALYSIS: ..................................................................................................................... 6

LESSONS LEARNED: ................................................................................................... 7

REFERENCES .................................................................................................................... 8

EXPLANATION OF TERMS ........................................................................................ 9

AGENCY CONTACT INFORMATION ......................................................................... 9
MARYLAND’S DATA LINKAGE AND ANALYSIS TO SUPPORT DECISION MAKING

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EXECUTIVE SUMMARY

Highway traffic safety analysis is a multi-dimensional process involving roadway characteristics, 

volumes, and crash data. State agencies may encounter difficulties sharing data between 

agencies and integrating the multiple data sources into a single safety analysis. The University of 

Maryland’s National Study Center for Trauma and Emergency Medical Services (NSC) receives 

data from several State agencies and provides integrated data analysis using the Crash Outcome 

Data Evaluation System (CODES) methodology. CODES helps States develop data linkage 

programs as crash data alone do not capture the full consequences of motor vehicle crashes. 

The intent of the CODES program was to provide a more comprehensive understanding of 

motor vehicle crashes by linking crash, vehicle, and behavior characteristics to their specific 

medical and financial outcomes. The purpose of this case study is to describe some of the 

unique qualities and successes of the Maryland CODES program and to explore how the NSC 

uses advanced CODES integration and safety analysis to support a variety of agencies and 

programs.
MARYLAND’S DATA LINKAGE AND ANALYSIS TO SUPPORT DECISION MAKING

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INTRODUCTION

Highway traffic safety analysis is a multi-dimensional process involving roadway characteristics, 

volumes, and crash data. State agencies may encounter difficulties sharing data between 

agencies and integrating the multiple data sources into a single safety analysis. The University of 

Maryland’s National Study Center for Trauma and Emergency Medical Services (NSC) receives 

data from several State agencies and provides integrated data analysis using the Crash Outcome 

Data Evaluation System (CODES) methodology.

CODES is a State-based program created in 1992 by the National Highway Traffic Safety 

Administration (NHTSA), National Center for Statistics and Analysis (NCSA). NHTSA 

implemented the program to help States develop data linkage programs as crash data alone do 

not capture the full consequences of motor vehicle crashes.(1) The intent of the CODES 

program was to provide a more comprehensive understanding of motor vehicle crashes by 

linking crash, vehicle, and behavior characteristics to their specific medical and financial 

outcomes.(2) NHTSA supported the program until 2013 anticipating that States would continue 

the effort using their own funding sources. In Maryland, the NSC has continued to use CODES

to inform State legislation, agency policy, and behavioral countermeasure programs.

The purpose of this case study is to describe some of the unique qualities and successes of the 

Maryland CODES program and to explore how the NSC uses advanced CODES integration 

and safety analysis to support a variety of agencies and programs.

AUDIENCE 

This case study applies to the following audiences:

 State Agencies: Governor’s Highway Safety Program, State Department of 

Transportation, State Law Enforcement and State Department of Public Safety, State 

Legislature, TRCCs, and Office of Highway Safety.

 Local and Regional: City and County Transportation Departments, Metropolitan 

Planning Organizations, Regional Planning Commissions, Law enforcement agencies.

 Federal: Local and Tribal Technical Assistance Program personnel.

BACKGROUND 

The NSC’s mission is to prevent death and disability caused by injury and sudden illness.

Established by Congress in 1986, it is part of the Shock, Trauma and Anesthesiology Research 

Center (STAR) in the University of Maryland School of Medicine.

The NSC staff, including epidemiologists, physicians, statisticians, and database coordinators, 

conducts research related to the causes, treatment, and outcomes of traumatic injury and 

sudden illness. NSC studies have been used to improve vehicular safety, to refine patient care 

and to develop public education programs for the prevention of trauma. NSC staff also 

collaborates with government agencies, professional associations, universities, and private 
MARYLAND’S DATA LINKAGE AND ANALYSIS TO SUPPORT DECISION MAKING

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enterprises to increase understanding of trauma epidemiology and emergency medical system 

response.(3)

NSC staff were conducting CODES type analysis prior to joining the NHTSA program and 

officially joined the NHTSA program in 1994 in an effort to institutionalize their data analysis 

efforts.

The scope of this case study includes all public roads in Maryland and numerous agencies with 

whom the NSC collaborates. 

Sample of Current Collaborators: (4)

AAA Mid-Atlantic Foundation for Safety & Education Maryland Department of Health and Mental Hygiene - Maryland 

Baltimore Metropolitan Council Health Services Cost Review Commission 

Centers for Disease Control and Prevention Maryland Department of Public Safety and Correctional Services 

District Court of Maryland Maryland Motor Vehicle Administration 

Federal Motor Carrier Safety Administration Maryland Highway Safety Office 

Injured Workers Insurance Fund Maryland State Highway Administration 

Insurance Institute for highway Safety Maryland State Police 

Johns Hopkins Bloomberg School of Public Health Maryland Institute for Emergency Medical Services Systems 

Maryland Department of Health and Mental Hygiene - National Highway Traffic Safety Administration 

Alcohol and Drug Abuse Administration National Safety Council – Chesapeake Regional Division 

Maryland Department of Health and Mental Hygiene - National Transportation Safety Board 

Core Violence and Injury Prevention Program Office of the Chief Medical Examiner 

U.S. Department of Transportation

SPECIFIC GUIDELINES AND PRACTICES

NSC uses data from a variety of sources including three core data sets (crash, emergency 

medical services (EMS), and hospital) along with ancillary data sets such as driver licensing, 

vehicle registration, citation, motorcycle training, trauma registry, and others. The NSC also 

uses a General Use Model (GUM) of regularly collected data.(5) The GUM data elements are:

 Collected by a majority of States.

 Have been mapped to standardize variables.

 Conforms with other NHTSA data systems.

 Contains rich medical information.

 Submitted on an annual basis.

 Available for analysis by NHTSA.

The NSC uses these datasets individually and collectively to conduct analyses on a variety of 

highway safety topics. Examples of the NSC’s analyses include:

 Fulfilling specific data query requests.
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 Developing general and program-specific fact sheets.

 Producing Maryland Highway Safety Office (MHSO) annual and benchmark reports.

 Conducting problem identification.

 Improving blood alcohol content test reporting for NHTSA’s Fatality Analysis Reporting 

System (FARS).

 Providing information and help with goal setting for the Maryland Department of 

Transportation (MDOT) Strategic Highway Safety Plan (SHSP) and the State Highway 

Administration (SHA) Highway Safety Improvement Program (HSIP) and provide data to 

assist with problem area prioritization for the MHSO Highway Safety Plan (HSP).

In order to fulfill the data analysis requests, NSC uses a variety of tools, including the CODES 

probabilistic matching software, fuzzy logic case matching rules, the SAS package for data 

management and analysis, and a Geographic Information System (GIS) for location-based linkage 

and analysis.(6) One example of how they use GIS for location-based analysis is with the City of 

Baltimore. The city maps their own crashes and provides those GIS files to NSC for analysis. In 

cases where the crashes have not been mapped, NSC uses the road name variables on the 

crash report to identify the crash location and if appropriate, tie it to an intersection. NSC uses 

the CODES software to combine information from different databases into a single dataset for 

analysis.(7) Desired information about study subjects is often contained in several databases, and 

if a shared unique identifier does not exist between these databases, it is not possible to 

combine the information directly. CODES uses probabilistic linkage to match records based on 

several linking variables that are common among all the source databases to quantify the 

likelihood that two or more records match. Fuzzy logic allows for matches when the values of 

the linking variables are similar but do not match exactly (e.g., crash time and EMS run time 

should be similar, but would rarely match precisely). The SAS package is a standard data 

management and statistical analysis tool with robust procedures for data linking and data 

manipulation among multiple source files. GIS is the standard for location-based data storage 

and reporting in Maryland. 

BENEFITS 

The NSC highlights the following benefits of integrated safety data and analyses:

 Data Governance. Agencies can feel confident in the protections afforded to them 

through the University’s Institutional Review Board (IRB). (9) Maryland CODES also has a 

Board of Directors that involves all agencies that provide data and meets once a year.

Due to the positive relationships that have been strengthened by the CODES Board of 

Directors and the establishment of data use agreements, the University has been able to 

continue their work with these various agencies, despite the withdrawal of support from 

NHTSA for the CODES program. 
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As users (rather than owners) of the data, NSC does not have specific data QA/QC 

procedures in place. Rather, logistical checks are performed to identify missing 

information for key fields and to ensure data consistency and completeness. Based on 

these checks NSC may make suggestions to the agency/data owner. In one example, 

NSC noticed a gap in FARS data where the blood alcohol content (BAC) was not 

recorded in fatal crashes where the driver survived. NSC was able to provide the 

connection between the FARS data and trauma registries throughout the State so that 

the BAC could be updated.

In 2015, Maryland’s Automated Crash Reporting System (ACRS) was initiated. NSC 

staff, along with representatives from the Maryland State Police, SHA, and MHSO, 

participate in the Maryland Traffic Records Coordinating Committee (TRCC) ACRS 

Task Force. Members of the TRCC ACRS Task force include technical and policy 

experts named by the Crash Data Tri-Agency Council, a subcommittee of the TRCC 

that includes the Maryland State Police, SHA, and MVA. The TRCC chair is selected 

from the participating agencies. The MHSO and the NSC share the responsibility for 

setting the agenda and running the meetings. These meetings tend to provide regular 

updates from each component of the traffic records system. The task force meets 

monthly and oversees continued improvements to ACRS through oversight, QA/QC, 

and training.(10) 

 Ability to work with agencies to answer questions and guide policy. NSC has worked with 

agencies to answer questions regarding the effectiveness of programs and to provide 

information to guide policy decisions. NSC is analyzing the effectiveness of ignition 

interlocks using District Court citation data, MVA data (driver’s license data, conviction 

data, interlock data, etc.), and crash data from Maryland State Police.

 Early institutionalization and diverse clients. One of the reasons why the NSC CODES 

program has maintained success was their ability to institutionalize prior to the 

completion of NHTSA support by finding supplemental funding opportunities and 

broadening the original intent of the CODES program. Instead of focusing on crash to 

hospital data, NSC understood that the agencies in Maryland had needs related to 

understanding the implications and effectiveness of programs, laws, and 

education/enforcement campaigns. Broadening the scope of data integration and analysis

contributed to program stability by attracting additional agencies to the CODES 

program, thereby providing supplemental funding to that already provided by NHTSA. 

RESULTS

Funding, processes, and lessons learned regarding the NSC implementation of CODES and data 

linkage and analysis are outlined below.

FUNDING 

 The NSC CODES program was initially partially funded by NHTSA. However, the 

University received supplemental funding from the organizations that they served, such 

as the Maryland Motor Vehicle Administration (MVA), MHSO, SHA, and Maryland State 
MARYLAND’S DATA LINKAGE AND ANALYSIS TO SUPPORT DECISION MAKING

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Police, among others. NSC is now fully funded through grants and specific requests from 

those agencies and organizations that receive data analysis assistance. 

MARYLAND PROGRAMS AND PROCESSES USING DATA LINKAGE AND 

ANALYSIS 

 Crash analysis: through their ability to analyze integrated data, NSC has conducted 

numerous research studies. 

o Some of the individual studies performed by NSC include one on older 

motorcyclists and another on lower-extremity injuries (LEI). For the older 

motorcyclist study, the results indicated that that older motorcyclists are 

significantly more likely to incur serious thoracic injuries, and that those injuries 

are more likely to result in death.(6) With the increased use in safety belts and the 

addition of air bags, more motor vehicle occupants are surviving crashes 

however, there has been an increase in LEIs. The injury ratings provided on 

crash reports do not accurately reflect the long-term impacts of LEIs as many LEI 

require multiple surgeries and rehabilitation after the initial hospital discharge.

Through their study, NSC researchers were able to provide details and 

implications of LEI’s, including the resulting long-term physical, psychosocial, and

financial impacts of LEI injuries. (8)Similarly, NSC has used data linkage to conduct 

studies pertaining to the crashes related to driver experience and licensure and 

the effectiveness of motorcycle helmets.

o NSC conducts crash analysis to support SHA with goal setting for the Strategic 

Highway Safety Plan and the Highway Safety Improvement Program along with 

providing data to assist with problem area prioritization for the Maryland 

Highway Office Highway Safety Plan. For the Strategic Highway Safety Plan, NSC 

analyzes the data for each of the emphasis areas and helps with goal setting by 

providing a five-year rolling average using an exponential trend line. Although the 

plan is updated every five years, the goals are updated annually.

 Development of standardized reports: NSC provides information to the MVA, MHSO’s

Regional Traffic Safety Program, and Maryland Legislators for the development of 

standardized reports. The CODES data include crash, EMS, emergency department, 

hospital, citation, licensing, toxicology, and vehicle registrations.(7)

 Answering highway safety legislative inquiries: NSC used various data sets related to 

highway safety to answer Maryland legislature inquiries regarding highway safety. Based 

on this data, Maryland created a Traffic Safety Fact Book modeled on one published by 

NHTSA along with program and county specific fact sheets.(11) NSC was also able to 

conduct extensive analysis of various behavioral program areas.

 Serving as an independent organization: the University is able to bridge organizations and 

bring together data from agencies that otherwise may have been analyzed separately.

For example, traditionally statewide data would not include Baltimore City. However, 

through their separate data use agreements, NSC is able to comprehensively analyze 

data from both the State of Maryland and also Baltimore City.(12)

 Providing data management feedback: At times agencies also request data management

feedback from NSC. NSC provided feedback on data management, validation, and 

analysis to SHA and the State police on the recent change to electronic crash reporting.
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LESSONS LEARNED 

 Personnel: When a program is comprised of one or two individuals, staff turnover can 

destabilize a program. With a larger program, knowledge of the data sharing 

relationships is retained, data analysis capabilities are strengthened, and overall program 

stability is strengthened. The way the NSC program is structured, there is a larger staff 

comprised of programmers, statisticians, epidemiologists, etc., all funded through various 

grants and other projects.

 Institutionalization and funding: Because the NSC CODES program institutionalized early 

after its inception, by broadening the types of analyses conducted and finding funding 

sources, they were able to sustain the program after NHTSA’s support ended.

Institutionalizing early also facilitated bringing in additional datasets and garnering buy-in 

and funding from other agencies. 

 Data sharing agreements: While NSC staff have been able to draw on established 

relationships, the University has formalized those relationships with data use agreements

and the creation of an oversight board, the CODES Board of Directors, comprised of 

data-owners. The establishment of these agreements and creation of the oversight 

board facilitated the access and analysis of data throughout the State.
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REFERENCES 

The following resources were consulted in development of this case study:

1. Kindelberger, J., & Milani, J. A. Crash Outcome Data Evaluation System (CODES): Program 

Transition and Promising Practices. Washington, DC : U.S. Department of Transportation 

National Highway Traffic Safety Administration, 2015. DOT HS 812 178.

2. National Highway Traffic Safety Administration. State Data Programs. [Online] [Cited: June 

6, 2015.] http://www.nhtsa.gov/Data/State+Data+Programs.

3. University of Maryland School of Medicine. NSC Overview. [Online] [Cited: June 6, 2015.] 

http://medschool.umaryland.edu/NSC_Trauma.asp.

4. University of Maryland. NSC Current Collaborators. [Online] [Cited: June 11, 2015.] 

http://medschool.umaryland.edu/NSCforTrauma_collaborators.asp.

5. University of Maryland National Study Center for Trauma and EMS. NHTSA CODES 

Update Presentation. 2015.

6. Dischinger, P., G. Ryb, S. Ho and E. Braver (2006), Injury Patterns and Severity Among 

Hospitalized Motorcyclists: A Comparison of Younger and Older Riders, Annual Proceedings of the 

Association for the Advancement of Automotive Medicine, 50: 237-249.

7. The Crash Outcome Data Evaluation System (CODES) and Applications to Improve Traffic 

Safety Decision-Making. Washington, DC: U.S. Department of Transportation National 

Highway Traffic Safety Administration, 2011.

8. P. C. Dischinger, K. M. Read, J. A. Kufera, T. J. Kerns, S. M. Ho, C.A. Burch, N. Jawed and 

A.R. Burgess (2005 June). Consequences and Costs of Lower-Extremity Injuries (DOT HS 809 

871). Washington, DC: National Highway Traffic Safety Administration.

9. University of Maryland Research and Compliance Office. Institutional Review Board (IRB).

[Online] [Cited: June 11, 2015.] http://www.umresearch.umd.edu/RCO/New/index.html.

10. Maryland Department of Transportation, Motor Vehicle Administration. Traffic Records 

Coordination Committee [Online] [Cited: March 14, 2016.]

http://www.mva.maryland.gov/safety/mhso/Traffic-Records-Coordinating-Committee.htm.

11. Maryland Department of Transportation. State Highway Administration. The University of 

Maryland National Study Center for Trauma and Emergency Medical Systems. Maryland 

Traffic Safety Facts, 2008. [Online] [Cited: March 14, 2016.]

http://www.marylandroads.com/MHSO/factbook2008.pdf.

12. Advanced CODES integration and analysis – Cynthia Burch and Tim Kerns. Telephone 

Interview. April 2, 2015.

13. Cook, L. J., Thomas, A., Olson, C., Funai, T., & Simmons, T. Crash Outcome Data 

Evaluation System (CODES): An Examination Of Methodologies and Multi-State Traffic 

Safety Applications. Washington, DC : U.S. Department of Transportation National 

Highway Traffic Safety Administration, 201. DOT HS 812 179.
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EXPLANATION OF TERMS 

Crash Outcome Data Evaluation System (CODES) is a program originated by the 

National Highway Traffic Safety Administration (NHTSA) that involves a statistical methodology 

to augment State crash data with medical outcome data using probabilistic linkage. (13)

General Use Model (GUM) is a model created to bring together and synchronize data 

collected from multiple States. The CODES Technical Resource Center worked with NHTSA’s 

State Data System and the CODES Data Network to develop a standardization model that 

mapped State-specific crash files onto a standardized format called the General Use Model 

(GUM).(13)

AGENCY CONTACT INFORMATION

Cynthia Burch 

Epidemiologist 

cburch@som.umaryland.edu

University of Maryland Baltimore

STAR-ORC National Study Center for 

Trauma and EMS

110 South Paca Street

Baltimore, MD 21201

Tim Kerns 

Database Engineer

tkerns@som.umaryland.edu

(410) 328-4244 

University of Maryland Baltimore

STAR-ORC National Study Center for 

Trauma and EMS

110 South Paca Street

Baltimore, MD 21201