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Safety Data and Analysis in Developing Emphasis Area Plans (2008)

Chapter: Section II - Data Types Used in Preparing the Safety Plan

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Suggested Citation:"Section II - Data Types Used in Preparing the Safety Plan." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section II - Data Types Used in Preparing the Safety Plan." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section II - Data Types Used in Preparing the Safety Plan." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section II - Data Types Used in Preparing the Safety Plan." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section II - Data Types Used in Preparing the Safety Plan." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
×
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Suggested Citation:"Section II - Data Types Used in Preparing the Safety Plan." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
×
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Suggested Citation:"Section II - Data Types Used in Preparing the Safety Plan." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
×
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Suggested Citation:"Section II - Data Types Used in Preparing the Safety Plan." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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8There are various types of data that can be used in the preparation of a safety plan. The procedures described in this guide are designed such that crash data are required as a min- imum. For the higher-order procedures, the crash data must be “location-coded,” and for some procedures, additional roadway inventory and traffic volume data are required. Thus, as described in Section III, the choice of procedure will depend on the data available in the user’s jurisdiction. There are other types of safety data that can also be used in the development of safety plans. These would include information ranging from driver citation/conviction data to observational surveys of occupant restraint usage. The following provides a brief description of the major types of data that might be used, and some information on where they might be found if not in the user’s own jurisdiction. Some of the following information was taken from NCHRP Report 501 (18). Crash Data and Related Files Local and Statewide Crash Data Records on traffic crashes are derived from the police report form that is usually completed by investigating police officers at the crash sites. A typical crash report contains data on about 100 different pieces of information that describe the crash, the location, and the people and vehicles involved. Crash reports may be used individually to explore the circumstances and factors that contributed to a particular event, and they may be used in aggregate to develop a picture of the safety performance of a given location or jurisdiction. At the local level, the analyst will generally use police- reported crash data from his/her own files. However, some localities that investigate crashes may not retain their own files or may not automate their paper files. In these cases, the ana- lyst should contact the state agency that serves as the custodian for the statewide crash database and request copies of the computerized data for their jurisdiction. The statewide crash database custodian differs from state to state, but is usually either the State Police (or State Highway Patrol), the State Department of Revenue or Motor Vehicles, or the State Department of Transportation. In addition, the safety engineering staff within the state highways department (often the Traffic Engineering Branch) is a major user of the state crash files and can often provide assistance and information concerning how the local jurisdiction can obtain data. In many cases, this staff is also responsible for assigning location codes to the crashes and may maintain a separate crash data- base with more complete location coding. If the analyst is looking for crash data that have gone through a location vali- dation process at the state level, it is often necessary to contact these staff. Note that in most cases, the location-validation process will only be conducted for state-system roads (i.e., Interstate, U.S., and state routes) in local jurisdictions, and not for all local streets and roads. However, the continuing development and refinement of spatial data systems in states (e.g., GIS systems) is increasing the ability to locate crashes to all roads in the state. As noted in NCHRP Report 501 (18), although these archives contain a wealth of information on the driver, the vehicle, and the circumstances of the crash, some caution is warranted. It is critical for the analyst to understand the boundaries and shortcomings in the crash database before using these data to support decision-making. Every state has a reporting threshold – usually a dollar amount of damage or a specific level of injury sustained in the crash – below which a crash report will not be entered into the statewide database. Local jurisdictions, however, may want to include all crashes in their automated systems, not just those resulting in damages or injuries above the state reporting threshold. Con- versely, some local jurisdictions may use a higher threshold such that local police respond to fewer crashes. The statewide crash database may also contain additional crashes for a jurisdiction if more than one law enforcement agency reports (e.g., the local police department, the county sheriff’s office, S E C T I O N I I Data Types Used in Preparing the Safety Plan

and the state highway patrol), with the possibility of each agency using a different crash reporting threshold. In several states, crash reports are collected from the drivers involved in a crash (i.e., an operator report). These operator reports may take the place of police-reported data under certain conditions; for example, below-threshold crashes, crashes in which no one was seriously injured or killed, and weather- or animal-related crashes during peak seasons. In other states, operator reports and officer reports are blended in the final statewide crash database, thus affect- ing the overall consistency of data from one record to the next. Moreover, the NHTSA reports, “. . . various sources suggest that about half of motor vehicle crashes in the coun- try are not reported to police . . .” (19, p. 5). Crash data depend heavily on the subjective judgments of the officers who attempt to describe the crash after the fact. These judgments cannot be error-free since the officer does not see the crash occur, and must rely on physical evidence and driver and witness statements to draw conclusions. Moreover, officers are not experts in some areas that may be of crucial interest to a highway safety analyst, but which the officer is called upon to record for the crash report. A com- parison of police-reported data to those collected by multi- disciplinary crash-investigation teams on the same crashes indicate that the most reliable police data were those concerned with crash descriptors and the least reliable were driver/vehicle variables (20). The police were most accurate on six variables: location (note that most safety engineers in highway departments question this finding), date, day of week, number of drivers, number of passengers, and number of vehicles. The least reliable police data concerned vertical and horizontal road character, crash severity, road surface composition, and speed limit. The accuracy of police judg- ment of crash causes varies by the cause type, with more reliability in detecting human-direct causes than in detecting vehicular, environmental, and human-indirect causes. How- ever, the authors also noted that in the area of human-direct causes, the police performance was relatively good in identi- fying “failure to yield” and “failure to stop” but was relatively poor with respect to “speeding,” “driving left of center,” and “other improper turns.” Data accuracy and data completeness also vary from state to state and among jurisdictions within a state. While it is generally agreed that state police and highway patrol officers provide more consistent and accurate crash data than their local counterparts by virtue of their greater familiarity with crashes and, typically, more extensive training, few states maintain the kind of quality-control measurement program that would support interagency comparisons of accuracy or completeness of crash report data. When using crash data from a single source, such as a municipal police department, it is important to know that agency’s reporting practices and how supervisors review each crash report before it is finally submitted. When using data from more than one source, such as when combining data from the state police, the local sheriff’s office, and the municipal police department, or when comparing crash experience among several jurisdictions, the differences in reporting practices among the various agencies can be critical. In these cases, the analyst should plan to con- duct validation tests as part of the overall analytic process. For example, the analyst might compare the proportions of injury and property-damage-only crashes or the distributions of property damage amounts in the data received from various agencies. If that is not possible, the analyst should learn about the thresholds and reporting practices of each agency as a minimum. Note that these warnings are not to indicate that police data are of questionable value in safety planning, but only to alert the analyst of issues that can affect conclusions. Police data provide large samples of data even in local jurisdictions. Moreover, even with the known problems, these data have been used successfully for years in identifying safety prob- lems, in choosing and targeting treatments, and in evaluating the treatment effects. It is also worth noting that decisions made using the available crash data are going to be better than decisions made without any data at all. Fatal Analysis Reporting System (FARS) Data While most states maintain a database of all reportable crashes that occur on all public roadways, there are frequently limitations to the crash data available for local roadways, especially with respect to location coding and crashes involv- ing property damage only. In addition, some states and local agencies may question the reliability of crash data for less severe crashes, may not have a usable computerized file, or may wish to conduct at least some safety-related analyses using only fatal crashes. In these cases, the Fatality Analy- sis Reporting System (FARS) data system maintained by NHTSA is an excellent database for analysis. FARS contains annual data on a census of fatal traffic crashes within the 50 states, the District of Columbia, and Puerto Rico. According to NHTSA, “. . . to be included in FARS, a crash must involve a motor vehicle traveling on a trafficway customarily open to the public, and must result in the death of an occupant of a vehicle or a non-motorist within 30 days of the crash.” FARS data are available annually back to 1975. Each new year’s file is typically available about 6 months following the end of the year; however, the FARS analyst in each state has access to his/her own state’s fatal crashes at all times. FARS contains more than 100 data elements related to the driver, vehicle, in- volved persons, and the crash itself. FARS has proven to be a rich information source for research and program evaluation focusing on fatal crashes. The quality of the FARS data is quite 9

high due to extensive training provided to the FARS analysts and the attention paid to each case. To assist users in analyzing these data related to fatal crashes, NHTSA provides a “FARS Web-Based Encyclope- dia” at http://www-fars.nhtsa.dot.gov/Main/index.aspx that provides links to national reports and statistics. By clicking on the “Create a Query” link, the user can choose her/his own state and run univariate tables and cross-tabulations for any of the 100+data items. City and county codes make it possi- ble to isolate fatal crash data for local jurisdictions. (Note that the FARS data contain information on every vehicle and every occupant within each fatal crash, not just the fatally injured occupant. Thus, care must be taken in choosing the screens to be used and in interpreting the results.) While multi-year queries are no longer supported, the site contains multi-year reports for individual states under the “States” and the “Trends” links, and analysts can run an analysis for multiple years, one year at a time, to develop multi-year com- parisons. FARS data can also be obtained from NHTSA (see “Request Data” link) on a CD or via download from an ftp site (ftp://ftp.nhtsa.dot.gov/fars/). It is noted that the reliance on fatal-only data has its drawbacks in targeting treatments, with the main one being sample size. In addition, targeting roadway treatments with fatal data is questionable since most factors that turn a crash into a fatal crash are not roadway-related – they are other factors such as driver age or seatbelt use. It is often tempting to conduct analyses using only fatal crash data because the state and national targets all address the number and rate of deaths on highways. It is strongly recommended, however, that crash fre- quency and rate at all levels of severity be used in safety analyses to avoid the problems of small, unrepresentative samples. It is also recommended that if the analyst is not already famil- iar with FARS data, an effort be made to learn about the way the records are created and the proper use of important data fields. Imputed Blood Alcohol Content (BAC) data is one example of a data field in FARS that contains data unlike that in most state or local crash databases. In FARS, BAC values are recorded from the information supplied by police officers and an additional im- puted value is calculated for each driver for which a BAC value was not supplied on the original crash report or cannot be obtained from follow-up contacts with local hospitals or med- ical examiners. Analyses of alcohol-involved crash frequency can obtain markedly different results depending on whether the records or recorded-plus-imputed values are used. This is but one example of how use of FARS data may differ from the use of more familiar local or statewide crash databases. Crash Outcome Data Evaluation System (CODES) The Crash Outcome Data Evaluation System (CODES) is an enhanced state-based crash data system in which police crash data are linked with detailed information on the med- ical consequences of the crash. Originally, seven states were funded by NHTSA to develop the CODES system (Hawaii, Maine, Missouri, New York, Pennsylvania, Utah, and Wisconsin). Twenty-two other states have had CODES demonstration grants or special projects (Alaska, Arizona, Connecticut, Delaware, Georgia, Indiana, Iowa, Kentucky, Maryland, Massachusetts, Minnesota, Nebraska, Nevada, New Hampshire, New Mexico, North Dakota, Oklahoma, Rhode Island, South Carolina, South Dakota, Tennessee, and Texas). At a minimum, basic statewide police crash data are supplemented with hospital data and either Emergency Medical Services (EMS) data or emergency department data. Some states also add data for each driver and other occupants concerning driver license status, vehicle registration, citation/conviction records, insurance claims, rehabilitation and long-term care, and other items. The linkage of medical information to crash and driver data is done through “probabilistic linkage technology” since direct linkage is not often possible due to missing personal information and privacy concerns. CODES data are used in safety studies of specific injury- related issues such as seatbelt and motorcycle helmet effectiveness – any crash-related issue in which more detailed injury data or injury cost data would be helpful. These data could also be used to study specific injuries occurring in road- side object crashes (e.g., head injury to right-front passengers in guardrail impacts) and truck crashes (e.g., abdominal injury for lap-belted truck drivers). Many states use their CODES data to develop a state-specific estimate of the economic impact of crashes that is based on the state’s own data. While CODES is funded by NHTSA, access is controlled by the states. More detail on CODES including links to some participating states may be obtained at http://www-nrd. nhtsa.dot.gov. Motor Carriers Management Information System (MCMIS) This database is a very comprehensive truck safety database that is the source of data for many of the Federal Motor Carrier Safety Administration’s (FMCSA) other data files (e.g., SAFER) and analysis procedures (e.g., SafeStat). Data are entered into MCMIS via the SafetyNet system accessed by per- sonnel in each state’s Motor Carrier Safety Assistance Program (MCSAP) agency. The database is maintained by the FMCSA to allow analysis of motor-carrier issues. MCMIS consists of five files, with input to each file from each state and from car- riers subject to federal truck safety regulations in all states: • Registration (“Census”) file – Carrier information including DOT numbers and descriptive information about a motor 10

carrier’s size and operations, including the number of power units, drivers, and type of cargo. Information is based on Form MCS-150 – the Motor Carrier Identification Report – required of all carriers. • Crash file – The National Governor’s Association has recommended crash data elements for all trucks with gross vehicle weight >10,000 lbs who are involved in a towaway or injury/fatal crash in any state. • Roadside Inspection file – Driver and vehicle information on roadside inspections conducted in all 50 states. Data include violations for both drivers and vehicles, out-of-service indi- cators, and, for drivers, moving violations (e.g., speeding) which are associated with the inspection/stop. • Compliance Review file – Information on detailed on-site examinations of company records for targeted companies. This includes information on violations of Federal Motor Carrier Safety Regulations and Hazardous Materials Regulations found in driver qualification files, duty status files, vehicle maintenance records, and safety management information. It also contains the “safety rating” which results from the Review. • Enforcement file – Information on safety-related sanctions imposed on carriers by FMCSA. These can range from placing the carrier (and all its vehicles) out-of-service to fines and civil penalties. Data are input into the MCMIS files by state and federal truck safety staffs using the SAFETYNET software. Listings of the variables in the crash files can be found in the MCMIS Data Dissemination Program Catalog at http://mcmiscatalog. fmcsa.dot.gov/beta/Catalogs&Documentation. These are the primary safety data used by FMCSA and state truck safety staff in all safety-related efforts. Data from MCMIS are either used directly or modified for use in such programs and methodologies as SAFER, SafeStat, and PRISM. State-based crash tables can be used to look at major factors associated with truck crashes, and comparisons can be made between states. A large number of reports and analysis tools can be found at http://www.fmcsa.dot.gov/facts-research/ facts-research.htm. The “Crash Profiles Online” tool within the “Analysis and Information Online” (A&I Online) suite of tools provides state-by-state truck crash statistics (see http://ai.fmcsa.dot.gov/mcspa.asp). The A&I Online staff, as well as the MCSAP staff in each state can provide annual crash data for reportable crashes involving trucks, buses, and vehicles placarded to carry hazardous materials. A recent Government Accounting Office audit (21) pointed to serious data quality problems in MCMIS, especially in the crash data file. In 2001, FMCSA implemented a Crash Data Improve- ment Program (CDIP) and, in 2004, a quality measurement system. Combined, these efforts have resulted in a large in- crease in the number of crashes reported to MCMIS and in overall quality and timeliness of the data. Analysts should use caution in making multi-year comparisons using MCMIS data until the reporting level and quality have stabilized at their new higher level. MCMIS crash data from 2004 onward are of considerably higher quality and completeness than are the data for prior years. Roadway Inventory Data State Inventory Data Each state highway agency and some local transportation and public works departments, and regional planning agen- cies (e.g., MPO, RPA, RPC) collect and maintain roadway inventory data on each section of roadway within the highway systems they control. The data are generally “cross-section” information on the roadway – number of lanes, shoulder type and width, median descriptors, and pavement types. Most states also have supplemental files describing bridges (as part of the National Bridge Inventory) and railroad grade crossings (as part of the Federal Railroad Administration’s Railroad Grade-Crossing Inventory) that can usually, but not always, be linked to the basic roadway inventory file. A very few state systems also include information on curves and grades, two important safety predictors. A limited number of states also have developed intersection and interchange inventory files providing detailed descriptions of such items as intersection type, traffic control type, turning lanes, mainline and cross- road traffic volumes, interchange type, and ramp length. There may also be additional roadway-oriented supplemental files on such safety-related information as skid numbers, intersection turning counts, intersection signalization phas- ing, pavement condition, and speed profiles. These files, which are not always computerized, will vary in the degree of completeness and accuracy. While the basic inventory files can usually be linked to the crash data, linkage between some of the supplemental files may be difficult. The basic inventory file is usually organized as “homo- geneous sections” of a given route, where all the basic in- ventory items are constant. If an item changes value, a new homogeneous-section record begins. This leads to very short sections in most state files. Each section has an “address” which often consists of a route and beginning and ending “milepost.” Crashes are given a route and mileposts based on the investigating officer’s location description so that they can be linked to the roadway file. Currently, these files are be- coming geo-coded (i.e., coordinates are added), so that they can be used in Geographic Information Systems (GIS). The move toward GIS mapping is causing some major changes in the way locations are coded in roadway inventory files, and, in many states, crash databases as well. At present, the most useful and effective systems support multiple ways to define 11

locations, sections/segments, and routes so that data entered or stored in one form can be linked to all other relevant data. The lack of intersection and interchange inventory data in most highway agencies is a key limitation in safety planning and safety management for intersections and for interchange features such as ramp, speed-change lanes, and collector- distributor roads. It is hoped that the development of uni- form requirements for such inventory data (see the discus- sion of the Minimum Inventory of Roadway Elements [MIRE] in Section XII of this guide) and the development of tools like SafetyAnalyst that can use such data will encourage the wider use of intersection and interchange inventory data. Some local jurisdictions will also maintain inventory files, but many do not have them computerized or in a central location. Generally, they will be maintained and stored by different departments (e.g., traffic engineering, street mainte- nance). The more extensive files will contain similar informa- tion to that collected by the states. Files on signalization at intersections are usually maintained for legal purposes, but are sometimes not easily linkable with other inventory or crash data. Some localities also maintain supplemental files related to sidewalk presence, crosswalks, bicycle paths, bus stops, and other variables. Highway Performance Monitoring System (HPMS) Many of the above described state roadway inventory sys- tems were expansions of the HPMS system, a 1978 congres- sionally mandated data system to collect data on the nation’s highways. HPMS is similar to the state inventory systems, but is based on a sample of locations from different functional classifications in each state, rather than containing the full state system. It contains limited data on all public roads. Data are inputted each year by each state, and collected, analyzed and reported to Congress by FHWA. While earlier versions of the system contained crash information for each sample section, this is no longer the case. However, since HPMS samples are usually flagged in the basic state inventory sys- tem, crashes could be linked with them. In general, the state analyst will use the state system rather than HPMS data in state-based safety analyses. Other Roadway and Intersection Characteristic Data Other data on roadway and intersection characteristics can be obtained from aerial photographs. In particular, ortho- photos are geographically converted to allow accurate meas- urements to be made. The ongoing development of asset management databases by state and local highway agencies will also provide a potentially valuable source of roadway and intersection characteristics data. These data sources may be particularly useful in development of safety plans if they can be linked to the location reference system used in crash data. Traffic Volume Data State highway agencies collect and maintain data on traffic volumes (Average Annual Daily Traffic [AADT]) for roads on the state-controlled system. The AADTs are based on counts made at both a limited number of permanent count stations and a much greater number of sampling locations where 2- to 3-day counts are taken on each highway system. The standard is that the entire state system is covered on 2- to 3-year cycles. The “short” counts are then converted to AADTs using factors based on the day of the count, season, and other factors, and are extrapolated to all sections of road- way and to years when counts are not made at a given count station. The AADTs are either retained as a variable on the roadway inventory file, or in a separate file that is linkable with the inventory. Not all states conduct counts on the rec- ommended 2- to 3-year cycle. Even in states that do adhere to the standard data collection cycle, traffic counts for some scheduled locations are not collected. In such cases, states typically replace the missing data with estimates. In addition to AADTs, state agencies also collect and main- tain large-truck counts or percentages for each roadway sec- tion. These are based on counts made with special equipment that can separate vehicles into classes by length and number of axles. These “classification counts” are usually made at many fewer locations than the basic traffic counts, so their accuracy is less than for the AADT estimates. Supplemental truck counts may be made at other locations where “weight- in-motion” systems are in place for use in truck-weight regulation efforts. Local jurisdictions will also have traffic volume informa- tion, but the consistency and quality varies by jurisdiction. While AADTs may be calculated for each city block in some cities, it is often the case that only intersection turning-volume counts made in signalization studies are available. In some lo- cations, linkage of count data to other inventory files may be problematic. In general, traffic volume data is more limited in local jurisdictions than for the state-system roads. Driver History Files Departments of motor vehicles maintain driver records of all licensed drivers in the state. Driver records are typically generated when a person enters the state licensing system to obtain a license or when unlicensed drivers have had a viola- tion or crash in the state. The record contains basic identifiers (e.g., name, address, driver license number), demographic information on the driver (e.g., birth date, gender), and in- formation relevant to license and driver improvement actions 12

(e.g., license issuance and expiry/renewal dates, license class, violation dates, suspension periods). In some states, informa- tion on crash involvements (e.g., occurrence date, crash sever- ity) is also available. Driver records are especially useful for examining issues related to driving history and rates of recidivism (e.g., re- offending for moving violations and traffic-related criminal convictions). However, many states purge the driver record of information on driving history after a certain period of time. Consequently, driver records are incomplete and driv- ers identified as first-time offenders may have had previous convictions for the same offence. Analysts should also be aware that a driver history file used for aggregate data analy- sis is certain to be a snapshot of the statewide data at the time the request was made. The data update and purge cycles can have a dramatic effect on the information available for analy- sis at any given time, so care must be taken to work with the driver file custodians to ensure that the resulting analyses and conclusions are valid and representative of the driver popu- lation of interest. Vehicle Registration Files Departments of motor vehicles maintain motor vehicle registration files for use in vehicle licensing and taxation. These files contain information on the vehicle identification number (VIN); plate number; and vehicle weight, model, make, and year. Vehicle registration data can be used in developing safety strategies when, for example, information on the number of licensed vehicle by type is needed. Note, however, that it would be unusual for these files to contain annual mileage driven, so a measure of “miles of exposure by vehicle type” cannot be developed. Even when the file does contain annual miles driven, the reliability of the mileage data and their utility in analyses are questionable. Analysts are cautioned to be sure they know exactly how the data are col- lected and how the state handles missing, incomplete information and odometer readings that are greater than a certain threshold (usually 100,000 miles). Statewide Injury Surveillance System Files With the growing interest in injury control programs within the traffic safety, public health, and enforcement com- munities, there are a number of local, state, and federal initiatives which drive the development of a Statewide Injury Surveillance System (SWISS). These systems typically incor- porate pre-hospital (EMS), trauma, emergency department (ED), hospital in-patient/discharge, rehabilitation and mor- bidity databases to track injury causes, magnitude, costs, and outcomes. Often, these systems rely upon other components of the traffic records system to provide information on injury mechanisms or events (e.g., traffic crash reports). The custo- dial responsibility for various files within the SWISS is typically distributed among several agencies and/or offices within a State Department of Health. Depending on its component data systems, the SWISS system can provide information that tracks magnitude, severity, and types of injuries sustained by persons in motor- vehicle-related crashes. There are standard coding systems for injuries and injury causal factors that can be gathered from the health-related datasets. Although traffic crashes cause only a portion of the injuries within any population, they often represent one of the more significant causes of in- juries in terms of frequency and cost to the community. The SWISS should support integration of the injury data with police reported traffic crashes and make this information available for analysis to support research, public policy and decision-making. In most states, this integration is most likely to happen through a CODES probabilistic linkage process. National Emergency Medical Services Information System (NEMSIS) The ability to evaluate and improve Emergency Medical Services (EMS) systems has long been hampered by the lack of consistent and detailed EMS data at either the state or national level. While a state’s EMS system is usually coordinated at the state level, with EMS providers trained and certified by the state EMS office, the system itself is composed of multiple local providers. Thus, the data required in a sound state (and ulti- mately national) database must be collected by these local agencies. Because of both the lack of a universal set of “endorsed” data variables and the fact that there is often no legal requirement for systematic collection of such data, state EMS data systems have varied greatly in terms of the composi- tion and completeness of their data. Working with the Centers for Disease Control (CDC) and the Health Resources and Services Administration (HRSA), NHTSA is coordinating the NEMSIS project which will ultimately lead to a national EMS database, populated from participating-state databases. The raw data will continue to be collected by the individual local providers, but the data collected will be based on a data dictionary containing standardized variables and codes. These data elements were developed by the three sponsoring agencies in consultation with a number of national EMS associations ranging from the National Association of State EMS Directors to the National Association of Emergency Medical Techni- cians. For computer storage, the data will be defined using an XML (extensible markup language) standard which will allow easy transfer of the data between different local (e.g., private EMS and fire-based EMS), state, and national computer systems. The data dictionary contains a set of core elements 13

that will be required in the national system, but also many additional standardized elements that the state and local agen- cies can choose to collect for their own use. To facilitate the development of this database, the NEMSIS project is also funding a Technical Assistance Center (TAC) that will not only build the National EMS Repository, but will also provide assistance to state and local agencies in their data collection efforts. The TAC will conduct site visits of states to assess current and planned systems, certify EMS software products developed by vendors to ensure that they are com- pliant with the new NHTSA 2.2.1 data dictionary, and provide other assistance to the states such as example legislation and data collection policy and procedures (including privacy policies). The collection of data from seven states that meet all the necessary criteria began in 2006, with additional states expected to join the effort in 2007. Population Census Files The U.S. Census Bureau and the state demographer main- tain data on population characteristics that can be useful in safety analyses. Typically, these data will give estimates of total population and gender, age, and ethnicity subpopulations broken out within political subdivisions. These data can be used to develop measures of crash risk, injury risk, and fatality risk for specific groups based upon their residence location and any demographic characteristics that are recorded in the crash and population databases. While these types of analyses are most often used for epidemiological research, they are gaining acceptance among highway safety practitioners because of the additional insight they can provide into a jurisdiction’s crash experience, especially when countermeasures may involve education or driver behavior-related programs. Citation Tracking and DUI Tracking Files A special case of multi-agency data sharing is the creation of citation tracking and DUI tracking databases. The cita- tion tracking system is viewed as a “cradle to grave” database of every citation issued in the state. From the point of initial printing, through assignment to an agency, an individual officer, issuance by that officer, processing by the Court or administrative processes, and final disposition, the citation is trackable. This supports a variety of safety-related analy- ses that are not possible if each agency controls their own citations and does not track what happens after the officer issues them. In particular, states have found that citation tracking systems are useful in detecting recidivism for seri- ous traffic offenses earlier in the process (i.e., prior to con- viction) and for tracking the behavior of law enforcement agencies and the courts with respect to dismissals and plea downs. Such analyses can be useful in identifying training needs for law enforcement officers, prosecutors, court clerks, and judges. DUI tracking systems incorporate some features of a cita- tion tracking system (however, only for drunk- or drugged- driving offenses) and add several other functions beyond those. In particular, a DUI tracking system is likely to contain data that could be used to evaluate the effectiveness of court- ordered and administrative actions required of offenders. The system can be used to track recidivism rates for people assigned to various treatment programs, or those subject to various license restrictions. In this way, the state can learn which measures are most effective in ensuring that offenders do not reviolate. Local Data Files Local engineering and law enforcement agencies, especially, are likely to maintain data on roadways and incidents (e.g., crashes, citations) in their jurisdiction. The roadway data may closely mirror that in a statewide system, but could also contain additional traffic counts, more precise or up-to-date information on changes to the roadway network and, perhaps, inventories of signs, markings, traffic control devices, and other roadside appurtenances. Where such data exists, the state DOT and other users can potentially access it to develop a more complete description of safety experience in the state by including details for the local roadway system that may not already exist in state files. Many local engineering agencies use a GIS and have sophisticated mapping capabilities that users can tap into. Local law enforcement agencies often have a record of every crash in their jurisdiction, and may have complete citation records as well. Law enforcement agencies use these records for manpower allocation and crime mapping, among other purposes. Other users may find the data useful in developing a more comprehensive view of traffic safety in a local area. Crashes that fall below the state’s reporting threshold may still be of interest to engineers looking for high-crash locations. Even crashes on private property may have some use for special analyses. One example would be an analysis of crashes in which one or more vehicles is backing up – the vast major- ity of such crashes occur in parking lots and are usually not recorded in the statewide crash database. The crash database at a local law enforcement agency is a potential source for valuable information not already captured in the statewide crash database. Other types of local databases may exist. For example, in the absence of a statewide EMS-run database, or a statewide trauma registry, it may still be possible to obtain this informa- tion from local sources (the EMS providers or trauma registries at designated trauma centers). A metropolitan planning organization (MPO) or regional planning council/commission 14

(RPC) is often an excellent source of traffic data, projections, and other highway design and usage information. With a few notable exceptions, court records are almost always obtainable only at the local level (if at all). These may be used to track citations through the court processes, look at recidivism rates, and document the frequency of plea bargaining in traffic- related cases. Other Safety Files A variety of other files that might be useful in safety studies is sometimes available in a jurisdiction. Speed surveys are collected by both state and local agencies. Note, however, that since statewide speed surveys on Interstate roads were essen- tially ended in 1995 with the repeal of the National Maximum Speed Limit, there are very few jurisdiction-wide speed surveys conducted. Instead, speed surveys are usually conducted at spe- cific sites where a change in speed limit is being considered or has been recently implemented. The speed data collected at these “special” locations should not be considered good indica- tors of jurisdiction-wide speeds. Thus, safety planning needing speed data will usually require in-field speed data collection. Trauma registry data and emergency medical services (EMS) data can potentially be used to enhance the complete- ness of crash data in much the same way as medical records are used to enhance crash data through the CODES database (see above). Data on roadway maintenance histories includ- ing the types of maintenance actions and their locations and dates may be useful in the development of safety plans. Because of their effectiveness in reducing fatalities and serious injuries, perhaps the most important of the “other” safety data is occupant restraint (shoulder belt) use data collected in each state since 1998 in compliance with TEA-21 requirements. NHTSA developed detailed sampling criteria for this data collection, and produces annual reports on changes in restraint usage for all states (see, for example, http:// www.nhtsa.gov/people/injury/airbags/809713.pdf). These data are usually collected by the state Highway Safety Office (or Office of the Governor’s Highway Safety Representative), and data and information can be obtained there. Finally, public opinion and customer service data can provide key inputs in the development of safety plans. Many highway agencies conduct or have access to results of surveys of the general public or, more specifically, of motorists. For example, NHTSA has a requirement for telephone surveys to measure the effect of media-based public information pro- grams. Some state and local agencies may maintain customer service call logs, where the type and number of reported con- cerns can be tracked by location. Customer service data, including complaints from the public and their disposition, may provide useful information on problem locations or safety programs that are not functioning as designed. Time Dimension of Data Some types of data used in safety planning by their nature cover specific time periods. For example, crash data and cita- tion data document events that occurred at a specific time, and data files generally cover a specified time period. A second type of data file provides supplementary infor- mation gathered subsequent to a crash that, in order to be useful, must be linked to the crash record. Examples include medical records, which can be linked through the CODES database, and trauma registry data. Such data may not include the actual time or location of the crash and must, therefore, be linked through the victim’s identity. A third type of data represents a snapshot of a population at a given point in time, but does not necessarily include the full history of that population. For example, driver history files typically include only drivers with active licenses at a specific point in time. The records for drivers who die or move out of state are deleted, so a current driver “history” file does not nec- essarily contain the history for all drivers during a given time period. Planning based on complete driver history data may need to consider historical files as well as current files. Closure In general, the most basic safety data – the police- reported crash report – will be available for use by ana- lysts in almost all state and local jurisdictions. The analyst will sometimes have to locate and acquire the data. Procedures are presented in this guide that require only basic crash data. Additional non-crash data (e.g., roadway inventory and AADT data) that can be used in planning safety efforts for roadway-, driver-, and vehicle- based treatments are usually available for state-system road- ways and sometimes available for local roads. With some effort, additional supplemental files that can further enhance safety analyses can be located. In summary, “lack of adequate data” is almost never a valid excuse for not developing a sound safety program. 15 “Lack of adequate safety data” is almost never a valid excuse for not developing a sound safety program.

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TRB's National Cooperative Highway Research Program (NCHRP) Report 500, Vol. 21: Guidance for Implementation of the AASHTO Strategic Highway Safety Plan: Safety Data and Analysis in Developing Emphasis Area Plans provides guidance on data sources and analysis techniques that may be employed to assist agencies in allocating safety funds.

In 1998, the American Association of State Highway and Transportation Officials (AASHTO) approved its Strategic Highway Safety Plan, which was developed by the AASHTO Standing Committee for Highway Traffic Safety with the assistance of the Federal Highway Administration, the National Highway Traffic Safety Administration, and the Transportation Research Board Committee on Transportation Safety Management. The plan includes strategies in 22 key emphasis areas that affect highway safety. The plan's goal is to reduce the annual number of highway deaths by 5,000 to 7,000. Each of the 22 emphasis areas includes strategies and an outline of what is needed to implement each strategy.

Over the next few years the National Cooperative Highway Research Program (NCHRP) will be developing a series of guides, several of which are already available, to assist state and local agencies in reducing injuries and fatalities in targeted areas. The guides correspond to the emphasis areas outlined in the AASHTO Strategic Highway Safety Plan. Each guide includes a brief introduction, a general description of the problem, the strategies/countermeasures to address the problem, and a model implementation process.

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