Analysis of Pennsylvania Crash Statistics Data By: Louis Pesci, Ph.D., Jeffrey Grim, P.T.P, Lucas Tatarko and Joseph Franze Indiana University of Pennsylvania May 2017 Executive Summary In 2015, 1,200 Pennsylvanians died in reported motor vehicle crashes and another 80,004 were injured. A disproportionate number of traffic fatalities in relation to the population occurs in rural areas of Pennsylvania and nationwide. This research analyzed vehicle crashes in Pennsylvania to determine if there are any differences in the number or severity of crashes between rural and urban Pennsylvania. The researchers analyzed vehicle crash data from 2010-2015 from the Pennsylvania Department of Transportation. The research analyzed the demographic profile and causes of crashes for individuals in Pennsylvania by age group, specifically for younger (16-20) and older (65+) drivers in Pennsylvania, by rural and urban municipality, and by proximity to emergency service providers, local police, Pennsylvania State Police stations, hospitals, and trauma center hospitals in Pennsylvania. The research results indicated that: In Pennsylvania, 28.9 percent of all reported crashes resulting in injuries and fatalities occur in rural areas: of these, 46.5 percent result in fatalities and 37.7 percent result in major injuries. areas have a higher share of crashes with major injuries and moderate injuries than urban areas. In both rural and urban areas, occupants that use no restraints are about four times more likely to suffer a fatality in an accident than occupants that use restraints (3.09 percent versus 0.83 percent for urban areas, and 3.14 percent versus 0.79 percent for rural areas, respectively).
In both rural and urban areas, the highest percentage of crashes with an injury or fatality occurs on state highways, followed by local roads or streets. In both rural and urban areas, males are two times more likely than females to be in a crash with a fatality. Drugs and/or alcohol were not suspected in the majority of fatal crashes in both rural and urban Pennsylvania. About 94 percent of all injury and fatal crashes in rural areas occur in townships of the second class. This result was not surprising since these municipalities cover about 98 percent of rural Pennsylvania and include 88 percent of the rural population. In urban areas, a plurality of injury and fatal crashes occur in cities and townships of the second class. The largest percentages of injury and fatal crashes occur during daylight hours in both rural and urban areas. However, in rural areas, higher percentages of injury and fatal crashes occur on dark streets with no street lights than in urban areas. In both rural and urban areas, crashes on dry roads are more likely to involve a fatality than crashes on roads that are wet, snow covered, icy or slushy. In both rural and urban areas, the highest percentage of those involved in injury and fatal crashes are those aged 25 to 34. In rural areas, higher percentages of youth, aged 15 to 24, are involved in moderate and major injury and fatal crashes than youth, aged 15 to 24, in urban areas. Crash areas that are more than 31 minutes from a trauma center have more than two times the percent of fatalities as those within 15 minutes. This supports the Golden Hour concept in emergency medicine that suggests the first hour after the occurrence of a traumatic injury is the most critical for successful emergency treatment. This project was sponsored by a grant from the Center for Pennsylvania, a legislative agency of the Pennsylvania General Assembly. The Center for Pennsylvania is a bipartisan, bicameral legislative agency that serves as a resource for rural policy within the Pennsylvania General Assembly. It was created in 1987 under Act 16, the Revitalization Act, to promote and sustain the vitality of Pennsylvania s rural and small communities. Information contained in this report does not necessarily reflect the views of individual board members or the Center for Pennsylvania. For more information, contact the Center for Pennsylvania, 625 Forster St., Room 902, Harrisburg, PA 17120, telephone (717) 787-9555, email: info@rural.palegislature.us, www.rural.palegislature.us.
Table of Contents Introduction... 1 Young Drivers... 1 Older Drivers... 2 Heavy Trucks... 2 The Golden Hour... 2 Goals and Methodology... 3 Data Collection... 3 Compiling and Formatting the Databases in Excel... 3 Crash Record Identifier... 4 Latitude and Longitude... 4 Replacing Empty Cells... 4 and Crash Data... 4 Mapping and Adding Attributes in ArcGIS... 5 Projection... 5 or... 5 Destinations: Hospitals and Trauma Centers... 6 Origins: Emergency Service Providers, Local Police Departments and State Police Stations... 7 Impact of the Marcellus Shale... 9 Objective 1... 10 Objective 2... 11 Results... 11 Statewide - Demographic Profile of and Crashes... 11 Statewide - Demographic Profile of and Crashes with Proximity Data... 23 Conclusion... 29 - Differences... 29 Limitations... 30 Areas of Future Research... 30 References... 31
Introduction In 2015, 1,200 Pennsylvanians died and another 80,004 were injured in reportable motor vehicle crashes (Pennsylvania Department of Transportation, 2015). Each year, the Pennsylvania Department of Transportation (PennDOT) provides information on these reportable crashes, defined as crashes in which an injury or a fatality occurs or at least one of the vehicles involved requires towing from the scene (PennDOT, 2015). While the PennDOT reports include statistics by county, they do not provide a breakdown by rural and urban Pennsylvania. According to the National Highway Traffic Safety Administration (NHTSA), a disproportionate number of traffic fatalities in relation to the population occur in rural areas in Pennsylvania and nationwide (2013). Areas defined as rural or urban in the NHTSA report are those used by the U.S. Census Bureau. According to the ity Analysis Reporting System (FARS), in 2011, about 50 percent of all traffic fatalities occurred in rural Pennsylvania while about 27 percent of the population lived in rural counties in 2010 (NHTSA, 2013). Also, in 2011, the national fatality rate per 100 million vehicle miles traveled was 2.5 times higher in rural areas than in urban areas (1.82 and 0.73, respectively) (NHTSA, 2013). Young Drivers According to Georges Benjamin of the American Public Health Association, Motor vehicle crashes remain the leading cause of death for youth and young adults between the ages of 5 and 24, (U.S. Department of Transportation, 2014). In the U.S. in 2010, 1,963 young drivers aged 15 to 20 years old were killed and another 187,000 were injured in car collisions (NHTSA, 2012). Even though young drivers represent 6.4 percent of licensed drivers in the U.S., they made up 10 percent of the drivers in fatal crashes and 14 percent of all drivers in all crashes (NHTSA, 2012). According to the most recent data from the Insurance Institute for Highway Safety, in 2008, drivers aged 16 to 19 years old were involved in 4.6 fatal crashes per 100 million miles traveled, compared to 3.8 fatal crashes for drivers aged 20 to 24 and 1.2 fatal crashes for drivers aged 30 to 59. These data indicate that, on a per-mile-driven basis, young drivers tend to be more involved in crashes Analysis of Pennsylvania Crash Statistics Data 1
(2011). When comparing driver fatalities versus passenger fatalities of teen drivers, 63 percent of fatalities are passengers of teen drivers or occupants of other vehicles (Shults and Ali, 2010). Older Drivers The number of older drivers has increased dramatically as the Baby Boomer generation began turning 65 in 2010. Nationwide, 16 percent of drivers are 65 years old and older. By 2030, this proportion is expected to rise to at least 20 percent (Goodwin et al., 2013). According to Goodwin et al., As drivers age, their physical and mental abilities, driving behaviors, and crash risks all change, though age itself does not determine driving performance. Many features of the current system of roads, traffic signals and controls, laws, licensing practices, and vehicles were not designed to accommodate older drivers. Older Americans are increasingly dependent on driving to maintain their mobility, independence, and health. The challenge is to balance mobility for older drivers with safety for all road users. (2013) Heavy Trucks Improving truck safety is especially critical in the rural areas of Pennsylvania that have seen crashes increase due to the presence of Marcellus Shale drilling activities. An Associated Press analysis of traffic deaths and U.S. Census data in six drilling states showed that fatalities have more than quadrupled in some places since 2004, a period when most U.S. roads have become much safer, even as the population has grown (Begos and Fahey, 2014). The Golden Hour The Golden Hour is a term used by emergency medical services to describe the concept of bringing severely injured trauma patients and surgeons together as quickly as possible to increase the patients chances of survival (Eisele, 2008). Although the medical community has debated the actual length of time, the validity of the concept remains. Using the Center for Pennsylvania s definitions for urban and rural counties, and data from the Pennsylvania Department of Health, the researchers identified 32 trauma hospitals, 25 of which are in the state s 19 urban counties and 7 of which are in the Analysis of Pennsylvania Crash Statistics Data 2
state s 48 rural counties. Eighteen of the total 32 trauma hospitals are located in the southeastern region of the state. Where regionalized trauma centers are present, death rates among severely injured car crash patients are significantly lower (Institute of Medicine, 2006). Seriously injured trauma victims are 25 percent less likely to die if they are treated at a trauma center (Centers for Disease Control, 2009). Individuals that are seriously injured in crashes located in rural areas may wait for hours to receive the appropriate care at trauma centers (Institute of Medicine, 2006). In rural areas, the most common first responders are emergency service providers and local and state police agencies. Goals and Methodology The goal of the research, which was conducted in 2016, was to analyze 2011 to 2015 Pennsylvania Department of Transportation injury and fatal crash data for rural and urban Pennsylvania to determine if: crash statistics data vary for rural and urban Pennsylvania and crash severity varies spatially with proximity to hospitals and trauma centers, emergency service providers, local and state police agencies, and Marcellus Shale well locations in Pennsylvania. Data Collection The analysis is based on reportable motor vehicle crash databases for Pennsylvania from the Pennsylvania Department of Transportation for the years 2011 to 2015. Compiling and Formatting the Databases in Excel To complete the formatting for use in ArcGIS, the researchers compiled five databases into one large database, modified the crash record identifier, converted the latitude and longitude units, replaced empty cells with a specific value, and selected injury and fatal crashes. Analysis of Pennsylvania Crash Statistics Data 3
Crash Record Identifier Each crash record has a unique identifier assigned by the Pennsylvania Department of Transportation in the field CRN, which stands for crash record number; each 10-digit CRN begins with the four-digit year of the crash. When converting the Excel database into a shapefile, the field CRN was defaulted into a field with ten digits with the last digit being a decimal. This caused the last digit of the identifier to be a zero. The unique identifier was needed to join the data to person data. To solve this issue, the researchers created the field CRN_2 in the Excel database. The field was populated by using the following formula: CRN/1000. This gave the unique identifier three decimal places while decreasing the numbers in front of the decimal. When the database was converted to a shapefile, the unique identifier in field CRN_2 remained intact. Latitude and Longitude Nearly 99 percent of all records have latitude and longitude coordinates. To map them using ArcGIS, the researchers converted the units from units of degrees-minutes-seconds to units of decimal degrees. This computation was performed for all crash records. The 2,144 crash records without latitude and longitude coordinates were not used in this analysis. Replacing Empty Cells ArcGIS is unable to compute empty cells while joining different data sets. Therefore, the researchers found all empty cells and replaced them with the value 999. After trial and error, the researchers found that replacing the empty cells prior to merging the databases helped to avoid slow processing times. and Crash Data The original dataset contained all reportable crashes in Pennsylvania. Reportable crashes include three types of crashes: fatal crashes, where one or more of the involved persons died within 30 days of the crash and the death(s) is attributable to the crash; injury crashes, where none of the involved persons were Analysis of Pennsylvania Crash Statistics Data 4
killed, but at least one was injured; and property damage only crashes, where no one was killed or injured but damage occurred to a vehicle requiring towing. Due to the large sample size of 319,455 records, fatal and injury crashes were selected to be used for the crash analysis. This limited the number of records that were analyzed to 217,323 records. Mapping and Adding Attributes in ArcGIS To prepare the database for analysis, the researchers used ArcGIS to map the data and execute geoprocessing tools to add fields with proximity data. They then assigned the crash records the following variables: as either urban or rural; minutes from trauma centers; whether they occurred within a municipality whose center is 5 miles from a hospital, a trauma center, an emergency service agency, a local police department, or a state police station; and areas that were identified by density of Marcellus Shale gas wells. Projection When originally displayed, crash records had only latitude and longitude reference but no defined projection. A defined projection allows geoprocessing tools to be used since the software can overlay the crash records with other geographic layers, like counties and municipalities. Once properly projected, 10 records that were outside of Pennsylvania were eliminated from the sample, because they could not be assigned proximity data. or The researchers used the Center for Pennsylvania s definition of urban and rural municipalities to assign each record as urban or rural. A municipality is rural when the population density within the municipality is less than 284 persons per square mile or the municipality s total population is less than 2,500, unless more than 50 percent of the population lives in an urbanized area, as defined by the U.S. Census Bureau. All other municipalities are considered urban. and rural municipalities are displayed in Figure 1. Analysis of Pennsylvania Crash Statistics Data 5
Additionally, the research identified 19 crashes that did not have an urban or rural code. Each of these 19 crashes was then located on a map and coded according to their location. Nine of the 19 crashes fell between municipalities that were urban and rural. These nine crashes were coded 999, since urban or rural could not be determined. Figure 1: and Pennsylvania Municipalities Source: Center for Pennsylvania, 2014, and Pennsylvania Department of Transportation, 2015. Destinations: Hospitals and Trauma Centers One key task of the Golden Hour is delivering patients to quality care as quickly as possible. Figure 2 shows the locations of hospitals and trauma centers. Trauma centers are a subset of hospitals. The major feature that differentiates trauma centers from hospitals is the requirement for 24-hour availability of a team of specially trained health care providers who have expertise in caring for severely injured patients (Pennsylvania Trauma Systems Foundation, 2016). Distance to trauma centers was determined for all injury and fatal crash records. Every crash record was coded based on the crash s location within 15, 30, 45, or 60 minutes of driving time to trauma Analysis of Pennsylvania Crash Statistics Data 6
centers (See Figure 2). Crashes outside 60 minutes driving time were coded 0, inside 60 minutes but outside 45 minutes were coded 1, inside 45 minutes but outside 30 minutes were coded 2, inside 30 minutes but outside 15 minutes were coded 3, and those inside 15 minutes were coded 4. The number of records for each driving time distance was recorded to make sure all records were coded. Figure 2: Hospitals, Trauma Centers, and Drive Time to Trauma Centers Sources: Pennsylvania Department of Health, 2012, Pennsylvania Department of Transportation, 2015, and the Center for Pennsylvania, 2014. Origins: Emergency Service Providers, Local Police Departments and State Police Stations Another Golden Hour key task is responding to incidents as quickly as possible. For this study, emergency service providers, local police departments and state police stations were selected as the agencies most likely to be first responders at the incident scene. Emergency service providers include Basic Life Support (BLS) agencies, Advanced Life Support Medical Command (ALS-MC), and Advanced Life Support Squad (ALS-SQ). The list of providers was obtained from the Pennsylvania Analysis of Pennsylvania Crash Statistics Data 7
Trauma Systems Foundation (PTSF, 2014). Because more than half of the addresses could not be geocoded, the data were grouped by ZIP Code, given a value of 1 if any provider within the zip code offered the service and a 0 if not, and then joined to a 2009 U.S. Census Bureau TIGER/line 5-digit zip code shapefile downloaded from the Pennsylvania Spatial Data Access (PASDA). Local police department data were obtained from the Pennsylvania Department of Community and Economic Development s (DCED) Municipal Statistics Municipal Police Service database (DCED, 2016). The data include municipalities in Pennsylvania by type of police service, which are Own Municipal Police Force, Regional Police Force, Police Service Contracted from Another Municipality, and State Police Coverage Only (See Figure 3). Crash data included the municipality where the crash occurred and the first police agency that responded to the 911 call. Local police were defined as a municipal or regional police departments. Using this information, the researchers determined the number and percent of crashes where the local police responded. If the local police did not respond, the state police were typically first on scene. This was done by calculating the total number of crashes in a municipality and the number of accidents where local police responded. From this data, the researchers identified high responsive local police departments, which were defined as local police agencies that either responded to 80 percent or more of the municipality s reportable traffic crashes or responded to 100 reportable traffic crashes. If a local police department is not considered a high responsive police department, it infers that it did not have the capacity to respond to traffic accidents or it did not have 100 or more crashes in a year. In addition, 87 Pennsylvania State Police (PSP) station locations, included the nine stations used by PSP Troop T, which is charged with patrolling the Pennsylvania Turnpike, were obtained from the PSP website and geocoded (See Figure 3). This helped to identify all municipalities with a state police presence and to determine which crashes occurred in a municipality with a state police presence. Analysis of Pennsylvania Crash Statistics Data 8
Figure 3: Pennsylvania Municipalities by Type of Police Coverage Source: Pennsylvania Department of Transportation, 2011-2015 and Pennsylvania Department of Community and Economic Development, 2016. A new field was added to the crash database called PoliceResp. This field was created to combine high responsive local police presence with municipalities with state police stations. The field included the following formula, [State_Pol] + [GrNum100] + [Gr80], and then converted to 0 for low responsive or no department and 1 for high responsive local department or state police stations. Impact of the Marcellus Shale Pennsylvania was divided into six regions based on the presence of gas wells as shown in Figure 4. After mapping the active unconventional gas wells, however, two high density areas, one in the southwest (Region 1) and one in the northeast (Region 2) were identified (See Figure 4). Counties vary in size, so the number of wells per county is somewhat arbitrary used alone. The number of active wells combined with the density of wells was used to determine if the counties were high-density,, Analysis of Pennsylvania Crash Statistics Data 9
moderate-density, or limited-density. The six regions shown in Figure 4 were coded as follows: high-density gas well counties of the southwest are coded 1, high-density gas well counties of the northeast are coded 2, moderate-density gas well counties of the western part of the state are coded 3, limited-density gas well counties in the northwest are coded 4, limited-density gas well counties in the southeast are coded 5, and Allegheny County is coded 6 because it had a temporary moratorium prohibiting unconventional gas wells. Figure 4: Pennsylvania Active Unconventional Gas Wells by Defined Region Source: Pennsylvania Department of Transportation, 2015 and Pennsylvania Department of Environmental Protection, 2015. Objective 1 The researchers created a demographic profile and cause of crashes for individuals in Pennsylvania from 2011 to 2015. The profile included the total number of injury and fatal crashes, the number and percent of crashes by injury severity (death, major injury, moderate injury, minor injury, and property damage only, injury severity by occupant protection (safety belt, child safety seat, none, other), injury severity by seat position (driver, front seat passenger, second or third row, bus, other), road owner Analysis of Pennsylvania Crash Statistics Data 10
(interstate, state highway, local), the number and percent of crashes by person type (driver, passenger, pedestrian, other), number of vehicles and persons involved, sex (male or female), and injury severity by suspected use of alcohol or drugs. Once a baseline was established, the data were analyzed by age. Age classes of particular importance are young drivers (aged 15 to 20) and older drivers (aged 65 and older) because of their likelihood to be involved in more reportable crashes and more fatal crashes than other age groups. These age classes were defined using the National Highway Traffic Safety Administration s (NHTSA) ity Analysis Reporting System (FARS) data classes. The young driver class starts at 15 since some states have a lower driving age than Pennsylvania. This range was maintained for this study, because the researchers also used the person type field and variable driver to select only young drivers. Data of all crash victims, and, in some cases, of only drivers, were aggregated as follows: ages 0 to 4; ages 5 to 9; ages 10 to 14; ages 15 to 20; ages 21 to 24; ages 25 to 34; ages 35 to 44; ages 45 to 54; ages 55 to 64; ages 65 to 74; ages 75 to 84; and ages 85 and older. Objective 2 This report assessed the impact of the crash s proximity to hospitals, trauma centers, Marcellus Shale gas wells, emergency service providers, local police departments, state police stations, and high responsive local police departments. The researchers used drive-time data from the Pennsylvania Department of Health. These files were used in GIS to create a field with five codes: less than 15-minute drive time; 16 to 30-minute drive time; 31 to 45-minute drive time; 46 to 60-minute drive time, and more than 60 minute drive time. Marcellus Shale gas well location data were from the Pennsylvania Department of Environmental Protection Oil and Gas Reports. Results Statewide - Demographic Profile of and Crashes The following tables and charts comprise the statewide demographic profile for injury and fatal crashes in Pennsylvania from 2011 to 2015. Table 1 shows the total number and percent of injury and fatal crashes from 2011 to 2015. Over this time period, the percent of crashes in rural areas has been Analysis of Pennsylvania Crash Statistics Data 11
slowly decreasing. Each year is within 1 percent of the 5-year average of 71 percent urban and 29 percent rural crashes. Table 1: 2011-2015 Pennsylvania and Crashes by - and Year of Crash Year Percent Percent Statewide 2011 31,743 70% 13,427 30% 45,170 2012 32,026 71% 13,023 29% 45,049 2013 30,518 71% 12,555 29% 43,073 2014 29,745 71% 11,880 29% 41,625 2015 30,502 72% 11,885 28% 42,387 Statewide 154,534 71% 62,770 29% 217,304 Source: Authors calculations from Pennsylvania Department of Transportation data, 2015. As shown in Table 2, 28.9 percent of all injury and fatal crashes occur in rural areas, of which 46.5 percent are fatal crashes and 37.7 percent are major injury crashes. The Pennsylvania Department of Transportation (PennDOT) identifies three types of injury: major, moderate and minor. A major injury is defined as any injury, other than fatal, which by its severity requires immediate emergency transport, such as an ambulance, to a hospital or clinic for medical treatment and/or hospitalization. A moderate injury is defined as any injury that may require some form of medical treatment, but is not life threatening or incapacitating and should be visible. A minor injury is defined as any injury that can be treated by first aid application, whether at the scene of the crash or in a medical facility. Complaints of injuries that are not visible, and do not appear to be of any major or moderate nature, should be considered as minor injuries (PennDOT, 2015). Table 2: 2011-2015 Pennsylvania and Crashes by - and Maximum Severity of Crash, Percent of Maximum Severity of Crash Percent Percent Statewide 3,056 53.5% 2,655 46.5% 5,712 8,387 62.3% 5,077 37.7% 13,464 34,941 68.4% 16,153 31.6% 51,100 108,150 73.6% 38,885 26.4% 147,037 Statewide 154,534 71.1% 62,770 28.9% Source: Authors calculations from Pennsylvania Department of Transportation data, 2015 data. 217,313 Analysis of Pennsylvania Crash Statistics Data 12
As shown in Table 3, a higher percentage of crashes in rural areas than urban areas result in fatalities. Higher percentages of crashes in rural areas than urban areas also result in major and moderate injuries. Table 3: 2011-2015 Pennsylvania and Crashes by - and Maximum Severity of Crash, Percent of Column Maximum Severity of Crash Percent Percent Statewide 3,056 2.0% 2,655 4.2% 5,712 8,387 5.4% 5,077 8.1% 13,464 34,941 22.6% 16,153 25.7% 51,100 108,150 70.0% 38,885 61.9% 147,037 Statewide 154,534 62,770 217,313 Source: Authors calculations from Pennsylvania Department of Transportation data, 2015 data. About 17 percent of all injury and fatal crashes involve occupants who are not wearing any type of restraint. Of these crashes, fatalities were more frequent than injuries in both rural (45.7 percent) and urban (38.3 percent) areas. In about 64 percent of all injury and fatal crashes, occupants used seat belts. Of these crashes, fatalities were less frequent in both rural (2.9 percent) and urban (1.1 percent) areas than major, moderate and minor injuries (See Table 4). Analysis of Pennsylvania Crash Statistics Data 13
Table 4: Pennsylvania and Crashes by -, Maximum Severity of Crash, and Occupant Protection, Percent of Column, 2011-2015 Occupant Protection None used or not applicable 38.3% 29.7% 20.0% 13.2% 45.7% 36.5% 23.5% 15.1% 17.1% Seat belt used 38.1% 45.3% 58.5% 65.3% 41.9% 47.1% 63.7% 75.8% 63.9% Child safety seat used 1.7% 2.1% 2.6% 3.2% 2.4% 3.0% 3.0% 3.5% 3.1% Motorcycle helmet used 4.1% 3.8% 2.4% 0.8% 3.6% 5.8% 4.5% 1.6% 1.7% Bicycle helmet used 0.1% 0.2% 0.2% 0.1% 0.1% 0.1% 0.1% 0.0% 0.1% Improper use 0.3% 0.3% 0.2% 0.2% 0.3% 0.5% 0.4% 0.2% 0.2% Restraint used/type unknown 0.2% 0.3% 0.2% 0.2% 0.0% 0.1% 0.1% 0.1% 0.2% Unknown 17.3% 18.3% 15.8% 16.9% 5.9% 6.9% 4.8% 3.7% 13.7% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. Table 5 again shows that seat belts save lives. In both rural and urban areas, occupants that use no restraint are about four times more likely to be in a fatal accident than those using a seat belt (4.4 percent versus 1.1 percent in urban areas and 10.5 percent versus 2.9 percent in rural areas, respectively). Vehicle occupants that are unrestrained have similar fatality rates to motorcyclists wearing their helmets. Analysis of Pennsylvania Crash Statistics Data 14
Table 5: Pennsylvania and Crashes by -, Maximum Severity of Crash, and Occupant Protection, Percent of, 2011-2015 Occupant Protection None used or not applicable 4.4% 9.7% 27.4% 58.5% 10.5% 15.0% 29.4% 45.1% 100.0% Seat belt used 1.1% 3.8% 20.6% 74.5% 2.9% 5.8% 23.8% 67.6% 100.0% Child safety seat used 1.0% 3.7% 18.8% 76.4% 3.5% 7.7% 23.5% 65.3% 100.0% Motorcycle helmet used 5.5% 14.6% 38.3% 41.7% 6.1% 17.5% 41.3% 35.0% 100.0% Bicycle helmet used 1.4% 6.4% 31.1% 61.1% 6.0% 14.0% 44.0% 36.0% 100.0% Improper use 2.8% 7.6% 23.2% 66.5% 5.5% 14.3% 32.4% 47.9% 100.0% Restraint used/type unknown 1.5% 8.1% 24.0% 66.4% 1.3% 7.5% 23.8% 67.5% 100.0% Unknown 1.9% 5.7% 20.6% 71.7% 6.3% 13.3% 28.3% 52.1% 100.0% 1.8% 5.2% 21.9% 71.0% 4.7% 8.4% 25.6% 61.2% 100.0% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. Drivers make up the highest percentages of fatalities in motor vehicle crashes in both rural and urban areas, followed by front seat passengers. A higher percentage of people that are not passengers or occupants, likely pedestrians or bicyclists, suffer fatalities in a motor vehicle crash in urban areas than in rural areas (See Table 6). Analysis of Pennsylvania Crash Statistics Data 15
Table 6: Pennsylvania and Crashes by -, Maximum Severity of Crash, and Seat Position, Percent of Column, 2011-2015 Seat Position Not a passenger or occupant 9.2% 6.9% 4.4% 2.9% 2.2% 2.1% 0.9% 0.4% 2.8% Driver - all vehicles 61.6% 61.9% 65.8% 66.1% 60.9% 63.6% 66.9% 66.9% 65.9% Front seat middle position 0.2% 0.2% 0.2% 0.1% 0.2% 0.4% 0.4% 0.2% 0.2% Front seat right side 14.3% 14.8% 15.5% 15.6% 15.2% 15.9% 17.4% 16.8% 15.8% Second or third row 9.5% 11.2% 10.7% 11.7% 12.2% 13.2% 11.8% 11.7% 11.5% Bus 3.6% 3.1% 2.2% 2.5% 7.7% 3.1% 1.8% 3.4% 2.7% Other 0.5% 0.5% 0.4% 0.3% 0.9% 1.0% 0.5% 0.3% 0.3% Unknown 1.2% 1.3% 0.9% 0.8% 0.7% 0.5% 0.3% 0.2% 0.7% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. Table 7 shows urban and rural differences in crash severity by road owner. In both rural and urban areas, the highest percentage of crashes with an injury or fatality occurs on state highways, followed by local roads or streets. Table 7: Pennsylvania and Crashes by -, Maximum Severity of Crash, and Road Owner, 2011-2015 Road Owner Interstate - non turnpike 5.6% 3.7% 3.8% 4.4% 6.2% 5.5% 5.2% 6.3% 4.6% State highway 61.8% 55.9% 53.7% 53.5% 73.5% 69.3% 70.1% 69.4% 57.6% County road 0.7% 0.5% 0.5% 0.5% 0.4% 0.4% 0.4% 0.4% 0.5% Local road or street 30.5% 38.7% 40.5% 40.4% 18.5% 23.4% 22.8% 22.0% 35.9% East-West portion of turnpike 0.9% 0.6% 0.7% 0.7% 0.7% 1.0% 0.9% 1.2% 0.8% Turnpike spur (extension) 0.3% 0.3% 0.4% 0.3% 0.3% 0.3% 0.4% 0.5% 0.3% Private Road 0.2% 0.2% 0.3% 0.3% 0.3% 0.1% 0.1% 0.2% 0.3% Other or Unknown 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. Analysis of Pennsylvania Crash Statistics Data 16
In both rural and urban areas, the majority of fatalities and injuries involve the driver (See Table 8). Also, pedestrians make up a larger share of fatalities in urban areas than rural areas. Table 8: Pennsylvania and Crashes by -, Maximum Severity of Crash, and Person Type, 2011-2015 Person Type Driver 64.6% 64.8% 71.1% 72.4% 62.4% 67.2% 73.0% 76.1% 72.2% Passenger 28.0% 28.8% 24.8% 24.9% 35.8% 30.9% 26.0% 23.4% 25.2% Pedestrian 6.6% 5.6% 3.5% 2.3% 1.6% 1.5% 0.6% 0.3% 2.2% Other 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.0% 0.1% Unknown 0.7% 0.6% 0.5% 0.4% 0.2% 0.3% 0.3% 0.1% 0.3% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. The majority of crashes in rural areas involve only one vehicle and the majority of crashes in urban areas involve two vehicles (See Table 9). Table 9: Pennsylvania and Crashes by -, Maximum Severity of Crash and Vehicle Count, 2011-2015 Vehicle Count 1 54.6% 48.9% 40.3% 30.9% 34.5% 57.8% 62.9% 61.7% 59.8% 60.5% 42.0% 2 35.7% 40.8% 47.2% 56.0% 52.8% 36.2% 31.7% 32.9% 35.1% 34.3% 47.4% 3 6.9% 7.3% 9.3% 10.3% 9.8% 4.6% 4.2% 4.3% 4.2% 4.3% 8.2% 4 or more 2.9% 3.0% 3.1% 2.8% 2.9% 1.4% 1.1% 1.1% 0.9% 1.0% 2.3% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. As Table 10 shows, rural injury and fatal crashes by the total number of persons in the crash were more likely to involve only one person. Analysis of Pennsylvania Crash Statistics Data 17
Table 10: Pennsylvania and Crashes by -, Maximum Severity of Crash and Person Count 2011-2015 Person Count 1 26.0% 24.1% 22.3% 18.7% 19.9% 38.6% 39.1% 43.4% 44.4% 43.5% 26.7% 2 40.0% 39.3% 38.7% 38.7% 38.8% 30.3% 32.0% 28.3% 28.1% 28.6% 35.8% 3 17.8% 17.9% 19.7% 21.1% 20.6% 15.1% 14.0% 14.8% 14.0% 14.3% 18.7% 4 7.6% 9.3% 9.4% 10.6% 10.2% 7.8% 7.3% 7.0% 6.8% 6.9% 9.2% 5 4.0% 4.6% 4.8% 5.5% 5.3% 4.0% 3.8% 3.3% 3.2% 3.3% 4.7% 6 or more 5% 5% 5% 5% 5% 4% 4% 3% 3% 3% 5% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. Table 11 shows the difference in injury and fatal crashes by gender. Females are less likely than males to be in an injury or fatal crash. Males are more likely to be in fatal crashes with only slight differences between urban and rural areas. Table 11: Pennsylvania and Crashes by -, Maximum Severity of Crash and Sex, 2011-2015 Sex Female 33.05% 38.71% 44.34% 47.56% 32.74% 35.29% 40.52% 43.25% 44.94% Male 65.49% 60.17% 54.31% 51.09% 66.85% 64.46% 59.14% 56.30% 53.96% Unknown 1.46% 1.11% 1.35% 1.35% 0.40% 0.25% 0.34% 0.45% 1.11% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. About 85 percent of all persons involved in injury and fatal crashes were not suspected of using alcohol or drugs (See Table 12). Analysis of Pennsylvania Crash Statistics Data 18
Table 12: Pennsylvania and Crashes by -, Maximum Severity of Crash, and Alcohol or Drugs Suspected, 2011-2015 Alcohol or Drugs Suspected No 53.4% 71.2% 84.3% 88.9% 58.0% 71.8% 82.8% 87.8% 85.4% Alcohol 10.3% 10.6% 5.7% 3.6% 12.0% 15.0% 9.4% 6.1% 5.5% Illegal drugs 2.1% 2.2% 1.0% 0.6% 2.2% 1.6% 1.0% 0.6% 0.8% Alcohol and drugs 2.8% 1.9% 1.2% 0.7% 2.4% 1.7% 1.5% 1.0% 1.0% Medication 0.9% 0.8% 0.7% 0.5% 0.9% 1.2% 1.3% 1.1% 0.7% Unknown 30.5% 13.3% 7.1% 5.8% 24.5% 8.6% 4.1% 3.3% 6.6% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data, Table 13 shows the distribution of injury and fatal crashes along with the count, area in square miles and population by municipality type by urban, rural and for all of Pennsylvania. About 73 percent of rural municipalities are townships of the second class. These municipalities cover about 98 percent of rural Pennsylvania and include 88 percent of the rural population. Therefore, it is not surprising that about 94 percent of all injury and fatal crashes in rural areas occur in townships of the second class. Analysis of Pennsylvania Crash Statistics Data 19
Table 13: Pennsylvania and Crashes by Municipality Type, 2011-2015 Municipality Type Count % Area (mi 2 ) % Population % & Crashes % First Class Township 92 9.4% 1,066 14.5% 1,558,464 15.7% 24,499 15.9% Second Class Township 286 29.3% 4,835 65.8% 3,095,975 31.2% 53,645 34.7% Borough 543 55.6% 1,014 13.8% 2,198,139 22.1% 24,187 15.7% City 55 5.6% 424 5.8% 3,064,743 30.9% 51,998 33.6% Town 1 0.1% 5 0.1% 14,855 0.1% 205 0.1% 977 7,344 9,932,176 154,534 Municipality Type Count % Area (mi 2 ) % Population % & Crashes % First Class Township 1 0.1% 5 0.0% 2,354 0.1% 19 0.0% Second Class Township 1,168 73.3% 36,688 98.1% 2,442,550 88.1% 59,277 94.4% Borough 423 26.5% 617 1.6% 312,448 11.3% 3,335 5.3% City 2 0.1% 92 0.2% 13,910 0.5% 139 0.2% Town 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1,594 37,402 2,771,262 62,770 Municipality Type Count % Area (mi 2 ) % Population % & Crashes % First Class Township 93 3.6% 1,071 2.4% 1,560,818 12.3% 24,518 11.3% Second Class Township 1,454 56.6% 41,523 92.8% 5,538,525 43.6% 112,922 52.0% Borough 966 37.6% 1,630 3.6% 2,510,587 19.8% 27,522 12.7% City 57 2.2% 517 1.2% 3,078,653 24.2% 52,137 24.0% Town 1 0.0% 5 0.0% 14,855 0.1% 205 0.1% 2,571 44,746 12,703,438 217,304 Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. A higher percentage of injury and fatal crashes in rural areas occur on snow, slush or ice covered roads, and these crashes are more likely to lead to injuries rather than fatalities. Crashes on dry roads are more likely to be fatal in both rural and urban areas (See Table 14). Analysis of Pennsylvania Crash Statistics Data 20
Table 14: Pennsylvania and Crashes by -, Maximum Severity of Crash and Road Conditions, 2011-2015 Road Condition Dry 81.1% 81.8% 79.1% 77.2% 78.0% 76.8% 76.7% 71.7% 65.8% 68.7% 75.3% Wet 14.8% 13.6% 15.4% 16.7% 16.2% 15.1% 13.5% 15.2% 16.6% 15.9% 16.1% Sand/mud/dirt/oil or gravel 0.3% 0.3% 0.2% 0.2% 0.2% 0.5% 1.3% 0.9% 0.6% 0.7% 0.3% Snow covered 1.0% 1.4% 1.8% 2.3% 2.1% 2.4% 3.5% 4.9% 7.2% 6.1% 3.3% Slush 0.6% 0.5% 0.7% 0.8% 0.8% 1.1% 1.2% 1.7% 2.6% 2.2% 1.2% Ice 0.9% 0.7% 1.1% 1.2% 1.1% 1.4% 1.3% 2.0% 2.9% 2.4% 1.5% Ice Patches 0.6% 1.0% 1.2% 1.2% 1.2% 1.7% 1.9% 2.7% 3.4% 3.0% 1.7% Water - standing or moving 0.3% 0.3% 0.2% 0.2% 0.2% 0.4% 0.4% 0.4% 0.7% 0.6% 0.3% Other 0.4% 0.4% 0.3% 0.2% 0.2% 0.6% 0.3% 0.4% 0.4% 0.4% 0.3% Unknown 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. The majority of crashes in both rural and urban areas occur during daylight hours. Not surprisingly, a higher percentage of crashes in rural areas occur on dark streets with no street lights than in urban areas (See Table 15). Table 15: Pennsylvania and Crashes by -, Maximum Severity of Crash and Illumination, 2011-2015 Illumination Daylight 46.8% 57.0% 64.0% 68.9% 66.7% 54.4% 56.2% 61.6% 62.7% 61.5% 65.2% Dark - no street lights Dark - street lights 22.7% 14.0% 10.4% 8.4% 9.5% 37.5% 34.6% 29.4% 28.2% 29.4% 15.2% 26.3% 25.4% 21.8% 19.2% 20.3% 3.4% 4.7% 4.2% 4.4% 4.3% 15.7% Dusk 1.8% 1.6% 2.0% 1.8% 1.8% 2.5% 2.1% 2.2% 1.9% 2.0% 1.9% Dawn 1.7% 1.2% 1.3% 1.2% 1.2% 1.8% 1.8% 2.1% 2.3% 2.2% 1.5% Dark - unknown roadway 0.5% 0.6% 0.4% 0.3% 0.4% 0.2% 0.5% 0.4% 0.4% 0.4% 0.4% lighting Other 0.2% 0.1% 0.1% 0.1% 0.1% 0.2% 0.1% 0.1% 0.1% 0.1% 0.1% Unknown 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. Analysis of Pennsylvania Crash Statistics Data 21
Table 16 shows the percentage of injury and fatal crashes that occur by age group. Higher percentages of rural youth, aged 15 to 24, are involved in moderate and major injury and fatal crashes than urban youth, aged 15 to 24. The highest percentage of those involved in injury and fatal crashes are those aged 25 to 34. Table 16: Pennsylvania and Crashes by -, Maximum Severity of Crash and Age Class, 2011-2015 Age Class ages 0 to 4 1.9% 2.6% 2.5% 3.0% 2.4% 2.4% 2.5% 2.8% 2.8% ages 5 to 9 1.7% 3.1% 2.8% 3.4% 2.1% 2.9% 2.3% 3.2% 3.2% ages 10 to 14 2.3% 2.9% 3.1% 3.6% 3.3% 3.7% 3.4% 3.9% 3.5% ages 15 to 20 11.5% 12.9% 12.3% 12.8% 13.6% 16.9% 16.3% 17.6% 13.8% ages 21 to 24 10.5% 11.4% 10.4% 10.5% 10.0% 11.9% 10.9% 11.0% 10.7% ages 25 to 34 16.4% 18.5% 18.4% 18.0% 15.0% 17.5% 16.2% 16.3% 17.7% ages 25 to 44 1.3% 1.6% 1.5% 1.5% 1.4% 1.4% 1.2% 1.2% 1.4% ages 35 to 44 12.5% 13.1% 13.4% 13.1% 13.1% 12.9% 12.7% 12.2% 13.0% ages 45 to 54 14.0% 13.5% 13.7% 13.2% 14.6% 13.5% 14.3% 12.7% 13.4% ages 55 to 64 11.1% 9.8% 10.4% 9.9% 10.8% 9.2% 10.3% 9.6% 10.0% ages 65 to 74 7.4% 5.2% 5.6% 5.3% 7.6% 4.7% 5.8% 5.6% 5.5% ages 75 to 84 4.9% 2.8% 2.9% 2.7% 5.1% 2.6% 3.1% 2.8% 2.9% ages 85 and older 2.6% 1.1% 1.1% 1.0% 1.8% 0.8% 1.0% 0.9% 1.0% Other 0.0% 0.1% 0.1% 0.1% 0.0% 0.2% 0.2% 0.3% 0.1% Unknown 3.0% 3.0% 3.1% 3.3% 0.5% 0.8% 1.0% 1.0% 2.7% 100% 100% 100% 100% 100% 100% 100% 100% 100% Average Age (in years) 43 38 39 38 40 36 37 36 38 Source: Authors calculations from Pennsylvania Department of Transportation 2015 data. Analysis of Pennsylvania Crash Statistics Data 22
Statewide - Demographic Profile of and Crashes with Proximity Data The research determined if there were differences in injuries and fatalities in terms of the proximity of first responders to crash sites. According to the analysis, crashes in rural areas are more likely to have a fatality, major injury or moderate injury than crashes in urban areas. The largest difference in the percent of fatalities in rural areas comes when comparing crashes near PSP stations and those that are not within 5 miles of PSP stations. There are also notable differences with the proximities of Advanced Life Support Medical Command, Advanced Life Support Squad, and High Responsive Police or PSP Stations (See Table 17). Table 17: Pennsylvania and Crashes by -, Maximum Severity of Crash and Age Class, 2011-2015 Origins: First Responders No Basic Life Support (BLS) 2.9% 7.2% 24.0% 65.9% 100.0% Basic Life Support 1.9% 5.3% 22.5% 70.2% 100.0% No Advanced Life Support - Medical Command 2.6% 6.7% 23.4% 67.3% 100.0% Advanced Life Support - Medical Command 1.9% 5.2% 22.5% 70.5% 100.0% No Advanced Life Support - Squad 2.4% 6.2% 23.1% 68.3% 100.0% Advanced Life Support - Squad 1.7% 5.0% 22.4% 70.9% 100.0% No Pennsylvania State Police Station 2.0% 5.7% 23.3% 69.0% 100.0% Pennsylvania State Police Station 1.8% 4.7% 20.7% 72.9% 100.0% No Local Police 2.7% 6.0% 23.2% 68.2% 100.0% Local Police 1.9% 5.4% 22.5% 70.2% 100.0% Low Responsive Police 2.6% 6.0% 23.2% 68.1% 100.0% High Responsive Police or PSP Station 1.9% 5.3% 22.5% 70.3% 100.0% 2.0% 5.4% 22.6% 70.0% 100.0% Analysis of Pennsylvania Crash Statistics Data 23
Origins: First Responders No Basic Life Support (BLS) 4.5% 8.2% 25.6% 61.6% 100.0% Basic Life Support 4.0% 8.0% 25.8% 62.2% 100.0% No Advanced Life Support - Medical Command 4.4% 8.1% 25.8% 61.7% 100.0% Advanced Life Support - Medical Command 3.8% 8.1% 25.4% 62.7% 100.0% No Advanced Life Support - Squad 4.3% 8.1% 25.8% 61.8% 100.0% Advanced Life Support - Squad 3.7% 8.1% 24.6% 63.6% 100.0% No Pennsylvania State Police Station 4.3% 8.1% 25.8% 61.7% 100.0% Pennsylvania State Police Station 3.3% 7.3% 24.5% 64.9% 100.0% No Local Police 4.3% 7.9% 25.6% 62.2% 100.0% Local Police 4.1% 8.6% 26.1% 61.3% 100.0% Low Responsive Police 4.3% 8.1% 25.7% 61.8% 100.0% High Responsive Police or PSP Station 3.7% 7.8% 26.1% 62.5% 100.0% 4.2% 8.1% 25.7% 61.9% 100.0% Origins: First Responders No Basic Life Support (BLS) 4.1% 8.0% 25.2% 62.7% 100.0% Basic Life Support 2.3% 5.9% 23.2% 68.6% 100.0% No Advanced Life Support - Medical Command 3.8% 7.6% 25.0% 63.6% 100.0% Advanced Life Support - Medical Command 2.1% 5.5% 22.8% 69.7% 100.0% No Advanced Life Support - Squad 3.4% 7.2% 24.5% 64.9% 100.0% Advanced Life Support - Squad 1.8% 5.2% 22.5% 70.5% 100.0% No Pennsylvania State Police Station 2.8% 6.5% 24.1% 66.6% 100.0% Pennsylvania State Police Station 1.9% 4.9% 21.1% 72.1% 100.0% No Local Police 3.9% 7.4% 25.0% 63.8% 100.0% Local Police 2.2% 5.7% 23.0% 69.2% 100.0% Low Responsive Police 3.8% 7.5% 24.9% 63.9% 100.0% High Responsive Police or PSP Station 2.0% 5.5% 22.7% 69.8% 100.0% 2.6% 6.2% 23.5% 67.7% 100.0% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data, Pennsylvania Trauma Systems Foundation, 2014, Pennsylvania Department of Community and Economic Development, 2016, and Pennsylvania State Police, 2016. Analysis of Pennsylvania Crash Statistics Data 24
The research also examined injuries and fatalities in relation to the site of the crash and the end of trip destinations, including hospitals and trauma centers. In all cases, crashes in rural areas are more likely to have a fatality, major injury or moderate injury than crashes in urban areas. The biggest decrease is in rural areas near trauma centers, where the fatality rate decreased from 4.2 percent to 2.2 percent. Trauma centers are a subset of hospitals that have special operations specifically for managing emergency situations (See Table 18). Table 18: Pennsylvania and Crashes by -, Maximum Severity of Crash and Age Class, 2011-2015 Destinations: Hospitals No Hospital 2.7% 6.8% 23.7% 66.8% 100.0% Hospital 1.8% 5.1% 22.4% 70.7% 100.0% No Trauma Center 2.2% 6.0% 23.5% 68.3% 100.0% Trauma Center 1.6% 4.7% 21.4% 72.3% 100.0% 2.0% 5.4% 22.6% 70.0% 100.0% Destinations: Hospitals No Hospital 4.3% 8.2% 26.0% 61.5% 100.0% Hospital 3.7% 7.8% 24.4% 64.1% 100.0% No Trauma Center 4.2% 8.1% 25.8% 61.9% 100.0% Trauma Center 2.2% 6.8% 23.8% 67.2% 100.0% 4.2% 8.1% 25.7% 61.9% 100.0% Destinations: Hospitals No Hospital 3.8% 7.7% 25.2% 63.4% 100.0% Hospital 2.0% 5.3% 22.5% 70.2% 100.0% No Trauma Center 3.1% 6.8% 24.4% 65.7% 100.0% Trauma Center 1.6% 4.7% 21.4% 72.3% 100.0% 2.6% 6.2% 23.5% 67.7% 100.0% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data, and Pennsylvania Department of Health, 2014. Analysis of Pennsylvania Crash Statistics Data 25
Table 19 shows the percentage of injury and fatal crashes according to different travel times to trauma center hospitals. Crash sites that are more than 31 minutes from a trauma center have a higher percentage of fatalities than those within 15 minutes of a trauma center. This supports Pollack et al. (2017 p.336) premise that the Golden Hour for emergency services includes 20 minutes for discovery of the incident and activation of emergency services and 10 minutes for initial assessment and intervention, leaving only about 30 minutes for transport time. Table 19: Pennsylvania and Crashes by Maximum Severity of Crash and Driving Time to Trauma Center, 2011-2015 Trauma Centers 15 minutes or less 1.8% 4.9% 22.0% 71.3% 100.0% Between 16 and 30 minutes 2.9% 6.5% 25.1% 65.6% 100.0% Between 31 and 45 minutes 3.5% 7.6% 24.7% 64.2% 100.0% Between 46 and 60 minutes 4.0% 8.0% 24.3% 63.7% 100.0% Crashes outside 60 minutes 4.0% 8.6% 24.9% 62.5% 100.0% 2.6% 6.2% 23.5% 67.7% 100.0% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data and Pennsylvania Department of Health 2012 data. Table 20 shows the percent of injury and fatal crashes by Marcellus Shale active gas well regions. The column shows the percent of crashes with an injury or fatality that occurred in each region. The southwest and northeast regions with many wells have slightly more fatal crashes in rural areas than the other four regions. Analysis of Pennsylvania Crash Statistics Data 26
Table 20: Pennsylvania and Crashes by -, Maximum Severity of Crash and Marcellus Shale Region, 2011-2015 Person Count 1 Southwest - many wells 2.5% 6.6% 22.4% 68.5% 4.5% 9.5% 24.9% 61.1% 3.4% 2 Northeast - many wells 1.9% 4.8% 19.3% 74.0% 4.8% 7.8% 24.7% 62.7% 2.8% 3 Western - moderate 2.5% 6.5% 22.3% 68.7% 4.3% 8.6% 26.3% 60.7% 13.9% 4 Northwest - limited 2.4% 5.8% 23.6% 68.3% 4.3% 8.1% 25.0% 62.6% 3.8% 5 Southeast - limited 1.9% 5.2% 22.3% 70.5% 4.0% 7.6% 25.8% 62.6% 68.1% 6 Allegheny County - prohibited by 1.6% 5.8% 25.1% 67.5% 3.6% 12.1% 24.6% 59.8% 8.0% ordinance 2.0% 5.4% 22.6% 70.0% 4.2% 8.1% 25.7% 61.9% 100.0% Source: Authors calculations from Pennsylvania Department of Transportation 2015 data and Pennsylvania Department of Environmental Protection 2015 data. Table 21 shows the typical fatal crash profile for selected characteristics for all of Pennsylvania, and for rural and urban areas. The majority of crashes in rural and urban areas have similar characteristics. Differences between rural and urban areas are typically more in magnitude, as illustrated in the earlier analysis of tables. Table 21: Crash Profiles by and Profile of the Typical Crash Profile of the Typical Crash Profile of the Typical Crash (53.5 percent) (100 percent) (100 percent) No seat belt used (41.7 percent) or seat belt used (39.8 percent) No seat belt used (45.7 percent) or seat belt used (41.9 percent) No seat belt used (38.3 percent) or seat belt used (38.1 percent) Driver (63.6 percent) and Driver s seat position (61.3 percent) Driver (62.4 percent) and Driver s seat position (60.9 percent) Driver (64.6 percent) and Driver s seat position (61.6 percent) On a state highway (66.7 percent) On a state highway (73.5 percent) On a state highway (61.8 percent) Dry conditions (79.1 percent) Dry conditions (76.8 percent) Dry conditions (81.1 percent) Daylight (50.3 percent) Daylight (54.4 percent) Daylight (46.8 percent) Involve single vehicle (56.1 percent) Involve single vehicle (57.8 percent) Involve single vehicle (54.6 percent) 2-person crash (35.5 percent) 1-person crash (38.6 percent) 2-person crash (40.0 percent) Male (66.1 percent) Male (66.9 percent) Male (65.5 percent) Age 15-24 (22.8 percent) Age 15-24 (23.6 percent) Age 15-24 (22.1 percent) No alcohol or drugs suspected (55.5%) No alcohol or drugs suspected (58.0%) No alcohol or drugs suspected (53.4%) Analysis of Pennsylvania Crash Statistics Data 27
Table 22 shows crash rates by crash severity per 10,000 population, 100 road miles, and 100,000 vehicle miles traveled by urban and rural. The results indicate that per 10,000 population and 100,000 vehicle miles traveled, crash rates are always higher in rural areas. Crash rates are higher in urban areas per 100 road miles. Table 22: Crash Rates by Crash Severity, Population, Road Miles and Vehicle Miles Traveled by and Per 10,000 population Per 100 road miles Per 100,000 vehicle miles traveled ities 3.1 6.4 1.7 injuries 8.4 17.6 4.7 injuries 35.2 73.4 19.5 injuries 108.9 227.2 60.2 155.6 324.7 86.0 Per 10,000 population Per 100 road miles Per 100,000 vehicle miles traveled ities 9.6 3.7 2.7 injuries 18.3 7.0 5.2 injuries 58.3 22.3 16.7 injuries 140.4 53.6 40.1 226.6 86.6 64.7 Per 10,000 population Per 100 road miles Per 100,000 vehicle miles traveled ities 4.5 4.8 2.1 injuries 10.6 11.2 4.9 injuries 40.2 42.6 18.5 injuries 115.7 122.4 53.2 171.1 181.0 78.6 Source: Authors calculations from Pennsylvania Department of Transportation 2016 data and 2010 United States Census Bureau. Analysis of Pennsylvania Crash Statistics Data 28
Conclusion - Differences According to the research results, 28.9 percent of all injury and fatal crashes occur in rural Pennsylvania, with 46.5 percent resulting in fatalities and 37.7 percent resulting in injuries. areas tend to have a higher share of crashes with major injuries and moderate injuries than urban areas. Also, there are higher fatality rates in rural areas than urban areas when a seat belt or child safety seat is used. In both rural and urban areas: the highest percentage of crashes with an injury or fatality occurs on state highways, followed by local roads or streets; males are two times more likely to be in a crash with a fatality than females; and crashes with a fatality are more likely to not involve alcohol or drugs. About 94 percent of all injury and fatal crashes in rural areas occur in townships of the second class. This result was not surprising since these municipalities cover about 98 percent of rural Pennsylvania and include 88 percent of the rural population. In urban areas, a plurality of injury and fatal crashes occurred in cities and townships of the second class. In both rural and urban areas, crashes on dry roads are more likely to involve a fatality than crashes on roads that are wet, snow covered, icy or slushy. The majority of crashes in both rural and urban areas occur during daylight hours. Not surprisingly, a higher percentage of crashes in rural areas occur on dark streets with no street lights than in urban areas. In both rural and urban areas, the highest percentage of those involved in injury and fatal crashes are those aged 25 to 34. In rural areas, higher percentages of youth, aged 15 to 24, are involved in moderate and major injury and fatal crashes than youth, aged 15 to 24, in urban areas. The research also found that crash sites that are more than 31 minutes from a trauma center have a higher percentage of fatalities than those within 15 minutes of a trauma center. This finding supports the Golden Hour concept for emergency services that includes 20 minutes for discovery of the incident and activation of emergency services, 10 minutes for initial assessment and intervention, and about 30 minutes for transport time. Analysis of Pennsylvania Crash Statistics Data 29
Limitations Study limitations are related to the availability and quality of the data. The Pennsylvania Department of Transportation provides a robust database that was the basis for this analysis. However, the inclusion of a field indicating if the patient was alive when reached by first responders would have been useful for this analysis. These crashes should be a subset for the analysis of first responders and hospitals and trauma centers. Another limitation was defining the crash events by maximum severity. This does not allow for analysis pre-crash and crash features that may have reduced injury, such as seat belt use. Defining crash events by their expected maximum severity, calculated according to vehicle speeds and sizes, would allow for an analysis of features that reduce injury severity. Areas of Future Research This analysis affirms the difference in rural and urban crashes, particularly for fatal crashes, and the importance of the Golden Hour for emergency medical services. Future research examining fatal crashes by themselves, preferably with data showing time of fatality relative to the original call and first responder response, would be worthwhile. In addition, an analysis that looks at origins and destinations together is needed. Analysis of Pennsylvania Crash Statistics Data 30
References Begos, K. and Fahey, J. (2014, May). Traffic Deaths Rise in Fracking Boom: Safety Measures Can t Keep Up with Growth in Population. Associated Press. Retrieved from http://www.durangoherald.com/article/20140505/news03/140509731/traffic-deaths-rise-infracking-boom-. The Center for Pennsylvania. (2014) Demographics Definitions. Retrieved from http://www.rural.palegislature.us/demographics_rural_urban.html. Centers for Disease Control and Prevention (CDC). (2009) Access to Trauma Centers in the U.S. Retrieved from http://www.cdc.gov/traumacare/pdfs/traumacentersfactsheet20090921-a.pdf. Centers for Transportation Safety (A&M). (2015) New Findings: More New Oil and Gas Wells, More Crashes and Costs. Retrieved from http://tti.tamu.edu/group/cts/2015/10/08/new-findingsmore-new-oil-and-gas-wells-more-crashes-and-injury-costs/. Eisele, C. (2008, August). The Golden Hour. Journal of Emergency Medical Services Website. Retrieved from http://www.jems.com/articles/2008/08/golden-hour.html. Federal Highway Administration (FHWA). (2011) Highway Safety Improvement Program Manual The Haddon Matrix. Retrieved from http://safety.fhwa.dot.gov/hsip/resources/fhwasa09029/app_c.cfm. Goodwin, A., Kirley, B., Sandt, L., Hall, W., Thomas, L., O Brien, N., and Summerlin, D. (2013, April). Countermeasures that work: A highway safety countermeasures guide for State Highway Safety Offices. 7th edition. (Report No. DOT HS 811 727). Washington, DC: NHTSA. Federal Highway Administration (FHWA). (2014). Highway Safety Improvement Program (HSIP). (n.d.). Retrieved from http://safety.fhwa.dot.gov/hsip/. Institute of Medicine (IOM). (2006). Emergency Medical Services: At the Crossroads. Washington, D.C.; National Academy Press. Insurance Institute for Highway Safety (IIHS). (2011). ity Facts 2010: Teenagers. Arlington, VA: Author. Retrieved from www.iihs.org/research/fatality_facts_2010/teenagers.html. National Highway Traffic Safety Administration (NHTSA). (2012). Traffic Safety Facts, 2010 Data: Young Drivers. (Report No. DOT HS 811 622). Washington, DC: Author. Retrieved from wwwnrd.nhtsa.dot.gov/pubs/811622.pdf. Analysis of Pennsylvania Crash Statistics Data 31
National Highway Traffic Safety Administration (NHTSA). (2013). Traffic Safety Facts, 2011 Data: / Comparison. (Report No. DOT HS 811 821). Washington, DC: Author. Retrieved from www-nrd.nhtsa.dot.gov/pubs/811821.pdf. Pennsylvania Department of Community and Economic Development (DCED). (2016). Municipal Statistics: Municipal Police Service. Retrieved from http://munstats.pa.gov/reports/reportinformation2.aspx?report=munipolice_excel. Pennsylvania Department of Transportation (PennDOT). (2015) Pennsylvania Crash Facts & Statistics, 2015 Data. Harrisburg, PA. Pennsylvania Trauma Systems Foundation (PTSF). (2014) Pennsylvania Ambulance Services. Retrieved from www.ptsf.org/upload/pennsylvania_licensed_ambulance_services_2014.xls. Pennsylvania Trauma Systems Foundation (PTSF). (2016) What is a trauma center? Retrieved from http://www.ptsf.org/index.php/our-trauma-centers/whats-trauma. Pollak, A. N., Edgerly, D., McKenna, K. D., and Vitberg, D. A. (2017). Emergency: Care and Transportation of the Sick and Injured. Burlington, Massachusetts: Jones & Bartlett Learning. Shults, R. A., and Ali, B. (2010). Drivers Aged 16 or 17 Years Involved in Crashes-United States, 2004-2008. MMWR Morbidity and Mortality Weekly Report, 59(41), 1329-1334. The Henry J. Kaiser Family Foundation (KFF). (2009). Life Expectancy at Birth (in years), by Gender. (2014, May 9). Retrieved from http://kff.org/other/state-indicator/life-expectancy-bygender/?currenttimeframe=0. Analysis of Pennsylvania Crash Statistics Data 32
The Center for Pennsylvania Board of Directors Chairman Senator Gene Yaw Vice Chairman Representative Garth D. Everett Treasurer Representative Sid Michaels Kavulich Secretary Dr. Nancy Falvo Clarion University Dr. Livingston Alexander University of Pittsburgh Stephen M. Brame Governor s Representative Dr. Michael A. Driscoll Indiana University Dr. Stephan J. Goetz Northeast Regional Center for Development Dr. Timothy Kelsey Pennsylvania State University The Center for Pennsylvania 625 Forster St., Room 902 Harrisburg, PA 17120 Phone: (717) 787-9555 www.rural.palegislature.us 1P0517 Analysis of Pennsylvania Crash Statistics Data 33