Report
Using Cost-Effectiveness Analysis to Prioritize Spending on Traffic Safety
Dec 14, 2015
Format | File Size | Notes |
---|---|---|
PDF file | 3 MB | Use Adobe Acrobat Reader version 10 or higher for the best experience. |
Each year, the U.S. federal government provides approximately $579 million to states for traffic safety programs. Although many lives are saved, many are still lost or negatively changed: In 2013, for example, 32,719 Americans were killed and more than 2.3 million were injured in motor vehicle crashes. The direct and indirect costs of lives lost and harmed are typically higher than the millions of dollars spent on prevention: In 2010, for example, crash-related costs reached at least $242 billion.
What if the United States invested just 10 percent more — $57.9 million — in traffic safety? How can the federal government best spend that money to save the most lives for the least cost? Could it save some of those billions of dollars and reduce the pain and suffering of individuals, families, and communities across the nation?
This research brief addresses these questions by taking two approaches:
We base the answers on the data set used to develop the Motor Vehicle Prioritizing Interventions and Cost Calculator for States (MV PICCS), a free-to-use tool to help policymakers prioritize and choose the traffic crash interventions that reduce the number of injuries and deaths for a given budget. The RAND Corporation created MV PICCS with funding and technical support from the Centers for Disease Control and Prevention's (CDC's) National Center for Injury Prevention and Control and the Robert Wood Johnson Foundation. It is available at the CDC website: www.cdc.gov/motorvehiclesafety/calculator.
Cost-effectiveness refers to the benefit of implementing a program or policy and how much it costs the state. The benefit is the value, expressed in dollar terms, of the lives saved and injuries avoided thanks to the intervention. The costs are the costs to the state for such things as extra police time and equipment. The ratio of the two is the cost-effectiveness ratio: The higher the ratio, the more cost-effective the intervention.
MV PICCS contains data on 14 traffic crash interventions (policies and programs) that have been shown to be effective. For a given budget, provided by the user, it selects the interventions that save the most lives and prevent the most injuries for the lowest cost. The two exercises presented in this brief analyze 11 of these policies and programs[1], which are shown in Table 1. In the first exercise, we give each state a 10-percent increase in its traffic safety budget and assess how many interventions it can afford. In the second, we allocate the $57.9 million to the most cost-effective interventions, regardless of state.
Devices that prevent a vehicle from starting until the driver has blown into a tube to prove sobriety
Requires drivers convicted of driving while intoxicated (DWI) to surrender their vehicles' license plates
Photo by lzf/Fotolia
Photo by trekandphoto/Fotolia
Cameras capture images of vehicles with drivers driving in excess of posted speed limits
Photo by carballo/Fotolia
Mandate that children who ride bicycles wear helmets to reduce the likelihood of head trauma and related consequences
Photo by stockpics/Fotolia
Prevent DWI arrestees from diverting cases or pleading out of charges
Cameras capture images of vehicles with drivers who fail to stop for red lights
Requires that a DWI offender's vehicle be confiscated for a period of time, after which the offender either reclaims or surrenders his or her vehicle
Photo by Oleh Tokarev/Fotolia
Requires all drivers over age 70 to renew their drivers' licenses in person rather than by mail or online
Photo by marino/Fotolia
Require all motorcyclists, regardless of age or experience level, to wear helmets that meet safety standards
At specific locations, teams of police officers stop cars to check whether drivers are intoxicated
An across-the-board 10-percent increase in spending on traffic crash interventions (i.e., 10 percent given to each state and the District of Columbia)[2] would fund 51 interventions in 47 states, saving 660 lives and preventing more than 46,000 injuries. Moreover, this positive outcome would cost less than the $57 million allotted to traffic safety in this exercise. The cost of putting these effective new policies and programs in place would come to $28.4 million.
Table 2 shows how many new policies or programs each state would be able to afford and how many lives would be saved with a 10-percent boost in state funding. We do not present numbers related to injury prevention, but those explain why some interventions are still cost-effective despite saving no lives.
State | Number of Interventions | Lives Saved |
---|---|---|
Alabama | 2 | 30 |
Alaska | 1 | 0 |
Arizona | 1 | 3 |
Arkansas | 1 | 0 |
California | 2 | 78 |
Colorado | 2 | 8 |
Connecticut | 1 | 15 |
Delaware | 1 | 2 |
District of Columbia | 0 | 0 |
Florida | 1 | 28 |
Georgia | 1 | 17 |
Hawaii | 0 | 0 |
Idaho | 2 | 8 |
Illinois | 1 | 4 |
Indiana | 4 | 35 |
Iowa | 2 | 15 |
Kansas | 1 | 0 |
Kentucky | 2 | 24 |
Louisiana | 1 | 13 |
Maine | 1 | 4 |
Maryland | 0 | 0 |
Massachusetts | 0 | 0 |
Michigan | 1 | 4 |
Minnesota | 1 | 1 |
Mississippi | 3 | 15 |
Missouri | 2 | 12 |
Montana | 1 | 7 |
State | Number of Interventions | Lives Saved |
---|---|---|
Nebraska | 2 | 3 |
Nevada | 2 | 6 |
New Hampshire | 2 | 4 |
New Jersey | 1 | 10 |
New Mexico | 2 | 13 |
New York | 1 | 18 |
North Carolina | 2 | 48 |
North Dakota | 1 | 4 |
Ohio | 2 | 25 |
Oklahoma | 2 | 15 |
Oregon | 1 | 4 |
Pennsylvania | 1 | 23 |
Rhode Island | 2 | 2 |
South Carolina | 2 | 13 |
South Dakota | 2 | 10 |
Tennessee | 2 | 33 |
Texas | 2 | 37 |
Utah | 2 | 8 |
Vermont | 3 | 3 |
Virginia | 2 | 17 |
Washington | 2 | 10 |
West Virginia | 2 | 5 |
Wisconsin | 2 | 18 |
Wyoming | 1 | 10 |
Total | 78 | 660 |
NOTE: The number of total lives saved does not sum precisely because of rounding. |
How did we come up with these numbers? First, we ranked traffic crash interventions for each state according to cost-effectiveness using the MV PICCS tool. Then, we calculated a 10-percent increase in federal traffic safety funding for each state according to that state's current allotment. If the highest-ranked intervention cost less than the funding available to the state, we put these funds toward supporting that intervention. If money was left over, we then considered the second-most cost-effective policy or program. If the highest-ranked intervention cost more than the available funding, we went to the second-highest-ranked intervention, and so forth. We continued this process until none of the remaining interventions was affordable.
How did we come up with these numbers? First, we ranked traffic crash interventions for each state according to cost-effectiveness using the MV PICCS tool.
As the table shows, four states (shown in red in Table 2) would not be able to spend any of their new funding. The District of Columbia would have only one intervention to implement, which costs more than the 10-percent increase. In Maryland, the only two interventions not implemented currently are limits on diversion and in-person license renewal; each of these exceeds $11 million, the amount that Maryland has available in this exercise. In Hawaii and Massachusetts, each of the interventions available exceeds the modest funding of $385,000 and $846,000, respectively.
In Alaska, Arkansas, Kansas, and Nebraska, funding is available to implement one intervention, but the impact is only on injuries prevented. Vermont and Mississippi can afford three interventions, and Indiana can afford four.
If the federal government were to allocate a 10-percent increase in traffic safety funding to areas where interventions are greatly needed, regardless of state, that increase would have a greater impact than if it were allotted as 10 percent to every state. This is because the type of interventions that can be funded changes quite dramatically. For example, instead of bicycle helmet laws, which are inexpensive but save relatively few lives, the 30 states that do not currently have them can implement universal motorcycle helmet laws, which are more expensive but also much more cost-effective. This intervention alone saves 745 lives.
The national approach allocates more of the hypothetical traffic safety funding increase of $57.9 million. It would cost approximately $57.7 million to create policies and programs in places where they would do the most good, as opposed to the $28.4 million allocated under the state-by-state approach. Yet, even if the federal government took this approach and spent only $28.4 million on the most-needed programs and policies, slightly more lives would be saved: 717, as opposed to 660.
Table 3 shows how many new policies or programs each state would receive and how many lives would be saved if a 10-percent funding boost were applied where it is needed most. Again, we exclude injury prevention.
Allocating the funds to areas where interventions are greatly needed, regardless of state, would have a greater positive impact than if each state receives more funding individually. As Table 3 suggests, however, the national approach results in spending being concentrated in fewer states: 44, as opposed to 47. There are several reasons for this. Four states — the District of Columbia, Maryland, Massachusetts, and Oregon — would not receive new policies or programs essentially because they have very few policies left to implement. Three other states marked in red — Michigan, Nebraska, and Virginia — do not have any potential interventions that exceed a 44-to-1 cost-effectiveness ratio, which ended up being the minimum ratio used in this approach.
State | Number of Interventions | Lives Saved |
---|---|---|
Alabama | 2 | 30 |
Alaska | 1 | 3 |
Arizona | 1 | 27 |
Arkansas | 1 | 24 |
California | 2 | 78 |
Colorado | 1 | 24 |
Connecticut | 2 | 20 |
Delaware | 1 | 2 |
District of Columbia | 0 | 0 |
Florida | 2 | 143 |
Georgia | 1 | 17 |
Hawaii | 1 | 8 |
Idaho | 2 | 12 |
Illinois | 1 | 38 |
Indiana | 4 | 65 |
Iowa | 2 | 27 |
Kansas | 1 | 12 |
Kentucky | 2 | 51 |
Louisiana | 1 | 13 |
Maine | 2 | 10 |
Maryland | 0 | 0 |
Massachusetts | 0 | 0 |
Michigan | 0 | 0 |
Minnesota | 1 | 14 |
Mississippi | 2 | 15 |
Missouri | 1 | 11 |
Montana | 2 | 15 |
State | Number of Interventions | Lives Saved |
---|---|---|
Nebraska | 0 | 0 |
Nevada | 1 | 3 |
New Hampshire | 2 | 10 |
New Jersey | 1 | 10 |
New Mexico | 1 | 11 |
New York | 1 | 18 |
North Carolina | 2 | 48 |
North Dakota | 2 | 8 |
Ohio | 2 | 72 |
Oklahoma | 2 | 37 |
Oregon | 0 | 0 |
Pennsylvania | 2 | 87 |
Rhode Island | 1 | 4 |
South Carolina | 2 | 40 |
South Dakota | 4 | 17 |
Tennessee | 2 | 33 |
Texas | 2 | 150 |
Utah | 3 | 13 |
Vermont | 1 | 1 |
Virginia | 0 | 0 |
Washington | 1 | 6 |
West Virginia | 2 | 23 |
Wisconsin | 2 | 47 |
Wyoming | 4 | 26 |
Total | 76 | 1,320 |
NOTE: The number of total lives saved does not sum precisely because of rounding. |
This exercise shows that, if additional funding were available at the national level to implement motor vehicle crash interventions, the most cost-effective way to allocate the funds would be to target the funding to the most cost-effective interventions regardless of state. This approach is more cost-effective than giving each state a 10-percent boost in funding, but it does not spread the benefit of reduced fatalities across as many states. Policymakers would face an important trade-off between cost-effectiveness and equity between states when considering different ways to allocate an increase in funding.
MV PICCS brings together, in one place, a wealth of information on the costs and effects of 14 traffic crash interventions. Users can change a variety of parameters: the state, the interventions to analyze, the type of analysis (looking at each intervention individually or using "portfolio analysis" to account for related interventions), the use of fines and fees to offset costs, and the budget. A built-in sensitivity analysis tool allows changes to the percentage reduction in injuries and deaths, the estimated monetary value of saving a life, and the total cost per intervention.
This report is part of the RAND Corporation Research brief series. RAND research briefs present policy-oriented summaries of individual published, peer-reviewed documents or of a body of published work.
This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.
The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.