ther than injury and illness esti- mations, it is uncertain how relevant an ideal classification system might be in practice.
1 National Occupational Research Agenda Agricultural, Forestry, and Fishing Sector Council, National Agriculture, For- estry


States, with most cropland on farms of at least 1,100 acres and many farms five and ten times that size.8 Clearly, the trend in U.S. agricultural production has been to shift away from small farms to very large farms and nonfamily farms. Consequentl


e farmwork- ers’ vulnerability, the panel report recommended focusing on hired farmworkers as a priority for surveillance efforts. Action 3.1 addresses this recommendation.
Action 3.1. Collaborate with the NAWS to field supplementary modules on occup


an injury module to be added to the NAWS for a three-year period. The prior interagency agreement specified a sample size of 1,500 at a cost of approximately $700,000. We assumed that an increased sample size would be required in future years to gene


yed in any occupation on a farm owned or operated by their parents (or people standing in place of their parents).13 Given their engagement in farm operations and lower experience or skill level, children in agri- culture may face the same hazards af


gricultural Workers: Assessment of Recommendations and Actions
Capability partners: This action pertains specifically to partnership with USDA on the CAIS. Because NIOSH does not itself administer the survey, USDA retains the capabilities necessary f


echanisms, and data processing techniques. Because the CAIS is based on NASS survey procedures, the col- lected data are considered to be high quality.
Action impacts: Improved representativeness would increase the utility of CAIS data; however, ther


 collected if resources are provided. Overall, data are technically available and acces- sible, but there are resource barriers to actually obtaining the data.
Policy: Interagency agreements may require lengthy lead time and coordination to accommoda


ssed for their utility in injury and illness surveillance for agricultural worker populations (e.g., federal agricultural and occupa- tional health surveys, state occupational health surveillance systems, trauma registries, death registries, claims d


ons would be made for improvements and a strategy forward. See Table 5.5.
Resource partners: Potential partners for this action may include institutions that cham- pion certain data sources for broad-based use, such as NIOSH’s CWCS. Workers’ compen-


r information. The high-end estimate includes the low-end estimate tasks and, in addition to the evaluation, would involve obtaining data from the most-promising sources. This would enable a comparative analysis of injury and illness estimates, and t


ultural worker safety and health risks
NIOSH has traditionally used grouped five-year age cohorts for children and youth (e.g., younger than ten, ten to 14, 15 to 19). The 15–19-year-old aggregation, however, includes individuals who would not be sub


e needed data, different kinds of analyses could be performed. Therefore, given the uncertainty regarding how this action might
Table 5.6
Action 6.1’s Implementation Plan
Overall
Action Mechanism Resource Partner Capability Partner Resources Timeline


tely developed and tar- geted. NIOSH has released demographic data indicating whether children are hired or unpaid (family members).24 According to NIOSH, it would be difficult to release existing data on children who are self-employed, given the sma


ion). Reports that lack details on these con- texts limit the ability to accurately define vulnerable groups and identify potentially hazard- ous work settings. Including these descriptions in reports will enable optimal comparability of surveillance


s action.
Program surveillance goals and priorities: NIOSH AgFF Program leadership consid- ered this action to be an important priority.
Information quality: The ability to carry out this action depends on the overall qual- ity and completeness of th


develop means for data- sharing and communications).
Cost and resources: Ongoing partnership development will result in uncertain costs, so we do not present fixed estimates. Internal NIOSH resources should be expended to develop a strategy, however,


ns for human health (zoonosis, water contamination, and other environmental changes). In addition to sug- gesting that NIOSH monitor the impact of these new systems on health and safety, the panel recommended that the NCC monitor developments and dev


n availability and accessibility: Alternative animal production systems are relatively new and evolving rapidly. There are hypotheses—e.g., increased risk of zoonotic dis- eases from so-called free-range livestock—about the potential injuries and ill


ls and priorities, information quality, and action impacts.
Overall, we found that direct-action and extramural funding mechanisms tended to show higher overall achievability than did actions that depended on partner capabilities for imple- mentation


y
8.1: Partner for zoonotic disease
Mechanism Cost per Year
a Duration Achievability Feasibility Desirability
(years) Score
Score Score
4.20 3.67
3.60 4.67
3.40 4.67
3.20 4.00
3.20 3.67
3.00 3.33
3.00 3.33
 EXF $150K
$170K 1
EXF $175K
$160K 5
PART $1


00 (1.1)
 $2,000,000 (4.2, 8.1)
       Desirability
5.0
4.5
4.0
3.5
3.0
2.5
2.5 3.0 3.5
 Feasibility
NOTES: Cost estimates are shown for the satisfactory version of the action. Action 8.1 had the same feasibility and desirability scores as action 4.2


acts. Action items will need to be evaluated individually to ascertain whether the ideal version would need to be implemented. For instance, to properly evaluate the potential value of exist- ing data sources for injury and illness surveillance (acti


ons based on average desirability score are the following:
• 3.1: Collaborate with the NAWS to field supplementary modules on occupational health outcomes among hired farmworkers and perform specific analyses on variability of risk.
• 4.1: Improve th


orkers within these systems.
Each of these actions would be achieved through a partnership mechanism and, therefore, tended to have lower feasibility scores. In particular, each of these three actions had a low score (2) in the category of informatio


validity of the CAIS PART 4.2: NAWS, child injury survey PART 8.1: Partnerships for zoonotic disease PART
NOTE: EXF = extramural funding; PART = partnerships.
Estimated Total Cost
$150K $250K $350K $350K
$500K
$800K ~$1 million
—
— ————
 Version
Sati


rred in spite of challenges that the program has faced in instituting a comprehensive agricultural injury and illness surveillance program over the years. These challenges include the diversity of the agricultural industry itself; changing injury and


addition, NIOSH could choose to pursue one or two actions that are considered highly impactful but also high in cost and low in feasibility. Resources would be targeted to building partnerships or gather- ing the resources necessary to enhance the f


Fishing Safety and Health Research (U01),” funding opportunity announcement, April 10, 2014. As of March 10, 2016: http://grants.nih.gov/grants/guide/pa-files/PAR-14-175.html
Department of Labor, Child Labor Requirements in Agricultural Occupations U


 “A Proposed Classification Code for Farm and Agricultural Injuries,” American Journal of Public Health, Vol. 83, No. 5, 1993, pp. 736–738.
National Children’s Center for Rural and Agricultural Health and Safety, “National Children’s Center for Rural


dc.gov/niosh/topics/aginjury/naws/
———, “Agricultural Safety: National Agricultural Workers Survey (NAWS); Hired Crop Worker Injury Rate Tables,” web page, last updated May 12, 2017. As of August 30, 2017: http://www.cdc.gov/niosh/topics/aginjury/naw


ewDocumentInfo.do;jsessionid=F154BA78C7C50C021C8CA9 24EDB72FD5?documentID=1063
———, 2007 Census of Agriculture: U.S. Summary and State Reports, Vol. 1, Washington, D.C., 2009. As of March 10, 2016:
http://www.agcensus.usda.gov/Publications/2007/Full_


  For more information on this publication, visit www.rand.org/t/RR1775-1
 Library of Congress Cataloging-in-Publication Data is available for this publication. ISBN: 978-0-8330-9793-4
Published by the RAND Corporation, Santa Monica, Calif. © Copyrig


Maltreated children fare worse than their peers on many important outcomes within these domains. The effects can persist and have long-term consequences into adulthood, including reduced labor market productivity, increased involvement with the crim


o young adulthood, manifested in numerous ways, including home- lessness, underemployment, criminal conviction, and substance abuse. Overall societal costs associated with child maltreatment may total $80 billion annually (Gelles and Perlman, 2012).


ion lead to decreases in mal- treatment and improvements in young adult outcomes but do not affect the experiences of children who enter the system and result in small additional costs. Increases in treatment lead to improvements in system experience


t events
in the model (e.g., maltreatment, referral to the system, placement in foster home). The baseline model, therefore, is intended to represent the current situation. We then used the model to assess the average effects relative to baseline of


the child welfare system, whether to emphasize in-home options or out-of-home placements.
What Effects Do Individual Policies Have?
To understand the effects of individual policies, we estimated how
the quantity and quality of preventive services, fa


s in the model, such as the Nurse-Family Partnership, have been shown to have a number of positive benefits for children and families beyond reducing the likelihood of maltreatment (Olds, 2006). These benefits include improved infant and child health


reservation efforts led to changes in the young adult outcomes, with the largest changes when both quantity and quality of the policy were increased. The effects ranged from 0.4 to –9.8 percent for substance abuse, from –3.6 to –11.2 percent for crim


that we considered achieves all these objectives.
We estimated the effect of a policy package that combined increases in preventive services and treatment in the form of support for kinship care. The results are summarized as a range for this combine


ystem and their outcomes in young adulthood. Family preservation and kinship care efforts also lead to reductions in the overall cost of the system because they promote placements that are less costly than the other options (foster care or residentia


mber of important improvements, including more-specific informa- tion on pathways through the system; better data on children’s experiences in the system; and information on how the child welfare system interacts with other related systems, such as e


hly engaged and provided invaluable input throughout the entire process. We are particularly grateful for her assistance in identifying and connecting us with experts to provide input into the model.
Susan Gates, director of RAND’s Office of Research


m et al., 2017) and lifetime substantiated maltreatment at 12.5 percent (Wildeman et al., 2014). Child maltreatment has been linked with child and family characteristics, such as a child’s age, race/ethnicity, gender, and special needs status (Sedlak


protec- tive and negative effects of the child welfare system are intertwined with the effects of the maltreatment itself, making it difficult to sepa- rate them when looking at outcomes (Masten and Wright, 1998).
Over time, the effects of maltreatme


a mix of state and local funding (DeVooght and Cooper, 2013). This total likely does not include funding for all child maltreat- ment preventive services. The survey that generates these estimates asks about funding for these services provided at th


el that estimates the average effect of implementing the policy in all jurisdictions across the country. To simulate the effect for a particular state or locale, the model assump- tions and data would need to be changed to better reflect the populati


tment and detection component of the model until he or she leaves childhood.
System Pathways
The child welfare system pathways component of the model represents the possible pathways through the child welfare system for a child whose suspected maltre


of risk and protective factors ultimately influence how children fare over time. The outcomes are influenced by the circumstances that led to the maltreat- ment itself and, to some extent, the involvement with the child wel- fare system. At the same


stimate the effect of implementing several different policy, program, or practice changes.
These steps are briefly described below and in greater detail in Appendix B, available on the project website (www.rand.org/ child-welfare-model).
Step 1: Lite


as poverty rate.1
To simulate the experiences of these children, we had to determine their chances of experiencing each of the many child welfare events and/or outcomes in our model. We pooled information from admin- istrative data, survey data, agen


thood: underemploy- ment, homeless- ness, criminal conviction,
and substance abuse.
and Foster Care Analysis and Reporting System (AFCARS) 2013 data set,
as well as AFCARS reports 18–22. We also reference the National Survey
of Child and Adolescent W


he outcomes model, we estimated the consequences of these childhood experiences on the odds of four kinds of negative life outcomes in early adulthood:4 un-
3 A typical goal for calibration is to get model outputs that are within the natural variance


n how both risk and protective factors interact and the uncertainties about the causal pathways. However, it allows for an understanding of how child maltreatment and system involvement affect outcomes into young adulthood and beyond.
Step 7: Simulat


ltreatment (e.g., neglect and physical abuse); the estimates have been adjusted to account for this.
Efforts to prevent maltreatment will also occur during this period. Collectively, our model estimates that prevention efforts, such as home visiting


is made about whether a child will be kept in the home or placed in out-of-home care.
Lower-risk cases are generally provided in-home services and sup- ports, such as family preservation, parent education, safety planning, and counseling, or are refe


 in 2016 dollars. As recommended by the National Academies of Sciences, Engineering, and Medi- cine (2016), we apply a discount rate of 3 percent to account for future costs.
6 Homelessness is defined as spending at least one week as an individual wh


eavy drinking, defined as typically consuming five or more drinks three times per week, and drug use, defined as use within the past year of cocaine, amphetamines, hallucinogens, or heroin, but not tobacco, marijuana, or prescription drugs.
  19
Belo


pproaches, home vis- iting is the most widely studied. A number of assessments have found associations between prevention approaches and reductions in the risk factors for child maltreatment. However, the evidence for reductions in child maltreatment


e services lower maltreatment by 42%
 A: Increase quantity
50% increase in preventive services
Same as baseline (preventive services lower maltreatment by 30%)
  C: Increase both quantity and quality
50% increase in preventive services
Preventive ser


 Detection, Percentage Change from Baseline
Scenario A –0.2%
Maltreatment episodes
Referrals to child welfare
RAND RR1775x1-4.3
Scenario B –0.3%
Scenario C –0.6%
       –1.4%
provided by other agencies or community-based organizations may not be incl


entive services would reduce lifetime referrals by 0.6 percent relative to baseline.
System Pathway. With fewer overall referrals, fewer children enter and flow through the system (Figure 4.4). In Scenario A, which increases only the quantity of prev


he system. Across all the young adult outcomes, reductions range from 3.4 to 3.6 percent.
–1.6%
–1.5%
–1.6%
–1.6%
–3.5%
–3.4%
–3.6%
–3.6%
 25
Family Preservation Services
Family preservation programs are designed to prevent out-of-home placements or


eipt of supports and services for transition to adulthood
 A: Increase quantity
10% increase in number of in-home placements;
10% increase in family preservation services
Same as baseline
 C: Increase both quantity and quality
10% increase in number


tion services are implemented significantly affects how children fare in terms of subsequent maltreat- ment and detection.
In our quantity scenario (A), the average number of maltreatment episodes increased 2 percent. The number of referrals for malt


 quantity of family preservation services
 29
 FIGURE 4.9
Effects of Family Preservation Scenarios on Costs, Percentage Change from Baseline
+0.2%
Scenario A
Scenario B
Scenario C
       –9.9%
–9.1%
–6.7%
–6.2%
–13.7%
–12.7%
   Prevention spending
Ch


s themselves, home visiting, mentoring, counseling, respite care, and legal services (Lin, 2014). How and where services are offered varies significantly (for example, they can be peer to peer, provider-led, school-based, or community-based). Trainin


ys through the system and have
11 These services cumulatively reduce the risk of underemployment, substance abuse, criminal conviction, and homelessness by 31, 39, 47, and 73 percent, respectively.
  32
 FIGURE 4.11
Effects of Kinship Care Scenarios


kinship care in the model (Table 4.4). The first, which focuses on quantity, results in a 50-percent increase in the quantity of funded preventive services and in the number of children placed with kin (Scenario A). The second option focuses on qual


rio C will reduce referrals by 0.6 percent.
System Pathway. Under the combined prevention and kinship care approach, increasing quantity will result in small decreases in investiga- tions (–0.3 percent) and substantiations (–1.3 percent) and an 8.3-p


D RR1775x1-4.15
 FIGURE 4.16
Effects of Combined Approach of Prevention and Kinship Scenarios on Outcomes, Percentage Change from Baseline
Scenario A
Homelessness Underemployment Substance abuse Criminal conviction
RAND RR1775x1-4.16
Scenario B
Scena


e options that intervene at different points in the system and have been discussed by policymakers. The options work in different ways. Preventive services are designed to prevent child maltreatment from occurring and thus reduce the number of childr


er workforce participation, and less reliance on public assistance.
Increasing preventive services requires new expenditures to provide services to more children. The increase is partially offset by reductions in spending on screenings, investigation


system. Rather, for children who require a temporary out-of-home placement, the option seeks to increase the proportion placed with kin and provide services and supports to the kin caregivers to ultimately decrease time in care and increase the child


objectives.
Limitations
Our approach has several limitations. The model provides a simplified representation of the child welfare system, which is extremely com- plicated. Building such a model requires many assumptions. In many cases, the available


nt with arguments that AFCARS under- represents children who move between many temporary placements and age out instead of finding a permanent placement. However, it is difficult to say how much of the discrepancy represents real differences in the s


hway through the child welfare system. Moreover, there is very little evidence that can help to disentangle the effects of maltreatment from the effects of system experience on outcomes. To address this problem, we augmented the information we found


implement are made at the state and local levels, so a jurisdiction-specific model is likely more valuable for informing specific policy decisions. Adapting the model to specific jurisdictions would allow a number of import-
ant improvements, includi


s of the child welfare system
or subpopulations of children or families, this is the first attempt to integrate maltreatment risk, detection, pathways through the system, and consequences in a comprehensive quantitative model that can be used to simu


 Department of Health and Human Services, 2013.
Courtney, M., A. Dworsky, J. Lee, and M. Raap, “Midwest Evaluation of the Adult Functioning of Former Foster Youth: Outcomes at Age 23 and 24,” Chicago, Ill.: Chapin Hall at the University of Chicago, 2


y Connection Discretionary Grants, 2009-Funded Grantees Cross-Site Evaluation Report, Arlington, Va., 2013.
James Bell Associates, Profiles of the Active Title IV-E Child Welfare Waiver Demonstrations, Arlington, Va., 2016.
Jones Harden, B. J., “Safe


t, Saint Paul, Minn.: Wilder Research, 2012.
Olds, D. L., “The Nurse–Family Partnership: An Evidence‐Based Preventive Intervention,” Infant Mental Health Journal, Vol. 27, No. 1, 2006, pp. 5–25.
Olds, D. L., J. Eckenrode, C. R. Henderson, Jr., H. Kit


tration on Children, Youth and Families; Children’s Bureau, Child Maltreatment 2014, Washington, D.C., 2016.
Washington State Institute for Public Policy, Intensive Family Preservation Programs: Program Fidelity Influences Effectiveness— Revised, Oly


 JUSTICE, INFRASTRUCTURE, AND ENVIRONMENT
Access to Medical
Treatment for Injured
Workers in California
Year 1 Annual Report
Andrew W. Mulcahy, Madeline B. Doyle, Rosalie Malsberger, Kandice A. Kapinos
For more information on this publication, visit


ct to peer review and disseminated widely to policymakers, practitioners in law and business, other researchers, and the public.
ICJ is part of RAND Justice Policy within RAND Justice, Infrastructure, and Environment, a division of the RAND Corporati


rocesses might have affected the decisions of some providers in terms of their interaction with WC patients and the WC system. Although this report is not an evaluation study of the direct impact of these changes, it is important to assess the variou


experience (e.g., receipt of guideline-concordant care, aspects of obtaining an appointment and wait times, referral patterns). Finally, outcome measures reflect whether appropriate care was received and, ultimately, whether health was improved. Ther


ative data offer an important but limited window into access to care for injured workers. These data can be used to calculate a range of measures related to access to care for injured workers, such as the number of providers who treat injured workers


ges in WCIS data completeness. We also note that adjusting for multiple comparisons results in a loss of statistical significance for some of these trends.
• We found an increase in the average number of claims per provider from 2010 to 2014 (from 47


ge in physician incentives through the transition to a new resource-based relative value scale (RBRVS) fee schedule for practitioner services as part of SB 863 changes, or some other factor. Further research is needed to investigate whether these red


rage number of PCPs seen in the year following injury fell slightly, from 1.24 to 1.21, and was relatively similar across injury types.
Pathways of Care
We examined “pathways of care,” defined by the initial visit setting and provider type and up to


r are related to, access to care for injured workers. In future reports, we will explore other measures, including provider-based measures and measures based on the network of providers. RAND is also separately conducting a study on the effect of the


care and indemnity (e.g., wage-replacement) benefits to workers who suffer on-the-job injuries and illnesses. Injured workers are entitled to receive all medical care reasonably required to cure or relieve the effects of their injuries with no deduct


Group, 2015). Although this report is not an evaluation study of the direct impact of any specific policy or other change, it is important to assess the various dimensions of access to care in the evolving policy environment to ensure that injured wo


ating in the WC system and an analysis of MPN listings.
 2
Organization of This Report
This report describes the access measures that we implemented in our monitoring analyses. There are three sets of interrelated analyses. The first set focuses on p


Healthcare Quality and Research has devoted significant resources to better measurement (e.g., through the National Quality Measures Clearinghouse). Measures are often differentiated across three key elements: structures, processes, and outcomes (Do


s, there are limits to the extent that outcome and structural measures related to access can be calculated from these data (Berenson, Pronovost, and Krumholz, 2013).
There are several congressionally mandated access studies about the California WC sy


, when they saw them, and what kind of treatment or other health care services was provided. This information can be used to construct a map—or a pathway—to illustrate how an injured worker interacted with providers over time and may better reflect t


hom the length of time between each visit was fewer than 31 days.
7
Figure 2.1. Pathway Framework
   8
3. Data and Methodology Overview of Approach
This report includes analyses of WCIS data to examine medical treatment provided from 2010 through 201


entifier (NPI)—during our study. The NPI can yield more-accurate counts of practitioners than TINs because each practitioner is assigned a unique NPI. The NPI field was, however, missing for many providers during our study period; as a result, we do


 with one or more of the qualifying visits within 12 months of injury. We define the first visit as
• an E&M visit with any provider: This measure is defined as the number of days from injury to the earliest visit date in any setting
• a non-ED E&M v


jured workers. We cannot disentangle changes in the number of TINs over time caused by consolidation from decisions to treat or not to treat injured workers.
There are more-general limitations to using the WCIS medical data. First, not all WC claims


2014, only about 1.5 percent of the claims were with out-of-state providers, but this varied from year to year, ranging from 1.5 percent in 2013 and 2014 to 5.8 percent in 2008. For these claims, the median time between the injury date and first E&M


ight increase using American Medical Association data and a slight decrease using Medical Board data (Coffman, Geyn, and Fix, 2017).
 14
Figure 4.1. Trend in Number of Providers Serving WCIS Patients
SOURCE: Analysis of WCIS data from 2010 to 2014.
N


combined psychiatry and behavioral health into behavioral health because of overlap in specialty. Results reported here are similar when comparing the disaggregated means.
 16
Trends in the Number of Claims per Provider
In Table 4.2, we present the n


lts that are qualitatively similar to those reported in Table 4.6.
This analysis can identify changes over time in the mix of services utilized by injured workers, which may reflect changes in access. However, other changes, such as changes in clinic


s
E&M
Medicine Laboratory/pathology Radiology
Surgery
Outpatient facility services
Anesthesia
DME
Prosthetics/orthotic devices
Other/unknown
Inpatient hospital stays
Number of Injuries (denominator)
2010
174.47** 439.99** 503.08** 25.86** 175.59** 18


 Observations for Timeliness of Care Analysis, by Injury Year and Body Part or Condition
             All Injuries
Low-back pain
Shoulder injuries
Knee injuries
Upper-back and neck injuries All other injuries
2010
261,747 44,755 19,012 12,110 7,999 1


t wait times increased more for shoulder, knee, and upper-back and neck injuries regardless of setting or provider. In any setting, median wait times for those injuries to have an E&M visit anywhere (even with ED visits excluded) increased from 3 day


n Analysis, by Injury Year and Body Part or Condition
8
  76543210
Northern Region Southern Region Out of State Unknown 2010 2011 2012 2013 2014
                         All injuries
Low-back pain
Shoulder injuries
Knee injuries
Upper-back and neck i


r injuries Knee injuries Upper-back and neck injuries
All other injuries
1.21 1.21 SOURCE: Analysis of WCIS data from 2010 to 2014.
1.24* 1.20* 1.18
* Means in 2010–2013 are statistically significantly different from the 2014 mean in the same injury


 stable wait times—two to three days with non-PCPs and three to four days with PCPs—over the period of our study.
There was little geographic variation over time, with slightly shorter wait times in the southern regions. Injured workers who lived out


n Table 6.2, we present the median number of days between injury and first visit (branch 1). Overall, there was little change in wait times across the different pathways over time, with most median waits between 0 and 1 days. However, the time from i


did so four to five days later, with either a PCP or HOPD visit or a visit in another setting (pathways 4 and 5). The second follow-up (third branch) for injured workers who were first seen at a PCP visit tended to have the third visit within six to


the most common. Patterns are similar using earlier years of claims data.
We also examined row percentages to understand, within a given pathway, which injury was most common (Table 6.7). Not surprisingly, the “other” injury category comprises the ma


the ED are likely to have more encounters overall. However, among those who first saw a PCP for an E&M visit, then a specialist, and who then followed up again with a PCP (pathway 7), 99 percent saw more than one PCP in a year. On average, injured w


ician’s office or HOPD. This was relatively stable over time.
The second visit for care was most often with a specialist or nonspecialist, with a third visit with a PCP. Having the first visit in an ED occurred in only about 10 percent of injuries, w


pists (increased by 554 providers) and other (increased by 670 providers).
Fewer providers does not necessarily mean less access, however, if there was inappropriate care in earlier years. Studying this was beyond the scope of our analysis.
Utilizati


jury
Improving or declining access to care among injured workers could result in changes in the observed volume of or payments for services, particularly in the first year after injury.
For most service categories, utilization within 12 months of inj


investigation, we do not know whether these are primarily first aid visits, for which no billing was generated, or whether there was underreporting of initial medical visits.
We also note that the measures of access to care that we examined are not e


to require that the Doctor’s First Report of Occupational Injury or Illness be filed electronically with DWC. In addition, the Labor Code was revised to require DWC to develop a system for electronic reporting by employers of documents related to ut


94 16,240 9,476 6,259 126,101 193,270
2014
43,921 20,305 11,437 7,758 159,450 242,871
Total
SOURCE: Analysis of WCIS data from 2010 to 2014.
 48
Table A.3. Number of Observations for Timeliness to Care—First Non-ED E&M Visit, by Injury Year and Natur


an Workforce Data Book, Washington, D.C., November 2011. As of August 21, 2018: https://www.aamc.org/download/263512/data/statedata2011.pdf
———, “California Physician Workforce Profile,” 2015. As of August 21, 2018: https://www.aamc.org/download/4471


-
 hospital-settings-than-in-other-clinical-locations
 Donabedian, A., “Evaluating the Quality of Medical Care,” The Milbank Memorial Fund
 Quarterly, Vol. 44, No. 3, 1966, pp. 166–206.
 Haddad, S., and K. Mohindra, “Access, Opportunities and Communi


, Workers’ Compensation: Benefits, Coverage, and Costs, Washington, D.C., October 2017. As of August 17, 2018: https://www.nasi.org/sites/default/files/research/NASI_Workers%20Comp%20Report%2020 17_web.pdf
Care Consumption,”
2018:
55
, May 2015.
 Pet


  CORPORATION
A Community-Based, Focused-Deterrence Approach to Closing Overt Drug Markets
A Process and Fidelity Evaluation of Seven Sites Jessica Saunders, Allison J. Ober, Beau Kilmer, Sarah Michal Greathouse
For more information on this publicati


their experiences. It should be of interest to decisionmakers considering new approaches to addressing overt drug markets and those assessing whether this intervention affected crime and other outcomes in these jurisdictions.
The RAND Justice Policy


hese efforts.
BJA originally had planned to support the training of 12 sites across two training cohorts of six sites each; however, there was much less demand for the training than anticipated. The training and technical assistance (TTA) providers e


vations they developed, barriers they encountered, and how well the sites adhered to the BJA model they were exposed to during the training (i.e., fidelity). Process evaluation data collection occurred primarily from March 2011 through April 2012 (so


ed and recruited individuals to fill each of the recommended four core roles on the team. During the planning phase, teams varied in how regularly they met, ranging from weekly to monthly. Barriers in the planning phase included difficulty in transla


e and heal damaged relationships. Sites employed a combination of activities to engage community members in the intervention, including community meetings, meetings with community leaders, community events, developing and administering community surv


continues to communicate with the community personally or through newsletters, meetings, etc., and follow up with the B-listers to ensure that they are not reoffending. Second, on the community side, community members organize and exert their own in


rtment, there were challenges because it was initiated at the managerial level; as a result, team members were hesitant to act because they were unsure of support from police department leadership. The Lake County initiative ultimately failed because


ffice and the Gary Police Department. During and after the transition, the team stalled and was not able to move forward with completing the targeting phase. In New Orleans, scandals within the police department led to a change in leadership. During


and Heather Perez. Also, we would like to acknowledge former team members Robert Davis and Greg Ridgeway, who worked on this piece, and Jim Burgdorf and Russell Lundberg for contributing to the literature review. Additionally, we would like to exten


on with police enforcement activities (Caulkins, 1993). In response to these challenges, another approach to addressing overt drug markets has been to implement a drug market intervention (DMI).
The goals of the DMI approach—borrowed from the “pullin


d Wong, 2009). After the call-in, the DMI team facilitates community mobilization and the formation of strong informal social control, such as formation of neighborhood watch groups and other activities that serve to lower tolerance for drug-dealing


o attend the training sessions; sites were not provided with any additional funding for implementation.
Figure 1.1. Evaluation Logic Model
 Program Elements Short-Term Intermediate Long-Term Inputs Outcomes Impact
       Preparing for the Interventio


aluation, including the study settings and the methods used. Chapters Four through Eight present the results of RAND’s process evaluation for each of the five phases, and Chapter Nine presents a discussion of our findings and implementation lessons l


at reducing drug crimes and eliminating drug markets, and, if these methods were effective, whether they were worth their cost in terms of community disruption and the damage to policy-community relations
(Sherman, 1998; Aitken et al., 2002). Some ar


Furthermore, retailers innovated with new forms of distribution that made cannabis dealing more visible in other areas of the city while market participants engaged in violent struggles for market share.
Kennedy and Wong (2009) note that typically af


 punishment and deter crime (McGarrell et al., 2006).
Another key insight in the development of new deterrence approaches is that a large portion of crime is committed by a small number of persistent offenders whose habits may be known and potentiall


nnedy, 2009) who are determined not to tolerate overt drug dealing and help prevent it from reoccurring (McGarrell, Corsaro, and Brunson, 2010). To improve the relationship between law enforcement and the community, the DMI involves an effort to exam


ommunity, while the police and prosecution maintain the evidence against the B-listers and obtain unsigned arrest warrants to be used as leverage to encourage the B-listers to stop dealing drugs.
• Phase III, which is concurrent with Phase II, involv


age to the B-listers and non-DMI–involved potential replacement dealers. During this time, the police develop a relationship with the community, demonstrating their commitment to improving the quality of life and preventing the overt market from re-e


ion with law enforcement and internal motivation to comply with the law (Hawdon, Ryan, and Griffin, 2003; Lind and Tyler, 1988; Meares, 2000; Meares, 2008; Tyler, 1990; Tyler, 2004). Police legitimacy has been found to be particularly important in th


f the police.
While building more-positive relationships with the community, the DMI also seeks to increase community capacity to begin to exert informal social control to prevent the market from reemerging. Programmatic elements that promote this in


evaluations of the efforts in Nashville Providence, Rockford, and Winston-Salem, suggest that the effort reduced crime (Corsaro, Brunson, and McGarrell, 2009; Corsaro and McGarrell, 2009; Frabutt et al., 2009; Kennedy and Wong, 2009; McGarrell, Corsa


, pharmaceutical pills, and
marijuana
347,965 Heroin and crack cocaine; some powder cocaine,
marijuana, and prescription pills
96,790 Crack cocaine and marijuana
Drug Sale Methods in the Target Drug Market
Export*/Local** Market: Heroin buyers predom


ea in northwest Flint, about one square mile, referred to as Flint’s Second Ward. By and large, the area consists primarily of single-family homes populated by a mix of owners and renters, with a few gas stations and fast-food restaurants. Nine in te


e St. Johns River, the city is a major military and civilian deep-water port. The local economy is based on services such as banking, insurance, health care, logistics and tourism. Of its more than 500 neighborhoods, those with ongoing poverty and hi


scussions among the team members began to delineate the boundaries of a target area for the project using data on drug and violent crime complaints, and began to identify areas where they could get cooperation from neighborhood residents.
Lake County


place.
 18
shape and size—and their residents stand in sharp contrast to the otherwise suburban, pastoral surroundings of Damascus, which consists of large, single-family dwellings along wide, tree- lined streets. Of the total 5,010 occupied housing


ften in darkness, which also aids criminal activity; law-abiding citizens are fearful of walking in the area. In addition to the established drug market, the area is experiencing problems with illegal dumping of tires, copper theft, open and abandone


United States—that is, jurisdictional teams consisting of at least one member of local law enforcement, one prosecutor, someone from the social service sector, and one influential community member—who were interested in implementing a program inspir


four trainings were structured to allow time for the following:
• brief overview and update of current site activities
• spotlighting of local DMI efforts by the host site
• team meetings
• meetings of functional or like discipline groups
4 The BJA T


n because of frequent variability in implementation procedures across sites (Harachi et al., 1999; Dusenbury et al., 2003).
22
Process evaluation contributes to an understanding of the relationship between program elements and program outcomes (Barth


aspects of the program and/or overcame implementation barriers.
The RAND team collected data from a number of sources using a variety of methods (e.g., site visits, interviews with all of the team members, and observation of BJA trainings). The team


barriers to implementation. RAND also maintained regular communications with BJA TTA provider staff from MSU on site progress. Because multiple TTA sessions were held over a period of years, RAND also received input from the trainers on implementati


sessment of planning phase fidelity at each site, and describe planning barriers and innovations.
Forming Teams, Assessing Readiness
DMI teams should consist of at least one member of law enforcement, one prosecutor, one member of a social service ag


o recruit other team members. In Montgomery County, a city council member suggested the DMI program to the county chief of police. After researching the possibility of adopting the program, the Montgomery County Police Department became enthusiastic


tings
Weekly
Biweekly
Monthly initially; dropped off
Biweekly initially; dropped off
Monthly
Monthly
Biweekly
        Site
Flint, Mich.
Guntersville, Ala.
Jacksonville, Fla.
Lake County, Ind.
Montgomery County, Md.
New Orleans, La.
Roanoke, Va.
On Or


osecutor, community service organization, community member) were identified and recruited. As a result, progress in planning for areas outside law enforcement was delayed and the team had difficulty gaining the full support of a social service agency


 during the planning phase was the procurement of MOUs with the social service providers. Both Flint and Lake County decided to formalize these relationships and formally outline the responsibilities of the community service providers.
Key Points on


ll relied on crime analyses to select a narrowly defined target area. In Flint, for example, the team examined crime data and chose the area within the city that contained the highest number of serious crimes, but did not identify a discrete drug mar


ed from an ongoing narcotics racketeering investigation in the Hoffman Triangle area of the 6th district. From the Racketeer Influenced and Corrupt Organizations (RICO) investigation, officers had been working to document drug dealers in the Hoffman


teria for inclusion on the A-list or the B-list were fairly similar across the sites. Most sites agreed that, to be on the B-list, individuals must not have a violent criminal history and no felony or gun charges on their criminal record. There were


s. The Roanoke police reported difficulty in finding informants to participate in drug purchases; the team ended up developing special operations to catch drug buyers and turning them into informants.
• Police forces played varying roles in building


ters had gone on to commit more serious offenses and were not eligible for the B-list within a year of the start of the targeting phase.
** Did not complete the targeting phase.
Fidelity ratings were determined as follows:
• high fidelity: used crime


undecided about how to conduct the investigations. The prosecutor’s office wanted to use undercover officers, rather than confidential informants, but the police department argued that its manpower resources were stretched too thin to devote officer


ing the target area, with four teams relying on a formal analysis of local crime data (as prescribed in the training model), one using calls for service, and others taking a more strategic approach, such as targeting the only areas with high crime, o


the intervention, including community meetings, meetings with community leaders, community events, community surveys, and door-to-door contact with residents (see Table 6.1). All but one of the sites that passed the targeting stage conducted at leas


proximately one year before the call-in. The team held a second community meeting in the month before the call-in. The official Flint website also contained information about the program—which changed names several times over the course
40
of a few y


rs and leaders of community organizations. Several smaller meetings with community leaders were subsequently held to garner support for the program, but no further community meetings with residents have been held. Many sites also gave media interview


 Activities; Fidelity to the Model
Assigned a Mentor/Resource Coordinator to B-Listers
  Flint, Mich. No
Guntersville, No Ala.
Montgomery No County, Md.
Roanoke, Va. Yes
Working with the Community Phase Barriers and Innovations
Barriers. Some sites h


munities’ perceptions of drugs, crime, and the police changed after the intervention.
Key Points on Working with the Community
• Of the sites that moved toward a call-in, most conducted activities to mobilize the community and engage them in the proc


s chapter, we discuss site preparation for the call-in, including A-lister arrests and prosecutions, notification of candidates, and conducting the call-in. We then provide our assessment of call-in phase fidelity and describe barriers and innovation


able to notify all offenders and/or their families eventually, and when it came time to hold the call-in, most B-listers at each of the sites attended.
Sites used varying approaches for notifying family members (see Appendices E and F for Roanoke’s r


sized that the B-listers had an opportunity to avoid the same fate.
Message. The message presented was also generally the same: B-listers were informed that the criminal justice system was aware of their drug-dealing activities and had sufficient evi


te drug and alcohol screenings. The screenings were never enforced, but the team included this requirement in the hope that the threat of potential testing would deter the B-listers from using.
In Guntersville and Montgomery County, the B-listers wer


  Sites
Flint, Mich.
Number of Community Members in Attendance
~95
Presentation of Evidence
Separate from community; a stack of B-lister files at front of room; were not shown evidence unless requested
Planned to show videotaped evidence but during


market from re-emerging. It consists of two main efforts: one from law enforcement and one from the community. On the law enforcement side, the target area receives additional services, manpower, and prioritized calls for service. Law enforcement pre


eighborhoods, generally for a period of at least three months, which included both additional personnel and attempts to buy drugs. Only Flint was unable to dedicate any additional enforcement efforts in the targeted area, because of budgetary issues.


ildren, a basketball camp sponsored by the Guntersville Police Department, and a follow-up resident meeting to update the community on intervention-related information. Finally, the Guntersville Public Library, located at the edge of the target area,


no arrests were made in the yearlong follow-up period. In Montgomery County, there was a complaint made against one of the B-listers, but this individual had not been arrested in the year after the program.
Three of the four sites did not assign a me


e Flint’s team conducted several community follow-up events, it was unable to secure funding for additional law enforcement or prosecutorial resources in the target area.
54
Table 8.1. Increased Enforcement Activities After Call-In; Fidelity to the M


asketball camp, a book
55
club, an after-school party, and a second park clean-up evening). A neighborhood watch that the police community relations group developed is also in the works.
In Flint, the team came up with an innovative method for monito


than 100 Section 8 apartments. Team members held several meetings, and many of them focused on problems within the apartment complex, mainly its disrepair. They were able to get the management company to make a large number of physical changes to the


ms followed training model and should not be taken as judgments how well the teams performed or how effective the intervention and its components were across the sites. Below, we provide a brief summary of site-by-site implementation.
 Table 9.1. Sum


 left for a new job.
New Orleans, Louisiana
Many of the obstacles New Orleans encountered focused on not getting enough support and involvement from higher-ranking NOPD officials. Although the initiative began in the police department, it began at a


th the community. Moving forward, team members say they hope to continue to build on their community engagement and collaboration efforts with other community groups. Since the original implementation of the intervention, the Flint team has conducted


d all but two A-listers received tough prison sentences. However, except for meetings held with management of the apartment complex, efforts to engage the community with formal meetings or events did not occur until after the call-in.
During the call


unity hot spot where they made constant patrols and created a relationship with residents. Finally, the Roanoke police began using license plate readers to identify the owners of outside vehicles in the neighborhood; police would then send the owners


 a case was related to the intervention, and the A-listers and B-listers who were caught violating the terms of their suspended cases were not sanctioned to the fullest extent, thus eroding program credibility.
Lesson Two: Participants should have a


he authorization to move forward. As a result, the process of putting together candidate cases stalled. While political situations may not be easy to prepare for, teams should be aware of this issue, and if applicable, bring new leadership on board w


(Rogers, 2002; Sales et al., 2006); and that cultivating “champions” (i.e., well-respected individuals within an organization or community) who can serve as peer consultants and role models also can facilitate implementation and, ultimately, adoptio


but there was still a commitment to putting most of the dealers on the B-list; for Southside the B-list share was 79 percent (22 of 28) and in East Side was 81 percent (26 of 32). The fifth DMI in Washington was an anomaly in High Point, with the B-l


DMI replications.3
With four of the five High Point DMI’s having B-lister rates hovering around 75 percent and three of the four BJA sites with rates closer to 33 percent, variations could affect outcomes. The high rate of A-listers (and arrests) at


onviction: Distribution of crack cocaine
− Sentence: ten years; suspend all but 18 months, four years’ supervised probation, stay
away order
3. Conviction: conspiracy for distribution of crack cocaine
− Sentence: four years; suspend all but nine mont


wing forms, which were used in the process evaluation:
• Planning Phase Data Collection form
• Targeting Phase Data Collection form
• Community Organizing Data Collection Form
• Call-In Data Collection Form
• Post–Call-In Data Collection Form
• DMI M


ght, their criminal histories, and ultimate case dispositions:
  1
2
3
4
5
6
7
8
9
10
11
12
Charge         Felony convictions
Case outcome
Sentence
                                                  Did the team make an effort to get community members


w many members of the community at large attended the call-in? _____________ Which social service providers were present at the call-in?
1) 4)
2) 5)
3) 6)
Who spoke at the call-in?
Prosecutor
Police
Social service providers
Community leaders
Members


__
Was there a procedure established for regular reporting of broken street lights, trash, unkept yards, graffiti to appropriate city agencies?
No YesèFor how long after the call-in was this procedure in place? _________________ 81
Did the team publ


s to implementation:
a. Identify target area using crime mapping.
b. Engage the community.
c. Survey police officers.
d. Identify street drug dealers.
e. Review street drug incidents.
f. Conduct the undercover investigation.
 84
g. Establish contact


to a meeting on at the located at . You will not be arrested. This is not a trick. You may bring someone with you who is important to you, like a friend or relative. I want you to see the evidence I have of your involvement in criminal activity, and


ing/outdoor activities (Frisbee, basketball, croquet, horseshoes) 5:00–5:45 p.m. Dinner
6:00–8:00 p.m. Conflict resolution/effective communication
8:00–8:45 p.m. Mindfulness/journaling
8:45–10:00 p.m. Personal hygiene and leisure time/subject-appropr


nt Research, Vol. 11, 1996, pp. 12–35.
Baumer, Eric P., Janet L. Lauritsen, Richard Rosenfeld, and Richard Wright, “The Influence of Crack Cocaine on Robbery, Burglary, and Homicide Rates: A Cross-City, Longitudinal Analysis,” Journal of Research in


icy, Vol. 11, No. 2, 2012, pp. 167-199.
Corsaro, Nicholas, and Edmund F. McGarrell, An Evaluation of the Nashville Drug Market Initiative (DMI) Pulling Levels Strategy, East Lansing, Mich.: Michigan State University, School of Criminal Justice, Drug


holas Corsaro, and Edmund F. McGarrell, The High Point Drug Market Initiative: A Process and Impact Assessment, East Lansing, Mich.: Michigan State University, School of Criminal Justice, 2010a.
———, The High Point Drug Market Initiative: A Process a


l of Criminal Justice and Security, Vol. 12, No. 4, 2010, pp. 397–407.
Meares, Tracey L., “Norms, Legitimacy, and Law Enforcement,” Oregon Law Review, Vol. 79, 2000, p. 391.
———, “The Legitimacy of Police Among Young African-American Men,” Marquette


s it Help Reduce Violence? Washington, D.C.: U.S. Department of Justice, Office of Justice Programs, National Institute of Justice, 1998.
Saunders, Jessica, Russell Lundberg, Anthony Braga, Greg Ridgeway, and Jeremy Miles, “A Synthetic Control Approa


 Autonomous Vehicle Technology
A Guide for Policymakers
James M. Anderson, Nidhi Kalra, Karlyn D. Stanley, Paul Sorensen, Constantine Samaras, Oluwatobi A. Oluwatola
 CORPORATION
For more information on this publication, visit www.rand.org/t/rr443-2


rs and by the fees earned on client-funded research.
The RAND Transportation, Space, and Technology Program
The research reported here was conducted in the RAND Transporta- tion, Space, and Technology Program, which addresses topics relating to trans


njuries per Million Vehicle MilesTraveled....................................................... 13
2.3. U.S. Roadway Fatalities per Billion Vehicle Miles Traveled . . . 14
2.4. Relationship Between Roadway Speed and Roadway Throughput...............


externalities,” on other people. For example, every addi- tional driver increases congestion for all other drivers and increases the chance that another driver will have an accident. These externalities have been estimated at approximately 13 cents


Level 3 or higher is likely to substantially reduce the cost of congestion, since occupants of vehicles could undertake other activities. These reductions to the costs of congestion will benefit individual AV operators. On the other hand, reductions


ency of crashes is reduced, cars and trucks could be made much lighter. This would increase fuel economy even more.
AVs might reduce pollution by enabling the use of alternative fuels. If the decrease in frequency of crashes allows lighter vehicles,


V or the public
Summary xvii
xviii Autonomous Vehicle Technology: A Guide for Policymakers
more generally. Such research would also be helpful in determining the optimal mixture of subsidies and taxes to help align the private and public costs and be


se the environment, AVs use a combination of sensors, including lidar (light detection and ranging), radar, cameras, ultrasonic, and infrared. A suite of sensors in combination can comple- ment one another and make up for any weaknesses in any one ki


enge for a technology widely available to the public.
Software upgrades also could pose challenges, as they might need to be backward-compatible with earlier models of vehicles and sensor systems. Moreover, as more vehicle models offer autonomous dri


hicle Technology: A Guide for Policymakers
dards for communications platforms within automobiles, along with issues pertaining to data security, data ownership, and privacy.
Standards and Regulations
Government regulations and engineering standards a


turers to use technology for closer monitoring of driver behavior.
Policymakers could also take actions to reduce manufacturers’ liability. Congress could explicitly preempt state tort law remedies, an approach that has some precedents. Congress coul


xample, safety regulations and liability rules should be designed with this overarching guiding principle in mind. Similarly, this principle can provide some guidance to judges strug- gling with whether a particular design decision was reasonable in


NHTSA NPRM NRC NTIA
NTSB OEM RITA SAE U-NII V2I V2V VIN VMT
Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation
International Harmonized Research Activities working group on intelligent transport systems
Insurance Institute for Hi


Meeting and the Transporta- tion Research Board’s Workshop on Road Vehicle Automation.
In the remainder of this chapter, we briefly define different levels of vehicle autonomy, explore why they merit the attention of policymak- ers, and enumerate que


ironmental conditions, and in those conditions to rely heavily on the vehicle to monitor for changes in those conditions requiring transition back to driver control. The driver is expected to be available for occasional control, but with sufficiently


ly, cars might share sensor information with nearby vehicles, which could provide an AV with more information on which to base its decisionmaking. While some have argued that connected vehicle technology will be central to achieving AV operation (KPM


t run, and to fall about twice that in the long run, with a range of –1.0 to –2.0 (Lee, Klein, and Camus, 1999; Litman, 2012). This implies that as travel costs (time and expenses) reduce by 10 percent, travel is expected to increase: by 7 to 8 perce


blur the line between vehicle and driver, and DMVs are beginning to test and license AVs. State DOTs maintain and operate highway infrastruc- ture, and thus would be responsible for any investments in intelligent infrastructure or the creation and o


 (e.g., Small and Kazimi, 1995; Delucchi, 2000; Parry, Wells, and Harrington, 2007; Michalek et al.,
9
10 Autonomous Vehicle Technology: A Guide for Policymakers
2011). These externalities include accidents, congestion, noise, air pol- lution, and gr


 2011 (EPA, 2013a), so the social cost of CO2 emissions from light-duty vehicles was nearly $41 billion annually.
Somewhat confusingly, different externalities are estimated in dif- ferent ways. Impacts from air pollution, GHG emissions, and oil impo


will be much higher if it is in a dense city. These estimates are based on data in the United States. The pat- tern of externalities will be different in other countries.
 The Promise and Perils of Autonomous Vehicle Technology 13
billions of dollars


0 fatalities with much fewer VMT (BTS, 2013). And, similar to the injuries dis- cussed above, pedestrian casualties were a considerable portion of the total, more than 4,400 in 2011. So, light-duty vehicle operation poses a risk not only for other li


kless—and can increase avoidance of
2 This is significant as more than 14,000 of the 32,000 roadway deaths in 2011 involved a single vehicle (BTS, 2013). Of course, driver error is still possible from other vehicles on the road that do not have autom


e, are used to pro- vide on-demand paratransit services. The per-trip costs of these ser- vices are often three or more times those of fixed-route transit services (GAO, 2012). Level 4 automation could expand mobility and access at reduced costs. Whi


KPMG and Center for Automotive Research, 2012)—a driverless taxi system that over time replaces traditional taxi service, car-sharing programs, and possibly even transit lines. Driver- less taxis could offer the same on-demand, door-to-door convenien


operating costs add another 21 cents per mile, including about 15 cents for gas, just under 5 cents for maintenance, and just over 1 cent for tires (note that the AAA data do not include the costs associated with tolls and parking, as these vary con


on to the additional per-mile costs asso- ciated with depreciation, insurance, and the like, it is thus possible that reliance on driverless taxis could eliminate the fixed costs of auto
The Promise and Perils of Autonomous Vehicle Technology 21
owne


ral- purpose lanes slow to 15 to 20 mph. At the same time, the express lanes carry roughly double the number of vehicles per lane per hour as the congested general-purpose lanes (Obenberger, 2004).
The State Route 91 example illustrates how maintaini


 2.2.
Based on the significant percentage of traffic congestion caused by crashes that AVs could help eliminate and the major improvements in throughput capacity they could enable, there is reason for optimism that the combined effects of these facto


e other costs associated with congestion, such as reduced economic efficiency, where AVs could also have a positive impact.
Unlike many of the other potential benefits of this technology, these benefits are realized by the user of the AV. Indeed, the


his should increase the willingness of households, and possibly some firms, to locate farther away from the urban core. Just as the rise of the automobile in the 20th century led to the emergence of sub- urbs and ultimately exurbs by reducing transpo


d cars. At the same time, AVs could support even greater dis- persion of low-density development along the outskirts of major met- ropolitan areas given the ability of owners to engage in other activi- ties as vehicles pilot themselves. These effects


e NRC estimated the potential fuel economy improvements to con- ventional vehicles between now and 2050 to be 130 to 250 percent
The Promise and Perils of Autonomous Vehicle Technology 29
Figure 2.5
Average Fuel Economy of U.S. Cars and Light Trucks,


hybrid cars, and autonomous cars (omitting light trucks) in Figure 2.6.
How Light Can We Make Vehicles If There Are Almost No Accidents? To move a vehicle, power is required to overcome inertia, rolling resistance (or “the street pushing back”) and a


y: A Guide for Policymakers
Figure 2.7
Average Weight of U.S. Cars and Light Trucks, 1975–2012
5,500
5,000
Average vehicle weight (lb)
3,500
3,000
2,500
2,000
1975 1979 1983
SOURCE: EPA, 2013b.
RAND RR443-2.7
   Light truck weight (lb)
Car weight (lb


ght reductions currently projected. These are substantial, projected as reductions of 20 to 25 percent by 2030 and of 32 to 50 percent by 2050 (NRC, 2013a). The successful deployment of Level 4 automation could then enable additional incremental weig


e to travel the same range using batteries that are smaller, and thus cheaper. The improved drive cycles and congestion management from Level 2, 3, and 4 AVs would also allow for smaller batteries. This would reduce the overall cost for consumers, an


tion GHG emissions, oil use, and conventional air pollutants (Samaras and Meis- terling, 2008; Michalek et al., 2011). Level 2, 3, and 4 AVs can hasten this transition, with Level 4 AVs also enabling radical redesigns of both electric vehicles and th


T demand from new sources. These include the elderly, the young, those without driver’s licenses, and those who explicitly or implicitly value the time or multi- task opportunities afforded by driverless taxis at high rates. But if Level 4 driverless


mental goals are met.
Costs and Disadvantages
While there are reasons to think that AV technology may increase safety and efficiency, and reduce congestion and emissions per mile
  Annual vehicle-distance traveled (billion miles)


anies are also important investors in federal, state, and municipal bonds. This entire sector of the economy may well be remade as crashes, and the wealth transfers they occasion, decline in frequency.
The eclipse of driving may also have cultural di


testing or even operation of a driverless vehicle; Bryant Walker Smith has argued that existing law probably permits the use of driverless cars (Smith, 2012b). Nor are we aware of any documented problems with the test- ing or use of AVs that the leg


collision occurs between the autonomous vehicle and another vehicle, object or natural person while the vehicle is operating in auton- omous mode. The autonomous technology sensor data must be captured and stored in a read-only format by the mechanis


ions that have been enacted to date.
Nevada (NRS 482.A and NAC 482.A)
• Enacted: June 2011, revised July 1, 2013.
• Definition of AVs: “Autonomous technology” means technology
which is installed on a motor vehicle and which has the capabil- ity to dr


queu- ing assistant, unless any such system alone or in combination with other systems enables the vehicle on which the technology is installed to drive without the active control or monitoring by a human operator” (Florida House of Representatives,


age the autono- mous technology; a visual indicator to indicate when the autono- mous technology is engaged; a system to safely alert the operator if an autonomous technology failure is detected while the autono- mous technology is engaged, and when


ve activity on this issue in many other states. These are summarized below:
Arizona (HB 2167)
• Introduced: January 2013.
• Status:Introduced.
• Key features: Defines AVs and autonomous technology (excludes
individual driver assist systems) (Arizona


ted technology,” “automated
vehicle,” “automated mode,” and “upfitter”; grants civil liability immunity to manufacturers of automated technology for dam- ages that arise out of any modification made by another person to a motor vehicle or an automate


hnology: A Guide for Policymakers
lina General Assembly, 2013, §56-12-10-70); directs the DMV to adopt regulation by January 1, 2015 (South Carolina General Assembly, 2013, §56-12-80). Manufacturer is defined as whoever installs autonomous technology


autiously in this area and adopt legislative solutions only in response to clearly identified problems. Further efforts to develop a model stat- ute to promote uniformity in requirements may be useful.2
1 Bryant Walker Smith has argued that AVs are m


ed by Ernst Dickmanns at Bundeswehr University Munich in Germany developed a vision- guided vehicle that navigated at speeds of 100 kilometers per hour without traffic (Lantos and Mâarton, 2011). Carnegie Mellon Univer- sity’s NavLab developed a ser


partici- pated in that competition. In the years since, Google has developed and tested a fleet of cars and initiated campaigns to demonstrate the applications of the technology through, for example, videos highlight- ing mobility offered to the blin


ons—its overall trajectory down the road and immediate decisions such as accelerating and changing directions. These plans are converted into actionable commands to the vehicle’s control system; i.e., steer- ing, throttle, brakes. Many “sense-plan-ac


road
surfaces, poorly marked roads, and detours
• traffic events, such as congestion or crashes.
It is in making sense of the world that humans often outperform robots. Human eyes are sophisticated and provide nearly all of the sensory data we use to


ight detection and ranging, or lidar, systems feature prominently in robotic systems, including AVs. Lidar systems determine dis- tances to obstacles by using laser range finders, which emit light beams and calculate the time-of-flight until a reflec


or parking assistance systems and backup warning systems (Ford, 2013). They are also relatively inexpensive, with after-market solutions retailing for as little as $120. Infrared sys- tems are capable of detecting lane markings without the lighting a


bility and provided civilian users the same quality signal as military users (National Coordination Office for Space-Based Positioning, Navigation, and Timing, 2014).
 64 Autonomous Vehicle Technology: A Guide for Policymakers
GPS is typically couple


y and respond to traffic lights. “The idea is to get the best out of camera-only autonomous driving,” noted one of MobilEye’s executives (Markoff, 2013). Similarly, the winner of the 2013 Intel International Science and Engineering Fair, a 19-year-ol


vironmental conditions) can also pose serious performance threats (Hwang et al., 2010). Sensors may fail because of electrical failures, physical damage, or age. It will be critical for AVs to have internal sensing and algorithms that can detect when


and ensuring ultra- reliability of public infrastructure for driverless cars may be prohibi- tively expensive, particularly in a time of growing fiscal uncertainty for transportation agencies. Additionally, to be safe and effective, V2V technologies


to ensure that the driver is sufficiently engaged—for example, a vibrating seat or wheel, or vehicle screens that show the road rather than entertainment. But while a vehicle manufacturer may carefully limit what is displayed on a vehicle’s screen, i


 consensus on the legality or ethics of companies’ abilities to collect and extract value from user data.
 70 Autonomous Vehicle Technology: A Guide for Policymakers
University, for example, has plans to introduce a driverless shuttle on its campus,


sensor readings to a vehicle’s sensors; e.g., sending false lidar returns to a vehicle that is using three-dimensional mapping to navigate through its environment.9 While this may be more difficult to achieve, it may also be more difficult to detect


ar-term DOT investments. We touch on these issues briefly here, and discuss them further in later chapters.
Policymakers could regulate different specific vehicle capabili- ties: highway vs. city driving, fast vs. slow driving, fully autonomous vs. d


ance to road signage and mark- ing standards to make the perception challenge easier. Standardiza- tion across states would also be significantly beneficial; not only for AV owners but also conventional drivers who sometimes struggle to understand co


out that obstruction is sensed by one car using this system, information about it can be nearly instantaneously communicated to every other car using the same system.
Second, the federal government has supported the development of Dedicated Short-Ran


ons Technologies Used by Autonomous Vehicles
The following section will provide a brief explanation of different tech- nologies and identify how they are used in AVs. All of these technolo- gies use radio frequency (RF) spectrum.1
Commercial Wireless


to increase the capacity and speed of wireless data networks using new digital signal processing techniques and modula- tions that were developed around 2000. The LTE wireless interface is incompatible with 2G and 3G networks, so that it must be ope


ol systems. For emergency vehicle warnings, DSRC would enable information to relay forward through traffic, which could clear the way for the emergency vehicle and reduce risks to other drivers.
Forward obstacle detection and avoidance
Emergency vehi


ciety of America, 2013).
Stakeholder Viewpoints on Autonomous Vehicle Communications
The Research and Innovative Technology Administration of the U.S. DOT characterized its vision of “connected cars” as requiring commu- nications in the following way


car: General Motors has announced that it will be integrating an LTE connection into all of its 2014 vehicles, whereas Ford has publicly described GM’s integration of LTE as a “mistake,” because integrating any technology into a car that lasts for 10


mbined approach of sensors, radar, lidar, and DSRC could accelerate deployment of AVs by bringing costs down for mass- market acceptance. Groupe Speciale Mobile, a European-based orga- nization of global mobile-technology providers, confirmed the vie


, to allocate spectrum for use by private, commercial, and state and local government authorities (U.S. Code, 1934). Recently, the FCC’s proposal to release up to 195 GHz of spectrum in the 5.9 GHz band raised concerns about implications of this acti


spectrum available for unlicensed devices across the overall radio spectrum.” Specifically, the FCC is considering changes to its Part 15 rules. Part 302(a) of the Communications Act of 1934 gives the Commission authority “con- sistent with the publ


not state that the FCC proceeding should include the 5850–5925 MHz band, which is the band assigned to DSRC.5 The U-NII NPRM rec- ognizes the precise assignment from Congress, stating, “the initiation
5 SEC. 6406. UNLICENSED USE IN THE 5 GHZ BAND.
(a


850–5925 MHz band.
(c) DEFINITIONS.—In this section:
(1) 5350–5470 MHZ BAND.—The term “5350–5470 MHz band” means the portion of the electromagnetic spectrum between the frequencies from 5350 megahertz to 5470 megahertz.
(2) 5850–5925 MHZ BAND.—The te


public safety expressed by federal and state agencies and departments that are experts on public safety issues. The FCC also will have to consider the $450 million that the U.S. DOT intelligent transport systems program has invested in researching an


rum in the 5.9 GHz DSRC band. Specifi- cally, the joint comments state that
the Alliance and Global are skeptical that, as proposed by the Commission, U-NII devices will be able to share, or operate in close proximity to, the 5.9 GHz DSRC band withou


 will either accelerate or inhibit deployment of DSRC and AVs.
Internet access is an important aspect of daily life and business, but DSRC can assist in preventing crash deaths on a major scale. While some have expressed concern about the lack of dev


us that building robust security protocols across many different automakers’ vehicles and different communica- tions platforms is likely to be very challenging technically. Similarly, one of the global technology developers who advocated the need for


ogies. We then reviewed stakeholder concerns and the upcoming decision by the FCC on whether to permit sharing of spectrum currently allocated to DSRC. Stakeholders have described a number of technical and policy issues concerning communications and


h prescribe an array of safety standards and test procedures, from crash-avoidance components (such as brakes and indicators) to crashworthiness features (such as seat belts and air bags) to post-crash factors (such as the integ- rity of the fuel sys


manufacturers often use these ratings in advertising their cars. More recently, in evaluating cars, NHTSA has noted the presence or absence of crash avoidance systems: electronic stability control, lane departure warning, and forward collision warni


004, p. 390) notes the perspective of policymakers and industry experts at the time:
They argued that a system of inflatable pillows could be auto- matically deployed inside a vehicle in the event of a collision that would hold occupants in place eve


een 1990 and July 2008, primarily due to the extreme force that is necessary to meet the performance standard of protecting the unbelted adult male passenger. Houston and Richardson (2000) describe the strong reaction to these losses and a backlash a


NTSB felt that the use of a variety of systems would lead to driver confusion and incorrect interventions and responses to system behavior (NTSB, 2001).
There are currently no federal regulations related specifically to AV technologies, though both N


bling elements of future systems” (Shulman and Deering, 2005, p. 3). It includes, for example, the For- ward Collision Warning Requirements Project, which addresses alert function and interface requirements through real and simulated tests with human


ward Collision Warning Systems: Operating Characteris- tics and User Interface Requirements (2003b); ISO, Transport Information and Control Systems: Adaptive Cruise Control Systems: Performance Requirements and Test Procedures (2007b); ISO, Transport


discussed, driver interaction and involvement is critical to many AV technologies (e.g., warning systems that operate specifically by influencing the driver, and other technologies, such as ACC, that must be activated by the driver and require the d


peration to certain areas or conditions).7
Conclusion
Mandating the inclusion of AV technologies may not be appropriate until at least the following circumstances are met. First, the technology must be mature enough that manufacturers are confident i


 of this technology. Gary Marchant and Rachel Lindor (2012, p. 1334) outlined one such scenario: 1
The technology is potentially doomed if there are a significant number of . . . cases, because the liability burden on the manu- facturer may be prohib


this complex issue and its implications would be useful.
3 Tort is a general term for wrong and is also a term that refers to the general legal field of torts. A negligent tort is a particular category of tort. Other categories include intentional to


defined as “a personal injury resulting in death, serious impairment of body function or permanent serious disfigurement” (Pennsylvania Statutes, Title 75, §1702).
7 It has proven somewhat disappointing in practice, with costs remaining higher than e


 and (f) extent to which its value to the community is outweighed by its dangerous attributes.
 Liability Implications of Autonomous Vehicle Technology 115
holders to invest in them. In Europe, for example, insurers have offered a 20-percent discount


less likely to undermine the sense to which the driver retains ultimate responsibility for the vehicle. In contrast, if a car with an engaged autopilot feature crashes into a car in front of it and the driver’s use of the autopilot was proper, it see


, new categories of crashes might arise, and these might pose interesting questions of how the liability system sets incentives to coordinate care among parties. For example, suppose that most cars brake automatically when they sense a pedestrian in


s and automobile-insurance companies. As responsibility for crashes shifts away from the driver, no-fault systems may become more attractive.
On the other hand, these technologies pose challenges for manu- facturers and may increase their liability r


 large.
In contrast, plaintiffs will likely seek to exclude any global cost- benefit analysis that considers the benefits of avoided crashes and try to focus the reasonableness analysis on the specific facts around the crash (for example, was the aut


le to victims in lieu of having to prove neg- ligence. Strict liability is conventionally contrasted with negligence because, in theory, it does not require any showing of negligence,
15 See Anderson (2007) for discussion of these issues.
 Liability


m to persons other than users or consumers; (2) to the seller of a product expected to be processed or otherwise substantially changed before it reaches the user or consumer; or (3) to the seller of a component part of a product to be assembled.
 122


duct not reasonably safe.
 Liability Implications of Autonomous Vehicle Technology 123
states that a seller is not liable for failing to warn of known risks and risk-avoidance measures that should be obvious.
Strict product liability is probably the


design: consumer expectations and cost-benefit. The consumer-expectation test was explained by one court as follows (Donegal Mutual Insurance v White Consolidated Industries, 2006):
A product is defective in design or formulation when it is more dang


event crashes 80 percent of the time. The other 20 percent of the time, how- ever, the technology does not work and the crash occurs as it would have in the absence of the technology. Victims in those crashes may sue the manufacturer and argue that t


for safety. Careful thought and further research may be necessary to determine which costs and benefits should be included in the cost- benefit analysis that accompanies product liability.
Human-Computer Interaction
We also anticipate litigation arou


for new technologies even when the technology seems clearly defective.
 128 Autonomous Vehicle Technology: A Guide for Policymakers
situation that could require a warning and that the instruction manual that accompanied the car clearly set out the li


lation that is inconsistent with state tort law. So, for example, product manu- facturers may argue that federal safety regulations preempt inconsis- tent state tort law and preclude lawsuits by injured plaintiffs.
Preemption is a controversial subje


ves that an important function of tort law is corrective justice or civil recourse, one might be skeptical of federal preemption.
Implied preemption has arisen in the automotive context in litiga- tion over a manufacturer’s failure to install air bag


l companies (U.S. Code, 1990). In 1994, the General Aviation Revitalization Act of 1994 created a statute of repose and immunized makers of small air- craft against liability for planes after 18 years from manufacture even if negligence was shown (U.


Warnings and consumer education will play a crucial role in managing manufacturer liability for these sys- tems. Manufacturers are likely to understate system capabilities during advertising, educate owners when purchasing vehicles with these capa-
L


product, rather than a good that is pur- chased and owned (Smith, 2013b). By doing so, manufacturers may be able to use contract law to limit their liability and better control the way their products are used. Scott (2008) discusses the way this issu


s of dollars and would double or triple the cost of most cars. It seems unlikely that consumer demand would be substantial at such a cost. While most stakeholders we interviewed were confident that substantial price reductions will occur, no one seem


are. For example, the expected reduc- tion in congestion is a benefit to other motorists, but the reduction in the cost of congestion—because the driver can do other things— is a benefit to the vehicle operator. If there is an increase in conges- ti


expressed concerns that premature regulation on the state level may result in a crazy-quilt of different, and perhaps incompat- ible, requirements. Attempting to meet state regulations could increase costs and make the technology uneconomical.
NHTSA


AV com- munications platforms will need to be standardized, at least through “best practices,” so developers can address a single platform design instead of many. According to several stakeholders, the size and type of processor is a developmental c


tors that “cause” a crash can be arbitrary.
As vehicles take on more of the driving functions that were histor- ically the responsibility of the driver, there may be a shift in our think- ing about accident responsibility. Rather than immediately att


s cov- ered in the next five sections.
Federal Statute Limiting Tort
Congress could pass a statute that limited liability of car manufac- turers (or immunized them completely) for certain categories of AV technology. Such an approach has some precede


s a substantial history with an alternative to con- ventional tort with respect to automobile crashes: no-fault. Currently the law in 12 states, the no-fault system allows crash victims to recover damages from their own auto insurers after a crash in


 manu- facturers would face substantially increased liability costs. However, it would still require legislative intervention.
Guidance for Policymakers and Conclusion 145
Incorporation of Appropriate Cost-Benefit Tests in Liability Determinations
As


ugh attempt to measure the more important dimension can be made, but that might not always be possible (Sunstein, 1994). Despite its imperfections, we think that focusing on comparing AV technology to vehicles operated by human drivers will provide u


identified, explore whether the model provides insight regarding how automated road vehi- cle data might be handled. Issues to be explored could include what parties may access personal location information, person- ally identifiable information, veh


ed in” to an unneces- sarily inefficient system (Hathaway, 2001). She offers the QWERTY keyboard as an example of an arguably subpar technology that became locked in as a result of the path-dependence of technological and eco- nomic development. In t


ensing of AVs?
• Whatpolicyrisksorgapsdoyouanticipateconcerninginsurance law in respect to AVs?
• What concerns do you have about privacy protection for data obtained and used by AVs?
• What are the communications issues you perceive, particularly co


rns extend to everyone, from software makers to infrastructure opera- tors—since it is early in the AV industry’s development, it is a loom- ing issue for all stakeholders. The liability issues appear to be increas- ing from the communications side a


lleagues noted that insurance should be analyzed from a short-, medium- and long-term perspective as far as being an accelerator or inhibitor. In the short term, insur-
Conclusions from Qualitative Interviews with Stakeholders 155
ance costs go up—it


e issuer of the certificate. It may be the government or a third party. Some people in government have asked the OEM whether there should be a tag on these data like a vehicle identification number (VIN). The OEM executive explained that all data com


cide what data they wish to share and what data they wish to keep private.
The automobile association executive we interviewed said data security issues are still unaddressed for AVS. He expressed the need for a credentialing system, and outlined the


, they provide another aspect of critical infrastructure and a potential target for a cyberattack. He said all of an AV’s systems had to be designed to resist possible intrusion by hackers, and cited an example where hackers were able to access a car


ions within the vehicle that would include car owners bringing their own device (like a smartphone), and some services being embedded into the vehicle (e.g., LTE).
An OEM executive concurred with this vision of “embedded vs. tethered” vehicle communi


s with Stakeholders 161
described the need for global harmonization on spectrum and commu- nications issues. He observed that “having to isolate technology makes it difficult to deploy.”
An automobile association executive said his organization had n


the United States is generally “robophobic.” The Europeans are confident in precision engi- neering and this provides confidence in precision-engineered vehicles. These consumer attitudes may have a significant impact on AV deploy- ment to the mass


ul, Minn.: American Law Institute Publishers, 1998.
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FMVSS—See Federal Motor Vehicle Safety St


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  CORPORATION
Driving to Safety
How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?
 Nidhi Kalra, Susan M. Paddock
In the United States, roughly 32,000 people are killed and more than two million injured in crashes


ity.
• Even with these methods, it may not be possible to establish with certainty the safety of autonomous vehicles. Uncertainty will persist.
• In parallel to creating new testing methods, it is impera- tive to develop adaptive regulations that are


verifi- cation. Curtain-style air bags, for example, are tested with a combina- tion of component tests to assess inflation time, fill capacity, and other responses in a range of temperature conditions and impact configura- tions, as well as laborato


last class of fully autonomous vehicles. Therefore, we use the total fatality, injury, and crash rates of human drivers in the United States as benchmarks against which to compare autonomous vehicle performance. However, the statistical approaches d


a certain number of failure-free miles and wishes to know the reliability (or, equivalently, the failure rate) that can be claimed at a particular level of confidence. Alternatively, for a given confidence C and reliability R we can solve for n, the


llion miles
  C = 50%
1.09
77
103
190
382
10
  1 10 100
Failure rate (failures per 100 million miles)
SOURCE: Authors’ analysis.
NOTE: The four colored lines show results for different levels of confidence. The five dashed vertical reference lines in


n to determine the sample size (number of miles) required to estimate the fatality rate of the fleet to within 20% of the assumed rate using a 95% CI. We apply Equation 4 to estimate the number of fatalities we would need to observe before having thi


 to estimate the failure rate with a precision of δ is:
⎛z ⎞2
x=⎜1−α2⎟. (Eq.4)
⎛z ⎞ ⎜ 1−α/2 ⎟.
⎝x⎠
⎜ δ ⎟ ⎝⎠
If the assumed failure rate (prior to data collection) is λ∗ (Mathews, 2010), then Equation 5 implies the number of miles that must be driven


n fact they do not—a dangerous proposition for policymakers, technology developers, the insurance industry, and of course consumers.
To be able to test the null hypothesis with significance level α, one can examine the upper confidence bound from Equ


ver fatality (blue), reported injury (purple), estimated total injury (green), reported crash (red), and estimated total crash (orange) rates. Note that the miles needed to be driven approaches infinity as the difference between the human rate and au


better than the human driver failure rate. The different lines represent perfor- mance relative to the human driver fatality (blue), reported injury (purple), estimated total injury (green), reported crash (red), and estimated total crash (orange) ra


millions)
         Yet even these results are optimistic. We have intention- ally framed this analysis to calculate the fewest number of miles that would need to be driven to demonstrate statisti-
cally significant differences between autonomous vehi


ng 24 hours a day, 365 days a year, at an average speed of 25 miles per hour. For example, one can ask, “How many miles (years) would autono- mous vehicles have to be driven (row 2) to demonstrate with 95% confidence their failure rate to within 20%


re rate is at most...
275 million miles (12.5 years)
3.9 million miles (2 months)
1.6 million miles (1 month)
(2) to demonstrate with 95% confidence their failure rate to within 20% of the true rate of...
8.8 billion miles (400 years)
125 million mil


t.gov/pubs/812013.pdf
Bureau of Transportation Statistics, Motorcycle Rider (Operator) Safety Data, Table 2–22, Washington, D.C.: U.S. Department of Transportation, 2014a. As of March 3, 2016: http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/


les: Opportunities, Barriers and Policy Recommendations,” Transportation Research Part A: Policy and Practice, Vol. 77, July 2015, pp. 167–181. As of March 3, 2016: http://dx.doi.org/10.1016/j.tra.2015.04.003
Farmer, Charles M., and Adrian K. Lund, “


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ogy policy.
Susan M. Paddock is a senior statistician at the RAND Corporation and a professor at the Pardee RAND Graduate School. Her research includes developing innovative statistical methods, with a focus on Bayesian methods, hierarchical (multile


ogram research is supported by government agencies, foundations, and the private sector.
This program is part of RAND Justice, Infrastructure, and Environment, a division of the RAND Corporation dedicated to improving policymaking and decisionmaking


 Consumer Attitudes Toward Data Breach Notifications and Loss of Personal Information
Lillian Ablon, Paul Heaton, Diana Catherine Lavery, Sasha Romanosky
 CORPORATION
For more information on this publication, visit www.rand.org/t/rr1187
 Library of C


risk management, and insurance. The institute builds on a long tradition of RAND Corporation research characterized by an inter-
iii
iv Consumer Attitudes Toward Data Breach Notifications
disciplinary, empirical approach to public policy issues and r


n
Technology, Such as Computers, Email, and Cell Phones?. . . . . 49
B.2. How Respondents Found Out About Their Last Breach . . . . . . . 51
B.3. Demographic Tabulation of Survey Respondents . . . . . . . . . . . . . . . 55
Summary
 Data breaches con


e data gathered and analyzed from this survey come from participant self-report and recall. As such, the data may be incomplete due to limits of memory, underreported due to forgetfulness of past notifications, or overreported due to increased media


opped dealing with the company follow- ing a breach.
Most respondents (89 percent) continued to conduct business with the breached firm, while only 11 percent stopped conducting business with it. One percent reported increasing the amount of busi- ne


es can review notification methods and data breach laws to speed up notification and prevent further harm with any stolen data.
More than one-quarter of respondents remember receiving a data breach notification in the 12 months preceding the survey,


, per- sonal data can appear within days on black markets, enabling crimi- nals to sell financial, health, and identity information (Ablon, Libicki, and Golay, 2014; Cárdenas et al., 2009) and causing various forms of identity, tax, and loan fraud (


s, or medical information. Some states (California, for example) do not require a disclosure if data other than these were compro- mised or lost (usernames and passwords, for example) (Hoofnagle and King, 2008).
2 Some commentators believe that the E


ications, or overreported due to increased media reporting (e.g., hearing about a data breach and misremembering being a part of it). With that caveat, these results can help establish a baseline of information about consumer attitudes toward data lo


ulk of our analy- sis. Our results suggest that most respondents who have lost personal information have had such an experience within the past 12 months. While not a panacea, by focusing only on the most-recent experience, the majority of which has


ernment Accountability Office, 2007). This underreporting effect may exist for a number of reasons: (1) a company may not be aware that it has suffered a data breach;7 (2) even if the company is aware, it is not always required to notify the public;8


(n = 2,038)
    Age Gender
Family income
Race/ Education Region ethnicity
Overall
Male Female
18–34 35–49 50–64 65+
$0–$30K $30K–$60K $60K–$100K >$100K
Northeast Midwest South West
High school or less Some college Bachelor's Postgraduate
Non-Hispanic


ercent versus 19 percent). This may be explained by the notion that those with greater income engage in more financial and recreational activities with more organizations, resulting in an increased risk of compromise of personal information.3
Region:


ify all individuals, rather than spending time to omit some individuals from select states.
We postulate that some of these patterns may also be explained by differential access to information and communication technolo- gies: In the past, those in t


ns
Figure 2.2
Percentage of Participants Who Recalled Receiving a Breach Notification in the 12 Months Preceding the Survey (n = 2,038)
  Age Gender
Family income
Race/ Education Region ethnicity
Overall
Male Female
18–34 35–49 50–64 65+
$0–$30K   9%


quires notifying organizations to offer identity-theft pro- tection and mitigation services to affected individuals (State Legislature
restricted to those who had some interaction with the federal government, either as current or former employees or


out (columns). 1, 2, 3, or 4 denotes statistically significant differences from the comfort-level groups (rows), within the ways that participants found out (columns). For example, among those who first learned about the breach from the company dire