Access to Health Care and Nonemergency Medical Transportation: Two Missing Links

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DOI: 10.3141/1924-10
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Abstract
Although lack of access to nonemergency medical transportation (NEMT) is a barrier to health care, national transportation and health care surveys have not comprehensively addressed that link. Nationally representative studies have not investigated the magnitude of the access problem or the characteristics of the population that experiences access problems. The current study, relying primarily on national health care studies, seeks to address both of those shortcomings. Results indicate that about 3.6 million Americans do not obtain medical care because of a lack of transportation in a given year. On average, they are disproportionately female, poorer, and older; have less education; and are more likely to be members of a minority group than those who obtain care. Although such adults are spread across urban and rural areas much like the general population, children lacking transportation are more concentrated in urban areas. In addition, these 3.6 million experience multiple conditions at a much higher rate than do their peers. Many conditions that they face, however, can be managed if appropriate care is made available. For some conditions, this care is cost-effective and results in health care cost savings that outweigh added transportation costs. Thus, it is found that great opportunity exists to achieve net societal benefits and to improve the quality of life of this population by increasing its access to NEMT. Furthermore, modifications to national health care and transportation data sets are recommended to allow more direct assessment of this problem.
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76
Although lack of access to nonemergency medical transportation
(NEMT) is a barrier to health care, national transportation and health
care surveys have not comprehensively addressed that link. Nationally
representative studies have not investigated the magnitude of the access
problem or the characteristics of the population that experiences access
problems. The current study, relying primarily on national health care
studies, seeks to address both of those shortcomings. Results indicate
that about 3.6 million Americans do not obtain medical care because of
a lack of transportation in a given year. On average, they are dispro-
portionately female, poorer, and older; have less education; and are
more likely to be members of a minority group than those who obtain
care. Although such adults are spread across urban and rural areas
much like the general population, children lacking transportation are
more concentrated in urban areas. In addition, these 3.6 million experi-
ence multiple conditions at a much higher rate than do their peers.
Many conditions that they face, however, can be managed if appropri-
ate care is made available. For some conditions, this care is cost-effective
and results in health care cost savings that outweigh added transporta-
tion costs. Thus, it is found that great opportunity exists to achieve net
societal benefits and to improve the quality of life of this population by
increasing its access to NEMT. Furthermore, modifications to national
health care and transportation data sets are recommended to allow
more direct assessment of this problem.
Millions of Americans are transportation disadvantaged because they
cannot provide or purchase their own transportation. Members of that
population, owing to low income, disability, inability to drive, geo-
graphic isolation, or some other reason, cannot transport themselves
and are unable to pay for buses or taxis. As a result, this population—
which is disproportionately elderly, poor, and disabled—depends on
others to access employment, education, shopping, and health care.
That dependency reduces access to routine and other nonemer-
gency medical services, and the reduced access can lead to poor
health outcomes. This possibility particularly affects those who have
chronic conditions (e.g., heart failure, asthma, and diabetes) and mul-
tiple diseases, as well as those who stand to benefit from screening,
prevention, and health promotion. Because of poor access to care,
routine conditions can escalate to a need for emergency care, for
example, when poorly managed asthma—a problem among children
in the inner city—causes a major attack. Therefore, improving access
to health care for the transportation-disadvantaged population can
reduce national health care costs, possibly offsetting the incremental
increase in transportation costs.
Given the concerns raised by missed medical trips and the effects
on the health of those who miss the trips, the goals are to identify and
describe the population of Americans who experience lack of access,
determine their medical conditions, and discuss the consequences of
missed care. With that information, an inquiry can begin about the
value of increasing the supply of transportation to meet this need in
relation to the health care gains achieved. To address those issues,
two methods were primarily relied on: (a) a thorough investigation
of both the health- and transportation-related literature and (b) an
analysis of data from two nationally representative health surveys.
The analysis was supplemented with queries of the 2001 National
Household Travel Survey (NHTS).
LITERATURE REVIEW
Because many definitions of transportation-disadvantaged individu-
als exist, the literature from the health and transportation sectors can
be used to support differing estimates of the size of the transportation-
disadvantaged population. Much of the literature avoids the term
altogether and instead documents discrepancies in transportation
access associated with socioeconomic, demographic, and geographic
factors. Thus, at one extreme, any household that does not own a
vehicle might be defined as transportation disadvantaged, and that
amounts to 8.3% of all households in the United States (1). Further-
more, 88% of Americans 15 years of age or higher report that they
are drivers, leaving 12% who do not operate personal vehicles for
mobility (2). Examining population subgroups, however, Pucher and
Renne found that 26.5% of households with incomes less than
$20,000 do not own a vehicle (1). They also found that members of
this income group were far more likely to use public transit (4.6% of
all trips compared with an average of 1.7% for all Americans) and
nonmotorized modes (walk or bicycle, 17.0% of all trips compared
with 10.4% for all Americans). Additionally, the Bureau of Trans-
portation Statistics (BTS) reported that households without vehi-
cles also are disproportionately renters, located in urban areas, and
composed of a single person (2). Even when transportation is avail-
able, the demand may exceed the supply of trips, resulting in denied
trip requests. For a paratransit service in southeastern Michigan,
Access to Health Care and
Nonemergency Medical Transportation
Two Missing Links
Richard Wallace, Paul Hughes-Cromwick,
Hillary Mull, and Snehamay Khasnabis
R. Wallace, P. Hughes-Cromwick, and H. Mull, Altarum Institute, 3520 Green
Court, Ann Arbor, MI 48105-1579. S. Khasnabis, Wayne State University, Room
1164, Engineering Building, 5050 Anthony Wayne Drive, Detroit, MI 48202.
Transportation Research Record: Journal of the Transportation Research Board,
No. 1924, Transportation Research Board of the National Academies, Washington,
D.C., 2005, pp. 76–84.
Wallace found that roughly 15% of trip requests could not be
accommodated (3).
Race and ethnicity also are associated with being transportation
disadvantaged. Using data from the NHTS, Pucher and Renne found
that African Americans and Hispanics have lower mobility and use
public transit at higher rates than does the general population (1).
Research has shown that compared with members of the white popu-
lation, 10% to 20% more members of racial minority groups are trans-
portation disadvantaged (4, 5). The Institute of Medicine cited access
issues among several factors explaining why members of minority
groups receive lower quality health care than do nonminorities, even
when there is equivalent insurance coverage (6). Addressing children
specifically, a study commissioned by the Children’s Health Fund
found that 9% of children in families with annual incomes less than
$50,000 miss essential medical appointments owing to transportation,
regardless of their insurance status (7). Other studies have shown that
lack of transportation is a problem even after accounting for insurance
status (8, 9).
Age and location also are important factors in defining the trans-
portation disadvantaged. Although studies have shown that older
adults and residents of rural areas continue to rely on personal vehi-
cles, they often have few, if any, options when a car is not available
(e.g., Americans over 65 make about 90% of their trips by car, and
97% of rural households own at least one car) (10, 11). Rosenbloom
reports that about 40% of rural counties have no public transporta-
tion, and only 14% of rural elderly people have transit service avail-
able within 0.5 mi of their residences (10). Examining one rural
county, Walker found that 40% of patients missed medical appoint-
ments and 28% could not get to a pharmacy because of transporta-
tion barriers (12). In rural areas, distance contributes to lack of access
because medical facilities tend to be farther away from the people
who use them. In one study, patients living more than 20 mi from the
site of care were twice as likely to miss scheduled appointments as
were those living closer (13).
Focusing on the population below age 65 in Dayton, Ohio, Ahmed
et al. found that 16% of respondents reported that finding trans-
portation for medical care was “hard” and another 15% reported that
it was “very hard” (14). Another study found that patients who were
over the age of 50 and whose household income was less than 200%
of the poverty line were nearly twice as likely as all patients above
age 50 to delay care because of transportation issues, time issues, or
both (15). In comparing barriers to care, transportation and time
issues were nearly as important as cost (14.3% versus 18.8%) for the
same transportation-disadvantaged group.
Having a medical condition—thereby increasing one’s need for
medical care—can also contribute to difficulty obtaining transporta-
tion. The 2001 NHTS revealed that 8.6% of respondents reported
having a medical condition that limits their travel, regardless of trip
purpose (2). It also revealed that 9% of Americans over the age of 14
have a “travel-affecting medical condition.” Furthermore, the NHTS
clearly demonstrates that this population makes fewer trips per day
than those without such a medical condition (2.8 versus 4.4 trips per
day). Another study conducted by BTS revealed that 3.5 million
Americans never leave their homes (16). Of these, 1.9 million are
persons with disabilities.
The literature clearly documents problems related to nonemergency
medical transportation (NEMT) in the United States, but it does not
provide a clear estimate of the size of the population that misses
nonemergency medical care or document the most important medical
conditions faced by that population. By using available health care
and other data sources, this paper aims to close that information gap.
Wallace, Hughes-Cromwick, Mull, and Khasnabis 77
NATIONAL HEALTH CARE DATA SETS
The U.S. government maintains several health information sources.
Two of them represent the noninstitutionalized population in the
United States They are the National Health Interview Survey
(NHIS) conducted by the National Center for Health Statistics and
the Medical Expenditure Panel Survey (MEPS) conducted by the
Agency for Healthcare Research and Quality. The NHIS is the most
comprehensive nationally representative assessment of the nation’s
health. For this research, both the 2001 and 2002 NHIS were ana-
lyzed because they were the most recent (the 2002 NHIS data were
released in December 2003). This study annually samples more than
90,000 persons and covers a range of health-related issues. The 2001
MEPS (full-year data for 2001 were released in April 2004) was also
used. The MEPS contains detailed health care utilization and expen-
ditures information on a subset of more than 30,000 individuals
from the NHIS sample. To supplement the use of these national
health care data sets, two nationally representative transportation
data sets were also used—the 2001 NHTS and the 2002 National
Transportation Availability and Use Survey conducted by BTS.
ESTIMATES OF TRANSPORTATION-
DISADVANTAGED POPULATION
An unambiguous estimate of the size of the transportation-
disadvantaged population does not exist. Even the definition of “trans-
portation disadvantaged” varies. The literature review indicates that a
nationally representative estimate of the population that misses med-
ical care because of a lack of transportation is not currently available.
In short, health-related data lack sufficient detail on transportation to
directly measure the number of missed trips, and transportation data
lack sufficient detail on health conditions to address utilization. Fur-
thermore, these studies use independent samples, precluding linking
of data sets. For this research, multiple estimates were made in the
belief that convergence implies reasonableness. To make these esti-
mates, results from a recent BTS study (15) were used and data from
the NHIS and the MEPS were analyzed.
BTS
2002 National Transportation Availability
and Use Survey
BTS conducted the 2002 National Transportation Availability and
Use Survey to investigate the transportation status of Americans with
disabilities and to compare their status with nondisabled Americans.
BTS sampled 5,000 persons (16), and roughly half of them were per-
sons with disabilities (who were oversampled to allow for better sta-
tistical description of this group). This study indicated that 3.5 million
Americans never leave their homes. Of these, 1.9 million are disabled.
Of these, 528,000 “experience transportation difficulties.” That implies
that nearly 1.4 million disabled persons who never leave the home do
not report experiencing transportation difficulties. Presumably, they
could obtain needed transportation if their other problems could be
overcome. Thus, these 528,000 persons can be seen as constituting
the lowest possible estimate of the transportation-disadvantaged
population missing medical trips, because with available trans-
portation, these individuals would have made at least one medical
trip during the year related to their disability. Not surprisingly, the
homebound disabled population of 1.9 million tends to be older
(average age is 66) and more severely disabled (58% report their
disability as severe) than the population at large. As a result, many
of the 528,000 who experience transportation difficulties likely are
missing more than one medical trip per year.
This study also showed that approximately 12.19% of disabled per-
sons either have difficulty obtaining transportation or cannot get the
transportation they need for any purpose. For nondisabled persons,
that is 3.32%. Because approximately 23% of the nation’s 290 mil-
lion people are disabled according to criteria used in this BTS study,
an estimated 15.5 million persons cannot obtain the transportation
they need (regardless of trip purpose). Although an unknown subset
of these 15.5 million people cannot make nonemergency medical trips
because they lack transportation, 15.5 million stands as a maximum
estimate of the population that misses medical care owing to a lack of
transportation. The calculations are as follows:
0.23 ×290 million ×0.1219 =8.13 million persons with
disabilities.
0.77 ×290 million ×0.033 =7.37 million persons without
disabilities.
Total: 15.5 million persons.
U.S. 2002 National Health Interview Survey
With its focus on health care and outcomes, the NHIS addresses trans-
portation in regard to impeding access to care. Thus, the NHIS incor-
porates the concept of transportation disadvantaged (unable to obtain
needed transportation) in the specific context of trips for medical care.
The NHIS contains the following question (posed in expanded adult
and child subsamples): “There are many reasons people delay getting
medical care. Have you delayed getting care for any of the following
reasons in the past 12 months . . . you didn’t have transportation?”
For the 2002 NHIS, the weighted results show that 1.33% of adults
(±0.15% at 95% confidence) reported that they did not have trans-
portation (Table 1). This result is quite consistent for the 5-year period
of 1998 through 2002, as shown in the list below (nonweighted results
from sample sizes of approximately 30,000 per year). The same ques-
tion was asked of children, and the weighted results from the 2002
NHIS for the child sample show that 1.31% of children (±0.24 at 95%
confidence) missed medical care because of a lack of transportation
(Table 1):
1998: 1.78%,
1999: 1.46%,
2000: 1.74%,
2001: 1.75%, and
2002: 1.75%.
With the combined results for adults and children, it was found that
3,702,531 individuals delayed getting medical care in the past year
78 Transportation Research Record 1924
because of transportation difficulties (2,745,947 adults plus 956,584
children), or approximately 3.7 million people. Those numbers
derive from respondents who explicitly link a transportation factor
to delayed care during a specific 1-year period. Delayed care does
not necessarily mean care never received, but with a short reference
period, “delay” and “missed” become equivalent. This distinction is
not pursued in the NHIS.
2001 Medical Expenditure Panel Survey
The MEPS also investigates barriers to care, including transporta-
tion. The questions used to identify transportation barriers, however,
are somewhat different and begin with a basic screening question:
“Anyone have difficulty obtaining care?”
To that question, 11.1% of respondents answered “yes.” Respon-
dents were then given a list of 14 items from which they were asked
to select the main reason for experiencing difficulty. Of these rea-
sons, three are transportation related: (a) medical care too far away;
(b) cannot drive, no car, or no public transportation; and (c) too
expensive to get there. Next the survey gives respondents an oppor-
tunity to cite a secondary reason for missing care. Summing those
responses produces a weighted estimate of 1.21% of the U.S. popu-
lation, amounting to 3.5 million people, who cite a transportation-
related reason (main or secondary response) to explain why they had
difficulty obtaining care. Although people miss care for a variety of
overlapping reasons, this estimate is tightly linked to the intersection
of transportation and difficulty obtaining care.
Summary of Estimates
To summarize, the range of estimates that have been calculated and
compiled for the number of persons who miss medical care because
of a lack of transportation in a year is as follows:
528,000 (BTS),
3,500,000 (BTS),
3,500,000 (MEPS),
3,700,000 (NHIS), and
15.5 million (BTS).
Despite the relatively large range in these estimates—from 0.5
to 15.5 million persons—the two extreme values are known to
understate and overstate, respectively, the size of the population.
Furthermore, the remaining estimates converge, despite deriving
from significantly different estimation approaches. Because of the
closeness of the MEPS and NHIS estimates and their explicit inter-
section of the health and transportation domains, the authors have
most confidence in the estimates arising from these data, particularly
TABLE 1 Lack of Transportation to Medical Care, from 2002 NHIS
Weighted Frequency Percentage of Weighted Frequency Percentage of
Response (adults) Adults (children) Children
Yes 2,745,947 1.33 956,584 1.31
No 201,250,000 97.78 71,615,707 97.78
Refused/NA/don’t know 1,827,604 0.89 397,651 0.55
Total 205,830,000 100.00 72,969,942 100.00
N=31,044 adults, 12,524 children; NA = not ascertained.
for estimating the yearly size of the population of interest, as opposed
to estimating the population at risk from lacking access to nonemer-
gency medical transportation. As a result, it is concluded that approx-
imately 3.6 million Americans (the NHIS and MEPS average) miss at
least one medical trip in a year because of transportation.
To confirm that these 3.6 million individuals reflect the demo-
graphic and socioeconomic conditions documented in the literature
about people who lack transportation access to medical care, the
NHIS adult sample data were queried to compare characteristics of
those who missed care owing to transportation and those who did not.
This analysis shows that the population that missed care because of a
lack of NEMT is
Poorer (54.63% have household incomes below $20,000 per
year versus 17.66% for those who did not miss care owing to a lack
of NEMT),
Older (16.28% age 70 or older versus 11.45%),
Disproportionately female (62.82% versus 51.88%),
Made up of fewer whites (64.6% versus 81.1%), and
Roughly half as likely to have a 4-year college degree.
Thus, the transportation-disadvantaged population that lacks trans-
portation to medical care identified through the NHIS using an NEMT
criterion matches well with the descriptions of the transportation-
disadvantaged population found in earlier studies and discussed in
the literature review. That increases the authors’ confidence that the
estimate of 3.6 million persons who miss medical care because of
transportation is on target.
The split of this population between urban and rural America was
also investigated. The 2002 NHIS currently lacks geographic location
information, so the 2001 NHIS data were considered. The “non-
metropolitan statistical area (non-MSA)” field in the 2001 NHIS
closely matches the “rural” field in the NHTS. Specifically, the 2001
NHIS indicates that 20.73% of adults and 19.99% of children reside
in non-MSA locations, and the 2001 NHTS indicates that 21.9% of
all persons live in rural locations. Thus, the non-MSA category in the
2001 NHIS was used as the operational definition of rural in this
analysis. From this, it was learned that 22.17% (weighted) of the
adults who reported delaying care owing to transportation problems
lived in rural (non-MSA) locations, as did 14.83% (weighted) of the
children. Thus, the percentage of children in rural areas who miss care
owing to a lack of NEMT is well below the overall percentage of rural
children, meaning that children who lack access to medical care
because of transportation reasons are more concentrated in urban
areas. Indeed, the data show that 53.7% of children who missed care
owing to a lack of NEMT live in metropolitan areas of 1 million or
more, whereas only 47.5% of all children live there.
Medical Conditions Affecting People Lacking
Access to Transportation
After the best estimate of the population that misses medical care in
a year for transportation reasons was determined, the medical con-
ditions faced by members of this population of about 3.6 million
people were determined. Again the 2002 NHIS data set was used,
and the conditions reported by respondents identified as delaying
care for transportation-related reasons were investigated. Because
of the structure of the data sets, adults and children were analyzed
separately.
Wallace, Hughes-Cromwick, Mull, and Khasnabis 79
Adult Disease Conditions
Table 2 presents a comprehensive, alphabetical list of medical con-
ditions for individuals who also reported difficulties accessing care
because of transportation problems and it reports the weighted per-
centage of these transportation-disadvantaged adults experiencing
the condition in question.
It was found that two comparisons between adults who miss med-
ical care for transportation-related reasons and those who do not are
instructive:
1. There is a great difference in the percentage of adults experi-
encing multiple conditions from this list (92% for those missing care
versus 64% for those who do not); the difference in the percentage
who experienced none of these conditions is also substantial (3% for
those who miss care versus 21%).
2. For each condition (except for “no conditions”), the prevalence
is higher for those who miss care than for those who do not. Table 3
shows that for highly prevalent conditions.
The ratios in Table 3 illustrate that these conditions disproportion-
ately affect the population that misses medical care. Furthermore, they
demonstrate that, in addition to physical conditions, mental health is
an important concern for this population. Not only do 49.7% of the
adults who miss care report experiencing depression, close to one-
third mention excessive sleepiness; nearly 50% note insomnia; and
5% or more report each of the “feeling” categories of “hopeless,”
“nervous,” “restless or fidgety,” “sad,” and “worthless.” Moreover,
these related mental health conditions correlate highly with other
conditions, again demonstrating the prevalence of comorbidities.
Distribution of Conditions for Adults by Location
The geographic distribution of individuals by transportation status and
medical condition was also analyzed. Although this analysis needs
to be expanded, it was found that a higher than expected prevalence
of diabetes, heart disease, and hypertension for urban, transportation-
disadvantaged adults was coupled with a lower than expected
prevalence of diabetes, heart disease, and hypertension for urban,
nontransportation-disadvantaged adults. The percentages for
transportation-disadvantaged adults residing in urban areas are as
follows: diabetes (82.8%), heart disease (79.2%), and hypertension
(80.5%). These numbers represent the percentages of the disadvan-
taged adults with each disease who live in urban locations and can
be compared with the overall figure of 77.8% of transportation-
disadvantaged adults who are urban residents. Conversely, a lower
than expected prevalence of diabetes (75.1%), heart disease (75.2%),
and hypertension (76.0%) was found for urban, nontransportation-
disadvantaged adults. These percentages can be compared with the
79.3% of nondisadvantaged adults in urban locations. For a summary
measure of these comparisons, an index was computed that divides
the urban, transportation-disadvantaged share for each health condi-
tion by the urban share for those without transportation difficulties.
The index numbers are as follows: diabetes (1.10), heart disease
(1.05), and hypertension (1.06). By contrast, the index for renal
disease is 0.94.
Child Disease Conditions
For children who miss care because of transportation problems, the
analysis produces results similar to those for adults. Table 4 presents
80 Transportation Research Record 1924
sus 14% for children who do not miss care) and the percentage expe-
riencing none of the listed conditions (39% for children who miss
care versus 57% for children who do not). In each case, the preva-
lence of the conditions is higher for children who miss care because
of transportation problems. For the high-prevalence conditions, the
percentages are as follows:
ADHD or ADD (9.4% for children who miss care versus 5.5%
for those who do not),
Asthma (24.4% versus 12.4%),
Frequent headaches (12.8% versus 5.3%),
Colds (32.2% versus 20.5%), and
Learning disabilities (11.7% versus 6.5%).
Summary from Analysis of Critical
Medical Conditions
By combining the results of the analyses above, the primary medical
conditions (or care needs) affecting those adults and children who lack
access to NEMT were identified. These primary conditions and needs
were defined as those that have particularly high prevalence for the
population that misses care, have disproportionate prevalence among
those who miss care, or are amenable to cost-effective amelioration
via improved transportation access. These conditions and needs are as
follows:
Obstetrical care (including prenatal, delivery, and postnatal care),
Cancer treatment and screening,
Screening for high cholesterol levels,
Screening for high blood pressure and hypertension treatment,
Arthritis,
Asthma,
Chronic obstructive pulmonary disease (COPD),
Dental problems,
Depression and mental health,
Diabetes,
Renal disease,
Heart disease,
Medical allergies,
Pain or aching joints,
Poor circulation, and
Vision problems.
CONSEQUENCES OF UNMET
TRANSPORTATION NEEDS
For both the adult and child samples, the analysis of the NHIS reveals
extensive comorbidities and a much higher prevalence of conditions
for individuals who miss care because of transportation problems
compared with those who do not miss care because of transportation
problems. This general finding has important implications for the con-
sequences of missed care. Transportation-disadvantaged status that
results in missed trips will potentially exacerbate the diseases and
may result in costly subsequent medical care (specialist visits, emer-
gency room visits, and possibly hospitalizations). Even when the
potential to decrease subsequent utilization by more prompt care of
an existing condition does not exist, quality-of-life concerns remain
evident and important. For example, the prevalence of frequent
headaches is more than twice as high for children who miss care
TABLE 2 Medical Conditions Experienced by Adults Who Lack
Transportation to Medical Care
Medical Unweighted Frequency of Weighted Percent of
Condition Adults with Condition Adults with Condition
Arthritis 235 40.0
Asthma 113 22.1
COPD 101 17.6
Cancer 60 11.3
Dental problems 157 28.0
Depression 280 49.7
Diabetes 96 16.0
ESRD 37 7.2
Excessive sleepiness 176 35.2
Food or odor allergies 97 17.8
Gynecologic problems 55 8.8
Hay fever 72 12.5
Hearing aid needed 35 6.8
Heart disease 167 29.6
High cholesterol 146 25.7
Hypertension 233 37.7
Insomnia 258 49.4
Irritable bowel syndrome 84 12.9
Liver condition 35 6.7
Medication allergies 130 23.2
Menopausal problems 40 6.5
Menstrual problems 73 13.1
Multiple sclerosis 6 1.2
Neuropathy 18 3.1
Pain or aching joints 304 55.8
Parkinson’s disease 2 1.4
Poor circulation 158 26.8
Prostate 3 0.5
Recurring pain 261 48.2
Seizures 42 7.5
Severe sprains 99 20.0
Sinusitis 101 16.9
Skin problems 120 21.4
Stroke 44 8.1
Thyroid problems 71 11.7
Ulcer 110 19.6
Urinary problems 119 20.8
Vision problems 219 37.5
Feelings
Hopeless 30 5.8
Nervous 45 8.5
Restless or fidgety 41 8.8
Sad 28 5.2
Worthless 26 4.8
N =537 adults; ESRD =end-stage renal disease.
an alphabetical list of the conditions for these children, including the
weighted percentage of children citing these conditions. The pattern
of comorbidities (multiple, simultaneous conditions) and condition
prevalence matches that found for adults. For comorbidities, the
results show a large difference for both the percentage experiencing
multiple conditions from the list (32% for children who miss care ver-
Wallace, Hughes-Cromwick, Mull, and Khasnabis 81
TABLE 3 High-Prevalence Medical Conditions for Adults, from 2002 NHIS
Prevalence in Population That Prevalence in Population That
Misses Care Due to Does Not Miss Care Due to
Medical Condition Transportation Problems (%) Transportation Problems (%) Prevalence Ratio
Arthritis 40.0 20.5 1.9
Asthma 22.1 10.5 2.1
COPD 17.6 5.3 3.3
Cancer 11.3 6.9 1.6
Depression 49.7 15.2 3.3
Dental problems 28.0 12.4 2.3
Diabetes 16.0 6.4 2.5
Heart disease 29.6 15.5 1.9
High cholesterol 25.7 20.5 1.3
Hypertension 37.7 24.0 1.6
Irritable bowel 12.9 5.4 2.4
Medication allergies 23.3 12.9 1.8
Pain or aching joints 55.8 29.1 1.9
Poor circulation 26.8 8.3 3.2
Recurring pain 48.2 17.7 2.7
Severe sprains 20.0 8.1 2.5
Skin problems 21.4 8.5 2.5
Vision problems 37.5 16.1 2.3
N =537 transportation disadvantaged (TD), 30,223 non-TD.
TABLE 4 Medical Conditions Experienced by Children Who Lack
Transportation to Medical Care
Unweighted Frequency of Weighted Percentage of
Medical Condition Children with Condition Children with Condition
ADHD or ADD 17 9.4
Anemia (past 12 months) 1 0.6
Arthritis 1 0.6
Asthma 44 24.4
Autism 1 0.6
Cerebral palsy 1 0.6
Depression 1 0.6
Ear infections 7 3.9
Eczema or skin allergies 5 2.8
Food or digestive allergies 3 1.7
Frequent diarrhea or colitis 6 3.3
Frequent headaches or migraines 23 12.8
Hay fever 4 2.2
Head or chest cold (past 2 weeks) 58 32.2
Heart disease 4 2.2
Learning disability 21 11.7
Mental retardation 4 2.2
Muscular dystrophy 1 0.6
Other developmental delay 1 0.6
Respiratory allergies 4 2.2
Seizures 2 1.1
Sickle cell anemia 1 0.6
Stutters or stammers 12 6.7
Vision problem 14 7.8
N =180; ADHD/ADD =attention deficit hyperactivity disorder/attention deficit disorder.
because of transportation problems than it is for other children. To the
extent that medical visits are being delayed for these transportation-
disadvantaged children, they could be subject to considerable pain
and suffering that otherwise could be effectively treated.
The effects of not obtaining needed nonemergency medical care
because of transportation barriers on the health of affected persons
depend, to some extent, on whether the missed care was preventive
or for treatment for an existing condition. In the preventive arena,
lack of transportation can lead to underimmunization (17), difficul-
ties in administering screening programs (18), failure to attend pedi-
atric checkups (19), and lack of prenatal care for poor women (9, 20).
For chronic problems, numerous studies have documented a lack
of care because of transportation barriers. Conover and Whetten-
Goldstein, for example, found that 16.7% of AIDS and HIV patients
reported difficulties in obtaining transportation and as a result were
much less likely to have a primary care physician or to obtain regu-
lar care (21). For people with diabetes, a recent study revealed that
those who missed more than 30% of scheduled appointments expe-
rienced worse health outcomes than those who attended more often
(22). Additionally, patients with asthma entering the emergency
room were much less likely to obtain follow-up care if they did not
have access to transportation (23–25).
DISCUSSION AND CONCLUSIONS
The United States makes a substantial investment to provide access
to medical services for transportation-disadvantaged people. In
addition to the services offered by public transportation providers
(paratransit and otherwise), other sources of transportation serve the
needs of the transportation disadvantaged; indeed, 62 federal pro-
grams offer funding for such travel (26). Much of that service is part
of the Medicaid program with a patchwork of van services, taxis,
ambulance services, and so forth. In many regions, brokerage services
or state or local agencies have been established to match riders with
available transportation services. In all cases, operators face the
challenge of optimizing the use of available transportation to meet
a growing trip demand. Studies from Kentucky (27), Georgia (28),
Connecticut (29), and North Carolina (30) have shown that factors
such as computer-aided scheduling and tight controls on eligibility
can increase the capacity of available service by reducing average trip
length, transporting multiple passengers simultaneously, and reduc-
ing the number of ineligible trips. In that way, average trip cost is
reduced and more trips can be provided with fixed resources.
The findings of this paper demonstrate that, despite these existing
transportation resources, millions of Americans still lack adequate
access to NEMT. In urban and rural areas, many public transportation
routes do not provide access to medical care, especially for the most
economically disadvantaged neighborhoods (31). Of patients riding
public transportation to get medical care in one recent study, 86%
reported missing an appointment because of transportation, and 95%
reported arriving late, as compared with 27% and 43%, respectively,
among patients with cars (32). On the basis of interviews with visitors
to a pediatric clinic at a large, urban hospital, this study also found that
60% of respondents had previously missed or arrived late for an
appointment because of transportation difficulties. In another study,
patients diagnosed with asthma were found to be much less likely to
return for a follow-up appointment with a primary care physician if
they relied on public transportation, friends, or walking to appoint-
ments than were patients with their own cars (23). Older adults are
82 Transportation Research Record 1924
also affected. Of adults over age 65, there are 21% who no longer
drive; these adults reported 15% fewer trips to the doctor compared
with elderly people who still drive (33).
This research shows that the transportation-disadvantaged popula-
tion that missed medical care because of transportation barriers
includes about 3.6 million individuals who miss at least one medical
trip over the course of 1 year. Compared with the rest of the U.S. pop-
ulation, this population has (a) a higher prevalence of every medical
condition that was examined and (b) a far greater prevalence of
comorbidities. There is evidence that disease severity is also higher
across the respective conditions for the affected population. Further-
more, this population is poorer and older, contains more females and
fewer whites, and is less educated than the rest of the population.
Although this analysis attempts to directly connect the disparate
transportation and health disciplines using the best available data
sets—specifically how many individuals missed health care because
of a lack of transportation—it undoubtedly underestimates the over-
all population at risk of having transportation problems affecting
access to health care. That is due to persistence—the dynamics of
health care utilization for a given population. In general, health care
utilization varies considerably over time, though greater persistence
is expected for the transportation-disadvantaged population because
of the higher prevalence of chronic conditions and a higher rate of
comorbidities (34). Nevertheless, although many of the 3.6 million
people will fall into the transportation-disadvantaged group that
misses care in a succeeding year, many will not. Others will cer-
tainly take their place when they unexpectedly require medical care,
and this year-to-year variation suggests an overall transportation-
disadvantaged population with health risks greater than 3.6 million.
Indeed, it was found that potentially as many as 15.5 million people
are at risk for missing care because of transportation barriers in a
given year, even though nearly 12 million of these either did not
need care in the study year or managed to obtain transportation when
it was needed, despite difficulties in doing so.
This analysis of conditions reveals that, even for large-scale and
nationally representative studies such as NHIS and MEPS, the process
of analyzing data at the condition level raises substantial concerns
over sample size. Although the results above convincingly demon-
strate the problem of transportation disadvantage vis à vis disease con-
ditions in the aggregate, the respective sample sizes of those who miss
or delay care for transportation reasons are small to begin with
(e.g., 537 adults in 2002 according to the NHIS) and become dra-
matically smaller at the condition level. This presents a difficulty for
analysts and policymakers interested in examining the costs and ben-
efits of providing missed transportation. (Recent research, employing
a comprehensive framework of health care access for low-income
individuals, failed to mention transportation at all. (35))
The authors are confident in the estimate of 3.6 million transporta-
tion-disadvantaged individuals who annually miss care because of
transportation barriers, but believe that estimating the number of trips
and associating these trips with particular conditions strains the relia-
bility of the data sources. To close that gap, it is recommended that
specific transportation follow-up questions be added to the NHIS and
MEPS via a special supplement that leverages the richness of the
existing health care information and provides enough transportation
detail so that researchers can more fully investigate the transportation
disadvantaged and missed health care. Careful consideration is
needed to establish sample sizes, and the supplement might need to
focus on a subset of the primary conditions identified here so that sta-
tistical analyses have sufficient power. Furthermore, the next round
of the NHTS could include additional questions on access to medical
care to further close the data gap. Other data sources can be used to
enhance the knowledge of diseases and comorbidities associated
with those experiencing transportation difficulties; however, only
these national data sets, appropriately modified, can provide reliable
estimates for national policy development.
For affected individuals, the consequences of missed health care
are more important than missing data. Consequences range from
quality-of-life concerns, such as the large proportion of transportation-
disadvantaged people who experience pain or aching joints, up
to life-threatening consequences, such as the importance of consis-
tent care for the high percentage of transportation-disadvantaged
children with asthma. An emerging perspective in the health arena
promotes evidence-based medicine and emphasizes that integrated
disease management has the potential to reduce health expenditures,
lower mortality, and increase quality of life (36). Transportation-
disadvantaged persons, however, are poor candidates for well-
managed care protocols that are based on frequent checkups to avoid
costly specialist care and unnecessary hospitalizations. Therefore, a
clear need is seen for cost-effectiveness analyses that investigate
transportation interventions to determine their effects on increas-
ing compliance with demanding care protocols for well-chosen
(i.e., amenable to successful treatment) conditions. Many conditions
faced by the roughly 3.6 million people that have been identified
(e.g., asthma, heart disease, and renal disease) can be managed if
appropriate care is made available. The authors have begun to use a
method to conduct these cost-effectiveness calculations. In essence,
it uses the literature to distinguish well and poorly managed care by
condition and then applies these designations to the MEPS expendi-
ture estimates. The difference in average expenditures between
poorly and well managed individuals, by condition, can then be used
as a proxy for the benefits that might be realized if improved trans-
portation access enables disadvantaged individuals to access better
health care. From this preliminary work, based on study of asthma
and heart disease, great potential has been found for net societal ben-
efits accruing from improving the quality of life of this transportation-
disadvantaged population by increasing its access to NEMT.
ACKNOWLEDGMENTS
The authors thank the Transportation Research Board for its support
of this work via TCRP Project B-27. The authors also thank Casey
Kangas, James Lee, and James Bologna of the Altarum Institute for
their assistance in this work.
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    Introduction: Accessing care is challenging for adults with chronic conditions. The challenge may be intensified for individuals needing to travel long distances to receive medical care. Transportation difficulties are associated with poor medication adherence and delayed or missed care. This study investigated the relationship between those traveling greater distances for medical care and their utilization of programs to prevent and/or manage their health problems. It was hypothesized that those traveling longer distances for medical care attended greater chronic disease management programs. Methods: Thirty six thousand households in nine counties of central Texas received an invitation letter to participate in a mailed health assessment survey in English or Spanish. A total of 5230 participants agreed to participate and returned the fully completed survey. To investigate distance traveled for medical services and participation in a chronic disease management program, the analyses were limited to 2108 adults aged ≥51 years with one or more chronic conditions who visited a healthcare professional at least once in the previous year. Other variables of interest included residential rurality, health status, and personal characteristics. The data were first analyzed using descriptive and bivariate analyses. Then, an ordinal logistic regression model was fitted to identify factors associated with longer distances traveled to medical services. Additionally, a binary logistic regression model was fitted to identify factors associated with attending a chronic disease self-management program. Results: Among 2108 adults, rural participants (p<0.001), those with more chronic conditions (p<0.001), and those attending a chronic disease program (p=0.037) reported traveling further distances to medical services. Participants with limited activity (p<0.001), those from urban counties (p=0.017), and those who traveled further (p=0.030) were more likely to attend a chronic disease program. Conclusion: While further distances to healthcare providers was found to be a protective factor based on the utilization of community-based resources, rural residents were less likely to attend a program to better manage their chronic conditions, potentially choosing to use long distance travel to address urgent medical needs rather than focusing on prevention and management of their conditions. Important policy and programmatic efforts are needed to increase reach of chronic disease self-management programs and other community services and resources in rural areas and to reduce rural inequities.
  • Article
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    The commute well-being (CWB) has been associated with the mental health and depends on the positive or negative emotions that occur during the daily commute. This paper analyzes the influencing factors and discusses the structural relationship between CWB and influencing factors, based on our evaluation of the results for daily CWB between different travel modes. We based our analyses on a CWB survey conducted in the central city proper of Xi’an. In contrast to previous studies, this paper investigates two commuting phases, in the morning and evening, to better analyze daily CWB. To conduct a more comprehensive analysis, in addition to considering multi-stage combined travel, the subjective and objective aspects of factors influencing CWB were deepened and expanded. The measurement was based on the Satisfaction with Travel Scale, which was developed based on a method for measuring subjective well-being. The average CWB level of each model was compared by analyzing the variances. The influencing factors were determined by stepwise regression, and the influence mechanism was analyzed using a structural equation model (SEM). The results indicate that CWB in Xi’an was highest for walking, which was followed, in order, by motorcycle, electric bicycle, staff shuttle bus, bicycle, metro, car, taxi, and bus. The result reflects that commuting by bus is associated with more negative emotions in Xi’an. The results of SEM indicate that the built environment does not directly affect CWB, but it will act on CWB by affecting other factors. The travel attitude, commute mode choice, and other travel characteristics affect each other and affect CWB directly and indirectly. Other travel characteristics has the largest total effect on CWB, and the travel attitudes have the largest direct effect. Without considering the travel attitude, reducing traffic congestion, commuting time, and transfer times can significantly improve CWB and reduce negative emotions in the future in Xi’an.
  • Article
    Transportation disadvantage may have important implications for the health, well-being, and quality of life of older adults. This study used the 2015 National Health Aging Trends Study, a nationally representative study of Medicare beneficiaries aged 65 and over ( N = 7,498), to generate national estimates of transportation modalities and transportation disadvantage among community-dwelling older adults in the United States. An estimated 10.8 million community-dwelling older adults in the United States rarely or never drive. Among nondrivers, 25% were classified as transportation disadvantaged, representing 2.3 million individuals. Individuals with more chronic medical conditions and those reliant on assistive devices were more likely to report having a transportation disadvantage ( p < .05). Being married resulted in a 50% decreased odds of having a transportation disadvantage ( p < .01). Some individuals may be at higher risk for transportation-related barriers to engaging in valued activities and accessing care, calling for tailored interventions such as ride-share services combined with care coordination strategies.
  • Article
    Objective: This study, designed to avoid methodologic limitations of previous research, aimed to identify the important noninsurance barriers to timely prenatal care. Methods: We identified a subsample of a cross-sectional statewide representative postpartum survey conducted in California during 1994–1995, focusing on 3071 low-income women with Medi-Cal or private coverage throughout pregnancy. Results: Twenty-eight percent of those women had untimely care, although only 6% were unaware of their pregnancies during the first trimester. Controlling for numerous sociodemographic factors; knowledge, attitudes, beliefs, and behaviors; stressful life circumstances; and logistic obstacles that might deter seeking or receiving care, the following risk factors for untimely care were significant and experienced by more than one fifth of women: unwanted or unplanned pregnancy (affecting 43% and 66% of women, respectively), no regular provider before pregnancy (affecting 22% of women), and no schooling beyond high school (affecting 76% of women). Transportation problems, affecting 8% of women, appeared to be the only significant logistic barrier to timely care. Conclusion: Improving timeliness of prenatal care among low-income women with third-party coverage is likely to require broad social and health policies that focus on factors affecting women before pregnancy. Assistance with transportation could contribute to more timely care for some low-income women, but programs focusing primarily on other noninsurance barriers during pregnancy might not substantially improve the timeliness of care, at least among low-income women with third-party coverage. Although the optimal content and number of prenatal care visits are unknown, few would question the importance of at least one prenatal care visit during the first trimester for timely risk assessment and health promotion, particularly among women at high medical or social risk.1–3 Health objectives for the nation include the goal of first-trimester initiation of prenatal care among at least 90% of pregnant women.4 High rates of delayed prenatal care among women who have Medic-aid coverage5–7 or are otherwise eligible for free care8 have led to concerns about barriers to care apart from lack of insurance or ability to pay, referred to here as noninsurance barriers. Many such barriers have been cited in the literature, including problems with child care or transportation; conflicts with work or school schedules; lack of belief in the importance of prenatal care or lack of knowledge that care should begin in the first trimester; negative perceptions or fear of health care providers or services; unplanned or unwanted pregnancy; denial, concealment, or lack of awareness of pregnancy; and emotional stress or family or personal problems.1,9–11 However, because of methodologic weaknesses, previous published studies have provided insufficient evidence to guide policy. Birth certificate and Medicaid data have been used to study prenatal care use,5,7,8,12,13 but those sources generally lack information on income, insurance, or noninsurance barriers. Many studies have examined noninsurance barriers using either convenience samples at one or a few clinical sites14–21 or random samples in a single city or county,22,23 but they might not be generalizable. Several studies have described the prevalence of barriers, without ascertaining how the reported barriers were related to actual use of care.11,24 Few studies have distinguished women with Medicaid coverage before pregnancy from those who first become eligible during pregnancy, although the nature or magnitude of their noninsurance barriers could differ. Although different factors can influence the initiation of prenatal care and subsequent recommended visits,25 most studies have used composite indices that do not distinguish between initiation and continuation of care.11,17–22,26 Of the three studies that looked specifically at first-trimester initiation,14,27,28 two were population-based27,28; those studies examined only two or three potential noninsurance barriers apart from demographic characteristics, and one27 had a low (48%) response rate. Given these limitations, we conducted this study in California to learn which of the many noninsurance barriers suggested by the literature should receive priority in developing policy and programs. To identify barriers apart from lack of insurance, we focused on low-income women with continuous third-party coverage for prenatal care because earlier analyses found that untimely care was rare among higher-income women.29
  • Article
    Accessible Raleigh Transportation (ART), a local, ordinance-based, complementary paratransit service, provides subsidized service for those unable to drive because of a disability and those unable to ride a bus. ART relies on Raleigh's open-door taxicab licensing policy established by city ordinance. No contract is required to manage the program or operate the service. ART has successfully provided paratransit service for more than 10 years in a fast-growing, highly suburbanized city of 280,000. ART's Americans with Disabilities Act paratransit element, Tier II, adheres strictly to trip-by-trip eligibility using a functional screening tool. The use of eligibility determination and the user-side subsidy points to a new direction for public transportation.
  • Article
    Because of the arrival of advanced public transportation systems (APTS) and other changes in the transit environment, the study of the paratransit customer deserves increaed attention. Demographic and other characteristics of paratransit customers in southeastern Michigan are presented, and the development of a casual model of the factors affecting customer satisfaction with the paratransit service is begun. Such models, which analyze the covariance structures variables and factors hypothesized to exhibit causal relations, can help researchers and transit operators gauge the potential of improving customer satisfaction through system changes, such as the addition of APTS. Furthermore, these modles can suggest which elements of customer satisfaction are most affected by specific system changes. A key finding from the modeling effort is that characteristics specific to the customers, such as personal mobility, contribute substantially toward explaining customer satisfaction.The casual modeling also revealed that transit system charactersistics contribute substantially to customer satisfaction, too, especially to customer satisfaction with the trip reservation process. Thus, system enhancements, such as APTS, have ample potential to increase customer satisfaction. Finally, directions for future research aimed at improving and enhancing the developed casual model are discussed and recomended, including specification of the data needs of such research.
  • Article
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    The 2001 National Household Travel Survey (NHTS) confirms most of the same travel trends and variations among socioeconomic groups documented by its predecessors, the Nationwide Personal Transportation Surveys (NPTS) of 1969, 1977, 1983, 1990, and 1995. The private car continues to dominate urban travel among every segment of the American population, including the poor, minorities, and the elderly. By comparison, public transport accounts for less than 2% of all urban travel. Even the lowest-income households make only 5% of their trips by transit. The most important difference in the 2001 NHTS is the doubling in modal share of walk trips in cities, due to a much improved survey technique that captured previously unreported walks. While the private car dominates travel, there are important variations in auto ownership and travel behavior by income, race, ethnicity, sex, and age. Overall, the poor, racial and ethnic minorities, and the elderly have much lower mobility rates than the general population. Moreover, the poor, blacks, and Hispanics are far more likely to use transit than other groups. Indeed, minorities and low-income households account for 63% of the nation's transit riders. Different socioeconomic groups also have different rates of carpooling, taxi use, bicycling, and walking. In addition, they travel different distances and at different times of day. Many of these socioeconomic variations in travel behavior have important consequences for public policy.
  • Article
    Full-text available
    This article uses data from the 2001 National Household Travel Survey to compare travel behavior in rural and urban areas of the United States. As expected, the car is the overwhelmingly dominant mode of travel. Over 97% of rural households own at least one car vs. 92% of urban households; 91% of trips are made by car in rural areas vs. 86% in urban areas. Regardless of age, income, and race, everyone in rural areas relies on the private car for almost all travel needs. Mobility levels in rural areas are generally higher than in urban areas. That results from the more dispersed residences and activity sites in rural areas, which increase trip distances and force reliance on the car. Somewhat surprisingly, the rural elderly and poor are considerably more mobile than their urban counterparts, and their mobility deficit compared to the rural population average is strikingly less than for the urban elderly and poor compared to the urban average. Data limitations prevented a measurement of accessibility, however, and it seems likely that rural areas, by their very nature, are less accessible than urban areas, especially for the small percentage of car-less poor and elderly households .
  • An understanding of perceived barriers to health-care is critical to improving healthcare access for all Americans. To determine perceived barriers to health-care in an urban poor population in Dayton, Ohio, a face-to-face door-to-door survey of individuals identified through targeted, stratified, area probability sampling was done. A sample of 413 non-elderly poor adults, including 19% without telephones, reported personal relevance of various barriers to healthcare access. Most frequently endorsed barriers were lack of information about free or reduced-cost health-care, anticipated cost, and difficulty accessing child-care. Seventy-four per cent of respondents reported more than one barrier. Individuals without telephones and those without health insurance reported more barriers to health-care. Reported barriers were similar for working and non-working poor, except for transportation problems, more frequently reported by non-working respondents. This study provides important data on what poor people in a medically underserved community perceive to be barriers to accessing health-care and underscores the importance of including people without telephones in the study design. Respondents who did not have telephones were more likely to report multiple barriers, particularly problems with lack of information about free or discounted medical care, child-care, and transportation. These findings suggest the importance of door-to-door surveys rather than telephone surveys for getting accurate data on the poor.
  • Article
    This paper makes recommendations for public policy. It states that public policy discussions assume that elderly people need government assistance or they require little governmental attention. Older Americans, however, lead complicated lives. They drive but still face mobility barriers, or have physical or medical problems but still seek an active community life. The elderly are a significant and growing component of many transportation issues including metropolitan decentralization, air pollution, environmental degradation, and congestion. This paper suggests that the elderly’s mobility needs create societal problems to which they contribute, and that policymakers must respond with refocussed and redirected public policies. [Country: USA]
  • Article
    The demographics of the United States will change dramatically during the next 25 years as more baby boomers reach their 60s, 70s and beyond. The U.S. Census Bureau projects that the number of Americans age 65 or older will swell from 35 million today to more than 62 million by 2025 - nearly an 80 percent increase. As people grow older, they often become less willing or able to drive, making it necessary to depend on alternative methods of transportation. Unfortunately, the United States is currently ill prepared to provide adequate transportation choices for our rapidly aging population. Alternatives to driving are sparse, particularly in some regions and in rural and small town communities. As the number of older people increases, so too will their mobility needs. How the nation addresses this issue will have significant social and economic ramifications. This report presents new findings based on the National Household Transportation Survey of 2001 and places them in the context of other research on mobility in the aging population.
  • Article
    Failure to attend the first newborn health supervision visit is an important problem for the Continuity Care Clinic of Children's Hospital Medical Center of Akron, Ohio. The goal of this study was to use objective data from the neonatal record to identify newborns at high risk of failure to attend. Clinical and social risk factors of the mother and newborn were abstracted from the neonatal progress notes of 319 infants. The relative risk (RR) of nonattendance was calculated for each factor, and rules for predicting failure to attend were evaluated. The best predictors were multiparous mother (RR = 2.4, P = .01), no telephone in home (RR = 2.6, P = .002), and unmarried teenage mother (RR = 5.8, P = .05). Newborns who had a medical problem and had a adult mother were more likely to attend (RR = 0.4, P = .02). These risk factors were easily identifiable from the medical record at birth. Because interventions may be labor-intensive, it is important to target the families at the highest risk.