Results
There are 196 observations for each variable in our analyses of State data
(observations for 49 States at four points in time), and Table 2 presents
a list of the variables and their respective means. The average number of
active, non-Federal physicians practicing per 100,000 residents in each State
was 208, and the average percent of the population in each State over the
age of 65 is 13 percent. The average unemployment rate is 5.53 percent, and
the average number of beds per 1,000 residents is 4.03.
Observations from each of the four time periods in our analyses (1985, 1990,
1995, and 2000) from each of the 49 States in our sample were combined to
estimate the impact of State laws that limit payments in malpractice cases
on physician availability. Table 3 presents the estimates of the coefficients
of each variable derived using ordinary least squares estimation techniques.
The coefficients of the independent variables in the equation were estimated
using 196 observations, and the independent variables explain 52 percent of
the variation between the square of the difference between the estimated and
actual value of the dependent variable.
All variables entered the equation with the expected signs, and all but one
were statistically significant at a 95-percent confidence level. The coefficient
for States with a cap on damage awards in malpractice cases is about 24 (Table 3). This implies that States with a cap average 24 more physicians per 100,000
residents than States without such a cap. Thus, States with caps have about
12 percent more physicians per capita than States without a cap (12% = 24/208).
The coefficient for the variable measuring the proportion of the population
65 years of age or older in Table 3 indicates that States with a greater proportion
of elderly citizens have more physicians. For each percentage-point increase
in the age variable, the number of physicians per 100,000 residents increased
by about 5. Thus, we would expect Florida, which averaged 18.5 percent of
its population 65 years of age or above, to have about 42 more physicians
per 100,000 residents than Georgia, which averaged 10.2 percent of its population
age 65 or older over the four time periods.
Table 3 also shows that a 1-percentage-point increase in the unemployment
rate was associated with a decrease in over 6 physicians per 100,000 residents,
and that a 1-percentage-point increase in the proportion of a State's domestic
product attributable to farm activities was associated with a decrease of
about 5 physicians per 100,000 residents. Income was positively related to
physician availability as hypothesized, and an increase of $1,000 per year
in income was related to an increase of slightly more than 1 physician per
100,000 residents.
Population density as measured by the number of residents in thousands per
square mile was also positively related to physician supply as anticipated,
and an increase of 1,000 residents per square mile in a State was associated
with an increase of about 17 physicians per 100,000 residents.
Table 4 presents estimates of coefficients after including dummy variables
for three of the four time periods (1990 is the reference time period). This
model also was estimated using the ordinary least squares regression technique,
and the coefficients for each of the three nonreference time periods were
statistically significant. Nevertheless, the size and sign of the coefficient
for the variable for States with a law capping damage awards were still positive,
statistically significant, and of similar magnitude as that in the model with
time variables.
Indeed, the magnitude of the coefficient for the damage caps variable was
robust across a diversity of models. In each of four equations that was estimated
using data from a single time period (results not reported here), the coefficient
for the damage cap variable was positive and was only slightly less than the
coefficient in the combined runs. Furthermore, the coefficients were statistically
significant in three of the four equations.
We also estimated our model setting the independent variable for caps equal
to 1 only for States listed in a 2003 report by the U.S. Department of Health
and Human Services with a cap on noneconomic damage awards of less than $350,000
(California, Hawaii, Indiana, Michigan, Montana, New Mexico, North Dakota,
South Dakota, Utah, and Wisconsin)41
and zero otherwise. We then estimated our model where the dummy variable
was equal to 1 for the other nine States with a cap on malpractice damage
awards above $350,000 (Colorado, Idaho, Kansas, Louisiana, Maryland, Massachusetts,
New Mexico, Virginia, West Virginia) and zero otherwise. We found the coefficient
for the cap variable in each of these models to be positive, but it was statistically
significant only in the model where the dummy variable was equal to 1 for
States with a cap on noneconomic damages of less than $350,000.
Variables with coefficients that are not statistically significant are considered
to have effects that are not distinguishable from a zero-effect. Thus, a
State that passes legislation capping payments for noneconomic damages in
malpractice cases at relatively high levels might not realize an increase
in the number of physicians practicing in the State.
Ohio, Oregon, and Texas had provisions that set limits on noneconomic damages
in malpractice cases that were struck down by their State Supreme Court, and
these limits were in effect for more than 4 years.a
We estimated our State data model setting our cap variable equal to 1 during
the time periods the State law capping noneconomic payments in malpractice
cases was in effect for Ohio, Oregon, and Texas in addition to setting it
equal to 1 for our original 19 States. The coefficient for the cap variable
remained positive, significant, and of similar magnitude.
While the State data provided a picture of liability caps over the years
1985, 1990, 1995, and 2000, we next used county data to provide a finer, more
detailed analysis of the final 5-year period: 1996-2000. Table 5 presents
the means of each of the variables used in our analyses based on 14,640 observations
from county data over the 5 years from 1996 through 2000.
The average number of physicians per 100,000 population was 117 over this
time period. This figure is significantly lower than the 208 physicians per
100,000 that we found in our analyses of State data from 1985, 1990, 1995,
and 2000. The reason for this is that most counties are rural with a low number
of doctors; and since each county has equal weight in the county analysis,
the average number of doctors per 100,000 population across all counties (117)
is lower than the average number of doctors across all States (208), which
is skewed upward by the highly populated metropolitan areas of the State.
Table 1A lists the number of physicians per 100,000 county residents State
by State for States that had caps in the year 2000. In contrast, Table 1B
lists the number of physicians per 100,000 county residents State by State
for States that either did not have caps or had their caps overturned in court.
Table 5 shows that about 10 percent of all counties had a hospital that operated
a residency training program, and the average unemployment rate was 5.3 percent.
About 22 percent of counties had a high HMO enrollment rate (i.e., an HMO
penetration rate greater than 30 percent).
Table 6 presents results using county data for the years 1996 through 2000.
The coefficient for the variable of interest is 13.65. That is, counties
in States without caps have 111.83 doctors per 100,000 population, while counties
in States with caps have 13.65 more doctors per 100,000 population (i.e.,
125.48 doctors). The mean number of doctors—111.83 in noncapped States and
125.48 in capped States—is simulated from a linear prediction of the regression
results in Table 6. Thus, States with caps have 12.2 percent more doctors
per county than States without caps (i.e., 12.2%=13.65/111.83). This county
coefficient is about half the absolute size of the coefficient found using
State data because the number of doctors per 100,000 residents is lower at
the county level than at the aggregate State level. However, the percentage
impact is about the same (12 percent). The coefficient of each of the other
variables in the equation was of the expected sign, and all coefficients were
statistically significant at a 99 percent level of confidence.
a Alabama, Florida, Idaho, Illinois, and Washington also had statutes overturned but they were in effect less than 4 years. Idaho overturned a statute that capped noneconomic damages that applied only to medical liability cases, but another statute that capped noneconomic damages in all liability cases was passed and is still in effect.
Return to Contents
Discussion
Between 1970 and 2000, the supply of physicians per capita increased at a faster rate in those States that passed tort reform laws that capped damage payments in malpractice cases (see Tables 1A and Table 1B). In 1970, before any States had enacted caps, the average number of physicians per 100,000 population per county was 69 in States that eventually enacted caps between 1970 and 2000, compared with 67 in States that never enacted caps. This difference (69 vs. 67) is statistically insignificant (P=0.22). However, by the year 2000, the States that had enacted caps had a significantly higher number of doctors per 100,000 population per county (135) compared with States that did not enact caps (120) (P=0.006).
This trend indicates that caps may have possibly increased
the availability of physicians. To examine whether this was indeed the case,
we controlled for other State and county characteristics that may have also
impacted physician availability (such as medical residency programs, HMO
penetration, etc.). In particular, this study utilizes information about such
numerous State characteristics in the years 1985, 1990, 1995, and 2000, as well
as information about numerous county characteristics in 1996, 1997, 1998, 1999,
and 2000 to ascertain the relationship between State tort reform laws that cap
damage payments in malpractice cases and the supply of physicians. This study
finds evidence supporting the claim that States with caps on noneconomic
damages awards or caps on total damage awards benefit from about 12 percent more
physicians per capita than States without such laws.
This evidence was derived first in analyses where the State
was the unit of observation and then in analyses where the county was the unit
of observation. We found that the magnitude of the impact of laws limiting
damage payments using State data and county data was similar. Furthermore, we
found that the magnitude of the coefficient of the variable representing the
existence of a State law limiting damage payments was similar across various
specifications of each type of model. The robustness of this finding supports
the argument that State laws limiting noneconomic damages in medical
malpractice cases increase the number of physicians who practice in the State.
Nevertheless, this study has limitations. First, there are
factors other than those included in our model that affect the supply of
physicians. For example, the proportion of the population without health
insurance is likely to be related to physician supply through its influence on
the demand for physician services. Nonetheless, the proportion of people
without health insurance is likely related to the unemployment level in a State
as well as to the proportion of its production attributable to farm
activities. Thus, there are variables in our analysis that are likely to account
for at least some of the influence of these omitted variables. In any event,
the variables in our model explain more than half of the variation around the
mean in our State analyses, and this is quite large for a model that is
estimated with predominantly cross-sectional data.
Second, there are other State laws that may affect physician
location decisions. For example, some States have passed laws that permit
awards in malpractice cases to be made over a period of time (i.e., they permit
periodic payments) and laws that eliminate or weaken the "joint and several
liability" principle (the common rule of joint and several liability calls for
losing defendants to pay all the damage in spite of their level of fault).
Although such laws may be related to the decision of a physician on whether or
not to practice in a given geographic area, these types of laws are not nearly
as conspicuous as laws that cap payments. Previous research has shown that laws
that indirectly affect the level of malpractice damage awards (e.g. laws
permitting periodic payments) have less impact on malpractice premiums than
laws that directly limit malpractice damage awards.42
Finally, this study employs State and county data. Consequently, there may
be problems with aggregation bias (i.e., the relationships that exist at the
individual level may be obscured when observations are viewed as a group).43,44
There is, however, justification for estimating an equation using State and
county data because the independent variable of interest in this study is
whether or not a State has a law that limits damage awards in malpractice
cases, and we are interested in the impact of this type of State law on the
supply of physicians.
Although it is not possible to conduct a randomized trial to confirm the
findings of this study, future studies should include more variables and utilize
data from more time periods. Future studies also should focus on important
questions such as: how the level at which noneconomic damages is capped is
related to the supply of physicians; whether or not physician supply is related
to the length of time since the law has been in effect; and whether or not
other types of state tort reform laws such as those that eliminate or weaken
the principle of joint and several liability are related to physician supply.
Return to Contents
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Return to Contents
Current as of July 2003
Internet Citation:
Hellinger FJ, Encinosa WE. Impact of State Laws Limiting Malpractice Awards on Geographic Distribution of Physicians. July 2003. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/research/tortcaps/tortcaps.htm
540 Gaither Road Rockville, MD 20850