expert behavior change in response to best practice ......expert behavior change in response to best...

Expert Behavior Change in Response to Best Practice Changes:

Evidence from Obstetrics∗

Emily Oster, Brown University and NBER

December, 2018

Abstract

Guidelines for best practices in medicine change frequently. In this paper, I analyze to whatextent such changes alter practice patterns and whether adoption of best practices differentiallyaffects some patient groups. I consider these questions in the context of changes in practiceguidelines in obstetrics. I find, first, that practice patterns do respond to new information, mostnotably to new research. Such response are slow, however, and do not seem to be sped up bychanges in official organizational guidelines. I suggest that media coverage is an important part ofcatalyzing behavior change, even in this setting where the changes come from experts. Changesin practice are faster for more advantaged groups of patients. Related to this, I find evidencethat changes occur more quickly for infants who are otherwise healthier, even conditional onobservable features. I connect this last point to challenges in learning about the impacts of thesepractices. The results overall suggest practice changes would be faster if they were more widelypromoted, and this might especially benefit infants who are otherwise disadvantaged.

1 Introduction

To what extent do doctors respond to changes in treatment guidelines by changing their practice

patterns? Do some change their behavior more quickly than others, implying that some patients

benefit first from improved treatment?

Practice guidelines in medicine change frequently (see, for example, changes in treatment thresh-

olds for high blood pressure (Kristensen et al”

2014; Jackson et al, 2008; Gu et al, 2012) or changes

∗James Okun, Jason Goettisheim and Cathy Yue Bai provided outstanding and crucial research assistance. I amalso grateful to Valeria Zurla and Lauren To.

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in antibiotic prescribing guidelines for children (Arroll and Kenealy, 2005; Sakulchit and Goldman,

2017), making these important questions for understanding treatment quality.

Changes in guidelines have some parallels to changes in technology, a topic in which economists

have long been interested, beginning with the classic Griliches (1957) work on hybrid corn, and

with many examples in the area of health (e.g. Skinner and Staiger, 2005; Freedman, Lin and

Simon, 2015; Gold et al, 2014; Chandra, Cutler and Song, 2011). A key difference between practice

changes and technology changes is the potential speed. In the case of new technology, adoption

often requires learning about an unfamiliar procedure or practice, and possibly investing in new

capital equipment. In contrast, many of the best practice changes simply change the recommended

balance of procedures, or the threshold for some prescription or treatment. As a result, the only

significant barriers to adoption are learning the information and reacting to it. In principle, changes

could be immediate.

In this paper I address the question of how medical practitioners respond to different types of

information in changing treatment patterns, focusing on obstetrics. Accepted best practices around

childbirth have evolved considerably even in the past two decades, and there may be considerable

welfare gains to improved practices, given that US outcomes for mothers and babies lag the rest of

the world (National Research Council, 2013; Chen, Oster and Williams, 2016).

I analyze the patterns of behavior around four medical decisions which are common during

childbirth: (1) whether to attempt a vaginal birth after cesarean section (VBAC); (2) whether to

deliver a breech baby by planned cesarean section; (3) use of vacuum extraction for vaginal birth;

and; (4) whether to discourage elective labor induction at 37 or 38 weeks of gestation.

The paper has two primary goals. The first is to analyze how these practices have changed

over time, and connect changes to new information or other events. The second is to explore

heterogeneity in the speed of response across groups of patients. Both analyses make use of the

Natality Detail Files, which contain detailed microdata on all births in the United States over time.

Focusing on the first question, I find that there are significant changes in all four behaviors

over time, and they do seem to reflect responses to changes in best practices. These responses are,

however, slow. During this period there are two major research findings - on VBAC and breech

delivery - which do change practice, but over a period of years, not months. I find limited evidence

that changes in official guidelines increase this speed of change.

Notably, there is one example of a sharp and sustained decline in behavior - a large drop in the

use of vacuum extraction over a one month period in 1999. This appears to be a result not, however,

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of important changes in knowledge but instead a reaction to an episode of the show 20/20.

The slow change has welfare consequences. If new practices achieve (as we expect) better

outcomes, then faster change would benefit more patients. The slow change also opens the related

question of whether some patients systematically benefit from new information first.

The technology adoption literature has been quite interested in variation across space in adop-

tion (e.g. Skinner and Staiger, 2005), so I also begin with this question. In practice in this case I

see very little evidence of variation across space. Although the levels of the behaviors differ across

space, the trends are the same.

Turning to demographics, however, there is evidence that changes in behavior are experienced

differentially by different patients. More specifically, it appears that the changes in behavior initially

benefit more positively selected patients. The changes occur more slowly for groups who have,

on average, worse birth outcomes - in particular, African-American mothers and those with less

education. To give one example of this, prior to the change in VBAC recommendations in 1996

those with less than a high school education were slightly less likely to have a VBAC than those

with more education. By 2005 they were 3 percentage points more likely.

I use regression evidence to show that the selection gradient with respect to race and education

moves systematically along with the level of the behavior. Further, I show similar conclusions when

I focus on predicted mortality - predicted based on demographics - rather than race or education

as the selection variable. In summary, the benefits of new information seem to accrue to mothers

and infants in groups who are initially more advantaged.

I extend this point to show that selective behavior change favors better-off infants even condi-

tional on demographics. Specifically, I explore whether the relationship between infant outcomes

and the treatment varies with recommendations; I find that it does. To continue the VBAC exam-

ple: after the change in recommendation, those infants born by VBAC have a lower APGAR score,

relative to the difference before, even conditional on their observables. This suggests that there is

also negative selection of behavior change on unobservables. This is true for all four behaviors, and

when I consider infant mortality as the outcome rather than APGAR score.

Aggregating these facts paints a consistent overall picture. Despite the fact that these changes

could be made quickly and universally, I see patterns similar to technology adoption: slow diffusion

of change, with the earlier changes benefiting the better off patients. This suggests that it might

be possible to do more to encourage faster changes, and doing so would benefit more vulnerable

patients. Although it seems surprising since the actors here are experts, the evidence suggests that

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media attention may be a way to prompt more significant and faster changes.

As a final note, the last piece of evidence on the changes in relationship with infant outcomes

over time relates to the general issue of dynamic selection which I explore elsewhere. Oster (2018)

focuses on consumer health recommendations and shows that changes in these recommendations

can generate dynamic selection, with otherwise healthier consumers adopting newly recommended

behaviors first, changing the apparent relationship between the behavior and health. The results

here show a similar dynamic occurs even with expert decision-makers. Similar to the central point

in that paper, these dynamic changes have the potential to make it more difficult to learn about

relationships in the data.

This paper relates closely to the literature on health technology adoption. I focus in particular

on the role of different types of information in driving changes in behavior. A large literature looks at

other drivers, including (among others) peer effects, hospital structure and insurance policy (Burke,

Fournier and Prasad, 2007; Bradley et al, 2006; Gold et al, 2014; Bokhari et al, 2008; Freedman,

Lin and Simon, 2015; Sacarny, 2014; Domino, 2012; Agha and Molitor, 2018; Smieliauskas, 2011;

Yu, 2015).

The analysis also relates to a smaller literature, primarily in medicine, on how doctors respond

to changes in practice guidelines. Notable here are a number of papers on response to changes in

hypertension and statin prescribing guidelines (Kristensen et al”

2014; Jackson et al, 2008; Gu et

al, 2012; Ma et al, 2006; Pauff et al, 2015). These papers tend to find doctors do respond to changes

in prescribing guidelines, although they do not focus on heterogeneity across patient types.

Finally, I relate to a large literature on understanding use of interventions in obstetrics, perhaps

most notably papers on differential use of cesarean sections across patient types (i.e. Johnson and

Rehavi, forthcoming).

The rest of the paper is organized as follows. Section 2 describes the background on the changes

in practice guidelines, and the data I use. Section 3 shows results on changes in practice patterns

over time. Section 4 shows the evidence on heterogeneity and Section 5 concludes.

2 Background and Data

This section begins by describing the context for each of the procedures I consider, and briefly

reviewing the changes in recommendations. In the second subsection I describe the data used in

the analysis.

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2.1 Background on Contexts Considered

There are four practices considered here: (1) vaginal birth after cesarean section; (2) delivery

method for breech births; (3) use of vacuum extraction for vaginal birth and; (4) elective labor

induction at 37 or 38 weeks of gestation (“early term”).

Vaginal Birth after Cesarean (VBAC)

Vaginal birth after cesarean (VBAC) refers to the case in which a woman who has previously

delivered a child by cesarean section delivers vaginally a subsequent birth. In 1988, the American

College of Obstetricians and Gynecologists (ACOG) recommended VBAC as an option for prior

cesarean patients. In 1996, however, a large study (McMahon et al, 1996) suggested outcomes were

better with planned cesarean section in the case of a prior cesarean. Following this, in 1998 an

ACOG bulletin cautioned that VBAC should only be attempted at hospitals readily equipped to

provide emergency care in the case of uterine rupture. ACOG bulletins after 1998 continued to

focus on the risks of VBAC and the necessity of immediately available emergency cesarean sections.

Breech Delivery

Most infants are head down in the uterus at the time of labor and delivery, a position referred to

as “vertex presentation.” Breech presentation, in contrast, refers to a case where the infant is in

another position, typically either feet down or butt down. Some breech babies can be delivered

vaginally, but it is a more complex birth procedure. In 2000, results of a large trial (TERM-

BREECH) suggested that outcomes for breech infants were better with a planned cesarean section

than a trial of vaginal birth (Hannah et al, 2000). In 2001, ACOG followed this with a bulletin

which recommends cesarean sections for breech births. They note that most physicians are not

experienced in vaginal breech births and that vaginal birth is generally not appropriate for this

position of the fetus.

Vacuum Extraction

Vacuum extraction is a method to assist in the delivery of a baby using a vacuum device which

attaches to the child’s head. It is used in the second stage of labor if the infant appears to be

stuck. Vacuum extraction has been variously recommended and rejected over time. In 1994,

ACOG released a bulletin that detailed the qualifications for vacuum extraction and encouraged it

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under appropriate circumstances. However, in 1998, the FDA released a report on the dangers of

vacuum extraction, citing reports of deaths, which was followed by significant negative press. Back

in the other direction, subsequent ACOG opinions and bulletins reaffirmed the safety of vacuum

extraction and noted that complications are rare. The widely used alternative to vacuum extraction

is cesarean section.

Redefinition of “Full Term Pregnancy”

On average, a pregnancy lasts 40 weeks, and a full-term pregnancy has generally been considered

to be any delivery that falls between 37 and 42 weeks. A baby born before 37 weeks is considered

premature. However, in 2013, ACOG redefined full-term to be between 39 and 40 weeks, and

divided full term pregnancies into four categories: early-term (37 to 38 weeks), full-term (39 to 40

weeks), late-term (41 to 42 weeks), and post-term (more than 42 weeks). This had implications for

induced labor, as part of the change was to discourage elective induction in the “early term” period.

2.2 Data

The primary data source in this paper is the US Natality Detail Files, from the National Center

for Health Statistics (NCHS). The analysis uses both linked birth-death files and, where those are

not available, birth files only. For most treatments I focus on the period from 1995 through 2005,

where we have consistently coded information on treatments and demographics and during which

time most of the major changes occur. For the redefinition of term pregnancy I extend the data

through 2015.

The NCHS files are a Census of births in the United States based on birth and death certificates

filed in vital statistics offices in all States and the District of Columbia. The data provides infor-

mation on infant death within a year of birth (through 2009), various demographic characteristics

such as race, age and level of education, the health of both mother and child post-partum, and

physician practices carried out during labor.

In most cases it is necessary to recode variables to capture the outcomes of interest. The VBAC

variable takes the value 1 if the infant is delivered vaginally when the mother had delivered another

infant by cesarean and 0 if the infant was delivered by other means and the mother previously

had a cesarean delivery. The breech delivery variable is 1 if the infant is breech presenting and is

delivered by cesarean section and 0 if the infant is breech presenting and delivered vaginally. For

vacuum extraction, the indicator variable is 1 if a vacuum delivery is performed and 0 otherwise.6

Lastly, the early term birth variable takes the value 1 if the infant is delivered between 37 and 38

weeks, inclusive, and 0 if the birth occurs after 38 weeks. Births before 37 weeks are excluded from

this analysis. Table 1 presents summary statistics on treatments, demographics and outcomes.

3 Evidence on Changes Over Time

This section reports the initial results on changes in practice patterns over time.

Figure 1 shows the evolution of each procedure over time. There are four sub-figures, each

corresponding to one of the outcomes and showing the monthly means of behavior. Vertical lines

in the figures indicate major research studies, ACOG bulletins or opinions and other events. Table

2 lists the changes in recommendations indicated by the vertical lines.

Below, I discuss these figures in turn.

Vaginal Birth after Cesarean

The trends over time for vaginal birth after cesarean (VBAC) are shown in Figure 1a.

Broadly, this outcome is trending down over time. In the first year of the data - 1995 - the series

shows little trend and the mean is around 27%. To interpret, this implies that of women who had

a prior cesarean section, 27% of them went on to deliver a second pregnancy vaginally. By 2005,

however, only about 7% of women with a prior cesarean section are delivering vaginally.

The change appears to be precipitated by McMahon et al (1996), which indicated that major

maternal complications were almost twice as common for trial of labor after cesarean than for a

repeat cesarean.

The overall changes in this behavior are large. It is notable, however, that they are slow to

diffuse, despite the fact that practitioners were clearly familiar with the procedures required at the

time the change was made. Notable also is that the two official statements from the American

College of Obstetricians and Gynecologists (ACOG) - in 1998 and 1999 - seem to have had little

effect, changing neither the level nor the trend. Both statements echoed the 1996 paper and urged

repeat cesarean sections rather than VBAC in most cases. To the extent that the goal of these

guidelines was to increase the speed with which changes were made, the data does not show strong

evidence of that.

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Breech Delivery Method

Figure 1b shows the share of breech births delivered by cesarean section.

This series is initially flat, or trending slightly down, and then begins trending up over time in

the 2000s. There is one sharp spike downwards, but overall the trend is towards universal use of

cesarean section for breech deliveries. The changes over time seem, again, to be related to the timing

of research findings. In 2000, researchers published the first results from the TERM-BREECH trial,

a large randomized trial of delivery methods for breech births (Hannah et al, 2000). The authors

concluded that short-term outcomes for breech infants were better after a planned cesarean section

than after a planned vaginal birth.

Similar to the case of VBAC, these findings do seem to prompt an upward trend in the use of

cesarean delivery although, again, the change is not sudden. Later changes in ACOG guidelines,

published in 2001, reinforced the preference for cesarean section for breech delivery. Again, similar

to VBAC, these do not seem to cause a change in level or trend.

In 2003, an abstract (Hannah et al, 2003) was released with follow-up data from the TERM-

BREECH trial. This later follow-up was somewhat more reassuring about the outcomes for the

planned vaginal birth group, showing no differences in outcomes after two years. This seems to

cause a short term revision in the use of cesarean section for breech deliveries, although this is very

short lived.

Vacuum Extraction

Figure 1c shows the share of births in which vacuum extraction is used, over time.

This figure has a sharp decline in the middle - over a one month period in 1999 there is a one

percentage point drop in the use of vacuum extraction in births, from a base of about 6%. This

continues, and is continued by, a downward trend.

The downward trend in use of this procedure seems to begin with a 1998 FDA report suggesting

there were significant dangers to using vacuum extraction, including the possibility of infant injury

or death. This alert was sent to all practitioners. The report begins a period of decline for this

procedure, which had until then been trending upwards. The report does not, however, cause an

immediate spike down. Indeed, the spike down does not coincide with any specific official events.

The timing is, however, consistent with the drop resulting from a sensationalist episode of the

TV news program “20/20” which focused on the risks of vacuum extraction for babies, and featured

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graphic images of injured or deceased infants. The news program was motivated by some of the

earlier findings from the FDA, but the timing is clearly later. This program aired at the very end

of January, 1999. While it is difficult to prove the two events are linked, we do not see any other

events which line up in terms of timing.

It is notable that there are a number of information shocks which supported the use and safety

of vacuum extraction. These include an ACOG bulletin in 1998 (the second dotted line) and a

significant review study release in 1999 (Towner et al, 1999). Both argued for the safety of vacuum

extraction. Towner et al (1999), for example, showed similar rates of infant injury for use of vacuum,

forceps or cesarean section.

These releases do not seem to have any impact on stemming the reduction in use of vacuum.

The downward trend continues through these releases.

Early Term Birth

Finally, I consider Figure 1d, which shows changes in the rate of early term delivery over time. This

graph is limited to the universe of infants who were born at or after 37 weeks of pregnancy, and

it shows the share of these births which were at 37 or 38 weeks. This share is increasing until the

mid to late 2000s and then declines. This slow decline is hard to trace to any particular event; it

seems, rather, to reflect a growing consensus over this period that early term births result in worse

outcomes than later term births (Reddy, Ko and Willinger, 2006; Engle and Kominiarek, 2008;

Fleischman, Oinuma and Clark, 2010).

In 2013, ACOG issued concrete guidelines around these issues - specifically, classifying 37 or 38

weeks as “early term” rather than “full term” as an approach to making clear that deliveries should

wait for 39 weeks. The timing of this release is shown in the figure. Again, we see no evidence of

an acceleration of change. If anything, the decline in early term births which had been continuous

up to that point is arrested, and the trend flattens, after the change in guidelines.

Discussion

Visually, Figure 1 makes clear that these practices do change over time and the discussion above

shows that, at least to some extent, these changes appear to be a response to changes in best

practice.

Notably and unsurprisingly, we find that major research studies - in particular, those on VBAC

and breech delivery - do play a significant role in catalyzing change. However, this information9

does not seem to result in immediate changes. It takes years for the decline in the VBAC rate to

taper off. If the appropriate level of this treatment is (say) 7% – where it stabilizes – there is a full

decade in which a faster decline would have been feasible.

One natural approach to speeding up adoption is to change official guidelines to reinforce study

findings. However, the evidence here suggests that is not an effective approach.

It is finally worth noting that changes which recommend more conservative behavior seem to

have greater take-up. This is notable in the case of vacuum extraction, where there are large

responses to both the FDA and, seemingly, the media, when they indicate that this procedure may

be dangerous. There is, however, no corresponding recovery in response to either official guidelines

or a major research study promoting safety.

This suggests, overall, that it may be more challenging to change some behaviors than others,

and there is clearly space for trying to better publicize new findings about best practices. The fact

that the behaviors change slowly leaves open the question of who benefits first, which I turn to

now.

4 Heterogeneity in Behavior Change

I focus now on heterogeneity, beginning with geography and demographics. There is significant focus

in the health economics literature on variation in practice patterns across space and demographic

groups; this practice variation has implications for varying health outcomes across these groups.

Here, I ask whether the changes in response to changes in best practice seem to differ across groups.

4.1 Geography and Demographics

A large literature has focused on variation across areas in the US in health outcomes in general

(Skinner, 2011) or in changes in health technology (e.g. Skinner and Staiger, 2005). In contrast

to this literature - which generally finds significant variation across space in health - I do not see

much variation in behavior change across regions of the US. This is visualized in Figure 2, which

replicates Figure 1 but includes separate lines for each region of the country. Note that due to

limited information on region (namely, it is not available after 2004) the early birth graph covers a

shorter time period here.

There are differences in levels of the behaviors - for example, vacuum extraction is used more

commonly in the West than elsewhere - but the changes over time are remarkably consistent. There

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is neither a coming together nor a fanning out over time across space. The one notable feature is

that the short-lived drop in the use of C-section for breech deliveries in 2003 seems to be entirely

due to the South. It is not clear why this is.

In contrast, I do see evidence that changes in behavior occur faster for some patient demographic

groups. To visualize this, consider Figure 3. This, again, replicates Figure 1 but adds a second series

in each figure. This second series shows the relationship between a dummy for low education and

the procedure over time - effectively, it shows the difference in the level of the procedure between

those with less than a high school degree and those with a high school degree or more.1

If we consider the VBAC example (Figure 3a) we see the series clearly moving in opposite

directions. As the procedure becomes less frequent, it becomes relatively more common among

those with less than a high school degree. Stated conversely, the change over time - the adoption of

VBAC - is faster among those with more education. We see similar patterns elsewhere. Appendix

Figure A1 shows the same graphs with a dummy for the mother reporting African-American race

rather than education. Finally, Appendix Figure A2 uses the predicted death rate - predicted based

on demographics - as the demographic measure. This provides a way to summarize the relative

speed of changes for better or worse off groups ex ante.

In many of these figures and sub-figures we see the same patterns – that is, changes which

suggest the change in practices occur earlier for more advantaged demographic groups. To get a

sense of whether these patterns are systematic, the first three columns of Table 3 show regression

evidence on the relationship. Specifically, in each case I regress the gradient (the coefficient from

a regression of the treatment on the demographic measure) on the level of treatment. A negative

coefficient here implies that as the level of the treatment goes up, the gradient goes down.

In the case of education, for example, the outcome in this regression is the excess procedure rate

for those with less education relative to more and the independent variable is the level of procedure.

A negative coefficient indicates that as the procedure becomes more common, it becomes relatively

less common among those with less education.

Column (1) of Table 3 shows these regression results for education, Column (2) for an indicator

for African-American and Column (3) for the predicted mortality measure. In all three cases, the

gradient is negative. Since each of these gradients are defined such that they take as the baseline the

less advantaged group, this implies that more advantaged women systematically see faster changes.

1These figures are computed at the quarterly, rather than the monthly level, to limit noise.

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4.2 Outcomes

Changes accrue first to those who are already more advantaged, at least along observable dimen-

sions. To explore the evolving relationship with infant outcomes, Figure 4 echoes Figure 3, but

here the coefficient relationship is between treatment and whether the infant has a low APGAR

score. To create these coefficients, I regress the low APGAR indicator on procedure measures, and

include in the regression a full set of demographic controls.

Figure 4 looks very similar to Figure 3, As procedures become (for example) less common they

become relatively more associated with low APGAR scores. Appendix Figure A3 shows the same

graph for neonatal mortality (deaths in the first month of life) and Columns (4) and (5) of Table 3

shows the corresponding regressions. As in the observables, the regressions show significant negative

coefficients.

This suggests that as the procedures become less common they are more commonly experienced

by infants who have poor outcomes. This can be seen as an extension of the observable selection

seen above, although since these gradient regressions are conditional on observables, the selection

here must be on unobserved characteristics. It should be noted that there is another possible

interpretation - namely, that there are heterogeneous treatment effects in these cases, and when the

behavior becomes less common the infants who are still treated are those with the most negative

treatment effects. This seems possible, but unlikely, as it would suggest that doctors are targeting

these treatments to the mothers and infants who benefit least. More plausible is the interpretation

that infants who are otherwise disadvantaged also get these practice improvements later.

5 Discussion and Conclusion

This paper opens by asking whether doctors respond to changes in best practices, and whether

these changes exacerbate or ameliorate health inequality. The results above suggest that some

types of information do prompt response, although even in these cases where in principle behavior

change could be very fast, actually change is generally slow. The slow pace of change appears to

favor positively selected patients, both based on observable demographics and on examining the

outcomes associated with the procedures over time.

This analysis provides added motivation for improving compliance with changing best prac-

tices. Universal adoption of improved procedures would disproportionately benefit ex ante worse

off mothers and infants. Given the poor record of the US overall in maternal and infant health

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(National Research Council, 2013) and the particular inequality in outcomes (Chen, Oster and

Williams, 2016) these issue are of policy concern.

These results provide less guidance in terms of how to speed up adoption. Official guidelines

seem to play little or no role, at least over and above the research studies they are based on.

Relying on the example of vacuum extraction, it would seem that alarmist publicity might increase

adoption speeds, but this is unlikely to be a widely acceptable policy response. It is also worth

saying that the approach here is unable to separate slow behavior change resulting from doctors

not learning about new evidence from slow behavior change due to resistance to change even in

the face of evidence. Understanding this distinction better empirically could allow development of

more effective approaches.

As a final point, the dynamics in Section 4.2 are notable because they highlight (as in Oster,

2018) that these changes in recommendations may increase the challenge of further research on the

impacts of these treatments. For research which relies on observational data, there may be biases

introduced by endogenous behavioral response. In the case of VBAC, for example, using these data

to estimate the risks in 2005 would yield a different estimate than in 1995, with the later data

suggesting a more negative outlook on VBAC.Given that much of our scientific knowledge relies on

observational data, these dynamics are worth considering when evaluating research results.

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16

Fig

ure

1:C

han

ges

inP

rocedure

sO

ver

Tim

e

Pan

elA

:V

BA

CC

han

ges

and

Eve

nts

Pan

elB

:B

reec

hSec

tion

Chan

ges

and

Eve

nts

.1.15.2.25.3VBAC Share

1995

m1

2000

m1

2005

m1

Rat

e of

VB

AC

Am

ong

Prio

r C

esar

ean

.84.86.88C-Section Share

1995

m1

2000

m1

2005

m1

Rat

e of

C-S

ectio

n A

mon

g B

reec

h B

irths

Pan

elC

:V

acu

um

Ch

ange

san

dE

vents

Pan

elD

:E

arly

Bir

thC

han

ges

and

Even

ts

.04.045.05.055.06.065Vacuum Share

1995

m1

2000

m1

2005

m1

Rat

e of

Vac

uum

.2.25.3.35Early Term Share

1995

m1

2000

m1

2005

m1

2010

m1

2015

m1

Rat

e of

Ear

ly T

erm

Birt

hs

Note

s:T

hes

efigure

ssh

owch

anges

inobst

etri

cpro

cedure

sov

erti

me

wit

hea

chdot

repre

senti

ng

am

onth

.V

BA

Cis

defi

ned

only

for

wom

enw

ith

apre

vio

us

cesa

rean

sect

ion.

Earl

yte

rmbir

ths

are

bir

ths

at

37

or

38

wee

ks,

as

ash

are

of

all

bir

ths

37

wee

ks

or

late

r.D

ott

edver

tica

llines

repre

sent

the

rele

ase

of

rese

arc

hst

udie

sre

late

dto

the

pro

cedure

s.Solid

ver

tica

llines

repre

sent

AC

OG

com

mit

tee

opin

ions

and

pra

ctic

ebullet

ins.

Det

ails

of

thes

eev

ents

app

ear

inT

able

2.

17

Fig

ure

2:C

han

ges

by

Geogra

phic

Are

a

Pan

elA

:V

BA

Cby

Reg

ion

Pan

elB

:B

reec

hC

-Sec

tion

by

Reg

ion

0.1.2.3.4VBAC Share

1995

m1

2000

m1

2005

m1

Nor

th E

ast

Mid

Wes

tS

outh

Wes

t

Rat

e of

VB

AC

Am

ong

Prio

r C

esar

ean

.8.85.9C-Section Share

1995

m1

2000

m1

2005

m1

Nor

th E

ast

Mid

Wes

tS

outh

Wes

t

Rat

e of

C-S

ectio

n A

mon

g B

reec

h B

irths

Pan

elC

:V

acu

um

by

Reg

ion

Pan

elD

:E

arly

Bir

thby

Reg

ion

.03.04.05.06.07.08Vacuum Share

1995

m1

2000

m1

2005

m1

Nor

th E

ast

Mid

Wes

tS

outh

Wes

t

Rat

e of

Vac

uum

.2.25.3.35Early Term Share

1995

m1

2000

m1

2005

m1

Nor

th E

ast

Mid

Wes

tS

outh

Wes

t

Rat

e of

Ear

ly T

erm

Birt

hs

Note

s:T

hes

efigure

ssh

owth

eth

ele

vel

of

beh

avio

rov

erti

me

by

regio

n.

The

four

are

as

corr

esp

ond

tost

andard

censu

sre

gio

ns:

Nort

hE

ast

,South

,W

est

and

Mid

-Wes

t.D

ott

edver

tica

llines

repre

sent

the

rele

ase

of

rese

arc

hst

udie

sre

late

dto

the

pro

cedure

s.Solid

ver

tica

llines

repre

sent

AC

OG

com

mit

tee

opin

ions

and

pra

ctic

ebullet

ins.

Det

ails

of

thes

eev

ents

app

ear

inT

able

2.

18

Fig

ure

3:V

ari

ati

on

inP

rocedure

Use

by

Educati

on

Over

Tim

e

Pan

elA

:L

owE

du

cati

onan

dV

BA

CP

anel

B:

Low

Edu

can

dB

reec

hC

-Sec

tion

-.02-.010.01.02.03VBAC Coefficients

.1.15.2.25.3VBAC Rate

1995

m1

2000

m1

2005

m1

date

VB

AC

Rat

eC

oeffi

cien

ts

Cov

aria

nce

betw

een

VB

AC

and

Low

Edu

c.

-.08-.06-.04-.020Breech x C-Section Coefficients

.84.86.88Breech x C-Section Rate 19

95m

120

00m

120

05m

1da

te

Bre

ech

x C

-Sec

tion

Rat

eC

oeffi

cien

ts

Cov

aria

nce

betw

een

Bre

ech

x C

-Sec

tion

and

Low

Edu

c.

Pan

elC

:L

owE

du

c.an

dV

acuum

Pan

elD

:L

owE

duc

and

Ear

lyB

irth

-.015-.01-.005Vacuum Coefficients

.04.045.05.055.06.065Vacuum Rate

1995

m1

2000

m1

2005

m1

date

Vac

uum

Rat

eC

oeffi

cien

ts

Cov

aria

nce

betw

een

Vac

uum

and

Low

Edu

c.

-.04-.020.02.04Early Birth Coefficients

.2.25.3.35Early Birth Rate

1995

m1

2000

m1

2005

m1

2010

m1

2015

m1

date

Ear

ly B

irth

Rat

eC

oeffi

cien

ts

Cov

aria

nce

betw

een

Ear

ly B

irth

and

Low

Edu

c.

Note

s:T

hes

efigure

ssh

owth

eth

ele

vel

of

beh

avio

rand

its

rela

tionsh

ipw

ith

educa

tion

over

tim

e.T

he

level

sre

plica

teF

igure

1.

To

crea

teth

eed

uca

tion

seri

esI

esti

mate

the

diff

eren

cein

trea

tmen

tle

vel

sb

etw

een

those

wit

hle

ssed

uca

tion

(defi

ned

as

less

than

hig

hsc

hool)

and

those

wit

hm

ore

educa

tion

than

that.

To

lim

itnois

eI

do

thes

eca

lcula

tions

the

quart

erly

level

.V

erti

cal

lines

indic

ate

even

tsas

inF

igure

1,

wit

hdet

ails

inT

able

2.

19

Fig

ure

4:

Vari

ati

on

inP

rocedure

Eff

ects

on

Outc

om

es:

AP

GA

R

Pan

elA

:E

ffec

tof

VB

AC

onlo

wA

PG

AR

Pan

elB

:E

ffec

tof

Bre

ech

onlo

wA

PG

AR

-.0020.002.004.006.008vbac Coefficients

.1.15.2.25.3VBAC Rate

1995

m1

2000

m1

2005

m1

date

VB

AC

Rat

eC

oeffi

cien

ts

Reg

ress

ion

of L

ow A

PG

AR

on

VB

AC

+ C

ontr

ols

-.095-.09-.085-.08-.075-.07breech Coefficients

.84.86.88Breech x C-Section Rate 19

95m

120

00m

120

05m

1da

te

Bre

ech

x C

-Sec

tion

Rat

eC

oeffi

cien

ts

Reg

ress

ion

of L

ow A

PG

AR

on

Bre

ech

x C

-Sec

tion

+ C

ontr

ols

Pan

elC

:E

ffec

tof

Vacu

um

onlo

wA

PG

AR

Pan

elD

:E

ffec

tof

Ear

lyB

irth

onlo

wA

PG

AR

.001.002.003.004.005vacuum Coefficients

.04.045.05.055.06.065Vacuum Rate

1995

m1

2000

m1

2005

m1

date

Vac

uum

Rat

eC

oeffi

cien

ts

Reg

ress

ion

of L

ow A

PG

AR

on

Vac

uum

+ C

ontr

ols

-.00050.0005.001.0015.002early_birth Coefficients

.2.25.3.35Early Birth Rate

1995

m1

2000

m1

2005

m1

2010

m1

2015

m1

date

Ear

ly B

irth

Rat

eC

oeffi

cien

ts

Reg

ress

ion

of L

ow A

PG

AR

on

Ear

ly B

irth

+ C

ontr

ols

Note

s:T

hes

efigure

ssh

owth

ele

vel

of

beh

avio

rand

its

rela

tionsh

ipw

ith

AP

GA

Rsc

ore

over

tim

e.T

he

level

sre

plica

teF

igure

1.

To

crea

teth

eA

PG

AR

seri

esI

regre

ss,

at

the

quart

erly

level

,an

indic

ato

rfo

rlo

wA

PG

AR

score

(<7)

on

the

trea

tmen

tand

dem

ogra

phic

contr

ols

.T

he

gra

phs

show

evolu

tion

of

this

coeffi

cien

tov

erti

me.

Ver

tica

llines

indic

ate

even

tsas

inF

igure

1,

wit

hdet

ails

inT

able

2.

20

Table 1: Summary Statistics

Mean Standard Deviation Sample Size Time Period

VBAC 0.19 0.39 4,768,286 1995-2005

Vacuum Extraction 0.05 0.22 43,771,430 1995-2005

Breech Delivered by Cesarean 0.86 0.34 1,694,848 1995-2005

Early Term 0.29 0.45 74,898,956 1995-2015

White 0.57 0.49 65,072,301 1995-2015

Black 0.15 0.35 65,072,301 1995-2015

Hispanic 0.22 0.41 65,072,301 1995-2015

Other Race 0.06 0.24 65,072,301 1995-2015

Unknown Education 0.01 0.12 65,072,301 1995-2015

Less than High School 0.10 0.29 65,072,301 1995-2015

High School 0.46 0.50 65,072,301 1995-2015

College 0.43 0.50 65,072,301 1995-2015

Age < 20 0.11 0.31 65,072,301 1995-2015

19 < Age < 30 0.52 0.50 65,072,301 1995-2015

29 < Age < 40 0.34 0.47 65,072,301 1995-2015

Age > 39 0.03 0.16 65,072,301 1995-2015

North East 0.17 0.38 39,929,013 1995-2004

South 0.36 0.48 39,929,013 1995-2004

Midwest 0.22 0.41 39,929,013 1995-2004

West 0.24 0.43 39,929,013 1995-2004

Notes: This table shows summary statistics on the data used from the NHCS. All variables are binary. VBAC shareis the share of women with at least one prior cesarean who have a vaginal birth. Breech delivery by cesarean is limitedto breech births. Early term delivery is defined as delivery at 37 or 38 weeks, among all births at or after 37 weeks.

21

Table 2: Information Events

Treatment Event 1 Event 2 Event 3 Event 4

VBAC 1996, Negative: A

research study from

McMahon is the first to

show that major

complications, including

uterine rupture, were more

likely for patients who

attempted VBAC than

those who had a repeat

cesarean. This study

influences the more

restrictive ACOG

guidelines later.

1998, Negative: ACOG

publishes Practice Bulletin

2 citing the risk of uterine

rupture. There is

subsequent media coverage

on the risks of VBAC.

1999, Negative: ACOG

publishes Practice Bulletin

5, which suggests that

physicians should be

“immediately” available to

provide emergency care to

women attempting VBAC.

This was seen as very

restrictive, and many

commented that there is

no such thing as an

immediate cesarean.

Breech

Delivery

2000, Guideline : A

research study, Hannah,

et. al. (2000), conducts a

trial of term breech births.

It concludes that planned

cesarean sections are

better than vaginal births

for term breech babies.

2001, Guideline :

ACOG publishes a

committee opinion

encouraging c-sections for

breech births.

2003, Guideline : A

follow-up research study

from Hannah, et. al

(2003) finds that there

were no substantial

differences between breech

presenting babies delivered

by planned c-section and

planned vaginal birth at

term 2 years post partum.

Vacuum

Extraction

1998/1999, Negative:

The FDA releases a report

about the dangers of

vacuum extraction. Also

media coverage of a

NJEM article in which

doctors protest a goal of

lowering c-section rates.

1998, Positive: ACOG

publishes a committee

opinion in response to the

FDA report to reassure

physicians that

complications from

vacuum extraction are

rare.

1999, Positive: Towner,

et. al (1999) publish a

study, widely cited in the

media, demonstrating that

the rates of intracranial

hemorrhage were similar

for vacuum extraction,

forceps delivery, and

cesarean delivery, refuting

prior claims about the

relative safety of vacuum

extraction.

2000, Positive: ACOG

published Practice

Bulletin 17, which remarks

that there is no difference

in mortality between

births achieved by forceps

and vacuum.

Redefinition of

Full Term

Pregnancy

2013, Guideline: ACOG

changes the definition of

full-term pregnancy,

creating four categories.

Notes: This table shows the information events identified for each outcome.

22

Table 3: Selection of Behaviors

(1) (2) (3) (4) (5)

Outcome: Low Educ Gradient Black Grad. Pred. Death Grad Low APGAR Grad. Mortality Grad.

Level of Behavior -0.073∗∗∗ -0.047∗∗∗ -0.00017∗∗ -0.025∗∗∗ -0.034∗∗∗

(0.012) (0.008) (0.00008) (0.005) (0.004)

Treatment FE YES YES YES YES YES

Year FE YES YES YES YES YES

Number of Obs. 600 600 600 600 552

Notes: This table shows statistical evidence on the co-movements between levels of treatment and the gradient withrespect to demographics (education and race), the predicted death rate based on demographics and two outcomes(low APGAR score and infant mortality). Each cell represents a different regression of gradients on the level oftreatment. An observation is a treatment-month. All regressions include fixed effects for each treatment and year.∗indicates significance at the 10% level, ∗∗indicates significance at the 5% level, ∗ ∗ ∗ indicates significance at the 1%level.

23

Appendix A: Appendix Figures and Tables

Figure A1: Variation in Procedure Use by Race Over Time

Panel A: Black Race and VBAC Panel B: Black Race and Breech C-Section

-.02

-.01

0.0

1V

BA

C C

oeffi

cien

ts

.1.1

5.2

.25

.3V

BA

C R

ate

1995m1 2000m1 2005m1date

VBAC Rate Coefficients

Covariance between VBAC and Race

-.07

-.06

-.05

-.04

-.03

Bre

ech

x C

-Sec

tion

Coe

ffici

ents

.84

.86

.88

Bre

ech

x C

-Sec

tion

Rat

e

1995m1 2000m1 2005m1date

Breech x C-Section Rate Coefficients

Covariance between Breech x C-Section and Race

Panel C: Black Race and Vacuum Panel D: Black Race and Early Birth

-.03

-.02

5-.

02-.

015

-.01

Vac

uum

Coe

ffici

ents

.04

.045

.05

.055

.06

.065

Vac

uum

Rat

e

1995m1 2000m1 2005m1date

Vacuum Rate Coefficients

Covariance between Vacuum and Race

.03

.04

.05

.06

Ear

ly B

irth

Coe

ffici

ents

.2.2

5.3

.35

Ear

ly B

irth

Rat

e

1995m1 2000m1 2005m1 2010m1 2015m1date

Early Birth Rate Coefficients

Covariance between Early Birth and Race

Notes: These figures show the level of behavior and its relationship with neonatal mortality (deaths in the firstmonth of life) over time. The levels replicate Figure 1. To create the mortality series I regress, at the quarterlylevel, an indicator for infant mortality on the treatment and demographic controls. The graphs show evolution of thiscoefficient over time. Vertical lines indicate events as in Figure 1, with details in Table 2.

24

Figure A2: Variation in Procedure Use by Predicted Death Over Time

Panel A: Predicted Death and VBAC Panel B: Predicted Death and Breech C-Section

-.00

005

0.0

0005

.000

1.0

0015

VB

AC

Coe

ffici

ents

.1.1

5.2

.25

.3V

BA

C R

ate

1995m1 2000m1 2005m1date


Covariance between VBAC and Predicted Death

-.00

4-.

0035

-.00

3-.

0025

-.00

2B

reec

h x

C-S

ectio

n C

oeffi

cien

ts

.84

.86

.88

Bre

ech

x C

-Sec

tion

Rat

e

1995m1 2000m1 2005m1date


Covariance between Breech x C-Section and Predicted Death

Panel C: Predicted Death and Vacuum Panel D: Predicted Death and Early Birth

-.00

03-.

0002

5-.

0002

-.00

015

-.00

01V

acuu

m C

oeffi

cien

ts

.04

.045

.05

.055

.06

.065

Vac

uum

Rat

e

1995m1 2000m1 2005m1date


Covariance between Vacuum and Predicted Death

0.0

0001

.000

02.0

0003

.000

04E

arly

Birt

h C

oeffi

cien

ts

.2.2

5.3

.35

Ear

ly B

irth

Rat

e

1995m1 2000m1 2005m1 2010m1 2015m1date


Covariance between Early Birth and Predicted Death


25

Figure A3: Variation in Procedure Effects on Outcomes: Mortality

Panel A: Effect of VBAC on Mortality Panel B: Effect of Breech on Mortality

0.0

01.0

02.0

03.0

04.0

05V

BA

C C

oeffi

cien

ts

.1.1

5.2

.25

.3V

BA

C R

ate

1995m1 2000m1 2005m1date


Regression of Infant Death on VBAC + Controls

-.08

-.07

5-.

07-.

065

-.06

Bre

ech

x C

-Sec

tion

Coe

ffici

ents

.84

.86

.88

Bre

ech

x C

-Sec

tion

Rat

e

1995m1 2000m1 2005m1date


Regression of Infant Death on Breech x C-Section + Controls

Panel C: Effect of Vacuum on Mortality Panel D: Effect of Early Birth on Mortality

-.00

32-.

003

-.00

28-.

0026

Vac

uum

Coe

ffici

ents

.04

.045

.05

.055

.06

.065

Vac

uum

Rat

e

1995m1 2000m1 2005m1date


Regression of Infant Death on Vacuum + Controls

.000

1.0

002

.000

3.0

004

.000

5E

arly

Birt

h C

oeffi

cien

ts

.2.2

5.3

.35

Ear

ly B

irth

Rat

e

1995m1 2000m1 2005m1 2010m1 2015m1date


Regression of Infant Death on Early Birth + Controls


26

expert behavior change in response to best practice ......expert behavior change in response to best...

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