Delivery by Cesarean section (C-section) is necessary in 10%–20% of births, but unnecessary C-sections result in elevated rates of maternal and infant morbidity and mortality and have high financial costs. For all of these reasons, excessive C-section rates have long been viewed as a serious public health problem. Iran has one of the highest rates of C-sections in the world, so reducing those rates (and the associated maternal and infant morbidity and mortality) has been an obvious public health priority. In 2014, the Iranian Ministry of Health and Medical Education created substantial financial incentives discouraging the use of C-sections in public hospitals, and it subsequently extended a modified version of these incentives to nonpublic hospitals. We examine the impact of these reforms on C-section frequency and health outcomes. C-section rates in Iranian public hospitals declined by almost 5%, with higher reductions for first-time mothers, and smaller reductions for mothers with higher-risk pregnancies (e.g., mothers with hypertension or diabetes). We contribute by using a difference-in-differences (DiD) approach to show that physician-level financial incentives explain roughly two-thirds of the decline and patient-level financial incentives explain most of the rest. We also contribute by showing these reforms resulted in improved outcomes, with fewer maternal deaths and neonatal intensive care unit admissions. Our findings indicate that economic incentives do affect C-section rates, but more aggressive strategies will be necessary to reduce C-section rates to the levels typically recommended by public health authorities (10%–20% of births).

Delivery by cesarean section (C-section) is medically necessary in 10%–20% of births [1, 2, 3]. Unnecessary C-sections result in elevated rates of maternal and infant morbidity (e.g., bleeding, infection, respiratory distress, temporary, and permanent disability) and mortality (i.e., death) [4, 5, 6, 7, 8]. Unnecessary C-sections also result in higher financial costs, including substantial out-of-pocket payments by patients [9]. For these reasons, high C-section rates have long been viewed as a serious public health problem [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15].

C-section rates vary widely across the globe. Data from 154 countries covering almost 95% of world live births show “averages ranging from 5% in sub-Saharan Africa to 42.8% in Latin America and the Caribbean” [7]. C-section rates have also been increasing rapidly everywhere, from 6% of all births in 1990, to 21% in 2018, to an estimated 28.5% in 2030 [7]. A 2018 Editorial in the Lancet summarized the situation as follows: “[T]he global rate of caesarean birth has doubled in the past 15 years to 21%, and is increasing annually by 4%. While in southern Africa use of caesarean section is less than 5%, the rate is almost 60% in some parts of Latin America” [10].

Iran has long had one of the highest C-section rates in the world, so reducing those rates (and the associated maternal and infant morbidity and mortality) is an obvious public health priority [16, 17, 18, 19, 20, 21, 22]. In 2005, 40.7% of births in Iran were by C-section, and in some facilities, the C-section rate was as high as 90% [20]. By 2014, fully 53% of births in Iran were by C-section [12, 21]. In terms of financial costs, the World Health Organization (WHO) estimated that Iran spent more than $100,000,000.on unnecessary C-sections in 2008—when the rate was materially lower than it is today [9].

During the 2013 Iranian Presidential campaign, reform of the Iranian health system was a prominent issue, with one candidate (Dr Hassan Rouhani, who won the election) placing health at the center of his campaign [23]. In 2014, Iran issued a Health Transformation Plan (HTP) which charged the Iranian Ministry of Health and Medical Education (IMHME) with materially reducing the frequency of C-sections [24]. The reform was motivated by concern about the morbidity and mortality associated with high C-section rates, along with the excessive financial costs being incurred by the Iranian health-care system and patients [23, 24].

Acting in accordance with the HTP, the IMHME modified the payment system to create substantial financial incentives discouraging C-sections. Initially, the reforms only affected public hospitals, but they were subsequently extended to private hospitals.

Table 1 summarizes the total payment and patient share (co-payment) for vaginal deliveries at public and nonpublic hospitals, expressed in terms of the percentage of payment for a C-section performed in the same type of hospital. Table 1 shows these figures at 3 different points in time: pre-reform, post-first reform, and post-second reform.

Table 1.

Payment for a vaginal delivery (expressed as a percentage of payment for a C-section)

PaymentHospital TypePre-ReformPost-First ReformPost-Second Reform
Total payment Public 81% 214% 125% 
Nonpublic 81% 81% 125% 
Co-payment (patient share) Public 81% 0% 0% 
Nonpublic 81% 81% 125% 
PaymentHospital TypePre-ReformPost-First ReformPost-Second Reform
Total payment Public 81% 214% 125% 
Nonpublic 81% 81% 125% 
Co-payment (patient share) Public 81% 0% 0% 
Nonpublic 81% 81% 125% 

Payment for vaginal delivery is expressed as a percentage of payment for C-section at the same hospital type at a specified point in time. Total payment = total amount received by the physician. Co-payment = patient’s share of the total payment to physician. Co-payment is set at 10% of total payment to physician, except for public hospitals post-first reform, when it is set to 0. Figures are for 471 public hospitals and 396 nonpublic hospitals in Iran. Pre-reform = delivery prior to May 5, 2014. Post-first reform = delivery on or after May 5, 2014, and before September 23, 2014. Post-second reform = delivery on or after September 23, 2014.

As Table 1 reflects, before the first reform, physicians who performed a vaginal delivery were paid 81% of amount they would receive had they performed a C-section at the same type of hospital, irrespective of whether the delivery was in a public or nonpublic hospital. The patient’s co-payment (i.e., their share of the payment) was set at 10% of the total payment, so it was also 81% of the amount that a patient who received a C-section would pay.

After the first reform, which took effect on May 5, 2014, physicians who delivered a patient vaginally in a public hospital received a payment that was more than twice as much (i.e., 214%) as the payment for a C-section performed in the same type of hospital. The patient’s co-payment for vaginal deliveries in public hospitals was eliminated entirely. However, as Table 1 reflects, these changes only applied to public hospitals; deliveries at nonpublic hospitals retained the payment arrangement that prevailed before the first reform took effect.

Subsequently, a modified version of these incentives was extended to all hospitals in Iran (second reform). After the second reform, which took effect on September 23, 2014, physicians who performed a vaginal delivery were paid 125% of the amount they would receive had they performed a C-section, irrespective of whether they were doing so at a public or nonpublic hospital. However, patient co-payments varied significantly depending on the type of hospital. Patients who delivered in public hospitals had no co-payment. Patients who delivered in nonpublic hospitals were responsible for a standard share (co-payment) of 10% of the total payment. Because physician payment for a vaginal delivery was set at 125% of the payment for a C-section, this meant that patients who had a vaginal delivery in a nonpublic hospital (paradoxically) paid a higher co-payment than patients who had a C-section in the same hospital.

We exploit this sequential round of reforms to assess the impact of substantial financial incentives on C-section rates using a difference-in-differences (DiD) approach. We use administrative data from the IMHME—including detailed information on every birth in Iran before and after the reforms in question—to analyze the effects of these reforms. Our data cover every birth in Iran from September 23, 2013 (32 weeks before the first reform was instituted on May 5, 2014) to April 21, 2015 (34 weeks after the second reform was instituted on September 23, 2014).

The first reform reduced C-section rates by 4.9% overall, with a larger (8.2%) impact for first-time mothers. By comparing the results from the first and second round of reforms, we show that physician-level financial incentives accounted for 55% of the observed reduction in C-section rates, and patient-level financial incentives accounted for 29% of the observed reduction. There was no evidence of adverse health effects associated with this reduction in C-section rates—and some evidence of health benefits, including lower neonatal intensive care unit (NICU) hospitalizations and fewer maternal deaths.

These findings indicate that financial incentives do have an effect on C-section rates, since they went down by roughly 10% (i.e., a 5% decline on a 53% base). However, these findings also indicate that more aggressive strategies will be necessary to reduce C-section rates to the levels typically recommended by public health authorities (i.e., 10%–20% of births). Stated more concretely, a 60% reduction in Iran’s rate of C-sections is required to get the C-section rate down to 20% of all births, and an 81% reduction is required to get the C-section rate down to 10% of all births—but the substantial financial incentives we study only reduced the C-section rate by 10%.

Section 2 reviews the factors that affect C-section rates and past efforts to reduce them. Section 3 describes our data and provides background on Iran’s health care system. Section 4 outlines our estimation strategy and provides the results. Section 5 considers the policy implications of our findings.

In any given pregnancy, the decision to deliver by C-section is affected by multiple clinical and nonclinical factors. Clinical factors include whether a prior delivery was by C-section, malpresentation, and fetal distress [25]. Nonclinical factors include financial incentives, physician and patient preferences, insurance status, malpractice risk, and hospital characteristics [13, 26, 27]. Physicians may have incentives to prefer C-sections in cases where the clinical indications are marginal; as an article in the flagship Journal of Obstetrics and Gynecology noted:

a cesarean takes about 45 minutes and can be scheduled at my convenience. In contrast, labor and vaginal delivery often require spending many hours at the patient’s bedside, canceling office hours, inconveniencing other patients, sacrificing sleep and personal time. And perhaps the most powerful incentive of all: it is rare for an obstetrician to be sued for the decision to perform a cesarean, even an unjustified cesarean. [28]

Another obstetrician put the matter more concisely in an interview with National Public Radio: “[y]ou’re going to pay me more, you’re not going to sue me and I’ll be done in a[n] hour” [29].

In Iran, factors that influence the choice of a C-section are multidimensional, and include economics (e.g., financial, insurance, and medical factors), the organizational and social context of delivery (e.g., the absence of an on-call physician, distrust between obstetricians and midwives), and the personal preferences of the patient (i.e., the perception that vaginal delivery is time-consuming, imposes high-stress levels, and is unpredictable) [30, 31]. Social and cultural factors are also important; a Time magazine article from 2006 noted that “[v]aginal childbirth is very out these days in Tehran .…No longer the provenance of last-minute complications or doctors’ liability fears, caesarean delivery is viewed here as the modern woman’s choice” [20].

Efforts to reduce C-section rates have included a wide array of initiatives, including education (aimed at patients) clinical practice guidelines (aimed at physicians), greater use of midwives, and direct economic incentives (i.e., paying the same amount for a vaginal delivery and a C-section) [13, 14, 32]. The use of financial incentives in this setting has been controversial, and public health personnel have cautioned against their use, except under limited and carefully controlled circumstances [13, 14].

Multiple studies have examined the impact of financial incentives on C-section rates in countries other than Iran [33, 34, 35, 36, 37, 38, 39, 40]. The more sophisticated studies use a DiD approach to compare C-section rates before and after a payment shock and find only a modest (<1%) reduction in C-section rates [32, 33, 36, 37]. Other scholars have also evaluated the impact of the HTP on various aspects of the Iranian health system, including C-section rates [23, 41, 42, 43, 44, 45]. Prior studies focusing on C-section rates have all used an event study approach, and have typically focused on a small number of hospitals [42]. Only one prior study uses nationwide data from Iran, and they find a significant decline in C-sections in public hospitals after the first reform, and in both public and private hospitals after the second reform using an event study approach [41].

Rather than an event study, we use nationwide data from Iran to conduct a DiD analysis, treating each round of reform as exogenous, consecutive, and nonidentical policy interventions. Our use of DiD analysis allows us to separately examine the effects of financial incentives on physicians and patients—unlike previous studies, which used an event study approach. We also examine clinical outcomes in greater depth than previous studies.

3.1. Data

The Iranian Maternal and Neonatal database (IMaN) includes detailed information on all births in Iran [46]. IMaN includes information on the date of birth, age of the mother, the number of past deliveries, weeks of gestation at birth, baby weight, birth order (for twins), method of delivery, nationality, number of past pregnancies and abortions, Apgar scores at 1 and 5 min, and information on maternal health and delivery outcomes. The IMaN database also includes information on the province, hospital, and hospital type at which the birth occurred. At each hospital, a specific department is responsible for submitting information to the IMaN database. Multiple previous studies have been based on information from the IMaN database [18, 39].

We cleaned the registry data and dropped observations with maternal age <15 (2,824 births); maternal age >60 (497 births); 13+ prior deliveries (163 births); baby weight >6 kg (74 births); or baby gender unknown (1,112 births). In total, we dropped 4,670 births, or 0.23% of all the births in our dataset. In robustness checks, we obtained similar results to those we report when we included all of these births. We provide additional detail on the demographics of our data in Appendix Table A-1.

3.2. Iran’s HTP

As noted previously, the HTP created large financial incentives discouraging the use of C-sections in 2014. Payment to physicians in Iran is calculated by multiplying the “Relative Value Unit” (RVU) for each service by a conversion factor. The United States uses a similar approach to physician payment under Medicare Part B. RVUs and conversion factors are set by an administrative process, which takes account of time and expertise required, location of services, and physician and patient characteristics.1

The first round of HTP reforms took effect on May 5, 2014, and dramatically increased the RVU for a vaginal delivery performed in a public hospital. The same reform eliminated the patient’s co-payment if they delivered vaginally. Just over 4 months later (September 23, 2014), the IMHME updated the RVUs for both public and private hospitals, which effectively extended a modified version of the first set of reforms to all hospitals.

Table 2 summarizes the applicable RVUs for vaginal deliveries and C-sections during each of the relevant periods (pre-reform, after the first reform, and after the second reform). Each cell is expressed as a multiple of the conversion factor, which is different in public and private hospitals. Apart from these 2 rounds of reform, annual updates in conversion factors affected both physician fees and patient co-payments for vaginal deliveries and C-sections proportionally.

Table 2.

Payment for vaginal delivery and C-sections in public and nonpublic hospitals (in RVUs)

Pre-ReformAfter First ReformAfter Second Reform
PaymentHospital TypeVaginalC-sectionVaginalC-sectionVaginalC-section
Total payment to physician Public 17kp 21kp 45kp 21kp 50kp 40kp 
Nonpublic 17knp 21knp 17knp 21knp 50knp 40knp 
Patient share (co-payment) Public 1.7kp 2.1kp 2.1kp 4kp 
Nonpublic 1.7k 2.1knp 1.7knp 2.1knp 5knp 4knp 
Pre-ReformAfter First ReformAfter Second Reform
PaymentHospital TypeVaginalC-sectionVaginalC-sectionVaginalC-section
Total payment to physician Public 17kp 21kp 45kp 21kp 50kp 40kp 
Nonpublic 17knp 21knp 17knp 21knp 50knp 40knp 
Patient share (co-payment) Public 1.7kp 2.1kp 2.1kp 4kp 
Nonpublic 1.7k 2.1knp 1.7knp 2.1knp 5knp 4knp 

Total payment to physician = payment from IMHME + co-payment from patient. Iran uses different conversion factors (k) for public and nonpublic hospitals, which we indicate with kp and knp. The first reform took effect on May 5, 2014, and the second reform took effect on September 23, 2014.

The RVUs in Table 2 are for Iranian mothers; non-Iranian mothers who delivered in public hospitals had a co-payment of 10% of the physician fees (i.e., 2.1kp prior to the second reform and 4kp after). Table 2 treats all nonpublic hospitals as if they have the same conversion factor, but there is additional variation based on ownership status (e.g., private, charity, social insurance, and military), which we ignore for purposes of Table 2. No hospital changed its ownership and status from public to nonpublic or vice versa during our study period. Table 1 expresses the same information in Table 2 in terms of the ratio of payment for a vaginal delivery, relative to a C-section.

Finally, we note that the first reform also imposed a physician-level ceiling on payment for C-sections performed in public hospitals. Hospitals are authorized (but not required) to cut payments to physicians whose C-section rate exceeds 45% for any additional C-sections. Unfortunately, we do not have detail on whether and how public hospitals actually implemented this part of the HTP, so we exclude it from Table 2. We treat this aspect of the HTP as a residual factor in our regression analysis in Section 4, after we quantify the impact of the economic incentives imposed on physicians and patients.

3.3. Summary statistics

Table 3 presents summary statistics for all births in Iran over an extended period (September 2013–April 2015) that includes both rounds of reform, broken down by delivery site (public and nonpublic hospitals). We provide additional detail in Appendix Table A-2.

Table 3.

Hospital type and C-section rate

OwnershipNo. of HospitalsShare of HospitalsNo. of BirthsShare of Births% Births by C-Section
Public 471 54% 1,234,503 60% 43% 
Nonpublic 396 46% 830,113 40% 67% 
All 867 100% 2,064,236 100% 53% 
OwnershipNo. of HospitalsShare of HospitalsNo. of BirthsShare of Births% Births by C-Section
Public 471 54% 1,234,503 60% 43% 
Nonpublic 396 46% 830,113 40% 67% 
All 867 100% 2,064,236 100% 53% 

Data are from September 23, 2013, to April 21, 2015.

As Table 3 reflects, 53% of all births in Iran were by C-section, but the rate of C-sections was significantly lower in public hospitals (43%) than in nonpublic hospitals (67%; t-stat: 340). In fairness, as we show in Appendix Table A-2, there is significant variation in C-section rates by hospital type within these broad categories, with some types of nonpublic hospitals having lower rates, and some types of public hospitals having higher rates.

If C-sections in Iran are driven primarily by medical/clinical factors, they should be randomly distributed throughout the week (14.2% per day). Figure 1 shows that although vaginal deliveries are evenly distributed throughout the week, C-sections are not. Delivery by C-section is substantially less common during the weekend (i.e., Thursday and Friday), with the largest difference from the expected rate on Friday (7.3% actual vs. 14.2% expected, t-stat: 85.9).

Figure 1.

Share of births by day. Share of C-section and vaginal births for 2,064,236 births from September 23, 2013, to April 21, 2015.

Figure 1.

Share of births by day. Share of C-section and vaginal births for 2,064,236 births from September 23, 2013, to April 21, 2015.

Close modal

Similarly, if C-sections are being driven primarily by medical/clinical factors, they should be randomly distributed throughout the day, with 4.1% occurring during each hour. Because of data limitations, we only have the time of delivery for births after March 21, 2015, which is after the second reform has taken effect. However, we have no reason to believe any of the reforms we study affect the timing of a C-section during the day, conditional on a decision to deliver by C-section.

Figure 2 presents the results. We round the time of delivery down to the closest hour—so a delivery that occurs at 7:59 AM is counted as a 7 AM delivery.

Figure 2.

Share of births by hour. Share of C-section and vaginal births for births that occurred between March 21, 2015, and January 6, 2018.

Figure 2.

Share of births by hour. Share of C-section and vaginal births for births that occurred between March 21, 2015, and January 6, 2018.

Close modal

As Figure 2 reflects, the period between 8 AM and 1 PM accounts for 50% of all C-sections performed in Iran, even though these time slots only account for 20.8% of the hours in a day. Figures 1 and 2 offer suggestive evidence that many C-sections are not driven by clinical factors but are instead being scheduled for the mutual convenience of physicians and patients.

What about the timing of a C-section relative to weeks of gestation? As Appendix Table A-1 reflects, about 42% of all C-sections are performed at 38 weeks of gestation. A C-section at 38 weeks of gestation is a full week earlier than is commonly recommended, particularly given the known risks of early delivery [47, 48]. In combination, Figures 1 and 2 and Appendix Table A-1 indicate that nonclinical factors substantially influence whether and when a C-section is performed in Iran. Before we turn to formal DiD analysis, Figure 3 visualizes the C-section rate in public and nonpublic hospitals during our study period.

Figure 3.

C-section rates in public and nonpublic hospitals over time. Data from September 23, 2013, to April 21, 2015. The left vertical red line is the first reform (May 5, 2014), and the right vertical red line is the second reform (September 23, 2014).

Figure 3.

C-section rates in public and nonpublic hospitals over time. Data from September 23, 2013, to April 21, 2015. The left vertical red line is the first reform (May 5, 2014), and the right vertical red line is the second reform (September 23, 2014).

Close modal

Figure 3 shows that C-section rates in public hospitals decreased substantially after the first reform was implemented, while they remained stable in nonpublic hospitals. The C-section rate in public hospitals declined by almost 7% (significant, t-stat: 167) after the first reform, while it increased by 1.2% in nonpublic hospitals (insignificant, t-stat: 1.9). After the second reform, we observe a downward trend in C-section rates in nonpublic hospitals, while they remained stable in public hospitals. The overall rate of C-sections in Iran dropped by 2.5% if we compare the rate prior to the first reform versus after the second reform. Visual inspection of Figure 3 suggests that there are similar pre-reform trends in C-section rate in public and nonpublic hospitals; we confirm this point using an F-test.2

In Section 4, we use DiD regression analysis to evaluate the impact of these reforms on C-section rates and disentangle the relative impact of the financial incentives created by these reforms on physicians and patients. Our regression analysis controls for various factors, including fixed effects for weeks of gestation, hospitals, and dummies for region and time (weeks of year).

To investigate the impact of the reforms, we estimate the following equation:

1

yijt are our dependent variables of interest including whether a C-section was performed, and maternal and infant health outcomes. Dj is a dummy for hospital, Dt is a dummy for week of the year, Dgt is group time dummy including group trends. In total we have 2,826 dummies in our benchmark regressions.

The unit of observation for our analyses is an individual delivery so we can control for characteristics of mother, baby, as well as labor conditions in Xi. RF is a first reform dummy, and α is our coefficient of interest using a DiD identification. The treatment dummy is 1 in public hospitals and 0 otherwise. Table 4 shows the results, restricted to observations (births) after the first reform, but prior to the second reform.

Table 4.

Impact of first reform on C-section rates

Variable(1)(2)(3)(4)(5)(6)
Public × After −0.080*** −0.076*** −0.053*** −0.055*** −0.051*** −0.049*** 
(0.010) (0.010) (0.006) (0.007) (0.005) (0.005) 
After −0.140*      
(0.008)      
Public −0.193*** −0.190***     
(0.0080) (0.0210)     
Fixed effects: 
 Week  
 Hospital   
 Group trend      
Week × Region    
Day of week     
Controls       
 Mother     
 Baby      
Constant 0.680 0.651 0.504 0.458 0.308 0.422 
(0.019) (0.020) (0.052) (0.049) (0.035) (0.032) 
No. Obs. 855,660 855,660 855,660 855,660 855,660 855,660 
R2 0.057 0.058 0.085 0.194 0.386 0.455 
Variable(1)(2)(3)(4)(5)(6)
Public × After −0.080*** −0.076*** −0.053*** −0.055*** −0.051*** −0.049*** 
(0.010) (0.010) (0.006) (0.007) (0.005) (0.005) 
After −0.140*      
(0.008)      
Public −0.193*** −0.190***     
(0.0080) (0.0210)     
Fixed effects: 
 Week  
 Hospital   
 Group trend      
Week × Region    
Day of week     
Controls       
 Mother     
 Baby      
Constant 0.680 0.651 0.504 0.458 0.308 0.422 
(0.019) (0.020) (0.052) (0.049) (0.035) (0.032) 
No. Obs. 855,660 855,660 855,660 855,660 855,660 855,660 
R2 0.057 0.058 0.085 0.194 0.386 0.455 

855,660 births from May 1, 2014, to September 23, 2014. Standard errors are clustered on hospitals. Control variables include dummy for midwifery labor, baby gender, mother’s age, number of pregnancies, number of previous births, previous abortion, gestation, baby weight, Apgar at 1 and 5 min, dummy for pregnancy complications, dummy for day and hour of week. Group trend = linear week trend for public hospitals and nonpublic hospitals. In Appendix Table A-3, we provide further detail on the impact of birth, mother and baby specifications on cesarean rates, based on the analysis in column (6).

***Significant at the 1% level. **Significant at the 5% level. *Significant at the 10% level.

Table 4 shows that the combined effects of the first reform are statistically significant but economically modest. Iran completely eliminated patient co-payments and increased physician payments by 164% for vaginal deliveries in public hospitals—but C-sections declined by only 4.9% (Table 4, column (6)). In fairness, this is a 10% decline on a C-section base rate of 53%—but Iran still has a long way to go to get to the C-section rates typically recommended by public health authorities (10%–20% of births).

To determine whether there is heterogeneity in the effects of the first reform, Table 5 reestimates Column (6) in Table 4 for various subgroups of mothers and infants.

Table 5.

Heterogeneous impact of first reform on C-section rates

Dependent Variable: C-Section Delivery
AllFirst ChildSecond ChildTwinsNon-Iranian MotherMaternal HypertensionMaternal Diabetes
Public × After −0.049*** −0.082*** −0.025*** 0.062 −0.033** −0.036* −0.060*** 
(0.005) (0.006) (0.0046) (0.046) (0.016) (0.019) (0.010) 
No. Obs. 855,660 386,388 308,674 1,835 38,668 14,057 19,029 
R2 0.455 0.292 0.638 0.694 0.459 0.471 0.484 
 Baby Weight (kg) Maternal Age  
 <2.5 2.5–4 >4 <20 20–30 >30 Delivery at 38 Weeks 
Public × After −0.029*** −0.051*** −0.032** −0.071*** −0.052*** −0.037*** −0.051*** 
(0.009) (0.005) (0.01) (0.009) (0.0053) (0.005) (0.005) 
No. Obs. 62,948 769,330 23,382 58,682 532,377 264,601 271,457 
R2 0.325 0.471 0.491 0.303 0.434 0.527 0.459 
Dependent Variable: C-Section Delivery
AllFirst ChildSecond ChildTwinsNon-Iranian MotherMaternal HypertensionMaternal Diabetes
Public × After −0.049*** −0.082*** −0.025*** 0.062 −0.033** −0.036* −0.060*** 
(0.005) (0.006) (0.0046) (0.046) (0.016) (0.019) (0.010) 
No. Obs. 855,660 386,388 308,674 1,835 38,668 14,057 19,029 
R2 0.455 0.292 0.638 0.694 0.459 0.471 0.484 
 Baby Weight (kg) Maternal Age  
 <2.5 2.5–4 >4 <20 20–30 >30 Delivery at 38 Weeks 
Public × After −0.029*** −0.051*** −0.032** −0.071*** −0.052*** −0.037*** −0.051*** 
(0.009) (0.005) (0.01) (0.009) (0.0053) (0.005) (0.005) 
No. Obs. 62,948 769,330 23,382 58,682 532,377 264,601 271,457 
R2 0.325 0.471 0.491 0.303 0.434 0.527 0.459 

Regressions correspond to column 6 in Table 4. Standard errors are clustered on hospitals. Hypertension and diabetes are not further explained in the data, so we do not know whether it is limited to gestational hypertension and gestational diabetes.

***Significant at the 1% level. **Significant at the 5% level. *Significant at the 10% level.

As Table 5 indicates, we find statistically significant reductions in most subpopulations, although the magnitude of the decline varies. The C-section rate declined across all maternal ages, and baby weights, with the largest decline for the youngest mothers (<20) and babies whose weight ranged from 2.5 to 4 kg. The C-section rate also declined for mothers with health issues that complicate pregnancy (i.e., diabetes and hypertension).

We do not observe a reduction in C-section rates in twin pregnancies—presumably because the decision to perform a C-section in such cases is primarily driven by medical considerations. We observe a smaller absolute reduction among non-Iranian mothers (3.3%), but they have a lower base rate of C-sections than the rest of the population (41% vs. 53%), so the relative reduction is comparable (10% for both groups), even though the co-payment is not waived for non-Iranian mothers who give birth in public hospitals. The largest reduction in Table 5 is for first-born children, where the C-section rate dropped by almost 8%. Vaginal birth after C-section is relatively uncommon in Iran, so the smaller (but still statistically significant) drop of 2.5% for second birth was expected.

Physicians in Iran are required to report to the IMHME the justification for performing a C-section. As we show in Table 6, there are material differences in the reasons given by physicians for performing a C-section in first-time mothers versus mothers who have delivered previously. We focus on the 4-month period immediately after the first reform and before the second reform (i.e., May–September 2014).

Table 6.

Justification for performing a C-section

First-Time MothersMothers With 1+ Previous Births
Previous C-section or myomectomy 3.4% 74.1% 
All other medical causes 60.1% 16.4% 
Mother’s request 17.6% 2.6% 
Other (not specified) 18.9% 6.9% 
First-Time MothersMothers With 1+ Previous Births
Previous C-section or myomectomy 3.4% 74.1% 
All other medical causes 60.1% 16.4% 
Mother’s request 17.6% 2.6% 
Other (not specified) 18.9% 6.9% 

Reasons given by physicians for performing a C-section for 220,384 births to first-time mothers and 249,646 births to mothers with 1+ prior births in Iran during May 1, 2014, to September 23, 2014. All other medical causes = lack of progress + fetal distress + abnormal presentation + placental/umbilical cord problems + maternal hypertension + cephalopelvic disproportion. “Previous C-section or myomectomy” are reported together in the original data, so we are unable to break them out.

As Table 6 reflects, during the period immediately after the first reform went into effect, among first-time mothers giving birth in Iran by C-section, the most popular physician justification were legitimate medical causes (i.e., lack of progress, fetal distress, abnormal presentation, placental/umbilical cord problems, maternal hypertension, cephalopelvic disproportion). These medical causes collectively accounted for 60.1% of births by C-section. By definition, there were no prior C-sections in first-time mothers—meaning that medical causes accounted for 63.5% of C-sections among first-time mothers (60.1% for other medical causes + 3.4% for myomectomy), followed by 18.9% for other (not specified) causes and 17.6% for mother’s request. By comparison, among mothers who had given birth previously, “previous C-section or myomectomy” was the most common reason, accounting for 74.1% of births by C-sections. All other medical causes accounted for 16.4% of births by C-section, followed by other (not specified) at 6.9% and mother’s request at 2.6%. These figures make it clear that the high rate of C-sections in Iran is a complex matter, but many physicians and mothers seem to be adhering to Cragin’s maxim: “once a Cesarean, always a Cesarean” [49].

We now turn to the impact of patient-level incentives on whether a C-section is performed. As Table 1 reflects, the first reform simultaneously increased physician compensation and eliminated patient co-payments for vaginal deliveries in public hospitals. What is the relative contribution of these 2 policies on the overall decline in C-section rates? To analyze that issue, we estimate a second equation that takes advantage of the fact that in the second reform, the patient co-payment for a vaginal delivery in nonpublic hospitals rose, while the co-payment for a vaginal delivery in public hospitals was set at $0 by the first reform. This variation in policies across 2 reforms allows us to estimate the following specification, based on the difference in physician fees and patient co-payments for vaginal delivery versus C-section:

2

The first term is the nominal difference in physician payment between vaginal and cesarean delivery for each observation. The second term is the nominal gap for the out-of-pocket payment by patient. The difference in physician fees and patient co-payments is expressed in millions of riyals; we obtain similar results when we use fee ratios.

Table 7 reports our estimation of Equation 2, which uses all of our data, including observations after the second reform. Because the patient’s co-payment is 10% of the amount that the physician receives, the magnitude of the coefficients for patient co-payments will be (by construction) 10× the magnitude of the coefficients for physician fees. Similarly, because the second reform dramatically increased physician fees for vaginal deliveries, patient co-payments in nonpublic hospitals went up as well—and exceeded the patient co-payments for C-sections. The result is that the coefficients in Table 7 are negative for physician fees, but positive for patient co-payments.

Table 7.

Impact of second round of reforms on C-section rates

(1)(2)(3)(4)(5)
Physician feeVD-CS −4.942*** −4.939*** −1.305*** −1.103*** −1.091*** 
(0.587) (0.593) (0.224) (0.174) (0.163) 
Patient paymentVD-CS 50.537*** 50.548*** 10.948*** 10.303*** 9.742*** 
(4.058) (4.066) (1.804) (1.505) (0.144) 
Fixed effects 
 Week  
 Hospital   
Week × Region   
Day of week   
Controls 
 Mother    
 Baby     
Constant 6.047 6.672 9.895 8.954 8.538 
(0.377) (0.207) (0.0846) (0.267) (0.193) 
No. Obs. 2,064,236 2,064,236 2,064,236 2,064,236 2,064,236 
R2 0.098 0.098 0.185 0.402 0.467 
(1)(2)(3)(4)(5)
Physician feeVD-CS −4.942*** −4.939*** −1.305*** −1.103*** −1.091*** 
(0.587) (0.593) (0.224) (0.174) (0.163) 
Patient paymentVD-CS 50.537*** 50.548*** 10.948*** 10.303*** 9.742*** 
(4.058) (4.066) (1.804) (1.505) (0.144) 
Fixed effects 
 Week  
 Hospital   
Week × Region   
Day of week   
Controls 
 Mother    
 Baby     
Constant 6.047 6.672 9.895 8.954 8.538 
(0.377) (0.207) (0.0846) (0.267) (0.193) 
No. Obs. 2,064,236 2,064,236 2,064,236 2,064,236 2,064,236 
R2 0.098 0.098 0.185 0.402 0.467 

2,064,236 deliveries from September 23, 2013, to April 21, 2015. Regressions are OLS. Standard errors are clustered on hospital. Physician fees and patient co-payments are normalized to millions of local currencies. In Appendix Table A-3, we provide further detail on the impact of birth, mother and baby specifications on cesarean rates, based on the analysis in column (5).

***Significant at the 1% level. **Significant at the 5% level. *Significant at the 10% level.

Table 7 shows that C-section rates are affected by both physician fees and patient co-payments, relative to the fees and co-payments for vaginal delivery. We find that a 1 million Rial increase in the fee for a vaginal delivery (i.e., approximately $40 at the time of the first reform) reduces the C-section rate by 1.1%. The first reform increased the fee for a vaginal delivery in public hospitals by roughly 2.4 million Rials, since the physician fee for a vaginal delivery increased from 17kp to 45kp with kp = 88,000 Rials. This translates into a 2.7% decline in C-section rates, or about half of the observed decline in Table 4.

Table 7 similarly shows that a 1 million Rial increase in the co-payment for a vaginal delivery results in a 9.7% increase in C-sections. In the first reform, the IMHME eliminated patient co-payments, which would otherwise have been 140,000 Rials (i.e., approximately $6 at the time of the first reform). This translates into a 1.4% decline in C-section rates. Putting these 2 findings together, we can explain roughly 84% of the total reduction in C-sections in public hospitals ([2.7+1.4]/4.9) after the first reform, with financial incentives for physicians explaining roughly twice as much of the reduction as financial incentives on patients. The remaining balance (16%) is attributable to factors other than the specific economic incentives imposed on physicians and patients—including any educational initiatives and the impact of allowing public hospitals to cut payments to physicians whose C-section rate exceeds 45% for any additional C-sections.

We used a similar set of regressions to examine whether there is heterogeneity (based on patient-level attributes) in the relative impact of these reforms. As shown in Appendix Tables A-4 to A-6, depending on the demographic group, we can explain 69%–86% of the decline in C-section rates—and 94% of the decline in C-sections at 38 weeks of gestation. Physician fee effects account for two-thirds of the reduction (range: 61%–75%), with patient co-payment effects accounting for the remainder.

What about the health effects of these reforms? Do we find evidence of increased maternal or infant morbidity and mortality? In Table 8 we examine these issues for all births, for all high-risk pregnancies, for all high-risk infants, and for various maternal and infant subgroups. With one exception, we find substantial evidence that the payment reforms in question resulted in either neutral or improved health outcomes for both mothers and babies.

Table 8.

Health effects of payment reforms

Regression(1)(2)(3)(4)(5)(6)
Mothers/BirthsNICU AdmissionMaternal ICU AdmissionApgar, 1 minApgar, 5 minInfant DeathMaternal Death (%)
All −0.013*** 0.005 0.001 −0.016 0.004 −0.004** 
0.004 0.004 0.054 0.069 0.005 0.002 
High-risk pregnancy −0.060** −0.031* −0.189 −0.271 −0.009 0.004 
0.024 0.016 0.387 0.315 0.007 0.018 
High-risk infants 0.060 0.000 −0.082 −0.041 −0.001 0.000 
0.082 0.001 0.043 0.077 0.002 0.051 
First child −0.017*** 0.016 0.125 0.138 0.000 0.005 
0.006 0.014 0.147 0.208 0.000 0.006 
Second child −0.017*** −0.001** −0.127 −0.074 −0.001 0.005 
0.006 0.001 0.092 0.086 0.001 0.004 
Maternal hypertension −0.192*** −0.024** −0.208 −0.152 −0.018 0.002 
0.025 0.008 0.467 0.273 0.001 0.023 
Maternal diabetes 0.016 0.048** −0.527 −0.309 0.001 0.003 
0.043 0.019 0.329 0.584 0.001 0.031 
Low birth weight (<2.5 kg) −0.041 0.004 0.154 −0.284 −0.006 0.048 
0.026 0.010 0.105 0.429 0.006 0.062 
Normal birth weight (2.5–4.0 kg) −0.005*** 0.006 −0.147 0.258 0.005 0.000 
0.002 0.005 0.107 0.379 0.006 0.001 
High birth weight (>4 kg) 0.001 0.016 −0.085 −0.022 −0.006 0.000 
0.005 0.006 0.101 0.085 0.082 1.538 
Twins 0.193 −0.005 −0.121 −0.052 −0.000 0.000 
0.128 0.007 0.087 0.064 0.000 0.006 
Maternal age <20 0.009 0.002 −0.053 −0.91 0.085 0.009 
0.010 0.010 0.036 0.791 0.086 0.008 
20 ≤ Maternal age < 30 −0.015*** 0.009 0.095 0.107** −0.001*** 0.004 
0.004 0.008 0.056 0.049 0.000 0.002 
Mother age ≥30 −0.015** 0.000 0.001 −0.082 0.001 0.004 
0.007 0.001 0.003 0.137 0.001 0.004 
Delivery at 38 weeks 0.001 0.002 0.119 0.100 −0.000 −0.000 
0.001 0.002 0.125 0.154 0.000 0.000 
Regression(1)(2)(3)(4)(5)(6)
Mothers/BirthsNICU AdmissionMaternal ICU AdmissionApgar, 1 minApgar, 5 minInfant DeathMaternal Death (%)
All −0.013*** 0.005 0.001 −0.016 0.004 −0.004** 
0.004 0.004 0.054 0.069 0.005 0.002 
High-risk pregnancy −0.060** −0.031* −0.189 −0.271 −0.009 0.004 
0.024 0.016 0.387 0.315 0.007 0.018 
High-risk infants 0.060 0.000 −0.082 −0.041 −0.001 0.000 
0.082 0.001 0.043 0.077 0.002 0.051 
First child −0.017*** 0.016 0.125 0.138 0.000 0.005 
0.006 0.014 0.147 0.208 0.000 0.006 
Second child −0.017*** −0.001** −0.127 −0.074 −0.001 0.005 
0.006 0.001 0.092 0.086 0.001 0.004 
Maternal hypertension −0.192*** −0.024** −0.208 −0.152 −0.018 0.002 
0.025 0.008 0.467 0.273 0.001 0.023 
Maternal diabetes 0.016 0.048** −0.527 −0.309 0.001 0.003 
0.043 0.019 0.329 0.584 0.001 0.031 
Low birth weight (<2.5 kg) −0.041 0.004 0.154 −0.284 −0.006 0.048 
0.026 0.010 0.105 0.429 0.006 0.062 
Normal birth weight (2.5–4.0 kg) −0.005*** 0.006 −0.147 0.258 0.005 0.000 
0.002 0.005 0.107 0.379 0.006 0.001 
High birth weight (>4 kg) 0.001 0.016 −0.085 −0.022 −0.006 0.000 
0.005 0.006 0.101 0.085 0.082 1.538 
Twins 0.193 −0.005 −0.121 −0.052 −0.000 0.000 
0.128 0.007 0.087 0.064 0.000 0.006 
Maternal age <20 0.009 0.002 −0.053 −0.91 0.085 0.009 
0.010 0.010 0.036 0.791 0.086 0.008 
20 ≤ Maternal age < 30 −0.015*** 0.009 0.095 0.107** −0.001*** 0.004 
0.004 0.008 0.056 0.049 0.000 0.002 
Mother age ≥30 −0.015** 0.000 0.001 −0.082 0.001 0.004 
0.007 0.001 0.003 0.137 0.001 0.004 
Delivery at 38 weeks 0.001 0.002 0.119 0.100 −0.000 −0.000 
0.001 0.002 0.125 0.154 0.000 0.000 

Births from September 23, 2013, to May 5, 2014 (before first reform) and September 23, 2014, to April 21, 2015 (after second reform) for births in public hospitals. High-risk pregnancies are those with maternal hypertension or maternal diabetes or pregnancies with maternal age >35 or maternal age <17. High-risk infants are high birth weight (>4 kg) and twin pregnancies. Fixed effects for week, hospital, and day of week and controls for mother and baby are in all regressions. Regressions are OLS. Standard errors are clustered on hospital. Observations and R2 for each row are in Appendix Table A-7.

***Significant at the 1% level. **Significant at the 5% level. *Significant at the 10% level.

Table 8 indicates that NICU admissions at public hospitals declined for all births, with larger declines for high-risk pregnancies, first and second births, mothers with high blood pressure, and mothers who were 20 years of age or older. Maternal deaths declined as well, as did infant deaths for mothers who were between 20 and 30 years. Maternal ICU admissions declined for all high-risk pregnancies, and for mothers with hypertension, and those giving birth to their second child, but increased for diabetic mothers. Table 5 also indicates that C-section rates for diabetic mothers declined more than for all births. There were no adverse health effects among high-risk infants. The combination of these findings indicates that apart from diabetic mothers, the health impact of the HTP was either neutral or positive. Further investigation of health outcomes among diabetic mothers is obviously warranted.

Reducing high C-section rates is a long-standing global public health priority, although the role of financial incentives in that effort is controversial. For example, recommendations from the WHO on reducing unnecessary C-sections prioritized nonfinancial strategies even while noting “financial incentive[s] remain a major determinant of caesarean births in all settings” [13, 14]. The WHO report cautioned that the use of financial incentives to reduce C-section rates “are recommended only in the context of rigorous research” [13, 14].

We report on the impact of substantial financial incentives on the rate of C-sections in Iran. This exogenous policy reform affected both physician fees and patient co-payments. Although the policy reform initially focused on public hospitals, it was subsequently extended to all hospitals in Iran. Prior to the first reform, physician fees for vaginal deliveries in public hospitals were 20% lower than physician fees for C-sections. After the first reform, physician fees for vaginal deliveries in public hospitals were 141% higher than physician fees for C-sections. Using DiD regression analysis, we show that this policy change caused a 4.9% reduction in the number of C-sections in public hospitals in Iran, with a larger impact on first-time mothers (8.2% reduction).

Iran has also used a variety of nonfinancial reforms to reduce the rate of C-sections, including “mother-friendly hospitals (220 new hospitals offer no-pain delivery methods by the end of 2016); development of standard protocols; preparation classes for mothers (450 thousand classes), midwives, and workshops for specialists and midwives (500 obligatory workshops), and construction of 865 LDR [labor and delivery rooms] in public hospitals” [24]. Other countries have experimented with these and other nonclinical interventions [13, 14, 50]. However, our findings indicate that the economic incentives imposed on physicians and patients accounted for the overwhelming majority of the reduction in C-sections (84%) in Iran.

Of course, the decision to deliver by C-section is affected by multiple factors [51, 52]. And even after the reforms we describe, the C-section rate in public hospitals in Iran is far above that of most countries—and the rate in nonpublic hospitals in Iran is higher still [7, 10]. Our findings also indicate the importance of nonclinical factors on C-section rates, such as the concentration of C-sections on weekday mornings, and at 38 weeks of gestation—a full week earlier than is clinically justified.

These dynamics also point to the limitations of using financial incentives as a “silver bullet” to reduce C-section rates to a reasonable level. Reducing Iran’s C-section rate to 30% (which is still 50% higher than the highest figure recommended in the public health literature [20%]) would require a further increase in physician payments for vaginal deliveries of roughly 550% while keeping C-section payments where they are.

In addition, we note that the formula for the patient co-payment in nonpublic hospitals is working at cross-purposes to the overall goal of reducing C-sections. After the second reform, physicians in Iran are paid 25% more for a vaginal delivery than for a C-section. But, patients who receive care in a nonpublic hospital must pay 25% more for a vaginal delivery than for a C-section, while in public hospitals patients who deliver vaginally have a co-payment of $0. If the goal is to reduce C-section rates, forcing patients who receive care in nonpublic hospitals to pay more for vaginal deliveries than for C-sections makes absolutely no sense. A consistent set of incentives (i.e., doctors get paid more and patients pay less [or nothing] when there is a vaginal delivery) would be a much more sensible design. Indeed, it might make sense to experiment with direct patient stipends for vaginal deliveries, and to selectively target large financial incentives discouraging elective C-sections—that is, those done at 38 weeks of gestation in first-time mothers with normal birth weight babies.

Critically, other than a modest increase in ICU admissions for mothers with diabetes, we find no evidence the HTP had an adverse impact on mothers and infants. Instead, we find evidence the HTP improved birth outcomes, by reducing maternal deaths and NICU admissions.

Because we do not have physician-specific identifiers for the entirety of the period covered by our dataset, we are unable to evaluate physician-level responses to these reforms. Some physicians work in both public and nonpublic hospitals and may have adjusted their practice patterns in response to the first reform. As noted above, we are also unable to quantify the impact of the reform authorizing public hospitals to cut payments to physicians whose C-section rate exceeds 45% for any additional C-sections—partly because we do not have physician-specific identifiers, and partly because we do not know which public hospitals implemented this policy.

Our findings (4.9% reduction in C-section rates from the first reform) are consistent with the only other study to use nationwide data from Iran (6% reduction, using an event study approach) [41]. The consistency of these findings provides reassurance that our results are robust to alternative specification strategies. Our DiD approach also allows us to separate out the impact of the economic incentives created by the HTP on physicians and patients—with the trade-off that unlike an event study, we are not able to quantify the impact of the second reform.

Our findings indicate the WHO might profitably reconsider its advice to prioritize nonfinancial strategies in addressing the high rate of C-sections. Money may not buy happiness, but when appropriately deployed, it can create incentives to do the right thing. That said, our results also show the limits of even substantial financial incentives in reducing C-sections. Other strategies will be necessary to reduce C-section rates in Iran and elsewhere to the levels typically recommended by public health authorities.

Appendix

Table A-1.

Summary statistics of key variables

HospitalNo. of BirthShare (All)ShareCesarean RateMaternal Death RateBaby Death Rate
PublicNonpublicPublicNonpublicPublicNonpublicPublicNonpublic
Baby weight <2,500 151,334 7.3 69.9 30.1 51.4 67.8 4.5 5.3 188.8 131.8 
2,500–4,000 1,853,860 89.8 59 41 42.4 66.8 0.6 0.5 3.8 
>4,000 59,042 2.9 60.6 39.4 53.4 71.6 0.8 1.7 6.7 3.9 
Week of gestation <30 20,603 1.0 78.6 21.4 32 32.6 22.6 38 964.2 1,106.1 
30–37 299,454 14.5 65.3 34.7 56.3 73.9 1.1 1.6 26.9 15.8 
38 645,529 31.3 50 50 58.6 82.9 0.7 0.3 3.3 1.4 
39+ 1,098,650 53.2 63.7 36.3 33.3 52.8 0.5 0.5 3.5 1.7 
Maternal age <20 139,029 6.7 73 27 28.1 49.5 0.7 0.5 24.8 11.7 
20–30 1,270,857 61.5 59.7 40.3 41.8 64.6 0.9 0.7 18.1 8.2 
>30 654,350 31.8 57.2 42.8 51 73.7 0.9 21.8 10.7 
No. of past delivery 909,080 44 55.4 44.6 41.7 69.6 0.7 22.9 9.9 
752,436 36.5 59.1 40.9 47.7 67 0.7 0.8 15.1 7.4 
2+ 402,720 19.5 71.2 28.8 40.1 58 1.2 0.9 21.6 11.5 
Twin and more No 2,051,099 99.4 59.8 40.2 43.2 66.9 0.9 0.8 19 8.8 
Yes 13,137 0.6 61.6 38.4 83 92.5 1.2 138.4 75.3 
Maternal diabetes 47,830 2.3 47.2 52.8 64.2 78.7 1.8 0.4 26.6 11.1 
Hypertension 46,573 2.3 62.1 37.9 57.3 76.5 1.7 36.3 18.1 
Cardiac disease 10,424 0.5 48.1 51.9 50.5 73.4 3.1 1.8 39.9 9.2 
All 2,064,236 100 59.8 40.2 43.5 67 0.9 0.7 19.8 9.2 
HospitalNo. of BirthShare (All)ShareCesarean RateMaternal Death RateBaby Death Rate
PublicNonpublicPublicNonpublicPublicNonpublicPublicNonpublic
Baby weight <2,500 151,334 7.3 69.9 30.1 51.4 67.8 4.5 5.3 188.8 131.8 
2,500–4,000 1,853,860 89.8 59 41 42.4 66.8 0.6 0.5 3.8 
>4,000 59,042 2.9 60.6 39.4 53.4 71.6 0.8 1.7 6.7 3.9 
Week of gestation <30 20,603 1.0 78.6 21.4 32 32.6 22.6 38 964.2 1,106.1 
30–37 299,454 14.5 65.3 34.7 56.3 73.9 1.1 1.6 26.9 15.8 
38 645,529 31.3 50 50 58.6 82.9 0.7 0.3 3.3 1.4 
39+ 1,098,650 53.2 63.7 36.3 33.3 52.8 0.5 0.5 3.5 1.7 
Maternal age <20 139,029 6.7 73 27 28.1 49.5 0.7 0.5 24.8 11.7 
20–30 1,270,857 61.5 59.7 40.3 41.8 64.6 0.9 0.7 18.1 8.2 
>30 654,350 31.8 57.2 42.8 51 73.7 0.9 21.8 10.7 
No. of past delivery 909,080 44 55.4 44.6 41.7 69.6 0.7 22.9 9.9 
752,436 36.5 59.1 40.9 47.7 67 0.7 0.8 15.1 7.4 
2+ 402,720 19.5 71.2 28.8 40.1 58 1.2 0.9 21.6 11.5 
Twin and more No 2,051,099 99.4 59.8 40.2 43.2 66.9 0.9 0.8 19 8.8 
Yes 13,137 0.6 61.6 38.4 83 92.5 1.2 138.4 75.3 
Maternal diabetes 47,830 2.3 47.2 52.8 64.2 78.7 1.8 0.4 26.6 11.1 
Hypertension 46,573 2.3 62.1 37.9 57.3 76.5 1.7 36.3 18.1 
Cardiac disease 10,424 0.5 48.1 51.9 50.5 73.4 3.1 1.8 39.9 9.2 
All 2,064,236 100 59.8 40.2 43.5 67 0.9 0.7 19.8 9.2 

Maternal and baby death rates are per 10,000 deliveries. Baby deaths are the death of the infant in the delivery room. Maternal death is the death of the mother up to 2 h after delivery. Data includes all deliveries/births in Iran from September 23, 2013, to April 21, 2015. Total number of observations is 2,068,906 before cleaning and 2,064,236 after cleaning. Maternal diabetes, hypertension, and cardiac disease are based on reports to IMaN.

Table A-2.

Additional detail on delivery location/hospital type

OwnershipNo. of HospitalsShare of HospitalsNo. of BirthsShare of Births% Births by C-Section
Public Noneducational 334 39% 677,602 33% 39% 
Educational 137 16% 556,901 27% 49% 
Nonpublic Private: Noneducational 199 23% 333,102 16% 87% 
Social insurance 83 10% 295,494 14% 44% 
Military 69 8% 98,507 5% 61% 
Private: Educational 31 4% 88,640 4% 71% 
Charity 14 2% 14,370 1% 89% 
All public 471 54% 1,234,503 60% 43% 
All nonpublic 396 46% 830,113 40% 67% 
All 867 100% 2,064,236 100% 53% 
OwnershipNo. of HospitalsShare of HospitalsNo. of BirthsShare of Births% Births by C-Section
Public Noneducational 334 39% 677,602 33% 39% 
Educational 137 16% 556,901 27% 49% 
Nonpublic Private: Noneducational 199 23% 333,102 16% 87% 
Social insurance 83 10% 295,494 14% 44% 
Military 69 8% 98,507 5% 61% 
Private: Educational 31 4% 88,640 4% 71% 
Charity 14 2% 14,370 1% 89% 
All public 471 54% 1,234,503 60% 43% 
All nonpublic 396 46% 830,113 40% 67% 
All 867 100% 2,064,236 100% 53% 

Data are from September 23, 2013, to April 21, 2015.

Table A-3.

Impact of birth, mother and baby specifications on cesarean rates

Control VariablesTable 4—Column 6Table 7—Column 5
Weeks of gestation ≤36 −0.0206*** (0.006) −0.0214*** (0.005) 
Weeks of gestation =37 −0.0187*** (0.004) −0.0215*** (0.004) 
Weeks of gestation =39 −0.09*** (0.005) −0.082*** (0.004) 
Weeks of gestation ≥40 −0.154*** (0.006) −0.139*** (0.006) 
20 ≤ age mother < 25 0.086*** (0.003) 0.086*** (0.002) 
25 ≤ age mother < 30 0.145*** (0.004) 0.145*** (0.003) 
30 ≤ age mother <35 0.167*** (0.004) 0.166*** (0.003) 
35 ≤ age mother < 40 0.187*** (0.004) 0.185*** (0.004) 
40 ≤ age mother 0.219*** (0.005) 0.217*** (0.004) 
Diabetics 0.047*** (0.005) 0.047*** (0.004) 
Cardio disease 0.017*** (0.008) 0.016*** (0.006) 
Chronic hypertension 0.113*** (0.006) 0.083*** (0.005) 
Second birth −0.283*** (0.005) −0.276*** (0.004) 
Third birth or higher −0.293*** (0.005) −0.287*** (0.005) 
Low birth weight (BW < 2,500) 0.0318*** (0.004) 0.0302*** (0.004) 
High birth weight (BW > 4,000) 0.105*** (0.004) 0.108*** (0.003) 
Gender −0.01*** (0.001) 0.01*** (0.000) 
Multiple birth (twin+) 0.308*** (0.02) 0.321*** (0.009) 
Prior-C-section(s) 0.628*** (0.01) 0.656*** (0.01) 
Control VariablesTable 4—Column 6Table 7—Column 5
Weeks of gestation ≤36 −0.0206*** (0.006) −0.0214*** (0.005) 
Weeks of gestation =37 −0.0187*** (0.004) −0.0215*** (0.004) 
Weeks of gestation =39 −0.09*** (0.005) −0.082*** (0.004) 
Weeks of gestation ≥40 −0.154*** (0.006) −0.139*** (0.006) 
20 ≤ age mother < 25 0.086*** (0.003) 0.086*** (0.002) 
25 ≤ age mother < 30 0.145*** (0.004) 0.145*** (0.003) 
30 ≤ age mother <35 0.167*** (0.004) 0.166*** (0.003) 
35 ≤ age mother < 40 0.187*** (0.004) 0.185*** (0.004) 
40 ≤ age mother 0.219*** (0.005) 0.217*** (0.004) 
Diabetics 0.047*** (0.005) 0.047*** (0.004) 
Cardio disease 0.017*** (0.008) 0.016*** (0.006) 
Chronic hypertension 0.113*** (0.006) 0.083*** (0.005) 
Second birth −0.283*** (0.005) −0.276*** (0.004) 
Third birth or higher −0.293*** (0.005) −0.287*** (0.005) 
Low birth weight (BW < 2,500) 0.0318*** (0.004) 0.0302*** (0.004) 
High birth weight (BW > 4,000) 0.105*** (0.004) 0.108*** (0.003) 
Gender −0.01*** (0.001) 0.01*** (0.000) 
Multiple birth (twin+) 0.308*** (0.02) 0.321*** (0.009) 
Prior-C-section(s) 0.628*** (0.01) 0.656*** (0.01) 

Estimates corresponds to original regressions of Column 6 in Table 4, and Column 5 in Table 7. These estimates are not reported in their respective tables.

***Significant at the 1% level. **Significant at the 5% level. *Significant at the 10% level.

Table A-4.

Conditional impact of reform on C-section rates

Dependent Variable: C-Section Delivery
Observation:AllFirst ChildSecond ChildTwinsNon-Iranian MotherHypertensionDiabetes
Physician feeVD-CS −1.1*** −1.77*** −0.63*** 1.1 −1.01*** 0.412 −1.18*** 
(0.16) (0.21) (0.13) (1.22) (0.38) (0.46) (0.31) 
Patient co-paymentVD-CS 9.7*** 18.74*** 4.2*** −3.67 3.27 10.38*** 
(0.14) (1.89) (1.17) (10.3)  (3.4) (2.49) 
No. Obs. 2,064,236 909,080 752,436 13,137 87,856 46,573 47,830 
R2 0.467 0.292 0.655 0.362 0.467 0.471 0.479 
 Baby Weight Maternal Age  
 <2,500 2,500–4,000 4,000 <20 20–30 >30 Delivery at 38 Weeks 
Physician feeVD-CS −0.63** −1.15*** −0.64** −1.76*** −1.18*** −0.80*** −1.2*** 
(0.25) (0.16) (0.32) (0.27) (0.17) (0.15) (0.17) 
Patient co-paymentVD-CS 3.69* 10.29*** 5.85** 13.55*** 10.35*** 7.44*** 13.49*** 
(2.02) (1.41) (2.43) (2.23) (1.49) (1.22) (1.48) 
No. Obs. 151,334 1,853,860 59,042 139,029 1,270,857 654,350 645,529 
R2 0.323 0.482 0.488 0.297 0.441 0.541 0.479 
Dependent Variable: C-Section Delivery
Observation:AllFirst ChildSecond ChildTwinsNon-Iranian MotherHypertensionDiabetes
Physician feeVD-CS −1.1*** −1.77*** −0.63*** 1.1 −1.01*** 0.412 −1.18*** 
(0.16) (0.21) (0.13) (1.22) (0.38) (0.46) (0.31) 
Patient co-paymentVD-CS 9.7*** 18.74*** 4.2*** −3.67 3.27 10.38*** 
(0.14) (1.89) (1.17) (10.3)  (3.4) (2.49) 
No. Obs. 2,064,236 909,080 752,436 13,137 87,856 46,573 47,830 
R2 0.467 0.292 0.655 0.362 0.467 0.471 0.479 
 Baby Weight Maternal Age  
 <2,500 2,500–4,000 4,000 <20 20–30 >30 Delivery at 38 Weeks 
Physician feeVD-CS −0.63** −1.15*** −0.64** −1.76*** −1.18*** −0.80*** −1.2*** 
(0.25) (0.16) (0.32) (0.27) (0.17) (0.15) (0.17) 
Patient co-paymentVD-CS 3.69* 10.29*** 5.85** 13.55*** 10.35*** 7.44*** 13.49*** 
(2.02) (1.41) (2.43) (2.23) (1.49) (1.22) (1.48) 
No. Obs. 151,334 1,853,860 59,042 139,029 1,270,857 654,350 645,529 
R2 0.323 0.482 0.488 0.297 0.441 0.541 0.479 

Estimates correspond to Column 6 in Table 4, performed on specified subsamples of full dataset. Week of birth, hospital identification, mother and baby conditions are all included in the regressions. Standard errors are clustered at the hospital level.

***Significant at the 1% level. **Significant at the 5% level. *Significant at the 10% level.

Table A-5.

Relative contribution of physician and patients’ effects to reduction in C-section rate

Effect SourceAllFirst ChildSecond ChildNon-Iranian MotherDiabeticDelivery at 38 Weeks
Physician effect 2.7% 4.2% 1.5% 2.4% 2.8% 2.9% 
Patient effect 1.4% 2.6% 0.6% 1.5% 1.9% 
Total effect 4.1% 6.8% 2.1% 2.4% 4.3% 5.1% 
 Baby Weight Maternal Age 
 <2,500 2,500–4,000 >4,000 <20 20–30 >30 
Physician effect 1.5% 2.8% 1.5% 4.2% 2.8% 1.9% 
Patient effect 0.5% 1.4% 0.8% 1.9% 1.4% 1% 
Total effect 2% 4.2% 2.3% 6.1% 4.2% 2.9% 
Effect SourceAllFirst ChildSecond ChildNon-Iranian MotherDiabeticDelivery at 38 Weeks
Physician effect 2.7% 4.2% 1.5% 2.4% 2.8% 2.9% 
Patient effect 1.4% 2.6% 0.6% 1.5% 1.9% 
Total effect 4.1% 6.8% 2.1% 2.4% 4.3% 5.1% 
 Baby Weight Maternal Age 
 <2,500 2,500–4,000 >4,000 <20 20–30 >30 
Physician effect 1.5% 2.8% 1.5% 4.2% 2.8% 1.9% 
Patient effect 0.5% 1.4% 0.8% 1.9% 1.4% 1% 
Total effect 2% 4.2% 2.3% 6.1% 4.2% 2.9% 

The Physician effect is calculated by multiplying the conditional impact of reform on the C-section rate (in Appendix Table A-4 for that subgroup) × 2.4 million Rials. The Patient effect is calculated by multiplying the conditional impact of reform on the C-section rate (in Appendix Table A-4 for that subgroup) × 0.14 million Rials. The total effect is calculated by summing these 2 components.

Table A-6.

Relative impact of physician fees and patient co-payments on C-section rates

Effect SourceAllFirst ChildSecond ChildNon-Iranian MotherDiabeticDelivery at 38 Weeks
Physician fee effect 55% 51% 60% 73% 47% 57% 
Patient co-payment effect 29% 32% 24% 0% 25% 37% 
Share of total impact 84% 83% 84% 73% 72% 94% 
 Baby Weights Mother Age 
 <2,500 2,500–4,000 >4,000 <20 20–30 >30 
Physician fee effect 52% 55% 47% 59% 54% 51% 
Patient co-payment effect 17% 27% 25% 27% 27% 27% 
Share of total impact 69% 82% 72% 86% 81% 78% 
Effect SourceAllFirst ChildSecond ChildNon-Iranian MotherDiabeticDelivery at 38 Weeks
Physician fee effect 55% 51% 60% 73% 47% 57% 
Patient co-payment effect 29% 32% 24% 0% 25% 37% 
Share of total impact 84% 83% 84% 73% 72% 94% 
 Baby Weights Mother Age 
 <2,500 2,500–4,000 >4,000 <20 20–30 >30 
Physician fee effect 52% 55% 47% 59% 54% 51% 
Patient co-payment effect 17% 27% 25% 27% 27% 27% 
Share of total impact 69% 82% 72% 86% 81% 78% 

Physician fee effect = Impact of payment reform on physicians/total impact of first payment reform, as calculated in Appendix Table A-4 and Table 4, respectively. Patient co-payment effect = Impact of payment reform on patients/total impact of first payment reform as calculated in Appendix Table A-4 and Table 4, respectively. Share of total impact = Physician fee effect + Patient co-payment effect. Results for twin pregnancies and maternal high blood pressure (hypertension) are omitted because of absence of statistical significance.

Table A-7.

Health effects of payment reform: Observations and R2

Regression(1)(2)(3)(4)(5)(6)
Mothers/BirthsNICU AdmissionMaternal ICU AdmissionApgar, 1 minApgar, 5 minInfant DeathMaternal Death
All Count 919,868 919,868 919,868 919,868 919,868 919,868 
R2 0.22 0.04 0.23 0.21 0.02 0.00 
First child Count 372,883 372,883 372,883 372,883 372,883 372,883 
R2 0.21 0.04 0.23 0.23 0.02 0.00 
Second child Count 330,944 330,944 330,944 330,944 330,944 330,944 
R2 0.2 0.02 0.22 0.19 0.04 0.00 
Maternal hypertension Count 25,685 25,685 25,685 25,685 25,685 25,685 
R2 0.18 0.03 0.26 0.21 0.03 0.00 
Maternal diabetes Count 16,976 16,976 16,976 16,976 16,976 16,976 
R2 0.17 0.02 0.24 0.21 0.02 0.00 
Low birth weight (<2,500 g) Count 78,930 78,930 78,930 78,930 78,930 78,930 
R2 0.12 0.06 0.17 0.22 0.07 0.00 
Normal birth weight (2,500–4,000 g) Count 814,199 814,199 814,199 814,199 814,199 814,199 
R2 0.1 0.03 0.14 0.11 0.01 0.01 
High birth weight (>4,000 g) Count 26,739 26,739 26,739 26,739 26,739 26,739 
R2 0.17 0.07 0.31 0.2 0.02 0.00 
Twins Count 6,970 6,970 6,970 6,970 6,970 6,970 
R2 0.14 0.02 0.18 0.16 0.02 0.00 
Maternal age <20 Count 75,502 75,502 75,502 75,502 75,502 75,502 
R2 0.18 0.08 0.15 0.19 0.04 0.01 
20 ≤ Maternal age < 30 Count 513,107 513,107 513,107 513,107 513,107 513,107 
R2 0.2 0.03 0.16 0.21 0.02 0.00 
Mother age ≥30 Count 331,259 331,259 331,259 331,259 331,259 331,259 
R2 0.2 0.05 0.09 0.22 0.02 0.01 
Regression(1)(2)(3)(4)(5)(6)
Mothers/BirthsNICU AdmissionMaternal ICU AdmissionApgar, 1 minApgar, 5 minInfant DeathMaternal Death
All Count 919,868 919,868 919,868 919,868 919,868 919,868 
R2 0.22 0.04 0.23 0.21 0.02 0.00 
First child Count 372,883 372,883 372,883 372,883 372,883 372,883 
R2 0.21 0.04 0.23 0.23 0.02 0.00 
Second child Count 330,944 330,944 330,944 330,944 330,944 330,944 
R2 0.2 0.02 0.22 0.19 0.04 0.00 
Maternal hypertension Count 25,685 25,685 25,685 25,685 25,685 25,685 
R2 0.18 0.03 0.26 0.21 0.03 0.00 
Maternal diabetes Count 16,976 16,976 16,976 16,976 16,976 16,976 
R2 0.17 0.02 0.24 0.21 0.02 0.00 
Low birth weight (<2,500 g) Count 78,930 78,930 78,930 78,930 78,930 78,930 
R2 0.12 0.06 0.17 0.22 0.07 0.00 
Normal birth weight (2,500–4,000 g) Count 814,199 814,199 814,199 814,199 814,199 814,199 
R2 0.1 0.03 0.14 0.11 0.01 0.01 
High birth weight (>4,000 g) Count 26,739 26,739 26,739 26,739 26,739 26,739 
R2 0.17 0.07 0.31 0.2 0.02 0.00 
Twins Count 6,970 6,970 6,970 6,970 6,970 6,970 
R2 0.14 0.02 0.18 0.16 0.02 0.00 
Maternal age <20 Count 75,502 75,502 75,502 75,502 75,502 75,502 
R2 0.18 0.08 0.15 0.19 0.04 0.01 
20 ≤ Maternal age < 30 Count 513,107 513,107 513,107 513,107 513,107 513,107 
R2 0.2 0.03 0.16 0.21 0.02 0.00 
Mother age ≥30 Count 331,259 331,259 331,259 331,259 331,259 331,259 
R2 0.2 0.05 0.09 0.22 0.02 0.01 

We obtained the data from Iran’s Ministry of Health (MOH). We are prohibited from further dissemination, but others can obtain the data from Iran’s MOH.

The authors appreciate the helpful comments that they received when this article was presented at the American Law & Economics Association Annual Meeting in 2022, anonymous comments from 2 reviewers in connection with the 2022 Conference on Empirical Legal Studies, and additional anonymous comments from 2 peer reviewers and the editor at Advances in Global Public Health.

The research was funded by our respective institutions.

None.

All authors were involved in the conceptualization, methodology, and formal analysis. ST was primarily responsible for data curation. ST and MHR were primarily responsible for the original draft. DAH was primarily responsible for review, rewriting, editing, and responding to peer review and editorial comments. Both DAH and MHR supervised ST’s work.

1.

Conversion factors and RVUs for Iran are at https://rvu.behdasht.gov.ir/ (In Persian).

2.

The trend coefficients for the control and treatment hospitals are 0.0945 and 0.0896, respectively, and the null hypothesis of their equality cannot be rejected with P < 0.1 (F value = 2.12).

1
World Health Organization
.
WHO statement on caesarean section rates
.
Geneva (Switzerland)
:
World Health Organization
;
2015
.
Available from:
https://iris.who.int/bitstream/handle/10665/161442/WHO_RHR_15.02_eng.pdf.
2
World Health Organization
.
Appropriate technology for birth
.
Lancet
.
1985
;
326
(
8452
):
436
-
7
.
doi:10.1016/S0140-6736(85)92750-3
.
3
Molina
G
,
Weiser
TG
,
Lipsitz
SR
,
Esquivel
MM
,
Uribe-Leitz
T
,
Azad
T
, et al
Relationship between cesarean delivery rate and maternal and neonatal mortality
.
JAMA
.
2015
;
314
(
21
):
2263
-
70
.
doi:10.1001/jama.2015.15553
.
4
Souza
JP
,
Gülmezoglu
AM
,
Lumbiganon
P
,
Laopaiboon
M
,
Carroli
G
,
Fawole
B
, et al.
Caesarean section without medical indications is associated with an increased risk of adverse short-term maternal outcomes, the 2004-2008 WHO Global Survey on Maternal and Perinatal Health
.
BMC Med
.
2010
;
8
(
1
):
71
.
5
Miller
DA
,
Chollet
JA
,
Goodwin
TM
.
Clinical risk factors for placenta previa–placenta accreta
.
Am J Obstet Gynecol
.
1997
;
177
(
1
):
210
-
4
.
6
Słabuszewska-Jóźwiak
A
,
Szymański
JK
,
Ciebiera
M
,
Sarecka-Hujar
B
,
Jakiel
G
.
Pediatrics consequences of caesarean section—a systematic review and meta-analysis
.
Int J Environ Res Public Health
.
2020
;
17
(
21
):
8031
.
7
Betran
AP
,
Ye
J
,
Moller
AB
,
Souza
JP
,
Zhang
J
.
Trends and projections of caesarean section rates: global and regional estimates
.
BMJ Glob Health
.
2021
;
6
(
6
):
e005671
.
8
Betran
AP
,
Temmerman
M
,
Kingdon
C
,
Mohiddin
A
,
Opiyo
N
,
Torloni
MR
, et al
Interventions to reduce unnecessary caesarean sections in healthy women and babies
.
Lancet
.
2018
;
392
(
10155
):
1358
-
68
.
9
Gibbons
L
,
Belizán
JM
,
Lauer
JA
,
Betrán
AP
,
Merialdi
M
,
Althabe
F
.
The global numbers and costs of additionally needed and unnecessary caesarean sections performed per year: overuse as a barrier to universal coverage
.
World Health Rep
.
2010
;
30
(
1
):
1
-
31
.
10
The Lancet
.
Stemming the global caesarean section epidemic
.
Lancet
.
2018
;
392
(
10155
):
1279
.
11
Boerma
T
,
Ronsmans
C
,
Melesse
DY
,
Barros
AJ
,
Barros
FC
,
Juan
L
, et al
Global epidemiology of use of and disparities in caesarean sections
.
Lancet
.
2018
;
392
(
10155
):
1341
-
8
.
12
Betrán
AP
,
Ye
J
,
Moller
A-B
,
Zhang
J
,
Gülmezoglu
AM
,
Torloni
MR
.
The increasing trend in caesarean section rates: global, regional and national estimates: 1990-2014
.
PLoS One
.
2016
;
11
(
2
):
e0148343
.
13
Opiyo
N
,
Kingdon
C
,
Oladapo
OT
,
Souza
JP
,
Vogel
JP
,
Bonet
M
, et al
Non-clinical interventions to reduce unnecessary caesarean sections: WHO recommendations
.
Bull World Health Organ
.
2020
;
98
(
1
):
66
-
8
.
14
World Health Organization
.
WHO recommendations: non-clinical interventions to reduce unnecessary caesarean sections
.
Geneva (Switzerland)
:
World Health Organization
;
2018
Oct
11
.
Available from:
https://www.who.int/publications/i/item/9789241550338.
15
Betrán
AP
,
Torloni
MR
,
Zhang
JJ
,
Gülmezoglu
AM
,
Aleem
HA
,
Althabe
F
, et al.
WHO statement on caesarean section rates
.
BJOG
.
2016
;
123
(
5
):
667
-
70
.
16
Rashidian
A
,
Moradi
G
,
Takian
A
,
Sakha
MA
,
Salavati
S
,
Faraji
O
, et al
Effects of the health transformation plan on caesarean section rate in the Islamic republic of Iran: an interrupted time series
.
East Mediterr Health J
.
2019
;
25
(
4
):
254
-
61
.
17
Bahadori
F
,
Hakimi
S
,
Heidarzade
M
.
The trend of caesarean delivery in the Islamic Republic of Iran
.
East Mediterr Health J
.
2013
;
19
:
67
-
70
.
doi:10.26719/2013.19.Supp3.S67
.
18
Rafiei
M
,
Saei Ghare
M
,
Akbari
M
,
Kiani
F
,
Sayehmiri
F
,
Sayehmiri
K
, et al
Prevalence, causes, and complications of cesarean delivery in Iran: a systematic review and meta-analysis
.
Int J Reprod Biomed
.
2018
;
16
(
4
):
221
-
34
.
19
Shahshahan
Z
,
Heshmati
B
,
Akbari
M
,
Sabet
F
.
Caesarean section in Iran
.
Lancet
.
2016
;
388
(
10039
):
29
-
30
.
20
Moaveni
A
.
Iran’s caesarean section craze
.
Time Magazine
.
2006
Sep
21
.
Available from:
http://content.time.com/time/world/article/0,8599,1537543,00.html.
21
Pourshirazi
M
,
Heidarzadeh
M
,
Taheri
M
,
Esmaily
H
,
Babaey
F
,
Talkhi
N
, et al
Cesarean delivery in Iran: a population-based analysis using the Robson classification system
.
BMC Pregnancy Childbirth
.
2022
;
22
(
1
):
185
.
22
Badakhsh
MH
,
Seifoddin
M
,
Khodakarami
N
,
Gholami
R
,
Moghimi
S.
Rise in cesarean section rate over a 30-year period in a public hospital in Tehran, Iran
.
Arch Iran Med
.
2012
;
15
(
1
):
4
-
7
.
23
Harirchi
I
,
Hajiaghajani
M
,
Sayari
A
,
Dinarvand
R
,
Sajadi
HS
,
Mahdavi
M
, et al
How health transformation plan was designed and implemented in the Islamic Republic of Iran?
Int J Prev Med
.
2020
;
11
(
1
):
121
.
doi:10.4103/ijpvm.IJPVM_430_19
.
24
Aghajani
M
,
Babaee
F
,
Eslamboulchi
L
,
Mazaheri
Z
,
Jourshari
M
.
Health Transformation Plan: natural childbirth
.
Ministry of Health and Medical Education
.
2016
:
36
.
Available from:
https://sharif.edu/∼rahmati/health/tarvij.pdf.
25
World Health Organization
.
Caesarean section rates continue to rise, amid growing inequalities in access
.
Geneva (Switzerland)
:
World Health Organization
;
2021
Jun
16
.
Available from:
https://www.who.int/news/item/16-06-2021-caesarean-section-rates-continue-to-rise-amid-growing-inequalities-in-access.
26
Lin
H-C
,
Xirasagar
S
.
Institutional factors in cesarean delivery rates: policy and research implications
.
Obstet Gynecol
.
2004
;
103
(
1
):
128
-
36
.
27
Oner
C
,
Catak
B
,
Sütlü
S
,
Kilinç
S
.
Effect of social factors on cesarean birth in primiparous women: a cross sectional study (social factors and cesarean birth)
.
Iran J Public Health
.
2016
;
45
(
6
):
768
-
73
.
28
Hirsch
E
.
Good eggs and bad eggs
.
Am J Obstet Gynecol
.
2016
;
215
(
6
):
800
-
1
.
29
Doucleff
M
.
Rate of c-sections is rising at an “alarming” rate, report says
.
NPR Goats and Soda
.
2018
Oct
12
.
Available from:
https://www.npr.org/sections/goatsandsoda/2018/10/12/656198429/rate-of-c-sections-is-rising-at-an-alarming-rate.
30
Sanavi
FS
,
Rakhshani
F
,
Ansari-Moghaddam
A
,
Edalatian
M
.
Reasons for elective cesarean section amongst pregnant women; a qualitative study
.
J Reprod Infertil
.
2012
;
13
(
4
):
237
-
40
.
31
Yazdizadeh
B
,
Nedjat
S
,
Mohammad
K
,
Rashidian
A
,
Changizi
N
,
Majdzadeh
R
.
Cesarean section rate in Iran, multidimensional approaches for behavioral change of providers: a qualitative study
.
BMC Health Ser Res
.
2011
;
11
(
1
):
159
.
32
Setudezadeh
F
,
Yousefinezhadi
T.
The increasing prevalence of cesarean in Iran: how the rate of cesareans could be controlled?
Obstet Gynecol Int J
.
2018
;
9
(
6
):
532
-
5
.
33
Yu
Y
,
Lin
F
,
Dong
W
,
Li
H
,
Zhang
X
,
Chen
C
.
The effectiveness of financial intervention strategies for reducing caesarean section rates: a systematic review
.
BMC Public Health
.
2019
;
19
:
1080
.
34
Stafford
RS
.
Cesarean section use and source of payment: an analysis of California hospital discharge abstracts
.
Am J Public Health
.
1990
;
80
(
3
):
313
-
5
.
35
Tussing
AD
,
Wojtowycz
MA
.
The cesarean decision in New York State, 1986. Economic and noneconomic aspects
.
Med Care
.
1992
;
30
(
6
):
529
-
40
.
36
Gruber
J
,
Owings
M
. Physician financial incentives and cesarean section delivery.
NBER Working Papers 4933
.
Cambridge (MA)
:
National Bureau of Economic Research
;
1994
.
37
Keeler
EB
,
Fok
T
.
Equalizing physician fees had little effect on cesarean rates
.
Med Care Res Rev
.
1996
;
53
(
4
):
465
-
71
.
38
Gruber
J
,
Kim
J
,
Mayzlin
D
.
Physician fees and procedure intensity: the case of cesarean delivery
.
J Health Econ
.
1999
;
18
(
4
):
473
-
90
.
39
Mossialos
E
,
Allin
S
,
Karras
K
,
Davaki
K
.
An investigation of caesarean sections in three Greek hospitals: the impact of financial incentives and convenience
.
Eur J Public Health
.
2006
;
15
(
3
):
288
-
95
.
40
Lo
JC
.
Financial incentives do not always work—an example of cesarean sections in Taiwan
.
Health Policy
.
2008
;
88
(
1
):
121
-
9
.
41
Pilvar
H
,
Yousefi
K
.
Changing physicians’ incentives to control the C-section rate: evidence from a major health care reform in Iran
.
J Health Econ
.
2021
;
79
:
102514
.
42
Behzadifar
M
,
Behzadifar
M
,
Bakhtiari
A
,
Azari
S
,
Saki
M
,
Golbabayi
F
, et al
The effect of the health transformation plan on cesarean section in Iran: a systematic review of the literature
.
BMC Res Notes
.
2019
;
12
(
1
):
37
.
43
Doshmangir
L
,
Moshiri
E
,
Mostafavi
H
,
Sakha
MA
,
Assan
A
.
Policy analysis of the Iranian health transformation plan in primary healthcare
.
BMC Health Serv Res
.
2019
;
19
(
1
):
670
.
44
Ghasemyani
S
,
Raoofi
S
,
Hamidi
H
,
Khodayari-Zarnaq
R
.
Iran’s health transformation plan; main issues and opportunities for improvement: a systematic review
.
Iran J Public Health
.
2022
;
51
(
9
):
1977
-
89
.
45
Heshmati
B
,
Joulaei
H
.
Iran’s health-care system in transition
.
Lancet
.
2016
;
387
(
10013
):
29
-
30
.
46
Khalili
N
,
Moradi-Lakeh
M
,
Heidarzadeh
M
.
Low birth weight in Iran based on Iranian Maternal and Neonatal Network (IMaN)
.
Med J Islam Repub Iran
.
2019
;
15
(
33
):
30
.
47
Pirjani
R
,
Afrakhteh
M
,
Sepidarkish
M
,
Nariman
S
,
Shirazi
M
,
Moini
A
, et al
Elective caesarean section at 38–39 weeks gestation compared to >39 weeks on neonatal outcomes: a prospective cohort study
.
BMC Pregnancy Childbirth
.
2018
;
18
(
1
):
140
.
48
Zanardo
V
,
Simbi
AK
,
Franzoi
M
,
Solda
G
,
Salvadori
A
,
Trevisanuto
D
.
Neonatal respiratory morbidity risk and mode of delivery at term: influence of timing of elective caesarean delivery
.
Acta Paediatr
.
2004
;
93
(
5
):
643
-
7
.
49
Cragin
EB
.
Conservatism in obstetrics
.
NY Med J
.
1916
;
104
:
1
-
3
.
50
Chen
I
,
Opiyo
N
,
Tavender
E
,
Mortazhejri
S
,
Rader
T
,
Petkovic
J
, et al
Non-clinical interventions for reducing unnecessary caesarean section
.
Cochrane Database Syst Rev
.
2018
;
9
(
9
):
CD005528
.
51
Azami-Aghdash
S
,
Ghojazadeh
M
,
Dehdilani
N
,
Mohammadi
M
.
Prevalence and causes of cesarean section in Iran: systematic review and meta-analysis
.
Iran J Public Health
.
2014
;
43
(
5
):
545
-
55
.
52
Shirzad
M
,
Shakibazadeh
E
,
Hajimiri
K
,
Betran
AP
,
Jahanfar
S
,
Bohren
MA
, et al
Prevalence of and reasons for women’s, family members’, and health professionals’ preferences for cesarean section in Iran: a mixed-methods systematic review
.
Reprod Health
.
2021
;
18
(
1
):
3
.

How to cite this article: Hyman DA, Taheri S, Rahmati MH. The impact of substantial financial incentives on C-section rates: Evidence from Iran. Adv Glob Health. 2024;3(1). https://doi.org/10.1525/agh.2024.2317379

Editor-in-Chief: Craig R. Cohen, University of California, San Francisco, CA, USA

Senior Editor: Harsha Thirumurthy, University of Pennsylvania, PA, USA

Section: Ending Poverty

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.