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Supplements Management of Preterm Birth: Current Practices, Challenges, and Opportunities
Current Perspectives on the Use of Fetal Fibronectin Testing in Preterm Labor Diagnosis and Management
Michael S. Ruma, MD, MPH; Katie C. Bittner, PhD; and Clara B. Soh, MPA
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Fetal Fibronectin Testing and Pregnancy Outcomes Among Texas Medicaid Patients at Risk for Preterm Birth
Jamie C. Barner, PhD; Allison A. Petrilla, MPH; Hyeun Ah Kang, MS; Xian Shen, PhD; Ahmed M. Alshehri, MS, B Pharm; Erin M. Sullivan, PhD, MPH; Kathleen A. Troeger, MPH; Kristin M. Richards, PhD; and Sean C. Blackwell, MD

Fetal Fibronectin Testing and Pregnancy Outcomes Among Texas Medicaid Patients at Risk for Preterm Birth

Jamie C. Barner, PhD; Allison A. Petrilla, MPH; Hyeun Ah Kang, MS; Xian Shen, PhD; Ahmed M. Alshehri, MS, B Pharm; Erin M. Sullivan, PhD, MPH; Kathleen A. Troeger, MPH; Kristin M. Richards, PhD; and Sean C. Blackwell, MD
Objectives: Fetal fibronectin (fFN) testing between the 24th and 34th weeks of pregnancy in patients with symptomatic preterm labor (PTL) helps assess the risk of spontaneous preterm birth (sPTB), yet the extent of its use is unknown. We assessed use of fFN testing among Texas Medicaid enrollees with symptomatic PTL and evaluated time to infant delivery and healthcare utilization/costs.
Study Design: Retrospective cohort study using medical and pharmacy claims for Texas Medicaid enrollees.
Methods: We identified pregnant women triaged through the emergency department (ED) and hospital labor-and-delivery units with symptomatic PTL between January 1, 2012, and May 31, 2015. Patients with fFN testing prior to delivery were propensity score matched 1:1 to patients without fFN testing. Primary outcomes included time to delivery from initial PTL encounter and all-cause maternal healthcare utilization and costs.
Results: A total of 29,553 women met the criteria for analysis, of whom 14% had a record of receiving fFN testing. Each matched cohort included 4098 patients. Compared with those who did not, patients who underwent fFN testing had significantly more clinical risk factors (mean [SD]: 1.7 [1.1] vs 1.1 [1.0]; P <.0001) and were less likely to deliver during the initial hospital stay (odds ratio [OR], 0.539; 95% CI, 0.489-0.594), deliver ≤3 days following the hospital/ED encounter (OR, 0.499; 95% CI, 0.452-0.551); and receive their first PTL diagnosis during the initial hospital/ED encounter (OR, 0.598; 95% CI, 0.539-0.665). Patients who had an fFN test, compared with those who did not, had 17.5% higher total costs (P <.0001) during the 5 months prior to delivery, but had gestation lengths 9.4 days longer (24.6 vs 15.2 days) than those without testing.
Conclusions: Frequency of fFN testing was low in Texas Medicaid enrollees with symptomatic PTL. Patients with fFN testing had longer gestation periods and were less likely to deliver within ≤3 days of a hospital/ED encounter for PTL. These results support the role of fFN in screening for risk for sPTB among women with symptomatic PTL. 
Am J Manag Care. 2017;23:-S0
Infants born prematurely, prior to 37 weeks of gestation, are more likely to experience both acute and long-term health problems, experience higher mortality rates, and incur substantial medical expenses compared with infants delivered at term (weeks 38-41).1,2 In the United States, it is estimated that approximately 10% of all infants are born prematurely,3 resulting in an estimated economic burden in excess of $26 billion per year.4 Medicaid disproportionately covers more preterm births (PTBs) than does private insurance (48.9% vs 42.3% of all PTBs in 2012, respectively).5 Given the socioeconomic, personal, and population-level health burden associated with PTB, it is imperative to identify and carefully manage patients who are at high risk for spontaneous PTB (sPTB) and/or present with symptoms of preterm labor (PTL), defined as the onset of labor between the 24th and 37th weeks of pregnancy.

Predicting which patients are at high risk for sPTB is a difficult process that involves assessment of the patient for risk factors of sPTB. Some of these risk factors include a history of prior PTB, multiple gestations, maternal infections, vaginal bleeding, use of in vitro fertilization, being either underweight or obese, being younger than 18 years or older than 35 years, maternal history of smoking or of illegal drug or alcohol use, race, and low socioeconomic status.6 Methods commonly used to assess the risk of sPTB include digital cervical examination, uterine activity monitoring, and transvaginal ultrasound (TVU) cervical length measurement. Additionally, testing for the presence of fetal fibronectin (fFN) in women with signs and symptoms of PTL between weeks 24 and 34 of pregnancy can aid in assessing the risk of preterm delivery within the following 14 days.7-9 Given the subjective nature of  PTL symptoms, differentiation between true and false PTL can be difficult, and errors can lead to risks of overtreatment as well as missed treatment.

Current management strategies for PTL include hospitalization, use of tocolytics, treatment with antibiotics for group beta streptococcus prophylaxis, administration of antenatal corticosteroids to increase the rate of fetal organ development, and magnesium sulfate for fetal neuroprotection. Posthospitalization care often includes activity restriction and/or bedrest.10

The objective of this study was to examine the use of diagnostic tools, including fFN testing, to evaluate women diagnosed with PTL or threatened PTL, and to assess delivery outcomes, healthcare utilization, and healthcare costs in a cohort of pregnant Medicaid enrollees. Efforts to more accurately identify patients who are at low risk of sPTB could also help to optimize patient management and potentially reduce healthcare costs, unnecessary treatments, and activity restriction.


We performed a retrospective cohort study to evaluate medical and pharmacy claims for Texas Medicaid enrollees, including both inpatient and outpatient visits. Information included in the data was extracted from Texas Medicaid claims and eligibility files, and it included: de-identified unique patient identification numbers; year of birth; gender; race/ethnicity; dates of enrollment; International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes (diagnostic codes); Diagnosis Related Group (DRG) codes; Current Procedural Terminology, 4th edition, codes (procedure codes); Healthcare Common Procedure Coding System codes (supplies and services codes); Generic Code Number; prescription dispense date; hospital admission date; hospital discharge date; date of outpatient visit; cost of drugs; and other medical services received. Costs were defined as paid Medicaid claims.

Eligibility Criteria

Female enrollees at least 21 years of age who were admitted to the hospital or had an emergency department (ED) visit with a diagnosis for PTL in any setting of care (inpatient or outpatient) between January 1, 2012, and May 31, 2015, were included in the analysis. We excluded patients with any of the following: (1 no record of infant delivery within 270 days (9 months) of the initial hospitalization or ED visit; (2 diagnosis of spontaneous/premature rupture of membranes, preeclampsia, or threatened abortion; or (3 not continuously enrolled in Medicaid for 5 months prior to the initial hospital or ED visit and 1 month post delivery. ICD-9-CM, Medicare Severity-DRG (prior to September 2012), and All Patients Refined-DRG (from September 2012 on) codes reported in the inpatient or outpatient medical claims files were used to identify women with these conditions. The index date was the date of delivery, and the preindex period was the 5 months prior to delivery.

Study Outcomes

Study outcomes were: (1 time to infant delivery from initial PTL hospital/ED visit, defined as the number of days from initial PTL hospital/ED visit to delivery; (2 proportion of women who delivered during the initial hospitalization/ED visit, defined as the sum of women who delivered during the initial hospitalization/ED visit divided by the total number of women in the initial sample; (3 all-cause healthcare utilization and costs, defined as total utilization and direct costs in the preindex period; (3a number of all-cause inpatient hospitalizations, ED visits, outpatient visits, pharmacy claims, and unique number of medications in the prenatal period (or preindex period); and (3b costs of all-cause inpatient hospitalizations, ED visits, outpatient visits, and pharmacy claims (adjusted to 2015 US dollars using the medical consumer price index from the US Bureau of Labor Statistics’ current data11).

Secondary outcomes of interest were: (1 hospital length of stay, defined as the number of days from admission to discharge; and (2 PTL type, defined as the proportion of patients who had actual (delivered during initial hospitalization) versus threatened (did not deliver during initial hospitalization) PTL. A sensitivity analysis compared healthcare resource utilization and costs among patients who had undergone any test or procedure for PTL, defined as: (a fFN testing, (b encounter for risk of PTL screening, or (c TVU to patients with no PTL procedures/tests.

Statistical Methods

The primary independent variable for all analyses was fFN testing status. Descriptive statistics were used to describe the characteristics of the study cohort and key study outcomes. Bivariate (unadjusted) analyses were performed to determine the relationship between fFN test status and age, race/ethnicity, risk factors, and comorbid conditions; bivariate analysis was also used to identify significant covariates to be used in multivariate regression analysis. For bivariate analysis, t tests for continuous variables and χ2 for categorical variables were employed.

Cohorts were matched based on the propensity to receive fFN testing. Propensity scores were calculated using logistic regression with a nearest neighbor match using a caliper set at 0.05 (sensitivity analyses were conducted to identify the most appropriate caliper).12 A classification of fFN test (1 = yes, 0 = no) served as the binary dependent variable, and independent variables included: delivery type (full term vs preterm), pregnancy-related complications, and presence or absence of risk factors, which included prior PTB, multiple gestation, tocolyzation, cervical incompetence/shortening, systemic infections, genitourinary infections, and other risk factors. To determine whether balance was achieved with propensity score matching and to assess standardized differences, statistical comparisons of baseline characteristics between the matched cohorts were conducted using McNemar’s test for categorical variables and 2-sided paired Student’s t test for continuous variables.

Both bivariate (unadjusted) and multivariate (adjusted) statistical analyses were performed to determine the relationship between fFN testing and delivery outcomes, healthcare utilization, or healthcare costs. Risk factors, comorbid conditions, and age were included as covariates in multivariate analyses. Race/ethnicity was excluded due to limited data availability. Statistical models (conditional logistic regression models, Poisson regression, generalized linear models with gamma distribution and log link, and generalized estimating equation regression) were employed for the adjusted analyses. All statistical analyses were 2-tailed; the significance level was set to P <.05 and confidence intervals were set to 95%. Distributions of the outcome variables to decide the statistical models to use were determined by running the modified Park test using STATA 14 (Stata Corp LLC; College Station, Texas). All other data manipulation and statistical analyses were performed using SAS for Windows, version 9.4 (SAS Institute; Cary, North Carolina).

Kaplan-Meier analysis was used to estimate the fraction of study subjects reaching the study endpoint (time to delivery). The time frame was the first hospitalization/ED visit with symptomatic PTL to delivery. Survival function curves of time to delivery were plotted for those who received fFN testing versus those who did not. Cox proportional hazard regression model was used to further test whether there was a significant difference between time to delivery and fFN test status, while controlling for covariates.


After applying all inclusion/exclusion criteria as described in Figure 1, 29,553 patients composed the final study cohort. Of these, 74.0% of the patients had an actual PTL diagnosis (early onset delivery) and 26.0% had a diagnosis of threatened PTL (early, threatened, or false labor) during the 5-month period prior to delivery. A total of 14.0% (n = 4151) of patients received fFN testing.

Patient Characteristics

Table 1 compares the demographic and clinical characteristics between women with and without fFN testing. More than 60% of the race/ethnicity data were missing. There were differences in multiple risk factors between groups, with women undergoing fFN testing having higher frequency of prior PTB (16.0% vs 5.5%) and of multiple gestation (7.6 % vs 5.2%). Data regarding tobacco use and history of substance abuse were limited based on diagnosis codes and were therefore not included for further analysis. There were no differences in the prevalence of comorbidities (hypertension, diabetes, or anemia) between the patients who had fFN testing and those who did not. Overall, patients who had fFN testing had more risk factors (mean [SD]: 1.7 [1.1] vs 1.1 [1.0];

P <.0001). After applying the 1:1 propensity score matching to account for the differences in baseline risk factors, the new population size was 8196 for fFN testing and no fFN testing (4098 patients in each group) and all subsequent analyses were performed using the propensity score matched cohorts.

Delivery Outcomes

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