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Variation in guideline-based prenatal care in a commercially insured population

Open AccessPublished:October 03, 2021DOI:https://doi.org/10.1016/j.ajog.2021.09.038

      Background

      Despite the importance of prenatal care, quality measurement efforts have focused on the number of prenatal visits, or prenatal care adequacy, rather than the services received. It is unknown whether attending more prenatal visits is associated with receiving more guideline-based prenatal care services. The relationship between guideline-based prenatal care and patients’ clinical and sociodemographic characteristics has also not been studied.

      Objective

      This study aimed to measure the receipt of guideline-based prenatal care among pregnant patients and to describe the association between guideline-based prenatal care and the number of prenatal visits and other patient characteristics.

      Study Design

      This was a retrospective descriptive cohort study of 176,092 pregnancy episodes between 2016 and 2019. We used de-identified administrative claims data on commercial enrollees across the United States from the OptumLabs Data Warehouse. We identified the following 8 components of prenatal care that are universally recommended by the American College of Obstetricians and Gynecologists and other guideline-issuing organizations: testing for sexually transmitted infections, obstetric laboratory test panel, urine culture, urinalysis, anatomy scan ultrasound, oral glucose tolerance test, tetanus, diphtheria, and pertussis vaccine, and group B Streptococcus test. We measured the proportion of pregnant patients who received each of these guideline-based services at the appropriate gestational age. We measured the association between guideline-based services and the number of prenatal visits and prenatal care adequacy. We described variation of guideline-based care according to patient age, comorbidities, high deductible health plan enrollment, and their county’s rurality, health professional shortage area status, racial composition, median income, and educational attainment.

      Results

      The 176,092 pregnancy episodes were mostly among patients aged 25 to 34 years (63%) with few pregnancy comorbidities (81%) and living in urban areas (92%). Guideline-based care varied by service, from 51% receiving a timely urinalysis to 90% receiving an anatomy scan and 91% completing testing for sexually transmitted infections. Patients with at least 4 prenatal visits received, on average, 6 of the 8 guideline-based services. Guideline-based care did not increase with additional prenatal visits and varied by patient characteristics. Rates of tetanus, diphtheria, and pertussis vaccination were lower in counties with high proportions of minoritized populations, lower education, and lower income.

      Conclusion

      In this commercially insured population, receipt of guideline-based care was not universal, did not increase with the number of prenatal visits, and varied by patient- and area-level characteristics. Measuring guideline-based care is feasible and may capture quality of prenatal care better than visit count or adequacy alone.

      Key words

      Introduction

      Despite its nearly universal use, little is understood about the quality of prenatal care and how it varies among pregnant patients.
      • Osterman M.J.K.
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      Timing and adequacy of prenatal care in the United States, 2016.
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      Assessing the role and effectiveness of prenatal care: history, challenges, and directions for future research.
      • Kotelchuck M.
      An evaluation of the Kessner Adequacy of Prenatal Care Index and a proposed Adequacy of Prenatal Care Utilization Index.
      Instead of tracking the services provided, quality measurement organizations and researchers describe prenatal care in terms of the timing of its initiation and the number of visits, together referred to as “adequacy” of care.
      These 2 elements of care may capture important components of quality, but they fail to describe whether the patient received the recommended care such as laboratory screenings, psychosocial support, and education on childbirth and parenting.
      • Kotelchuck M.
      An evaluation of the Kessner Adequacy of Prenatal Care Index and a proposed Adequacy of Prenatal Care Utilization Index.
      • Peoples-Sheps M.D.
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      Content of prenatal care during the initial workup.
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      Quality of prenatal care questionnaire: instrument development and testing.
      Indeed, work in other areas of health services research has shown that healthcare visits vary substantially in their quality.
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      This distinction is relevant to the growing debate in the United States about the number and structure of prenatal visits.
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      • et al.
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      As clinicians and policymakers rethink the models of prenatal care, it is important to understand the existing variation in the services provided, rather than just the quantity and timing of prenatal visits.

      Why was this study conducted?

      It is unknown whether a patient’s number of prenatal visits is positively associated with their receipt of guideline-based prenatal care services. We used national data to examine variation in the provision of 8 guideline-based services by a patient’s number of prenatal visits and other characteristics.

      Key findings

      Many patients do not receive these guideline-based services. There is little variation in the number of guideline-based services received among patients with 6 or more prenatal visits.

      What does this add to what is known?

      There is a significant gap in the provision of guideline-based prenatal care that is not well explained by the number of visits. Using number of visits alone to describe prenatal care quality masks important heterogeneity in the services received.
      This study moves beyond adequacy to measure whether prenatal care is consistent with national clinical guidelines in a commercially insured population. We overcome barriers to such an analysis by using a national database of de-identified health insurance claims that includes prenatal services billed individually instead of as a global fee.
      • Gourevitch R.A.
      • Peahl A.F.
      • McConnell M.
      • Shah N.
      Understanding the impact of prenatal care: improving metrics, data, and evaluation.
      We describe variation in guideline-based care according to a patient’s number of prenatal visits, adequacy, and their clinical and demographic characteristics.

      Materials and Methods

      Data

      This is a retrospective descriptive study of prenatal care utilization among pregnant patients with commercial insurance. We used de-identified administrative claims data from the OptumLabs Data Warehouse (OLDW), which include medical and pharmacy claims and enrollment records for commercial enrollees. The database contains longitudinal health information on enrollees, representing a mixture of ages and geographic regions across the United States.

      US Preventive Services Task Force. Douglas K.O, Karina WD, HK, et al. Screening for asymptomatic bacteriuria in adults: us preventive services task force recommendation statement. JAMA 2019;322:1188–1194.

      Study population

      The study population included commercially insured enrollees who had a claim for delivery of a neonate between June 1, 2016, and July 1, 2019 (Appendix A provides billing codes used to identify delivery episodes). For each delivery episode, we identified a corresponding approximate date of last menstrual period (LMP) using International Classification of Diseases, 10th Revision, (ICD-10) codes (Appendix B and Appendix C).
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      • et al.
      Validation of an algorithm to estimate gestational age in electronic health plan databases.
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      • Clifford C.R.
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      • Gately R.
      • Seeger J.D.
      Utilization of ICD-10 codes indicating weeks of gestation in routine clinical care of pregnant women in the US. Poster presented at the. 2018.
      Enrollees were required to have continuous coverage in a commercial plan with medical and pharmacy benefits starting 6 months before the estimated date of LMP; this criterion was necessary for accurate measurement of the obstetric comorbidity index (OCI).
      • Bateman B.T.
      • Mhyre J.M.
      • Hernandez-Diaz S.
      • et al.
      Development of a comorbidity index for use in obstetric patients.
      ,
      • Metcalfe A.
      • Lix L.M.
      • Johnson J.A.
      • et al.
      Validation of an obstetric comorbidity index in an external population.
      All included patients were aged from 12 to 55 years at their approximate date of LMP and were not listed as male sex. We excluded patients with missing age, sex, or ZIP code data, which are indicators of incomplete or incorrect data capture in the OLDW (Appendix D describes the construction of the analytical cohort).

      Outcomes

      We measured “guideline-based care,” or timely receipt of specific prenatal services according to guidelines set by the American College of Obstetricians and Gynecologists, the Centers for Disease Control and Prevention, the US Preventive Services Task Force, and/or the International Society of Ultrasound in Obstetrics and Gynecology. Table 1 shows the 8 components of guideline-based care, the organization(s) that issued the corresponding recommendations, and their clinical purpose. These 8 components of care do not include all services that patients should receive prenatally; however, they are recommended for all pregnant patients and we can interpret the absence of any of this care as a departure from clinical guidelines. The relative value of the 8 guideline-based services, or their respective contributions to preventing maternal and infant morbidity and mortality, varies based on patient risk factors (eg, drug use, multiple sexual partners, preexisting hypertension, or diabetes).
      Table 1Guideline-based prenatal care and recommending organizations
      ServiceTiming of service
      Recommended timing of the service as specified by the organization’s guidelines
      Recommending organizationClinical need
      Testing for sexually transmitted infections (HIV, syphilis, and hepatitis B)N/ACDC, ACOG, USPSTF
      Centers for Disease Control and Prevention
      STD treatment guidelines: special populations, pregnant women.
      • Owens D.K.
      • Davidson K.W.
      • et al.
      US Preventive Services Task Force
      Screening for HIV infection: US Preventive Services Task Force recommendation statement.

      American Academy of Pediatrics. In: American College of Obstetricians and Gynecologists, ed. Guidelines for perinatal care. 7th ed. American Academy of Pediatrics; American College of Obstetricians and Gynecologists, Elk Grove Village, IL : Washington, DC; 2012.

      United States Preventive Services Task force
      Final recommendation statement: syphilis infection in pregnant women: screening.
      United States Preventive Services Task force
      Final recommendation statement: Rh(D) incompatibility: screening.
      Treat maternal infection; prevent transmission to fetus
      Obstetrical laboratory panel (D [Rh] type, RBC antibody screen, Rubella avidity test [IgG], and CBC)First prenatal visitACOG, USPSTF

      American Academy of Pediatrics. In: American College of Obstetricians and Gynecologists, ed. Guidelines for perinatal care. 7th ed. American Academy of Pediatrics; American College of Obstetricians and Gynecologists, Elk Grove Village, IL : Washington, DC; 2012.

      ,
      United States Preventive Services Task force
      Final recommendation statement: Rh(D) incompatibility: screening.
      ,
      Centers for Disease Control and Prevention
      Pregnancy and rubella.
      Pregnancy risk assessment and management (eg, treatment for Rh incompatibility or anemia)
      Urine culture or test for asymptomatic bacteriuriaFirst trimesterACOG, USPSTF

      American Academy of Pediatrics. In: American College of Obstetricians and Gynecologists, ed. Guidelines for perinatal care. 7th ed. American Academy of Pediatrics; American College of Obstetricians and Gynecologists, Elk Grove Village, IL : Washington, DC; 2012.

      ,
      • Owens D.K.
      • Davidson K.W.
      • et al.
      US Preventive Services Task Force
      Screening for asymptomatic bacteriuria in adults: US Preventive Services Task Force recommendation statement.
      Identify urinary tract infection and treat to prevent pregnancy complications
      UrinalysisFirst trimesterACOG

      American Academy of Pediatrics. In: American College of Obstetricians and Gynecologists, ed. Guidelines for perinatal care. 7th ed. American Academy of Pediatrics; American College of Obstetricians and Gynecologists, Elk Grove Village, IL : Washington, DC; 2012.

      Assess urine properties that may be indicative of infection or kidney disease
      Anatomy scan ultrasound
      Concordance with guidelines for the second and third trimester services was only evaluated among pregnancies that reached the maximum recommended gestational age for each service (ie, 22 completed weeks for the anatomy scan, 28 completed weeks for gestational diabetes screening, 36 completed weeks for the TDAP vaccine, and 37 completed weeks for the group B Streptococcus test). This is because, for example, pregnancies lasting 30 weeks should not be expected to include a group B Streptococcus test at 35 to 37 weeks
      18–22 wkACOG, ISUOG

      American Academy of Pediatrics. In: American College of Obstetricians and Gynecologists, ed. Guidelines for perinatal care. 7th ed. American Academy of Pediatrics; American College of Obstetricians and Gynecologists, Elk Grove Village, IL : Washington, DC; 2012.

      ,
      • Salomon L.J.
      • Alfirevic Z.
      • Berghella V.
      • et al.
      Practice guidelines for performance of the routine mid-trimester fetal ultrasound scan.
      Detect fetal, placental, or umbilical cord abnormalities; accurate gestational age dating
      Oral glucose tolerance test
      Concordance with guidelines for the second and third trimester services was only evaluated among pregnancies that reached the maximum recommended gestational age for each service (ie, 22 completed weeks for the anatomy scan, 28 completed weeks for gestational diabetes screening, 36 completed weeks for the TDAP vaccine, and 37 completed weeks for the group B Streptococcus test). This is because, for example, pregnancies lasting 30 weeks should not be expected to include a group B Streptococcus test at 35 to 37 weeks
      24–28 wkUSPSTF, ACOG

      American Academy of Pediatrics. In: American College of Obstetricians and Gynecologists, ed. Guidelines for perinatal care. 7th ed. American Academy of Pediatrics; American College of Obstetricians and Gynecologists, Elk Grove Village, IL : Washington, DC; 2012.

      ,
      United States Preventive Services Task force
      Final recommendation statement: gestational diabetes mellitus, screening.
      Test for gestational diabetes
      TDAP vaccination
      Concordance with guidelines for the second and third trimester services was only evaluated among pregnancies that reached the maximum recommended gestational age for each service (ie, 22 completed weeks for the anatomy scan, 28 completed weeks for gestational diabetes screening, 36 completed weeks for the TDAP vaccine, and 37 completed weeks for the group B Streptococcus test). This is because, for example, pregnancies lasting 30 weeks should not be expected to include a group B Streptococcus test at 35 to 37 weeks
      27–36 wkCDC, ACOG
      American College of Obstetricians and Gynecologists
      Update on immunization and pregnancy: tetanus, diphtheria, and pertussis vaccination.
      ,
      Centers for Disease Control and Prevention
      Summary of pertussis vaccination recommendations.
      Transfer pertussis antibodies and prevent transmission of pertussis to the newborn
      Group B Streptococcus test
      Concordance with guidelines for the second and third trimester services was only evaluated among pregnancies that reached the maximum recommended gestational age for each service (ie, 22 completed weeks for the anatomy scan, 28 completed weeks for gestational diabetes screening, 36 completed weeks for the TDAP vaccine, and 37 completed weeks for the group B Streptococcus test). This is because, for example, pregnancies lasting 30 weeks should not be expected to include a group B Streptococcus test at 35 to 37 weeks
      ,
      In July 2019 (after our study period), the group B Streptococcus screening guidelines were amended from recommending screening at between 35 to 37 weeks to recommending screening between 36 to 39 weeks’ gestation.37
      35–37 wkCDC, ACOG

      American Academy of Pediatrics. In: American College of Obstetricians and Gynecologists, ed. Guidelines for perinatal care. 7th ed. American Academy of Pediatrics; American College of Obstetricians and Gynecologists, Elk Grove Village, IL : Washington, DC; 2012.

      ,
      Centers for Disease Control and Prevention
      Group B strep.
      Prevent transmission to the newborn which can cause sepsis
      ACOG, American College of Obstetricians and Gynecologists; CDC, Centers for Disease Control and Prevention; IgG, immunoglobulin G; ISUOG, International Society of Ultrasound in Obstetrics and Gynecology; RBC, red blood cell; Rh, rhesus; TDAP, tetanus, diphtheria, and pertussis; USPSTF, US Preventive Services Task Force.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      a Recommended timing of the service as specified by the organization’s guidelines
      b Concordance with guidelines for the second and third trimester services was only evaluated among pregnancies that reached the maximum recommended gestational age for each service (ie, 22 completed weeks for the anatomy scan, 28 completed weeks for gestational diabetes screening, 36 completed weeks for the TDAP vaccine, and 37 completed weeks for the group B Streptococcus test). This is because, for example, pregnancies lasting 30 weeks should not be expected to include a group B Streptococcus test at 35 to 37 weeks
      c In July 2019 (after our study period), the group B Streptococcus screening guidelines were amended from recommending screening at between 35 to 37 weeks to recommending screening between 36 to 39 weeks’ gestation.
      • Puopolo K.M.
      • Lynfield R.
      • Cummings J.J.
      COMMITTEE ON FETUS AND NEWBORN, COMMITTEE ON INFECTIOUS DISEASES
      Management of infants at risk for Group B streptococcal disease.
      Guideline-based care requires receiving the right services at the right time during pregnancy. Care was only considered guideline-based if the claim for that service occurred at the recommended pregnancy stage (when applicable) based on the difference between the date the service was provided and the patient’s approximate date of LMP (Appendix E provides results without the timeliness constraint and Appendix F provides a sensitivity analysis).
      Prenatal care is often included in a global fee with the delivery hospitalization, which has limited the utility of claims data as a measure of prenatal services and visits.
      • Gourevitch R.A.
      • Peahl A.F.
      • McConnell M.
      • Shah N.
      Understanding the impact of prenatal care: improving metrics, data, and evaluation.
      However, claims for prenatal, delivery, and postpartum care in the OLDW are not bundled or billed under a global fee. Instead, each prenatal visit and service is individually billed. This data resource therefore represents a unique opportunity to overcome key limitations of claims data for measuring the number of prenatal visits and the services patients receive. We used ICD-10 codes, Current Procedural Terminology codes, Healthcare Common Procedure Coding System, and National Drug Codes to identify the 8 components of guideline-based care (Appendix G) and the number of prenatal visits (Appendix B and Appendix H provide details). We carefully selected the billing codes used to identify visits and services, testing the sensitivity of our definitions to exclusion and inclusion of relevant codes and relying on previous work where possible.
      • Carroll C.
      • Chernew M.
      • Fendrick A.M.
      • Thompson J.
      • Rose S.
      Effects of episode-based payment on health care spending and utilization: evidence from perinatal care in Arkansas.
      • Adams E.K.
      • Dunlop A.L.
      • Strahan A.E.
      • Joski P.
      • Applegate M.
      • Sierra E.
      Prepregnancy insurance and timely prenatal care for Medicaid births: before and after the Affordable Care Act in Ohio.
      • Rodriguez M.I.
      • Kaufman M.
      • Lindner S.
      • Caughey A.B.
      • DeFede A.L.
      • McConnell K.J.
      Association of expanded prenatal care coverage for immigrant women with postpartum contraception and short interpregnancy interval births.

      Patient characteristics

      We measured the number of prenatal visits before delivery and the Adequacy of Prenatal Care Utilization (APNCU) index, which is also known as the Kotelchuck Index. The APNCU index describes the totality of a patient’s prenatal care as inadequate, intermediate, adequate, or adequate plus based on the timing of their prenatal care initiation and by comparing the number of prenatal visits they received with the number that they would have been recommended to receive based on their gestational age at initiation and at delivery.
      • Kotelchuck M.
      An evaluation of the Kessner Adequacy of Prenatal Care Index and a proposed Adequacy of Prenatal Care Utilization Index.
      We used the OCI, a validated claims-based method, to identify patients’ comorbidities.
      • Bateman B.T.
      • Mhyre J.M.
      • Hernandez-Diaz S.
      • et al.
      Development of a comorbidity index for use in obstetric patients.
      ,
      • Metcalfe A.
      • Lix L.M.
      • Johnson J.A.
      • et al.
      Validation of an obstetric comorbidity index in an external population.
      We used enrollment and benefit design information in the OLDW to measure patient age at the approximate date of LMP and to capture high deductible health plan (HDHP) enrollment. The enrollment data included the patient’s ZIP code of residence, which we used to link to county characteristics from the Area Health Resources Files (AHRF). The AHRF data include US Department of Agriculture urban influence codes, which we used to identify whether the patient’s county is urban, nonurban urban-adjacent, or rural, consistent with previous work.
      United States Department of Agriculture
      Rural-urban commuting area codes.
      ,
      • Kozhimannil K.B.
      • Hung P.
      • Henning-Smith C.
      • Casey M.M.
      • Prasad S.
      Association between loss of hospital-based obstetric services and birth outcomes in rural counties in the United States.
      We also used the AHRF to identify whether the patient resided in a full or partial primary care health professional shortage area (HPSA).
      To maintain de-identification of the OLDW data some individual-level demographic elements were not available for this analysis. We instead described race, income, and educational attainment at the county-level using episode-weighted percentiles of data from the AHRF. For race/ethnicity, we created three indicator variables capturing whether the patient resided in a county that was above the 75th percentile of counties with percent of the population that was (1) White non-Hispanic/Latino, (2) Black non-Hispanic/Latino, and (3) Hispanic/Latino. For income, we created a categorical variable with 3 levels corresponding to county terciles of median annual household income (low [<$56,732], middle [$56,732 to $70,461], or high [>$70,461]). For educational attainment, we created a categorical variable for whether the patient resided in a county in the lowest, middle, or highest tercile of the percentage of individuals aged 25 or older with less than a high school diploma (lowest attainment [>12.90% without diploma], middle attainment [9.21% to 12.90% without diploma], and highest attainment [<9.21% without diploma]).

      Analyses

      We report the overall levels of each guideline-based service across our analytical sample and describe how a patient’s number of guideline-based services received varies by their number of prenatal visits and their APNCU index category. We also measure variation in the number and type of guideline-based services across patient- and area-level characteristics.
      All analyses were conducted at the delivery episode level. Descriptive analysis was performed with SAS version 9.4 (SAS Institute Inc, Cary, NC) and figures were created in R version 4.0.2 (R Core Team, 2020, Vienna, Austria); all analyses were independently replicated by a second data analyst. Because this study involved analysis of preexisting, de-identified data, it was deemed exempt from institutional review board approval.
      • Wallace P.J.
      • Shah N.D.
      • Dennen T.
      • Bleicher P.A.
      • Crown W.H.
      Optum labs: building a novel node in the learning health care system.

      Results

      We identified 329,101 pregnancy episodes with dates of delivery and LMP in our study time frame, of which 176,092 (54%) met our study inclusion criteria (Appendix D). The 176,092 delivery episodes were among 171,107 individual patients (3% of patients had >1 delivery episode during our study period). The pregnancies in our sample were mostly among patients between the ages of 25 and 34 years (63%) and with a few obstetrical comorbidities (81% had an OCI score of ≤2) (Table 2). Most patients were not in an HDHP (75%). Nearly all resided in an urban county (92%) and in a partial primary care HPSA (88%). The cohort was evenly distributed across the terciles of county racial composition, median income, and educational attainment.
      Table 2Sample characteristics
      Total episodes: N=176,092
      The 176,092 delivery episodes were among 171,107 distinct patients
      Age (y)N (%)HPSAN (%)
       12–2422,589 (12.8)Non-HPSA county15,681 (8.9)
       25–2944,291 (25.2)Partial-HPSA county155,271 (88.2)
       30–3467,228 (38.2)Full-HPSA county5140 (2.9)
       ≥3541,984 (23.8)
      HDHP enrollmentCounty racial composition
      A county is classified as having a “high” population of each racial or ethnic group if that county is above the 75th percentile (episode-weighted) of counties’ proportion of the population from that racial or ethnic group
       HDHP43,842 (24.9)High non-Hispanic White44,113 (25.1)
       No HDHP132,250 (75.1)High non-Hispanic Black42,901 (24.4)
      Obstetric comorbidity index scoreHigh Hispanic/Latino43,521 (24.7)
       074,092 (42.1)County median income
      The county median household income categories corresponded to terciles of episode counties’ household median income (low [<$56,732], middle [$56,732–$70,461], or high [>$70,461])
       1–268,711 (39.0)Lowest income58,917 (33.5)
       3–626,902 (15.3)Middle income58,790 (33.4)
       ≥76387 (3.6)Highest income58,385 (33.2)
      RuralityCounty educational attainment
      County educational attainment categories indicate whether the county is in the lowest, middle, or highest tercile of the percent of individuals ages ≥25 years with less than a high school diploma among the pregnancy episodes’ counties (lowest attainment [>12.90% without diploma], middle attainment [9.21%–12.9% without diploma] and highest attainment [<9.21% without diploma]).
       Urban162,064 (92.0)Lowest education54,986 (31.2)
       Urban-adjacent9329 (5.3)Middle education61,359 (34.8)
       Rural4699 (2.7)Highest education59,747 (33.9)
      HDHP, high deductible health plan; HPSA, health professional shortage area.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      a The 176,092 delivery episodes were among 171,107 distinct patients
      b A county is classified as having a “high” population of each racial or ethnic group if that county is above the 75th percentile (episode-weighted) of counties’ proportion of the population from that racial or ethnic group
      c The county median household income categories corresponded to terciles of episode counties’ household median income (low [<$56,732], middle [$56,732–$70,461], or high [>$70,461])
      d County educational attainment categories indicate whether the county is in the lowest, middle, or highest tercile of the percent of individuals ages ≥25 years with less than a high school diploma among the pregnancy episodes’ counties (lowest attainment [>12.90% without diploma], middle attainment [9.21%–12.9% without diploma] and highest attainment [<9.21% without diploma]).
      Receipt of guideline-based prenatal care was not universal. As seen in Figure 1, approximately half of the cohort received a timely urinalysis (51%), and less than three-quarters had a timely obstetrical laboratory panel (61%) or received a tetanus, diphtheria, pertussis (TDAP) vaccination (63%). The components of guideline-based care that were most consistently received were an anatomy scan ultrasound (90%) and testing for sexually transmitted infections (STIs) (91%). Among those who did not undergo the full obstetrical laboratory panel, almost half did receive a timely complete blood count (CBC) (47%). Among those who did not receive the full STI testing panel, most were tested for syphilis (51%), but less than half were tested for hepatitis B (41%) or HIV (20%) (Appendix I).
      Figure thumbnail gr1
      Figure 1Receipt of guideline-based care in the full sample (N=176,092)
      The figure displays the percentage of the full sample that received each component of guideline-based prenatal care at the recommended gestational age (timely guideline-based care). provides additional details on the guideline-based services.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      The number of guideline-based services received did not have a strong association with the number of prenatal patient visits. Enrollees with at least 4 prenatal visits (97% of the sample) received, on average, 6 of the 8 timely guideline-based services. Figure 2 shows the distribution of the number of guideline-based services received by the binned number of prenatal visits (left) and by adequacy of prenatal care (right). Individuals who had <6 visits or inadequate prenatal care were less likely to receive all 8 of the guideline-based services. However, the distribution of the number of guideline-based services received is similar among patients with ≥6 visits and those with intermediate, adequate, or adequate plus care.
      Figure thumbnail gr2
      Figure 2Relationship between the number of guideline-based services received and number of prenatal visits (left) and the adequacy of prenatal care utilization index (right)
      Dots proportional to patient number. See and .
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      The proportion of patients who received at least 6 of the 8 timely guideline-based services varied by patient characteristics (Figure 3 and Appendix J). 60% of patients <25 years of age received at least 6 timely services compared with 71% of patients aged ≥25 years. We observed little difference in the rates of guideline-based care by HDHP enrollment (71% of HDHP enrollees vs 69% of non-HDHP enrollees received at least 6 timely services). Patients with higher-risk pregnancies were less likely to receive at least 6 timely services than patients with no obstetrical comorbidities (64% among patients with OCI ≥7 vs 71% among patients with OCI=0).
      Figure thumbnail gr3
      Figure 3Percentage of patients who received at least 6 out of the 8 guideline-based prenatal care services studied by patient characteristics
      See for addiitional details.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      In addition, patients living in nonurban counties or counties that included a HPSA were less likely to receive at least 6 timely services than patients in urban counties or counties without a HPSA (64% in rural counties vs 70% in urban counties and 65% in full-HPSA counties vs 74% in non-HPSA counties). Patients living in counties with a high non-Hispanic White population were more likely to receive at least 6 timely services (72%) than patients living in counties with a high non-Hispanic Black (68%) or high Hispanic/Latino population (66%). Patients in counties with a lower median income or lower educational attainment were less likely to receive at least 6 timely services (65% among the lowest income tercile vs 74% among highest income tercile and 66% among lowest education tercile vs 74% among highest education tercile).
      Of the 8 timely guideline-based services studied, TDAP vaccination showed the most pronounced variation by county-level demographics. Counties with the lowest educational attainment had a 29% lower rate of TDAP vaccination than counties with the highest educational attainment (55% vs 71%). Counties with the lowest median income had a 27% lower rate of TDAP vaccination than counties with the highest median income (56% vs 71%). TDAP vaccination rates also varied by county-level racial composition as follows: compared with counties with a high non-Hispanic White population, counties with a high non-Hispanic Black population had 13% lower rates of TDAP vaccination and counties with a high Hispanic population had 24% lower rates of TDAP vaccination (55% among high Hispanic counties, 60% among high non-Hispanic Black counties, and 68% among high non-Hispanic White counties).

      Comment

      Principal findings

      Services provided during prenatal care are not always consistent with clinical guidelines. The relationship between the number of prenatal visits or prenatal care adequacy and guideline-based care is weak. Patients with very few prenatal care visits or inadequate care received fewer guideline-based services. However, there was little difference in receipt of these services among patients with 6 or more visits or among patients with intermediate, adequate, or adequate plus care.

      Results

      Younger patients were less likely to receive guideline-based care, which may be driven by an association between age and pregnancy intention. People with unintended pregnancies are more likely to be younger and to have inadequate prenatal care.
      • Finer L.B.
      • Zolna M.R.
      Declines in unintended pregnancy in the United States, 2008-2011.
      We find little variation in guideline-based care by deductible level, which may be because these preventive services are exempt from deductible spending or because patients anticipate surpassing their deductible during the year of a pregnancy. Patients with many comorbidities were less likely to receive guideline-based services; these cases may represent clinically appropriate deviations from guideline-based care, such as not screening for gestational diabetes in patients with preexisting diabetes. However, this finding and the observed variation across rurality and HPSA should be interpreted with caution given that only a small proportion of our sample is in the highest comorbidity, nonurban, or full-HPSA groups.
      We find lower rates of TDAP vaccination in counties with a high proportion of non-Hispanic Black or Hispanic residents and in those with low educational attainment or median income. Although we cannot be sure that our patients are representative of their county demographics, other work has found lower TDAP vaccination rates among pregnant patients from minoritized populations, with lower educational attainment, or with incomes below the poverty level.
      Centers for Disease Control and Prevention
      Pregnant women and Tdap vaccination, Internet panel survey, United States, April 2016.
      • Goldfarb I.T.
      • Little S.
      • Brown J.
      • Riley L.E.
      Use of the combined tetanus-diphtheria and pertussis vaccine during pregnancy.
      • DiTosto J.D.
      • Weiss R.E.
      • Yee L.M.
      • Badreldin N.
      Association of Tdap vaccine guidelines with vaccine uptake during pregnancy.
      • Razzaghi H.
      • Kahn K.E.
      • Black C.L.
      • et al.
      Influenza and Tdap vaccination coverage among pregnant women - United States, April 2020.
      These disparities may reflect differences in the likelihood of the provider offering the vaccination or lower uptake rates of vaccinations among these vulnerable populations—both of which are linked to structural and interpersonal racism.
      • Boyd R.W.
      • Lindo E.G.
      • Weeks L.D.
      • McLemore M.R.
      On racism: a new standard for publishing on racial health inequities.

      Clinical implications

      Our results suggest that many commercially insured pregnant patients are not receiving timely guideline-based services. Some patients who do not receive timely guideline-based care instead receive these services at another point in pregnancy (Appendix E). Still, these services were not universally applied in our sample despite being recommended for all pregnant patients.
      Moreover, our results illustrate that the number of prenatal visits and adequacy do not sufficiently capture the quality of care. The measures of guideline-based care that we implement may be a suitable starting point for more meaningful measurements of prenatal care quality; these are universally recommended based on clinical evidence and are observable in health insurance claims data. Measuring the quality of care provided during the management of conditions like gestational diabetes or group B streptococcus infection, which are detected via the tests that we study here, is an important direction for future quality measurement efforts. In addition, understanding the quality and consistency of nonbillable physical examinations (eg, blood pressure monitoring, fundal height measurements) and the quality of the counseling and anticipatory guidance provided during prenatal visits is important for evaluating prenatal care quality.
      These findings have implications for the ongoing work of redesigning prenatal care to be better suited to patients’ diverse medical and psychosocial needs.
      • Peahl A.F.
      • Gourevitch R.A.
      • Luo E.M.
      • et al.
      Right-sizing prenatal care to meet patients’ needs and improve maternity care value.
      ,
      • Gourevitch R.A.
      • Peahl A.F.
      • McConnell M.
      • Shah N.
      Understanding the impact of prenatal care: improving metrics, data, and evaluation.
      ,
      • Barrera C.M.
      • Powell A.R.
      • Biermann C.R.
      • et al.
      A review of prenatal care delivery to inform the Michigan Plan for Appropriate Tailored Health Care in pregnancy panel.
      The COVID-19 pandemic has required clinicians to rethink how to flexibly provide prenatal care, which has been largely unchanged in the last century.
      • Peahl A.F.
      • Zahn C.M.
      • Turrentine M.
      • et al.
      The Michigan Plan for Appropriate Tailored Health Care in pregnancy prenatal care recommendations.
      ,
      • Peahl A.F.
      • Howell J.D.
      The evolution of prenatal care delivery guidelines in the United States.
      • Aziz A.
      • Zork N.
      • Aubey J.J.
      • et al.
      Telehealth for high-risk pregnancies in the setting of the COVID-19 pandemic.
      • Peahl A.F.
      • Smith R.D.
      • Moniz M.H.
      Prenatal care redesign: creating flexible maternity care models through virtual care.
      • Reid C.N.
      • Marshall J.
      • Fryer K.
      Evaluation of a rapid implementation of telemedicine for delivery of obstetric care during the COVID-19 pandemic.
      As we move toward more flexible prenatal care models, the need for quality measures that go beyond visit number will only become more relevant.

      Research implications

      The primary value of high-quality prenatal care is improving maternal and neonatal outcomes. Future work should quantify the impact of guideline-based care on maternal and neonatal outcomes such as preterm delivery, birthweight, and infection. In addition, other measures of quality including patient-reported outcomes and satisfaction should continue to be developed and incorporated into quality measurement strategies.
      • Afulani P.A.
      • Altman M.R.
      • Castillo E.
      • et al.
      Development of the person-centered prenatal care scale for People of Color.
      ,
      • Vedam S.
      • Stoll K.
      • Taiwo T.K.
      • et al.
      The Giving Voice to Mothers study: inequity and mistreatment during pregnancy and childbirth in the United States.
      There are many potential explanations for why a patient may not have received a component of guideline-based care. First, the provider may not submit a claim to the insurer. We use unbundled claims and find high rates of billing for these services across pregnancy (Appendix E), and therefore we do not believe that inconsistent billing practices are driving our results. Second, the patient may be unable to, or choose not to, receive the service, or the provider may feel that the service is not appropriate for that patient (eg, gestational diabetes testing for patients with preexisting diabetes). Patients may decline these services because of structural factors impeding access to care, like transportation or the ability to take time off from work, or hesitancy around blood draws or vaccinations.
      • Razzaghi H.
      • Kahn K.E.
      • Black C.L.
      • et al.
      Influenza and Tdap vaccination coverage among pregnant women - United States, April 2020.
      ,
      • Holcomb D.S.
      • Pengetnze Y.
      • Steele A.
      • Karam A.
      • Spong C.
      • Nelson D.B.
      Geographic barriers to prenatal care access and their consequences.
      Future work should examine the roles of patient and physician discretion in driving variation in guideline-based care.
      In addition, measuring guideline-based care among patients covered by Medicaid or who churn across insurers before or during pregnancy is an important direction for future work.
      • Daw J.R.
      • Hatfield L.A.
      • Swartz K.
      • Sommers B.D.
      Women in the United States experience high rates of coverage ‘churn’ in months before and after childbirth.
      Other work has shown that women covered by Medicaid may be less likely to receive preventive care; therefore, this analysis may overestimate the rates of guideline-based care across all pregnant people.
      • McMorrow S.
      • Long S.K.
      • Fogel A.
      Primary care providers ordered fewer preventive services for women with Medicaid than for women with private coverage.
      ,
      • Geissler K.
      • Ranchoff B.L.
      • Cooper M.I.
      • Attanasio L.B.
      Association of insurance status with provision of recommended services during comprehensive postpartum visits.

      Strengths and limitations

      Our study adds to the literature on prenatal care by demonstrating that measuring only prenatal visit number, or adequacy, can mask important variation in guideline-based care. We used a large, nationwide sample rich in information on patients’ clinical and sociodemographic characteristics.
      Our sample only included commercially insured women who were continuously enrolled in coverage during pregnancy; our results may therefore not be generalizable to pregnancies covered by Medicaid or to people who change insurers during pregnancy. We did not observe individual patient race, education or income, nor did we observe those variables at a geographic level smaller than county. Correlations between county-level demographics and receipt of guideline-based care should be interpreted with caution because the individuals in our sample may not be representative of the counties in which they live (and, inferring individual-level patterns from area-level estimates is subject to the ecologic fallacy).
      • Piantadosi S.
      • Byar D.P.
      • Green S.B.
      The ecological fallacy.
      We rely on claims data, which do not capture any services that were provided but not billed to the insurance company. Our lists of billing codes are based on previous analyses using claims when possible.
      • Carroll C.
      • Chernew M.
      • Fendrick A.M.
      • Thompson J.
      • Rose S.
      Effects of episode-based payment on health care spending and utilization: evidence from perinatal care in Arkansas.
      ,
      • Adams E.K.
      • Dunlop A.L.
      • Strahan A.E.
      • Joski P.
      • Applegate M.
      • Sierra E.
      Prepregnancy insurance and timely prenatal care for Medicaid births: before and after the Affordable Care Act in Ohio.
      In addition, we use unbundled claims, which should limit the number of unbilled services relative to other databases of obstetrics claims.

      Conclusion

      Our work shows that receipt of guideline-based care is not universal, does not increase with the number of prenatal visits, and that care varies across patient characteristics. Future research and policy attention should be devoted to more meaningful measurements of prenatal care quality.

      Supplementary Data

      Appendix A

      Supplemental Table 1Billing codes for delivery episode
      Code typeCodes indicating delivery
      ICD-10 DXZ37%, O80%, O82%
      ICD-10 PX10D07Z3,10D07Z6,10D07Z8,10D07Z7,10E0XZZ,0W8NXZZ,10D00Z0, 10D00Z1,10D00Z2,10D07Z4,10D07Z5,10S07ZZ
      DRG765, 766, 774, 775, 767, 768, 783, 784, 786, 787, 785, 788, 805, 806, 807, 796, 797, 798
      DRG, Diagnosis Related Group, Version 39; ICD-10, International Classification of Diseases, Tenth Revision.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.

      Appendix B

      Supplemental methods

      Algorithm to approximate date of last menstrual period

      We developed a novel algorithm for approximating the date of the last menstrual period (LMP)—which marks the start of a pregnancy—using International Classification of Diseases (ICD)-10 codes in claims data. Identifying LMP is essential to understanding the gestational age at which each prenatal service was received. Because pregnancies vary in length, it is imprecise to identify the date of LMP as 40 weeks before delivery. Instead, our algorithm uses information contained in diagnosis and procedure codes to identify the date of LMP more precisely. We adapted this algorithm from previous studies that used ICD-9 codes to identify the date of LMP in claims data, and leveraged preliminary work by OptumLabs researchers to convert those algorithms to ICD-10 codes.
      • Margulis A.V.
      • Palmsten K.
      • Andrade S.E.
      • et al.
      Beginning and duration of pregnancy in automated health care databases: review of estimation methods and validation results.
      • Li Q.
      • Andrade S.E.
      • Cooper W.O.
      • et al.
      Validation of an algorithm to estimate gestational age in electronic health plan databases.
      • Phiri K.
      • Clifford C.R.
      • Doherty M.
      • Gately R.
      • Seeger J.D.
      Utilization of ICD-10 codes indicating weeks of gestation in routine clinical care of pregnant women in the US. Poster presented at the. 2018.
      ,

      Phiri K, Clifford CR, Doherty M, Fan Y, Wang F, Seeger JD. Timing of routine prenatal tests relative to the last menstrual period estimated from an ICD-10 based algorithm. Poster presented at the: 35th International Conference on Pharmacoepidemiology and Therapeutic Risk Management; August 2019; Philadelphia, PA.

      The algorithm takes advantage of new diagnosis codes included in the ICD-10 that capture gestational age at any clinical encounter during the pregnancy (the Z3A.XX codes). Appendix C provides the full algorithm.

      Identifying prenatal visits

      We identified the first prenatal visit as the first claim after the patient’s estimated LMP with a diagnosis or procedure code for prenatal care, an evaluation and management (E&M) visit with an obstetrician-gynecologist, a provider-ordered pregnancy test in a setting other than the emergency department, an obstetrical ultrasound, or any of the obstetrical laboratory panel tests listed in Table 1 of the manuscript (Appendix G provides billing codes). If the patient receives most of their prenatal care from a primary care physician or neonatologist, we also count an E&M visit with that provider type as a prenatal visit.
      We identify subsequent prenatal care visits in the same way with the caveat that claims for ultrasounds and laboratory tests do not count as a subsequent prenatal visit. Although these services should be taken as an indication that prenatal care has been initiated, they may be billed by ultrasound technicians or independent laboratories on dates when the patient did not have an in-person prenatal care visit.
      Appendix H provides the list of billing codes used to identify prenatal visits.

      Appendix C

      Figure thumbnail fx1
      Supplemental FigureAlgorithm for approximating date of LMP
      1. Upper bound of gestational age range chosen for consistency with prior work.
      • Catling C.J.
      • Medley N.
      • Foureur M.
      • et al.
      Group versus conventional antenatal care for women.
      2. Percentage symbol indicates that any code beginning with the text preceding the % should be captured. 3. Delivery date is defined as the date of admission for the inpatient stay for delivery 4. If an enrollee had >1 delivery during the study period (ie, had 1 or more deliveries that were subsequent to the first), we made the following adjustment to step 2: we looked for Z3A.% codes starting from the date of their subsequent delivery to either (1) 11 months before that delivery date, or (2) the discharge date of prior delivery, whichever was earlier.
      ICD-10, International Classification of Diseases, Tenth Revision; LMP, last menstrual period.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.

      Appendix D

      Supplemental Table 2Study cohort construction
      Number of episodesEpisodes dropped n (%)
      384,649
      The 384,649 episodes originally identified are those with an inpatient delivery date between June 1, 2016 and July 1, 2019


      55,548 (14)Approximate LMP date out of time period, or not identified
      329,101

      144,465 (44)Do not meet continuous enrollment requirements
      184,636

      1746 (1)Gender, age, or zip code exclusion
      182,890

      5639 (3)Abortive pregnancy, too-close delivery episodes, county does not link to the Area Health Resources Files
      177,251

      1,159 (1)Delivery gestational age outside of 20–43 wk
      176,092
      Three percent of individuals in the sample had 2 or more deliveries during the study period (the final sample consists of 176,092 episodes among 171,107 individuals).
      Final analytical sample
      LMP, last menstrual period.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      a The 384,649 episodes originally identified are those with an inpatient delivery date between June 1, 2016 and July 1, 2019
      b Three percent of individuals in the sample had 2 or more deliveries during the study period (the final sample consists of 176,092 episodes among 171,107 individuals).

      Appendix E

      Supplemental Table 3Study outcomes by sample characteristics with and without timeliness constraint (%)
      Full SampleObstetrical panelSTI panelUrinalysisUrine cultureAnatomy scanGlucose testTDAP vaccinationGroup B Streptococcus test
      TimelyAnytimeAnytimeTimelyAnytimeTimelyAnytimeTimelyTimelyAnytimeTimelyAnytimeTimelyAnytime
      Full Sample6190915166829390809463717895
      APNCU index
       Inadequate107277784252728274668051576885
       Intermediate307392934558849491829564728096
       Adequate265792944966839592839667758097
       Adequate Plus345091936078819493799462717796
      Number of prenatal visits
       0–5147782834251778580718454617187
       6–8317292934559839491829564728096
       9–11235791935067829592829666748097
       12–14145291935774829492819564727896
       ≥15184291926381819594799462717696
      Age (y)
       12–24136187885876769183708749587291
       25–29256590915267829390819462707895
       30–34386291934963839492829567757996
       35–55245590924964829392809465737895
      HDHP
       HDHP256491914862829391809465737995
       No HDHP756090915267819390809462707795
      Obstetric comorbidity index
       0426590915063829389819463717996
       1–2396090925065829391809463717795
       3–6155590915371819391779362707695
       ≥744990915677809392729060687493
      Rurality
       Urban926190925065829390809463717895
       Urban-adjacent56388885673779188779258677794
       Rural36387875774748887749058677492
      Health professional shortage area
       Non-HPSA county96291925064859592829568768096
       Partial-HPSA county886190915166819390809463717895
       Full-HPSA county36488915572789186759153627493
      County racial composition
       High non-Hispanic White256489904965819392809468768095
       High non-Hispanic Black246090924863819389799360697795
       High Hispanic or Latino256191925570819388799355637494
      County median income
       Lowest income336290915268799288789356647594
       Middle income336291905166809290799462707895
       Highest income335990934963869592829571788096
      County educational attainment
       Lowest education316089925772799288789355647494
       Middle education356191914965819390809461697895
       Highest education346290914762849492819571798196
      Note: “Timely” indicates that the guideline-based service was received at the recommended gestational age (Table 1). “Anytime” indicates that the service was received anytime between the patient’s approximate date of last menstrual period and the day before their delivery episode. There is no timely column for STI panel because we did not impose a gestational age requirement for this service. There is no anytime column for anatomy scan because it cannot be considered at the 18 to 22 weeks’ gestation anatomy scan if it is outside of that recommended gestational age range.
      APNCU, Adequacy of Prenatal Care Utilization; HDHP, High deductible health plan; HPSA, Health professional shortage area; STI, sexually transmitted infection; TDAP, tetanus, diphtheria, and pertussis.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.

      Appendix F

      Supplemental Table 4Sensitivity analysis for timeliness constraint on applicable guideline-based services


      Outcome
      The outcomes included in the sensitivity analysis were limited to those with timeliness definitions depended on the claims-based algorithm used to estimate the date of LMP. The STI panel was not included because we did not impose a gestational age requirement for this service. The anatomy scan was not included because it cannot be considered at a 18–22 week anatomy scan if it is outside of that recommended gestational age range. The obstetrical laboratory panel was not included because it is considered timely if it is billed any time before the patient’s second prenatal visit; this definition does not depend on the gestational age at the time of the visit
      Timely definition: primaryTimely definition: sensitivity analysis
      Gestational age at time of testPercentage of sampleGestational age at time of testPercentage of sample
      Urinalysis
      For the primary definitions of timely care, urinalysis and urine culture were considered timely if they occurred either in the first 90 days of gestation (first trimester), within 38 days of the first prenatal visit, or within 8 days of the second prenatal visit. The sensitivity analysis only altered the 90 days of gestation criterion because it is the only component dependent on the claims-based algorithm for determining date of LMP.
      0–90 d510–95 d52
      Urine culture
      For the primary definitions of timely care, urinalysis and urine culture were considered timely if they occurred either in the first 90 days of gestation (first trimester), within 38 days of the first prenatal visit, or within 8 days of the second prenatal visit. The sensitivity analysis only altered the 90 days of gestation criterion because it is the only component dependent on the claims-based algorithm for determining date of LMP.
      0–90 d820–95 d83
      Glucose test24 wk+0 d to 28 wk+0 d8023 wk+2 d to 28 wk+5 d87
      TDAP vaccination27 wk+0 d to 36 wk+0 d6326 wk+2 d to 36 wk+5 d65
      Group B Streptococcus test35 wk+0 d to 37 wk+0 d7834 wk+2 d to 37 wk+5 d88
      LMP, last menstrual period; STI, sexually transmitted infection; TDAP, tetanus, diphtheria, and pertussis.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      a The outcomes included in the sensitivity analysis were limited to those with timeliness definitions depended on the claims-based algorithm used to estimate the date of LMP. The STI panel was not included because we did not impose a gestational age requirement for this service. The anatomy scan was not included because it cannot be considered at a 18–22 week anatomy scan if it is outside of that recommended gestational age range. The obstetrical laboratory panel was not included because it is considered timely if it is billed any time before the patient’s second prenatal visit; this definition does not depend on the gestational age at the time of the visit
      b For the primary definitions of timely care, urinalysis and urine culture were considered timely if they occurred either in the first 90 days of gestation (first trimester), within 38 days of the first prenatal visit, or within 8 days of the second prenatal visit. The sensitivity analysis only altered the 90 days of gestation criterion because it is the only component dependent on the claims-based algorithm for determining date of LMP.

      Appendix G

      Supplemental Table 5Billing codes for identifying guideline-based prenatal care
      CPT/HCPCSICD-10NDC
      STI Testing - HIV87806, 87534, 87535, 87536, 87537, 87538, 87539, 87390, 87391, 87389, 3292F, 3490F, 3491F, 3492F, 3494F, 3496F, 3497F, 3498F, 3500F, 3502F, 3503F, G0432, G0433, G0435, S3645, G0475, 86689, 86701, 86702, 86703, 80081Z114
      STI testing - Syphilis86592, 86593, 3512F, 0065U, 87285, G9228, 86781, 86780, 0064U, 80055, 80081
      STI testing - Hepatitis B80074, 86704, 86705, 86706, 87340, 87341, 87516, 87517, G8869, G9912, 80081, 80055
      Obstetrical panel component: D(Rh)86901, 86906, 3290F, 3291F, 3293F, 80055, 80081
      Obstetrical panel component: RBC86850, 86860, 86870, 86905, 86976, 86975, 86977, 86971, 86970, 86972, 86978, 80055, 80081
      Obstetrical panel component: Rubella86762, 86765, 80055, 80081
      Obstetrical panel component: CBC85004, 85007, 85009, 85013, 85014, 85018, 85025, 85027, 85032, 85041, 85044, 85045, 85046, 85048, 85049, G0306, G0307, 80050, 80055, 80081
      Urine culture or asymptomatic bacteriuria81007, 81015, 81020, 87086, 87088, P7001, 87150, 87802, 87653, 87801
      Urinalysis81000, 81001, 81002, 81003, 81005, 81099
      Anatomy scan76805, 76810, 76811, 76812, 76815, 76816, 76817
      Oral glucose tolerance test82950, 82951, 82947
      TDAP vaccine90696, 90697, 90698, 90700, 90701, 90714, 90715, 90471, 90472, 90460, 9046149281040010, 49281040015, 49281040020, 58160084211, 58160084252
      Group B Streptococcus87150, 3294F, 87802, 87653, 87801, 87081, 87084, 87070, 87077, 87147Z36.85
      CBC, complete blood count; CPT, current procedural terminology; HCPCS, Healthcare Common Procedure Coding System; ICD-10, International Classification of Diseases, Tenth Revision; NDC, National Drug Codes; RBC, red blood cells; STI, sexually transmitted infections; TDAP, tetanus, diphtheria, and pertussis.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.

      Appendix H

      Supplemental Table 6Billing codes for identifying prenatal visits
      CPT/HCPCSICD-10Additional requirements/notes
      Prenatal visit procedure codesH1000, H1001, H1002, H1003, H1005, 0500F, 0502F, 59425, 59426, 0501F, 0503FZ36.%, Z34.%, O09.%, Z03.7
      E&M Codes99211-99215, 99201-99205, 99241-99245, 99401-99404, 99384-99386, 99394-99396, 3725F, 3351F, 3352F, 3353F, 3354F, 96150, 96151, 96152, 96156, 96158, 96127, 1220F, G0442-G0447, G8431-G8433, G8510, G8511, G9717, H0004, G8419-G8422, G8938, G8752-G8755, 3008F, 3074F, 3075F, 3077F, 3078F, 3079F, 3080F, 2000F, 2001FProvider must be an OB/GYN or neonatologist. If a primary care provider was the primary prenatal care provider (provided most of the prenatal care visits), then codes billed by primary care providers were counted
      Pregnancy test81025, 84163, 84703, 84702, 84704, 0167UZ32.00, Z32.01Must not be from ER setting
      Ultrasound76805, 76810, 76811, 76812, 76815, 76816, 76817Only counts for first prenatal visit
      Obstetrical laboratory tests80055, 80081, 80050, G9228, 86762, 86765, 86901, 86906, 3290F, 3291F, 3293F, 87806, 87534, 87535, 87536, 87537, 87538, 87539, 87390, 87391, 87389, 3292F, 3490F, 3491F, 3492F, 3494F, 3496F, 3497F, 3498F, 3500F, 3502F, 3503F, G0432, G0433, G0435, S3645, G0475, 86689, 86701, 86702, 86703, 86592, 86593, 3512F, 0065U, 87285, 86781, 86780, 0064U, 80074, 86704, 86705, 86706, 87340, 87341, 87516, 87517, G8869, G9912, 87110, 87270, 87320, 87810, 86631, 86632, 87490, 87491, 87492, G9820, 87590, 87591, 87592, 87850Z114Only counts for first prenatal visit
      CPT, current procedural terminology; ER, emergency room; E&M, evaluation and management; HCPCS, Healthcare Common Procedure Coding System; ICD-10, International Classification of Diseases, Tenth Revision; OB/GYN, obstetrician or gynecologits.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.

      Appendix I

      Supplemental Table 7Receipt of individual obstetric laboratory panel components among episodes without all components (N = 17,447)
      Obstetrical laboratory panel
      ComponentReceived panel component, timelyReceived panel component, anytime
      n%n%
      D (Rh) type422024651337
      RBC antibody screen391822681939
      CBC8116471499386
      Rubella avidity test (IgG)427224628236
      There were 17,447 pregnancies (10%) that did not receive all the obstetrical panel components over the course of their pregnancy. The table shows receipt of each component of the obstetrical laboratory panel, with and without the timeliness criteria, among those episodes.
      CBC, complete blood test; IgG, immunoglobulin G; RBC, red blood cells; Rh, rhesus.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      Supplemental Table 8Receipt of individual obstetric laboratory panel components among episodes without all timely components (N = 51,309)
      ComponentReceived panel component, timely
      n%
      D (Rh) type732314
      RBC antibody screen36697
      CBC1002120
      Rubella avidity test (IgG)21144
      There were 51,309 pregnancies (29%) that did receive all the obstetrical panel components during pregnancy but did not receive at least 1 of those components in a timely way. The table shows receipt of each component of the obstetrical laboratory panel, with the timeliness criteria (because all satisfied the anytime criteria), among those pregnancies.
      CBC, complete blood test; IgG, immunoglobulin G; RBC, red blood cells; Rh, rhesus.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.
      Supplemental Table 9Receipt of individual sexually transmitted infection tests among episodes without all three tests (N = 15,160)
      ComponentReceived panel component
      n%
      Syphilis test775151
      HIV test302820
      Hepatitis B test621841
      There were 15,160 pregnancies that did not receive all the components of the STI testing panel (9%). The table shows receipt of each component of the STI testing panel among those episodes.
      STI, sexually transmitted infections.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.

      Appendix J

      Supplemental Table 10Percentage of patients receiving at least 6 of 8 guideline-based services by patient characteristics, both timely and anytime
      CharacteristicsPercentage of patients receiving at least 6 of the 8 guideline-based services
      TimelyAnytime
      Percentage95% CIPercentage95% CI
      Full sample7093
      APNCU
       Inadequate58(57–58)76(76–77)
       Intermediate73(73–74)94(94–94)
       Adequate71(71–72)96(95–96)
       Adequate plus69(68–69)95(95–95)
      Number of prenatal visits
       0–564(63–65)80(80–81)
       6–873(72–73)94(94–94)
       9–1171(70–71)95(95–96)
       12–1470(69–71)95(95–96)
       ≥1567(66–68)95(95–96)
      Age (y)
       12–2460(59–61)88(87–88)
       25–2971(70–71)93(93–93)
       30–3473(72–73)94(94–94)
       35–5568(68–69)93(93–93)
      HDHP
       HDHP71(71–72)93(93–93)
       No HDHP69(69–69)93(92–93)
      Obstetric comorbidity index
       071(71–71)92(92–93)
       1–269(69–70)93(93–93)
       3–667(66–68)93(93–94)
       ≥764(61–66)93(92–94)
      Rurality
       Urban70(70–70)93(93–93)
       Urban-adjacent66(65–67)90(90–91)
       Rural64(62–65)89(88–90)
      Health professional shortage area
       Non-HPSA county74(73–75)94(93–94)
       Partial-HPSA county69(69–70)93(93–93)
       Full-HPSA county65(63–66)91(90–92)
      County racial composition
       High White Non-Hispanic72(71–72)92(92–92)
       High Black Non-Hispanic68(67–68)92(92–93)
       High Hispanic/Latino66(66–67)92(92–93)
      County median income
       Lowest income65(65–66)91(91–92)
       Middle income69(69–70)92(92–93)
       Highest income74(74–75)94(94–95)
      County educational attainment
       Lowest education66(66–67)92(92–92)
       Middle education69(68–69)93(92–93)
       Highest education74(73–74)93(93–94)
      Percentages and 95% confidence intervals are predicted probabilities calculated from logistic regressions (regression of an indicator for receiving at least 6 of the 8 guideline-based services on each patient characteristic).
      APNCU, Adequacy of Prenatal Care Utilization; CI, confidence interval; HDHP, High deductible health plan; HPSA, Health professional shortage area.
      Gourevitch et al. Variation in guideline-based prenatal care. Am J Obstet Gynecol 2022.

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