Despite advancements in medical care, rates of maternal morbidity and mortality are significantly higher in the United States compared with other wealthy countries.1 The greatest effects of the maternal mortality crisis in the United States are observed in minority communities. Black women have nearly a 3-fold higher risk of dying during childbirth and a 5-fold higher risk of dying from pregnancy-related cardiomyopathy and blood pressure-related disorders compared with White women.2,3 Poor quality of care and lack of access to care are among the many factors that lead to higher rates of maternal mortality among minority populations.4 Addressing the maternal mortality gap requires reversing deeply rooted biases among health care professionals and within clinical algorithms and implementing telemedicine and other health technologies.
Organizations have taken steps to resolve the maternal mortality gap by implementing implicit bias training and reevaluating clinical guidelines in treating patients in minority populations. Changes in standardizing care across patient demographics are also being considered.
Tiffany Green, PhD, an economist and assistant professor of Population Health Sciences and Obstetrics and Gynecology at the University of Wisconsin-Madison, shared her insight on the true effectiveness of these solutions. Dr Green’s research focuses on population health disparities and maternal reproductive health.
Implicit Bias Training
Implicit bias has long been recognized as a threat to quality maternal care and some states, such as California, Illinois, and Michigan, have taken steps to resolve this disparity by mandating implicit bias training.5-7 In 2021, Congress passed The Black Maternal Momnibus Act, which would provide federal funding to medical and nursing schools to implement implicit bias training.8
While implicit bias training is well-intentioned, current training models and programs are found to be ineffective in the long term.9 A few hours to several days after completing implicit bias training, it appears that these levels of bias return back to baseline.10
Treating implicit bias as an individual issue also overlooks the bias embedded within some clinical algorithms.11
Q: Why might implicit bias training not be effective in addressing the racial disparities seen in maternal health? What are ways we can reform this training to better serve patients?
Dr Green: What we don’t know a lot about is whether differences in discrimination or biases are directly related to racial inequities in medical treatment and outcomes. While it may seem obvious, it’s not fully clear.
We’re at this point in terms of public policy where there’s been a massive push in laws directed at implicit bias training. Unfortunately, we don’t have a huge amount of evidence that implicit bias training has long-term effects on behaviors, including medical treatment decisions.
Hospital systems and practitioners need to bear the accountability because I think it’s really hard to change people’s beliefs on an individual level. We do have to work really hard not to let that spill over into medical practice.
Reforming Clinical Algorithms
One of the ways that health care organizations have taken steps to address this issue is by correcting racial disparities in clinical algorithms involved with this process. An example of this is the recent change to the vaginal birth after cesarean (VBAC) calculator to eliminate race and ethnicity from the algorithm.
These disparities are evidenced by the high rates of cesarean delivery among women in the United States. Cesarean delivery rates have increased to 31.8% in 2020, with Black women having the highest rate at 36.3%.13 Women who undergo cesarean delivery also have higher risks of maternal death.14 The World Health Organization found that countries with a low rate of cesarean delivery (≤10%) have a decreased rate of maternal and neonatal mortality compared with countries with higher cesarean delivery rates.12
Before 2021, the Maternal-Fetal Medicine Units Network’s vaginal birth after cesarean (VBAC) calculator, which predicts the likelihood of success having a vaginal birth following cesarean delivery, included questions on race and ethnicity and predicted a lower chance of successful VBAC for Black and Hispanic patients.15,16 It was criticized for using social factors that perpetuate maternal mortality disparities rather than biological factors in its decision-making algorithm, given that vaginal birth has been shown to result in faster recovery time and fewer complications in following pregnancies.15,16 The calculator was replaced by a new validated version that removed race and ethnicity as risk factors for a reduced likelihood of successful VBAC.
Q: What steps have been taken by organizations and hospitals to best address maternal mortality among women in minority communities?
Dr Green: We do have evidence of inequitable treatment across groups, and it’s not clear that treatment is driven by differences in underlying factors. We know, for example, Black birthing people are more likely to get procedures such as cesarean delivery even when controlling for underlying factors. This is not to demonize cesarean deliveries in any way — I want to be clear about that — but when birthing people get a cesarean delivery that is unneeded, that is the problem.
The Society for Maternal-Fetal Medicine has been working to correct some of these issues, including removing race correction from the VBAC algorithm.16 Things like that are really important in addressing the ubiquitousness of race embedded in clinical algorithms.
Standardization of Care
Standardizing care across patient groups can potentially help resolve racial issues in medicine as it has been associated with improved maternal outcomes.17,18 For example, a standardized protocol has been shown to reduce racial disparities for cesarean deliveries and neonatal morbidity.19
Standardizing care can produce favorable outcomes but it can also result in unintentional adverse consequences. When standardizing a prenatal substance use reporting protocol to child protective services, nearly 5 times more Black than White birthing parents were reported.20
Implementing standardized quality improvement protocols can also exacerbate disparities in health systems that do not have proper resources, which are the same systems that tend to treat underserved populations.21
Dr Green’s research suggests that changes in the patient care process are a solution to these disparities and standardization of protocols and guideline-based care could be an important factor in this change. Dr Green shared some measures that should be considered before standardizing care in institutions.
Q: How should institutions implement changes in a way that best serves this population?
Dr Green: It’s really important to make sure that if you’re going to implement these procedures, you do as much as possible to give resource-deprived institutions that disproportionately serve people of color the needed resources.
We can’t automatically assume that standardizing treatment protocols is going to improve outcomes, but it’s important to work towards making sure that patients are treated in an equitable way. To do that, we need much better measures of patient quality, particularly in obstetrics.
Using Health Technology to Address Maternal Mortality Gap
An emerging body of research suggests that applying the social determinants of health (SDoH) to health information technology, such as electronic health records (EHRs) and clinical decision support systems, could be important in addressing health inequities.22
Electronic health records provide health care professionals with important data for patient assessment. Organizations like the National Academy of Medicine endorsed the idea of standardizing SDoH screening in EHRs.23 This technology could be used to adjust for individual disease risk and can be used for targeted preventative care. Researchers suggest identifying population-level indicators that can be used to inform therapeutic intervention.24
Decision aid tools can be useful in assisting with patient education and promoting shared decision-making. Other health tools, such as telemedicine, can address other identified areas of needed improvement.
Nathaniel DeNicola, MD, MSHP, FACOG, a board-certified Ob/Gyn and chair of Telehealth at the American College of Obstetricians and Gynecologists (ACOG) shared his thoughts on the current and future role of health technology in addressing gaps in care in minority populations.
Clinical Decision Support Tools
Evidence suggests that clinical decision-support tools reduce racial inequities in certain patient populations.25 However, these tools could be subject to their own biases based on incomplete data and measurement error, further contributing to existing disparities.26
Q: How often do you use clinical decision support tools in practice? Is there potential for these tools to help resolve racial disparities in health care?
Dr DeNicola: Decision support tools and other applications may have been a novelty prior to the COVID-19 pandemic. I do feel like these tools are becoming more commonly adopted and that may not be due to the pandemic. It may just be that time has shown proof of concept for these products.
For example, if I need to decide when to induce a patient who has a number of high-risk conditions, it would be routine for me to look at the ACOG guidance why using a virtual app.
These support tools would guide us in deciding the best time for deliveries for certain high-risk conditions, many of which are more prevalent in minority communities.
Telemedicine has become widely adopted in response to the COVID-19 pandemic and has been shown to improve access to health care within rural communities, which often overlaps with minority populations.27 Telemedicine can dramatically improve patient access to specialist care without having to travel long distances.
Dr Denicola chaired the task force that developed ACOG’s guidelines on telehealth and discusses ways that we should maximize the potential of telemedicine to better serve minority populations.
Q: What is the most significant barrier to using telemedicine to treat birthing patients in minority communities?
Dr DeNicola: This is an area where some investment has to be made because while the data are strong that most people across demographics have access to a smartphone or tablet, typically more than 90%, access to high-quality fast broadband internet is not as common.28 That has been one of the biggest barriers that I’ve encountered personally.
I also liaison with the group called the Maternal Applications of Technology for Community Health (MATCH) Coalition. This community organization is approaching maternal health from a community level by trying to leverage technology. The coalition has made one of the largest priorities to increase broadband access to some underserved communities because it is a key ingredient in maximizing the benefits of telehealth.
Health care access is no longer defined by the number of miles, but it’s defined as the number of bars.
Allison Nguyen is a 4th-year student at Ernest Mario School of Pharmacy at Rutgers University in New Brunswick, NJ.
|This is the second article in a 2-part series on maternal mortality. The first article Maternal Mortality Crisis Among Minority Patients in the US is available here.|
- Pregnancy-related mortality. Health System Tracker. Accessed December 20, 2022. https://www.healthsystemtracker.org/indicator/quality/maternal-mortality/
- Hoyert DL. Maternal mortality rates in the United States, 2020. Centers for Disease Control and Prevention. Reviewed February 23, 2022. Accessed December 20, 2022. https://www.cdc.gov/nchs/data/hestat/maternal-mortality/2020/maternal-mortality-rates-2020.htm
- MacDorman MF, Thoma M, Declcerq, E, Howell EA. Racial and ethnic disparities in maternal mortality in the United States using enhanced vital records, 2016‒2017. Am J Public Health. 2021;111(9):1673-1681. doi: 10.2105/AJPH.2021.306375.
- Howell EA, Zeitlin J. Improving hospital quality to reduce disparities in severe maternal morbidity and mortality. Semin Perinatol. 2017;41(5):266-272. Published online July 21, 2017. doi:10.1053/j.semperi.2017.04.002
- California Dignity in Pregnancy and Childbirth Act. Open States. Accessed December 20, 2022. https://openstates.org/ca/bills/20192020/SB464/
- Gov. Pritzker signs equity driven healthcare reform legislation. Illinois Government website. Published April 27, 2021. Accessed December 20, 2022. https://www.illinois.gov/news/press-release.23204.html
- Executive Directive 2020-09. Michigan Government website. Published August 5, 2020. December 20, 2022. https://www.michigan.gov/whitmer/news/state-orders-and-directives/2020/08/05/executive-directive-2020-9
- Momnibus. Black Maternal Health Caucus. Accessed December 20, 2022. https://blackmaternalhealthcaucus-underwood.house.gov/Momnibus
- Fitzgerald C, Martin A, Berner D, Hurst S. Interventions designed to reduce implicit prejudices and implicit stereotypes in real world contexts: a systematic review. BMC Psychol. 2019;7(1):29. doi:10.1186/s40359-019-0299-7
- Lai CK, Skinner AL, Cooley E, et al. Reducing implicit racial preferences: II. Intervention effectiveness across time. J Exp Psychol Gen. 2016;145(8):1001-1016. Published April 7, 2016. doi:10.1037/xge0000179
- Payne K, Vuletich HA, Lundberg KB. The bias of crowds: How implicit bias bridges personal and systemic prejudice. Psychol Inq. 2017;28(4):233-248. doi:10.1080/1047840X.2017.1335568
- WHO Statement on Caesarean Section Rates. World Health Organization. Published June 9, 2021. Accessed August 10, 2022. https://www.who.int/news-room/questions-and-answers/item/who-statement-on-caesarean-section-rates-frequently-asked-questions
- Osterman MJK, Hamilton BE, Martin JA, Driscolli AK, Valenzuela CP. Births: final data for 2020. Natl Vital Stat Rep. 2021;70(17):1-50.
- Mascarello KC, Horta BL, Silveira MF. Maternal complications and cesarean section without indication: systematic review and meta-analysis. Rev Saude Publica. 2017;51:105. doi: 10.11606/S1518-8787.2017051000389
- Curtin SC, Gregory KD, Korst LM, Uddin SF. Maternal morbidity for vaginal and cesarean deliveries, according to previous cesarean history: new data from the birth certificate, 2013. Natl Vital Stat Rep. 2015;64(4):1-13.
- Grobman WA, Sandoval G, Rice MM, et al. Prediction of vaginal birth after cesarean delivery in term gestations: a calculator without race and ethnicity. Am J Obstet Gynecol. 2021;225(6):664.e1-664.e7. doi:10.1016/j.ajog.2021.05.021
- Shamshirsaz AA, Fox KA, Salmanian B, et al. Maternal morbidity in patients with morbidly adherent placenta treated with and without a standardized multidisciplinary approach. AJOG. 2015;212(2):218.e1-9. doi:10.1016/j.ajog.2014.08.019
- Shields LE, Wiesner S, Fulton J, Pelletreau B. Comprehensive maternal hemorrhage protocols reduce the use of blood products and improve patient safety. AJOG. 2015;212(3):272-280. doi:10.1016/j.ajog.2014.07.012
- Hamm RF, Srinivas SK, Levine LD. A standardized labor induction protocol: impact on racial disparities in obstetrical outcomes. Am J Obstet Gynecol MFM. 2020;2(3):100148. doi:10.1016/j.ajogmf.2020.100148
- Roberts SCM, Zahnd E, Sufrin C, Armstrong MA. Does adopting a prenatal substance use protocol reduce racial disparities in CPS reporting related to maternal drug use? A California case study. J Perinatol. 2015;35(2):146-150. doi:10.1038/jp.2014.168
- Corl K, Levy M, Phillips G, Terry K, Friedrich M, Trivedi AN. Racial and ethnic disparities in care following the New York state sepsis initiative. Health Affairs. 2019;38(7):1119-1126. doi:10.1377/hlthaff.2018.05381
- Jean-Francois B, Lash TB, Dagher RK, Green Parker MC, Han SB, Lewis Johnson T. The potential for health information technology tools to reduce racial disparities in maternal morbidity and mortality. J Womens Health (Larchmt). 2021;30(2):274-279. doi:10.1089/jwh.2020.8889
- Shah T, Borondy Kitts A, Gold JA, et al. Electronic health record optimization and clinician well-being: a potential roadmap toward action. NAM Perspect. 2020;2020:10.31478/202008a. doi:10.31478/202008a
- Nelson DB, Moniz MH, Davis MM. Population-level factors associated with maternal mortality in the United States, 1997–2012. BMC Public Health. 2018;18(1):1007. doi:10.1186/s12889-018-5935-2
- Lau BD, Haider AH, Streiff MB, et al. Eliminating healthcare disparities via mandatory clinical decision support: The venous thromboembolism (VTE) example. Med Care. 2015;53(1):18-24. doi:10.1097/MLR.0000000000000251
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- Melvin SC, Wiggins C, Burse N, Thompson E, Monger M. The role of public health in COVID-19 emergency response efforts from a rural health perspective. Prev Chronic Dis. 2020;17:E70. doi:10.5888/pcd17.200256
- Computer and Internet Use in the United States: 2018. United States Census Bureau. Published April 21, 2021. December 20, 2022. https://www.census.gov/history/pdf/computer-internetuse2018.pdf