Abstract
Background:
Although telehealth is increasingly being used for providing postpartum care, its role in ensuring timely postpartum care initiation in racial/ethnic minorities and rural residents is unknown.
Objectives:
To compare attendance and timeliness of postpartum care initiation by pandemic exposure and telehealth uptake across race/ethnicity and rural-urban residences.
Research Design:
Retrospective cohort study.
Subjects:
Medicaid-insured individuals who gave birth in South Carolina between January 1, 2018, and September 30, 2022, were aged 15–49 years, and were followed up until December 31, 2022.
Measures:
Cox proportional hazards models examined associations between pandemic exposures, telehealth uptake, and racial/ethnic and rural/urban disparities in postpartum care initiation timeliness.
Results:
Median time to postpartum care initiation was 25 days [interquartile range (IQR): 14–41 d] with variations across race/ethnicity and residence. Fully-exposed nontelehealth users had slower initiation [adjusted hazard ratio (aHR): 0.95; 95% CI: 0.91–1.00], while telehealth users had quicker initiation (aHR: 2.19; 95% CI: 1.93–2.48) compared with non- or partially-exposed individuals. Among minimal- or no-telehealth users, postpartum care initiation was slower for Hispanic and non-Hispanic Black individuals compared with their non-Hispanic White peers. There were no differences in timely care initiation by race or residence among fully-exposed telehealth users.
Conclusions:
Telehealth may improve racial/ethnic disparities in timely postpartum care initiation. Rural-urban disparities in initiating timely postpartum care still warrant further investigation.
Key Words: access to care, health disparities, maternal and child health
Timely postpartum care can ensure maternal and child well-being through early detection and treatment of maternal morbidity.1,2 The American College of Obstetricians and Gynecologists recommends a postpartum follow-up within 21 days of childbirth and a comprehensive visit by 84 days postpartum.3 However, racial, ethnic, and geographic disparities persist.4–6 Medicaid data of Pennsylvania from November 2011 to December 2015 showed only 56% of Black individuals initiated postpartum care within 56 days, compared with 63% of White individuals and 73% of Asian individuals.6 Another study from 2 clinical sites in Pennsylvania from March to June 2019 echoed these racial disparities, showing only 63.9% of Black postpartum individuals versus 88.7% of non-Black postpartum individuals initiated care within 56 days of childbirth discharge.7 An analysis of PRAMS 2016–2018 data found that 88.1% of rural residents received any postpartum visit, compared with 90.3% of urban residents.8 Disparity in initiating timely postpartum care is an important contributor to adverse maternal outcomes.3,9 These disparities in access to timely postpartum care persist and coincide with increased pregnancy-related mortality rates for Black, American Indian, and rural individuals10,11—a trend exacerbated during the COVID-19 pandemic.12,13
Telehealth has shown potential to mitigate disparities in accessing timely care. Appointment scheduling, care coordination, and timely access to care facilities often act as major barriers to timely postpartum care initiation in some populations.14,15 Studies conducted before COVID-19 showed that telehealth use was associated with timely access to pediatric care,16 virtual urgent care,17 mental health services,18 and maternal health care services19 in both urban and rural communities. Similarly, telehealth use has also been associated with improved timely access to acute stroke care,20 diabetes care,21 mental health services,22 and care for perinatal depression,23 especially in racial and ethnic minority communities.20
Widespread disruptions in health care delivery systems during the COVID-19 pandemic drove the rapid rollout of telehealth services to ensure continued access to health care.24 Yet, little is known about telehealth’s role in addressing racial, ethnic, or rural-urban disparities in postpartum care during COVID-19, especially in the South, where maternal health professional shortages and pregnancy-associated mortality rates are higher than elsewhere in the United States. Before COVID-19, among Medicaid beneficiaries in the South and South Carolina, postpartum care uptake varied by geographic location and race/ethnicity, with higher odds among rural compared with urban residents and lower odds among Hispanic compared with non-Hispanic White individuals.25,26 Rural South Carolinians also had higher readmission rates for mental health disorders in the later postpartum period, and Black individuals had disproportionately high readmission rates.26 Yet, neither of these studies examined the role that telehealth use played in postpartum care, making it difficult to inform statewide interventions for access to maternity care in South Carolina.27 Some studies in the urban Northeast region have shown encouraging results. In Pennsylvania, postpartum care attendance using telehealth during early COVID-19 (March 2020–June 2020) had no racial differences in postpartum care follow-up or depression screening.7 In Chicago, telehealth use eliminated racial disparities in postpartum follow-up between non-Hispanic Black and non-Hispanic White individuals.28 A New York study also found that telehealth implementation was associated with maintained postpartum visit rates during COVID-19.29 However, these studies were centered around the Northeast region and focused on receiving postpartum care; yet, examining postpartum care should go beyond whether one received care to also examine how timely it was. Examining both access to and timeliness of postpartum care initiation is critical, as delays in care could compound considerable maternal health risks facing postpartum people, especially those in racial/ethnic minority and rural communities.
The South Carolina Telehealth Alliance envisages the potential for telehealth in mitigating access disparities in maternal-fetal medicine.30 However, the role of telehealth in ensuring access to timely postpartum care in racial, ethnic minorities or urban- and rural-communities remains underexplored. Understanding these disparities is crucial for the effective allocation of limited resources and the development of efficient interventions to improve postpartum outcomes. This population-based retrospective cohort study used statewide Medicaid data to investigate rural-urban and racial and ethnic disparities in postpartum care follow-up and its timeliness. We further compared the timeliness of postpartum care initiation across birthing people by their postpartum exposure to the COVID-19 pandemic and their telehealth uptake.
METHODS
Data Source
This statewide cohort study used data from Medicaid claims and enrollment data in South Carolina. This database includes 100% of Medicaid eligibility and enrollment transactions and Medicaid-paid records from inpatient, emergency departments, and outpatient settings. We linked this information to birth certificate data using unique identifiers of birthing individuals and their childbirth year.31 We identified all Medicaid-covered childbirths for birthing individuals who lived in South Carolina, were aged 15–49 years, and gave birth from January 2018 to September 2022. Each included individual was followed up for 365 days, or until December 31, 2022 (whichever came first), so we would have a complete 3-month follow-up for defining early postpartum care initiation.
Measures
Postpartum pandemic exposure was classified into 3 groups based on childbirth timing relative to the onset of COVID-19 public health emergency and the associated telehealth flexibility changes under the CARES Act, which was passed on March 20.27,32 Never-exposed group had childbirth between January 1, 2018, and February 28, 2019, with 1-year postpartum before March 1, 2020; partially-exposed group had childbirth before March 1, 2020, but exposed part of their postpartum year during the pandemic (March 1, 2019–February 29, 2020), and fully-exposed group had childbirth from March 1, 2020, to September 30, 2022. The fully-exposed cohort was further categorized into telehealth nonusers and telehealth users.27,32 Telehealth use was only separately examined for the fully-exposed cohort because telehealth use was minimal before this period (0.13% among the never-exposed and 1.36% among the partially-exposed groups), which increased to 5.6% among the fully-exposed group (eFig. 1, Supplemental Digital Content 1, http://links.lww.com/MLR/D139). Other key independent factors include race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, and others/unknown), and residence location at the county level (urban, rural, unknown) based on 2023 Rural-Urban Continuum Codes (RUCC).
Our primary outcome was timeliness in postpartum care initiation, measured by days from childbirth discharge date to the first postpartum care visit or censored at the last follow-up date available (ie, December 31, 2022). Using this measure, we further compared the proportions of individuals who initiated postpartum care within 90 days of discharge across pandemic exposure status, race/ethnicity, and residence location.
Other similar studies were referred to while selecting covariates,7,28,29,33 including age at childbirth, maternal educational attainment, prepregnancy body mass index (BMI), chronic or gestational diabetes mellitus, pre-existing or pregnancy-induced hypertension or pre-eclampsia, mental health disorder diagnosis during pregnancy, plurality, parity, gestational week at childbirth [preterm (<37 wk) or full term (37–47 wk)], obstetric comorbidity index to capture risk of severe maternal morbidity, and hospital level of obstetric care to capture level of specialty care.
Ethics Clearance
Given that the study uses secondary data for deriving insights, it is exempt from IRB clearance.
Statistical Analysis
We first compared maternal and hospital characteristics using the Pearson χ2 tests (nominal variables), the Mantel-Haenszel test (for ordinal variables, eg, age group), and the Fisher exact test (for residence location, diabetes, plurality), to compare the distributions of maternal and hospital characteristics between the never-exposed group and each exposure group: partially-exposed, fully-exposed without telehealth use, and fully-exposed with telehealth use. The percentages of individuals initiating postpartum care within 90 days of childbirth discharge and the median [interquartile range (IQR)] days to access first postpartum care visit within 365 days postdischarge were compared using the Pearson χ2 test and the Wilcoxon/Kruskal-Wallis test, respectively.
The Kaplan-Meier method was used to estimate the timeliness of postpartum care initiation overall and in subgroups of varying birthing individuals by postpartum pandemic exposure and telehealth uptake, race, ethnicity, and residence location. We generated a Cox proportional hazards model to adjust our findings for identified confounders. The proportional hazards assumption was evaluated using log-log survival curves and Schoenfeld residuals, which indicated a violation of the proportional hazards assumption. To address this violation, we included interaction terms for pandemic exposure (the categorized time-varying variable),34 race/ethnicity, and exposure and residence. Consequently, we generated 4 Cox proportional hazards multivariable models: without interaction, interacting only for pandemic exposure and race/ethnicity, interacting only for pandemic exposure and residence location, and interacting for pandemic exposure with both race/ethnicity and residence location. Hazard ratios (HRs) with 95% CIs were used to assess the association between exposures and timeliness in initiating postpartum care. We also included hospital-level fixed effects to control for between-hospital differences.
SAS 9.4 was used to perform statistical analysis from February 9 to August 25, 2024. A two-sided P<0.05 indicates statistical significance. This study followed the STROBE reporting guideline for cohort studies.
RESULTS
Study Population
Of 103,977 SC postpartum Medicaid beneficiaries from South Carolina giving birth from January 2018 to September 2022, 26,402 (25.4%) were never-exposed, 22,441 (21.6%) were partially-exposed, and 55,134 (53.0%) were fully-exposed to the COVID-19 pandemic during the 1-year postpartum (Table 1). In the fully-exposed group, only 3103 (5.6%) ever used telehealth for postpartum care. By race and ethnicity, 44,354 (42.6%) were non-Hispanic White, 43,432 (41.8%) were non-Hispanic Black, 8054 (7.8%) were Hispanic, and 8137 (7.8%) were of other or unknown race. By residence, 17,361 (16.7%) were rural residents, 86,238 (82.9%) were urban residents, and 378 (0.4%) did not mention their residence location.
TABLE 1.
Demographic Characteristics of Medicaid-Insured Birthing Individuals in South Carolina Who Gave Birth Between January 1, 2018, and September 30, 2022
| Postpartum pandemic exposure | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Fully-exposed | |||||||||
| All | Never-exposed | Partially-exposed | Nontelehealth user | Telehealth user | |||||
| All childbirths | n (%) | n (%) | P | n (%) | P | n (%) | P | n (%) | P |
| 103,977 | 26,402 | 22,441 | 52,031 | 3103 | |||||
| Race/ethnicity | |||||||||
| Non-Hispanic White | 44,354 (42.6) | 11,436 (43.4) | Ref. | 9548 (42.6) | 0.0099 | 21,585 (41.5) | <0.001 | 1785 (57.5) | <0.001 |
| Hispanic | 8054 (7.8) | 1748 (6.6) | 1653 (7.4) | 4508 (8.7) | 145 (4.7) | ||||
| Non-Hispanic Black | 43,432 (41.8) | 11,179 (42.3) | 9498 (42.2) | 21,725 (41.7) | 1030 (33.2) | ||||
| Other/unknown | 8137 (7.8) | 2039 (7.7) | 1742 (7.8) | 4213 (8.1) | 143 (4.6) | ||||
| Residence location | |||||||||
| Rural | 17,361 (16.7) | 4515 (17.1) | Ref. | 3775 (16.8) | 0.6019 | 8738 (16.8) | 0.2954 | 333 (10.7) | <0.001 |
| Urban | 86,238 (82.9) | 21,798 (82.6) | 18,583 (82.8) | 43,090 (82.8) | >2760 (89.2) | ||||
| Unknown | 378 (0.4) | 89 (0.3) | 83 (0.4) | 203 (0.4) | <10 | ||||
| Age (y) | |||||||||
| <20 y | 10,199 (9.8) | 2747 (10.4) | Ref. | 2274 (10.1) | 0.0004 | 4951 (9.6) | <0.001 | 227 (7.3) | <0.001 |
| 20–24 y | 31,326 (30.1) | 8333 (31.6) | 6881 (30.7) | 15,294 (29.4) | 818 (26.4) | ||||
| 25–29 y | 32,334 (31.1) | 8413 (31.9) | 7010 (31.2) | 15,943 (30.6) | 968 (31.2) | ||||
| 30–34 y | 19,676 (18.9) | 4515 (17.1) | 4125 (18.4) | 10,319 (19.8) | 717 (23.1) | ||||
| 35–56 y | 10,440 (10.1) | 2394 (9.0) | 2151 (9.6) | 5522 (10.6) | 373 (12.0) | ||||
| Education | |||||||||
| High school diploma or lower | 62,662 (60.3) | 15,714 (59.5) | Ref. | 13,463 (60.0) | 0.2068 | 31,878 (61.3) | <0.001 | 1607 (51.8) | <0.001 |
| Some college or an associate’s degree | 33,860 (32.6) | 8877 (33.6) | 7440 (33.1) | 16,312 (31.3) | 1231 (39.7) | ||||
| Bachelor | 5660 (5.4) | 1347 (5.1) | 1188 (5.3) | 2921 (5.6) | 204 (6.6) | ||||
| Graduate or professional | 1222 (1.2) | 316 (1.2) | 227 (1.0) | 631 (1.2) | 48 (1.5) | ||||
| Unknown | 573 (0.5) | 148 (0.6) | 123 (0.6) | 289 (0.6) | 13 (0.4) | ||||
| Prepregnancy BMI | |||||||||
| Healthy weight | 32,439 (31.2) | 8622 (32.7) | Ref. | 7038 (31.4) | 0.0327 | 15,870 (30.5) | <0.001 | 909 (29.3) | <0.001 |
| Underweight | 4117 (4.0) | 1016 (3.9) | 860 (3.8) | 2111 (4.1) | 130 (4.2) | ||||
| Overweight | 26,178 (25.2) | 6540 (24.8) | 5684 (25.3) | 13,218 (25.4) | 736 (23.7) | ||||
| Obesity | 40,279 (38.7) | 9846 (37.3) | 8554 (38.1) | 20,577 (39.5) | 1302 (42.0) | ||||
| Unknown | 964 (0.9) | 378 (1.4) | 305 (1.4) | 255 (0.5) | 26 (0.8) | ||||
| Diabetes mellitus (DM) | |||||||||
| No | 97,316 (93.6) | 24,887 (94.3) | Ref. | 21,117 (94.1) | 0.483 | 48,458 (93.1) | <0.001 | 2854 (92.0) | <0.001 |
| Type I, type II, or gestational diabetes | 6659 (6.4) | 1514 (5.7) | 1324 (5.9) | 3572 (6.9) | 249 (8.0) | ||||
| Hypertension | |||||||||
| Normotensive | 94,447 (90.8) | 24,090 (91.2) | Ref. | 20,454 (91.2) | 0.6054 | 47,235 (90.8) | 0.0915 | 2668 (86.0) | <0.001 |
| Hypertension, or pregnancy-induced hypertension (PIH) | 9528 (9.2) | 2311 (8.7) | 1987 (8.8) | 4795 (9.2) | 435 (14.0) | ||||
| Mental health conditions | |||||||||
| No known mental health disorders | 80,764 (77.7) | 21,011 (79.6) | Ref. | 17,520 (78.1) | 0.0003 | 40,329 (77.5) | <0.001 | 1904 (61.4) | <0.001 |
| Substance use disorder (SUD) only | 11,328 (10.9) | 2868 (10.9) | 2549 (11.4) | 5621 (10.8) | 290 (9.3) | ||||
| Non-SUD mental health diagnosis only | 8434 (8.1) | 1739 (6.5) | 1654 (7.4) | 4373 (8.4) | 668 (21.5) | ||||
| Both SUD and other co-occurring mental health conditions | 3451 (3.3) | 784 (3.0) | 718 (3.1) | 1708 (3.3) | 241 (7.8) | ||||
| Plurality | |||||||||
| Multiple births | 1804 (1.7) | 437 (1.7) | Ref. | 367 (1.6) | 0.8641 | 934 (1.8) | 0.2858 | 66 (2.1) | 0.0548 |
| Singleton | 102,172 (98.3) | 25,965 (98.3) | 22,074 (98.4) | 51,096 (98.2) | 3037 (97.9) | ||||
| Parity | |||||||||
| Primigravida | 35,225 (33.9) | 9187 (34.8) | Ref. | 7684 (34.2) | 0.0356 | 17,355 (33.4) | <0.001 | 999 (32.2) | 0.018 |
| One previous live birth | 30,388 (29.2) | 7690 (29.1) | 6426 (28.6) | 15,326 (29.5) | 946 (30.5) | ||||
| Two previous live births | 20,518 (19.7) | 5239 (19.8) | 4473 (19.9) | 10,152 (19.5) | 654 (21.1) | ||||
| Three or more previous live births | 17,770 (17.1) | 4264 (16.1) | 3845 (17.1) | 9157 (17.5) | 504 (16.2) | ||||
| Unknown | 76 (0.1) | 22 (0.1) | 13 (0.1) | 41 (0.1) | 0 (0.0) | ||||
| Gestation period | |||||||||
| Preterm (<37 wk) | 12,767 (12.3) | 3134 (11.9) | Ref. | 2678 (11.9) | 0.6515 | 6501 (12.5) | 0.0027 | 454 (14.6) | <0.001 |
| Full term (≥37 wk) | 91,177 (87.7) | 23,254 (88.1) | 19,755 (88.0) | 45,519 (87.4) | 2649 (85.4) | ||||
| Unknown | 33 (0.03) | 14 (0.05) | <10 | 11 (0.01) | 0 (0.0) | ||||
| Obstetric comorbidity index | |||||||||
| Quartile I | 21,358 (20.5) | 5331 (20.2) | Ref. | 4849 (21.6) | <0.01 | 10,753 (20.7) | <0.001 | 425 (13.7) | <0.001 |
| Quartile II | 6021 (5.8) | 1462 (5.5) | 1229 (5.5) | 3217 (6.2) | 113 (3.6) | ||||
| Quartile III | 13,685 (13.2) | 4180 (15.8) | 2874 (12.8) | 6208 (11.9) | 423 (13.6) | ||||
| Quartile IV | 19,842 (19.1) | 5597 (21.20) | 3834 (17.1) | 9918 (19.1) | 493 (15.9) | ||||
| Unknown | 43,071 (41.4) | 9832 (37.3) | 9655 (43.0) | 21,935 (42.1) | 1649 (53.2) | ||||
| Hospital level of obstetric care | |||||||||
| Level I | 11,955 (11.5) | 3022 (11.4) | Ref. | 2570 (11.4) | <0.001 | 6050 (11.6) | <0.001 | 313 (10.1) | <0.001 |
| Level II | 37,568 (36.2) | 9124 (34.6) | 7881 (35.1) | 19,613 (37.7) | 950 (30.6) | ||||
| Level III | 45,144 (43.4) | 11,287 (42.8) | 10,111 (45.1) | 22,105 (42.5) | 1641 (52.9) | ||||
| Unknown | 9310 (8.9) | 2969 (11.2) | 1879 (8.4) | 4263 (8.2) | 199 (6.4) | ||||
Postpartum pandemic exposure was classified as never-exposed (childbirth between January 1, 2018, and February 28, 2019 with 1-year postpartum before March 1, 2020), partially-exposed [childbirth before March 1, 2020 and exposed to COVID-19 (which hit on March 1, 2020) during the 1-year postpartum, ie, March 1, 2019–February 29, 2020], and fully-exposed (childbirth from March 1, 2020, to September 30, 2022). Maternal and hospital characteristics were compared by postpartum pandemic exposure and telehealth uptake.
P-values were calculated using the Pearson χ2 tests (nominal variables), Mantel-Haenszel tests (for ordinal variables, eg, age group), and Fisher exact tests (for residence location, diabetes, plurality), to compare the distributions of maternal and hospital characteristics between the never-exposed group and each exposure group: partially-exposed, fully-exposed without telehealth use, and fully-exposed with telehealth use.
Compared with the unexposed group, Hispanic individuals and individuals of other races were more likely to be in the partially-exposed and the fully-exposed nontelehealth user groups, whereas non-Hispanic White individuals were more likely to be in the fully-exposed telehealth user group. Among the fully-exposed group, urban residents were more likely to be using telehealth when compared with rural residents (Table 1).
Timeliness of Postpartum Care Initiation by Pandemic Exposure and Telehealth Uptake
Overall, 71,646 (68.9%) individuals initiated postpartum care within 90 days postdischarge, with a median (IQR) days to initiation at 25 (14–41) days (Table 2). When compared across postpartum pandemic exposure, 18,397 (69.7%) of never-exposed, 15,522 (69.2%) of partially-exposed, and 34,624 (66.6%) of fully-exposed nontelehealth users initiated postpartum care within 90 days postdischarge. In contrast, all [3103 (100.0%)] of fully-exposed telehealth users initiated postpartum care within 90 days postdischarge (Table 2; eTable 1, Supplemental Digital Content 1, http://links.lww.com/MLR/D139). By timing, postpartum care initiation was significantly quicker in telehealth users [median (IQR): 18 (9–28 d); P<0.0001], compared with the never- and partially-exposed groups [both 25 (13–40 d)], and the fully-exposed group without telehealth use [27 (15–43 d); Table 2]. Among all exposure groups, the never-exposed and partially-exposed groups had similar time to postpartum care initiation but had it earlier than did the fully-exposed group without telehealth use (log-rank test, χ2=3178.2 and P=<0.01; eFig. 2, Supplemental Digital Content 1, http://links.lww.com/MLR/D139).
TABLE 2.
Proportion of Postpartum Individuals Giving Birth From January 1, 2018, to September 30, 2022, in South Carolina Who Received Follow-Up Care and Timeliness to Postpartum Care Initiation
| Days to first postpartum follow-up | |||
|---|---|---|---|
| Characteristics | No. people with postpartum follow-up within 90 days postchildbirth discharge, n (%) | Median (IQR) | P |
| All | 71,646 (68.9) | 25 (14–41) | — |
| Postpartum pandemic exposure and telehealth | |||
| Never-exposed | 18,397 (69.7) | 25 (13–40) | <0.001 |
| Partially-exposed | 15,522 (69.2) | 25 (13–40) | |
| Fully-exposed—nontelehealth user | 34,624 (66.6) | 27 (15–43) | |
| Fully-exposed—telehealth user | 3103 (100.00) | 18 (9–28) | |
| Race/ethnicity | |||
| Non-Hispanic White | 32,899 (74.2) | 24 (13–39) | <0.001 |
| Hispanic | 2635 (32.7) | 25 (13–39) | |
| Non-Hispanic Black | 31,786 (73.2) | 26 (14–43) | |
| Other/unknown | 4326 (53.2) | 25 (14–40) | |
| Residence location | |||
| Rural | 12,524 (72.1) | 26 (14–42) | <0.001 |
| Urban | 58,956 (68.4) | 25 (14–40) | |
| Unknown | 166 (44.1) | 26 (15–53) | |
| Age (y) | <0.001 | ||
| <20 y | 7208 (70.7) | 27 (15–44) | |
| 20–24 y | 21,719 (69.3) | 26 (15–42) | |
| 25–29 y | 22,386 (69.2) | 25 (14–41) | |
| 30–34 y | 13,471 (68.5) | 24 (13–39) | |
| 35–56 y | 6862 (65.7) | 23 (12–38) | |
| Education | |||
| High school diploma or lower | 40,276 (64.3) | 26 (14–43) | <0.001 |
| Some college or an associate’s degree | 26,034 (76.9) | 24 (14–39) | |
| Bachelor | 4177 (73.8) | 23 (13–36) | |
| Graduate or professional | 868 (71.0) | 23 (13–36) | |
| Unknown | 291 (51.0) | 26 (13–50.5) | |
| Prepregnancy BMI | |||
| Healthy weight | 21,579 (66.5) | 26 (15–42) | <0.001 |
| Underweight | 2752 (66.8) | 27 (15–44) | |
| Overweight | 17,540 (67.0) | 26 (14–41) | |
| Obesity | 29,304 (72.7) | 24 (13–39) | |
| Unknown | 471 (49.0) | 25 (12–46) | |
| Diabetes mellitus (DM) | |||
| No | 66,881 (68.7) | 25 (14–41) | <0.001 |
| Type I, type II, or gestational diabetes | 4765 (71.6) | 24 (12–38) | |
| Hypertension | |||
| Normotensive | 64,728 (68.5) | 26 (14–41) | <0.001 |
| Hypertensive or pregnancy-induced hypertension (PIH) | 6918 (72.6) | 23 (11–39) | |
| Mental health conditions | |||
| No known mental health conditions | 55,009 (68.1) | 26 (14–40) | <0.001 |
| Substance use disorder (SUD) only | 7490 (66.1) | 26 (13–36) | |
| Non-SUD mental health diagnosis only | 6598 (78.2) | 23 (12–39) | |
| Both SUD and other co-occurring mental health conditions | 2549 (73.9) | 24 (11–45) | |
| Plurality | |||
| Multiple births | 1337 (74.1) | 22 (10–39) | <0.001 |
| Singleton | 70,309 (68.8) | 25 (14–41) | |
| Parity | |||
| Primigravida | 26,340 (74.8) | 24 (13–38) | <0.001 |
| One previous live birth | 20,972 (69.0) | 26 (14–41) | |
| Two previous live births | 13,522 (65.9) | 26 (14–42) | |
| Three or more previous live births | 10,773 (60.6) | 27 (14–46) | |
| Unknown | 39 (52.7) | 28 (15 - 55) | |
| Gestation period | |||
| Preterm (<37 wk) | 8909 (69.8) | 24 (11–41) | <0.001 |
| Full term (≥37 wk) | 62,725 (68.8) | 25 (14–41) | |
| Unknown | 12 (38.7) | 47.5 (12.5–81.5) | |
| Obstetric comorbidity index | |||
| Quartile I | 13,841 (64.8) | 27 (16–40) | <0.001 |
| Quartile II | 3763 (62.5) | 25 (14–39) | |
| Quartile III | 9716 (71.0) | 25 (14–40) | |
| Quartile IV | 13356 (67.3) | 25 (13–41) | |
| Unknown | 30,970 (71.9) | 25 (13–41) | |
| Hospital levels of obstetric care | |||
| Level I | 7882 (65.9) | 26 (14–43) | <0.001 |
| Level II | 26,854 (71.5) | 26 (14–41) | |
| Level III | 30,896 (68.4) | 25 (14–40) | |
| Unknown | 6014 (64.6) | 25 (13–40) | |
Postpartum pandemic exposure was classified as never-exposed (childbirth between January 1, 2018, and February 28, 2019 with 1-year postpartum before March 1. 2020), partially-exposed [childbirth before March 1, 2020 and exposed to COVID-19 (which hit on March 1, 2020) during the 1-year postpartum, ie, March 1, 2019–February 29, 2020] and fully-exposed (childbirth from March 1, 2020, to September 30, 2022). Interquartile range (IQR) (quartile 1–quartile 3) for childbirth between January 1, 2018, and September 30, 2022.
P-values were calculated to compare timeliness to accessing first postpartum care follow-up within each group of postpartum individuals during 1-year postpartum periods using the Wilcoxon/Kruskal-Wallis test.
Testing for the proportional hazards assumption suggested that the HR did not vary over time. After adjusting for maternal sociodemographic and clinical characteristics, there were no significant differences in the timeliness of postpartum care initiation between never-exposed and partially-exposed postpartum individuals. Although postpartum care initiation was slower for fully-exposed nontelehealth users [adjusted HR (aHR): 0.95; 95% CI: 0.91–1.00], telehealth users had significantly earlier initiation of postpartum care (aHR: 2.19; 95% CI: 1.93–2.48) compared with the never-exposed group (Table 3).
TABLE 3.
Adjusted Hazard Ratios of Days to Postpartum Care Initiation for Individuals Giving Birth From January 1, 2018, to September 30, 2022, in South Carolina
| Characteristics | aHR | 95% CI | P | |
|---|---|---|---|---|
| Postpartum pandemic exposure and utilization of telehealth among rural Non-Hispanic White individuals | ||||
| Never-exposed | Reference | |||
| Partially-exposed | 0.99 | 0.93 | 1.05 | 0.746 |
| Fully-exposed—nontelehealth user | 0.95 | 0.91 | 1.00 | 0.033 |
| Fully-exposed—telehealth user | 2.19 | 1.93 | 2.48 | <0.001 |
| Differential timeliness of accessing postpartum care by exposure status and race/ethnicity | ||||
| Never-exposed | ||||
| Non-Hispanic White | Reference | |||
| Non-Hispanic Black | 0.96 | 0.93 | 0.99 | 0.0105 |
| Hispanic | 0.35 | 0.32 | 0.38 | <0.001 |
| Others/unknown | 0.59 | 0.55 | 0.63 | <0.001 |
| Partially-exposed | ||||
| Non-Hispanic White | Reference | |||
| Non-Hispanic Black | 0.94 | 0.91 | 0.97 | <0.001 |
| Hispanic | 0.33 | 0.3 | 0.36 | <0.001 |
| Others/unknown | 0.59 | 0.55 | 0.64 | <0.001 |
| Fully-exposed—nontelehealth user | ||||
| Non-Hispanic White | Reference | |||
| Non-Hispanic Black | 0.98 | 0.96 | 1.01 | 0.119 |
| Hispanic | 0.33 | 0.31 | 0.35 | <0.001 |
| Others/unknown | 0.65 | 0.63 | 0.68 | <0.001 |
| Fully-exposed—telehealth user | ||||
| Non-Hispanic White | Reference | |||
| Non-Hispanic Black | 1.01 | 0.93 | 1.09 | 0.806 |
| Hispanic | 1.09 | 0.92 | 1.3 | 0.329 |
| Others/unknown | 1.04 | 0.87 | 1.24 | 0.664 |
| Differential timeliness of accessing postpartum care by exposure status and residence location | ||||
| Never-exposed | ||||
| Rural | Reference | |||
| Urban | 0.99 | 0.95 | 1.03 | 0.626 |
| Unknown | 0.41 | 0.29 | 0.57 | <0.001 |
| Partially-exposed | ||||
| Rural | Reference | |||
| Urban | 1.01 | 0.97 | 1.06 | 0.660 |
| Unknown | 0.6 | 0.44 | 0.81 | 0.001 |
| Fully-exposed—nontelehealth user | ||||
| Rural | Reference | |||
| Urban | 0.92 | 0.89 | 0.95 | <0.001 |
| Unknown | 0.47 | 0.38 | 0.59 | <0.001 |
| Fully-exposed—telehealth user | ||||
| Rural | Reference | |||
| Urban | 0.93 | 0.83 | 1.05 | 0.226 |
| Unknown | 1.76 | 0.57 | 5.51 | 0.329 |
Postpartum pandemic exposure was classified as never-exposed (childbirth between January 1, 2018, and February 28, 2019, with 1-year postpartum before March 1, 2020), partially-exposed [childbirth before March 1, 2020, and exposed to COVID-19 (which hit on March 1, 2020) during the 1-year postpartum; childbirth March 1, 2019–February 29, 2020) and fully-exposed (childbirth from March 1, 2020, to September 30, 2022]. The adjusted Hazard Ratios (aHRs) and 95% CIs were estimated based on the Cox proportional hazards model of timeliness to accessing the first postpartum visit, after controlling for hospital-level fixed effects. Using this model, we calculated differences in timeliness to the first postpartum care visit by COVID-19 exposure and telehealth use. The full set of estimates and covariates from the two-way interaction model is provided in eTable 3 in the Supplemental Material, Supplemental Digital Content 1, http://links.lww.com/MLR/D139.
Timeliness of Postpartum Care Initiation by Race, Ethnicity, and Residence Location
By race/ethnicity, nearly three-quarters of non-Hispanic White [32,899 (74.2%)] and non-Hispanic Black [31,786 (73.2%)] individuals initiated postpartum care within 90 days postdischarge, compared with 2635 (32.7%) of Hispanic and 4326 (53.2%) of postpartum individuals of other race groups (Table 2). On average, postpartum care initiation was modestly earlier for non-Hispanic White individuals [median (IQR): 24 (13–39 d)] when compared with other racial and ethnic identities, especially non-Hispanic Black [26 (14–43 d); P<0.01]. Almost three-fourths [12,524, (72.1%)] of rural residents and 58,956 (68.4%) of urban residents initiated postpartum care within 90 days, with urban residents initiating postpartum care slightly earlier [25 (14–40 d)] than rural [26 (14–42 d); P<0.01].
Racial and ethnic disparities in postpartum care initiation timeliness varied across pandemic exposure groups (Fig. 1, Table 3). Postpartum care initiation was faster among fully exposed telehealth users across all race ethnicities compared to thosenever- or partially-exposed (Table 3; eTable 3, Supplemental Digital Content 1, http://links.lww.com/MLR/D139). While non-Hispanic Black postpartum individuals had similarly slow initiation compared with their non-Hispanic White counterparts when they were fully exposed and did not use telehealth, Hispanic and other race groups experienced disproportionally slower initiation. Hispanic-White disparities in delayed postpartum care initiation were exacerbated for partially-exposed (aHR: 0.33, 95% CI: 0.30–0.36) and fully-exposed nontelehealth users (aHR: 0.33, 95% CI: 0.31–0.35), relative to never-exposed group (aHR: 0.35, 95% CI: 0.32–0.38). Among the telehealth users, such racial and ethnic disparities were not statistically significant. By residence, rural-urban gaps in the timeliness of postpartum care initiation were modest for never-exposed or partially-exposed postpartum individuals and exacerbated for fully-exposed individuals who did not use telehealth (Fig. 2). After adjusting for maternal and hospital characteristics, we found slower postpartum care initiation in urban nontelehealth users (aHR: 0.92, 95% CI: 0.89–0.95) in the fully-exposed group, but this urban disparity was not statistically significant among telehealth users.
FIGURE 1.
Postpartum care initiation within the first 90 days postdischarge, by race and ethnicity and telehealth utilization.
FIGURE 2.
Postpartum care initiation within the first 90 days postdischarge, by residence location and telehealth utilization.
Number of Postpartum Care Visits
Across all pandemic exposure groups, the number of postpartum care visits remained the same, with modest variations across maternal race, ethnicity, and urban-rural residence status (eTable 2, Supplemental Digital Content 1, http://links.lww.com/MLR/D139). Hispanic individuals and rural residents in the fully-exposed group who were able to access telehealth had significantly more visits [Hispanic telehealth users: median (IQR)=2 (1–3) visits; rural telehealth users: 3 (2–4) visits] compared with their counterparts without using telehealth [Hispanic nontelehealth users: median (IQR)=1 (1–2) visits; rural nontelehealth users: 2 (1–3) visits].
DISCUSSION
This retrospective cohort study of birthing individuals in South Carolina revealed persistent racial and ethnic disparities in postpartum care initiation before and during the pandemic in telehealth nonusers. Yet telehealth users, even when fully exposed to the pandemic, had not only the highest rates of postpartum follow-up within 90 days postpartum but also the shortest time intervals from childbirth discharge to the first postpartum follow-up visit. Urban residents in the fully-exposed nontelehealth user group experienced more delays in postpartum care initiation than rural residents; however, this urban-rural disparity was not observed in the fully-exposed group with telehealth use.
Our findings align with historical patterns of racial and ethnic disparities in postpartum care initiation and utilization, which persisted during the COVID-19 pandemic but only among those without telehealth use. Prepandemic (2016–2019) studies showed lower rates of receiving postpartum depression screening and contraceptive counseling in racial and ethnic minorities,5 and significant delays in care or lack of postpartum follow-up for non-Hispanic Black individuals compared with non-Hispanic White individuals.6 While telehealth is envisioned to mitigate health care access disparities, the outcomes have been mixed.35 Telehealth has reduced racial and ethnic disparities in prenatal36 and postpartum care utilization,7 but some studies have found persistent racial and ethnic disparities.35 Patient- and community-centered telehealth solutions have shown greater acceptability by racial and ethnic minorities.37
Our findings that Hispanic beneficiaries who did not use telehealth initiated postpartum care more slowly than their White counterparts are consistent with historical barriers such as limited English proficiency and language discordance, which can delay in-person care.38 This is especially pertinent for states like South Carolina, where more than half of the Hispanic population is foreign-born.39 Although our study did not examine language concordance or interpreter tools specifically, telehealth as a modality may more easily support remote interpretation, which may help mitigate communication and logistical barriers for foreign-born patients. Therefore, multiple systemic inequities need to be considered and addressed before telehealth implementation can start yielding desired results.
We found delayed postpartum care initiation for urban nontelehealth users compared with their rural peers, aligning with prior prepandemic research.40 An Illinois study using 2009–2010 Medicaid claims data found that urban residents were the most likely to delay postpartum care initiation across urban, suburban, and rural communities.40 Whereas rural individuals encounter significant barriers to health care access,41 urban communities also experience unique challenges.14 Urban residents often face difficulties in appointment scheduling due to overcrowding, limited time slots, and unavailable childcare options, delaying postpartum care initiation.14 Potentially, these barriers can be overcome by telehealth modality, which evidently improved efficiency and convenience.42 Indeed, we found that while urban-rural disparities in postpartum care timing exist among nontelehealth users, urban telehealth users did not experience delayed postpartum care initiation relative to their rural counterparts. These findings add compelling evidence on the potential role of telehealth in the complex nature of postpartum care access to the existing, limited evidence. During COVID-19, the Office of Health Policy found improved postpartum care follow-up; however, they did not explore the association of telehealth uptake with rural-urban disparities.43 Other studies have found that implementation of telehealth initiatives to deliver postpartum care may fail to reach the most underserved rural communities due to the rural-urban digital divide.44,45 Rural communities often grapple with the dual barriers of physical distance from the closest health care facility and poor digital access, leading to limited telehealth reach.46 Findings from our study, however, indicate that once telehealth access is ensured, it can help address urban-rural disparities in postpartum care initiation timeliness.
Our findings shed light on 2 key gains that can result from implementing telehealth for postpartum care. First, telehealth implementation for postpartum care access can be an efficient modality for ensuring timely postpartum care initiation in racial and ethnic minority communities in South Carolina. Second, telehealth implementation can also be leveraged to ensure timely postpartum care initiation in urban residents. Nevertheless, both of these recommendations come with caveats. Equal access to and timeliness of postpartum care follow-up among the telehealth users in the fully-exposed group, across race, ethnicity, and residential rurality groups, might be driven by multiple factors. At the individual level, birthing people with higher clinical needs are more likely to have timely initiation of postpartum care. Indeed, we found that birthing individuals who were older, overweight or obese, with diabetes, with hypertension, had a higher obstetric comorbidity index score, and/or had mental health diagnoses were more likely to use telehealth when fully exposed to the pandemic. However, to ensure sustained gains, caution should be exercised to ensure that services delivered using telehealth are risk-appropriate, community-centered, respectful, and informed by the needs of these high-risk pregnancies. This may—as our results indicated—result in 1 or 2 additional postpartum visits for conducting necessary tests, such as blood pressure or laboratory tests, to complement virtual postpartum care consultations.47 Policy makers should also consider systemic barriers in accessing telehealth. Ongoing research into determinants of satisfactory and equitable access to telehealth and telemedicine has identified digital determinants of health—defined as “factors rooted in or contingent on the digital world that can directly or indirectly influence health or well-being”48—as an important underlying factor, which should be considered before wider implementation of telehealth for postpartum care access.
Limitations
This study has a few limitations. First, our findings are based on data obtained from pregnant and postpartum individuals in South Carolina, thereby limiting their applicability to other state settings. Second, individual digital access, digital literacy, and fluency may play a role in telehealth use and care timing, but are unobserved in this study. Third, we did not include SARS-CoV-2 diagnosis status for the postpartum individuals in our model, due to the focus on the comparisons between pandemic exposure groups. SARS-CoV-2 status could have influenced their decision regarding postpartum care initiation and modality for accessing postpartum care. Fourth, not all postpartum care providers offered telehealth as an option for accessing postpartum care. However, by including hospital fixed effects, we were able to control for organizational-level time-invariant factors. Also, although the timing differences between rural-urban and across racial and ethnic groups were statistically significant, they were minimal (1–2 d) and may not be clinically significant. However, the potential impact of initiating postpartum care even a day earlier on perinatal outcomes warrants further investigation. Fifth, our results reflect telehealth uptake patterns during the COVID-19 pandemic. Further research is warranted to examine its utility in telehealth utilization in addressing access disparities as the pandemic wanes beyond the pandemic, as in-person care becomes widely available again, and providers and patients gain more experience with telehealth. However, to our knowledge, this is the first study documenting not only postpartum care patterns by the COVID-19 pandemic exposure but also comparing those with and without telehealth use during the pandemic across various socioeconomic groups. This is especially pertinent since the pandemic was a time of rapid telehealth investment. Therefore, our findings highlight the potential promise of telehealth in addressing disparities in postpartum care initiation timeliness seen in nontelehealth-using peers both before and during the pandemic. Finally, Medicaid claims data have limitations, including nonrepresentativeness of the population, especially the commercially insured, limiting the generalizability of our findings.
CONCLUSION
Telehealth has the potential to address longstanding disparities in timely postpartum care initiation, particularly by countering the pandemic’s negative effects on delayed care. Future research is warranted to explore the detrimental impacts of the COVID-19 pandemic on urban birthing individuals in South Carolina who were unable to take advantage of telehealth services, despite their widespread availability, to better inform strategies for enhancing the resilience and equity of perinatal care in the face of future public health epidemics. In addition, further examination of the impact of telehealth on disparities in timely access to postpartum care can be instrumental in ensuring equitable policy decisions in the postpandemic period.
Supplementary Material
Footnotes
This study was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institute of Health (NIH) (5U01HD110062-03).
The authors declare no conflict of interest.
Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal's website, www.lww-medicalcare.com.
Contributor Information
Anirban Chatterjee, Email: anirbanc@email.sc.edu.
Xuzhuo Zhao, Email: xuzhuo@email.sc.edu.
Jihong Liu, Email: jliu@mailbox.sc.edu.
Berry A. Campbell, Email: berry.campbell@prismahealth.org.
Jiani Yu, Email: jiy4002@med.cornell.edu.
Nansi S. Boghossian, Email: nboghoss@email.sc.edu.
Bo Cai, Email: bocai@mailbox.sc.edu.
Xiaoming Li, Email: xiaoming@mailbox.sc.edu.
Peiyin Hung, Email: hungp@mailbox.sc.edu.
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