The impact of the COVID-19 pandemic on maternal healthcare costs in a UK inner-city multi-ethnic population

The impact of the COVID-19 pandemic on maternal healthcare costs in a UK inner-city multi-ethnic population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of the COVID-19 pandemic on maternal healthcare costs in a UK inner-city multi-ethnic population Alice McGreevy, Marina Soley-Bori, Florence Tydeman, Kathryn Dalrymple, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5544062/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : During the COVID-19 pandemic, maternity care reconfigurations disrupted in-person care, which shifted towards virtual care and self-monitoring. We assessed the impact of these changes on healthcare costs. Methods : Data from October 2018 to April 2023 were used from the population-based early-LIfe data cross-LInkage in Research-Born-in-South London (eLIXIR-BiSL) platform linking maternity, neonatal, and mental healthcare data from three National Health Service (NHS) hospitals in South London, United Kingdom. Pregnancy costs were generated from the NHS perspective, using national unit costs and individual-level use of maternity, mental health, and primary care services. Interrupted time series analysis estimated the pandemic impact on monthly mother-newborn costs over time. Cross-sectional pre-pregnancy cost models isolated the impact of virtual care, and gestational diabetes (GDM) self-monitoring using the GDm-Health app. Findings : Among 36,895 pregnancies, the monthly cost trendline level dropped by 4% (£38, 95% confidence interval: [£10-65]), during the first pandemic lockdown, and by £72 [36-108], when lockdowns were lifted. However, the pre-pandemic upward trendline slope of costs was unchanged (£0.46 [-2.93 to 3.84]). Monthly costs increased with first lockdown for Black (£103 [26-181]) and Asian women (£128 [38-218]) and increased more slowly during post-lockdown (-£12 [-23 to -2]), for Asian women, remaining higher throughout the pandemic for Black and Asian women. A 1% increase in virtual care was associated with a £7 [3-10] increase in maternity costs. GDM self-monitoring via GDm-Health was cost-neutral (£140 [-68 to 348]). Interpretation : The pandemic was associated with temporary reductions in maternity costs due to lower healthcare utilisation. Ongoing, rising maternity costs were unchanged. The pandemic had differential effects on Black and Asian women compared to White. Further research is needed into clinical outcomes of virtual care (associated with higher costs) and use of GDm-Health (cost-neutral). Funding : National Institute for Health Research (NIHR134293), Medical Research Council (MR/P003060/1, MR/X009742/1). Maternity care Covid-19 interrupted series analysis maternity care costs Figures Figure 1 Panel: Putting research into context Evidence before this study The COVID-19 pandemic triggered rapid changes in maternity care delivery, including use of virtual care and self-monitoring. To inform policy about future maternity care and health system shocks, the impact of service reconfigurations on healthcare outcomes and costs required careful evaluation. Before undertaking this study, we performed a PubMed search to identify studies assessing the impact of the pandemic on maternity care costs. Search terms included variations of maternity care, virtual care, self-monitoring, healthcare costs and utilisation, Great Britain, National Health Service and COVID-19; the search retrieved 312 items as of 6 June 2023, of which there were 12 studies and one systematic literature review of interest. Existing UK evidence on the association of virtual care and self-monitoring with maternity costs was scarce and inconclusive. Published studies based on small sample sizes suggest that virtual care reduces healthcare use and self-monitoring is cost-neutral, but well-powered studies are needed to confirm these findings. Understanding the overall impact of the pandemic on maternity care costs, along with the specific effects of virtual care and self-monitoring, is particularly urgent in the current context of increasingly constrained health budgets globally and to prepare for future health system shocks. Added value of this study In this analysis of maternal and newborn costs for more than 35,000 ethnically-diverse pregnancies, with birth from October 2018 to April 2023, we found that the COVID-19 pandemic led to an overall decrease in pregnancy costs, associated with a drop in healthcare utilisation. The drop in costs occurred at the onset of pandemic lockdowns, and again when all lockdowns were lifted, but there was no change in the rate of rise of costs over time within either pandemic period (i.e., with or without lockdowns). The use of virtual care was associated with an increase in pregnancy costs. For women with GDM, self-monitoring through the GDm-Health app had no significant impact on pregnancy costs. Implications of the available evidence Overall, the COVID-19 pandemic caused only a temporary reduction in maternity care costs. Virtual care was associated with increased costs, while GDM self-monitoring was cost neutral. The impact on health outcomes of both virtual care and self-monitoring is needed to complement these findings and inform future health policy. Introduction The COVID-19 pandemic had profound consequences for healthcare services, including maternity care 1 , 2 . Some midwifery units closed or merged, and staffing shortages affected the available skill mix 3 . Perceived risk of infection led to hesitation in seeking healthcare, 4 and there were reductions in routine 5 and unscheduled 6 antenatal care visits, prolonged maternal length of stay, and more maternal readmissions to hospital 7 . However, most data is from the first pandemic year (to February 2021), during lockdowns, and unadjusted for pre-existing trends; thus, the impact of the pandemic overall on maternity costs over time remains largely unexplored. During the pandemic in the United Kingdom (UK), the Royal College of Obstetricians & Gynaecologists advised expansion of ‘virtual care’ (also known as ‘remote consultation’, ‘telehealth’, or ‘eHealth’) while ensuring at least six face-to-face antenatal visits 8 . By July 2020, most UK maternity units had adopted virtual care in varying intensities 3 . No impact of virtual care on outcomes was reported in an interrupted time series analysis from Australia 9 , but extensive international qualitative data indicate that most women were less satisfied and less reassured by virtual (vs. face-to-face) care, resulting in further health care utilisation and potentially increased healthcare costs 10 , 11 . Also, there were concerns that the pandemic exacerbated inequalities when virtual care is offered to digitally-disadvantaged groups 12 . Existing studies of virtual care impact on UK maternity healthcare costs are scarce and inconclusive, highlighted by a systematic review of telemedicine among pregnant women with diabetes 13 . While subsequent studies of general 14 and diabetes-specific 15 pre/peripartum populations reported lower healthcare use with virtual care, results were based on small sample sizes (75 and 63 patients, respectively) and healthcare costs for mothers and newborns were not assessed. The pandemic also saw rapid adoption of the GDm-Health app for gestational diabetes mellitus (GDM) care in the UK 16 . The app records remotely measured blood glucose levels with real-time review by healthcare-providers, facilitating rapid provider-patient communication 17 . This contrasts to alternative to the traditional written ‘sugar diary’ record discussed retrospectively at face-to-face appointments. Studies of the GDm-Health app show positive impacts on pregnancy outcomes when GDM self-monitoring is part of a care package 18 , without incurring greater costs 17 , acknowledging the small size of studies to date. We assessed: (i) the overall impact of the COVID-19 pandemic on monthly trajectory costs for maternity and newborn care, from October 2018 to April 2023; (ii) the impact of virtual care and GDm-Health app use on pregnancy costs; and (iii) whether costs differed across sociodemographic groups. Methods Study design and setting In a longitudinal study design, monthly electronic health record data from the early-LIfe data cross-LInkage in Research–Born-in-South London (eLIXIR-BiSL) data linkage cohort were assessed. The dataset comprises routine maternity and neonatal health records of pregnant women accessing care via Guy’s and St Thomas’ Hospital National Health Service [NHS] Foundation Trust and King’s College Hospital NHS Foundation Trust, linked to mental health (South London and Maudsley NHS Foundation Trust) and primary care data (Lambeth DataNet). These hospitals in inner-city boroughs in South London, UK, serve an urban, largely deprived, multi-ethnic population. Details for eLXIR-BiSL have been published previously 19 . The study sample includes women registering for maternity care between October 2018 (eLIXIR-BiSL cohort initiation) and April 2023, with antenatal registration and birth information. Study epochs are defined as ‘pre-pandemic’ (October 2018 to February 2020), ‘pandemic lockdowns’ (March 2020 to June 2021), and ‘post-lockdown’ (July 2021 to April 2023). March 2020 was when the UK healthcare system’s response began and the first national lockdown was implemented. Data variables and measurement Pregnancy costs were generated from the NHS perspective, based on individual-level health service use and 2021-22 national unit costs ( Box S1 ), with the NHS Cost Inflation Index used to adjust for inflation 20 . Maternity services, mental healthcare, and primary care utilisation were included, from antenatal registration appointment to six weeks postpartum. Maternity services captured routine antenatal appointments, maternity assessment unit visits, birth and other inpatient stays, and postnatal reviews. Mental health services included ‘Talking therapies’ (for depression or anxiety), secondary mental health services ‘community contacts’, and inpatient stays. Primary care costs reflect primary care consultations and were available for 32% of individuals in our sample (limited to general practice in Lambeth borough). Neonatal costs were included across relevant services (inpatient stays, postnatal reviews and primary care). Total pregnancy costs are aggregated for analyses at the monthly mother-newborn level. Statistical methods Maternal characteristics and healthcare utilisation and costs were compared via descriptive statistics across pre-pandemic, pandemic lockdowns, and post-lockdown periods, with differences assessed using t-tests or Mann–Whitney U-tests for continuous variables, and Pearson Chi-Squared tests for categorical variables. Model 1: Effect of the COVID-19 pandemic on monthly pregnancy costs Interrupted time series (ITS) analysis was used to predict the effect of the pandemic on monthly pregnancy costs, comparing with pre-pandemic costs and differentiating between lockdown and post-lockdown periods. Pregnancy-month is the unit of analysis. Interaction terms considered both a change in level (immediate effect) and slope (gradual effect) of the cost trendline, from lockdown impositions (March 2020) to lifting (July 2021). Models adjusted for seasonality and autocorrelation, as well as ethnicity and the percentage of deliveries, each of which changed over time ( Box S2 and Figures S1-S4 ). Model 2: Impact of virtual antenatal care on maternity costs In this cross-sectional model, the dependent variable was total cost per pregnancy, summing all monthly costs from antenatal registration to six weeks postpartum. The independent variable was ‘Virtual care percentage’, capturing the percentage of antenatal care delivered virtually, by telephone or video. To avoid the virtual care estimate capturing the effect of pandemic lockdowns, a control is included for the percentage of care that occurred from March 2020 to June 2021. Other control variables were maternal age (years), ethnicity (Black/Asian/Mixed/Other/Missing), difficulty speaking English (yes/no), socioeconomic deprivation (Index of Multiple Deprivation [IMD] in quintiles), multiple birth (yes/no), gestational age at booking (weeks), smoking status (yes/no), and antenatal care plan type (i.e., ‘Midwife only’, ‘Shared midwife and obstetrician’ (75/25 split), or ‘Obstetrician only’, as granular information on the type of provider who delivered care at each antenatal appointment was not available), GDM, one/more other health conditions (i.e., GDM, other physical or mental health conditions) recorded at antenatal registration (by organ system, see Box S3 ), and the hospital providing care. The choice of independent variables was guided by Andersen’s revised conceptual framework of healthcare utilisation, by which use of health services is determined by predisposing factors, enabling factors, and need 21 . Model 3: Effect of GDm-Health app self-monitoring on maternity costs The last analysis was restricted to women with GDM. The dependent variable was total cost per pregnancy. The independent variable was ‘App-User’, (dichotomised by app registration status [1 = yes, 0 = no]). As women may have initially registered, but stopped using it, a sensitivity analysis was run with the definition of ‘App-User’ to those who recorded sufficient blood glucose readings to be clinically meaningful ( Box S4 ). An app cost of £8 per pregnancy was added to total cost per pregnancy for app-users, based on payment made by each hospital for app access, and the number of individuals in our sample. The same control variables are used as in Model 2 (above). Across all models, to assess inequalities in the impact of the pandemic on maternity care costs across minority groups and individuals with medical complexity, subgroup analyses are presented, examining: ethnicity, IMD, difficulty speaking English, GDM, and mental health problems. Interactions are added between each subgroup variable and the key terms of interest (i.e., change in trendline level, change in trendline slope, and independent variables of virtual care and GDm-Health app use). Missing data were kept as missing except for primary care utilisation, for which multiple imputation via chained equations (MICE) 22 was performed ( Box S5, Figure S5 and Table S3 ). Sensitivity analyses explore the impact of multiple imputation of primary care costs (by excluding primary care costs from total costs), considering July 2021 in the pandemic lockdowns period (rather than in post-lockdown), and changing the definition of ‘Shared midwife and obstetrician’ antenatal care from a 75/25 to 90/10 split. Goodness of fit measures are used to identify the most appropriate estimation method for each of Models 1 to 3: an ordinary least squares model (OLS) or a generalised linear model (GLM) with a gamma distribution and log link. All analyses were conducted using R version 4.3.0. Results Our sample size was 36,985 pregnancies, across pre-pandemic (N = 13,284), pandemic lockdowns (N = 11,470), and post-lockdown pandemic (N = 12,231) periods. Pre-pandemic, women were on average aged 33 years, half were of White ethnicity, relatively deprived (60% in the two most deprived IMD quintiles), and with English as primary language in 70% (Table 1 ). Ten percent developed GDM, and many had a record at the booking appointment of at least one physical (41%) or mental (22%) health condition. Maternal characteristics remained stable during pandemic lockdowns and post-lockdown, albeit with slight, statistically significant, increases in: age, the percentage of individuals of non-White ethnicity, those with missing IMD, GDM, and physical or mental health conditions. Table 1 Maternal characteristics in the pre-pandemic, pandemic (with lockdowns), and post-pandemic (without lockdowns) periods Pre-pandemic Pandemic with lockdowns p-value Pandemic without lockdowns p-value N = 13,284 N = 11,470 N = 12,231 Age (years) 32.63 32.80 0.048 32.82 0.024 Ethnicity (%) < 0.001 < 0.001 White 50.12 52.03 48.43 Black 19.72 20.63 21.37 Asian 8.36 9.85 10.91 Mixed 4.43 5.24 5.96 Other 6.50 7.99 6.36 Missing 10.87 4.26 6.96 IMD 0.2 < 0.001 Quintile 1 (most deprived) 19.11 19.22 20.01 Quintile 2 41.41 41.15 40.32 Quintile 3 25.38 24.83 23.52 Quintile 4 9.21 9.26 9.55 Quintile 5 (least deprived) 3.62 3.92 4.16 Missing 1.28 1.62 2.44 % of English speakers 69.56 70.28 0.2 69.59 > 0.9 % Difficulty speaking English 6.94 6.82 0.7 7.28 0.30 % with GDM 10.19 13.49 < 0.001 13.05 < 0.001 % with a physical health condition 40.95 45.25 < 0.001 47.96 < 0.001 % with a mental health condition 21.67 24.90 < 0.001 27.08 < 0.001 Notes: IMD: Index of Multiple Deprivation. GDM: Gestational Diabetes Mellitus. pandemic (without lockdowns) periods Costs per pregnancy Pre-pandemic, the distribution of total cost per pregnancy was right-skewed, with a mean of £7,625 (standard deviation [SD] = 2,668) and median of £7,118 (interquartile range [IQR]=£5,625-£9,085) (Table 2 ). Total costs were driven primarily by delivery costs (~ 60%, £4,734, SD = 1,781), followed by routine antenatal costs (~ 20%, £1,344, SD = 775), with much smaller contributions from primary care (mean of £154 per pregnancy, SD = 128) and mental healthcare (mean of £28, SD = 593). The composition of total costs remained stable across the pandemic, with or without lockdowns ( Figure S6 ). Table 2 Mean total mother-newborn pregnancy costs (SD) in the pre-pandemic, pandemic (with lockdowns), and post-pandemic (without lockdowns) periods Pre-pandemic Pandemic with lockdowns 1 Pandemic without lockdowns 2 N = 13,284 N = 11,470 N = 10,233 Total pregnancy costs £7,624.54 (2,668.05) £7,932.20 (2,833.68) *** £8,095.86 (2,799.60)*** Total maternity services costs £7,442.85 (2,577.67) £7,704.72 (2,548.21) *** £7,860.91 (2,657.19)*** Routine antenatal £1,344.45 (775.10) £1,571.02 (710.41) *** £1,557.70 (743.36)*** Maternity assessment unit £341.03 (321.70) £373.94 (349.37) *** £427.37 (411.22)*** Inpatient stay £248.21 (634.64) £282.59 (674.05) *** £313.75 (775.25)*** Delivery £4,734.06 (1,781.55) £4,810.31 (1,791.18) *** £4,976.29 (1,855.58) *** Post-natal review £775.10 (573.65) £666.87 (590.31) *** £585.80 (553.61) *** Total primary care costs £153.91 (128.06) £171.50 (156.12) *** £199.86 (172.69) *** Total mental health services costs £27.79 (593.21) £55.98 (1,156.36) ** £35.10 (789.80) *** Talking therapy £7.58 (59.07) £11.07 (77.23) *** £9.15 (64.54) *** Community contacts £9.33 (87.94) £14.50 (139.36) £13.41 (115.95) *** Inpatient stay costs £10.87 (572.28) £30.41 (1,093.15) £12.55 (751.45) Notes: 1 The stars indicate statistical significance corresponding to the t-tests (Mann–Whitney U) comparing mean costs during the pandemic with lockdowns to pre-pandemic. 2 The stars indicate statistical significance corresponding to the t-tests (Mann–Whitney U) comparing mean costs during the pandemic without lockdowns to pre-pandemic. *** <0.001; ** <0.01; * <0.05. Over the pandemic, mean total cost per pregnancy grew, to £7,932 (SD = 2,833) during pandemic lockdowns and £8,096 (SD = 2,799) post-lockdown (Table 2 ). All cost components increased, except for progressive declines in routine postnatal review costs (from £775 pre-pandemic, to £667 during pandemic lockdowns, and £586 post-lockdown). Mean mental health costs showed the largest relative pandemic increase, from £28 pre-pandemic, to £56 during pandemic lockdowns and £35 post-lockdown. Similar fluctuations in healthcare utilisation were observed across the study period ( Table S4 ). There was a sharp increase in use of virtual care during pandemic lockdowns compared with pre-pandemic use ( Figure S7 ). While in February 2020 only 2% of routine antenatal care was virtual, this peaked at 18% in June 2020. Thereafter, virtual antenatal care declined progressively through pandemic lockdowns to 7% by June 2021 (resulting in an average monthly proportion of virtual care during the lockdowns of 12.3%), and reaching 5% by the end of post-lockdown (April 2023). Overall, 4,399/35,985 (12%) of pregnancies were complicated by GDM, of which 3,215 (75%) were registered on the GDm-Health app ( Table S5 ). Main Results Model 1: Effect of the COVID-19 pandemic on monthly pregnancy costs According to the ITS model, in the initial months of pandemic lockdowns, monthly pregnancy costs (blue line, Fig. 1 ) were lower than they would have been if the pandemic had not occurred (dotted red line, Fig. 1 ). Compared with pre-pandemic, the level of the monthly cost trendline dropped by £38 (95% CI: 10–65) with the onset of pandemic lockdowns (equivalent to 4% of monthly pregnancy costs), and by £72 (36–108) with the onset of post-lockdown (Table 3 ). However, there were no statistically significant changes to the cost trendline slopes. In March 2020, monthly pregnancy costs were 3% lower (£991) than the counterfactual if the pandemic had not occurred (£1,024) ( Table S6 ). Table 3 Parameter estimates from the ITS model assessing the impact of the pandemic on monthly pregnancy costs Control Parameter estimate 95% CI Constant 147.64 *** (124.35, 170.93) Time 3.56 * (0.30, 6.83) Pandemic lockdowns - change in level -37.66 ** (-65.07, -10.25) Pandemic lockdowns - change in slope 0.46 (-2.93, 3.84) Post lockdown - change in level -72.05 *** (-107.95, -36.16) Post lockdown - change in slope 0.87 (-2.42, 4.17) Delivery 5,659.46 *** (5,636.88, 5,682.04) Ethnicity Black 52.11 *** (42.36, 61.85) Asian 33.71 *** (22.38, 45.04) Mixed 2.64 (-11.57, 16.84) Other 16.43 * (2.19, 30.68) Missing -40.80 *** (-55.22, -26.38) Notes: *p < 0.05; **p < 0.01; ***p < 0.001. Model also controls for month, hospital and lagged residuals. Reference group for ethnicity is "White" and changes in level and slope are compared to the pre-pandemic period. Subgroup analyses found a differential effect of monthly pregnancy costs over time, by ethnicity ( Tables S7-8 and Figure S8 ). While mean costs among White ethnicity women dropped in level by £74 (95% CI: -£38 to -£109) at the start of pandemic lockdowns, costs for Black ethnicity women increased in level by £30 (for a difference vs. White ethnicity women of +£103, CI: 26–181) and costs for Asian ethnicity women grew by £54 (for a difference of +£128, CI: 38–218). Thereafter, costs for Black and Asian (vs. White) ethnicity women grew more slowly during the pandemic (by -£10 and -£16 per month, respectively, vs. +£4 for White ethnicity women), but those costs for Black and Asian (vs. White) ethnicity women remained higher throughout the pandemic ( Figure S8 ). There was less variation in costs post-lockdown, with the only difference being for women of Asian ethnicity, who had a £12 slower monthly trend. Model 2: Impact of virtual antenatal care on maternity costs In this cross-sectional model, women with a higher proportion of virtual antenatal care had higher pregnancy costs, with a 1% point increase in virtual care associated with a £7 (95% CI: 3–10) increase in costs (Table 4 ). As the average monthly proportion of virtual care during pandemic lockdowns was 12.3%, compared with 1.9% pre-pandemic (a 10.4% difference), this represents a £73 increase in cost per pregnancy during pandemic lockdowns. Assuming that all of the 11,470 pregnancies during pandemic lockdowns received 12.3% of their antenatal care virtually, the NHS incurred £837,310 (£73 x 11,470) additional costs compared with pre-pandemic use of virtual care). Table 4 Parameter estimates from the cross-sectional models assessing the impact of virtual care and self-monitoring via the GDm-Health app on costs per pregnancy Control Parameter estimate 95% CI Parameter estimate 95% CI Virtual care 6.92 *** (3.49, 10.35) - Self-monitoring 139.73 (-68.49, 347.95) Proportion of care during the pandemic -200.14 (-569.15, 168.86) -746.06 (-1,948.91, 456.80) Age (years) 12.24 *** (7.27, 17.21) 23.14 ** (8.61, 37.67) Ethnicity Black 302.33 *** (226.48, 378.18) 369.81 *** (175.61, 564.02) Asian 222.91 *** (138.60, 307.21) 62.90 (-135.95, 261.76) Mixed 63.27 (-46.46, 172.99) 17.57 (-337.27, 372.40) Other 144.99 ** (40.72, 249.26) 53.59 (-206.81, 314.00) Missing -243.46 *** (-332.54, -154.39) -196.11 (-565.34, 173.13) IMD Quintile 2 -62.95 (-135.58, 9.68) -84.08 (-278.38, 110.23) Quintile 3 -101.66 * (-179.69, -23.62) -42.63 (-265.66, 180.39) Quintile 4 -102.54 * (-202.57, -2.51) -121.56 (-425.70, 182.57) Quintile 5 (Least deprived) -98.62 (-229.47, 32.23) -290.64 (-666.53, 85.25) Missing -105.40 (-333.46, 122.66) 174.64 (-680.17, 1,029.45) Smoking status Smoker -7.16 (-148.23, 133.91) 4.96 (-479.15, 489.07) Smoking status missing 67.08 (-74.79, 208.94) -4.33 (-383.82, 375.16) Antenatal care type Shared 735.79 *** (680.15, 791.42) 799.68 *** (606.96, 992.41) Obstetrician only 1,470.96 *** (1,209.05, 1,732.87) 2,794.53 *** (1,889.53, 3,699.52) Missing 318.00 (-39.87, 675.88) 1465.98 (-317.37, 3,249.33) Multiple births 7,655.76 *** (7,387.55, 7,923.96) 7,671.23 *** (7,096.10, 8,246.36) Difficulty speaking English -0.59 (-57.00, 55.82) 25.63 (-131.99, 183.25) Physical condition 451.56 *** (398.95, 504.16) 523.34 *** (368.99, 677.70) Mental health condition 393.68 *** (328.55, 458.82) 560.81 *** (364.92, 756.70) GDM 726.84 *** (648.03, 805.66) - Gestation at booking (weeks) -57.89 *** (-61.49, -54.29) -57.89 *** (-70.80, -44.97) Constant 6,345.05 *** (6,117.46, 6,572.63) 6,172.56 *** (5,449.89, 6,895.23) Notes: *p < 0.05; **p < 0.01; ***p < 0.001. Two separate cost models were estimated, one assessing the impact of virtual care and the other the impact of self-monitoring. IMD = Index of Multiple Deprivation. GDM = Gestational Diabetes Mellitus. Model also controls for month of booking appointment and hospital. Reference group for ethnicity is "White", and reference group for antenatal care type is "Midwife only" care. Multiple births, difficulty speaking English, physical condition, mental health condition and GDM are all yes/no variables, with “no” as the reference category. Table 5 Parameter estimates from the cross-sectional model assessing the impact on costs per pregnancy of self-monitoring via the GDm-Health app Control Parameter estimate 95% CI Self-monitoring 139.73 (-68.49, 347.95) Proportion of care during pandemic lockdowns -746.06 (-1,948.91, 456.80) Age 23.14 ** (8.61, 37.67) Ethnicity Black 369.81 *** (175.61, 564.02) Asian 62.90 (-135.95, 261.76) Mixed 17.57 (-337.27, 372.40) Other 53.59 (-206.81, 314.00) Missing -196.11 (-565.34, 173.13) IMD Quintile 2 -84.08 (-278.38, 110.23) Quintile 3 -42.63 (-265.66, 180.39) Quintile 4 -121.56 (-425.70, 182.57) Quintile 5 (Least deprived) -290.64 (-666.53, 85.25) Missing 174.64 (-680.17, 1,029.45) Smoking status Smoker 4.96 (-479.15, 489.07) Smoking status missing -4.33 (-383.82, 375.16) Antenatal care type Shared 799.68 *** (606.96, 992.41) Obstetrician only 2,794.53 *** (1,889.53, 3,699.52) Missing 1465.98 (-317.37, 3,249.33) Multiple births 7,671.23 *** (7,096.10, 8,246.36) Difficulty speaking English 25.63 (-131.99, 183.25) Physical condition 523.34 *** (368.99, 677.70) Mental health condition 560.81 *** (364.92, 756.70) Gestation at booking (weeks) -57.89 *** (-70.80, -44.97) Constant 6,172.56 *** (5,449.89, 6,895.23) Note: *p < 0.05; **p < 0.01; ***p < 0.001. IMD = Index of Multiple Deprivation. GDM = Gestational Diabetes Mellitus. Model also contains control for month of booking appointment and hospital. Reference group for ethnicity is "White", and reference group for antenatal care type is "Midwife only" care. Multiple births, difficulty speaking English, physical condition, mental health condition and GDM are all yes/no variables, with “no” as the reference category. Model 3: Effect of GDm-Health app self-monitoring on maternity costs Among women with GDM, there were no differences in total costs per pregnancy between those who registered on the GDm-Health app and those who did not (Table 4 ). Also, there was no difference in costs in the sensitivity analysis that compared costs for those who showed clinically-relevant app use (vs. those who did not; analyses available upon request). In both Models 2 and 3, no differential impacts on cost per pregnancy were found for virtual care ( Table S9 ) or GDM app registration ( Table S10 ), across ethnic groups, IMD quintiles, difficulty speaking English, or mental health status. All models were estimated using OLS, as it showed slightly better goodness of fit than a GLM model with the log link and the gamma distribution ( Table S11 ). The GLM log link and gamma distribution model yielded comparable parameter estimates to OLS across the three models (results available upon request). Sensitivity analyses supported the stability of our results, with similar findings: after exclusion of primary care costs, with a change in the proportion of midwifery/obstetrician care in a shared care model, or after considering July 2021 as part of pandemic lockdowns (rather than post-lockdown) ( Table S12-S14 ). Discussion Summary The COVID-19 pandemic led to a drop from pre-pandemic values in maternity costs at the onset of pandemic lockdowns, and again post-lockdown when all restrictions were lifted, but there was no change in the rate of rise of costs over time within either pandemic period (with or without lockdowns). Importantly, our findings suggest that the pandemic affected minority ethnic women differently; compared with White ethnicity women, those of Black or Asian ethnicity experienced an increase (not decrease) in costs at the start of pandemic lockdowns, and their costs rose more slowly during pandemic lockdowns, with that trend continuing for Asian ethnicity women during post-lockdown. Descriptive analyses of costs per pregnancy (resulting from aggregating monthly pregnancy costs for each woman over the duration of their pregnancy) suggest that a pregnancy was more expensive for the NHS during the pandemic than before, with (by an average of £307), or without lockdowns (by £471). However, this pattern reflects a pre-pandemic trend of rising pregnancy costs that continued at the same rate during the pandemic, and so the higher costs cannot be attributed to the pandemic per se . 1170 In additional analyses, use of virtual care was associated with an increase in pregnancy costs. However, for women with GDM, self-monitoring through the GDm-Health app had no significant impact on pregnancy costs. There was no evidence of a differential impact of the pandemic on these costs according to ethnicity. Comparison with the literature To our knowledge, this is the first study assessing the impact of the COVID-19 pandemic on maternity costs, covering the entire pandemic period and differentiating between overall trends in monthly pregnancy costs and costs per pregnancy. Our ITS results predicting lower monthly pregnancy costs during the pandemic align with previous literature reporting decreased healthcare utilisation in maternity services during the pandemic 7 , 23 . This has been attributed to women’s hesitancy to seek care during the pandemic, due to fears of infection or staff shortages restricting access to care 3 , 4 , 24 , 25 . The decrease in monthly pregnancy costs occurred with the onset of pandemic lockdowns and their withdrawal, without ongoing change in the previous rate of rise in monthly pregnancy costs. Whereas an increase might have been anticipated with release of lockdowns, we saw another decrease in monthly pregnancy costs. A potential explanation may be continued fear of infection from contacts with the healthcare system, particularly as maternity services were still cautious 26 . Also, the post-lockdown reduction in use of virtual care – which we had found to be more expensive than standard care – may have contributed. Thereafter, and in common with the pandemic with lockdowns, there was no ongoing change in the rate of rise in monthly pregnancy costs. Importantly, we found some evidence that the pandemic affected minority ethnic groups differently than White ethnicity women. A previous population-based study using routinely-collected data from England reported that individuals of ethnicities other than White (vs. White) were associated with slightly higher rates of preterm birth and Caesareans, and lower unassisted vaginal birth 7 . Our results suggest that women of Black and Asian (vs. White) ethnicities experienced an initial increase in maternity costs at the onset of pandemic lockdowns, and a slower rise thereafter, but still resulting in overall higher costs during pandemic lockdowns. Higher costs for women of Black and Asian (vs. White) ethnicities could have resulted from these minority ethnic groups being at higher risk of severe COVID-19 illness, and having a disproportionally higher number of hospital admissions during their pregnancy 27 . The cost component with the largest relative increase over the study period was mental health services, although they made up a small fraction (0.5%) of overall pregnancy and postpartum costs. This finding aligns with previous literature reporting worsening of women’s mental health during pandemic pregnancy; reasons cited have included disruption of service delivery, uncertainty about the effects of COVID-19 on pregnancy, and birth partners being excluded from some elements of pregnancy care and delivery 4 , 28 , 29 . Postnatal reviews were the only cost component of maternity care that decreased over time, which aligns with surveys that found that care after birth was particularly impacted by the pandemic, and women’s reports that they received less postnatal support 30 . While virtual care is generally considered less expensive than face-to-face care, our findings are that virtual antenatal care is associated with higher pregnancy costs, suggesting virtual (vs. face-to-face), appointments may result in further healthcare use due to poorer quality of care or outcomes 4 . Existing comparable literature is limited. Our results contradict two previous studies which found virtual care in maternity care to be associated with lower healthcare use 14 , 15 ; each study had a small sample size (75 and 63 patients), and only one addressed virtual care in general; the others was focused on virtual care for GDM. Given the importance of understanding the full impact of virtual care in maternity services, further quantitative studies of the healthcare costs of virtual care are warranted. Finally, this study complements previous research on the positive impacts of GDM self-monitoring using GDm-Health 17 , 18 , by finding it is cost-neutral compared with the traditional, non-digital health approach. Our findings add to the scarce cost evidence base in this area. Strengths and Limitations Strengths of our work include an ethnically- and socioeconomically-diverse study population. Comprehensive ethnicity data allowed for assessment of ethnic inequalities when examining the impact of the pandemic on maternity care costs. Total costs captured healthcare use, for mothers, as well as newborns. Maternity services assessed included mental health and primary care, to provide a more holistic view of healthcare needs during pregnancy and postpartum. Some limitations should be acknowledged. Total costs were computed from the NHS perspective and did not capture social care costs and patient out-of-pocket expenses, which may have been substantial during pandemic lockdowns and the subsequent cost-of-living crisis. Primary care use was available for only 32% of women, who were registered to a GP practice in the borough of Lambeth; despite this, missing values were imputed, and our sensitivity analyses removing primary care from total costs did not affect the main results. While granular information was not available on the type of provider who delivered care at each antenatal appointment, in sensitivity analyses, our results were robust to assumptions about the proportion of care provided by midwives and obstetricians. Last, ITS is a quasi-experimental design with limited ability to assign causality to pandemic effects detected in this study; the possibility of residual confounding cannot be ruled out. Conclusions Maternity care costs declined in association with the COVID-19 pandemic, with onset of pandemic lockdowns and then with lifting of all restrictions; however, there was no effect on the trend of rising costs seen pre-pandemic, despite the most severe public health crisis in the last century. Of importance for planning future maternity services, is our findings that virtual antenatal care appears to be more expensive than face-to-face care, and the cost-neutral nature of digital technology to support GDM self-monitoring of glycaemic control. Further research on the effects of virtual care and GDm-Health use on clinical outcomes is needed to inform future guidelines on antenatal care delivery, especially during health system shocks. Declarations Contributors statement: Alice McGreevy: Conceptualization, Methodology, Software, Validation, Formal analysis, Writing - Original Draft, Writing - Review & Editing. Marina Soley-Bori: Conceptualization, Methodology, Validation, Formal analysis, Writing - Original Draft, Writing - Review & Editing, Supervision, Funding acquisition. Florence Tydeman : Methodology, Software, Validation, Writing - Review & Editing. Kathryn Dalrymple: Writing - Review & Editing, Validation, Software . Sara White: Writing - Review & Editing, Funding acquisition. Asma Khalil: Writing - Review & Editing, Funding acquisition. Lucilla Poston : Writing - Review & Editing, Funding acquisition. Emma Duncan: Writing - Review & Editing, Funding acquisition Tisha Dasgupta : Writing - Review & Editing., Hiten D. Mistry : Writing - Review & Editing. Julia Fox-Rushby: Conceptualization, Methodology, Resources, Writing - Review & Editing, Supervision, Funding acquisition. Peter von Dadelszen : Writing - Review & Editing, Funding acquisition. Laura A. Magee: Conceptualization, Methodology, Resources, Writing - Review & Editing, Supervision, Funding acquisition. Declaration of Interests: This study represents independent research funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Acknowledgement statement : We wish to thank the women, their infants, and families from all participating sites for sharing their data and supporting the eLIXIR-BiSL programme. Ethnics approval: The Early Life Cross Linkage in Research, Born in South London (eLIXIR-BiSL) Partnership has received ethical approval from the Oxfordshire Research Ethics Committee C (23/SC/0116) as an anonymised dataset for medical research. Data sharing: The data accessed by eLIXIR remain within an NHS firewall and governance is provided by the eLIXIR Oversight Committee reporting to relevant information governance clinical leads. Subject to these conditions, data access is encouraged and those interested should contact the eLIXIR Chief Investigator (Professor Lucilla Poston; [email protected] ). References BMA. COVID-19: Impact of the pandemic on healthcare delivery. The British Medical Association is the trade union and professional body for doctors in the UK. 2023. Accessed April 24, 2024. https://www.bma.org.uk/advice-and-support/covid-19/what-the-bma-is-doing/covid-19-impact-of-the-pandemic-on-healthcare-delivery WHO. The Impact of COVID-19 on Health and Care Workers: A Closer Look at Deaths .; 2021. https://iris.who.int/bitstream/handle/10665/345300/WHO-HWF-WorkingPaper-2021.1-eng.pdf?sequence=1&isAllowed=y Brigante L, Morelli A, Jokinen M, Plachcinski R, Rowe R. Impact of the COVID-19 pandemic on midwifery-led service provision in the United Kingdom in 2020-21: Findings of three national surveys. Midwifery . 2022;112:103390. doi:10.1016/j.midw.2022.103390 Flaherty SJ, Delaney H, Matvienko-Sikar K, Smith V. Maternity care during COVID-19: a qualitative evidence synthesis of women’s and maternity care providers’ views and experiences. BMC Pregnancy Childbirth . 2022;22(1):438. doi:10.1186/s12884-022-04724-w NICE. Rationale and impact | Antenatal care | Guidance | NICE. August 19, 2021. Accessed April 29, 2024. https://www.nice.org.uk/guidance/ng201/chapter/Rationale-and-impact#antenatal-appointments-2 Khalil A, Von Dadelszen P, Kalafat E, et al. Change in obstetric attendance and activities during the COVID-19 pandemic. The Lancet Infectious Diseases . 2021;21(5):e115. doi:10.1016/S1473-3099(20)30779-9 Gurol-Urganci I, Waite L, Webster K, et al. Obstetric interventions and pregnancy outcomes during the COVID-19 pandemic in England: A nationwide cohort study. PLOS Medicine . 2022;19(1):e1003884. doi:10.1371/journal.pmed.1003884 RCOG. Guidance for Antenatal and Postnatal Services in the Evolving Coronavirus (COVID-19) Pandemic .; 2020. https://www.rcm.org.uk/media/4132/2020-06-18-guidance-for-antenatal-and-postnatal-services-in-the-evolving-coronavirus-covid-19-pandemic.pdf Thirugnanasundralingam K, Davies-Tuck M, Rolnik DL, et al. Effect of telehealth-integrated antenatal care on pregnancy outcomes in Australia: an interrupted time-series analysis. The Lancet Digital Health . 2023;5(11):e798-e811. doi:10.1016/S2589-7500(23)00151-6 Davis A, Bradley D. Telemedicine utilization and perceived quality of virtual care among pregnant and postpartum women during the COVID-19 pandemic. J Telemed Telecare . Published online November 17, 2022:1357633X221133862. doi:10.1177/1357633X221133862 Stacey T, Darwin Z, Keely A, Smith A, Farmer D, Heighway K. Experiences of maternity care during the COVID-19 pandemic in the North of England. British Journal of Midwifery . 2021;29(9):516-523. doi:10.12968/bjom.2021.29.9.516 Khilnani A, Schulz J, Robinson L. The COVID-19 pandemic: new concerns and connections between eHealth and digital inequalities. Journal of Information, Communication and Ethics in Society . 2020;18(3):393-403. doi:10.1108/JICES-04-2020-0052 Ming WK, Mackillop LH, Farmer AJ, et al. Telemedicine Technologies for Diabetes in Pregnancy: A Systematic Review and Meta-Analysis. J Med Internet Res . 2016;18(11). doi:10.2196/jmir.6556 Fazal N, Webb A, Bangoura J, Nasharty ME. Telehealth: improving maternity services by modern technology. BMJ Open Qual . 2020;9(4):e000895. doi:10.1136/bmjoq-2019-000895 Alqudah A, McMullan P, Todd A, et al. Service evaluation of diabetes management during pregnancy in a regional maternity hospital: potential scope for increased self-management and remote patient monitoring through mHealth solutions. BMC Health Services Research . 2019;19(1):662. doi:10.1186/s12913-019-4471-9 Royal College. Guidance for Antenatal and Postnatal Services in the Evolving Coronavirus (COVID-19) Pandemic . Mackillop L, Hirst JE, Bartlett KJ, et al. Comparing the Efficacy of a Mobile Phone-Based Blood Glucose Management System With Standard Clinic Care in Women With Gestational Diabetes: Randomized Controlled Trial. JMIR Mhealth Uhealth . 2018;6(3):e71. doi:10.2196/mhealth.9512 Yeh PT, Kennedy CE, Rhee DK, et al. Self-monitoring of blood glucose levels among pregnant individuals with gestational diabetes: a systematic review and meta-analysis. Front Glob Womens Health . 2023;4. doi:10.3389/fgwh.2023.1006041 Carson LE, Azmi B, Jewell A, et al. Cohort profile: the eLIXIR Partnership—a maternity–child data linkage for life course research in South London, UK. BMJ Open . 2020;10(10):e039583. doi:10.1136/bmjopen-2020-039583 Jones KC, Burns A. Unit costs of health and social care 2021. Published online 2021. Andersen RM. Revisiting the Behavioral Model and Access to Medical Care: Does it Matter? Journal of Health and Social Behavior . 1995;36(1):1-10. doi:10.2307/2137284 Azur MJ, Stuart EA, Frangakis C, Leaf PJ. Multiple imputation by chained equations: what is it and how does it work? Int J Methods Psychiatr Res . 2011;20(1):40-49. doi:10.1002/mpr.329 Khalil A, von Dadelszen P, Kalafat E, et al. Change in obstetric attendance and activities during the COVID-19 pandemic. Lancet Infect Dis . 2021;21(5):e115. doi:10.1016/S1473-3099(20)30779-9 Jardine J, Relph S, Magee LA, et al. Maternity services in the UK during the coronavirus disease 2019 pandemic: a national survey of modifications to standard care. BJOG . 2021;128(5):880-889. doi:10.1111/1471-0528.16547 Semaan A, Audet C, Huysmans E, et al. Voices from the frontline: findings from a thematic analysis of a rapid online global survey of maternal and newborn health professionals facing the COVID-19 pandemic. BMJ Global Health . 2020;5(6):e002967. doi:10.1136/bmjgh-2020-002967 Emmott EH, Gilliland A, Lakshmi Narasimhan A, Myers S. The impact of COVID-19 lockdown on postpartum mothers in London, England: An online focus group study. J Public Health (Berl) . Published online May 15, 2023. doi:10.1007/s10389-023-01922-4 Marian Knight, Rema Ramakrishnan, Kathryn Bunch, et al. Females in Hospital with SARS-CoV-2 infection, the association with pregnancy and pregnancy outcomes, 25 March 2021. Published online March 2021. https://www.gov.uk/government/publications/ukossisaricco-cin-females-in-hospital-with-sars-cov-2-infection-the-association-with-pregnancy-and-pregnancy-outcomes-25-march-2021 Harrison S, Quigley MA, Fellmeth G, Stein A, Alderdice F. The impact of the Covid-19 pandemic on postnatal depression: analysis of three population-based national maternity surveys in England (2014–2020). The Lancet Regional Health - Europe . 2023;30:100654. doi:10.1016/j.lanepe.2023.100654 Jackson L, Davies SM, Gaspar M, et al. The social and healthcare professional support drawn upon by women antenatally during the COVID-19 pandemic: A recurrent, cross-sectional, thematic analysis. Midwifery . 2024;133:103995. doi:10.1016/j.midw.2024.103995 Many women still positive about their maternity care - but pandemic impacted on choice and involvement and increased concerns about postnatal support. Published online February 9, 2022. https://www.cqc.org.uk/news/releases/many-women-still-positive-about-their-maternity-care-pandemic-impacted-choice Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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16:17:39","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5544062/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5544062/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70485697,"identity":"ef4ab8a8-1b6f-4a62-b1b6-a8ac72143949","added_by":"auto","created_at":"2024-12-03 15:45:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82011,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of ITS analysis—Total monthly pregnancy costs (blue line) and counterfactual scenario (dashed red line)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5544062/v1/e13009d53802c13c777e510d.png"},{"id":70487239,"identity":"66f29294-a867-48f9-b851-6acb6b8c2e1c","added_by":"auto","created_at":"2024-12-03 16:01:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1090056,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5544062/v1/2bfac373-c077-40ff-8017-ad14515491e9.pdf"},{"id":70485705,"identity":"57e75d22-4117-48ff-8402-9d1503ef754e","added_by":"auto","created_at":"2024-12-03 15:45:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":369760,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-5544062/v1/cf2ddaafece6abf66f6145f3.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe impact of the COVID-19 pandemic on maternal healthcare costs in a UK inner-city multi-ethnic population\u003c/p\u003e","fulltext":[{"header":"Panel: Putting research into context ","content":"\u003cp\u003e\u003cstrong\u003eEvidence before this study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe COVID-19 pandemic triggered rapid changes in maternity care delivery, including use of virtual care and self-monitoring. To inform policy about future maternity care and health system shocks, the impact of service reconfigurations on healthcare outcomes and costs required careful evaluation. Before undertaking this study, we performed a PubMed search to identify studies assessing the impact of the pandemic on maternity care costs. Search terms included variations of maternity care, virtual care, self-monitoring, healthcare costs and utilisation, Great Britain, National Health Service and COVID-19; the search retrieved 312 items as of 6 June 2023, of which there were 12 studies and one systematic literature review of interest. Existing UK evidence on the association of virtual care and self-monitoring with maternity costs was scarce and inconclusive. Published studies based on small sample sizes suggest that virtual care reduces healthcare use and self-monitoring is cost-neutral, but well-powered studies are needed to confirm these findings. Understanding the overall impact of the pandemic on maternity care costs, along with the specific effects of virtual care and self-monitoring, is particularly urgent in the current context of increasingly constrained health budgets globally and to prepare for future health system shocks.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdded value of this study\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this analysis of maternal and newborn costs for more than 35,000 ethnically-diverse pregnancies, with birth from October 2018 to April 2023, we found that the COVID-19 pandemic led to an overall decrease in pregnancy costs, associated with a drop in healthcare utilisation. The drop in costs occurred at the onset of pandemic lockdowns, and again when all lockdowns were lifted, but there was no change in the rate of rise of costs over time within either pandemic period (i.e., with or without lockdowns). The use of virtual care was associated with an increase in pregnancy costs. For women with GDM, self-monitoring through the GDm-Health app had no significant impact on pregnancy costs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications of the available evidence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, the COVID-19 pandemic caused only a temporary reduction in maternity care costs. Virtual care was associated with increased costs, while GDM self-monitoring was cost neutral. The impact on health outcomes of both virtual care and self-monitoring is needed to complement these findings and inform future health policy.\u0026nbsp;\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe COVID-19 pandemic had profound consequences for healthcare services, including maternity care\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Some midwifery units closed or merged, and staffing shortages affected the available skill mix\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Perceived risk of infection led to hesitation in seeking healthcare,\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and there were reductions in routine\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and unscheduled\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e antenatal care visits, prolonged maternal length of stay, and more maternal readmissions to hospital\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, most data is from the first pandemic year (to February 2021), during lockdowns, and unadjusted for pre-existing trends; thus, the impact of the pandemic overall on maternity costs over time remains largely unexplored.\u003c/p\u003e \u003cp\u003eDuring the pandemic in the United Kingdom (UK), the Royal College of Obstetricians \u0026amp; Gynaecologists advised expansion of \u0026lsquo;virtual care\u0026rsquo; (also known as \u0026lsquo;remote consultation\u0026rsquo;, \u0026lsquo;telehealth\u0026rsquo;, or \u0026lsquo;eHealth\u0026rsquo;) while ensuring at least six face-to-face antenatal visits\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. By July 2020, most UK maternity units had adopted virtual care in varying intensities\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. No impact of virtual care on outcomes was reported in an interrupted time series analysis from Australia\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, but extensive international qualitative data indicate that most women were less satisfied and less reassured by virtual (vs. face-to-face) care, resulting in further health care utilisation and potentially increased healthcare costs\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Also, there were concerns that the pandemic exacerbated inequalities when virtual care is offered to digitally-disadvantaged groups\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eExisting studies of virtual care impact on UK maternity healthcare costs are scarce and inconclusive, highlighted by a systematic review of telemedicine among pregnant women with diabetes\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. While subsequent studies of general\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and diabetes-specific\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e pre/peripartum populations reported lower healthcare use with virtual care, results were based on small sample sizes (75 and 63 patients, respectively) and healthcare costs for mothers and newborns were not assessed.\u003c/p\u003e \u003cp\u003eThe pandemic also saw rapid adoption of the GDm-Health app for gestational diabetes mellitus (GDM) care in the UK\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The app records remotely measured blood glucose levels with real-time review by healthcare-providers, facilitating rapid provider-patient communication\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. This contrasts to alternative to the traditional written \u0026lsquo;sugar diary\u0026rsquo; record discussed retrospectively at face-to-face appointments. Studies of the GDm-Health app show positive impacts on pregnancy outcomes when GDM self-monitoring is part of a care package\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, without incurring greater costs\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, acknowledging the small size of studies to date.\u003c/p\u003e \u003cp\u003eWe assessed: (i) the overall impact of the COVID-19 pandemic on monthly trajectory costs for maternity and newborn care, from October 2018 to April 2023; (ii) the impact of virtual care and GDm-Health app use on pregnancy costs; and (iii) whether costs differed across sociodemographic groups.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eIn a longitudinal study design, monthly electronic health record data from the early-LIfe data cross-LInkage in Research\u0026ndash;Born-in-South London (eLIXIR-BiSL) data linkage cohort were assessed. The dataset comprises routine maternity and neonatal health records of pregnant women accessing care via Guy\u0026rsquo;s and St Thomas\u0026rsquo; Hospital National Health Service [NHS] Foundation Trust and King\u0026rsquo;s College Hospital NHS Foundation Trust, linked to mental health (South London and Maudsley NHS Foundation Trust) and primary care data (Lambeth DataNet). These hospitals in inner-city boroughs in South London, UK, serve an urban, largely deprived, multi-ethnic population. Details for eLXIR-BiSL have been published previously\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe study sample includes women registering for maternity care between October 2018 (eLIXIR-BiSL cohort initiation) and April 2023, with antenatal registration and birth information. Study epochs are defined as \u0026lsquo;pre-pandemic\u0026rsquo; (October 2018 to February 2020), \u0026lsquo;pandemic lockdowns\u0026rsquo; (March 2020 to June 2021), and \u0026lsquo;post-lockdown\u0026rsquo; (July 2021 to April 2023). March 2020 was when the UK healthcare system\u0026rsquo;s response began and the first national lockdown was implemented.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData variables and measurement\u003c/h3\u003e\n\u003cp\u003ePregnancy costs were generated from the NHS perspective, based on individual-level health service use and 2021-22 national unit costs (\u003cb\u003eBox S1\u003c/b\u003e), with the NHS Cost Inflation Index used to adjust for inflation\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Maternity services, mental healthcare, and primary care utilisation were included, from antenatal registration appointment to six weeks postpartum. Maternity services captured routine antenatal appointments, maternity assessment unit visits, birth and other inpatient stays, and postnatal reviews. Mental health services included \u0026lsquo;Talking therapies\u0026rsquo; (for depression or anxiety), secondary mental health services \u0026lsquo;community contacts\u0026rsquo;, and inpatient stays. Primary care costs reflect primary care consultations and were available for 32% of individuals in our sample (limited to general practice in Lambeth borough). Neonatal costs were included across relevant services (inpatient stays, postnatal reviews and primary care). Total pregnancy costs are aggregated for analyses at the monthly mother-newborn level.\u003c/p\u003e\n\u003ch3\u003eStatistical methods\u003c/h3\u003e\n\u003cp\u003eMaternal characteristics and healthcare utilisation and costs were compared via descriptive statistics across pre-pandemic, pandemic lockdowns, and post-lockdown periods, with differences assessed using t-tests or Mann\u0026ndash;Whitney U-tests for continuous variables, and Pearson Chi-Squared tests for categorical variables.\u003c/p\u003e \u003cp\u003eModel 1: Effect of the COVID-19 pandemic on monthly pregnancy costs\u003c/p\u003e \u003cp\u003eInterrupted time series (ITS) analysis was used to predict the effect of the pandemic on monthly pregnancy costs, comparing with pre-pandemic costs and differentiating between lockdown and post-lockdown periods. Pregnancy-month is the unit of analysis. Interaction terms considered both a change in level (immediate effect) and slope (gradual effect) of the cost trendline, from lockdown impositions (March 2020) to lifting (July 2021). Models adjusted for seasonality and autocorrelation, as well as ethnicity and the percentage of deliveries, each of which changed over time (\u003cb\u003eBox S2\u003c/b\u003e and \u003cb\u003eFigures S1-S4\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eModel 2: Impact of virtual antenatal care on maternity costs\u003c/p\u003e \u003cp\u003eIn this cross-sectional model, the dependent variable was total cost per pregnancy, summing all monthly costs from antenatal registration to six weeks postpartum. The independent variable was \u0026lsquo;Virtual care percentage\u0026rsquo;, capturing the percentage of antenatal care delivered virtually, by telephone or video. To avoid the virtual care estimate capturing the effect of pandemic lockdowns, a control is included for the percentage of care that occurred from March 2020 to June 2021. Other control variables were maternal age (years), ethnicity (Black/Asian/Mixed/Other/Missing), difficulty speaking English (yes/no), socioeconomic deprivation (Index of Multiple Deprivation [IMD] in quintiles), multiple birth (yes/no), gestational age at booking (weeks), smoking status (yes/no), and antenatal care plan type (i.e., \u0026lsquo;Midwife only\u0026rsquo;, \u0026lsquo;Shared midwife and obstetrician\u0026rsquo; (75/25 split), or \u0026lsquo;Obstetrician only\u0026rsquo;, as granular information on the type of provider who delivered care at each antenatal appointment was not available), GDM, one/more other health conditions (i.e., GDM, other physical or mental health conditions) recorded at antenatal registration (by organ system, see \u003cb\u003eBox S3\u003c/b\u003e), and the hospital providing care. The choice of independent variables was guided by Andersen\u0026rsquo;s revised conceptual framework of healthcare utilisation, by which use of health services is determined by predisposing factors, enabling factors, and need\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eModel 3: Effect of GDm-Health app self-monitoring on maternity costs\u003c/p\u003e \u003cp\u003eThe last analysis was restricted to women with GDM. The dependent variable was total cost per pregnancy. The independent variable was \u0026lsquo;App-User\u0026rsquo;, (dichotomised by app registration status [1\u0026thinsp;=\u0026thinsp;yes, 0\u0026thinsp;=\u0026thinsp;no]). As women may have initially registered, but stopped using it, a sensitivity analysis was run with the definition of \u0026lsquo;App-User\u0026rsquo; to those who recorded sufficient blood glucose readings to be clinically meaningful (\u003cb\u003eBox S4\u003c/b\u003e). An app cost of \u0026pound;8 per pregnancy was added to total cost per pregnancy for app-users, based on payment made by each hospital for app access, and the number of individuals in our sample. The same control variables are used as in Model 2 (above).\u003c/p\u003e \u003cp\u003eAcross all models, to assess inequalities in the impact of the pandemic on maternity care costs across minority groups and individuals with medical complexity, subgroup analyses are presented, examining: ethnicity, IMD, difficulty speaking English, GDM, and mental health problems. Interactions are added between each subgroup variable and the key terms of interest (i.e., change in trendline level, change in trendline slope, and independent variables of virtual care and GDm-Health app use).\u003c/p\u003e \u003cp\u003eMissing data were kept as missing except for primary care utilisation, for which multiple imputation via chained equations (MICE) \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e was performed (\u003cb\u003eBox S5, Figure S5\u003c/b\u003e and \u003cb\u003eTable S3\u003c/b\u003e). Sensitivity analyses explore the impact of multiple imputation of primary care costs (by excluding primary care costs from total costs), considering July 2021 in the pandemic lockdowns period (rather than in post-lockdown), and changing the definition of \u0026lsquo;Shared midwife and obstetrician\u0026rsquo; antenatal care from a 75/25 to 90/10 split. Goodness of fit measures are used to identify the most appropriate estimation method for each of Models 1 to 3: an ordinary least squares model (OLS) or a generalised linear model (GLM) with a gamma distribution and log link.\u003c/p\u003e \u003cp\u003eAll analyses were conducted using R version 4.3.0.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOur sample size was 36,985 pregnancies, across pre-pandemic (N\u0026thinsp;=\u0026thinsp;13,284), pandemic lockdowns (N\u0026thinsp;=\u0026thinsp;11,470), and post-lockdown pandemic (N\u0026thinsp;=\u0026thinsp;12,231) periods.\u003c/p\u003e\n\u003cp\u003ePre-pandemic, women were on average aged 33 years, half were of White ethnicity, relatively deprived (60% in the two most deprived IMD quintiles), and with English as primary language in 70% (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Ten percent developed GDM, and many had a record at the booking appointment of at least one physical (41%) or mental (22%) health condition. Maternal characteristics remained stable during pandemic lockdowns and post-lockdown, albeit with slight, statistically significant, increases in: age, the percentage of individuals of non-White ethnicity, those with missing IMD, GDM, and physical or mental health conditions.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMaternal characteristics in the pre-pandemic, pandemic (with lockdowns), and post-pandemic (without lockdowns) periods\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePre-pandemic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePandemic with lockdowns\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePandemic without lockdowns\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;13,284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;11,470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;12,231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnicity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 1 (most deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 5 (least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e% of English speakers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e% Difficulty speaking English\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e% with GDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e% with a physical health condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e% with a mental health condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eNotes: IMD: Index of Multiple Deprivation. GDM: Gestational Diabetes Mellitus.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003e\u003cstrong\u003epandemic (without lockdowns) periods\u003c/strong\u003e\u003c/h3\u003e\n\u003ch3\u003eCosts per pregnancy\u003c/h3\u003e\n\u003cp\u003ePre-pandemic, the distribution of total cost per pregnancy was right-skewed, with a mean of \u0026pound;7,625 (standard deviation [SD]\u0026thinsp;=\u0026thinsp;2,668) and median of \u0026pound;7,118 (interquartile range [IQR]=\u0026pound;5,625-\u0026pound;9,085) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Total costs were driven primarily by delivery costs (~\u0026thinsp;60%, \u0026pound;4,734, SD\u0026thinsp;=\u0026thinsp;1,781), followed by routine antenatal costs (~\u0026thinsp;20%, \u0026pound;1,344, SD\u0026thinsp;=\u0026thinsp;775), with much smaller contributions from primary care (mean of \u0026pound;154 per pregnancy, SD\u0026thinsp;=\u0026thinsp;128) and mental healthcare (mean of \u0026pound;28, SD\u0026thinsp;=\u0026thinsp;593). The composition of total costs remained stable across the pandemic, with or without lockdowns (\u003cstrong\u003eFigure S6\u003c/strong\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean total mother-newborn pregnancy costs (SD) in the pre-pandemic, pandemic (with lockdowns), and post-pandemic (without lockdowns) periods\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePre-pandemic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePandemic with lockdowns\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePandemic without lockdowns\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;13,284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;11,470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10,233\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal pregnancy costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;7,624.54 (2,668.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;7,932.20 (2,833.68) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;8,095.86 (2,799.60)***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal maternity services costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;7,442.85 (2,577.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;7,704.72 (2,548.21) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;7,860.91 (2,657.19)***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoutine antenatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;1,344.45 (775.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;1,571.02 (710.41) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;1,557.70 (743.36)***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternity assessment unit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;341.03 (321.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;373.94 (349.37) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;427.37 (411.22)***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInpatient stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;248.21 (634.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;282.59 (674.05) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;313.75 (775.25)***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;4,734.06 (1,781.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;4,810.31 (1,791.18) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;4,976.29 (1,855.58) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePost-natal review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;775.10 (573.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;666.87 (590.31) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;585.80 (553.61) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal primary care costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;153.91 (128.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;171.50 (156.12) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;199.86 (172.69) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal mental health services costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;27.79 (593.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;55.98 (1,156.36) **\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;35.10 (789.80) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTalking therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;7.58 (59.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;11.07 (77.23) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;9.15 (64.54) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommunity contacts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;9.33 (87.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;14.50 (139.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;13.41 (115.95) ***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInpatient stay costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;10.87 (572.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;30.41 (1,093.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026pound;12.55 (751.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eNotes: \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The stars indicate statistical significance corresponding to the t-tests (Mann\u0026ndash;Whitney U) comparing mean costs during the pandemic with lockdowns to pre-pandemic. \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e The stars indicate statistical significance corresponding to the t-tests (Mann\u0026ndash;Whitney U) comparing mean costs during the pandemic without lockdowns to pre-pandemic. *** \u0026lt;0.001; ** \u0026lt;0.01; * \u0026lt;0.05.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOver the pandemic, mean total cost per pregnancy grew, to \u0026pound;7,932 (SD\u0026thinsp;=\u0026thinsp;2,833) during pandemic lockdowns and \u0026pound;8,096 (SD\u0026thinsp;=\u0026thinsp;2,799) post-lockdown (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). All cost components increased, except for progressive declines in routine postnatal review costs (from \u0026pound;775 pre-pandemic, to \u0026pound;667 during pandemic lockdowns, and \u0026pound;586 post-lockdown). Mean mental health costs showed the largest relative pandemic increase, from \u0026pound;28 pre-pandemic, to \u0026pound;56 during pandemic lockdowns and \u0026pound;35 post-lockdown. Similar fluctuations in healthcare utilisation were observed across the study period (\u003cstrong\u003eTable S4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eThere was a sharp increase in use of virtual care during pandemic lockdowns compared with pre-pandemic use (\u003cstrong\u003eFigure S7\u003c/strong\u003e). While in February 2020 only 2% of routine antenatal care was virtual, this peaked at 18% in June 2020. Thereafter, virtual antenatal care declined progressively through pandemic lockdowns to 7% by June 2021 (resulting in an average monthly proportion of virtual care during the lockdowns of 12.3%), and reaching 5% by the end of post-lockdown (April 2023).\u003c/p\u003e\n\u003cp\u003eOverall, 4,399/35,985 (12%) of pregnancies were complicated by GDM, of which 3,215 (75%) were registered on the GDm-Health app (\u003cstrong\u003eTable S5\u003c/strong\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eMain Results\u003c/h2\u003e\n \u003cp\u003eModel 1: Effect of the COVID-19 pandemic on monthly pregnancy costs\u003c/p\u003e\n \u003cp\u003eAccording to the ITS model, in the initial months of pandemic lockdowns, monthly pregnancy costs (blue line, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) were lower than they would have been if the pandemic had not occurred (dotted red line, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Compared with pre-pandemic, the level of the monthly cost trendline dropped by \u0026pound;38 (95% CI: 10\u0026ndash;65) with the onset of pandemic lockdowns (equivalent to 4% of monthly pregnancy costs), and by \u0026pound;72 (36\u0026ndash;108) with the onset of post-lockdown (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). However, there were no statistically significant changes to the cost trendline slopes. In March 2020, monthly pregnancy costs were 3% lower (\u0026pound;991) than the counterfactual if the pandemic had not occurred (\u0026pound;1,024) (\u003cstrong\u003eTable S6\u003c/strong\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eParameter estimates from the ITS model assessing the impact of the pandemic on monthly pregnancy costs\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter estimate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e147.64\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(124.35, 170.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.56\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.30, 6.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePandemic lockdowns - change in level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-37.66\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-65.07, -10.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePandemic lockdowns - change in slope\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-2.93, 3.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePost lockdown - change in level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-72.05\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-107.95, -36.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePost lockdown - change in slope\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-2.42, 4.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,659.46\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(5,636.88, 5,682.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.11\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(42.36, 61.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.71\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(22.38, 45.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-11.57, 16.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.43\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(2.19, 30.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-40.80\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-55.22, -26.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNotes: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Model also controls for month, hospital and lagged residuals. Reference group for ethnicity is \u0026quot;White\u0026quot; and changes in level and slope are compared to the pre-pandemic period.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSubgroup analyses found a differential effect of monthly pregnancy costs over time, by ethnicity (\u003cstrong\u003eTables S7-8\u003c/strong\u003e and \u003cstrong\u003eFigure S8\u003c/strong\u003e ). While mean costs among White ethnicity women dropped in level by \u0026pound;74 (95% CI: -\u0026pound;38 to -\u0026pound;109) at the start of pandemic lockdowns, costs for Black ethnicity women increased in level by \u0026pound;30 (for a difference vs. White ethnicity women of +\u0026pound;103, CI: 26\u0026ndash;181) and costs for Asian ethnicity women grew by \u0026pound;54 (for a difference of +\u0026pound;128, CI: 38\u0026ndash;218). Thereafter, costs for Black and Asian (vs. White) ethnicity women grew more slowly during the pandemic (by -\u0026pound;10 and -\u0026pound;16 per month, respectively, vs. +\u0026pound;4 for White ethnicity women), but those costs for Black and Asian (vs. White) ethnicity women remained higher throughout the pandemic (\u003cstrong\u003eFigure S8\u003c/strong\u003e). There was less variation in costs post-lockdown, with the only difference being for women of Asian ethnicity, who had a \u0026pound;12 slower monthly trend.\u003c/p\u003e\n \u003cp\u003eModel 2: Impact of virtual antenatal care on maternity costs\u003c/p\u003e\n \u003cp\u003eIn this cross-sectional model, women with a higher proportion of virtual antenatal care had higher pregnancy costs, with a 1% point increase in virtual care associated with a \u0026pound;7 (95% CI: 3\u0026ndash;10) increase in costs (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). As the average monthly proportion of virtual care during pandemic lockdowns was 12.3%, compared with 1.9% pre-pandemic (a 10.4% difference), this represents a \u0026pound;73 increase in cost per pregnancy during pandemic lockdowns. Assuming that all of the 11,470 pregnancies during pandemic lockdowns received 12.3% of their antenatal care virtually, the NHS incurred \u0026pound;837,310 (\u0026pound;73 x 11,470) additional costs compared with pre-pandemic use of virtual care).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eParameter estimates from the cross-sectional models assessing the impact of virtual care and self-monitoring via the GDm-Health app on costs per pregnancy\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter estimate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter estimate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVirtual care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.92\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(3.49, 10.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e139.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-68.49, 347.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of care during the pandemic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-200.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-569.15, 168.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-746.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-1,948.91, 456.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(7.27, 17.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(8.61, 37.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e302.33\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(226.48, 378.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e369.81\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(175.61, 564.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e222.91\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(138.60, 307.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-135.95, 261.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-46.46, 172.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-337.27, 372.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e144.99\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(40.72, 249.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-206.81, 314.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-243.46\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-332.54, -154.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-196.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-565.34, 173.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-62.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-135.58, 9.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-84.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-278.38, 110.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-101.66\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-179.69, -23.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-42.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-265.66, 180.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-102.54\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-202.57, -2.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-121.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-425.70, 182.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 5 (Least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-98.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-229.47, 32.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-290.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-666.53, 85.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-105.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-333.46, 122.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e174.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-680.17, 1,029.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-148.23, 133.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-479.15, 489.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking status missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-74.79, 208.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-383.82, 375.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAntenatal care type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e735.79\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(680.15, 791.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e799.68\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(606.96, 992.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObstetrician only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,470.96\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1,209.05, 1,732.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,794.53\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1,889.53, 3,699.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e318.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-39.87, 675.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1465.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-317.37, 3,249.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple births\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,655.76\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(7,387.55, 7,923.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,671.23\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(7,096.10, 8,246.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDifficulty speaking English\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-57.00, 55.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-131.99, 183.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e451.56\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(398.95, 504.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e523.34\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(368.99, 677.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMental health condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e393.68\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(328.55, 458.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e560.81\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(364.92, 756.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e726.84\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(648.03, 805.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestation at booking (weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-57.89\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-61.49, -54.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-57.89\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-70.80, -44.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,345.05\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(6,117.46, 6,572.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,172.56\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(5,449.89, 6,895.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNotes: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Two separate cost models were estimated, one assessing the impact of virtual care and the other the impact of self-monitoring. IMD\u0026thinsp;=\u0026thinsp;Index of Multiple Deprivation. GDM\u0026thinsp;=\u0026thinsp;Gestational Diabetes Mellitus. Model also controls for month of booking appointment and hospital. Reference group for ethnicity is \u0026quot;White\u0026quot;, and reference group for antenatal care type is \u0026quot;Midwife only\u0026quot; care. Multiple births, difficulty speaking English, physical condition, mental health condition and GDM are all yes/no variables, with \u0026ldquo;no\u0026rdquo; as the reference category.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eParameter estimates from the cross-sectional model assessing the impact on costs per pregnancy of self-monitoring via the GDm-Health app\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter estimate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e139.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-68.49, 347.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of care during pandemic lockdowns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-746.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-1,948.91, 456.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(8.61, 37.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e369.81\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(175.61, 564.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-135.95, 261.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-337.27, 372.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-206.81, 314.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-196.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-565.34, 173.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-84.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-278.38, 110.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-42.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-265.66, 180.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-121.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-425.70, 182.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuintile 5 (Least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-290.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-666.53, 85.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e174.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-680.17, 1,029.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-479.15, 489.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking status missing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-383.82, 375.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAntenatal care type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e799.68\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(606.96, 992.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObstetrician only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,794.53\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1,889.53, 3,699.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1465.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-317.37, 3,249.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple births\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,671.23\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(7,096.10, 8,246.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDifficulty speaking English\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-131.99, 183.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e523.34\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(368.99, 677.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMental health condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e560.81\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(364.92, 756.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestation at booking (weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-57.89\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-70.80, -44.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,172.56\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(5,449.89, 6,895.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eNote: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. IMD\u0026thinsp;=\u0026thinsp;Index of Multiple Deprivation. GDM\u0026thinsp;=\u0026thinsp;Gestational Diabetes Mellitus. Model also contains control for month of booking appointment and hospital. Reference group for ethnicity is \u0026quot;White\u0026quot;, and reference group for antenatal care type is \u0026quot;Midwife only\u0026quot; care. Multiple births, difficulty speaking English, physical condition, mental health condition and GDM are all yes/no variables, with \u0026ldquo;no\u0026rdquo; as the reference category.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eModel 3: Effect of GDm-Health app self-monitoring on maternity costs\u003c/p\u003e\n \u003cp\u003eAmong women with GDM, there were no differences in total costs per pregnancy between those who registered on the GDm-Health app and those who did not (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Also, there was no difference in costs in the sensitivity analysis that compared costs for those who showed clinically-relevant app use (vs. those who did not; analyses available upon request).\u003c/p\u003e\n \u003cp\u003eIn both Models 2 and 3, no differential impacts on cost per pregnancy were found for virtual care (\u003cstrong\u003eTable S9\u003c/strong\u003e) or GDM app registration (\u003cstrong\u003eTable S10\u003c/strong\u003e), across ethnic groups, IMD quintiles, difficulty speaking English, or mental health status.\u003c/p\u003e\n \u003cp\u003eAll models were estimated using OLS, as it showed slightly better goodness of fit than a GLM model with the log link and the gamma distribution (\u003cstrong\u003eTable S11\u003c/strong\u003e). The GLM log link and gamma distribution model yielded comparable parameter estimates to OLS across the three models (results available upon request).\u003c/p\u003e\n \u003cp\u003eSensitivity analyses supported the stability of our results, with similar findings: after exclusion of primary care costs, with a change in the proportion of midwifery/obstetrician care in a shared care model, or after considering July 2021 as part of pandemic lockdowns (rather than post-lockdown) (\u003cstrong\u003eTable S12-S14\u003c/strong\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSummary\u003c/h2\u003e \u003cp\u003eThe COVID-19 pandemic led to a drop from pre-pandemic values in maternity costs at the onset of pandemic lockdowns, and again post-lockdown when all restrictions were lifted, but there was no change in the rate of rise of costs over time within either pandemic period (with or without lockdowns). Importantly, our findings suggest that the pandemic affected minority ethnic women differently; compared with White ethnicity women, those of Black or Asian ethnicity experienced an increase (not decrease) in costs at the start of pandemic lockdowns, and their costs rose more slowly during pandemic lockdowns, with that trend continuing for Asian ethnicity women during post-lockdown.\u003c/p\u003e \u003cp\u003eDescriptive analyses of costs per pregnancy (resulting from aggregating monthly pregnancy costs for each woman over the duration of their pregnancy) suggest that a pregnancy was more expensive for the NHS during the pandemic than before, with (by an average of \u0026pound;307), or without lockdowns (by \u0026pound;471). However, this pattern reflects a pre-pandemic trend of rising pregnancy costs that continued at the same rate during the pandemic, and so the higher costs cannot be attributed to the pandemic \u003cem\u003eper se\u003c/em\u003e. 1170\u003c/p\u003e \u003cp\u003eIn additional analyses, use of virtual care was associated with an increase in pregnancy costs. However, for women with GDM, self-monitoring through the GDm-Health app had no significant impact on pregnancy costs. There was no evidence of a differential impact of the pandemic on these costs according to ethnicity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eComparison with the literature\u003c/h2\u003e \u003cp\u003eTo our knowledge, this is the first study assessing the impact of the COVID-19 pandemic on maternity costs, covering the entire pandemic period and differentiating between overall trends in monthly pregnancy costs and costs per pregnancy.\u003c/p\u003e \u003cp\u003eOur ITS results predicting lower monthly pregnancy costs during the pandemic align with previous literature reporting decreased healthcare utilisation in maternity services during the pandemic\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. This has been attributed to women\u0026rsquo;s hesitancy to seek care during the pandemic, due to fears of infection or staff shortages restricting access to care\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The decrease in monthly pregnancy costs occurred with the onset of pandemic lockdowns and their withdrawal, without ongoing change in the previous rate of rise in monthly pregnancy costs. Whereas an increase might have been anticipated with release of lockdowns, we saw another decrease in monthly pregnancy costs. A potential explanation may be continued fear of infection from contacts with the healthcare system, particularly as maternity services were still cautious\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Also, the post-lockdown reduction in use of virtual care \u0026ndash; which we had found to be more expensive than standard care \u0026ndash; may have contributed. Thereafter, and in common with the pandemic with lockdowns, there was no ongoing change in the rate of rise in monthly pregnancy costs.\u003c/p\u003e \u003cp\u003eImportantly, we found some evidence that the pandemic affected minority ethnic groups differently than White ethnicity women. A previous population-based study using routinely-collected data from England reported that individuals of ethnicities other than White (vs. White) were associated with slightly higher rates of preterm birth and Caesareans, and lower unassisted vaginal birth\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Our results suggest that women of Black and Asian (vs. White) ethnicities experienced an initial increase in maternity costs at the onset of pandemic lockdowns, and a slower rise thereafter, but still resulting in overall higher costs during pandemic lockdowns. Higher costs for women of Black and Asian (vs. White) ethnicities could have resulted from these minority ethnic groups being at higher risk of severe COVID-19 illness, and having a disproportionally higher number of hospital admissions during their pregnancy\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe cost component with the largest relative increase over the study period was mental health services, although they made up a small fraction (0.5%) of overall pregnancy and postpartum costs. This finding aligns with previous literature reporting worsening of women\u0026rsquo;s mental health during pandemic pregnancy; reasons cited have included disruption of service delivery, uncertainty about the effects of COVID-19 on pregnancy, and birth partners being excluded from some elements of pregnancy care and delivery\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Postnatal reviews were the only cost component of maternity care that decreased over time, which aligns with surveys that found that care after birth was particularly impacted by the pandemic, and women\u0026rsquo;s reports that they received less postnatal support\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile virtual care is generally considered less expensive than face-to-face care, our findings are that virtual antenatal care is associated with higher pregnancy costs, suggesting virtual (vs. face-to-face), appointments may result in further healthcare use due to poorer quality of care or outcomes\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Existing comparable literature is limited. Our results contradict two previous studies which found virtual care in maternity care to be associated with lower healthcare use\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e; each study had a small sample size (75 and 63 patients), and only one addressed virtual care in general; the others was focused on virtual care for GDM. Given the importance of understanding the full impact of virtual care in maternity services, further quantitative studies of the healthcare costs of virtual care are warranted.\u003c/p\u003e \u003cp\u003eFinally, this study complements previous research on the positive impacts of GDM self-monitoring using GDm-Health\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, by finding it is cost-neutral compared with the traditional, non-digital health approach. Our findings add to the scarce cost evidence base in this area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eStrengths of our work include an ethnically- and socioeconomically-diverse study population. Comprehensive ethnicity data allowed for assessment of ethnic inequalities when examining the impact of the pandemic on maternity care costs. Total costs captured healthcare use, for mothers, as well as newborns. Maternity services assessed included mental health and primary care, to provide a more holistic view of healthcare needs during pregnancy and postpartum.\u003c/p\u003e \u003cp\u003eSome limitations should be acknowledged. Total costs were computed from the NHS perspective and did not capture social care costs and patient out-of-pocket expenses, which may have been substantial during pandemic lockdowns and the subsequent cost-of-living crisis. Primary care use was available for only 32% of women, who were registered to a GP practice in the borough of Lambeth; despite this, missing values were imputed, and our sensitivity analyses removing primary care from total costs did not affect the main results. While granular information was not available on the type of provider who delivered care at each antenatal appointment, in sensitivity analyses, our results were robust to assumptions about the proportion of care provided by midwives and obstetricians. Last, ITS is a quasi-experimental design with limited ability to assign causality to pandemic effects detected in this study; the possibility of residual confounding cannot be ruled out.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMaternity care costs declined in association with the COVID-19 pandemic, with onset of pandemic lockdowns and then with lifting of all restrictions; however, there was no effect on the trend of rising costs seen pre-pandemic, despite the most severe public health crisis in the last century. Of importance for planning future maternity services, is our findings that virtual antenatal care appears to be more expensive than face-to-face care, and the cost-neutral nature of digital technology to support GDM self-monitoring of glycaemic control. Further research on the effects of virtual care and GDm-Health use on clinical outcomes is needed to inform future guidelines on antenatal care delivery, especially during health system shocks.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eContributors statement:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAlice McGreevy:\u003c/strong\u003e Conceptualization, Methodology, Software, Validation, Formal analysis, Writing - Original Draft, Writing - Review \u0026amp; Editing. \u003cstrong\u003eMarina Soley-Bori:\u003c/strong\u003e Conceptualization, Methodology, Validation, Formal analysis, Writing - Original Draft, Writing - Review \u0026amp; Editing, Supervision, Funding acquisition. \u003cstrong\u003eFlorence Tydeman\u003c/strong\u003e: Methodology, Software, Validation, Writing - Review \u0026amp; Editing. \u003cstrong\u003eKathryn Dalrymple:\u0026nbsp;\u003c/strong\u003eWriting - Review \u0026amp; Editing, Validation, Software\u003cstrong\u003e. Sara White:\u0026nbsp;\u003c/strong\u003eWriting - Review \u0026amp; Editing, Funding acquisition. \u003cstrong\u003eAsma Khalil:\u0026nbsp;\u003c/strong\u003eWriting - Review \u0026amp; Editing, Funding acquisition. \u003cstrong\u003eLucilla Poston\u003c/strong\u003e: Writing - Review \u0026amp; Editing, Funding acquisition. \u003cstrong\u003eEmma Duncan:\u003c/strong\u003e Writing - Review \u0026amp; Editing, Funding acquisition\u003cstrong\u003e\u0026nbsp;Tisha Dasgupta\u003c/strong\u003e: Writing - Review \u0026amp; Editing., \u003cstrong\u003eHiten D. Mistry\u003c/strong\u003e: Writing - Review \u0026amp; Editing. \u003cstrong\u003eJulia Fox-Rushby:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Resources, Writing - Review \u0026amp; Editing, Supervision, Funding acquisition. \u003cstrong\u003ePeter von Dadelszen\u003c/strong\u003e: Writing - Review \u0026amp; Editing, Funding acquisition. \u003cstrong\u003eLaura A. Magee:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Resources, Writing - Review \u0026amp; Editing, Supervision, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interests:\u003c/strong\u003e This study represents independent research funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King\u0026rsquo;s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement statement\u003c/strong\u003e: We wish to thank the women, their infants, and families from all participating sites for sharing their data and supporting the eLIXIR-BiSL programme.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthnics approval:\u003c/strong\u003e The Early Life Cross Linkage in Research, Born in South London (eLIXIR-BiSL) Partnership has received ethical approval from the Oxfordshire Research Ethics Committee C (23/SC/0116) as an anonymised dataset for medical research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing:\u003c/strong\u003e The data accessed by eLIXIR remain within an NHS firewall and governance is provided by the eLIXIR Oversight Committee reporting to relevant information governance clinical leads. Subject to these conditions, data access is encouraged and those interested should contact the eLIXIR Chief Investigator (Professor Lucilla Poston; [email protected] ).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBMA. COVID-19: Impact of the pandemic on healthcare delivery. The British Medical Association is the trade union and professional body for doctors in the UK. 2023. Accessed April 24, 2024. https://www.bma.org.uk/advice-and-support/covid-19/what-the-bma-is-doing/covid-19-impact-of-the-pandemic-on-healthcare-delivery\u003c/li\u003e\n\u003cli\u003eWHO. \u003cem\u003eThe Impact of COVID-19 on Health and Care Workers: A Closer Look at Deaths\u003c/em\u003e.; 2021. https://iris.who.int/bitstream/handle/10665/345300/WHO-HWF-WorkingPaper-2021.1-eng.pdf?sequence=1\u0026amp;isAllowed=y\u003c/li\u003e\n\u003cli\u003eBrigante L, Morelli A, Jokinen M, Plachcinski R, Rowe R. Impact of the COVID-19 pandemic on midwifery-led service provision in the United Kingdom in 2020-21: Findings of three national surveys. \u003cem\u003eMidwifery\u003c/em\u003e. 2022;112:103390. doi:10.1016/j.midw.2022.103390\u003c/li\u003e\n\u003cli\u003eFlaherty SJ, Delaney H, Matvienko-Sikar K, Smith V. Maternity care during COVID-19: a qualitative evidence synthesis of women\u0026rsquo;s and maternity care providers\u0026rsquo; views and experiences. \u003cem\u003eBMC Pregnancy Childbirth\u003c/em\u003e. 2022;22(1):438. doi:10.1186/s12884-022-04724-w\u003c/li\u003e\n\u003cli\u003eNICE. Rationale and impact | Antenatal care | Guidance | NICE. August 19, 2021. Accessed April 29, 2024. https://www.nice.org.uk/guidance/ng201/chapter/Rationale-and-impact#antenatal-appointments-2\u003c/li\u003e\n\u003cli\u003eKhalil A, Von Dadelszen P, Kalafat E, et al. 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Published online March 2021. https://www.gov.uk/government/publications/ukossisaricco-cin-females-in-hospital-with-sars-cov-2-infection-the-association-with-pregnancy-and-pregnancy-outcomes-25-march-2021\u003c/li\u003e\n\u003cli\u003eHarrison S, Quigley MA, Fellmeth G, Stein A, Alderdice F. The impact of the Covid-19 pandemic on postnatal depression: analysis of three population-based national maternity surveys in England (2014\u0026ndash;2020). \u003cem\u003eThe Lancet Regional Health - Europe\u003c/em\u003e. 2023;30:100654. doi:10.1016/j.lanepe.2023.100654\u003c/li\u003e\n\u003cli\u003eJackson L, Davies SM, Gaspar M, et al. The social and healthcare professional support drawn upon by women antenatally during the COVID-19 pandemic: A recurrent, cross-sectional, thematic analysis. \u003cem\u003eMidwifery\u003c/em\u003e. 2024;133:103995. doi:10.1016/j.midw.2024.103995\u003c/li\u003e\n\u003cli\u003eMany women still positive about their maternity care - but pandemic impacted on choice and involvement and increased concerns about postnatal support. Published online February 9, 2022. https://www.cqc.org.uk/news/releases/many-women-still-positive-about-their-maternity-care-pandemic-impacted-choice\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"King's College London","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Maternity care, Covid-19, interrupted series analysis, maternity care costs","lastPublishedDoi":"10.21203/rs.3.rs-5544062/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5544062/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: During the COVID-19 pandemic, maternity care reconfigurations disrupted in-person care, which shifted towards virtual care and self-monitoring. We assessed the impact of these changes on healthcare costs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Data from October 2018 to April 2023 were used from the population-based early-LIfe data cross-LInkage in Research-Born-in-South London (eLIXIR-BiSL) platform linking maternity, neonatal, and mental healthcare data from three National Health Service (NHS) hospitals in South London, United Kingdom. Pregnancy costs were generated from the NHS perspective, using national unit costs and individual-level use of maternity, mental health, and primary care services. Interrupted time series analysis estimated the pandemic impact on monthly mother-newborn costs over time. Cross-sectional pre-pregnancy cost models isolated the impact of virtual care, and gestational diabetes (GDM) self-monitoring using the GDm-Health app.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings\u003c/strong\u003e: Among 36,895 pregnancies, the monthly cost trendline level dropped by 4% (£38, 95% confidence interval: [£10-65]), during the first pandemic lockdown, and by £72 [36-108], when lockdowns were lifted. However, the pre-pandemic upward trendline slope of costs was unchanged (£0.46 [-2.93 to 3.84]). Monthly costs increased with first lockdown for Black (£103 [26-181]) and Asian women (£128 [38-218]) and increased more slowly during post-lockdown (-£12 [-23 to -2]), for Asian women, remaining higher throughout the pandemic for Black and Asian women. A 1% increase in virtual care was associated with a £7 [3-10] increase in maternity costs. GDM self-monitoring via GDm-Health was cost-neutral (£140 [-68 to 348]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e: The pandemic was associated with temporary reductions in maternity costs due to lower healthcare utilisation. Ongoing, rising maternity costs were unchanged. The pandemic had differential effects on Black and Asian women compared to White. Further research is needed into clinical outcomes of virtual care (associated with higher costs) and use of GDm-Health (cost-neutral).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: National Institute for Health Research (NIHR134293), Medical Research Council (MR/P003060/1, MR/X009742/1).\u003c/p\u003e","manuscriptTitle":"The impact of the COVID-19 pandemic on maternal healthcare costs in a UK inner-city multi-ethnic population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-03 15:45:21","doi":"10.21203/rs.3.rs-5544062/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c570bc09-5f1b-40b0-a0a2-4048d53a59ca","owner":[],"postedDate":"December 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-03T15:45:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-03 15:45:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5544062","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5544062","identity":"rs-5544062","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}