Download PDF
Am J Perinatol
DOI: 10.1055/a-2625-6437
Original Article

Diabetes Technology Use in Pregnancies with Type 1 Diabetes in the United States from 2009 to 2020

Nasim C. Sobhani 
1   Division of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Francisco, San Francisco, California
,
Yongmei Huang
2   Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, New York
,
Kartik K. Venkatesh 
3   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
,
Jason D. Wright
4   Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, New York
,
Alexander M. Friedman
5   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, New York
,
Timothy Wen
6   Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, California
7   Division of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, California
› Author Affiliations
Funding None.
› Further Information
Also available at
   Permissions and Reprints

Abstract

Objective

The use of continuous glucose monitors (CGM) and insulin pumps has revolutionized the care of patients with type 1 diabetes (T1D). Few data are available regarding the use of diabetes technology use in the pregnant T1D population. This study was conducted to evaluate temporal trends of diabetes technology use and predictors of use among pregnant individuals with TID in the United States from 2009 to 2020.

Study Design

MarketScan Research Databases from 2009 to 2020 were used to identify pregnant individuals with T1D who were and were not using CGM and/or insulin pumps. Joinpoint regression analysis was used to estimate the average annual percent change (AAPC) in diabetes technology use over time. Unadjusted and adjusted log-linear Poisson regression models were developed to assess the associations between the outcomes of CGM and insulin pump use and demographic and clinical predictors. Associations were reported as adjusted risk ratios (ARR) with 95% confidence intervals (CI).

Results

Among 9,201 pregnancies with T1D, CGM use increased from 2.3% in 2009 to 13.7% in 2020 (AAPC: 13.9%; 95% CI: 11.7–17.1), while insulin pump use remained unchanged from 10.9% in 2009 to 11.8% in 2020 (AAPC: −2.4%; 95% CI: −4.4 to 0.4). Medicaid insurance and obesity were associated with a lower likelihood of CGM use and insulin pump use, while a high obstetric comorbidity index score was associated with a higher likelihood of insulin pump use (ARR: 1.26; 95% CI: 1.05–1.51).

Conclusion

From 2009 to 2020, CGM use among pregnant individuals with T1D increased, while insulin pump use remained unchanged. Use varied by patient demographic and clinical factors, most notable for lower likelihood of CGM use and insulin pump use with Medicaid insurance. Although CGM use increased over time, overall CGM use remained lower than expected despite the known benefits of CGM use in improving neonatal outcomes in pregnancies complicated by T1D.

Key Points

  • CGM use in pregnant individuals with T1D increased from 2.3 to 13.7%, but pump use was stable.

  • Medicaid and obesity were associated with lower CGM and pump use in pregnant individuals with T1D.

  • Low CGM use in pregnant T1D individuals highlights barriers and the need for equitable access.

Keywords

continuous glucose monitors - insulin pumps - pregnancy - type 1 diabetes

Supplementary Material



Publication History

Received: 12 December 2024

Accepted: 02 June 2025

Accepted Manuscript online:
03 June 2025

Article published online:
24 June 2025

© 2025. Thieme. All rights reserved.

Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 

  • References

  • 1 Deputy NP, Kim SY, Conrey EJ, Bullard KM. Prevalence and changes in preexisting diabetes and gestational diabetes among women who had a live birth, United States, 2012–2016. MMWR Morb Mortal Wkly Rep 2018; 67 (43) 1201-1207
    CrossrefPubMedSearch in Google Scholar
  • 2 Persson M, Norman M, Hanson U. Obstetric and perinatal outcomes in type 1 diabetic pregnancies: a large, population-based study. Diabetes Care 2009; 32 (11) 2005-2009
    CrossrefPubMedSearch in Google Scholar
  • 3 Murphy HR, Howgate C, O'Keefe J. et al; National Pregnancy in Diabetes (NPID) advisory group. Characteristics and outcomes of pregnant women with type 1 or type 2 diabetes: a 5-year national population-based cohort study. Lancet Diabetes Endocrinol 2021; 9 (03) 153-164
    CrossrefPubMedSearch in Google Scholar
  • 4 American Diabetes Association Professional Practice Committee. Diabetes technology: standards of medical care in diabetes 2024. Diabetes Care 2024; 47 (Suppl. 01) S126-S144
    CrossrefPubMedSearch in Google Scholar
  • 5 Dovc K, Battelino T. Evolution of diabetes technology. Endocrinol Metab Clin North Am 2020; 49 (01) 1-18
    PubMedSearch in Google Scholar
  • 6 Kravarusic J, Aleppo G. Diabetes technology use in adults with type 1 and type 2 diabetes. Endocrinol Metab Clin North Am 2020; 49 (01) 37-55
    PubMedSearch in Google Scholar
  • 7 Feig DS, Donovan LE, Corcoy R. et al; CONCEPTT Collaborative Group. Continuous glucose monitoring in pregnant women with type 1 diabetes (CONCEPT): a multicentre international randomised controlled trial. Lancet 2017; 390 (10110): 2347-2359
    CrossrefPubMedSearch in Google Scholar
  • 8 Murphy HR, Rayman G, Lewis K. et al. Effectiveness of continuous glucose monitoring in pregnant women with diabetes: randomised clinical trial. BMJ 2008; 337: a1680
    CrossrefPubMedSearch in Google Scholar
  • 9 Perez-Nieves M, Juneja R, Fan L, Meadows E, Lage MJ, Eby EL. Trends in US insulin use and glucose monitoring for people with diabetes: 2009–2018. J Diabetes Sci Technol 2022; 16 (06) 1428-1435
    PubMedSearch in Google Scholar
  • 10 Foster NC, Beck RW, Miller KM. et al. State of type 1 diabetes management and outcomes from the T1D Exchange in 2016–2018. Diabetes Technol Ther 2019; 21 (02) 66-72
    CrossrefPubMedSearch in Google Scholar
  • 11 Gerhardsson P, Schwandt A, Witsch M. et al. The SWEET project 10-year benchmarking in 19 countries worldwide is associated with improved HbA1C and increased use of diabetes technology in youth with type 1 diabetes. Diabetes Technol Ther 2021; 23 (07) 491-499
    PubMedSearch in Google Scholar
  • 12 Venkatesh KK, Powe CE, Buschur E. et al. Disparities in continuous glucose monitoring use among women of reproductive age with type 1 diabetes in the T1D exchange. Diabetes Technol Ther 2023; 25 (03) 201-205
    CrossrefPubMedSearch in Google Scholar
  • 13 DeSalvo DJ, Noor N, Xie C. et al. Patient demographics and clinical outcomes among type 1 diabetes patients using continuous glucose monitors: data from T1D exchange real-world observational study. J Diabetes Sci Technol 2023; 17 (02) 322-328
    PubMedSearch in Google Scholar
  • 14 Kanbour S, Jones M, Abusamaan MS. et al. Racial disparities in access and use of diabetes technology among adult patients with type 1 diabetes in a U.S. academic medical center. Diabetes Care 2023; 46 (01) 56-64
    PubMedSearch in Google Scholar
  • 15 Majidi S, Ebekozien O, Noor N. et al; T1D Exchange Quality Improvement Collaborative Study Group. Inequities in health outcomes in children and adults with type 1 diabetes: data from the T1D exchange quality improvement collaborative. Clin Diabetes 2021; 39 (03) 278-283
    PubMedSearch in Google Scholar
  • 16 IBM Watson Health.. IBM MarketScan research databases for life sciences researchers. Accessed December 30, 2022 at: https://www.ibm.com/downloads/cas/0NKLE57Y
    PubMed
  • 17 Chua KP, Lee JM, Conti RM. Out-of-pocket spending for insulin, diabetes-related supplies, and other health care services among privately insured US patients with type 1 diabetes. JAMA Intern Med 2020; 180 (07) 1012-1014
    PubMedSearch in Google Scholar
  • 18 Bateman BT, Mhyre JM, Hernandez-Diaz S. et al. Development of a comorbidity index for use in obstetric patients. Obstet Gynecol 2013; 122 (05) 957-965
    CrossrefPubMedSearch in Google Scholar
  • 19 Metcalfe A, Lix LM, Johnson JA. et al. Validation of an obstetric comorbidity index in an external population. BJOG 2015; 122 (13) 1748-1755
    PubMedSearch in Google Scholar
  • 20 Du R, Ali MM, Sung YS. et al. Maternal comorbidity index and severe maternal morbidity among Medicaid covered pregnant women in a US Southern rural state. J Matern Fetal Neonatal Med 2023; 36 (01) 2167073
    PubMedSearch in Google Scholar
  • 21 Alan Kinlaw. Easy ICD9-to-10 general equivalence mappings. Accessed May 31, 2021 at: https://github.com/alankinlaw/Easy_ICD9-to-10_GEMs_mapping
    PubMed
  • 22 National Cancer Institute. Joinpoint Trend Analysis Software. Accessed March 20, 2021 at: https://surveillance.cancer.gov/joinpoint/
    PubMed
  • 23 National Cancer Institute. Average Annual Percent Change (AAPC) and Confidence Interval. Accessed November 15, 2021 at: https://surveillance.cancer.gov/help/joinpoint/setting-parameters/method-and-parameters-tab/apc-aapc-tau-confidence-intervals
    PubMed
  • 24 Helman S, James-Todd TM, Wang Z. et al. Time trends in pregnancy-related outcomes among women with type 1 diabetes mellitus, 2004-2017. J Perinatol 2020; 40 (08) 1145-1153
    PubMedSearch in Google Scholar
  • 25 Levy CJ, Foster NC, DuBose SN. et al. Changes in device uptake and glycemic control among pregnant women with type 1 diabetes: data from the T1D Exchange. J Diabetes Sci Technol 2021; 15 (06) 1297-1302
    PubMedSearch in Google Scholar
  • 26 Ebekozien O, Mungmode A, Sanchez J. et al. Longitudinal trends in glycemic outcomes and technology use for over 48,000 people with type 1 diabetes (2016–2022) from the T1D exchange quality improvement collaborative. Diabetes Technol Ther 2023; 25 (11) 765-773
    PubMedSearch in Google Scholar
  • 27 Boettcher C, Tittel SR, Meissner T. et al. Sex differences over time for glycemic control, pump use and insulin dose in patients aged 10-40 years with type 1 diabetes: a diabetes registry study. BMJ Open Diabetes Res Care 2021; 9 (02) e002494
    PubMedSearch in Google Scholar
  • 28 van den Boom L, Karges B, Auzanneau M. et al. Temporal trends and contemporary use of insulin pump therapy and glucose monitoring among children, adolescents, and adults with type 1 diabetes between 1995 and 2017. Diabetes Care 2019; 42 (11) 2050-2056
    CrossrefPubMedSearch in Google Scholar
  • 29 Thorius IH, Husemoen LLN, Nordsborg RB. et al. Congenital malformations among offspring of women with type 1 diabetes who use insulin pumps: a prospective cohort study. Diabetologia 2023; 66 (05) 826-836
    PubMedSearch in Google Scholar
  • 30 Kjölhede K, Berntorp K, Kristensen K. et al. Glycemic, maternal and neonatal outcomes in women with type 1 diabetes using continuous glucose monitoring during pregnancy - pump vs multiple daily injections, a secondary analysis of an observational cohort study. Acta Obstet Gynecol Scand 2021; 100 (05) 927-933
    CrossrefPubMedSearch in Google Scholar
  • 31 Kallas-Koeman MM, Kong JM, Klinke JA. et al. Insulin pump use in pregnancy is associated with lower HbA1C without increasing the rate of severe hypoglycaemia or diabetic ketoacidosis in women with type 1 diabetes. Diabetologia 2014; 57 (04) 681-689
    PubMedSearch in Google Scholar
  • 32 American Diabetes Association Professional Practice Committee. Management of diabetes in pregnancy: standards of care in diabetes 2024. Diabetes Care 2024; 47 (Suppl. 01) S282-S294
    CrossrefPubMedSearch in Google Scholar
  • 33 Howe G, Chavis J. Expanding Medicaid access to continuous glucose monitors. Accessed February 1, 2024 at: https://www.chcs.org/media/Expanding-Medicaid-Access-to-Continuous-Glucose-Monitors_011222.pdf
    PubMed
  • 34 Sherr JL, Heinemann L, Fleming GA. et al. Automated insulin delivery: benefits, challenges, and recommendations – a consensus report of the joint diabetes technology working group of the European Association for the Study of Diabetes and the American Diabetes Association. Diabetes Care 2022; 45 (12) 3058-3074
    PubMedSearch in Google Scholar
  • 35 Albert L, Romero A, Capel I. et al. Off-label use of an automated insulin delivery system in pregnant women with type 1 diabetes. Diabetes Res Clin Pract 2023; 202: 110800
    PubMedSearch in Google Scholar
  • 36 Wang XS, Dunlop AD, McKeen JA, Feig DS, Donovan LE. Real-world use of Control-IQ technology automated insulin delivery in pregnancy: a case series with qualitative interviews. Diabet Med 2023; 40 (06) e15086
    PubMedSearch in Google Scholar
  • 37 Sobhani NC, Killion M, Patzek S. Use of open-source automated insulin delivery systems in pregnancies with type 1 diabetes. J Diabetes Sci Technol 2023; 17 (04) 1126-1128
    PubMedSearch in Google Scholar
  • 38 Lemieux P, Yamamoto JM, Donovan LE. Do-it-yourself artificial pancreas system use in pregnant women with type 1 diabetes in a real-world setting: 2 case reports. Can J Diabetes 2021; 45 (08) 804-808.e2
    PubMedSearch in Google Scholar
  • 39 Bukhari K, Malek R. Open-source automated insulin delivery systems for the management of type 1 diabetes during pregnancy. BMJ Case Rep 2021; 14 (09) e243522
    PubMedSearch in Google Scholar
  • 40 Stewart ZA, Wilinska ME, Hartnell S. et al. Closed-loop insulin delivery during pregnancy in women with type 1 diabetes. N Engl J Med 2016; 375 (07) 644-654
    CrossrefPubMedSearch in Google Scholar
  • 41 Lee TTM, Collett C, Bergford S. et al; AiDAPT Collaborative Group. Automated insulin delivery in women with pregnancy complicated by type 1 diabetes. N Engl J Med 2023; 389 (17) 1566-1578
    CrossrefPubMedSearch in Google Scholar