Gestational diabetes mellitus screening and diagnosis: A prospective randomised controlled trial comparing costs of one-step and two-step methods

Division of Endocrinology and Metabolism, Department of Medicine and Obstetrics and Gynecology, Faculty of Medicine, McGill University Health Center, 687 Pine Avenue West, Montreal, QC, Canada.
BJOG An International Journal of Obstetrics & Gynaecology (Impact Factor: 3.45). 03/2010; 117(4):407-15. DOI: 10.1111/j.1471-0528.2009.02475.x
Source: PubMed


To conduct a cost minimisation analysis of three methods of gestational diabetes mellitus (GDM) screening and diagnosis.
Prospective randomised controlled trial.
University teaching hospital.
Pregnant women (n = 1594) presenting for GDM screening.
Women presenting for GDM screening, who consented to participate, were randomised to GR1 [1-hour, 50-g glucose screen (GS) +/- 3-hour, 100-g oral glucose tolerance test (OGTT)], GR2 (50-g GS +/- 2-hour, 75-g OGTT) or GR3 (2-hour, 75-g OGTT). Demographics, health and time/travel cost information were assessed for each glucose testing visit.
Costs (direct and indirect) and prevalence of GDM diagnosis.
The direct sampling costs of the glucose tests per woman were as follows: GS, CAN$12.57; 75-g OGTT, $36.10; 100-g OGTT, CAN$48.13. Among women in the two-step method groups diagnosed with GDM, 39% of the GR1 and 61% of the GR2 groups were diagnosed at the first step by GS > or = 10.3 mmol/l, according to the Canadian Diabetes Association recommendations, contributing to a lower total cost in these groups. The total costs per woman screened were as follows: GR1, CAN$91.61; GR2, CAN$89.03; GR3, CAN$108.38. The GDM prevalence was similar (3.7%, 3.7% and 3.6%, respectively). The higher costs of GR3 were related to more blood draws and the time required for all women to undergo the 2-hour OGTT.
Careful consideration should be given to an internationally recommended method of universal screening for GDM which minimises the burden and cost for individual women and the healthcare system, yet provides diagnostic efficacy. The two-step method (GS +/- OGTT) accomplished this better than the one-step method (75-g OGTT).

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Available from: Sara J Meltzer, Sep 15, 2014
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    • "Thus cost analysis is a method of measuring the use of resources and describing the allocation of costs within the health care sector, and may help to create more cost-effective treatment procedures. To the best of our knowledge, there are no reports on the GDM risk group comparing the pre- and postnatal health care costs for women with GDM, and for women without a GDM diagnosis, but there are several studies related to the costs of screening [18-20]. We have previously reported the outcomes of GDM prevention in a cluster-randomised trial [21,22]. "
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    ABSTRACT: Background The costs of gestational diabetes mellitus (GDM) screening have been frequently reported, but total GDM-related health care costs compared to the health care costs of women without GDM have not been reported. The aim of this study was to analyse GDM-related health care costs among women with an elevated risk of GDM. Methods The study was based on a cluster-randomised GDM prevention trial (N = 848) carried out at maternity clinics, combined with data from the Finnish Medical Birth Register and Care Registers for Social Welfare and Health Care. Costs of outpatient visits to primary and secondary care, cost of inpatient hospital care before and after delivery, the use of insulin, delivery costs and babies’ stay in the neonatal intensive care unit were analysed. Women who developed GDM were compared to those who were not diagnosed with GDM. Results Total mean health care costs adjusted for age, body mass index and education were 25.1% higher among women diagnosed with GDM (€6,432 vs. €5,143, p < 0.001) than among women without GDM. The cost of inpatient visits was 44% higher and neonatal intensive care unit use was 49% higher in the GDM group than among women without GDM. The delivery costs were the largest single component in both groups. Conclusions A confirmed GDM diagnosis was associated with a significant increase in total health care costs. Effective lifestyle counselling by primary health care providers may offer a means of reducing the high costs of secondary care.
    BMC Pregnancy and Childbirth 07/2012; 12(1):71. DOI:10.1186/1471-2393-12-71 · 2.19 Impact Factor
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    ABSTRACT: Aims/hypothesis It is currently not clear how to construct a time- and cost-effective screening strategy for gestational diabetes mellitus (GDM). Thus, we elaborated a simple screening algorithm combining (1) fasting plasma glucose (FPG) measurement; and (2) a multivariable risk estimation model focused on individuals with normal FPG levels to decide if a further OGTT is indicated. Methods A total of 1,336 women were prospectively screened for several risk factors for GDM within a multicentre study conducted in Austria. Of 714 women (53.4%) who developed GDM using recent diagnostic guidelines, 461 were sufficiently screened with FPG. A risk prediction score was finally developed using data from the remaining 253 women with GDM and 622 healthy women. The screening algorithm was validated with a further 258 pregnant women. Results A risk estimation model including history of GDM, glycosuria, family history of diabetes, age, preconception dyslipidaemia and ethnic origin, in addition to FPG, was accurate for detecting GDM in participants with normal FPG. Including an FPG pretest, the receiver operating characteristic AUC of the screening algorithm was 0.90 (95% CI 0.88, 0.91). A cut-off value of 0.20 was able to differentiate between low and intermediate risk for GDM with a high sensitivity. Comparable results were seen with the validation cohort. Moreover, we demonstrated an independent association between values derived from the risk estimation and macrosomia in offspring (OR 3.03, 95% CI 1.79, 5.19, p < 0.001). Conclusions/interpretation This study demonstrates a new concept for accurate but cheap GDM screening. This approach should be further evaluated in different populations to ensure an optimised diagnostic algorithm.
    Diabetologia 09/2012; 55(12). DOI:10.1007/s00125-012-2726-7 · 6.67 Impact Factor
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