Health service use and health system costs associated with diabetes during pregnancy in Australia

Healthcare costs attributable to diabetes in pregnancy: A cost of illness study in Tasmania, Australia

AIMS

To estimate the direct costs during the prenatal, delivery and postpartum periods in mothers with diabetes in pregnancy, compared to those without.

METHODS

This study used a population-based dataset from 2004 to 2017, including 57,090 people with diabetes and 114,179 people without diabetes in Tasmania, Australia. Based on diagnostic codes, delivery episodes with gestational diabetes mellitus (GDM) were identified and matched with delivery episodes without diabetes in pregnancy. A group of delivery episodes with pre-existing diabetes was identified for comparison. Hospitalisation, emergency department and pathology costs of these groups were calculated and adjusted to 2020-2021 Australian dollars.

RESULTS

There were 2774 delivery episodes with GDM, 2774 delivery episodes without diabetes and 237 delivery episodes with pre-existing diabetes identified. Across the 24-month period, the pre-existing diabetes group required the highest costs, totalling $23,536/person. This was followed by the GDM ($13,210/person), and the no diabetes group ($11,167/person). The incremental costs of GDM over the no diabetes group were $890 (95% CI 635; 1160) in the year preceding delivery; $812 (616; 1031) within the delivery period and $341 (110; 582) in the year following delivery (p < 0.05). Within the year preceding delivery, the incremental costs in the prenatal period were $803 (579; 1058) (p < 0.05). Within the year following delivery, the incremental costs in the postpartum period were $137 (55; 238) (p < 0.05).

CONCLUSIONS

Our results emphasised the importance of proper management of diabetes in pregnancy in the prenatal and postpartum periods and highlighted the significance of screening and preventative strategies for diabetes in pregnancy.

Motivational factors for dietary intake behavior in gestational diabetes mellitus: A cross-sectional study

Context

Decision-making behavior pertains to the cognitive process where a patient evaluates the advantages and disadvantages of health-related decisions, taking into account their personal preferences, values, and cognitive factors. This behavior is central to the successful implementation of clinical care. Effective decision-making enhances an individual's or organization's response to challenges and opportunities, improves problem-solving capabilities, reduces risks and uncertainties, and facilitates the attainment of desired outcomes.

Objective

The goal of this study was to investigate the current status of dietary choice decision-making in gestational diabetes mellitus and to analyze its influencing factors, and then to find the determining factors and give targeted nursing interventions in order to improve the dietary decision-making ability of gestational diabetes mellitus patients and further standardize their dietary patterns.

Methods

A cross-sectional research design was employed in this study. Convenience sampling was utilized to survey 539 GDM patients attending the obstetrics outpatient clinic and obstetrics ward of a tertiary hospital in Wuxi City, China, from March 2023 to July 2023. The survey instruments used were the General Information Questionnaire, the Motivation to Protect Pregnant Women with Gestational Diabetes Mellitus Dietary Intake Questionnaire, and the Conflict in Decision-Making Scale.

Results

The findings were derived from data collected from 539 GDM cases. The participants' ages ranged from 19 to 52 years, with a mean age of 31.53 ± 4.37 years. The scores for GDM disease perceived susceptibility were 15.200 ± 3.481, disease perceived severity 18.455 ± 4.670, internal reward 13.226 ± 4.275, external reward 8.278 ± 2.923, response efficacy 15.078 ± 3.889, self-efficacy 18.952 ± 4.800, cost of response 14.540 ± 5.227, and decision conflict questionnaire score 70.96 ± 11.78.

Conclusions

The study revealed that GDM patients exhibited a moderate level of decision-making dilemma. Notably, the patients' perceived susceptibility and severity of the disease, along with their response efficacy and self-efficacy, positively influenced their dietary decision-making abilities. Specifically, enhancing patients' awareness of their condition and boosting their self-efficacy significantly improved their decision-making capabilities. Conversely, internal and external rewards, as well as the cost of response, exerted a negative impact on GDM patients' decision-making abilities. Therefore, it is imperative to mitigate potential barriers in GDM patients' dietary intake behaviors, thereby enhancing their decision-making skills related to dietary intake.

Protocol for cost-effectiveness analysis of a randomised trial of mHealth coaching (Bump2Baby and Me) compared with usual care for healthy gestational weight gain and postnatal outcomes in at-risk women and their offspring in the UK, Australia, Ireland and Spain

INTRODUCTION

Gestational diabetes mellitus and overweight are associated with an increased likelihood of complications during birth and for the newborn baby. These complications lead to increased immediate and long-term healthcare costs as well as reduced health and well-being in women and infants. This protocol presents the health economic evaluation to investigate the cost-effectiveness of Bump2Baby and Me (B2B&Me), which is a health coaching intervention delivered via smartphone to women at risk of gestational diabetes.

METHODS AND ANALYSIS

Using data from the B2B&Me randomised controlled trial, this economic evaluation compares costs and health effects between the intervention and control group as an incremental cost-effectiveness ratio. Direct healthcare costs, costs of pharmaceuticals and intervention costs will be included in the analysis, body weight and quality-adjusted life-years for the mother will serve as the effect outcomes. To investigate the long-term cost-effectiveness of the trial, a Markov model will be employed. Deterministic and probabilistic sensitivity analysis will be employed.

ETHICS AND DISSEMINATION

The National Maternity Hospital Human Research and Ethics Committee was the primary approval site (EC18.2020) with approvals from University College Dublin HREC-Sciences (LS-E-20-150-OReilly), Junta de Andalucia CEIM/CEI Provincial de Granada (2087-M1-22), Monash Health HREC (RES-20-0000-892A) and National Health Service Health Research Authority and Health and Care Research Wales (HCRW) (21/WA/0022). The results from the analysis will be disseminated in scientific papers, through conference presentations and through different channels for communication within the project.

TRIAL REGISTRATION NUMBER

ACTRN12620001240932.

Associations of a current Australian model of dietetic care for women diagnosed with gestational diabetes and maternal and neonatal health outcomes

BACKGROUND

Gestational diabetes mellitus (GDM) is a significant public health burden in Australia. Subsequent strain on healthcare systems is widespread and current models of care may not be adequate to provide optimal healthcare delivery. This study aimed to assess a current model of dietetic care with maternal and neonatal outcomes.

METHODS

Hospital medical record data from The Women's Hospital, Melbourne, for women with GDM (n = 1,185) (July 2105-May 2017) was retrospectively analysed. Adjusted linear and logistic regression were used to analyse associations between the number of dietitian consultations and maternal and neonatal health outcomes.

RESULTS

Half of all women (50%) received two consultations with a dietitian. 19% of women received three or more consultations and of these women, almost twice as many were managed by medical nutrition therapy (MNT) and pharmacotherapy (66%) compared with MNT alone (34%). Higher odds of any maternal complication among women receiving 3 + consultations compared to those receiving zero (OR = 2.33 [95% CI: 1.23, 4.41], p = 0.009), one (OR = 1.80 [95% CI: 1.09, 2.98], p = 0.02), or two (OR = 1.65 [95% CI: 1.04, 2.60], p = 0.03) consultations were observed. Lower odds of infant admission to the Neonatal Intensive Care Unit (NICU) were observed among women receiving one (OR = 0.38 [95% CI: 0.18, 0.78], p = 0.008), two (OR = 0.37 [95% CI: 15 0.19, 0.71], p = 0.003), or three + consultations (OR = 0.43 [95% CI: 0.21, 0.88], p = 0.02), compared to no consultations.

CONCLUSION

The optimal schedule of dietitian consultations for women with GDM in Australia remains largely unclear. Alternate delivery of education for women with GDM such as telehealth and utilisation of digital platforms may assist relieving pressures on the healthcare system and ensure optimal care for women during pregnancy.

Long-term cost-effectiveness of implementing a lifestyle intervention during pregnancy to reduce the incidence of gestational diabetes and type 2 diabetes

AIMS/HYPOTHESIS

The aim of this study was to determine the long-term cost-effectiveness and return on investment of implementing a structured lifestyle intervention to reduce excessive gestational weight gain and associated incidence of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus.

METHODS

A decision-analytic Markov model was used to compare the health and cost-effectiveness outcomes for (1) a structured lifestyle intervention during pregnancy to prevent GDM and subsequent type 2 diabetes; and (2) current usual antenatal care. Life table modelling was used to capture type 2 diabetes morbidity, mortality and quality-adjusted life years over a lifetime horizon for all women giving birth in Australia. Costs incorporated both healthcare and societal perspectives. The intervention effect was derived from published meta-analyses. Deterministic and probabilistic sensitivity analyses were used to capture the impact of uncertainty in the model.

RESULTS

The model projected a 10% reduction in the number of women subsequently diagnosed with type 2 diabetes through implementation of the lifestyle intervention compared with current usual care. The total net incremental cost of intervention was approximately AU$70 million, and the cost savings from the reduction in costs of antenatal care for GDM, birth complications and type 2 diabetes management were approximately AU$85 million. The intervention was dominant (cost-saving) compared with usual care from a healthcare perspective, and returned AU$1.22 (95% CI 0.53, 2.13) per dollar invested. The results were robust to sensitivity analysis, and remained cost-saving or highly cost-effective in each of the scenarios explored.

CONCLUSIONS/INTERPRETATION

This study demonstrates significant cost savings from implementation of a structured lifestyle intervention during pregnancy, due to a reduction in adverse health outcomes for women during both the perinatal period and over their lifetime.

Web-Based Interventions for Pregnant Women With Gestational Diabetes Mellitus: Systematic Review and Meta-analysis

BACKGROUND

Effective management of gestational diabetes mellitus (GDM) is essential because it is one of the most prevalent diseases during pregnancy, and the consequent condition maternal hyperglycemia is closely related to considerable short- and long-term maternal and neonatal complications. Web-based interventions (WBIs), defined as therapeutic interventions offered via the web, have been implemented to assist in managing GDM owing to their advantages of high accessibility and efficiency, but findings across relevant studies are inconsistent.

OBJECTIVE

This systematic review and meta-analysis aimed to evaluate the effectiveness of WBIs on glycemic control among pregnant women with GDM; examine whether specific types of intervention interactivity, format, and technology have beneficial effects on maternal glycemic control; and comprehensively assess the efficacy of WBIs in maternal behavioral outcomes, cognitive and attitudinal outcomes, mental health, maternal and neonatal clinical outcomes, and medical service use and costs among pregnant women with GDM.

METHODS

PubMed, Embase, Cochrane Library, Web of Science, CINAHL, and PsycINFO were searched from their respective inception to November 19, 2022, to identify relevant randomized controlled trials and controlled clinical trials. The methodological quality of the included studies was assessed using the Effective Public Health Practice Project tool. Where possible, the data for all outcomes were meta-analyzed using the Stata software (version 12.0; StataCorp). Overall, 3 subgroup analyses and post hoc sensitivity analyses of maternal glycemic control parameters were performed.

RESULTS

Overall, 25 publications arising from 21 randomized controlled trials and controlled clinical trials were included. The overall meta-analyses on glycemic control parameters demonstrated that WBIs could significantly improve fasting blood glucose (standardized mean difference=-1.764, 95% CI -2.972 to -0.557; P=.004) and 2-hour postprandial blood glucose (standardized mean difference=-1.433, 95% CI -2.561 to -0.304; P=.01) compared with the control group, whereas no significant effect was found on glycated hemoglobin and 1-hour postprandial blood glucose. The results of the subgroup analyses indicated that mobile app-delivered interventions with a personalized format and interactive function showed more beneficial effects on maternal glycemic control. Moreover, WBIs could significantly enhance compliance with the self-monitoring of blood glucose; increase the rate of normal vaginal delivery; and decrease the chance of emergency cesarean, admission to the neonatal intensive care unit, and composite neonatal complications. GDM knowledge, risk perception of the disease, self-efficacy, satisfaction with care, and medical service use of the participants in the WBI group were also improved compared with the control group. However, the effectiveness of WBIs on other secondary outcomes was either nonsignificant or uncertain.

CONCLUSIONS

WBIs are a promising approach to GDM management. Personalized, interactive, and mobile app-delivered interventions seem more worthy of being recommended for future clinical practice. Further high-quality studies are required to verify these findings before making broad recommendations.

TRIAL REGISTRATION

PROSPERO CRD42022296625; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=296625.

Addressing Obesity in Preconception, Pregnancy, and Postpartum: A Review of the Literature

PURPOSE OF REVIEW

Reproductive-aged women (aged 19 to 50 years) are a key population warranting focused research for the prevention of overweight and obesity. This review highlights the importance of addressing weight before, during and after pregnancy.

RECENT FINDINGS

Obesity decreases fertility during the preconception period; increases the risk of adverse pregnancy outcomes including gestational diabetes, pre-eclampsia and caesarean section and postpartum weight retention; and increases the long-term health risks for both the mother and offspring. Despite overwhelming efficacy evidence on solutions, there are significant implementation gaps in translating this evidence into pragmatic models of care and real-world solutions. Interventions during preconception, pregnancy and postpartum are likely to be cost-effective or cost-saving, with future investigation needed in the preconception and postpartum period. International clinical guidelines and public health policies are needed for a concerted effort to prevent unhealthy weight gain in these life stages and to reverse the significant adverse health outcomes for women and the next generation.

Trends in hospitalizations and emergency department visits among women with hyperglycemia in pregnancy between 2008 and 2017 in Taiwan

INTRODUCTION

We investigated health service utilization, including hospitalizations and emergency department visits, for women with hyperglycemia in pregnancy between 2008 and 2017 in Taiwan.

METHODS

Data from the Health and Welfare Data Science Center were used to conduct this nationwide population-based study. We identified pregnant women and the date of childbirth according to Birth Certificate Applications from 2007 to 2018. The study population was divided into four groups: known DM, newly diagnosed DM, GDM, and no DM/GDM. To assess quality of healthcare during the gestation period, trends in 30-day readmission rate, number of emergency department visits/hospitalizations per 100 childbirths, and length of hospital stay from 2008 to 2017 were examined.

RESULTS

A total of 1830511 childbirths and 990569 hospitalizations were identified for analyses. Between 2008 and 2017, women with hyperglycemia in pregnancy (known DM, newly diagnosed DM, and GDM) had a higher rate of hospitalization, a longer length of hospital stay, and higher rates of various maternal and fetal outcomes, compared with women with no DM/GDM. Nevertheless, the differences between women with GDM and those with no DM/GDM in the aforementioned outcome measures were modest. Women with GDM had a modest decrease in the 30-day readmission rate (p for trend 0.046) with no significant difference in the number of emergency department visits during the study period.

DISCUSSION

Our findings provide evidence of the quality of healthcare for women with GDM between 2008 and 2017 in Taiwan.

Projected Return on Investment From Implementation of a Lifestyle Intervention to Reduce Adverse Pregnancy Outcomes

IMPORTANCE

Structured antenatal diet and physical activity interventions have been shown to be associated with reduced adverse pregnancy outcomes and recommended to be routinely offered to all pregnant women. The health cost implications of population-level implementation are unclear.

OBJECTIVE

To estimate the budget impact associated with integrating structured diet and physical activity interventions into routine antenatal care.

DESIGN, SETTING, AND PARTICIPANTS

This economic evaluation was conducted from the perspective of Australian health funders. An open-source decision-tree model was constructed to compare the projected budget outcomes of implementing lifestyle intervention vs usual care. Scenario, deterministic, and probabilistic sensitivity analysis were completed. The study setting was Australian health services, and the study population was all Australian women projected to give birth in the years 2022 to 2026 (approximately 330 000 per year).

INTERVENTIONS

Structured diet and physical activity intervention provided by trained health professionals, integrated into routine antenatal care. Comparator was usual care, which currently in Australia does not include routine structured lifestyle interventions.

MAIN OUTCOMES AND MEASURES

Return on investment (ROI) ratio for lifestyle intervention (cost of intervention divided by cost savings attributable to reduced maternal and infant adverse events) from the perspective of Australian health care funders. Adverse events were obtained from a published meta-analysis and population data. Costs were estimated from aggregate trial data and clinical pathways and valued at the year incurred.

RESULTS

Intervention offered an ROI ratio of 4.75 over the 5-year program; hence every Australian dollar spent on implementation produced an estimated return of A$4.75. The projected total 5-year intervention cost was A$205 million ($151 million), with cost offsets (from reduced incidence of adverse pregnancy outcomes) of A$1022 million ($755 million), and health budget savings of A$807 million (95% CI, A$129 million to A$1639 million) ($596 million [95% CI, $95 million to $1211 million]); 93.3% of the 10 000 iterations were within cost saving, and results were robust to scenario and sensitivity analyses.

CONCLUSIONS AND RELEVANCE

This economic evaluation found that providing access to structured diet and physical activity lifestyle interventions for all pregnant Australian women was estimated to provide strong return on investment for health funders. The open-source model developed can be used by other jurisdictions and health services to explore cost implications of implementation within their patient population.

Discussion on Health Service System of Mobile Medical Institutions Based on Internet of Things and Cloud Computing

Because modern human beings pay more and more attention to physical health, and there are many problems in the traditional medical service system, human beings have a higher and higher voice for the new medical model. At present, there are many researches on the application of modern science and technology to put forward solutions to medical development, but they generally pay attention to some details and ignore the construction of the whole medical service system. In order to solve the problems of low efficiency of the traditional medical model, difficult communication between doctors and patients, unreasonable allocation of medical resources, and so on, this article proposes establishing a perfect medical and health service system. First, the correlation functions are used, such as cosine correlation, to calculate the correlation of various medical products, and then the correlation measurement methods of cloud computing and the Internet of Things are used to realize the network connection of smart medical equipment, efficiently store, calculate and analyze health data, and realize online outpatient services, health file management, data analysis, and other functions. Then, the energy consumption formula of the wireless transceiver was used to reduce the resource loss in the operation of the system. Then, we use the questionnaire to understand the current situation of mobile medical and put forward improvement suggestions. This article also scores the performance of the system. The experimental results show that the performance rating of traditional medical institutions is B, while the model rating of mobile medical institutions is a, and the efficiency is optimized by 4.42%.