Type 1 diabetes is an autoimmune condition in which the pancreas produces little or no insulin, requiring people to manage their glucose through external insulin for life. More than 121,000 Australians live with the condition, and roughly 3000 new cases are diagnosed each year. Over decades, persistently elevated glucose damages small blood vessels, driving complications such as retinopathy, neuropathy, and kidney disease. Recent Australian data estimate average annual direct healthcare costs of AUD 7084 per person with type 1 diabetes, more than two and a half times the AUD 2789 spent on people without diabetes, and the 2022 Australian National Diabetes Audit identified peripheral neuropathy and retinopathy as the most frequently reported complications, with rates climbing as the duration of disease lengthens.

Automated insulin delivery systems represent the newest generation of diabetes technology. These hybrid closed-loop devices link a continuous glucose monitor to an insulin pump via a control algorithm that adjusts insulin dosing every few minutes, mimicking some of the feedback function of a healthy pancreas. A 2024 consensus statement convened and endorsed by Diabetes Australia and numerous other societies declared automated insulin delivery the standard of care and recommended that all Australians with type 1 diabetes should have access to it. Yet fewer than 20 percent of people with the condition in Australia currently use such systems, largely because of cost and the limited funding arrangements available to adults outside top-tier private health insurance.

The new analysis focused on the MiniMed 780G advanced hybrid closed-loop system and compared it with the combination of multiple daily injections and continuous glucose monitoring. Clinical inputs came from the ADAPT randomized controlled trial, a European study in adults with type 1 diabetes and baseline HbA1c of at least 8.0 percent. In that trial, participants using the MiniMed 780G achieved a mean reduction in HbA1c of 1.54 percentage points from a baseline of 9.04 percent, while those on injections plus glucose monitoring achieved only a 0.20 percentage point reduction. The researchers assumed that intermittently scanned and real-time continuous glucose monitors had equivalent HbA1c efficacy, an assumption supported by published meta-analyses, though the modeling restricted treatment effects to HbA1c differences alone.

The simulation used the IQVIA Core Diabetes Model, an established platform for projecting long-term outcomes in diabetes. The model consists of multiple interdependent Markov sub-models covering both acute events and chronic complications, run through patient-level Monte Carlo simulations with tracker variables allowing the sub-models to interact. Physiological parameters such as HbA1c drive individual event risks and progress naturally over time based on long-term epidemiological studies. The simulated cohort reflected Australian registry data, with a mean baseline age of 43.3 years and a mean diabetes duration of 20.3 years. The base case analysis took a public healthcare payer perspective, captured only direct costs, ran over a 50-year horizon, and applied the 5 percent annual discount rate that Australian health economic guidance requires for future costs and outcomes.

The base case results showed that long-term use of the MiniMed 780G was projected to yield 13.32 quality-adjusted life years compared with 11.81 for injections plus monitoring, a difference of 1.51 quality-adjusted life years. Lifetime direct costs were higher with the technology, at AUD 367,341 versus AUD 317,819, driven mainly by device acquisition and consumable expenses. However, complication costs ran in the opposite direction, falling for users of the automated system because fewer people progressed to diabetes-related damage. The resulting incremental cost-effectiveness ratio was AUD 32,840 per quality-adjusted life year gained, well below the AUD 50,000 per quality-adjusted life year threshold that more than 60 percent of Australian cost-utility analyses published between 1992 and 2022 have assumed, even though Australia has no official willingness-to-pay threshold.

The projected clinical benefits extended across nearly every complication category. Simulated users of the automated system spent 1.15 years longer free of any diabetes-related complication, a 128 percent increase, with the largest gains seen in microvascular outcomes: 9.67 additional years free of macular edema, 8.20 years free of proliferative retinopathy, 7.58 years free of microalbuminuria, 6.25 years free of neuropathy, and 5.78 years free of severe vision loss. These delays translated into meaningful savings, including AUD 18,882 less in ulcer, amputation, and neuropathy costs, AUD 15,323 less in eye complication costs, AUD 8150 less in cardiovascular costs, and AUD 5428 less in renal costs over a lifetime.

Sensitivity analyses underscored how strongly the result depends on the long view. Over shorter horizons of 10 to 15 years, the incremental cost-effectiveness ratio exceeded AUD 50,000 per quality-adjusted life year, likely because many diabetes complications take decades to develop, so the savings and quality-of-life gains from preventing them only accumulate late. The analysis was also sensitive to the inclusion of hypoglycemic event rates and to the quality-of-life benefit associated with reduced fear of hypoglycemia, which the ADAPT trial had quantified. When that fear-related utility benefit of 0.0544 annually for the automated system was removed entirely, the ratio rose to AUD 55,976 per quality-adjusted life year, pushing the result above the conventional threshold. Conversely, adding severe hypoglycemic events and diabetic ketoacidosis lowered the ratio to AUD 19,234 per quality-adjusted life year, since preventing these acute crises avoids expensive emergency care.

A secondary analysis from the societal perspective, which incorporated indirect costs such as lost productivity from absenteeism using the human capital approach, made the case for the technology even stronger. Without hypoglycemia and ketoacidosis included, the societal-perspective ratio was AUD 23,378 per quality-adjusted life year; with those events included, it fell to just AUD 9446. Previous research has shown that even non-severe hypoglycemic episodes impair workplace productivity, and Australian users of advanced glucose technologies report in community surveys that the devices ease limitations on eating, sleeping, exercising, and socializing while improving emotional well-being. Severe hypoglycemic events causing loss of consciousness can also trigger temporary suspension of a person’s driving license in Australia, a consequence that compounds the personal burden beyond anything a cost model can capture.

The authors acknowledge limitations, including the reliance on a European trial, the assumption of equivalent HbA1c efficacy between glucose monitor types, the exclusion of complications not captured in the model such as oral, hearing, and autonomic effects, and the restriction to people with baseline HbA1c above 8.0 percent. Even so, real-world Australian studies, including a multicenter Queensland evaluation showing that starting automated insulin delivery improved time in range and HbA1c, particularly for those with higher baseline levels, support the generalizability of the findings. With the Australian Government’s Insulin Pump Program currently means-tested for people under 21, and Diabetes Australia and a 2024 parliamentary committee report both calling for stepwise expansion of access, the analysis concludes that broader funding of automated insulin delivery for adults with above-target HbA1c would improve long-term outcomes and likely represent an efficient use of healthcare resources.

Subject of Research: Long-term cost-effectiveness of advanced hybrid closed-loop automated insulin delivery versus multiple daily injections with continuous glucose monitoring in Australian adults with type 1 diabetes

Article Title: Long-Term Cost-Effectiveness of an Advanced Hybrid Closed-Loop Automated Insulin Delivery System Versus Multiple Daily Insulin Injections Plus Continuous Glucose Monitoring in Adults with Type 1 Diabetes in Australia

Article References: Glastras, S., Read, M., Ozdemir Saltik, A. Z., Huynh, M., Challis, G., Hill, M., Field, M., Pollock, R., & de Portu, S. (2026). Long-Term Cost-Effectiveness of an Advanced Hybrid Closed-Loop Automated Insulin Delivery System Versus Multiple Daily Insulin Injections Plus Continuous Glucose Monitoring in Adults with Type 1 Diabetes in Australia. Advances in Therapy. https://doi.org/10.1007/s12325-026-03752-8

Image Credits: AI Generated

DOI: 10.1007/s12325-026-03752-8

Keywords: type 1 diabetes, automated insulin delivery, hybrid closed-loop, MiniMed 780G, cost-effectiveness, continuous glucose monitoring, health economics, Australia, HbA1c, quality-adjusted life years, diabetes complications, IQVIA Core Diabetes Model

The protocol, published in Health Science Reports and registered with the international PROSPERO registry, describes a mixed-methods systematic review and meta-analysis that will pull together randomised trials, real-world cohort studies, qualitative interviews and implementation research on hybrid closed-loop systems such as CamAPS FX, Medtronic MiniMed platforms, Tandem Control-IQ and Omnipod 5. What makes the effort timely is the sheer speed of adoption. In England and Wales, the 2025 National Pregnancy in Diabetes Audit recorded that nearly 45 percent of women with type 1 diabetes at 28 weeks of pregnancy were using the CamAPS FX closed-loop system, with another 12 percent on a different hybrid platform. Yet that figure comes from a single publicly funded health system, and the researchers caution it cannot be extrapolated to countries where reimbursement, regulatory approval and clinical workforce differ wildly.

The stakes are high because type 1 diabetes in pregnancy remains stubbornly dangerous despite decades of specialist care. Women with the condition face elevated risks of pre-eclampsia, preterm birth, caesarean delivery, excessively large babies, neonatal hypoglycaemia and admission of their newborns to intensive care. The mothers themselves risk severe hypoglycaemia, diabetic ketoacidosis and progression of retinal and kidney damage. Large national audits continue to report worse outcomes than in the general obstetric population, even as technology use climbs. The core problem is physiological: insulin sensitivity shifts across gestation, glucose variability increases, and the relentless self-management burden falls on women, families and care teams already stretched thin.

Continuous glucose monitoring has transformed how clinicians measure that burden. The metric at the heart of the new review is time in range, specifically the pregnancy-specific target of 3.5 to 7.8 millimoles per litre, a window far tighter than the standard adult range. Landmark studies such as CONCEPTT and subsequent large cohort analyses established that more time in this range and less glucose variability translate directly into fewer large-for-gestational-age births, fewer hypoglycaemic newborns and fewer intensive care admissions. But even sensor-augmented pumps and monitored injection regimens still depend heavily on users and clinicians manually adjusting insulin doses, leaving dangerous highs and lows to persist precisely when insulin requirements are changing fastest.

Automated insulin delivery systems promise to close that gap. These platforms couple a glucose sensor, an insulin pump and an embedded algorithm that continuously modulates insulin delivery in response to sensor readings, adjusting basal rates and, in some systems, delivering automated correction doses. In non-pregnant populations, trials and meta-analyses show such systems increase time in range and reduce time spent dangerously low without clear increases in severe hypoglycaemia or ketoacidosis. Pregnancy, however, is not simply an extension of ordinary type 1 diabetes care. Many commercial algorithms were never designed around pregnancy-specific glucose targets, raising unresolved questions about device suitability, target settings, the best timing for initiation, clinician oversight, use during labour and adaptation to rapidly shifting insulin needs.

The clinical evidence so far is promising but fragmented. Randomised trials including AiDAPT, which tested CamAPS FX, and CRISTAL, which evaluated the MiniMed 780G, have reported improved glycaemic outcomes in selected settings, but they differ in device, comparator, algorithm targets, timing of initiation and support models. Observational cohorts and case series add real-world texture but vary enormously in size, baseline technology use and outcome definitions. The protocol’s authors argue that commercial automated insulin delivery in pregnancy must not be treated as a single homogeneous intervention; the meaning of any pooled result depends on which system was used, when it was started, how it was supported and which outcomes were measured.

That heterogeneity shapes the review’s unusually rigorous methodology. The team will not pool randomised and non-randomised studies together, and pairwise meta-analyses will be run separately for each comparator: closed-loop versus sensor-augmented pump therapy, versus monitored multiple daily injections, and versus clearly defined usual care. The primary outcome, pregnancy-specific time in range, will be harmonised by prioritising second-trimester estimates, with third- and first-trimester values used in descending order of preference. Network meta-analysis is deliberately not planned, because differences in devices, populations, timing and care models could violate the statistical assumptions such analyses require. Rare events such as diabetic ketoacidosis, severe hypoglycaemia and perinatal mortality will be handled with sparse-data methods or synthesised narratively when estimates are unstable.

What truly distinguishes the protocol is its breadth beyond glucose numbers. The review will capture maternal outcomes including hypertensive disorders, retinopathy progression and mode of delivery; neonatal outcomes from birthweight centiles to intensive care admission; and early postpartum outcomes grouped into the first 48 hours, the first two weeks after discharge and out to 12 weeks, a period when breastfeeding, sleep disruption and collapsing insulin requirements create new hazards. Psychosocial measures, including diabetes distress, fear of hypoglycaemia, sleep quality, anxiety and depression, will be extracted with full attention to instrument validation. Crucially, qualitative studies of women’s and clinicians’ lived experiences will be synthesised thematically and then integrated with the quantitative findings through structured side-by-side comparison, so that numbers can be explained, contextualised or challenged by human experience.

Implementation realities also take centre stage. The review will document device and consumable costs, reimbursement arrangements, out-of-pocket expenses, clinician workload, training demands, uptake and retention rates, and reported barriers to equitable access, always tied to the specific jurisdiction and regulatory context of each study. The authors are explicit that access, equity and workload will be treated as descriptive domains, with causal claims made only where study designs genuinely support them. Certainty in the quantitative evidence will be graded using the GRADE framework, while confidence in qualitative findings will be assessed with GRADE-CERQual, allowing the two evidence streams to be weighed on their own terms.

The anticipated limitations are candidly acknowledged: likely few randomised trials, inconsistent definitions for neonatal hypoglycaemia and device-related adverse events, off-label use of systems with non-pregnancy-specific settings, and qualitative evidence skewed toward specialist early-adopter centres. Yet the strengths are substantial, including prospective registration, alignment with PRISMA-P reporting standards, no language restrictions on searches extending back to 2010, and dual independent screening and appraisal at every stage. When the completed review arrives, it should give clinicians, guideline developers and health services something the field currently lacks: a clear, device-specific, globally honest account of whether automated insulin delivery improves diabetic pregnancies, and what it takes, technically, financially and organisationally, to deliver that benefit safely and equitably.

Subject of Research: A mixed-methods systematic review protocol evaluating commercial automated insulin delivery systems in type 1 diabetes pregnancy

Article Title: Commercial Automated Insulin Delivery Systems in Type 1 Diabetes Pregnancy: Protocol for a Mixed‐Methods Systematic Review and Meta‐Analysis of Glycaemic, Perinatal, Psychosocial and Implementation Outcomes

Article References: Li, J., Sheklabadi, E., Goldstein, R. F., Ng, A. H., Teede, H., & Naderpoor, N. (2026). Commercial Automated Insulin Delivery Systems in Type 1 Diabetes Pregnancy: Protocol for a Mixed‐Methods Systematic Review and Meta‐Analysis of Glycaemic, Perinatal, Psychosocial and Implementation Outcomes. Endocrinology, Diabetes & Metabolism, 9(5), Article e70309. https://doi.org/10.1002/edm2.70309

Image Credits: AI Generated

DOI: 10.1002/edm2.70309

Keywords: type 1 diabetes, pregnancy, automated insulin delivery, hybrid closed-loop, continuous glucose monitoring, time in range, perinatal outcomes, CamAPS FX, systematic review, meta-analysis, health technology, implementation science