Emerging technologies, pharmacology and therapeutics••

FreeStyle Libre Flash Glucose Monitoring system for people with type 1 diabetes in the UK: a budget impact analysis

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Abstract

Introduction This study aims to estimate the budget impact of increased uptake of the FreeStyle Libre Flash Glucose Monitoring system in people with type 1 diabetes mellitus (T1DM) in the UK.

Research design and methods A budget impact model was developed, applying real-world data collected in the Association of British Clinical Diabetologists (ABCD) FreeStyle Libre Nationwide Audit. Costs of diabetes glucose monitoring in a T1DM population (n=1790) using self-monitoring of blood glucose (SMBG) or the FreeStyle Libre system were compared with a scenario with increased use of the FreeStyle Libre system.

Results The ABCD audit demonstrates FreeStyle Libre system use reduces diabetes-related resource utilization. The cost analysis found that higher acquisition costs are offset by healthcare costs avoided (difference £168 per patient per year (PPPY)). Total costs were £1116 PPPY with FreeStyle Libre system compared with £948 PPPY with SMBG. In an average-sized UK local health economy, increasing FreeStyle Libre system uptake from 30% to 50% increased costs by 3.4% (£1 787 345–£1 847 618) and when increased to 70% increased by a further 3.3%.

Conclusion Increased uptake of the FreeStyle Libre system in the T1DM population marginally increases the cost to UK health economies and offers many system benefits.

Significance of this study

What is already known about this subject?

The Association of British Clinical Diabetologists (ABCD) set up a nationwide audit to study the effect of the FreeStyle Libre system on glycemic control, hypoglycemia, diabetes-related distress, and resource utilization.
The audit demonstrated the FreeStyle Libre system use is associated with significantly improved glycemic control, hypoglycemia awareness and reduction in hospital admission.

What are the new findings?

This analysis quantifies the budget impact of widespread adoption of the FreeStyle Libre system in type 1 diabetes mellitus populations from a local UK health economy’s perspective.
Higher acquisition costs for FreeStyle Libre system are partially off-set by reduced healthcare utilization.
In an average-sized local health economy in the UK, increasing the proportion of people with T1DM using the FreeStyle Libre system from 30% in year 1 to 70% over 3 years is expected to result in a 3.4% and 3.3% year-on-year increase in glucose monitoring and diabetes-related healthcare costs for this population.

How might these results change the focus of research or clinical practice?

The results are relevant to current decision making for UK local health economy budget holders.
Widespread adoption of the FreeStyle Libre system in T1DM populations offers many benefits and has a relatively small budget impact compared with the total cost of glucose management.

Introduction

Improved glycemic control, facilitated by effective blood glucose monitoring improves acute outcomes in type 1 diabetes mellitus (T1DM) by reducing the risk of hypoglycemia and severe hypoglycemic events (SHE),1 as well as longer term outcomes such as slowing down disease progression of retinopathy, nephropathy and other diabetes endpoints.2 Self-monitoring of blood glucose (SMBG), or ‘finger-prick’ testing, has been the standard of care for people with T1DM. However, the introduction of new technology is changing the standard approach to glucose monitoring.3 Traditional continuous glucose monitoring (CGM) is demonstrated to improve glycemic control and is increasingly used in diabetes management.4 However, high cost has limited widespread adoption, and therefore, traditional CGM is mainly recommended in the UK to adults with T1DM who have problematic hypoglycemia (National Institute for Health and Care Excellence (NICE)).5

The FreeStyle Libre system (Abbott Diabetes Care, Witney, Oxon, UK), a sensor-based glucose monitoring system, is convenient and easy to use and improves the frequency of glucose monitoring relative to SMBG.6 7 Furthermore, it provides data on time in range, estimated glycated hemoglobin (HbA1c) and time below range as well as other measures. This enables informed discussion between people with diabetes and their clinicians about glucose management. The addition of digital communication tools (LibreView), helps clinicians risk-stratify patients, enabling clinicians to review glucose data in the cloud. This potentially minimizes the need for face-to-face contact with those considered to be lower risk through remote assessment.8 In contrast to traditional CGM, the user must scan the sensor to access glucose data, the system does not have alarms, and has lower acquisition costs. It is indicated for measuring interstitial fluid glucose levels in people age 4 years and older with diabetes mellitus, including pregnant women and is designed to replace SMBG testing in the self-management of diabetes.

In 2017, the FreeStyle Libre system was listed on the National Health Service (NHS) business services authority Drug Tariff for England and Wales, making it available to people with diabetes in the UK.9 In 2020, it is being used by over 30% of the T1DM population in England (unpublished internal market report provided by IQVIA). The clinical and patient benefits of FreeStyle Libre system have been demonstrated in two meta-analyses, of clinical studies and real-world evidence,10 11 two randomized controlled trials (RCTs) in a T1DM population (NCT02232698 (IMPACT))6 and in T2DM populations (NCT02082184 (REPLACE))7 12 as well as a single-arm study in younger people with diabetes (NCT02821117 (SELFY))13 and several large real-world studies.14–18

The ABCD nationwide audit was set-up to assess the patterns of use of FreeStyle Libre system and to study its effect on glycemic control, hypoglycemia, diabetes-related distress, and hospital admissions due to hypoglycemia and hyperglycemia/diabetic ketoacidosis (DKA).15 The study commenced in November 2017 and involved clinicians from 102 NHS hospitals in the UK for which they were asked to submit user data collected during routine clinical care. Data collected included baseline pre-Freestyle Libre system demographics, source of funding, previous structured diabetes education completion, HbA1c values from the previous 12 months, Gold score (to assess hypoglycemia awareness), severe hypoglycemia, paramedic callouts, and hospital admissions due to hypoglycemia, hyperglycemia, and DKA over the previous 12 months. The objective of the current study is to estimate the budget impact of more widespread adoption of the FreeStyle Libre system from a local health economy’s perspective in the UK by applying the outcome data reported in the ABCD nationwide audit.

Method

Analytical methods

A budget impact model was developed in Microsoft Excel to calculate the net difference in costs per patient and total budget impact over a 3-year time horizon, comparing the FreeStyle Libre system to SMBG. Traditional CGM was excluded from the analysis because data on traditional CGM were not captured in the ABCD audit. Included in the analysis were the acquisition costs, costs associated with SHE, DKA events, and cost savings from a reduction in HbA1c. The change in resource utilization with the FreeStyle Libre system compared with SMBG was sourced from the ABCD nationwide audit, where the people included in the ABCD audit are a subgroup of all T1DM populations defined by the NHS funding criteria and those able to self-fund.19 All costs are reported in 2019 Great British pounds. Unit costs were sourced from either 2018/2019 or 2019/2020 databases or 2019 list prices, therefore no cost inflation was applied. The budget impact analysis applied FreeStyle Libre system uptake assumptions to estimate total costs, multiplying uptake by the cost per person using the FreeStyle Libre system and SMBG.

Budget impact model inputs

The analysis considered a hypothetical population of 1790 people with T1DM, which represents the mean number of people with T1DM across all clinical commissioning groups, representing local health economies in England.18 In the base-case, parameters for the rate of SHE events, DKA events and change in HbA1c for the FreeStyle Libre system and SMBG were sourced using the most up to date, previously unpublished, data from ABCD audit and are listed in table 1. For post-FreeStyle Libre system use, 7-month data were applied and prorated to estimate annual outcomes. While 7.5 months’ follow-up data have been published on 3182 participants,13 more recent, unpublished data in a larger cohort (n=4250) were applied. The global COVID-19 pandemic has limited the number of patients with 12-month follow-up data at the time of this publication due to the disruption to planned follow-ups.8 The demographic characteristics of the 4250 participants with 7-month follow-up data are similar to the baseline data of participants without follow-up. The mean age of those with 7-month follow-up was 46.9 (±15.3), 50% were female and the mean pre-FreeStyle Libre HbA1c was 68.1 (±16.3) (mmol/mol). Further details are provided in the online supplemental table 1.

Table 1

Model parameters

All unit costs applied in the model are reported in table 1. Acquisition costs for the FreeStyle Libre system were obtained from NHS tariff databases.7 Unit costs for SMBG testing are the average of top 1o strips used in the UK calculated from IQVIA prescribing data (Internal market report provided by IQVIA). The number of tests strips per day with SMBG was sourced from IMPACT, a multicenter RCTs of the FreeStyle Libre in T1DM.6 The cost of an ambulance callout and admission for SHE and DKA events were sourced from the NHS reference cost and tariff data collection for 2018/2019, respectively.20 21

The cost associated with each incremental reduction in HbA1c was sourced from a study that estimated the costs associated with microvascular and macrovascular complications with different HbA1c levels using the diabetes CORE model. It reports the cost avoided from a UK payer perspective in 5-year periods,22 stratified by baseline HbA1c. The costs for the first 5-year period reported were annualized to a 1-year basis.

The budget impact analysis evaluates a scenario where the FreeStyle Libre system would replace a proportion of SMBG use in T1DM adults within 3 years from the perspective of a UK local health economy (using hypothetical population size of 1790). In year 1, 30% of the T1DM population are assumed to use the FreeStyle Libre system and the remaining 70% use SMBG, reflecting estimated trends in 2020.23 In years 2 and 3, uptake of the FreeStyle Libre system is assumed to increase to 50% and 70% respectively, with the remaining population using SMBG.

Sensitivity analysis

One-way sensitivity analysis was performed on all model parameters to investigate the sensitivity of the cost-effectiveness model result to variations in each of the parameter values. Where CIs were not appropriate, we varied the parameters by ±25% (refer to table 1).

In addition, threshold analysis varied the number SMBG tests per day to consider a low estimate of four tests per day and identify the SMBG test rate per day rate required to achieve cost-neutrality.

Subgroup analysis

The results from the ABCD nationwide audit found that the reduction in HbA1c was greater among people with a higher baseline HbA1c. The impact of this was considered in a subgroup analysis comparing the FreeStyle Libre system with SMBG reporting the cost-per patient treated in people with T1DM with higher baseline HbA1c.

Results

Per patient cost analysis

In all years, the FreeStyle Libre system is marginally more expensive than SMBG when testing 5.6 time per day because higher acquisition costs are partly offset by cost savings from reduced resource utilization (table 2).

Table 2

Per patient cost analysis

Budget impact analysis: FreeStyle Libre system versus SMBG

In an average local health economy (hypothetical population size of 1790), the net budget impact of increasing the proportion of people with T1DM using the FreeStyle Libre system from 30% in year 1% to 50% and 70% in year 2 and 3, respectively, is illustrated in table 3. In year 1, the total cost was £1 787 345 increasing to £1 847 618 and £1 907 890 in years 2 and 3, respectively, representing 3.4% and 3.3% year-on-year increase.

Table 3

Budget impact

Sensitivity analysis

In the incremental cost per patient sensitivity analysis (online supplemental figure 1) and sensitivity analysis, it was found that the model was most sensitive to the number of SMBG tests per day and costs of the test strips.

Applying a low estimate of four tests per day, increased the difference in cost per patient per year with the FreeStyle Libre System compared with SMBG is, to £326 compared with £163 in the base-case. Cost neutrality with SMBG would be achieved when carrying out 7.3 tests per day.

Subgroup analysis

The results of the subgroup analysis in people with higher baseline HbA1c are reported in online supplemental table 2. Among those with a high HbA1c baseline (>8.5%), the costs savings from reduced HbA1c with the FreeStyle Libre system are projected to be greater relative to the overall population. The difference in cost per patient per year with the FreeStyle Libre system compared with SMBG is £73, compared with £163 in the overall population. Threshold analysis of the number of tests per day in the high HbA1c group shows that cost neutrality with SMBG would be achieved when carrying out approximately 6.5 tests per day.

Discussion

This budget impact analysis is the first to apply UK data collected in a real-world setting to estimate the impact of widespread adoption of the FreeStyle Libre system from an NHS budget holder’s perspective. The results are therefore relevant to current decision making for UK local budget holders.

The ABCD nationwide audit demonstrates that the FreeStyle Libre system use is associated with improved outcomes, resulting in reduced diabetes-related resource utilization in T1 DM populations in the real world. This finding is consistent with other real-world studies that report reduced hospitalizations,16 17 24–26 improved HbA1c16 18 or improved quality of life or well-being14 16–18 associated with FreeStyle Libre system. Applying these data in a budget impact analysis, it was found that higher acquisition costs are partially offset by healthcare costs avoided. In an average-sized local English health economy (population size of 1790 T1DM), increasing FreeStyle Libre system uptake from 30% in year 1 to 50% in year 2 increased costs by 3.4%. Similarly increasing the FreeStyle Libre system uptake to 70% in year 3 increased the budget by a further 3.3%.

This increase in costs is associated with patient and healthcare system benefits including improved glucose monitoring, reduced hospital admissions and improved quality of life. FreeStyle Libre system use is associated with improved quality of life as reported in a time trade-off study,20 which reported a mean difference in health states of 0.03 (±0.053) between sensor-based (flash glucose monitoring) and conventional monitoring. This gain is assumed to reflect the greater convenience as well as intangible benefits of empowering patients to monitor and self-manage their glucose levels compared with SMBG. In addition, further quality of life improvements with FreeStyle Libre system compared with SMBG alone are expected, due to reduced risk of SHE27 and DKA events28 and improved HbA1c.29 Other benefits of FreeStyle Libre system not captured in this analysis include access to glucose management indicators that can be used as a substitute for quarterly HbA1c blood tests, further reducing system costs as well as the function to facilitate remote consultation and monitoring of people with diabetes. This feature has been particularly beneficial during the global COVID-19 pandemic.30–32

The findings of this analysis should be considered in the context of the following limitations. As with all budget impact analyses, there is uncertainty in the assumptions applied to project future uptake of the new intervention. The only RCT that has evaluated FreeStyle Libre system use in T1DM (IMPACT)6 did not observe statistically significant differences in HbA1c reduction, and thus the effects observed in real world settings cannot be definitively said to be a result of FreeStyle Libre system use. However, the primary outcome of IMPACT6 was to measure change in hypoglycemia, and this study only recruited people with a baseline HbA1c of 7.5% and under, therefore a change in HbA1c was not expected. The ABCD audit demonstrated that people with T1DM with baseline HbA1c of over 8.5% had a mean reduction in HbA1c of 1.2% compared with 0.5% in the overall T1DM population. This is consistent with other real world studies, demonstrating improved HbA1c pre and post starting FreeStyle Libre system.10 11

An assumption implicit in this cost analysis is that the change in resource utilization reported in the ABCD audit is transferrable to all T1DM populations that may switch to the FreeStyle Libre system in the future. However, the people included in the ABCD audit are a subgroup of all T1DM populations defined by the NHS funding criteria and those able to self-fund.19 These criteria, which include high testing frequency or hypoglycemia unawareness, may influence baseline characteristics and therefore resource utilization. However, although this has the potential to bias the analysis, it is not clear in which direction. The substantial reduction in HbA1c seen in the earliest cohort enrolled in the ABCD audit may be partly influenced by a ‘regression to the mean’ effect, as the HbA1c level at baseline was 8.3%. Unpublished data provided by a national specialty advisor for diabetes with NHS England suggests that these data are reasonably representative because at the time of this analysis, approximately 40% of people with T1DM living in the UK were using the FreeStyle Libre system. If later adopters have lower baseline HbA1c, similar to those recruited to IMPACT,6 they may not experience the same decrease in HbA1c or reduction in hospital events. Similarly, the baseline rate of DKA events and SHEs requiring hospital admissions was found to be between 5% and 10%. These rates may be high compared with the total T1DM population because people with a history of hospital admission for diabetes related events were prioritized for starting FreeStyle Libre system. Nonetheless, these rates are comparable with other real-world studies. The UK hypoglycemia study33 reported 1.1 and 3.2 episodes of SHE per person-year among people with T1DM for less than 5 years and between 5 and 15 years, respectively, and Heller et al34 reported that 5% of SHE in T1DM populations resulted in hospital stay.

Furthermore, 7-month data were prorated to estimate the annual outcomes post-FreeStyle Libre system use to capture outcomes from a larger sample. This was not expected to introduce a seasonal bias because recruitment was ongoing, and therefore, people were started and followed up at difference times of the year. Furthermore, comparison of the data applied in this analysis with 7-month data extracted at a different time point15 show similar trends.

There is also uncertainty regarding the attribution of a cost reduction to change in HbA1c because healthcare costs were not directly measured in the ABCD audit. The cost reduction assumption was sourced from a prior cost-effectiveness analysis23 using the previously validated CORE diabetes economic model in a UK context and therefore carries with it the uncertainty associated with that model. Furthermore, the cohort modelled in this modelling study may differ from the ABCD audit participants considered in this cost analysis. However, the cost attributed to a 1% reduction in HbA1c reported in Baxter et al19 was stratified by baseline HbA1c and matched to the baseline rate in the participants in the ABCD audit. The costs for the first 5-year period reported were annualized to a 1 -year basis. If the 5-year costs were weighted towards year 5 more than year 1, this assumption would have overestimated the short-term (1 year) impact. However, this potential cost-saving would be expected to be realized over the medium term (5 years).

The effect of uncertainty in our analysis was explored in one-way sensitivity analysis and threshold analysis that concluded that the results were most sensitive to the cost and number per day of SMBG tests in the SMBG arm. A range of plausible hypothetical uptake scenarios were therefore considered, including applying conservative scenarios for SMBG tests per. Furthermore, subgroup analysis found that the potential costs avoided with the FreeStyle Libre system may be higher among those with a higher baseline HbA1c. The difference in cost per patient were even lower in this group compared with the overall population.

This analysis did not compare the FreeStyle Libre system to traditional CGM or conduct cost utility analysis. The aqusition cost of FreeStyle Libre system of £937 per patient per year (PPPY) applied in this analysis are considerably lower than the acquisition cost of Dexcom G6 (£1850 PPPY) applied in recent cost utility analysis of traditional CGM conducted from a UK payer perspective.13 While the original FreeStyle Libre system differs from traditional CGM because it does not have alarms, the FreeStyle Libre 2 system, the next-generation device, was launched in late 2020 and has the added benefit of optional alarms. This therefore has the potential to provide similar functionality as other traditional CGMs in respect to triggering a patient response when glucose levels go too low or too high.

Conclusion

Widespread adoption of FreeStyle Libre system in T1DM populations offers many benefits and has a relatively small budget impact compared with the total cost of glucose management to health economies in the UK. People with T1DM and healthcare systems stand to benefit from the improved glycemic control, reduced diabetes related distress, reduced hospital admissions and the opportunity of virtual reviews that this easy to use monitoring solution provides.

Contributors: RB and DB conducted the economic analysis and had leading roles in drafting the manuscript writing. FL-G, HD, EGW, REJR, CW and TS contributed to the methodology, the economic analysis and the manuscript writing. RB was the guarantor for this analysis
Funding: The Association of British Clinical Diabetologists (ABCD) nationwide FreeStyle Libre audit is supported by an unrestricted grant from Abbott Diabetes Care. The audit data collection and analysis were independently initiated and performed by ABCD.
Disclaimer: The views expressed in this paper are those of the individual authors and not of ABCD.
Competing interests: FL-G is employed by Abbott Diabetes Care. DB and RB are managing directors of MedTech Economics, a consultancy contracted by Abbott Diabetes Care to conduct economic analysis. EGW has received personal fees from Abbott Diabetes Care, Dexcom, Diasend, Eli Lilly, Insulet, Medtronic, Novo Nordisk, and Sanofi Aventis. REJR has received speaker fees and/or consultancy fees and/or educational sponsorships from AstraZeneca, BioQuest, GI Dynamics, Janssen, Novo Nordisk, Sanofi-Aventis, and Takeda. TS has received clinical trials support from Novo Nordisk, Eli Lilly, Sanofi-Aventis and non-promotional educational grants from Abbott, Novartis, and Novo Nordisk. HD and CW have no conflict of interest.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Data availability statement

Data are available on reasonable request.

Ethics statements

Patient consent for publication:

Ethics approval:

This study does not involve human participants.

Pickup JC, Sutton AJ. Severe hypoglycaemia and glycaemic control in type 1 diabetes: meta-analysis of multiple daily insulin injections compared with continuous subcutaneous insulin infusion. Diabet Med 2008; 25:765–74.
doi:10.1111/j.1464-5491.2008.02486.x•Google Scholar •PubMed
Higgins GT, Khan J, Pearce IA, et al. Glycaemic control and control of risk factors in diabetes patients in an ophthalmology clinic: what lessons have we learned from the UKPDS and DCCT studies? Acta Ophthalmol Scand 2007; 85:772–6.
doi:10.1111/j.1600-0420.2007.00944.x•Google Scholar
Unger J, Kushner P, Anderson JE, et al. Practical guidance for using the FreeStyle Libre flash continuous glucose monitoring in primary care. J Postgraduate Med 2020;
Google Scholar
Poolsup N, Suksomboon N, Kyaw AM, et al. Systematic review and meta-analysis of the effectiveness of continuous glucose monitoring (CGM) on glucose control in diabetes. Diabetol Metab Syndr 2013; 5.
doi:10.1186/1758-5996-5-39•Google Scholar
National Institute of Health and Care Excellence. Integrated sensor-augmented pump therapy systems for managing blood glucose levels in type 1 diabetes (the MiniMed paradigm Veo system and the VibE and G4 platinum CGM system). 2016;
Google Scholar
Bolinder J, Antuna R, Geelhoed-Duijvestijn P, et al. Novel glucose-sensing technology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlled trial. Lancet 2016; 388:2254–63.
doi:10.1016/S0140-6736(16)31535-5•Google Scholar •PubMed
Haak T, Hanaire H, Ajjan R, et al. Use of flash glucose-sensing technology for 12 months as a replacement for blood glucose monitoring in insulin-treated type 2 diabetes. Diabetes Ther 2017; 8:573–86.
doi:10.1007/s13300-017-0255-6•Google Scholar •PubMed
Nagi D, Wilmot E, Owen K, et al. Abcd position statement on risk stratification of adult patients with diabetes during COVID-19 pandemic. Br J Diabetes 2021; 21:123–31.
doi:10.15277/bjd.2021.282•Google Scholar
N.B.S. Authority. Approved list of appliances. 2020;
Google Scholar
Evans M, Welsh Z, Ells S, et al. The impact of flash glucose monitoring on glycaemic control as measured by HbA1c: a meta-analysis of clinical trials and real-world observational studies. Diabetes Ther 2020; 11:83–95.
doi:10.1007/s13300-019-00720-0•Google Scholar •PubMed
Kröger J, Fasching P, Hanaire H, et al. Three European retrospective real-world chart review studies to determine the effectiveness of flash glucose monitoring on HbA1c in adults with type 2 diabetes. Diabetes Ther 2020; 11:279–91.
doi:10.1007/s13300-019-00741-9•Google Scholar •PubMed
Yaron M, Roitman E, Aharon-Hananel G, et al. Effect of flash glucose monitoring technology on glycemic control and treatment satisfaction in patients with type 2 diabetes. Diabetes Care 2019; 42:1178–84.
doi:10.2337/dc18-0166•Google Scholar
Campbell FM, Murphy NP, Stewart C, et al. Outcomes of using flash glucose monitoring technology by children and young people with type 1 diabetes in a single arm study. Pediatr Diabetes 2018; 19:1294–301.
doi:10.1111/pedi.12735•Google Scholar •PubMed
Al Hayek AA, Robert AA, Al Dawish MA, et al. Effectiveness of the freestyle libre flash glucose monitoring system on diabetes distress among individuals with type 1 diabetes: a prospective study. Diabetes Ther 2020; 11:927–37.
doi:10.1007/s13300-020-00793-2•Google Scholar •PubMed
Deshmukh H, Wilmot EG, Gregory R, et al. Effect of flash glucose monitoring on glycemic control, hypoglycemia, diabetes-related distress, and resource utilization in the Association of British Clinical Diabetologists (ABCD) nationwide audit. Diabetes Care 2020; 43:2153–60.
doi:10.2337/dc20-0738•Google Scholar •PubMed
Fokkert M, van Dijk P, Edens M, et al. Improved well-being and decreased disease burden after 1-year use of flash glucose monitoring (FLARE-NL4). BMJ Open Diab Res Care 2019; 7:e000809.
doi:10.1136/bmjdrc-2019-000809•Google Scholar
Charleer S, De Block C, Van Huffel L, et al. Quality of life and glucose control after 1 year of nationwide reimbursement of intermittently scanned continuous glucose monitoring in adults living with type 1 diabetes (FUTURE): a prospective observational real-world cohort study. Diabetes Care 2020; 43:389–97.
doi:10.2337/dc19-1610•Google Scholar
Tyndall V, Stimson RH, Zammitt NN, et al. Marked improvement in HbA1c following commencement of flash glucose monitoring in people with type 1 diabetes. Diabetologia 2019; 62:1349–56.
doi:10.1007/s00125-019-4894-1•Google Scholar •PubMed
N. England. Flash glucose monitoring: national arrangements for funding of relevant diabetes patients. 2019;
Google Scholar
N. England. National cost collection for the NHS (2018/19). 2019;
Google Scholar
N. England. National tariff for 2017/18 and 2018/19. 2020;
Google Scholar
Baxter M, Hudson R, Mahon J, et al. Estimating the impact of better management of glycaemic control in adults with type 1 and type 2 diabetes on the number of clinical complications and the associated financial benefit. Diabet Med 2016; 33:1575–81.
doi:10.1111/dme.13062•Google Scholar •PubMed
Type 2 diabetes prevention programme and type 1 diabetes glucose monitoring: letter from Professor Jonathan Valabhji, Professor Partha KAR and TOM Newbound, N. England, editor. 2020;
Google Scholar
Kerr M. CGM use associated with reduction in acute diabetes complications, even in patients using less than four test strips per day. In Diabetes Technology & Therapeutics. 140 Huguenot Street, 3rd Fl, New Rochelle, NY 10801 USA, Mary Ann Liebert, Inc 2020;
Google Scholar
Bergenstal RM, Kerr MSD, Roberts GJ, et al. Flash CGM is associated with reduced diabetes events and hospitalizations in insulin-treated type 2 diabetes. J Endocr Soc 2021; 5.
doi:10.1210/jendso/bvab013•Google Scholar
Roussel R, Guerci B, Vicaut E, et al. 68-OR: dramatic drop in ketoacidosis rate after FreeStyle Libre system initiation in type 1 and type 2 diabetes in France, especially in people with low self-monitoring of blood glucose (SMBG): a nationwide study. Diabetes 2020; 69.
doi:10.2337/db20-68-OR•Google Scholar
Currie CJ, Morgan CL, Poole CD, et al. Multivariate models of health-related utility and the fear of hypoglycaemia in people with diabetes. Curr Med Res Opin 2006; 22:1523–34.
doi:10.1185/030079906X115757•Google Scholar •PubMed
Peasgood T, Brennan A, Mansell P, et al. The impact of diabetes-related complications on preference-based measures of health-related quality of life in adults with type I diabetes. Med Decis Making 2016; 36:1020–33.
doi:10.1177/0272989X16658660•Google Scholar •PubMed
McQueen RB, Ellis SL, Maahs DM, et al. Association between glycated hemoglobin and health utility for type 1 diabetes. Patient 2014; 7:197–205.
doi:10.1007/s40271-014-0045-4•Google Scholar •PubMed
Galindo RJ, Aleppo G, Klonoff DC, et al. Implementation of continuous glucose monitoring in the hospital: emergent considerations for remote glucose monitoring during the COVID-19 pandemic. J Diabetes Sci Technol 2020; 14:822–32.
doi:10.1177/1932296820932903•Google Scholar
Bianchi C, Aragona M, Rodia C, et al. Freestyle Libre trend arrows for the management of adults with insulin-treated diabetes: a practical approach. J Diabetes Complications 2019; 33:6–12.
doi:10.1016/j.jdiacomp.2018.10.012•Google Scholar •PubMed
Edelman SV, Argento NB, Pettus J, et al. Clinical implications of real-time and intermittently scanned continuous glucose monitoring. Diabetes Care 2018; 41:2265–74.
doi:10.2337/dc18-1150•Google Scholar •PubMed
UK Hypoglycaemia Study Group. Risk of hypoglycaemia in types 1 and 2 diabetes: effects of treatment modalities and their duration. Diabetologia 2007; 50:1140–7.
doi:10.1007/s00125-007-0599-y•Google Scholar •PubMed
Heller SR, Frier BM, Hersløv ML, et al. Severe hypoglycaemia in adults with insulin-treated diabetes: impact on healthcare resources. Diabet Med 2016; 33:471–7.
doi:10.1111/dme.12844•Google Scholar •PubMed

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