1
|
Hachem M, Hearn T, Kelly R, Eer A, Moore B, Sommerville C, Atkinson-Briggs S, Twigg S, Freund M, O'Neal D, Story D, Brown A, McLean A, Sinha A, Furler J, O'Brien R, Tran-Duy A, Clarke P, Braat S, Koye DN, Eades S, Burchill L, Ekinci E. Can flash glucose monitoring improve glucose management for Aboriginal and Torres Strait Islander peoples with type 2 diabetes? A protocol for a randomised controlled trial. Trials 2024; 25:493. [PMID: 39030640 PMCID: PMC11264795 DOI: 10.1186/s13063-024-08267-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 06/19/2024] [Indexed: 07/21/2024] Open
Abstract
BACKGROUND Aboriginal and Torres Strait Islander peoples are disproportionately impacted by type 2 diabetes. Continuous glucose monitoring (CGM) technology (such as Abbott Freestyle Libre 2, previously referred to as Flash Glucose Monitoring) offers real-time glucose monitoring that is convenient and easy to use compared to self-monitoring of blood glucose (SMBG). However, this technology's use is neither widespread nor subsidised for Aboriginal and Torres Strait Islander peoples with type 2 diabetes. Building on existing collaborations with a national network of Aboriginal and Torres Strait Islander communities, this randomised controlled trial aims to assess the effect of CGM compared to SMBG on (i) haemoglobin A1c (HbA1c), (ii) achieving blood glucose targets, (iii) reducing hypoglycaemic episodes and (iv) cost-effective healthcare in an Aboriginal and Torres Strait Islander people health setting. METHODS This is a non-masked, parallel-group, two-arm, individually randomised, controlled trial (ACTRN12621000753853). Aboriginal and Torres Strait Islander adults with type 2 diabetes on injectable therapy and HbA1c ≥ 7.5% (n = 350) will be randomised (1:1) to CGM or SMBG for 6 months. The primary outcome is change in HbA1c level from baseline to 6 months. Secondary outcomes include (i) CGM-derived metrics, (ii) frequency of hypoglycaemic episodes, (iii) health-related quality of life and (iv) incremental cost per quality-adjusted life year gained associated with the CGM compared to SMBG. Clinical trial sites include Aboriginal Community Controlled Organisations, Aboriginal Medical Services, primary care centres and tertiary hospitals across urban, rural, regional and remote Australia. DISCUSSION The trial will assess the effect of CGM compared to SMBG on HbA1c for Aboriginal and Torres Strait Islander people with type 2 diabetes in Australia. This trial could have long-term benefits in improving diabetes management and providing evidence for funding of CGM in this population. TRIAL REGISTRATION Australian and New Zealand Clinical Trials Registry ACTRN12621000753853. Registered on 15th June 2021.
Collapse
Affiliation(s)
- Mariam Hachem
- Department of Medicine, Austin Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Endocrinology, Austin Health, Melbourne, Victoria, Australia
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Tracey Hearn
- Department of Medicine, Austin Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Medical Clinic, Rumbalara Aboriginal Cooperative, Mooroopna, Victoria, Australia
| | - Ray Kelly
- Department of Medicine, Austin Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Audrey Eer
- Department of Medicine, Austin Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Endocrinology, Austin Health, Melbourne, Victoria, Australia
| | - Belinda Moore
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Implementation Science Research Group, University of Melbourne, Melbourne, Victoria, Australia
| | - Christine Sommerville
- Department of Medicine, Austin Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | | | - Stephen Twigg
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Meagan Freund
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, Health Behaviour Research Collaborative, University of Newcastle, Newcastle, New South Wales, Australia
| | - David O'Neal
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Department of Medicine, FacultyofMedicine,DentistryandHealth Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Endocrinology, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia
| | - David Story
- Critical Care, FacultyofMedicine,DentistryandHealthSciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Alex Brown
- Indigenous Genomics, Telethon Kids Institute, Adelaide, South Australia, Australia
- Indigenous Genomics, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Anna McLean
- Department of Endocrinology and Diabetes, Cairns Hospital, Cairns, Queensland, Australia
| | - Ashim Sinha
- Department of Endocrinology and Diabetes, Cairns Hospital, Cairns, Queensland, Australia
| | - John Furler
- Department of General Practice, University of Melbourne, Melbourne, Victoria, Australia
| | - Richard O'Brien
- Endocrinology, Austin Health, Melbourne, Victoria, Australia
| | - An Tran-Duy
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Methods and Implementation Support for Clinical and Health research (MISCH) Hub, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Philip Clarke
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Health Economics Research Centre, University of Oxford, Oxford, United Kingdom
| | - Sabine Braat
- Methods and Implementation Support for Clinical and Health research (MISCH) Hub, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Epidemiology and BiostatisticsMelbourne School of Population and Global HealthFaculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Digsu N Koye
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Methods and Implementation Support for Clinical and Health research (MISCH) Hub, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Epidemiology and BiostatisticsMelbourne School of Population and Global HealthFaculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Sandra Eades
- Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Luke Burchill
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Cardiovascular Medicine, Rochester, Minnesota, United States of America
| | - Elif Ekinci
- Department of Medicine, Austin Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia.
- Endocrinology, Austin Health, Melbourne, Victoria, Australia.
- Australian Centre for Accelerating Diabetes Innovations (ACADI), Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia.
| |
Collapse
|
2
|
Alsaif M, Farhat A, Blumer Z, Barham L. Budget impact analysis of continuous glucose monitoring in individuals with type 2 diabetes on insulin treatment in England. HEALTH ECONOMICS REVIEW 2024; 14:32. [PMID: 38709338 PMCID: PMC11071237 DOI: 10.1186/s13561-024-00505-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 04/08/2024] [Indexed: 05/07/2024]
Abstract
INTRODUCTION In 2022, updated guidance from NICE expanded the options for self-monitoring of blood glucose for patients with type 2 diabetes (T2DM), to include continuous glucose monitoring (CGM). In this budget impact analysis, the cost impact of CGM was compared with traditional self-monitoring of blood glucose (SMBG) in adults with T2DM over 1 year from the commissioner perspective in England. RESEARCH DESIGN AND METHODS The NICE-eligible T2DM cohort was split into 4 subgroups to enable nuanced costing by insulin administration frequency: basal human insulin, premixed insulin, basal-bolus insulin and bolus insulin. The model's cost components comprised mild and severe hypoglycaemia (SH), diabetic ketoacidosis (DKA), consumables and healthcare resource utilisation in primary and secondary care. RESULTS The introduction of CGM is estimated to be cost additive by approximately £4.6 million in the basecase, driven by increased spending on the CGM device. Overall, healthcare activity was reduced by approximately 20,000 attendances, due to fewer SH and DKA episodes in the CGM arm. General Practitioner (GP) practice-based activity is expected to drop after the first year as patients requiring CGM training is reduced. The budget impact could be neutralised if the CGM sensor was discounted by 13.2% (£29.76 to £25.83). CONCLUSIONS CGM may result in increased spending in the NICE-eligible T2DM cohort but is expected to reduce demand on secondary care services and GP time. These findings may be of interest to local decision-makers who wish to resolve the COVID-19 backlog with transformational investment in primary care to reduce secondary care activity.
Collapse
Affiliation(s)
- Murtada Alsaif
- IPG Health Global Market Access, London, UK.
- PharmaSaif Ltd, Slough, UK.
| | - Ali Farhat
- IPG Health Global Market Access, London, UK
| | - Zoe Blumer
- IPG Health Global Market Access, London, UK
| | - Leela Barham
- Learna Ltd in partnership with the University of South Wales, Cardiff, Wales, UK
| |
Collapse
|
3
|
Ssemmondo E, Deshmukh H, Wilmot EG, Adeleke KA, Shah N, Walton C, Barnes D, Ryder REJ, Sathyapalan T. Effect of intermittently scanned continuous glucose monitoring in people with diabetes with a psychosocial indication for initiation. Diabetes Obes Metab 2024; 26:1340-1345. [PMID: 38228571 DOI: 10.1111/dom.15435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/04/2023] [Accepted: 12/15/2023] [Indexed: 01/18/2024]
Abstract
AIM To understand the effect of intermittently scanned continuous glucose monitoring (isCGM) in people with diabetes with a 'psychosocial' indication for access. METHODS The study utilized baseline and follow-up data from the Association of British Clinical Diabetologists nationwide audit of people with diabetes in the UK. Diabetes-related distress (DRD) was assessed using the two-item diabetes-related distress scale (DDS). Participants were categorized into two groups: high DRD (DDS score ≥ 3) and lower DRD (DDS score < 3). The t-test was used to assess the difference in the pre- and post-isCGM continuous variables. RESULTS The study consisted of 17 036 people with diabetes, with 1314 (7%) using isCGM for 'psychosocial' reasons. Follow-up data were available for 327 participants, 322 (99%) of whom had type 1 diabetes with a median diabetes duration of 15 years; 75% (n = 241) had high levels of DRD. With the initiation of isCGM, after a mean follow-up period of 6.9 months, there was a significant reduction in DDS score; 4 at baseline versus 2.5 at follow-up (P < .001). The prevalence of high DRD reduced from 76% to 38% at follow-up (50% reduction in DRD, P < .001). There was also a significant reduction in HbA1c (78.5 mmol/mol [9.3%] at baseline vs. 66.5 mmol/mol [8.2%] at follow-up; P < .001). This group also experienced an 87% reduction in hospital admissions because of hyperglycaemia/diabetic ketoacidosis (P < .001). CONCLUSION People with diabetes who had isCGM initiated for a psychosocial indication had high levels of DRD and HbA1c, which improved with the use of isCGM.
Collapse
Affiliation(s)
- Emmanuel Ssemmondo
- Allam Diabetes Centre, University of Hull, Hull, UK
- Hull University Teaching Hospitals NHS Trust, Hull, UK
| | - Harshal Deshmukh
- Allam Diabetes Centre, University of Hull, Hull, UK
- Hull University Teaching Hospitals NHS Trust, Hull, UK
| | - Emma G Wilmot
- University Hospitals of Derby & Burton NHS FT, Derby, UK
- University of Nottingham, Nottingham, UK
| | - Kazeem A Adeleke
- Allam Diabetes Centre, University of Hull, Hull, UK
- Hull University Teaching Hospitals NHS Trust, Hull, UK
| | - Najeeb Shah
- Allam Diabetes Centre, University of Hull, Hull, UK
- Hull University Teaching Hospitals NHS Trust, Hull, UK
| | - Chris Walton
- Hull University Teaching Hospitals NHS Trust, Hull, UK
| | | | | | - Thozhukat Sathyapalan
- Allam Diabetes Centre, University of Hull, Hull, UK
- Hull University Teaching Hospitals NHS Trust, Hull, UK
| |
Collapse
|
4
|
Elliott RA, Rogers G, Evans ML, Neupane S, Rayman G, Lumley S, Cranston I, Narendran P, Sutton CJ, Taxiarchi VP, Burns M, Thabit H, Wilmot EG, Leelarathna L. Estimating the cost-effectiveness of intermittently scanned continuous glucose monitoring in adults with type 1 diabetes in England. Diabet Med 2024; 41:e15232. [PMID: 37750427 DOI: 10.1111/dme.15232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 09/11/2023] [Accepted: 09/18/2023] [Indexed: 09/27/2023]
Abstract
OBJECTIVE We previously showed that intermittently scanned continuous glucose monitoring (isCGM) reduces HbA1c at 24 weeks compared with self-monitoring of blood glucose with finger pricking (SMBG) in adults with type 1 diabetes and high HbA1c levels (58-97 mmol/mol [7.5%-11%]). We aim to assess the economic impact of isCGM compared with SMBG. METHODS Participant-level baseline and follow-up health status (EQ-5D-5L) and within-trial healthcare resource-use data were collected. Quality-adjusted life-years (QALYs) were derived at 24 weeks, adjusting for baseline EQ-5D-5L. Participant-level costs were generated. Using the IQVIA CORE Diabetes Model, economic analysis was performed from the National Health Service perspective over a lifetime horizon, discounted at 3.5%. RESULTS Within-trial EQ-5D-5L showed non-significant adjusted incremental QALY gain of 0.006 (95% CI: -0.007 to 0.019) for isCGM compared with SMBG and an adjusted cost increase of £548 (95% CI: 381-714) per participant. The lifetime projected incremental cost (95% CI) of isCGM was £1954 (-5108 to 8904) with an incremental QALY (95% CI) gain of 0.436 (0.195-0.652) resulting in an incremental cost-per-QALY of £4477. In all subgroups, isCGM had an incremental cost-per-QALY better than £20,000 compared with SMBG; for people with baseline HbA1c >75 mmol/mol (9.0%), it was cost-saving. Sensitivity analysis suggested that isCGM remains cost-effective if its effectiveness lasts for at least 7 years. CONCLUSION While isCGM is associated with increased short-term costs, compared with SMBG, its benefits in lowering HbA1c will lead to sufficient long-term health-gains and cost-savings to justify costs, so long as the effect lasts into the medium term.
Collapse
Affiliation(s)
- Rachel A Elliott
- Manchester Centre for Health Economics, Division of Population Health, Health Service Research & Primary Care, University of Manchester, Manchester, UK
| | - Gabriel Rogers
- Manchester Centre for Health Economics, Division of Population Health, Health Service Research & Primary Care, University of Manchester, Manchester, UK
| | - Mark L Evans
- Wellcome-MRC Institute of Metabolic Science, NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals and University of Cambridge, Cambridge, UK
| | - Sankalpa Neupane
- Elsie Bertram Diabetes Centre, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Norwich Medical School, University of East Anglia, Norwich, Norfolk, UK
| | - Gerry Rayman
- The Diabetes and Endocrine Centre, Ipswich Hospital, East Suffolk and North Essex NHS Foundation Trust, Ipswich, UK
| | | | - Iain Cranston
- Academic Department of Diabetes & Endocrinology, Queen Alexandra Hospital, Cosham, Portsmouth, UK
| | - Parth Narendran
- Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham, UK
- Department of Diabetes, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Christopher J Sutton
- Centre for Biostatistics, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Vicky P Taxiarchi
- Centre for Women's Mental Health, Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Matthew Burns
- Manchester Clinical Trials Unit, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health University of Manchester, Manchester, UK
| | - Hood Thabit
- Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Manchester Diabetes Centre, Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Emma G Wilmot
- Royal Derby Hospital, University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK
- University of Nottingham, Nottingham, UK
| | - Lalantha Leelarathna
- Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Manchester Diabetes Centre, Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| |
Collapse
|
5
|
Kandiyali R, Taylor H, Thomas E, Cullen F, Hollingworth W, Ingram J, Kenward C, West N, McGregor D, Smith B, Hamilton-Shield J. Implementation of flash glucose monitoring in four pediatric diabetes clinics: controlled before and after study to produce real-world evidence of patient benefit. BMJ Open Diabetes Res Care 2023; 11:e003561. [PMID: 37640505 PMCID: PMC10462967 DOI: 10.1136/bmjdrc-2023-003561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/01/2023] [Indexed: 08/31/2023] Open
Abstract
AIMS To assess the real-world evidence for flash glucose monitoring (Abbott FreeStyle Libre) for children with type 1 diabetes in terms of glucose control, secondary healthcare resources and costs. RESEARCH DESIGN AND METHODS We conducted a controlled before and after study (approximately 12 months before and after) using routinely collected health record data on children who start using flash monitors and a control population of children with self-monitoring of blood glucose (SMBG). Our population-based sample of eligible individuals using flash monitoring (n=114) and controls (n=80) aged between 4 and 18 years was drawn from four paediatric diabetes clinics (secondary care) in the South West England. Outcome measures included: glycated hemoglobin (HbA1c), frequency of BG tests; frequency of sensor scans; time in recommended glucose range; short-term complications (hypoglycemia, diabetic ketoacidosis and related illness resulting in investigation) and secondary care costs. RESULTS After adjustment for age, time since diagnosis, deprivation and the test modality (point of care or laboratory), the mean HbA1c reading for controls was 61.2 (mmol/mol) for the period before and 63.9 after. For individuals using flash monitoring, the adjusted mean HbA1c reading was 64.6 for the period before implementation and 63.8 after. Rates of short-term complications were low across all groups in the study. Whereas the 'after' flash monitoring group had substantially higher incremental costs (+£703 vs the flash monitoring 'before' comparison and +£841 vs contemporaneous SMBG controls), these cost differences were driven by primary care prescribing (sensor costs). CONCLUSIONS There was some indication that flash monitoring might help young people improve the control of their diabetes but for our sample, the difference between finger-prick testing and flash monitoring was not clinically significant (HbA1c improvement <5 mmol/mol). Given the pace of technological change within diabetes, research efforts should now facilitate the real-time analysis of long-term routine data on flash and continuous glucose monitors.
Collapse
Affiliation(s)
| | - Hazel Taylor
- Research and Development, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Elizabeth Thomas
- Bristol Paediatric Diabetes, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Freyja Cullen
- Bristol Paediatric Diabetes, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | | | - Jenny Ingram
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Charlie Kenward
- North Somerset and South Gloucestershire Integrated Care Board, Bristol, UK
| | - Nicol West
- Department of Paediatrics, Great Western Hospitals NHS Foundation Trust, Swindon, UK
| | - David McGregor
- Department of Paediatrics, Royal Devon and Exeter Foundation Trust, Exeter, UK
| | - Becky Smith
- Department of Paediatrics, University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - Julian Hamilton-Shield
- Bristol Paediatric Diabetes, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| |
Collapse
|
6
|
Palacios A, Rodriguez-Cairoli F, Balan D, Rojas-Roque C, Moreno-López C, Braun B, Augustovski F, Pichon-Riviere A, Bardach A. Budget Impact Analysis of the FreeStyle Libre Flash Continuous Glucose Monitoring System ® in Patients with Type 1 Diabetes Mellitus and Type 2 Diabetes Mellitus with Multiple Daily Insulin Injections in Argentina. APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2023; 21:637-650. [PMID: 37062046 DOI: 10.1007/s40258-023-00800-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/23/2023] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To estimate the budget impact of the potential coverage of FreeStyle Libre Flash Continuous Glucose Monitoring System (FSL) for glycemia monitoring in all type 1 diabetes mellitus (T1DM) patients and in those with type 2 diabetes mellitus (T2DM) with multiple daily insulin injections, from the social security and the private third-party payer's perspective in Argentina. METHODS A budget impact model was developed to estimate the cost difference between the self-monitoring of blood glucose (standard of care) and FSL over 5 years. Input parameters were retrieved from local literature complemented by expert opinion. Health care costs were estimated by a micro-costing approach and reported in USD as of April 2022 (1 USD = 113.34 Argentine pesos). One-way sensitivity and scenario analyses were conducted. RESULTS From a social security third-party payer perspective, the incorporation of FSL was associated with net savings per member per month (PMPM) of $0.026 (Year 1) to $0.097 (Year 5) and net savings PMPM of $0.002 (Year 1) to $0.008 (Year 5) for T1DM and T2DM patients, respectively. Similar findings are reported from the private third-party payer perspective. The budget impact results were more sensitive to the acquisition costs of the FSL and test strips. CONCLUSION The potential coverage of FSL in patients with T1DM and T2DM with multiple daily insulin injections could be associated with small financial savings considering current technology acquisition costs (FSL and test strips) for social security and the private sector third-party payers in Argentina.
Collapse
Affiliation(s)
- Alfredo Palacios
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina.
- Department of Economics, Universidad de Buenos Aires, Buenos Aires, Argentina.
- Centre for Health Economics (CHE), University of York, York, UK.
| | - Federico Rodriguez-Cairoli
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Dario Balan
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Carlos Rojas-Roque
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Carolina Moreno-López
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Barbara Braun
- Departamento de Clínica Médica y Diabetología, Sanatorio de la Trinidad Palermo, Buenos Aires, Argentina
| | - Federico Augustovski
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Andrés Pichon-Riviere
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Ariel Bardach
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
- Center for Research in Epidemiology and Public Health (CIESP), Buenos Aires, Argentina
| |
Collapse
|
7
|
Al Hayek AA, Al Dawish MA. Use of Flash Glucose Monitoring and Glycemic Control in Patients with Type 2 Diabetes Mellitus Not Treated with an Intensive Insulin Regimen: 1-Year Real-Life Retrospective Cohort Study. Adv Ther 2023; 40:2855-2868. [PMID: 37133646 DOI: 10.1007/s12325-023-02508-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 03/27/2023] [Indexed: 05/04/2023]
Abstract
INTRODUCTION Estimation of laboratory-derived glycated hemoglobin (HbA1c) cannot be individually used to monitor clinically significant trends in glucose variability. Hence, clinicians advise use of continuous glucose monitoring (CGM) devices such as the Freestyle Libre™ flash glucose monitoring system (FLASH) to optimize glycemic control by estimating glucose monitoring index (GMI) values, which convert mean glucose into an estimate of simultaneously measured laboratory HbA1c. This study aimed to investigate the sustainability of intermittently scanned continuous glucose monitoring (isCGM) in patients with type 2 diabetes mellitus (T2DM) not on intensive insulin regimen, and correlations between GMI values obtained from isCGM and laboratory-derived HbA1c values. METHODS A retrospective review of 93 patients with T2DM not on intensive insulin regimen, using FLASH device, was conducted at a major tertiary hospital in Saudi Arabia, over 1 year of continuous device use. To determine the sustainability of isCGM, various glycemic markers such as average glucose and time in range were evaluated. Paired t test or Wilcoxon signed-rank test was used to assess differences in markers of glycemic control, and Pearson's correlation was used to determine correlations between HbA1c and GMI values. RESULTS Descriptive analysis shows the mean HbA1c value significantly decreased following continued use of isCGM. Pre-isCGM mean HbA1c value of 8.3% improved to 8.1% (p < 0.001) and 7.9% (p < 0.001) in the first 90 and last 90 days of device use, respectively. For both 90-day time periods, correlation analysis revealed a statistically significant positive correlation and linear regression between laboratory-derived HbA1c and GMI values (first 90 days r = 0.7999, p < 0.001; last 90 days r = 0.6651, p < 0.001). CONCLUSION Continuous use of isCGM demonstrated reductions in HbA1c levels for patients with T2DM not on an intensive insulin regimen. The GMI values showed high levels of agreement with measured HbA1c, indicating their accuracy in glucose management.
Collapse
Affiliation(s)
- Ayman A Al Hayek
- Department of Endocrinology and Diabetes, Diabetes Treatment Center, Prince Sultan Military Medical City, P.O. Box 7897, Riyadh, 11159, Kingdom of Saudi Arabia.
| | - Mohamed A Al Dawish
- Department of Endocrinology and Diabetes, Diabetes Treatment Center, Prince Sultan Military Medical City, P.O. Box 7897, Riyadh, 11159, Kingdom of Saudi Arabia
| |
Collapse
|
8
|
Palacios A, Rodriguez Cairoli F, Balan D, Balmaceda C, Augustovski F, Pichon-Riviere A, Bardach A. Budget impact analysis of the freestyle libre flash continuous glucose monitoring system® in patients with diabetes mellitus type 1 in Chile. Expert Rev Pharmacoecon Outcomes Res 2023; 23:353-363. [PMID: 36701814 DOI: 10.1080/14737167.2023.2171989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE To estimate the budget impact of covering the FreeStyle Libre Flash Continuous Glucose Monitoring System (FSL) for type 1 Diabetes Mellitus patients (T1DM), compared to self-monitoring of blood glucose (SMBG), from the perspective of public and private third-party payers in Chile. METHODS A budget impact model was developed to estimate the cost difference between SMBG and FSL over five years. Two FSL coverage schemes were assessed. Input parameters were retrieved from the literature review and complemented by expert opinion. Healthcare costs were estimated by a micro-costing approach and reported in USD. RESULTS For a public sector third-party payer, incorporating FSL implied a cost increase up to USD 0.013 per member per month (PMPM) for the fifth year under the broad coverage scheme and a net saving of 0.0001 PMPM (all years) under the restricted coverage scheme. From a private sector third-party payer, incorporating FSL implied savings up to USD 0.028 PMPM (fifth year) for the broad coverage scheme and up to USD 0.012 PMPM (fifth year) for the restricted scheme. CONCLUSION Incorporating the FSL for T1DM patients was associated with a marginal incremental cost for the public sector third-party payer and cost savings in Chile's private healthcare sector.
Collapse
Affiliation(s)
- Alfredo Palacios
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina.,Centre for Health Economics, University of York, York, UK.,Department of Economics, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Federico Rodriguez Cairoli
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Dario Balan
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Carlos Balmaceda
- Centre for Health Economics, University of York, York, UK.,Unidad de Evaluación de Tecnologías Sanitarias, Centro de Investigación Clínica, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Federico Augustovski
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Andres Pichon-Riviere
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| | - Ariel Bardach
- Department of Health Technology Assessment and Health Economics, Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
| |
Collapse
|