Applied Health Economics and Health Policy

, Volume 9, Issue 6, pp 351–365

Cost effectiveness of self-monitoring of blood glucose (SMBG) for patients with type 2 diabetes and not on insulin

Impact of modelling assumptions on recent Canadian findings
Original Research Article

Abstract

Background

Canadian patients, healthcare providers and payers share interest in assessing the value of self-monitoring of blood glucose (SMBG) for individuals with type 2 diabetes but not on insulin. Using the UKPDS (UK Prospective Diabetes Study) model, the Canadian Optimal Prescribing and Utilization Service (COMPUS) conducted an SMBG cost-effectiveness analysis. Based on the results, COMPUS does not recommend routine strip use for most adults with type 2 diabetes who are not on insulin. Cost-effectiveness studies require many assumptions regarding cohort, clinical effect, complication costs, etc. The COMPUS evaluation included several conservative assumptions that negatively impacted SMBG cost effectiveness.

Objectives

Current objectives were to (i) review key, impactful COMPUS assumptions; (ii) illustrate how alternative inputs can lead to more favourable results for SMBG cost effectiveness; and (iii) provide recommendations for assessing its long-term value.

Methods

A summary of COMPUS methods and results was followed by a review of assumptions (for trial-based glycosylated haemoglobin [HbA1c] effect, patient characteristics, costs, simulation pathway) and their potential impact. The UKPDS model was used for a 40-year cost-effectiveness analysis of SMBG (1.29 strips per day) versus no SMBG in the Canadian payer setting. COMPUS assumptions for patient characteristics (e.g. HbA1c 8.4%), SMBG HbA1c advantage (−0.25%) and costs were retained. As with the COMPUS analysis, UKPDS HbA1c decay curves were incorporated into SMBG and no-SMBG pathways. An important difference was that SMBG HbA1c benefits in the current study could extend beyond the initial simulation period. Sensitivity analyses examined SMBG HbA1c advantage, adherence, complication history and cost inputs. Outcomes (discounted at 5%) included QALYs, complication rates, total costs (year 2008 values) and incremental cost-effectiveness ratios (ICERs).

Results

The base-case ICER was $Can63 664 per QALY gained; approximately 56% of the COMPUS base-case ICER. SMBG was associated with modest risk reductions (0.10–0.70%) for six of seven complications. Assuming an SMBG advantage of −0.30% decreased the current base-case ICER by over $Can10 000 per QALY gained. With adherence of 66% and 87%, ICERs were (respectively) $Can39231 and $Can54349 per QALY gained. Incorporating a more representative complication history and 15% complication cost increase resulted in an ICER of $Can49 743 per QALY gained.

Conclusions

These results underscore the importance of modelling assumptions regarding the duration of HbA1c effect. The current study shares several COMPUS limitations relating to the UKPDS model being designed for newly diagnosed patients, and to randomized controlled trial monitoring rates. Neither study explicitly examined the impact of varying the duration of initial HbA1c effects, or of medication or other treatment changes. Because the COMPUS research will potentially influence clinical practice and reimbursement policy in Canada, understanding the impact of assumptions on cost-effectiveness results seems especially important. Demonstrating that COMPUS ICERs were greatly reduced through variations in a small number of inputs may encourage additional clinical research designed to measure SMBG effects within the context of optimal disease management. It may also encourage additional economic evaluations that incorporate lessons learned and best practices for assessing the overall value of SMBG for type 2 diabetes in insulin-naive patients.

Supplementary material

40258_2012_90603511_MOESM1_ESM.pdf (200 kb)
Supplementary material, approximately 205 KB.

References

  1. 1.
    Canadian Diabetes Association (CDA). Diabetes: Canada at the tipping point. Charting a new path [online]. Available from URL: http://www.diabetes.ca/advocacy/reports-and-information/diabetes-canada-at-the-tipping-point/ [Accessed 2011 Apr 2]
  2. 2.
    Canadian Diabetes Association (CDA). The harsh reality: diabetes is a global pandemic [online]. Available from URL: http://www.diabetes.ca/research/specialpopulations/ [Accessed 2010 Sep 15]
  3. 3.
    Maddigan SL, Feeny DH, Majumdar SR, et al. Understanding the determinants of health for people with type 2 diabetes. Am J Pub Health 2006; 96: 1649–55CrossRefGoogle Scholar
  4. 4.
    Ray JA, Valentine WJ, Secnik K, et al. Review of the cost of diabetes complications in Australia, Canada, France, Germany, Italy and Spain. Curr Med Res Opin 2005; 10: 1617–29CrossRefGoogle Scholar
  5. 5.
    O’Brien JA, Patrick AR, Caro JJ. Cost of managing complications resulting from type 2 diabetes mellitus in Canada. BMC Health Serv Res 2003; 3: 17PubMedCrossRefGoogle Scholar
  6. 6.
    Harris SB, Ekoé JM, Zdanowicz Y, et al. Glycemic control and morbidity in the Canadian primary care setting (results of the diabetes in Canada evaluation study). Diabetes Res Clin Pract 2005; 70(1): 90–7PubMedCrossRefGoogle Scholar
  7. 7.
    Canadian Optimal Medication Prescribing and Utilization Service (COMPUS). Cost-effectiveness of blood glucose test strips in the management of adult patients with diabetes mellitus. Ottawa (ON): Canadian Agency for Drugs and Technologies in Health (CADTH) Optimal Therapy Report 2009; 3(3) [online]. Available from URL: http://www.cadth.ca/media/pdf/BGTS_Consolidated_Economic_Report.pdf [Accessed 2010 Aug 6]Google Scholar
  8. 8.
    Clarke P, Gray A, Legood R, et al. The impact of diabetes-related complications on healthcare costs: results from the United Kingdom Prospective Diabetes Study (UKPDS 65). Diabetes Med 2003; 20: 442–50CrossRefGoogle Scholar
  9. 9.
    Skyler JS, Bergenstal RM, Bonow RO, et al. Intensive glycemic control and the prevention of cardiovascular events: implications of the ACCORD, ADVANCE, and VA diabetes trials. Diabetes Care 2009; 32: 187–92PubMedCrossRefGoogle Scholar
  10. 10.
    Davis WA, Bruce DG, Davis TM. Does self-monitoring of blood glucose improve outcome in type 2 diabetes? The Freemantle Diabetes Study. Diabetologia 2007; 50: 510–5PubMedCrossRefGoogle Scholar
  11. 11.
    Davidson MB. Counter point: self-monitoring of blood glucose in type 2 diabetes patients not receiving insulin: a waste of money [letter]. Diabetes Care 2005; 28: 1531–3PubMedCrossRefGoogle Scholar
  12. 12.
    Klonoff DC, Bergenstal R, Blonde L, et al. Consensus report of the coalition for clinical research-self-monitoring of blood glucose. J Diabetes Sci Technol 2008; 2: 1030–53PubMedGoogle Scholar
  13. 13.
    Schnell O, Heinemann L. Self-monitoring of blood glucose in noninsulin-treated patients with type 2 diabetes: a never ending story? J Diabetes Sci Technol 2007; 1: 614–6PubMedGoogle Scholar
  14. 14.
    McAndrew L, Schneider SH, Burns E, et al. Does patient blood glucose monitoring improve diabetes control? A systematic review of the literature. Diabetes Educ 2007; 33: 991–1009PubMedCrossRefGoogle Scholar
  15. 15.
    Kempf K, Neukirchen W, Martin S, et al. Self-monitoring of blood glucose in type 2 diabetes: a new look at published trials [letter]. Diabetologia 2008; 51: 686–8PubMedCrossRefGoogle Scholar
  16. 16.
    Karter AJ, Ackerson LM, Darbinian JA, et al. Self-monitoring of blood glucose levels and glycemic control: The Northern California Kaiser Permanente Diabetes Registry. Am J Med 2001; 111: 1–9PubMedCrossRefGoogle Scholar
  17. 17.
    Karter AJ, Parker MM, Moffet HH, et al. Longitudinal study of new and prevalent use of self-monitoring of blood glucose. Diabetes Care 2006; 29: 1757–63PubMedCrossRefGoogle Scholar
  18. 18.
    Soumerai SB, Mah C, Zhang F, et al. Effects of health maintenance organization coverage of self-monitoring devices on diabetes self-care and glucose control. Arch Intern Med 2004; 164: 645–52PubMedCrossRefGoogle Scholar
  19. 19.
    Canadian Diabetes Association (CDA). 2008 clinical practice guidelines for the prevention and management of diabetes in Canada. Can J Diabetes 2008; 32Suppl. 1: i–201Google Scholar
  20. 20.
    American Diabetes Association (ADA). 2010 clinical practice recommendations. Diabetes Care 2010; 33Suppl. 1: 1–96Google Scholar
  21. 21.
    Palmer AJ, Dinneen S, Gavin JR, et al. Cost-utility analysis in a UK setting of self-monitoring of blood glucose in patients with type 2 diabetes. Curr Med Res Opin 2006; 22: 861–72PubMedCrossRefGoogle Scholar
  22. 22.
    Tunis SL, Minshall ME. Self-monitoring of blood glucose in type 2 diabetes: cost-effectiveness in the United States. Am J Manag Care 2008; 14: 131–40PubMedGoogle Scholar
  23. 23.
    Simon J, Gray A, Clarke P, et al. Cost-effectiveness of self monitoring of blood glucose in patients with non-insulin treated type 2 diabetes: economic evaluation of data from the DiGEM Trial. BMJ 2008; 336: 1177–80PubMedCrossRefGoogle Scholar
  24. 24.
    Farmer AJ, Wade AN, French DP, et al. Blood glucose self-monitoring in type 2 diabetes: a randomized controlled trial. Health Technol Assess 2009; 13: 13–23Google Scholar
  25. 25.
    Tunis SL, Minshall ME. Self-monitoring of blood glucose (SMBG) for type 2 diabetes patients treated with oral anti-diabetes drugs and with a recent history of monitoring: cost-effectiveness in the US. Curr Med Res Opin 2010; 26: 151–62PubMedCrossRefGoogle Scholar
  26. 26.
    Tunis SL, Willis WD, Foos V. Self-monitoring of blood glucose for type 2 diabetes patients on oral anti-diabetes drugs: cost-effectiveness in France, Germany, Italy, and Spain. Curr Med Res Opin 2010; 26: 162–75Google Scholar
  27. 27.
    Farmer A, Wade A, Goyder E, et al. Impact of self monitoring of blood glucose in the management of patients with non-insulin treated diabetes: open parallel group randomised trial. BMJ 2007; 335: 132–9PubMedCrossRefGoogle Scholar
  28. 28.
    Clar C, Barnard K, Royle P, et al. Self-monitoring of blood glucose in type 2 diabetes: systematic review. Health Technol Assess 2010; 14: 1–140Google Scholar
  29. 29.
    Dean HJ. Self-monitoring of blood glucose levels in persons with type 2 diabetes not requiring insulin: routine use is not recommended. Can J Diabetes 2011; 35: 19–20Google Scholar
  30. 30.
    Cameron C, Coyle D, Ur E, et al. Cost-effectiveness of self-monitoring of blood glucose in patients with type 2 diabetes mellitus managed without insulin. CMAJ 2010; 182: 28–34PubMedGoogle Scholar
  31. 31.
    Canadian Optimal Medication Prescribing and Utilization Service (COMPUS). Optimal therapy recommendations for the prescribing and use of blood glucose test strips [CADTH Optimal Therapy Report]. Ottawa (ON): Canadian Agency for Drugs and Technologies in Health (CADTH), July 2009; 3 (6) [online]. Available from URL: http://www.cadth.ca/media/pdf/compus_BGTS_OT_Rec_e.pdf [Accessed 2010 Oct 4]Google Scholar
  32. 32.
    O’Reilly D, Hopkins R, Blackhouse G, et al. Development of an Ontario diabetes economic model (ODEM) and application to a multidisciplinary primary care diabetes management program. Hamilton (ON): Program for Assessment of Technology in Health (PATH), 2006 NovGoogle Scholar
  33. 33.
    Clarke PM, Gray AM, Briggs A, et al. A model to estimate the lifetime health outcomes of patients with type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS 68). Diabetologia 2004; 47: 1747–59PubMedCrossRefGoogle Scholar
  34. 34.
    Barnett AH, Krentz AJ, Strojek K, et al. The efficacy of self-monitoring of blood glucose in the management of patients with type 2 diabetes treated with a gliclazide modified release-based regimen: a multicentre, randomized, parallel-group, 6-month evaluation (DINAMIC 1 study). Diabetes Obes Metab 2008; 10: 1239–47PubMedCrossRefGoogle Scholar
  35. 35.
    Davidson MB, Castellanos M, Kain D, et al. The effect of self-monitoring of blood glucose concentrations on glycated hemoglobin levels in diabetic patients not taking insulin: a blinded, randomized trial. Am J Med 2005; 118: 422–5PubMedCrossRefGoogle Scholar
  36. 36.
    Guerci B, Drouin P, Grange V, et al. Self-monitoring of blood glucose significantly improves metabolic control in patients with type 2 diabetes mellitus: the Auto-Surveillance Intervention Active (ASIA) study. Diabetes Metab 2003; 29: 587–94PubMedCrossRefGoogle Scholar
  37. 37.
    Muchmore DB, Springer J, Miller M. Self-monitoring of blood glucose in overweight type 2 diabetic patients. Acta Diabetol 1994; 31: 215–9PubMedCrossRefGoogle Scholar
  38. 38.
    O’Kane MJ, Bunting B, Copeland M, et al. Efficacy of self-monitoring of blood glucose in patients with newly diagnosed type 2 diabetes (ESMON study): randomised controlled trial. BMJ 2008; 336: 1174–7PubMedCrossRefGoogle Scholar
  39. 39.
    Schwedes U, Siebolds M, Mertes G, SMBG Study Group. Meal-related structured self-monitoring of blood glucose. Diabetes Care 2002; 25: 1928–32PubMedCrossRefGoogle Scholar
  40. 40.
    Canadian Optimal Medication Prescribing and Utilization Service (COMPUS). Systematic review of use of blood glucose test strips for the management of diabetes mellitus [CADTH Optimal Therapy Report]. Ottawa (ON): Canadian Agency for Drugs and Technologies in Health (CADTH) 2009; 3 (2) [online]. Available from URL: http://www.cadth.ca/media/pdf/BGTS_SR_Report_of_Clinical_Outcomes.pdf [Accessed 2010 Jun 14]Google Scholar
  41. 41.
    Scottish Intercollegiate Guidelines Network. Methodology checklist 2: randomized controlled trials. In SIGN 50: a guideline developers’ handbook. Edinburgh: The Network, 2004Google Scholar
  42. 42.
    Sullivan PW, Ghushchyan V. Preference-based EQ-5D index scores for chronic conditions in the United States. Med Decis Making 2006; 26: 410–20PubMedCrossRefGoogle Scholar
  43. 43.
    International Society for Pharmacoeconomics and Outcomes Research. Guidelines for the economic evaluation of health technologies: Canada [online]. Available from URL: http://www.ispor.org/PEguidelines/source/HTAGuidelinesfortheEconomicEvaluationofHealthTechnologies-Canada.pdf [Accessed 2010 Oct 15]
  44. 44.
    Poolsup N, Suksomboon N, Rattanasookchit S. Metaanalysis of the benefits of self-monitoring of blood glucose on glycemic control in type 2 diabetes patients: an update. Diabetes Technol Ther 2009; 11: 775–84PubMedCrossRefGoogle Scholar
  45. 45.
    Towfigh A, Romanova M, Weinreb JE, et al. Self-monitoring of blood glucose levels in patients with type 2 diabetes mellitus not taking insulin: a meta-analysis. Am J Manag Care 2008; 14: 468–75PubMedGoogle Scholar
  46. 46.
    Welchen LM, Bloemendal E, Nijels G, et al. Self-monitoring of blood glucose in patients with type 2 diabetes who are not using insulin: a systematic review. Diabetes Care 2005; 28: 1510–7CrossRefGoogle Scholar
  47. 47.
    Sarol JN, Nicodemus NA, Tan KM, et al. Self-monitoring of blood glucose as part of a multi-component therapy among non-insulin requiring type 2 diabetes patients: a meta-analysis (1966-2004). Curr Med Res Opin 2005; 21: 173–83PubMedCrossRefGoogle Scholar
  48. 48.
    Jansen JP. Self-monitoring of glucose in type 2 diabetes mellitus: a Bayesian meta-analysis of direct and indirect comparisons. Curr Med Res Opin 2006; 22: 671–81PubMedCrossRefGoogle Scholar
  49. 49.
    Poolsup N, Suksomboon N, Jiamsathit W. Systematic review of the benefits of self-monitoring of blood glucose on glycemic control in type 2 diabetes patients. Diabetes Technol Ther 2008; 10Suppl. 1: 51–66Google Scholar
  50. 50.
    Martin S, Schneider B, Heinemann L, et al. Self-monitoring of blood glucose in type 2 diabetes and long-term outcome: an epidemiological cohort study. Diabetologia 2006; 49: 271–8PubMedCrossRefGoogle Scholar
  51. 51.
    Tunis SL, Minshall ME. The impact of clinical trial design on cost-effectiveness analyses: illustration from a published study of the One-Touch Ultrasmart Blood Glucose Meter for insulin-using diabetes patients. Diabetes Technol Ther 2008; 10: 227–31PubMedCrossRefGoogle Scholar
  52. 52.
    Tunis SL. Randomized clinical trial (RCT) design and analytic issues impacting assumed clinical effects and results of cost-effectiveness analyses: illustration from a recent Canadian report on the cost-effectiveness of blood glucose test strips for type 2 diabetes [poster]. 15th Annual International Meeting of ISPOR; Atlanta (GA); 2010 May 15-19Google Scholar
  53. 53.
    Polonsky WH, Fisher L, Schikman CH, et al. The value of episodic, intensive blood glucose monitoring in non-insulin treated persons with type 2 diabetes: design of the structured testing program (STeP) study, a cluster-randomised, clinical trial. BMC Fam Pract 2010; 11: 37–46PubMedCrossRefGoogle Scholar
  54. 54.
    Polonsky WH, Fisher L, Schikman CH, et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, non-insulin treated type 2 diabetes: results from the Structured Testing Program Study. Diabetes Care 2011; 34: 262–7PubMedCrossRefGoogle Scholar
  55. 55.
    Klonoff DC. New evidence demonstrates that self-monitoring of blood glucose does not improve outcomes in type 2 diabetes — when this practice is not applied properly. J Diabetes Sci Technol 2008; 2: 342–8PubMedGoogle Scholar
  56. 56.
    The National Collaborating Centre for Chronic Conditions. Type 2 diabetes national clinical guidelines for management in primary and secondary care (update). London: Royal College of Physicians for National Institute for Health and Clinical Excellence (NICE), 2008 [online]. Available from URL: http://www.nice.org.uk/nicemedia/live/11983/40803/40803.pdf [Accessed 2010 Sep 4]Google Scholar
  57. 57.
    Vincze G, Barner JC, Lopez D. Factors associated with adherence to self-monitoring of blood glucose among persons with diabetes. Diabetes Educ 2004; 30:112–9PubMedCrossRefGoogle Scholar
  58. 58.
    UKPDS Outcomes Model User Manual, version 1.2.1.June3, 2009. Oxford: ISIS Innovation Ltd, University of Oxford Diabetes Trials Unit (DTU) and Health Economics Research Centre (HERC), 2010 [online]. Available from URL: http://www.dtu.ox.ac.uk/outcomesmodel/ [Accessed 2010 Oct3]
  59. 59.
    Tunis SL. A cost-effectiveness analysis to illustrate the impact of cost definitions on results, interpretations, and comparability of pharmacoeconomic studies in the United States. Pharmacoeconomics 2009; 27(9): 735–44PubMedCrossRefGoogle Scholar
  60. 60.
    Gray A, Raikou M, McGuire A, et al. Cost effectiveness of an intensive blood glucose control policy in patients with type 2 diabetes: economic analysis alongside randomised controlled trial (UKPDS 41). BMJ 2000; 320: 1373–8PubMedCrossRefGoogle Scholar
  61. 61.
    McEwan P, Peters JR, Bergenheim K, et al. Evaluation of the costs and outcomes from changes in risk factors in type 2 diabetes using the Cardiff stochastic simulation cost-utility model (DiabForecaster). Cur Med Res Opin 2006; 22: 121–9CrossRefGoogle Scholar
  62. 62.
    Holman RR, Paul SK, Bethel MA, et al. Long-term follow-up after tight control of blood pressure in type 2 diabetes. N Engl J Med 2008; 359: 1565–76PubMedCrossRefGoogle Scholar
  63. 63.
    Clarke P, Gray A, Holman R. Estimating utility values for health states of type 2 diabetic patients using the EQ-5D (UKPDS 62). Med Decis Making 2002; 22: 340–9PubMedGoogle Scholar
  64. 64.
    Holman RR, Paul SK, Bethel MA, et al. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 2008; 359: 1577–89PubMedCrossRefGoogle Scholar
  65. 65.
    Hirsch IB. Home blood glucose monitoring in type 2 diabetes: broken health system undermines study’s impact. Diabetes Care 2011; 34: 527–8PubMedCrossRefGoogle Scholar
  66. 66.
    Latter C, McLean-Veysey P, Dunbar P, et al. Self-monitoring of blood glucose: what are healthcare professionals recommending? Can J Diabetes 2011; 35: 31–8Google Scholar

Copyright information

© Adis Data Information BV 2011

Authors and Affiliations

  1. 1.Independent Health Economics Research ConsultantIndianapolisUSA
  2. 2.IndianapolisUSA

Personalised recommendations