OBJECTIVES: To simulate and compare the clinical and economic outcomes of self-monitoring of blood glucose (SMBG) devices along ranges of accuracy from a German payer perspective. METHODS: We programmed a long-term type 1 diabetes natural history and treatment cost-effectiveness model. In phase one, using past in-silico evidence (UVa/Padova simulator, accepted by the Food and Drug Administration for pre-clinical studies), we associated changes in SMBG error to changes in HbA1c, and separately, changes in severe hypoglycemia and hyperglycemia requiring an inpatient stay. In phase two, using Markov cohort simulations, we estimated the lifetime clinical and economic outcomes based on a German payer perspective. The primary comparison was a SMBG device with strip price €0.56 Euros and 10% error (exceeding accuracy requirements by International Organization for Standardization (ISO) 15197:2013) versus a SMBG device with the same strip price and 15% error (accuracy meeting ISO 15197:2013). Outputs for the average patient over a 5-year time horizon, discounted at 3% per annum, were severe hypoglycemic and hyperglycemic events requiring an inpatient stay, quality-adjusted life years (QALYs), and cost differences per patient. RESULTS: Assuming the benefits translate into HbA1c improvements only, an SMBG device with 10% versus 15% error was associated with an increase of 0.023 QALYs and a cost savings of €100 Euros per patient over 5 years. Assuming the benefits translate into reduced severe hypoglycemic and hyperglycemic events requiring an inpatient stay only, an SMBG device with 10% versus 15% error was associated with a combined decrease in severe hypoglycemic and hyperglycemic events of 0.86 and cost savings of €976 Euros per patient over 5 years. CONCLUSIONS: Investing in devices with improved accuracy (less error) appears to be an affordable strategy with improved quality of life for type 1 diabetes patients.