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Insulin use is challenging for both primary care providers (PCPs) and patients.  For PCPs, a major challenge is time constraints, and for many, inexperience.  For patients, it is providing enough fingerstick glucose readings for insulin dose adjustments to be made.  The first author has developed algorithms for adjusting insulin doses based on the following principles.  Depending on when injected, each component of the insulin regimen has a maximal effect on a specific period of the 24-hour cycle, e.g., overnight, morning, afternoon, evening.  The glucose pattern in that period determines whether the dose of that component of the insulin regimen requires adjusting or not.  There needs to be enough glucose readings in a period that reflects a patient’s current lifestyle for a decision to be made about that component of the insulin regimen that maximally affects that period.

A registered nurse using these algorithms at clinic visits lowered HbA1c levels in 111 poorly controlled insulin-requiring patients from 11.0% to 7.2% within 9-12 months.  When computerized, these FDA-cleared algorithms produce a report within 15 seconds after glucose meters are downloaded with recommendations for insulin dose adjustments that the PCP can modify or accept.  In a pilot project utilizing these computerized algorithms in poorly controlled insulin-requiring patients who performed remote glucose monitoring, baseline HbA1c levels decreased from 10.0% to 8.1% in 3 months and to 7.6% in 6 months without any clinic visits for adjustment of insulin doses.  In a proof-of-concept project utilizing these computerized algorithms in poorly controlled insulin-requiring patients using continuous glucose monitoring (CGM), baseline HbA1c levels decreased from 11.5% to 8.3% over a mean of 3 months.

Computerized insulin dose adjustment algorithms and CGM meet both the PCP and patient challenges.  These innovations should be strongly considered to effectively decrease HbA1c levels, especially in poorly controlled patients.