OBJECTIVES: More than one-third of hospitalized patients have hyperglycemia. Despite evidence that improving glycemic control leads to better outcomes, achieving recognized targets remains a challenge. The objective of this study was to evaluate the implementation of a computerized insulin order set and titration algorithm on rates of hypoglycemia and overall inpatient glycemic control. METHODS: A prospective observational study evaluating the impact of a glycemic order set and titration algorithm in an academic medical center in non-critical care medical and surgical inpatients. The initial intervention was hospital-wide implementation of a comprehensive insulin order set. The secondary intervention was initiation of an insulin titration algorithm in two pilot medicine inpatient units. Point of care testing blood glucose reports were analyzed. These reports included rates of hypoglycemia (BG < 70 mg/dL) and hyperglycemia (BG >200 mg/dL in phase 1, BG > 180 mg/dL in phase 2). RESULTS: In the first phase of the study, implementation of the insulin order set was associated with decreased rates of hypoglycemia (1.92% vs 1.61%; p < 0.001) and increased rates of hyperglycemia (24.02% vs 27.27%; p < 0.001) from 2010 to 2011. In the second phase, addition of a titration algorithm was associated with decreased rates of hypoglycemia (2.57% vs 1.82%; p = 0.039) and increased rates of hyperglycemia (31.76% vs 41.33%; p < 0.001) from 2012 to 2013. CONCLUSIONS: A comprehensive computerized insulin order set and titration algorithm significantly decreased rates of hypoglycemia. This significant reduction in hypoglycemia was associated with increased rates of hyperglycemia. Hardwiring the algorithm into the electronic medical record may foster adoption.
OBJECTIVES: More than one-third of hospitalized patients have hyperglycemia. Despite evidence that improving glycemic control leads to better outcomes, achieving recognized targets remains a challenge. The objective of this study was to evaluate the implementation of a computerized insulin order set and titration algorithm on rates of hypoglycemia and overall inpatient glycemic control. METHODS: A prospective observational study evaluating the impact of a glycemic order set and titration algorithm in an academic medical center in non-critical care medical and surgical inpatients. The initial intervention was hospital-wide implementation of a comprehensive insulin order set. The secondary intervention was initiation of an insulin titration algorithm in two pilot medicine inpatient units. Point of care testing blood glucose reports were analyzed. These reports included rates of hypoglycemia (BG < 70 mg/dL) and hyperglycemia (BG >200 mg/dL in phase 1, BG > 180 mg/dL in phase 2). RESULTS: In the first phase of the study, implementation of the insulin order set was associated with decreased rates of hypoglycemia (1.92% vs 1.61%; p < 0.001) and increased rates of hyperglycemia (24.02% vs 27.27%; p < 0.001) from 2010 to 2011. In the second phase, addition of a titration algorithm was associated with decreased rates of hypoglycemia (2.57% vs 1.82%; p = 0.039) and increased rates of hyperglycemia (31.76% vs 41.33%; p < 0.001) from 2012 to 2013. CONCLUSIONS: A comprehensive computerized insulin order set and titration algorithm significantly decreased rates of hypoglycemia. This significant reduction in hypoglycemia was associated with increased rates of hyperglycemia. Hardwiring the algorithm into the electronic medical record may foster adoption.
Entities:
Keywords:
Hypoglycemia; computerized order sets; hyperglycemia; inpatient glycemic control
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