Evaluation of the clinical effectiveness of a computerised decision-supported intensive insulin therapy regimen

Introduction

It has been proposed that intensive insulin therapy (IIT) aiming for a blood glucose (BG) of 4.4–6.1 mmol/l reduces mortality in critically ill patients when compared with conventional insulin therapy (CIT) targeting BG at 10.0–11.1 mmol/l. Difficulties with IIT include inadvertent hypoglycaemia and low efficacy at achieving the target BG. We proposed that computerised decision support may mitigate these problems.

Objective

To comprehensively describe BG and outcome from decision-supported IIT.

Methods

A clinical information system at each bedspace guided staff through the IIT algorithm. The time spent within glucose ranges was calculated assuming a linear trend between successive measurements.

Results

Patient characteristics are shown in Table 1. The IIT group had more frequent BG evaluation (7,007 over 8,944 patient-hours, 0.78 tests/hour) than the CIT group (3,609 over 8,617 hours, 0.42 tests/hour). The median (interquartile range (IQR)) proportion of time spent in the target range 4.4–6.1 mmol/l was similar in the IIT and CIT groups (23.21% (15.4–29.8) vs 17.9% (9.8–29.3), respectively; P = 0.17). Similarly, time spent with a BG between 6.2 and 7.99 mmol/l was no different for the two groups (48.5% (IQR 36.9–59.3) for IIT and 43.9% (IQR 34.7–60.9), P = 0.72). In the IIT and CIT groups, five and six patients experienced a BG below 2.2 mmol/l, respectively.

Table 1

Discussion

Computerised decision-support and more intensive monitoring did not improve BG control or reduce the incidence of hypoglycaemia.