Glucose alert system improves health professional responses to adverse glycaemia and reduces the number of hyperglycaemic episodes in non‐critical care inpatients

Kyi, Mervyn; Wraight, Paul R; Rowan, Lois M.; Marley, Katie A.; Colman, Peter G; Fourlanos, Spiros

doi:10.1111/dme.13623

Cited by 9 publications

(12 citation statements)

References 27 publications

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“…Glucometric assessment might be possible without networked meter technology, but it would require more resources, and incomplete or inaccurate data would be more likely. Most importantly, networked meters contribute to improved glycaemic and clinical outcomes by enabling remote surveillance of BG measurements and proactive glycaemic management programs …”

Section: Discussionmentioning

confidence: 99%

“…Similarly, acute hypoglycaemia in hospital can lead to neuroglycopenia, causing seizures, falls, and neurological injury, as well as cardiac ischaemia and arrhythmia . Adverse glycaemia is a term used to describe both hyperglycaemia and hypoglycaemia; both are associated with pathophysiology and adverse clinical outcomes, and optimising glycaemic control in hospital patients is essential . Glucometric reporting and benchmarking standards for optimal diabetes care, however, have not been standardised in Australian hospitals.…”

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confidence: 99%

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Glucometric benchmarking in an Australian hospital enabled by networked glucose meter technology

Kyi

Colman

Rowan

et al. 2019

Medical Journal of Australia

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Objective: To assess glucometric outcomes and to estimate the incidence of hypo-and hyperglycaemia among non-critical care inpatients in a major Australian hospital.Design, setting and participants: A prospective 10-week observational study (7 March -22 May 2016) of consecutive inpatients with diabetes or newly detected hyperglycaemia admitted to eight medical and surgical wards at the Royal Melbourne Hospital. Point-of-care blood glucose (BG) data were collected with networked glucose meters. Main outcome measures:Glycaemic control, as assessed with three glucometric models (by population, by patient, by patientday); incidence of adverse glycaemic days (AGDs; patient-days with BG levels below 4 mmol/L or above 15 mmol/L). Results:During the study period, there were 465 consecutive admissions of 441 patients with diabetes or newly detected hyperglycaemia, and 9817 BG measurements over 2953 patientdays. The mean patient-day BG level was 9.5 mmol/L (SD, 3.3 mmol/L). The incidence of hyperglycaemia was higher than for a United States hospital benchmark (patient-days with mean BG level above 10 mmol/L, 37% v 32), and that of hypoglycaemia lower (proportion of patient-days with mean BG level below 3.9 mmol/L, 4.1% v 6.1%). There were 260 (95% CI, 245-277) AGDs per 1000 patient-days; the incidence was higher in medical than surgical ward patients (290 [CI,] v 206 [CI, 181-230] per 1000 patient-days). 604 AGDs (79%) were linked with 116 patients (25%). Episodes of hyperglycaemia (BG above 15 mmol/L) were more frequent before lunch, dinner, and bedtime; 94 of 187 episodes of hypoglycaemia (BG below 4 mmol/L) occurred between 11 pm and 8 am.Discussion: Glucometric analysis supported by networked glucose meter technology provides detailed inpatient data that could enable local benchmarking for promoting safe diabetes care in Australian hospitals.The known: Despite the importance of glucose control for people admitted to hospital, inpatient glucose levels have not been systematically audited or benchmarked in Australia. The new:We report the first detailed glucometric analysis for inpatients in a major Australian hospital, an analysis facilitated by networked glucose meter technology. For 260 of every 1000 patient-days, blood glucose levels were outside the safe range for hospital patients. The incidence of hyperglycaemia was higher and that of hypoglycaemia lower than in an American hospital benchmark.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Glucometric benchmarking in an Australian hospital enabled by networked glucose meter technology

Kyi

Colman

Rowan

et al. 2019

Medical Journal of Australia

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“…Target blood glucose level during acute coronary syndrome was defined as between 5 and 10 mmol/l, to reflect guideline recommendations . We defined an adverse glycaemic day, a concept developed by Kyi et al ., as a patient‐day with any blood glucose level < 4 or > 12 mmol/l, as these numbers reflect the parameters of our blood glucose monitoring chart . We incorporated this only as an exploratory measure for glycaemic control, as it is not a widely used concept.…”

Section: Participants and Methodsmentioning

confidence: 99%

Implementing simple algorithms to improve glucose and lipid management in people with diabetes and acute coronary syndrome

et al. 2019

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Aim Diabetes mellitus is associated with increased risk of adverse outcomes following acute coronary syndrome. Translating evidence‐based recommendations into practice is necessary to improve outcomes. We evaluated whether implementing algorithms to guide inpatient care improved glycaemic control, and increased use of sodium–glucose co‐transporter 2 (SGLT2) inhibitors and lipid‐lowering medication in a tertiary cardiac unit. Method A 3‐month audit (phase 1) was conducted to evaluate hyperglycaemia and dyslipidaemia management, and medication prescriptions. Consecutive people with diabetes admitted for acute coronary syndrome were prospectively identified. Target blood glucose level was defined as 5–10 mmol/l. A multidisciplinary committee designed and implemented decision‐support algorithms plus education. A 3‐month post‐implementation audit (phase 2) was conducted. Results There were 104 people in phase 1 and 101 in phase 2, with similar characteristics [HbA1c 64 ± 20 mmol/mol vs. 61 ± 21 mmol/mol (8.0 ± 1.8% vs. 7.8 ± 1.9%]. Post implementation, the incidence of blood glucose levels > 10 mmol/l was lower [phase 1: 46.4% vs. phase 2: 31.8%, rate ratio (RR) = 0.77, 95% confidence intervals (CI) 0.60–0.98; P = 0.031], without a difference in blood glucose levels < 5mmol/l (phase 1: 4.9% vs. phase 2: 4.5%, RR = 1.20, 95% CI 0.70–2.08; P = 0.506). SGLT2 inhibitor prescriptions increased significantly (baseline to discharge: 12.5% to 15.4% vs. 7.9% to 24.8%; P = 0.007) but high‐intensity statin prescriptions did not (baseline to discharge: 35.6% to 72.1% vs. 40.6% to 85.1%; P = 0.074). Prescription rates of non‐statin lipid‐lowering medications were not significantly increased. Conclusions Implementing decision‐support algorithms was associated with improved inpatient glycaemic control and increased use of cardioprotective therapies at discharge in people with diabetes and acute coronary syndrome.

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“…In addition to doctors, pharmacists and nurse prescribers may be well positioned to engage in autonomous or collaborative prescribing models to focus on diabetes care. Additionally, new technologies such as continuous glucose monitoring devices can reduce the burden of manual point‐of‐care blood glucose recording 19,20 . Centralised alert systems using networked glucose meters can bring hyperglycaemia, and hypoglycaemia, to the attention of clinicians, thus targeting therapeutic inertia and allow for streamlined benchmarking of glycaemic performance 19,20 .…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, new technologies such as continuous glucose monitoring devices can reduce the burden of manual point‐of‐care blood glucose recording 19,20 . Centralised alert systems using networked glucose meters can bring hyperglycaemia, and hypoglycaemia, to the attention of clinicians, thus targeting therapeutic inertia and allow for streamlined benchmarking of glycaemic performance 19,20 . A combination of these strategies may be necessary to optimise care for inpatients with diabetes and ACS.…”

Section: Discussionmentioning

confidence: 99%

Managing inpatient hyperglycaemia and initiating sodium‐glucose cotransporter 2 inhibitor therapy in the setting of diabetes and acute coronary syndrome

Hitchen

Lan

Hort

et al. 2021

Internal Medicine Journal

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We previously showed that implementing algorithms for managing diabetes in acute coronary syndrome was associated with improved inpatient glycaemic control and increased sodium‐glucose cotransporter 2 (SGLT2) inhibitor prescriptions. The present study performed 1 year later found that inpatient hyperglycaemia had relapsed to pre‐intervention rates, although SGLT2 inhibitor prescriptions remained increased. We discuss the challenges of improving inpatient glycaemic control.

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Glucose alert system improves health professional responses to adverse glycaemia and reduces the number of hyperglycaemic episodes in non‐critical care inpatients

Abstract: Use of a novel glucose alert system improved health professional responses to adverse glycaemia and decreased hyperglycaemia in the hospital setting.

Cited by 9 publications

References 27 publications

Glucometric benchmarking in an Australian hospital enabled by networked glucose meter technology

Glucometric benchmarking in an Australian hospital enabled by networked glucose meter technology

Implementing simple algorithms to improve glucose and lipid management in people with diabetes and acute coronary syndrome

Managing inpatient hyperglycaemia and initiating sodium‐glucose cotransporter 2 inhibitor therapy in the setting of diabetes and acute coronary syndrome

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