Tides of change: improving glucometrics in a large multihospital health care system

Digital interventions to improve safety and quality of inpatient diabetes management: A systematic review

IMPORTANCE

Diabetes is common amongst hospitalised patients and contributes to increased length of stay and poorer outcomes. Digital transformation, particularly the implementation of electronic medical records (EMRs), is rapidly occurring across the healthcare sector and provides an opportunity to improve the safety and quality of inpatient diabetes care. Alongside this revolution has been a considerable and ongoing evolution of digital interventions to optimise care of inpatients with diabetes including optimisation of EMRs, digital clinical decision support systems (CDSS) and solutions utilising data visibility to allow targeted patient review.

OBJECTIVE

To systematically appraise the recent literature to determine which digitally-enabled interventions including EMR, CDSS and data visibility solutions improve the safety and quality of non-critical care inpatient diabetes management.

METHODS

Pubmed, Embase and Cochrane databases were searched for suitable articles. Selected articles underwent quality assessment and analysis with results grouped by intervention type.

RESULTS

1202 articles were identified with 42 meeting inclusion criteria. Four key interventions were identified; computerised physician order entry (n = 4), clinician decision support systems (n = 21), EMR driven active case finding (data visibility solutions) and targeted patient review (n = 10) and multicomponent system interventions (n = 7). Studies reported on glucometric outcomes, evidence-based medication ordering including medication errors, and patient and user outcomes. An improvement in glucometric measures particularly mean blood glucose and proportion of target range blood glucose levels and rates of evidence-based insulin prescribing were consistently demonstrated.

CONCLUSION

Digitally-enabled interventions utilised to improve quality and safety of inpatient diabetes care were heterogenous in design. The majority of studies across all intervention types reported positive effects for evidence-based prescribing and glucometric outcomes. There was less evidence for digital interventions reducing diabetes medication administration errors or impacting patient outcomes (length of stay).

Subcutaneous Insulin Dosing Calculators for Inpatient Glucose Control

PURPOSE OF REVIEW

The goal of this review is to summarize information about insulin dosing software and calculators used as computerized decision support systems or electronic glucose management systems (eGMS). These are used for hospitalized, insulin-treated patients with diabetes. We describe the advantages and disadvantages and the rationale for their use.

RECENT FINDINGS

We compared commercially available insulin dosing software, namely, Glucommander™, EndoTool®, GlucoStabilizer®, and GlucoTab®, in addition to computerized order entry systems that are available in electronic health records. The common feature among these eGMS is their ability to limit occurrences of hypoglycemia while achieving and maintaining patients at target blood glucose level. More research needs to be done examining the efficacy of eGMS in disease-specific states and their benefits and utility in preventing adverse outcomes. Their long-term benefits to health care systems are beginning to emerge in cost-saving benefits and prevention of readmissions.

Interventions to improve insulin prescribing practice for people with diabetes in hospital: a systematic review

AIM

To conduct a systematic review of literature to identify interventions that are effective in improving insulin prescribing for people with diabetes in the hospital setting.

METHODS

Computerized bibliographic databases were searched for studies published in English that described the effectiveness of interventions to improve insulin prescribing within the hospital setting. Studies were eligible for inclusion if they reported data that compared insulin prescribing practice after an intervention or compared with a control group. Studies were not excluded on the basis of publication date, geographical location or risk of bias assessment.

RESULTS

We identified 35 studies for inclusion in the review, including two cluster randomized controlled trials, two cohort studies, and 31 uncontrolled before-after studies. Studies reported a variety of interventions that aimed to increase insulin prescribing accuracy or completeness or decrease the use of discouraged subcutaneous sliding scale insulin regimens. Differences in definition of insulin prescribing error, terminology and common practice based on geographical location was evident, and quality issues with respect to study design and reporting somewhat limited the interpretation of conclusions.

CONCLUSIONS

Implementing strategies that are sensitive to local context and designed to increase adherence to insulin prescribing guidelines are associated with a reduction in prescribing errors. Future implementation should build on effective approaches including multifaceted interventions involving multiple stakeholders at various institutional levels. Future studies in insulin prescribing errors would benefit from the use of standardized approaches, terminology and outcome measures to enable greater comparison.

Safely Converting an Entire Academic Medical Center From Sliding Scale to Basal Bolus Insulin via Implementation of the eGlycemic Management System

OBJECTIVE

Hyperglycemia is common in the inpatient setting and providers frequently rely on sliding scale insulin. This case study reviews the experience of one hospital moving from high utilization of sliding scale to basal bolus insulin therapy.

METHOD

This Retrospective Quality Improvement Study describes the journey of clinicians at a 580-bed hospital to convert from high usage of SSI to BBI. Hyperglycemic adult patients prescribed insulin, with/without a diagnosis of diabetes, were included.

RESULTS

Data over the first year showed that patients treated with Glucommander (GM) spent more time in the target range of 70-180 mg/dL than patients treated with non-Glucommander (non-GM), with 2,434 fewer hypoglycemic events and 40,589 fewer hyperglycemic events. Prior to implementation of GM, SSI was close to 95%, BBI at 5%. Within the first month of use, 96% usage of BBI was achieved. Reduction of hypoglycemic events (% of BG < 70 mg/dL) by 21% with 2.16% non-GM compared to GM at 1.74% and severe Hypoglycemia (% of BG < 50 mg/dL) by 50% in the ICU 3% non-GM compared to GM at 1.5%. In addition, patients treated with GM had a shorter LOS than patients treated with non-GM by 3.18 days and used 47.4% less point of care tests per patient.

CONCLUSION

Glycemic management improved with use of eGMS. The conversion from SSI to BBI enhanced overall patient safety, eliminated the time and effort otherwise required when manually titrating insulin and reduced overall cost of care for patients on insulin therapy.

Comparison of an Electronic Glycemic Management System Versus Provider-Managed Subcutaneous Basal Bolus Insulin Therapy in the Hospital Setting

BACKGROUND

American Diabetes Association (ADA) guidelines recommend a basal bolus correction insulin regimen as the preferred method of treatment for non-critically ill hospitalized patients. However, achieving ADA glucose targets safely, without hypoglycemia, is challenging. In this study we evaluated the safety and efficacy of basal bolus subcutaneous (SubQ) insulin therapy managed by providers compared to a nurse-directed Electronic Glycemic Management System (eGMS).

METHOD

This retrospective crossover study evaluated 993 non-ICU patients treated with subcutaneous basal bolus insulin therapy managed by a provider compared to an eGMS. Analysis compared therapy outcomes before Glucommander (BGM), during Glucommander (DGM), and after Glucommander (AGM) for all patients. The blood glucose (BG) target was set at 140-180 mg/dL for all groups. The safety of each was evaluated by the following: (1) BG averages, (2) hypoglycemic events <40 and <70 mg/dL, and (3) percentage of BG in target.

RESULT

Percentage of BG in target was BGM 47%, DGM 62%, and AGM 36%. Patients' BGM BG average was 195 mg/dL, DGM BG average was 169 mg/dL, and AGM BG average was 174 mg/dL. Percentage of hypoglycemic events <70 mg/dL was 2.6% BGM, 1.9% DGM, and 2.8% AGM treatment.

CONCLUSION

Patients using eGMS in the DGM group achieved improved glycemic control with lower incidence of hypoglycemia (<40 mg/dL and <70 mg/dl) compared to both BGM and AGM management with standard treatment. These results suggest that an eGMS can safely maintain glucose control with less hypoglycemia than basal bolus treatment managed by a provider.