Clinical Decision Support for Glycemic Management Reduces Hospital Length of Stay

A systematic review of the value of clinical decision support systems in the prescription of antidiabetic drugs

INTRODUCTION

The management of chronic diabetes mellitus and its complications demands customized glycaemia control strategies. Polypharmacy is prevalent among people with diabetes and comorbidities, which increases the risk of adverse drug reactions. Clinical decision support systems (CDSSs) may constitute an innovative solution to these problems. The aim of our study was to conduct a systematic review assessing the value of CDSSs for the management of antidiabetic drugs (AD).

MATERIALS AND METHODS

We systematically searched the scientific literature published between January 2010 and October 2023. The retrieved studies were categorized as non-specific or AD-specific. The studies' quality was assessed using the Mixed Methods Appraisal Tool. The review's results were reported in accordance with the PRISMA guidelines.

RESULTS

Twenty studies met our inclusion criteria. The majority of AD-specific studies were conducted more recently (2020-2023) compared to non-specific studies (2010-2015). This trend hints at growing interest in more specialized CDSSs tailored for prescriptions of ADs. The nine AD-specific studies focused on metformin and insulin and demonstrated positive impacts of the CDSSs on different outcomes, including the reduction in the proportion of inappropriate prescriptions of ADs and in hypoglycaemia events. The 11 nonspecific studies showed similar trends for metformin and insulin prescriptions, although the CDSSs' impacts were not significant. There was a predominance of metformin and insulin in the studied CDSSs and a lack of studies on ADs such as sodium-glucose cotransporter-2 (SGLT-2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists.

CONCLUSION

The limited number of studies, especially randomized clinical trials, interested in evaluating the application of CDSS in the management of ADs underscores the need for further investigations. Our findings suggest the potential benefit of applying CDSSs to the prescription of ADs particularly in primary care settings and when targeting clinical pharmacists. Finally, establishing core outcome sets is crucial for ensuring consistent and standardized evaluation of these CDSSs.

Technology in the management of diabetes in hospitalised adults

Suboptimal glycaemic management in hospitals has been associated with adverse clinical outcomes and increased financial costs to healthcare systems. Despite the availability of guidelines for inpatient glycaemic management, implementation remains challenging because of the increasing workload of clinical staff and rising prevalence of diabetes. The development of novel and innovative technologies that support the clinical workflow and address the unmet need for effective and safe inpatient diabetes care delivery is still needed. There is robust evidence that the use of diabetes technology such as continuous glucose monitoring and closed-loop insulin delivery can improve glycaemic management in outpatient settings; however, relatively little is known of its potential benefits and application in inpatient diabetes management. Emerging data from clinical studies show that diabetes technologies such as integrated clinical decision support systems can potentially mediate safer and more efficient inpatient diabetes care, while continuous glucose sensors and closed-loop systems show early promise in improving inpatient glycaemic management. This review aims to provide an overview of current evidence related to diabetes technology use in non-critical care adult inpatient settings. We highlight existing barriers that may hinder or delay implementation, as well as strategies and opportunities to facilitate the clinical readiness of inpatient diabetes technology in the future.

Practice-enhancing publications about the medication-use process in 2022

PURPOSE

This article identifies, prioritizes, and summarizes published literature on the medication-use process (MUP) from calendar year 2022 that can impact health-system pharmacy daily practice. The MUP is the foundational system that provides the framework for safe medication utilization within the healthcare environment. The MUP is defined in this article as having the following components: prescribing/transcribing, dispensing, administration, and monitoring. Articles evaluating at least one step of the MUP were assessed for their usefulness toward practice improvement.

SUMMARY

A PubMed search was conducted in January 2023 for articles published in calendar year 2022 using targeted Medical Subject Headings (MeSH) keywords, and searches of the table of contents of selected pharmacy journals were conducted, providing a total of 6,213 articles. A thorough review identified 69 potentially practice-enhancing articles: 13 for prescribing/transcribing, 13 for dispensing, 5 for administration, and 38 for monitoring. Practice trends discussed in the articles are briefly summarized, with a mention of their importance within health-system pharmacy. The articles are listed and summarized in tables for further review and evaluation.

CONCLUSION

It is important to routinely review the published literature and to incorporate significant findings into daily practice. This article assists in identifying and summarizing the most impactful publications. Health-system pharmacists have an active role in improving the MUP in their institution, and awareness of the significant published studies can assist in changing practice at the institutional level.

Implementing a Sodium-Glucose Cotransporter 2 Inhibitor Module With a Software Tool (Future Health Today): Qualitative Study

BACKGROUND

Primary care plays a key role in the management of type 2 diabetes. Sodium-glucose cotransporter 2 (SGLT2) inhibitors have been demonstrated to reduce hospitalization and cardiac and renal complications. Tools that optimize management, including appropriate prescribing, are a priority for treating chronic diseases. Future Health Today (FHT) is software that facilitates clinical decision support and quality improvement. FHT applies algorithms to data stored in electronic medical records in general practice to identify patients who are at risk of a chronic disease or who have a chronic disease that may benefit from intensification of management. The platform continues to evolve because of rigorous evaluation, continuous improvement, and expansion of the conditions hosted on the platform. FHT currently displays recommendations for the identification and management of chronic kidney disease, cardiovascular disease, type 2 diabetes, and cancer risk. A new module will be introduced to FHT focusing on SGLT2 inhibitors in patients with type 2 diabetes who have chronic kidney diseases, cardiovascular diseases, or risk factors for cardiovascular disease.

OBJECTIVE

The study aims to explore the barriers and enablers to the implementation of an SGLT2 inhibitor module within the Future Health Today software.

METHODS

Clinic staff were recruited to participate in interviews on their experience in their use of a tool to improve prescribing behavior for SGLT2 inhibitors. Thematic analysis was guided by Clinical Performance Feedback Intervention Theory.

RESULTS

In total, 16 interviews were completed. Identified enablers of use included workflow alignment, clinical appropriateness, and active delivery of the module. Key barriers to use were competing priorities, staff engagement, and knowledge of the clinical topic.

CONCLUSIONS

There is a recognized benefit to the use of a clinical decision support tool to support type 2 diabetes management, but barriers were identified that impeded the usability and actionability of the module. Successful and effective implementation of this tool could support the optimization of patient management of type 2 diabetes in primary care.

Comparison of in-patient glucose team based management with conventional blood glucose management- a retrospective study from China

BACKGROUND

Glycemic control for patients with diabetes in the surgical department is often unsatisfactory. Compounding this issue is the fact that conventional glucose management models are often inefficient and difficult to monitor over time.

OBJECTIVE

To investigate the impact of inpatient glucose team-based management on glycemic control and hospital days in surgical patients with diabetes.

METHODS

A retrospective analysis was conducted on 4156 patients with diabetes in the surgical department who received inpatient management of diabetes at a tertiary medical center from June 2020 to May 2022. Based on whether they received inpatient glucose team-based management, the surgical patients with diabetes were divided into two groups: the inpatient glucose team-based management (GM group, consisting of 1698 participants) and the conventional blood glucose management group (control group, consisting of 2458 participants). We compared the two groups in terms of glycemic control, hospital days, and health-care costs. Multiple logistic regression analysis was performed to build the hospital days prediction model and nomogram. Finally, the performance of the model was evaluated.

RESULTS

The rate of glucose detection was higher in the GM group at 2 h postprandial (P < 0.01). The incidence of hypoglycemia and severe hyperglycemia, blood glucose attainment time, pre-operative preparation days, hospital days, and health-care costs were lower in the GM group than in the control group (P < 0.01). The linear regression model revealed that blood glucose attainment time, incidence of hypoglycemia (< 3.9mmol/L), preoperative preparation days, perioperative complications, and health-care costs were the factors influencing the hospital days (Total Point 83.4 points, mean hospital days 9.37 days). Receiver operating characteristic (ROC) curve analysis demonstrated that the nomogram had good accuracy for predicting hospital days (area under the ROC curve 0.83, 95% confidence interval [CI], 0.74 to 0.92).

CONCLUSION

Inpatient glucose team-based management demonstrated significant improvements in glycemic control among surgical patients with diabetes, resulting in reduced hospital days and associated costs. The developed nomogram also exhibited promising potential in predicting hospital days, offering valuable clinical applications.