Clinical Decision Support for Glycemic Management Reduces Hospital Length of Stay

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.