Clinical decision support to improve management of diabetes and dysglycemia in the hospital: a path to optimizing practice and outcomes

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.

Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review

BACKGROUND

Providing comprehensive and individualized diabetes care remains a significant challenge in the face of the increasing complexity of diabetes management and a lack of specialized endocrinologists to support diabetes care. Clinical decision support systems (CDSSs) are progressively being used to improve diabetes care, while many health care providers lack awareness and knowledge about CDSSs in diabetes care. A comprehensive analysis of the applications of CDSSs in diabetes care is still lacking.

OBJECTIVE

This review aimed to summarize the research landscape, clinical applications, and impact on both patients and physicians of CDSSs in diabetes care.

METHODS

We conducted a scoping review following the Arksey and O'Malley framework. A search was conducted in 7 electronic databases to identify the clinical applications of CDSSs in diabetes care up to June 30, 2022. Additional searches were conducted for conference abstracts from the period of 2021-2022. Two researchers independently performed the screening and data charting processes.

RESULTS

Of 11,569 retrieved studies, 85 (0.7%) were included for analysis. Research interest is growing in this field, with 45 (53%) of the 85 studies published in the past 5 years. Among the 58 (68%) out of 85 studies disclosing the underlying decision-making mechanism, most CDSSs (44/58, 76%) were knowledge based, while the number of non-knowledge-based systems has been increasing in recent years. Among the 81 (95%) out of 85 studies disclosing application scenarios, the majority of CDSSs were used for treatment recommendation (63/81, 78%). Among the 39 (46%) out of 85 studies disclosing physician user types, primary care physicians (20/39, 51%) were the most common, followed by endocrinologists (15/39, 39%) and nonendocrinology specialists (8/39, 21%). CDSSs significantly improved patients' blood glucose, blood pressure, and lipid profiles in 71% (45/63), 67% (12/18), and 38% (8/21) of the studies, respectively, with no increase in the risk of hypoglycemia.

CONCLUSIONS

CDSSs are both effective and safe in improving diabetes care, implying that they could be a potentially reliable assistant in diabetes care, especially for physicians with limited experience and patients with limited access to medical resources.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.37766/inplasy2022.9.0061.

Guardians For Health: A Practical Approach to Improving Quality of Life and Longevity in People with Type 2 Diabetes

Type 2 diabetes is one of the fastest-growing health emergencies of the twenty-first century, in part due to its association with cardiovascular and renal disease. Successful implementation of evidence-based guidelines for the management of patients with diabetes and pre-diabetes has been shown to improve patient outcomes by controlling risk factors for cardiovascular and renal disease. Recommendations include the early introduction of lifestyle adjustments, supported by pharmacological tools. Despite the availability of regularly updated, evidence-based guidelines, guideline implementation in clinical practice is low. As a result, people living with type 2 diabetes are not consistently receiving ideal clinical care. Improving guideline adherence has the potential to improve quality of life and longevity in patients with type 2 diabetes. This article introduces Guardians For Health, a global initiative that aims to improve guideline adherence by simplifying patient management and encouraging patient participation in the implementation of guidelines for type 2 diabetes. Guardians For Health is supported by a global community of implementers, with tools to support decision-making and quality assurance. Through achieving better guideline adherence, Guardians For Health hopes to achieve its vision to "stop early mortality by reducing cardiovascular and kidney complications in people with type 2 diabetes".

How Can Point-of-Care Technologies Support In-Hospital Diabetes Care?

People with diabetes admitted to hospital are at risk of diabetes related complications including hypoglycaemia and diabetic ketoacidosis. Point-of-care (POC) tests undertaken at the patient bedside, for glucose, ketones, and other analytes, are a key component of monitoring people with diabetes, to ensure safety. POC tests implemented with a quality framework are critical to ensuring accuracy and veracity of results and preventing erroneous clinical decision making. POC results can be used for self-management of glucose levels in those well-enough and/or by healthcare professionals to identify unsafe levels. Connectivity of POC results to electronic health records further offers the possibility of utilising these results proactively to identify patients 'at risk' in real-time and for audit purposes. In this article, the key considerations when implementing POC tests for diabetes in-patient management are reviewed and potential to drive improvements using networked glucose and ketone measurements are discussed. In summary, new advances in POC technology should allow people with diabetes and the teams looking after them whilst in hospital to integrate to provide safe and effective care.

Day-to-day fasting plasma glucose variability on the short-term prognosis of ST-segment elevation myocardial infarction: A retrospective cohort study

BACKGROUND AND HYPOTHESIS

Glycemic variability in one fact that explain the differences in cardiovascular outcomes. The short-term fasting plasma glucose (FPG) variability may have an on major adverse cardiovascular events (MACE) in type 2 diabetes mellitus (T2DM) patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

This study retrospectively analyzed T2DM patients who underwent emergent percutaneous coronary intervention (PCI) due to STEMI in Fuwai Hospital, Chinese Academy of Medical Sciences, Shenzhen, between January 2016 and March 2020. All patients underwent at least 5 FPG measurements during the perioperative period. FPG variability score (FPG-VS) was defined as the percentage of the number of FPG variations > 1 mmol/L between two adjacent FPG measurements. The Cox proportional-hazards model was used to estimate the relationship between FPG-VS and MACE. A validation set was utilized to further evaluate the prognostic value of FPG-VS in a standardized STEMI diabetic diet cohort following PCI intervention.

RESULTS

A total of 612 patients were included in the retrospective cohort study. In comparison to the minimum quintile, FPG-VS > 60% was associated with an increased risk of 30-day MACE. Moreover, compared to FPG-VS ≤ 20%, the FPG-VS > 80% group had a higher risk of MACE (odd ratio [OR] = 4.87, 95% confidence interval [CI]: 2.55-5.28), recurrent angina pectoris (OR = 5.43, 95% CI: 2.27-8.27), nonfatal myocardial infarction (OR = 5.00, 95% CI: 2.47-7.69), heart failure (OR = 3.70, 95% CI: 1.92-5.54), malignant arrhythmia (OR = 4.63, 95% CI: 1.12-6.25) and cardiac death (OR = 1.41, 95% CI: 0.17-1.97). Consistent results were obtained after adjustment for HbA1c, demonstrating the robustness of FPGFPG-VS. Moreover, the standard diet intervention group had a lower FPG-VS index as well as a lower incidence of MACE.

CONCLUSION

Higher FPG variability is associated with an increased risk of MACE within 30 days in diabetes patients receiving PCI for STEMI. A standardized diet may improve the prognosis of STEMI patients by reducing the FPG-VS.

Clinical Decision Support for Glycemic Management Reduces Hospital Length of Stay

OBJECTIVE

Dysglycemia influences hospital outcomes and resource utilization. Clinical decision support (CDS) holds promise for optimizing care by overcoming management barriers. This study assessed the impact on hospital length of stay (LOS) of an alert-based CDS tool in the electronic medical record that detected dysglycemia or inappropriate insulin use, coined as gaps in care (GIC).

RESEARCH DESIGN AND METHODS

Using a 12-month interrupted time series among hospitalized persons aged ≥18 years, our CDS tool identified GIC and, when active, provided recommendations. We compared LOS during 6-month-long active and inactive periods using linear models for repeated measures, multiple comparison adjustment, and mediation analysis.

RESULTS

Among 4,788 admissions with GIC, average LOS was shorter during the tool's active periods. LOS reductions occurred for all admissions with GIC (-5.7 h, P = 0.057), diabetes and hyperglycemia (-6.4 h, P = 0.054), stress hyperglycemia (-31.0 h, P = 0.054), patients admitted to medical services (-8.4 h, P = 0.039), and recurrent hypoglycemia (-29.1 h, P = 0.074). Subgroup analysis showed significantly shorter LOS in recurrent hypoglycemia with three events (-82.3 h, P = 0.006) and nonsignificant in two (-5.2 h, P = 0.655) and four or more (-14.8 h, P = 0.746). Among 22,395 admissions with GIC (4,788, 21%) and without GIC (17,607, 79%), LOS reduction during the active period was 1.8 h (P = 0.053). When recommendations were provided, the active tool indirectly and significantly contributed to shortening LOS through its influence on GIC events during admissions with at least one GIC (P = 0.027), diabetes and hyperglycemia (P = 0.028), and medical services (P = 0.019).

CONCLUSIONS

Use of the alert-based CDS tool to address inpatient management of dysglycemia contributed to reducing LOS, which may reduce costs and improve patient well-being.

American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update

OBJECTIVE

The objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers.

METHODS

The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development.

RESULTS

This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes.

CONCLUSIONS

This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.

Electronic Health Record-Based Decision-Making Support in Inpatient Diabetes Management

PURPOSE OF REVIEW

This review discusses ways in which the electronic health record (EHR) can offer clinical decision support (CDS) tools for management of inpatient diabetes and hyperglycemia.

RECENT FINDINGS

The use of electronic order sets can help providers order comprehensive basal bolus insulin regimens that are consistent with current guidelines. Order sets have been shown to reduce insulin errors and hypoglycemia rates. They can also help set glycemic targets, give hemoglobin A1C reminders, guide weight-based dosing, and match insulin regimen to nutritional profile. Glycemic management dashboards allow multiple variables affecting blood glucose to be shown in a single view, which allows for efficient evaluation of glucose trends and adjustment of insulin regimen. With the use glycemic management dashboards, active surveillance and remote management also become feasible. Hypoglycemia prevention and management are another part of inpatient diabetes management that is enhanced by EHR CDS tools. Furthermore, diagnosis and management of diabetic ketoacidosis and hyperglycemia hyperosmolar state are improved with the aid of EHR CDS tools. The use of EHR CDS tools helps improve the care of patients with diabetes and hyperglycemia in the inpatient hospital setting.

Relationships Among Perception of Cognitive Function, Diabetes Self-Management, and Glucose Variability in Older Adults: A Mixed Methods Study

The aim of the current study was to explore relationships among perceived cognitive function, glucose variability, and self-management in older adults with type 2 diabetes mellitus (T2DM). A mixed methods design was used with data from: (a) questionnaires on perceived cognitive function and diabetes self-management; (b) continuous glucose monitoring (CGM) reports; and (c) semi-structured interviews. Thirty adults with T2DM (47% female; mean age = 68.5 [SD = 5.2] years) participated. Those who exercised more days per week had more stable glucose. Those who reported fewer days of diet adherence had more hypoglycemia. Participants who reported higher levels of memory dissatisfaction exhibited higher levels of glucose variability. Findings point to the potential of glucose variability as a target to reduce the effect of diabetes on cognitive function. Instruction in recognition of glucose patterns found via CGM can be integrated into self-management education to improve self-management and subsequent glucose control and cognitive function. [Research in Gerontological Nursing, xx(x), xx-xx.].

Use of a Continuous Glucose Monitoring System in High Risk Hospitalized Non-critically ill Patients with Diabetes after Cardiac Surgery and during their Transition of Care from the Intensive Care Unit during Covid-19-A Pilot Study

OBJECTIVE

Continuous glucose monitoring (CGM) has demonstrated benefits in managing inpatient diabetes. We initiated this single-arm pilot feasibility study during the COVID-19 pandemic in 11 patients to determine the feasibility and accuracy of real-time CGM in cardiac surgery patients with diabetes after their transition of care from the intensive care unit(ICU).

METHODS

Clarke Error Grid(CEG) analysis was used to compare CGM and point-of-care(POC) measurements. Mean absolute relative difference(MARD) of the paired measurements was calculated to assess the accuracy of the CGM for glucose measurements during the first 24 hours on CGM, the remainder of time on the CGM as well as for different chronic kidney disease(CKD) strata.

RESULTS

Overall MARD between POC and CGM measurements was 14.80%. MARD for patients without CKD IV and V with eGFR < 20 ml/min/1.73m² was 12.13%. Overall, 97% of the CGM values were within the no-risk zone of the CEG analysis. For the first 24 hours, a sensitivity analysis of the overall MARD for all subjects and for those with eGFR > 20 ml/min/1.73m² was 15.42% (+/- 14.44) and 12.80% (+/- 7.85) respectively. Beyond the first 24 hours, overall MARD for all subjects and for those with eGFR > 20 ml/min/1.73m² was 14.54% (+/- 13.21) and 11.86% (+/- 7.64) respectively.

CONCLUSIONS

CGM has great promise to optimize inpatient diabetes management in the noncritical care setting and after the transition of care from the ICU with high clinical reliability, and accuracy. More studies are needed to further assess CGM in patients with advanced CKD.

Lack of recognition and documentation of stress hyperglycemia is a disruptor of optimal continuity of care

Stress hyperglycemia (SH) is a manifestation of altered glucose metabolism in acutely ill patients which worsens outcomes and may represent a risk factor for diabetes. Continuity of care can assess this risk, which depends on quality of hospital clinical documentation. We aimed to determine the incidence of SH and documentation tendencies in hospital discharge summaries and continuity notes. We retrospectively examined diagnoses during a 12-months period. A 3-months representative sample of discharge summaries and continuity clinic notes underwent manual abstraction. Over 12-months, 495 admissions had ≥ 2 blood glucose measurements ≥ 10 mmol/L (180 mg/dL), which provided a SH incidence of 3.3%. Considering other glucose states suggestive of SH, records showing ≥ 4 blood glucose measurements ≥ 7.8 mmol/L (140 mg/dL) totaled 521 admissions. The entire 3-months subset of 124 records lacked the diagnosis SH documentation in discharge summaries. Only two (1.6%) records documented SH in the narrative of hospital summaries. Documentation or assessment of SH was absent in all ambulatory continuity notes. Lack of documentation of SH contributes to lack of follow-up after discharge, representing a disruptor of optimal care. Activities focused on improving quality of hospital documentation need to be integral to the education and competency of providers within accountable health systems.