Trends in glycemic control over a 2-year period in 126 US hospitals

Longitudinal Digital Glucometric Benchmarking to Evaluate the Impact of Institutional Diabetes Care Initiatives in Adults With Diabetes Mellitus Over the 2016-2020 Period

BACKGROUND

While glucometric benchmarking has been used to compare glucose management between institutions, the value of longitudinal intra-institution benchmarking to assess quality improvement changes is not established.

METHODS

A prospective six-month observational study (October 2019-March 2020 inclusive) of inpatients with diabetes or newly detected hyperglycemia admitted to eight medical and surgical wards at the Royal Melbourne Hospital. Networked blood glucose (BG) meters were used to collect capillary BG levels. Outcomes were measures of glycemic control assessed by mean and threshold glucometric measures and comparison with published glucometric benchmarks. Intra-institution comparison was over the 2016-2020 period.

RESULTS

In all, 620 admissions (588 unique individuals) met the inclusion criteria, contributing 15 164 BG results over 4023 admission-days. Compared with the 2016 cohort from the same institution, there was increased BG testing (3.8 [SD = 2.2) vs 3.3 [SD = 1.7] BG measurements per patient-day, P < .001), lower mean patient-day mean glucose (PDMG; 8.9 mmol/L [SD = 3.2] vs 9.5 mmol/L [SD = 3.3], P < .001), and reduced mean and threshold measures of hyperglycemia (P < .001 for all). Comparison with institutions across the United States revealed lower incidence of mean PDMG >13.9 or >16.7 mmol/L, and reduced hypoglycemia (<3.9, <2.8, and <2.2 mmol/L), when compared with published benchmarks from an earlier period (2009-2014).

CONCLUSIONS

Comprehensive digital-based glucometric benchmarking confirmed institutional quality improvement changes were followed by reduced hyperglycemia and hypoglycemia in a five-year comparison. Longitudinal glucometric benchmarking enables evaluation and validation of changes to institutional diabetes care management practices.

Early intervention model of inpatient diabetes care improves glycemia following hospitalization

Admission to hospital provides an opportunity to optimize long-term diabetes management, but clinical inertia is common. We previously reported the randomized study of a proactive inpatient diabetes service (RAPIDS), investigating an early intervention model of care and demonstrated improved in-hospital glycemia and clinical outcomes. This follow-up study assessed whether proactive care in hospital improved postdischarge HbA1c. In a subgroup of 298 RAPIDS trial participants with type 2 diabetes, age <80 years, and admission HbA1c ≥ 7.0%, diabetes treatment intensification occurred more often in early intervention versus usual care groups (37% vs. 19% [p = .001]), adjusted odds ratio 3.2 (95% confidence interval [CI]: 1.7-6.0). There was a greater change in HbA1c in the early intervention group (mean -0.9% [95% CI -1.3 to -0.4]) versus the usual care group (-0.3% [-0.6 to -0.1]), p = .029. The value of acute care by dedicated inpatient diabetes teams can extend beyond improving inpatient clinical outcomes and can lead to sustained improvement in glycemia.

Safety and Efficacy of Inpatient Diabetes Management with Non-insulin Agents: an Overview of International Practices

PURPOSE OF REVIEW

The field of inpatient diabetes has advanced significantly over the last 20 years, leading to the development of personalized treatment approaches. However, outdated guidelines still recommend the use of basal-bolus insulin therapy as the preferred treatment approach, and against the use of non-insulin anti-hyperglycemic agents.

RECENT FINDINGS

Several observational and prospective randomized controlled studies have demonstrated that oral anti-hyperglycemic agents are widely used in the hospital, including studies of DPP-4 agents and GLP-1 agonists. With advances in the field of inpatient diabetes management, a paradigm shift has occurred, from an approach of recommending "basal-bolus regimens" for all patients to a more precision medicine option for hospitalized non-critically ill patients with type 2 diabetes.

Evidence-based therapeutics for hyperglycemia in hospitalized noncritically ill patients

Hyperglycemia in hospitalized patients, either with or without diabetes, is a common, serious, and costly healthcare problem. Evidence accumulated over 20 years has associated hyperglycemia with a significant increase in morbidity and mortality, both in surgical and medical patients. Based on this documented link between hyperglycemia and poor outcomes, clinical guidelines from professional organizations recommend the treatment of hospital hyperglycemia with a therapeutic goal of maintaining blood glucose (BG) levels less than 180 mg/dL. Insulin therapy remains a mainstay of glycemic management in the inpatient setting. The use of non-insulin antidiabetic drugs in the hospital setting is limited because little data are available regarding their safety and efficacy. However, information about the use of incretin-based therapy in inpatients has increased in the past 15 years. This review aims to summarize the different treatment strategies for hyperglycemia in hospitalized noncritical patients that are supported by observational studies or clinical trials with insulin and non-insulin drugs. In addition, we propose a protocol to help with the management of this important clinical problem.

Incretin-based therapy for glycemic control of hospitalized patients with type 2 diabetes: a systematic review

Incretin-based therapy leads to glycemic control in a glucose-dependent manner with a low risk of hypoglycemia, making it appealing for use in the hospital. The aim of this systematic review was to assess the benefits of incretin-based therapy in patients with type 2 diabetes hospitalized outside of the intensive care unit. We searched for studies published up to August 2021 in the PubMed and Scopus databases. Clinical trials comparing incretin-based therapy (alone or in combination with insulin) versus an insulin regimen were selected. The results of the included studies showed that incretin-based therapy showed mean blood glucose values, a percentage of records within the therapeutic target, and a percentage of treatment failure similar to insulin management, particularly in patients with mild to moderate hyperglycemia. Furthermore, incretin-based treatment was associated with a lower total insulin dose and a lower incidence of hypoglycemia. In conclusion, incretin-based therapy achieved glycemic control similar to insulin treatment in patients with type 2 diabetes hospitalized outside the intensive care unit and has the advantages of reducing the insulin requirement and a lower risk of hypoglycemia.

Age and glycemic control among adults with type 2 diabetes in the United States: An assessment from the National Health and Nutrition Examination Survey (NHANES) 2013-2014

AIM

To assess the age and its association with glycemic control (GC) among adults with type 2-diabetes in the United States.

MATERIALS AND MATERIALS

Data were collected from the National Nutrition Examination Survey (NHANES) 2013-2014 (n = 697), cross-sectional national survey adults with Type2 diabetes. Characteristics included retinopathy diagnosis, blood pressure, albumin-creatinine ratio, hemoglobin A1c (HbA1c), BMI, cholesterol, smoking status, pills/insulin, exercise, age, age at diagnosis, education, sex, race, and marital status. Diabetes preventive behaviors were included. Predictors of GC were assessed using logistic regression.

RESULTS

The mean age was 61 (SD ±13); the average age at diagnosis 50 (SD ±12.9) and women (51%). Age ≥60, diabetes length >10yrs, taking pills/on insulin, albumin-creatinine ratio ≤30mg/g, optimal BP, no retinopathy diagnosis, optimal cholesterol, seeing a doctor for diabetes, doctors checkup ≥2 times and checking HbA1c annually were significant predictors of GC. The association between GC and age (OR=.97, p<.001; CI: .96-.98) diabetes length >10yrs (OR=1.55, p<.05; CI: 1.02-2.34), creatinine-albumin ratio ≤30mg/g (OR=1.97, p<.001; CI: 1.32-2.94) and checking HbA1c annually (OR=1.86, p<.01; CI: 1.16-3.00) remained significant after adjustment for the effects of all other statistically significant covariates.

CONCLUSIONS

GC was prevalent among older individuals; suggestive of intervention programs for young adults with diabetes and continuous HbA1c assessment at least annually.

Treatment of Diabetes in Older Adults: An Endocrine Society* Clinical Practice Guideline

OBJECTIVE

The objective is to formulate clinical practice guidelines for the treatment of diabetes in older adults.

CONCLUSIONS

Diabetes, particularly type 2, is becoming more prevalent in the general population, especially in individuals over the age of 65 years. The underlying pathophysiology of the disease in these patients is exacerbated by the direct effects of aging on metabolic regulation. Similarly, aging effects interact with diabetes to accelerate the progression of many common diabetes complications. Each section in this guideline covers all aspects of the etiology and available evidence, primarily from controlled trials, on therapeutic options and outcomes in this population. The goal is to give guidance to practicing health care providers that will benefit patients with diabetes (both type 1 and type 2), paying particular attention to avoiding unnecessary and/or harmful adverse effects.

An individualized inpatient diabetes education and hospital transition program for poorly controlled hospitalized patients with diabetes

OBJECTIVE

To evaluate predictors of outcomes associated with an inpatient diabetes education and discharge support program for hospitalized patients with poorly controlled diabetes (glycated hemoglobin [HbA1c]>9%).

METHODS

Patients participated in individualized diabetes education conducted by a certified diabetes educator (CDE) that included an exploration of barriers and goal setting during hospitalization with telephone follow-up and communication with primary providers at discharge. Predictors of HbA1c reduction, successful follow-up, and readmission were analyzed.

RESULTS

There were 82 subjects, and 48% were insulin naïve. Patients with type 2 diabetes (T2D, n = 58) had a significant decrease in HbA1c at follow-up (-2.8%, P<.0001), while those with type 1 diabetes (T1D, n = 19) did not (+0.02%, P = .96). However, after adjustment for other factors, only increasing age, higher baseline HbA1c, earlier education, and initiation of basal insulin were significant predictors of reduction in HbA1c. Higher area level income and empowerment and earlier education were significant predictors of outpatient follow-up within 30 days. While 28% were admitted for severe hyperglycemia, only 1 patient was readmitted with severe hyperglycemia. Successful phone contact was 77% and 57% with and without the support of non-CDE assistants respectively, but all outcomes were similar.

CONCLUSION

The study suggests that an individualized inpatient diabetes education and transition program is associated with a significant reduction in HbA1c that is dependent on baseline HbA1c, older age, initiation of insulin, and earlier enrollment. Additional interventions are needed to ensure better continuity of care.

The association of postoperative glycemic control and lower extremity procedure outcomes

OBJECTIVE

The effect of postoperative hyperglycemia in patients undergoing open and endovascular procedures on the lower extremities has not been fully characterized with regard to associated admission diagnoses, hospital complications, mortality, and 30-day readmission. This study evaluated the relationship of postoperative hyperglycemia on outcomes after lower extremity vascular procedures for peripheral artery disease.

METHODS

Patients with peripheral artery disease admitted for elective lower extremity procedures between September 2008 and March 2014 were selected from the Cerner Health Facts (Cerner Corporation, Kansas City, Mo) database using International Classification of Diseases, Ninth Edition, Clinical Modification diagnosis and procedure codes. Using χ² analysis, we evaluated the relationship of postoperative hyperglycemia (>180 mg/dL) with sociodemographic characteristics, acute and chronic diagnoses, infections, hospital length of stay (LOS), and 30-day readmission. An adjusted multivariable logistic model was used to examine the association of postoperative hyperglycemia with infection and LOS.

RESULTS

Of 3586 patients in the study, 2812 (78%) had optimal postoperative glucose control, and 774 (22%) had suboptimal glucose control (hyperglycemia). On average, patients with postoperative hyperglycemia experienced longer hospital stays (6.9 vs 5.1 days; P < .0001), higher Charlson Comorbidity Index scores (3.4 vs 2.5, P < .0001), higher rates of infection (23% vs 14%, P < .0001), more acute complications (ie, fluid and electrolyte disorders, acute renal failure, postoperative respiratory complications), and chronic problems (ie, anemia, chronic heart disease, chronic kidney disease, and diabetes) than patients with optimal glucose control. Overall 30-day readmission was 10.9% and was similar between the groups (10.9% for both; P = .93). Major amputations did not differ between groups (P = .21). After adjusting for other risk factors using multivariable logistic regression, patients with hyperglycemia have 1.3-times the odds to have an infectious complication compared with those with optimal glucose control (odds ratio [OR], 1.34; 95% confidence interval [CI], 1.06-1.69) and 1.7-times the odds to have a hospital LOS >10 days (OR, 1.69; 95% CI, 1.32-2.15). As well, patients with postoperative hyperglycemia have 8.4-times the odds of dying in the hospital (OR, 8.40; 95% CI, 3.95-17.9).

CONCLUSIONS

One in five patients undergoing vascular procedures had postoperative hyperglycemia. Postoperative hyperglycemia was associated with adverse events after lower extremity vascular procedures in patients with and without diabetes, including infection, increased hospital utilization, and mortality. No difference was found with respect to hospital readmission. Postprocedure glucose management may represent an important quality marker for improving outcomes after lower extremity vascular procedures.

Is all hypoglycaemia treated as equal? An observational study of how the type of diabetes and treatment prescribed prior to admission influences quality of treatment of inpatient hypoglycaemia

AIMS

Inpatient hypoglycaemia is common and associated with adverse outcomes. There is often increased vigilance of hypoglycaemia in inpatients with type 1 diabetes (T1DM) compared to type 2 diabetes (T2DM). We aimed to investigate this apparent discrepancy, utilising the time to repeat (TTR) capillary blood glucose (CBG) measurement as a surrogate for engagement with guidelines stating that CBG should be rechecked following intervention within 15 min of an initial CBG of <4 mmol/L.

METHODS

This is an observational study of inpatient CBG data from 8 hospitals over a 7-year period. A national diabetes registry allowed identification of individual's diagnosis and diabetes therapy. For each initial (index) CBG, the TTR for individuals with T2DM-on insulin or sulphonylurea-was compared with the TTR for individuals with T1DM, using a t test for significance performed on log(TTR). The median TTR was plotted for each group per index CBG.

RESULTS

In total, 1480,335 CBG measurements were obtained. A total of 26,664 were <4 mmol/L. The TTR in T2DM individuals on sulphonylurea was significantly greater than in T1DM individuals where index CBG was ≥2.3 mmol/L (except index CBG 2.6 mmol/L). For T2DM patients receiving insulin significance exists for index CBGs of ≥3.2 mmol/L.

CONCLUSIONS

This analysis suggests that quality of care of hypoglycaemia varies according to diagnosis and medication. The group with the highest TTR (T2DM sulphonylurea treated) are possibly the clinical group in whom hypoglycaemia is most concerning. These data therefore suggest a need for education and raising awareness within the inpatient nursing staff.

Statistical transformation and the interpretation of inpatient glucose control data

OBJECTIVE

To introduce a statistical method of assessing hospital-based non-intensive care unit (non-ICU) inpatient glucose control.

METHODS

Point-of-care blood glucose (POC-BG) data from hospital non-ICUs were extracted for January 1 through December 31, 2011. Glucose data distribution was examined before and after Box-Cox transformations and compared to normality. Different subsets of data were used to establish upper and lower control limits, and exponentially weighted moving average (EWMA) control charts were constructed from June, July, and October data as examples to determine if out-of-control events were identified differently in nontransformed versus transformed data.

RESULTS

A total of 36,381 POC-BG values were analyzed. In all 3 monthly test samples, glucose distributions in nontransformed data were skewed but approached a normal distribution once transformed. Interpretation of out-of-control events from EWMA control chart analyses also revealed differences. In the June test data, an out-of-control process was identified at sample 53 with nontransformed data, whereas the transformed data remained in control for the duration of the observed period. Analysis of July data demonstrated an out-of-control process sooner in the transformed (sample 55) than nontransformed (sample 111) data, whereas for October, transformed data remained in control longer than nontransformed data.

CONCLUSION

Statistical transformations increase the normal behavior of inpatient non-ICU glycemic data sets. The decision to transform glucose data could influence the interpretation and conclusions about the status of inpatient glycemic control. Further study is required to determine whether transformed versus nontransformed data influence clinical decisions or evaluation of interventions.

Addressing Inpatient Glycaemic Control with an Inpatient Glucometry Alert System

Background. Poor inpatient glycaemic control has a prevalence exceeding 30% and results in increased length of stay and higher rates of hospital complications and inpatient mortality. The aim of this study was to improve inpatient glycaemic control by developing an alert system to process point-of-care blood glucose (POC-BG) results. Methods. Microsoft Excel Macros were developed for the processing of daily glucometry data downloaded from the Cobas IT database. Alerts were generated according to ward location for any value less than 4 mmol/L (hypoglycaemia) or greater than 15 mmol/L (moderate-severe hyperglycaemia). The Diabetes Team provided a weekday consult service for patients flagged on the daily reports. This system was implemented for a 60-day period. Results. There was a statistically significant 20% reduction in the percentage of hyperglycaemic patient-day weighted values >15 mmol/L compared to the preimplementation period without a significant change in the percentage of hypoglycaemic values. The time-to-next-reading after a dysglycaemic POC-BG result was reduced by 14% and the time-to-normalization of a dysglycaemic result was reduced from 10.2 hours to 8.4 hours. Conclusion. The alert system reduced the percentage of hyperglycaemic patient-day weighted glucose values and the time-to-normalization of blood glucose.

Point-of-care blood glucose testing for diabetes care in hospitalized patients: an evidence-based review

Glycemic control in hospitalized patients with diabetes requires accurate near-patient glucose monitoring systems. In the past decade, point-of-care blood glucose monitoring devices have become the mainstay of near-patient glucose monitoring in hospitals across the world. In this article, we focus on its history, accuracy, clinical use, and cost-effectiveness. Point-of-care devices have evolved from 1.2 kg instruments with no informatics to handheld lightweight portable devices with advanced connectivity features. Their accuracy however remains a subject of debate, and new standards for their approval have now been issued by both the International Organization for Standardization and the Clinical and Laboratory Standards Institute. While their cost-effectiveness remains to be proved, their clinical value for managing inpatients with diabetes remains unchallenged. This evidence-based review provides an overall view of its use in the hospital setting.

Using the glucometrics website to benchmark ICU glucose control before and after the NICE-SUGAR study

Prior to 2009, intensive glycemic control was the standard in main intensive care units (ICUs). Glucose targets have been recalibrated after publication of the NICE-SUGAR study in that year, followed by updated guidelines that endorsed more moderated control. We sought to determine if the prevalence of hyperglycemia in US ICUs had increased after the NICE-SUGAR study's results were reported. We used data from hospitals submitted to the Yale Glucometrics™ website to assess mean blood glucose values, percentage of blood glucose within various ranges, and the prevalence of hypo- and hyperglycemic excursions, based on the patient-day method, comparing the pre- to post-NICE-SUGAR time period. Among more than a total of 2 million blood glucose determinations, comprising 408 790 patient-days, median patient-day blood glucose decreased from 144 mg/dL to 141 mg/dL (P < .001) in the pre- versus post-NICE-SUGAR time period. The percentage of patient days with a mean blood glucose of 110-179 mg/dl increased from 58.3 to 63.6%. The percentage of patient-days with either hypoglycemia (<70 mg/dl) or severe hyperglycemia (≥300 mg/dl) decreased during this time. Our results suggest that glycemic control in US ICUs has improved when comparing time periods before versus after publication of the NICE-SUGAR study. We found no evidence that fewer hypoglycemic events were achieved at the expense of more hyperglycemia.

Addressing Glycemic Targets from Diagnosis to Discharge

On any given day, from 25 to 50% of all hospitalized patients meet criteria for a diagnosis of diabetes, prediabetes, or hyperglycemia. It is essential for all health care providers, including diabetes clinicians, to examine current processes to ensure the delivery of the highest quality care, with a focus on glucose control, improved outcomes, and patient safety from admission through discharge.

Statistical transformation and the interpretation of inpatient glucose control data from the intensive care unit

Glucose control can be problematic in critically ill patients. We evaluated the impact of statistical transformation on interpretation of intensive care unit inpatient glucose control data. Point-of-care blood glucose (POC-BG) data derived from patients in the intensive care unit for 2011 was obtained. Box-Cox transformation of POC-BG measurements was performed, and distribution of data was determined before and after transformation. Different data subsets were used to establish statistical upper and lower control limits. Exponentially weighted moving average (EWMA) control charts constructed from April, October, and November data determined whether out-of-control events could be identified differently in transformed versus nontransformed data. A total of 8679 POC-BG values were analyzed. POC-BG distributions in nontransformed data were skewed but approached normality after transformation. EWMA control charts revealed differences in projected detection of out-of-control events. In April, an out-of-control process resulting in the lower control limit being exceeded was identified at sample 116 in nontransformed data but not in transformed data. October transformed data detected an out-of-control process exceeding the upper control limit at sample 27 that was not detected in nontransformed data. Nontransformed November results remained in control, but transformation identified an out-of-control event less than 10 samples into the observation period. Using statistical methods to assess population-based glucose control in the intensive care unit could alter conclusions about the effectiveness of care processes for managing hyperglycemia. Further study is required to determine whether transformed versus nontransformed data change clinical decisions about the interpretation of care or intervention results.

Diurnal temporal patterns of hypoglycaemia in hospitalized people with diabetes may reveal potentially correctable factors

AIM

To determine whether diurnal temporal variations in hypoglycaemic frequency occur in hospitalized patients.

METHODS

Hypoglycaemic events were identified in a snapshot bedside audit of capillary blood glucose results from diabetes charts of all inpatients receiving insulin or a sulphonylurea (with or without insulin) on 2 days separated by 6 weeks. Additionally, capillary blood glucose measurements were remotely captured over 2 months, in the same category of patients, and analysed for temporal patterns. Hypoglycaemia was defined as 'severe' when the capillary blood glucose was < 3.0 mmol/l and 'mild' when the capillary blood glucose was between 3.0 and 3.9 mmol/l.

RESULTS

The bedside audit found that 74% of those audited experienced a hypoglycaemia event. Eighty-three per cent of all hypoglycaemic events and 70% of severe events were recorded between 21.00 and 09.00 h. This was confirmed in the longer duration remote monitoring study where 70% of all hypoglycaemic events and 66% of severe events occurred between 21.00 and 09.00 h.

CONCLUSION

Hypoglycaemia occurs more frequently between 21.00 and 09.00 h in hospitalized patients receiving treatments that can cause hypoglycaemia. This may be related to insufficient carbohydrate intake during this period, and is potentially preventable by changes in catering practice.