The Effects of a Comprehensive Multidisciplinary Outpatient Diabetes Program on Hospital Readmission Rates in Patients with Diabetes: A Randomized Controlled Prospective Study.

OBJECTIVE: The diagnosis of diabetes mellitus is associated with an increased risk of hospital readmissions. The goal of this study was to determine whether there was a difference in the rates of 30-day and 365-day hospital readmissions between diabetic patients who, upon their discharge, received diabetes care in a standard primary care setting and those who received their care in a specialized multidisciplinary diabetes program. METHODS: This was a randomized controlled prospective study. RESULTS: One hundred and ninety two consecutive patients were recruited into the study, 95 (49%) into standard care (control group) and 97 (51%) into a multidisciplinary diabetes program (intervention group). The 30-day overall hospital readmission rates (including both emergency department and hospital readmissions) were 19% in the control group and 7% in the intervention group (P = .02). The 365-day overall hospital readmission rates were 38% in the control group and 14% in the intervention group (P = .0002). CONCLUSION: Patients with diabetes who are assigned to a specialized multidisciplinary diabetes program upon their discharge exhibit significantly reduced hospital readmission rates at 30 days and 365 days after discharge.

Reliability of continuous glucose monitoring system in the inpatient setting.

AIMS/HYPOTHESIS: Hyperglycemia and hypoglycemia are associated with increased morbidity and mortality in the inpatient setting. Standard point of care capillary glucose testing (POCT) is commonly used in hospitalized patients to monitor their glucose levels. The goal of this study was to examine the relationships between the glucose readings obtained by a continuous glucose monitoring system (CGMS) (Freestyle Libre) and the capillary blood glucose results obtained by the inpatient glucose POCT meter (Accuchek Inform II) as well as between CGMS readings and the serum glucose values obtained by the hospital laboratory. Study participants had either primary or secondary diagnosis of diabetes mellitus and were admitted to non-critical units. We hypothesized that there exists an acceptable agreement between the capillary blood glucose results obtained by the inpatient glucose POCT meter (Accuchek Inform II) and the readings obtained by the CGMS (Freestyle Libre); and that there exists an acceptable agreement between the serum glucose levels and the glucose values obtained by the CGMS. METHODS: This was an Institutional Review Board approved prospective cohort study for the non- critical inpatient setting. Fifty-two hospitalized patients with diabetes were recruited. After informed consent was obtained, patients were instructed on the application and use of the CGMS. The data were assessed using a standard regression analysis and modified Bland Altman analysis. All analyses were conducted using SAS, release 3.8 Enterprise Edition (SAS Institute Inc., Cary, NC). RESULTS: Fifty-two subjects recruited into the study represented a sample of convenience. There were a total of 467 AccuChek-Libre pairs, The regression analysis showed a negative bias between.Libre and AccuChek, R2 = 0.83, with Libre glucose readings on average being lower than those of AccuChek. Using Bland-Altman analysis, 42% of the 467 Libre-AccuChek pairs had a difference in glucose reading more than 15%. Mean absolute relative difference (MARD) between Libre and AccuChek was 15.6%; mean relative difference (MRD) between Libre and AccuChek was -11.4%.The regression analysis showed a negative bias between Libre and serum glucose, R2 = 0.89. Using Bland Altman analysis, 36% of the 44 Libre-serum pairs had a difference in glucose reading more than 15%. Mean absolute relative difference (MARD) between Libre and serum glucose was 13.2%; mean relative difference (MRD) between Libre and serum glucose was -12.5%.A review of the data pairs showed that 71/467 Accuchek-Libre pairs had one result that was either below 70 mg/dl or above 200 mg/dl (combined American Diabetes Association-ADA-, American College of Physicians-ACP- and American College of Endocrinology-AACE- goals). Thus 85%, of these pairs would have yielded results that engendered the same intervention (e.g. treatment for hypoglycemia or hyperglycemia). Likewise 5/45 Serum-Libre pairs had one result that was either below 70 mg/dl or above 200 mg/dl; thus 89% of these pairs would have yielded results requiring the same intervention. CONCLUSION/INTERPRETATION: These findings confirm the existent literature and indicate acceptable agreement between the standard POCT and the CGMS as well as between serum glucose and the CGMS values. Because of the advantages of the CGMS over capillary blood glucose testing (reduced patient discomfort and reduced staff exposure to patients in isolation) CGMS use may be preferable to the current bedside capillary blood glucose testing in hospitalized patients with diabetes mellitus. As with other laboratory measures, clinical judgement needs to be exercised when the laboratory values are used to guide patient care.

Social and Behavioral Determinants of Perceived Insufficient Sleep.

Insufficient sleep is associated with cardiometabolic disease and poor health. However, few studies have assessed its determinants in a nationally representative sample. Data from the 2009 behavioral risk factor surveillance system were used (N = 323,047 adults). Insufficient sleep was assessed as insufficient rest/sleep over 30 days. This was evaluated relative to sociodemographics (age, sex, race/ethnicity, marital status, region), socioeconomics (education, income, employment, insurance), health behaviors (diet, exercise, smoking, alcohol), and health/functioning (emotional support, BMI, mental/physical health). Overall, insufficient sleep was associated with being female, White or Black/African-American, unemployed, without health insurance, and not married; decreased age, income, education, physical activity; worse diet and overall health; and increased household size, alcohol, and smoking. These factors should be considered as risk factors for insufficient sleep.