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1.
Endocr Pract ; 20(9): 876-83, 2014 Sep.
Article in English | MEDLINE | ID: mdl-24641927

ABSTRACT

OBJECTIVE: Report data on glucose control from 635 U.S. hospitals. METHODS: Point-of-care blood glucose (POC-BG) test data from January through December 2012 from 635 facilities were extracted. Glucose control was evaluated using patient-day-weighted mean POC-BG values. We calculated hypoglycemia and hyperglycemia rates, stratified by presence or absence of intensive care unit (ICU) admission, and we evaluated the relationship between glycemic control and hospital characteristics. RESULTS: In total, 51,375,764 POC-BG measurements (non-ICU, 39,197,762; ICU, 12,178,002) from 2,612,966 patients (non-ICU, 2,415,209; ICU, 575,084) were analyzed. The mean POC-BG was 167 mg/dL for non-ICU patients and 170 mg/dL for ICU patients. The prevalence of hyperglycemia (defined as glucose value >180 mg/dL) was 32.3 and 28.2% in non-ICU and ICU patients, respectively. The prevalence of hypoglycemia (defined as glucose value <70 mg/dL) was 6.1 and 5.6% in non-ICU and ICU patients, respectively. In non-ICU and ICU settings, the patient-day-weighted mean glucose was highest in the smallest hospitals, in rural hospitals, and in hospitals located in the Northeast (all P<.01). For non-ICU patients, we observed a significant difference in the percentage of patient days with hypoglycemia by geographic region only (P<.001). In ICU patients, the prevalence of hypoglycemia varied significantly by hospital type (P<.03) and geographic region (P<.01). CONCLUSION: In this largest POC-BG data set analysis conducted to date, glycemic control varied according to hospital characteristics. Our findings remain consistent with previous reports. Among other variables, national benchmarking of inpatient glucose data will need to consider differences in hospital characteristics.

2.
J Diabetes Sci Technol ; 4(6): 1507-13, 2010 Nov 01.
Article in English | MEDLINE | ID: mdl-21129348

ABSTRACT

BACKGROUND: Hyperglycemia in the adult inpatient population remains a topic of intense study in U.S. hospitals. Most hospitals have established glycemic control programs but are unable to determine their impact. The 2009 Remote Automated Laboratory System (RALS) Report provides trends in glycemic control over 4 years to 576 U.S. hospitals to support their effort to manage inpatient hyperglycemia. METHODS: A proprietary software application feeds de-identified patient point-of-care blood glucose (POC-BG) data from the Medical Automation Systems RALS-Plus data management system to a central server. Analyses include the number of tests and the mean and median BG results for intensive care unit (ICU), non-ICU, and each hospital compared to the aggregate of the other hospitals. RESULTS: More than 175 million BG results were extracted from 2006-2009; 25% were from the ICU. Mean range of BG results for all inpatients in 2006, 2007, 2008, and 2009 was 142.2-201.9, 145.6-201.2, 140.6-205.7, and 140.7-202.4 mg/dl, respectively. The range for ICU patients was 128-226.5, 119.5-219.8, 121.6-226.0, and 121.1-217 mg/dl, respectively. The range for non-ICU patients was 143.4-195.5, 148.6-199.8, 145.2-201.9, and 140.7-203.6 mg/dl, respectively. Hyperglycemia rates of >180 mg/dl in 2008 and 2009 were examined, and hypoglycemia rates of <40 mg/dl (severe) and <70 mg/dl (moderate) in both 2008 and 2009 were calculated. CONCLUSIONS: From these data, hospitals can determine the current state of glycemic control in their hospital and in comparison to other hospitals. For many, glycemic control has improved. Automated POC-BG data management software can assist in this effort.


Subject(s)
Automation, Laboratory/standards , Benchmarking , Blood Glucose/analysis , Hospitals/standards , Hyperglycemia/diagnosis , Hypoglycemia/diagnosis , Outcome and Process Assessment, Health Care/standards , Point-of-Care Systems/standards , Quality Indicators, Health Care/standards , Biomarkers/blood , Humans , Hyperglycemia/blood , Hyperglycemia/prevention & control , Hypoglycemia/blood , Hypoglycemia/prevention & control , Inpatients , Intensive Care Units/standards , Medical Records Systems, Computerized/standards , Severity of Illness Index , Software , United States
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