Elsevier

Endocrine Practice

Volume 20, Issue 9, September 2014, Pages 876-883
Endocrine Practice

Original Article
Benchmarking Glycemic Control In U.S. Hospitals

https://doi.org/10.4158/EP13516.ORGet rights and content

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. (Endocr Pract. 2014;20:876-883)

Section snippets

INTRODUCTION

The prevalence of diabetes mellitus continues to increase and currently affects about 8% of the U.S. population. Costs associated with inpatient diabetes care continue to rise as well 1., 2.. In-hospital blood glucose control has received considerable attention over the years 3., 4., 5., 6., and several organizations have embraced the importance of managing inpatient hyperglycemia; furthermore, they have developed guidelines and educational programs to assist practitioners with management 7., 8.

METHODS

This study was reviewed and considered exempt from requiring review by the Mayo Clinic Institutional Review Board.

Characteristics of Participating Hospitals and Blood Glucose Measurement Data

The current data set (derived from 635 hospitals) included 149 hospitals that were new to the RALS system since the last analysis, published in 2011 (13). Additionally, 87 institutions that were included previously no longer reported data. The greatest number of new additions and withdrawals were characteristically the smallest hospitals (< 200 beds), urban community hospitals, and Southern hospitals (Table 1). The data set included a large sample of POC-BG values, patients, and hospitalizations

DISCUSSION

The number of hospitalizations associated with diabetes and their related costs continue to increase. Thus, inpatient diabetes care will pose a significant challenge and burden to the U.S. healthcare system 1., 2.. Optimal inpatient glycemic control is advocated by many professional organizations and healthcare institutions 3., 7., 8., 9., 11.. Assessment of glycemic control may become of greater importance to individual hospitals as healthcare reimbursements become tied to outcome. As many

CONCLUSION

Despite these limitations, we report the largest data set of glycemic measures in U.S. hospitals available to date. Although the types and numbers of facilities reporting POC-BG data have varied from one published report to the next, consistent relationships between blood glucose control and hospital characteristics were observed across analyses. Given these hospital-based differences, along with nonstandard and possibly changing technologies used to measure POC-BG values, more discussion is

DISCLOSURE

Gail L. Kongable is an employee of the Epsilon and Alere Informatics Solutions, Charlottesville, VA. Jianfen Shu has received statistical consultant grand from the Epsilon Group, Charlottesville, VA. Denise R. Zito is an employee of Alere Informatics Solution, Charlottesville, VA. The other authors have no multiplicity of interest to disclose.

ACKNOWLEDGMENT

Alere Informatics provides the RALS-Plus laboratory information system software to hospitals. Roche Diagnostics has provided grant support to generate glucose management data reports as value-added for their hospital clients. This analysis was supported entirely by Alere Informatics (as the Epsilon Group), Charlottesville, Virginia, and a contractual arrangement is in place between Mayo Clinic and Alere Informatics.

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    Published as a Rapid Electronic Article in Press at http://www.endocrinepractice.org on March 18, 2014. DOI: 10.4158/EP13516.OR

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