Original Research

Predictors of Suboptimal Glycemic Control for Hospitalized Patients with Diabetes: Targets for Clinical Action


 

From Sharp HealthCare, San Diego, CA (Ms. Thompson, Mr. Koucheki, Dr. Holdy), National University, San Diego, CA (Dr. Smith), and University of California, Irvine (Dr. Bender).

 

ABSTRACT

• Objective: Suboptimal glycemic control (SGC) puts hospitalized patients with diabetes at risk for poor outcomes. The purpose of this study was to quantify factors with predictive capacity to identify patients at risk for SGC during hospitalization.

• Methods: 32 baseline and demographic variables were extracted from the electronic records of 23,100 patients with diabetes hospitalized between 2009 and 2012. The rate of blood glucose values between 70 and 180 mg/dL was calculated for each patient. A predictive model for SGC was developed using regression modeling, standardized coefficients, and classification tree analysis. Odds ratios (ORs) were calculated to isolate adjusted odds of SGC for top predictors.

• Results: The final predictive model included 13 variables (C statistic = 0.88). HbA1c (OR, 0.60 [95% confidence interval {CI}, 0.58–0.61]), admission blood glucose (OR, 0.91 [CI, 0.91–0.92]), and steroid use (OR, 0.06 [CI 0.04–0.08]) were the highest-ranking predictors of SGC. HbA1c and SGC had a strong linear relationship (R = 0.99), with increasing odds for SGC as HbA1c increased. Admission blood glucose and SGC had a polynomial relationship (R 2 = 0.95); increasing odds for SGC until 240 mg/dL; then odds started decreasing. Steroid use showed a steady threefold increase in odds for SGC across all rates of use.

• Conclusions: Poor preadmission diabetes control and inpatient steroid use strongly predict SGC. A range of thresholds for these predictors was empirically determined, providing a basis for targeted therapies on admission. Guidelines incorporating empirically derived thresholds should enhance the ability to achieve optimal glycemic control for hospitalized patients with diabetes.

 

Current recommendations for glycemic control of hospitalized patients include use of multidisciplinary diabetic care teams and standardized insulin order sets [1,2], yet there is still uncertainty how best to target such protocols for patients with diabetes at risk for suboptimal glycemic control [2,3]. Many factors are theorized to hinder optimal inpatient glycemic control, such as steroid use [4,5],comorbid states [6],severity of illness [7,8], and preadmission glycemic control [9,10]. However, there currently exists little evidence of these factors’ ability to predict suboptimal glycemic control (SGC). Identifying straightforward predictive factors of SGC would provide a clinically meaningful basis for targeted therapy. The purpose of this study was to describe the prevalence of a range of potential risk factors in a diverse hospitalized patient population with a secondary diagnosis of diabetes (types 1 and 2), and to determine which factors were predictive of SGC.

 

METHODS

A retrospective cohort study design was used to identify factors predictive of inpatient SGC for patients admitted to any of 3 hospitals aligned with Sharp HealthCare (“Sharp”), a community-based, nonprofit integrated health system headquartered in San Diego, California, that serves more than 27% of the county’s 3 million-plus residents each year.

 

Inclusion Criteria

We extracted data for 23,100 patients hospitalized between January 2009 and December 2012 with a secondary diagnosis of diabetes (types 1 and 2), a length of stay (LOS) ≥ 3 days, and a minimum of 2 point-of-care (POC) blood glucose tests per day. The LOS and blood glucose minimum are standard criteria for Sharp glycemic monitoring to ensure a minimum quantity of blood glucose monitoring for glycemic management.

 

Glycemic Control (Independent Variable)

Glycemic control was defined as POC blood glucose values within the target range of 70 to 180 mg/dL during hospitalization. POC tests outside that range were defined as SGC. This range was determined based on current Sharp benchmark targets and was not adjusted for total number of blood glucose values.

 

Predictive Variables

A framework for potentially relevant patient and clinical care factors associated with suboptimal glycemic control was developed based on literature review and input from Sharp clinical experts. Administrative and clinical patient characteristics, including patient demographic, clinical status and care process factors were operationalized into 32 variables that were extracted from Sharp’s data warehouse (see  Table 1 ). The majority of variables were selected to be identifiable on or shortly after admission, although operationalization of some variables in this study was done with administrative rather than clinical data. Steroid use and ICU stay were operationalized for the entire admission because of clinician interest: while it is generally known fairly soon after admission whether a patient will be admitted to an ICU or if steroids will be administered, the study question from the clinician standpoint was not so much if steroids or 
ICU

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