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Glucometrics: Assessing Quality in Inpatient Glycemic Management

This article discusses the concept of quality inpatient glucose management and explores different ways to measure it. It also highlights the importance of instituting a comprehensive program for glycemic management in hospitals. The article provides examples of glucometrics data and discusses special issues involved in measuring inpatient glycemic control. It concludes with a discussion on the various metrics used in the literature and presents the objectives and methods of a glucometrics project.

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Glucometrics: Assessing Quality in Inpatient Glycemic Management

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  1. “Glucometrics:” Assessing Quality in Inpatient Glycemic Management

  2. “Glucometrics”: Assessing Quality in Inpatient Glycemic Management Outline • What is ‘quality’ inpatient glucose management? • How should we measure it? • Future directions

  3. The 4 Spheres of a Quality Inpatient Glucose Management Program

  4. A Hospital Priority Why? • Enhance quality & patient safety • Competitive advantage • Cost savings • The Joint Commission

  5. Institution-Wide Educational Efforts

  6. Patient Care • Identification (& coding) of patients • Policies & procedures • Point-of-Care BG Testing • Institutional BG Targets (ICU, Wards) • Hypoglycemia protocol • ICU IV insulin protocols • Standardized SQ insulin order sets • Patient education tools • “Inpatient diabetes management team” • Transition to outpatient care (access)

  7. Example of a Glucometrics Report

  8. Graphic Display of Glucometrics Data MICU/CCU Avg BG Level By Year Diabetic All Patients 159.9 Non-Diabetic 160 158 152.3 150.3 149.6 150 141.8 141.6 141.2 144.9 140 133.9 133.6 130.8 130 120 2004 2005 2006 2007-Q1 Fiscal Year www.aace.com/resources/igcrc

  9. Graphic Display of Glucometrics Data Diabetic Patients Non-Diabetic Patients All Patients www.aace.com/resources/igcrc

  10. Patient 2 Patient 1 Patient 3 500 400 300 200 100 50 0 Patient 4 Patient 5 Blood Glucose (mg/dl) SUN MON TUE WED THU FRI SAT

  11. Measuring Inpatient Glycemic Control: Special Issues • Sample site (fingersticks, lab plasma glucose) • Multiple measures during hypoglycemic or hyperglycemic “events” • Varying time intervals of measurement • Timing in relationship to meals • Effects of IV fluids (dextrose) • How to collect glucose measurements? • How to analyze them? • How to present data to clinicians/adminstrators?

  12. The 4 Spheres of a Quality InpatientGlucose Management Program Metrics • Systematic review of hospital BG data • Analytical models • What’s the “HbA1c” for glucose controlduring a hospitalization?

  13. Metrics Traditionally Used in the Inpatient Glucose Literature • Raw blood glucose (BG) average • % of BGs within a pre-specified range (80-110, 100-150, <180, <200 mg/dl) • % of patients with a certain % of BGs within a pre-specified range • Hypoglycemia rates (<40, <50, <60, <70 mg/dl) • % of BGs • % of patients • Hyperglycemic excursions (>180, >200, >300 mg/dl) • % of BGs • % of patients Malmberg 1997; Queale 1999; Capes 2000, 2001; Bhattacharrya 2002; van den Berghe 2001, 2006; Funary 2003; Krinsley 2003; Goldberg 2004, 2005; Baldwin 2005; McCallister 2005; Kosiborod 2006

  14. Glucometrics Project: Objectives • Define inpatient glucose quality metrics • Define ‘units of analysis’ • Compare metric results for the differentanalytical units Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  15. Methods: Sample • Yale-New Haven Hospital BG data • BG data downloaded into relational database for analysis • BG values • Date / Time • Patient ID • Hospital ward • Sample: One general medical ward’s March 2004 BG results (n=1,552) Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  16. Methods: Metrics Tested • Mean / Median BG • % BG in “favorable” range (80 - 139 mg/dl) • % Hyperglycemia (>300 mg/dl) • % Hypoglycemia (<60 mg/dl) Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  17. “Ward” n = 1,552 “Patient Stay” n = 118 [13.2 BGs / stay] “Patient Day” n = 467 [3.3 BGs / day] Methods: Units of Analysis Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  18. Patient 2 Patient 1 Patient 3 500 400 300 200 100 50 0 Patient 4 Patient 5 Blood Glucose (mg/dl) SUN MON TUE WED THU FRI SAT

  19. Patient 2 Patient 1 Patient 3 500 400 300 200 100 50 0 Patient 4 Patient 5 “ward” model Blood Glucose (mg/dl) X SUN MON TUE WED THU FRI SAT

  20. Patient 4 Patient 2 Patient 1 Patient 3 500 400 300 200 100 50 0 Blood Glucose (mg/dl) SUN MON TUE WED THU FRI SAT

  21. Patient 2 Patient 1 Patient 3 500 400 300 200 100 50 0 Patient 4 Patient 5 “patient stay model” Blood Glucose (mg/dl) SUN MON TUE WED THU FRI SAT

  22. Patient 2 Patient 1 Patient 3 500 400 300 200 100 50 0 Patient 4 Patient 5 Blood Glucose (mg/dl) SUN MON TUE WED THU FRI SAT

  23. Patient 2 Patient 1 Patient 3 500 400 300 200 100 50 0 Patient 4 Patient 5 “patient day model” Blood Glucose (mg/dl) SUN MON TUE WED THU FRI SAT

  24. Mean / Median BG Mean/median of each pt’s mean BG during each day Mean/median of each pt’s mean BG during hosp’n Mean/median of all BGs on that ward Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  25. % BGs Within Range (80-139 mg/dl) % of the mean BGs for each patient’s hosp’n that are within target range % of the mean BGs for each patient’s hosp. day that are within target range % of all BGs on ward that are within target range Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  26. % Hyperglycemic Events (>300 mg/dl) % of the patient hospitalizations where any BG was severely hyper % of the patient hosp. days where any BG was severely hyper % of all BGs on ward that are severely hyper C Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  27. % Hypoglycemic Events (<60 mg/dl) % of the patient hospitalizations where any BG was hypo % of the patient hosp. days where any BG was hypo % of all BGs on ward that are hypo Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  28. Summary of Results • Metrics for mean BG, median BG & the % “in target range” are similar for all three analytical models. • There were substantial differences between the models for % hyperglycemia and % hypoglycemia. • ‘WARD’ model has lowest % • ‘PATIENT STAY’ model has highest % • ‘PATIENT DAY’ model is intermediate Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  29. Other Findings • Addition of venous plasma lab glucose measurements to fingerstick data • Slight reduction in mean glucose values, but not clinically meaningful • Deletion of 1st hospital day of blood glucose • Slight reduction in mean glucose values, but not clinically meaningful • Applying glucometrics to the ICU (‘gold standard’ with IV insulin infusion) - the realistic maximum % of patient days within target range is probably~ 80%

  30. Conclusions • Glucometrics are useful intermediate outcomes measures of inpatient hyperglycemia management. • Perception of performance & quality may depend upon the unit of analysis • All 3 Units of Analysis provide useful information • ‘WARD’ model is the simplest; may be most useful in operational analyses. • ‘PATIENT STAY’ model perhaps most useful to consumers (& risk management). • ‘PATIENT DAY’ model may be the most actionable by providers. Goldberg PA et al. Diabetes Technology & Therapeutics 2006

  31. Inpatient Diabetes Management Team:Impact on Glucometrics (Before vs. After) Bozzo J et al. 67th Scientific Sessions, American Diabetes Association, Chicago, IL, 2007 (576-P)

  32. Inpatient Diabetes Management Team:Impact on Glucometrics (vs. Matched Controls) * McNemar’s Test Bozzo J et al. 67th Scientific Sessions, American Diabetes Association, Chicago, IL, 2007 (576-P)

  33. Other Proposed Metrics

  34. “Time Average Glucose (TAG)”

  35. Persistent Hyperglycemia: An IndependentPredictor of AMI Outcomes van der Horst et al. Cardiovascular Diabetology 2007. 30-day major adverse cardiac events (MACE) according to quartiles of admission glucose and persistent hyperglycemia in MI patients. P value for trend in admission glucose is 0.023 and for persistent hyperglycemia is <0.0001.

  36. ‘Hyperglycemic Index’ As a Tool to Assess Glucose Control: A Retrospective Study • 10 yr analysis in a 12-bed surgical ICU • 1779 patients (LOS >4 days) • 65,528 glucose values Mathijs Vogelzang, Iwan CC van der Host, Maarten WN Nijsten. Critical Care 2004; 8(3):R122-127

  37. HGI: 0.73 Glucose (mmol/L) Time (hours) The “Hyperglycemic Index” (HGI) • Calculation of the hyperglycemic index (HGI). All measured glucose values (black dots) and their corresponding sampling times are taken into account. The average over time is calculated for the area (shaded) under the glucose curve for hyperglycemic values only. The normal glucose range is indicated by the hatched area, with 6.0 mmol/L (dotted line) as the cutoff. HGI is the shaded area divided by the total length of stay. In this case, HGI is 0.73 mmol/L, as indicated by the dashed line. Note that normal or hypoglycemic measurements do not affect HGI, and thus, they do not falsely lower this index. Vogelzang et al. Critical Care 2004

  38. Receiver Operator Characteristic (ROC) Curvesfor Different Glucose Measures ROC HGI 0.64 Mean BG 0.62 Mean AM BG 0.61 Vogelzang et al. Critical Care 2004

  39. http://glucometrics.med.yale.edu

  40. All Glucose Samples Patient-stay Means Patient-day Means Glucose (mg/dL) Glucose (mg/dL) Glucose (mg/dL) Glucometrics • Institution: Second Hospital Ward: Medical ICU Type: Adult Internal Medicine ICU1/3/2005 – 2/1/2005 • A patient’s glycemic control can be analyzed at three time resolutions. Individual glucoses measure control at the shortest interval, the time between samples. Mean glucose measures control for the longest interval, the entire hospital stay. A day’s mean glucose measures control for an intermediate interval, one day. Only this method has a fixed interval which allows better comparison of one patient to another. The figures below show frequency distributions; the dark bar on the x-axis between 70 and 149 shows a target or goal glucose range. Percentiles of the data are shown by the lines and dot over the histogram: 5–––25 •50 75–––95 * For patient-stays and patient-days, summary statistics are computed on the mean glucose of these intervals. For example, in calculating the medians, the median {of individual patient-samples}, the median {of patient-stay means}, and the median {of patient-day means} are taken. Mean, median, percentile, and spread are stated as mg/dL. Courtesy of Dr. Prem Thomas, Yale Center for Medical Informatics. http://glucometrics.med.yale.edu

  41. “Glucometrics”: Assessing Quality in Inpatient Glycemic Management SUMMARY • “Quality” in inpatient glucose management needs to be better defined. • Achieving it requires efforts in 4 spheres: prioritization; education; patient care; and metrics. • Measures of inpatient glucose management are dependent on the analytical methods employed. • It is important for the diabetes community, hospitals, clinical investigators & the QI experts work together to better define & validate standardized “glucometrics” which are meaningful, fair, and actionable.

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