Point-of-care Blood Glucose Values Research Articles

What Can We Learn From Point-of-Care Blood Glucose Values Deleted and Repeated by Nurses?

Hospitals rely on point-of-care (POC) blood glucose (BG) values to guide important decisions related to insulin administration and glycemic control. Evaluation of POC BG in hospitalized patients is associated with measurement and operator errors. Based on a previous quality improvement (QI) project we introduced an option for operators to delete and repeat POC BG values suspected as erroneous. The current project evaluated our experience with deleted POC BG values over a 2-year period. A retrospective QI project included all patients hospitalized at two regional academic medical centers in the Pacific Northwest during 2014 and 2015. Laboratory Medicine POC BG data were reviewed to evaluate all inpatient episodes of deleted and repeated POC BG. Inpatient operators choose to delete and repeat only 0.8% of all POC BG tests. Hypoglycemic and extreme hyperglycemic BG values are more likely to be deleted and repeated. Of initial values <40 mg/dL, 58% of deleted values (18% of all values) are errors. Of values >400 mg/dL, 40% of deleted values (5% of all values) are errors. Not all repeated POC BG values are first deleted. Optimal use of the option to delete and repeat POC BG values <40 mg/dL could decrease reported rates of severe hypoglycemia by as much as 40%. This project demonstrates that operators are frequently able to identify POC BG values that are measurement/operator errors. Eliminating these errors significantly reduces documented rates of severe hypoglycemia and hyperglycemia, and has the potential to improve patient safety.

Glycemic Control of Hospitalized Patients at a Medical Center in Taiwan

Achieving the glycemic target is essential to reduce morbidity and mortality in hospitalized patients; however, the status of glycemic control in Taiwan has not yet been evaluated. We conducted a retrospective study to evaluate the status of glycemic control in our hospital. We collected all the point-of-care blood glucose (POC-BG) data generated in general wards and intensive care units (ICUs) between April 2012 and June 2012. Parameters including mean of total POC-BG values, proportion of any POC-BG value less than 70 mg/dL, more than 250 mg/dL and 70 ~ 250 mg/dL, patient-day weighted mean glucose (PDWMG) value and percentage of PDW-MG value more than 180 mg/dL were compared between patients in medical and surgical wards, patients in medical and surgical ICUs, and among patients in each of the medical wards and surgical wards. The mean glucose and PDW-MG values were 192.4 mg/dL and 183.1 mg/dL in the general wards and 196.3 mg/dL and 187.7 mg/dL in the ICUs, respectively. The quality of inpatient glycemic control was poorer for patients in medical wards than in surgical wards, but the difference was smaller between patients in medical and surgical ICUs. The quality of glycemic control among patients in the different medical wards was inconsistent. In summary, the quality of inpatient glycemic control in our hospital was found to be suboptimal as compared with the current guidelines. The development of a strategy for improvement is critical, and the subsequent clinical effectiveness needs further investigation.

Retrospective Study of Glycemic Control Following Transition from the Intensive Care Unit in A National Sample of U.S. Hospitals

Retrospective study to evaluate glycemic control outcomes after transition from the intensive care unit (ICU) to a non-ICU area in a national sample of U.S. hospitals. Mean point-of-care blood glucose (POC-BG) data were assessed overall and at 24 hours before and up to 72 hours after the transition. Comparisons in glucose variability (standard deviation of POC-BG data) were assessed. Impact on glycemic control was evaluated after accounting for hospital characteristics through logistic regression analysis. POC-BG data were obtained from 576 hospitals. Overall mean (SD) POC-BG values in ICU versus non-ICU areas were 176 (24) versus 169 (21) mg/dL (P<.01). Mean (SD) of the ICU POC-BG data were 76 (16) versus 73 (16) mg/dL in the non-ICU data (P<.01). However, when comparing values of POC-BG in the last 24-hour ICU period with those from up to 72 hours posttransition, we found no differences, indicative of overall stable glycemic control and variability after transition. Any deterioration of glucose control following the transition was significantly associated with hospital size (P<.01): the smallest hospitals had the highest percentage of these cases. In addition, geographic region showed significant variability (P = .04), with hospitals in the Midwest and West having the highest proportion of cases in which glycemic control worsened following the transition. Glycemic control and variability did not change after transition from the ICU, but outcomes may depend on certain hospital characteristics. Inpatient glycemic control assessment should move beyond just cross-sectional studies and consider the impact of transitioning across inpatient areas. Other statistical approaches to studying this question should be evaluated.

Benchmarking Glycemic Control In U.S. Hospitals

Report data on glucose control from 635 U.S. hospitals. 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. 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). 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.

Statistical Transformation and the Interpretation of Inpatient Glucose Control Data

To introduce a statistical method of assessing hospital-based non-intensive care unit (non-ICU) inpatient glucose control. Point-of-care blood glucose (POC-BG) data from hospital non-ICUs were extracted for January 1 through December 31, 2011. Glucose data distribution was examined before and after Box-Cox transformations and compared to normality. Different subsets of data were used to establish upper and lower control limits, and exponentially weighted moving average (EWMA) control charts were constructed from June, July, and October data as examples to determine if out-of-control events were identified differently in nontransformed versus transformed data. A total of 36,381 POC-BG values were analyzed. In all 3 monthly test samples, glucose distributions in nontransformed data were skewed but approached a normal distribution once transformed. Interpretation of out-of-control events from EWMA control chart analyses also revealed differences. In the June test data, an out-of-control process was identified at sample 53 with nontransformed data, whereas the transformed data remained in control for the duration of the observed period. Analysis of July data demonstrated an out-of-control process sooner in the transformed (sample 55) than nontransformed (sample 111) data, whereas for October, transformed data remained in control longer than nontransformed data. Statistical transformations increase the normal behavior of inpatient non-ICU glycemic data sets. The decision to transform glucose data could influence the interpretation and conclusions about the status of inpatient glycemic control. Further study is required to determine whether transformed versus nontransformed data influence clinical decisions or evaluation of interventions.

Statistical transformation and the interpretation of inpatient glucose control data from the intensive care unit.

Glucose control can be problematic in critically ill patients. We evaluated the impact of statistical transformation on interpretation of intensive care unit inpatient glucose control data. Point-of-care blood glucose (POC-BG) data derived from patients in the intensive care unit for 2011 was obtained. Box-Cox transformation of POC-BG measurements was performed, and distribution of data was determined before and after transformation. Different data subsets were used to establish statistical upper and lower control limits. Exponentially weighted moving average (EWMA) control charts constructed from April, October, and November data determined whether out-of-control events could be identified differently in transformed versus nontransformed data. A total of 8679 POC-BG values were analyzed. POC-BG distributions in nontransformed data were skewed but approached normality after transformation. EWMA control charts revealed differences in projected detection of out-of-control events. In April, an out-of-control process resulting in the lower control limit being exceeded was identified at sample 116 in nontransformed data but not in transformed data. October transformed data detected an out-of-control process exceeding the upper control limit at sample 27 that was not detected in nontransformed data. Nontransformed November results remained in control, but transformation identified an out-of-control event less than 10 samples into the observation period. Using statistical methods to assess population-based glucose control in the intensive care unit could alter conclusions about the effectiveness of care processes for managing hyperglycemia. Further study is required to determine whether transformed versus nontransformed data change clinical decisions about the interpretation of care or intervention results.

Evaluation of Point-of-Care Blood Glucose Measurements in Patients with Diabetic Ketoacidosis or Hyperglycemic Hyperosmolar Syndrome Admitted to a Critical Care Unit

Point-of-care (POC) blood glucose (BG) measurement is currently not recommended in the treatment of patients presenting with diabetic ketoacidosis (DKA) or hyperglycemic hyperosmolar syndrome (HHS). We prospectively evaluated and compared capillary and venous POC BG values with laboratory venous glucose in patients with DKA or HHS admitted to one critical care unit over 8 months. Venous laboratory glucose was strongly correlated with venous (r = 0.98) and capillary (r = 0.96) POC glucose values, though POC glucose values were higher than venous laboratory values (venous POC 21 ± 3 mg/dl, capillary POC 30 ± 4 mg/dl; both p < .001). Increased plasma osmolality had no effect on glucose meter error, while acidemia (pH < 7.3) was associated with greater glucose meter error (p = .04) independent of glucose levels. Comparing hypothetical insulin infusion rates based on laboratory venous glucose to actual infusion rates based on POC glucose values showed that 33/61 insulin infusion rates would have been unchanged, while 28 out of 61 rates were on average 7% ± 2% higher. There were no instances of hypoglycemia in any of the patients. Overall, both venous and capillary POC BG values were safe for the purpose of titrating insulin infusions in patients with severe hyperglycemia. Acidemia, but not hyperosmolality, increased POC BG value errors.

Undetected hypoglycemia in a patient receiving TPN

Case reportA 58-year-old female was admitted to the hospital in a severely malnourished state. She was treated for Crohn's disease with total parental nutrition (TPN). The patient's blood glucose was monitored by point of care (POC) testing every 4h, and a specimen is also drawn daily for metabolic assessment. The POC blood glucose values were consistently much higher than the lab values. Humalog insulin (5U) was given to the patient to decrease high blood glucose levels that developed following administration of TPN. The patient then became hypoglycemic as a result of this insulin treatment. POC glucose testing, performed every 4h, did not detect the iatrogenic hypoglycemia, while lab glucose results were not given close attention. The lab sample was always drawn 1–2h after insulin was given to the patient and resulted in a lower blood glucose value. In addition, the symptoms of hypoglycemia such as shaking and dizziness were masked by the patient's poor health status, supine position, and the continuously given TPN. ConclusionsThese findings highlighted the importance of the correct sampling time following insulin administration and the consideration of the lab results in addition to POC. The patient's insulin regimen was modified to prevent further hypoglycemic events.

Intraoperative Accuracy of a Point-of-Care Glucose Meter Compared with Simultaneous Central Laboratory Measurements

Concerns have been raised about the use of point-of-care (POC) glucose meters in the hospital setting. Accuracy has been questioned especially in critically ill patients. Although commonly used in intensive care units and operating rooms, POC meters were not approved by the Food and Drug Administration for such use. Data on POC glucose meter performance during anesthesia are lacking. We evaluated accuracy of a POC meter in the intraoperative setting. We retrospectively reviewed 4,333 intraoperative records in which at least one intraoperative glucose was measured using electronic medical records at a large academic hospital. We evaluated the accuracy of a POC glucose meter (ACCU-CHEK® Inform, Roche Pharmaceuticals) based on the 176 simultaneous central laboratory (CL) blood glucose (BG) measurements that were found (i.e., documented collection times within 5 minutes). Point-of-care and central lab BG differences were analyzed by Bland-Altman and revised error grid analysis (rEGA). Mean POC BG was 163.4 ± 64.7 mg/dl [minimum (min) 48 mg/dl, maximum (max) 537 mg/dl] and mean CL BG was 162.6 ± 65.1 mg/dl (min 44 mg/dl, max 502 mg/dl). Mean absolute difference between POC and CL BG was 24.3 mg/dl. Mean absolute relative difference was 16.5% with standard deviation 26.4%. Point-of-care measurements showed a bias of 0.8 relative to the corresponding CL value, with a precision of 39.0 mg/dl. Forty (23%) POC BG values fell outside the Clinical and Laboratory Standards Institute guideline and 3.4% POC measurements fell in zones C and D of the rEGA plot. The tested POC glucose meter performed poorly compared to a CL analyzer intraoperatively. Perioperative clinicians should be aware of limitations of specific POC glucose meters, and routine use of POC glucose meters as sole measurement devices in the intraoperative period should be carefully considered.