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

George E. Saulnier, Janna C. Castro, Curtiss B. Cook

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)560-567
Number of pages8
JournalJournal of diabetes science and technology
Volume8
Issue number3
DOIs
StatePublished - 2014

Fingerprint

Point-of-Care Systems
Intensive care units
Intensive Care Units
Glucose
Blood Glucose
Inpatients
Blood
Critical Illness
Hyperglycemia
Observation
Population

Keywords

  • Diabetes
  • Hospital
  • Hyperglycemia
  • Inpatient
  • Statistical process control

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Internal Medicine
  • Bioengineering
  • Biomedical Engineering

Cite this

Statistical transformation and the interpretation of inpatient glucose control data from the intensive care unit. / Saulnier, George E.; Castro, Janna C.; Cook, Curtiss B.

In: Journal of diabetes science and technology, Vol. 8, No. 3, 2014, p. 560-567.

Research output: Contribution to journalArticle

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