NDLI: Bernoulli Cumulative Sum (CUSUM) control charts for monitoring of anesthesiologists' performance in supervising anesthesia residents and nurse anesthetists.

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Bernoulli Cumulative Sum (CUSUM) control charts for monitoring of anesthesiologists' performance in supervising anesthesia residents and nurse anesthetists.

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Bernoulli Cumulative Sum (CUSUM) control charts for monitoring of anesthesiologists' performance in supervising anesthesia residents and nurse anesthetists.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Dexter, Franklin Ledolter, Johannes Hindman, Bradley J.
Description	Author Affiliation: Dexter F ( From the *Division of Management Consulting, Department of Anesthesia, Department of Management Sciences, and Department of Anesthesia, University of Iowa, Iowa City, Iowa.)
Abstract	We describe our experiences in using Bernoulli cumulative sum (CUSUM) control charts for monitoring clinician performance. The supervision provided by each anesthesiologist is evaluated daily by the Certified Registered Nurse Anesthetists (CRNAs) and/or anesthesia residents with whom they work. Each of 9 items is evaluated (1 = never, 2 = rarely, 3 = frequently, 4 = always). The score is the mean of the 9 responses. Choosing thresholds for low scores is straightforward, <2.0 for CRNAs and <3.0 for residents. Bernoulli CUSUM detection of low scores was within 50 ± 14 (median ± quartile deviation) days rather than 182 days without use of CUSUM. The true positive detection of anesthesiologists with incidences of low scores greater than the chosen 'out-of-control' rate was 14 of 14. The false-positive detection rate was 0 of 29. This CUSUM performance exceeded that of Shewhart individual control charts, for which the smallest threshold sufficiently large to detect 14 of 14 true positives had false-positive detection of 16 of 29 anesthesiologists. The Bernoulli CUSUM assumes that scores are known right away, which is untrue. However, CUSUM performance was insensitive to this assumption. The Bernoulli CUSUM assumes statistical independence of scores, which also is untrue. For example, when an evaluation of an anesthesiologist 1 day by a CRNA had a low score, there was an increased chance that another CRNA working in a different operating room on the same day would also give that same anesthesiologist a low score (P < 0.0001). This correlation among scores does affect the Bernoulli CUSUM, such that detection is more likely. This is an advantage for our continual process improvement application since it flags individuals for further evaluation by managers while maintaining confidentiality of raters.
File Format	HTM / HTML
ISSN	00032999
Issue Number	3
Volume Number	119
e-ISSN	15267598
Journal	Anesthesia & Analgesia
Language	English
Publisher	Lippincott Williams & Wilkins
Publisher Date	2014-09-01
Publisher Place	United States
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discipline Anesthesiology Algorithms Anesthesiology Education Standards Internship And Residency Nurse Anesthetists Organization And Administration Confidentiality Data Interpretation, Statistical Documentation Employee Performance Appraisal False Positive Reactions Humans Operating Rooms Physicians Reproducibility Of Results Journal Article Research Support, Non-u.s. Gov't
Content Type	Text
Resource Type	Article
Subject	Anesthesiology and Pain Medicine

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