OBJECTIVE: To apply the cumulative summation (CUSUM) technique for an evaluation of the learning process of sonographic fetal weight estimation at term in combination with the z-scores of biometry determinants and to assess the time of appearance and sources of errors. METHODS: Learning curve (LC-CUSUM) and double CUSUM charts for systematic error detection based on absolute and signed mean percentage error were generated to retrospectively estimate the longitudinal accuracy of sonographic fetal weight estimation conducted by three trainees and one experienced examiner. For LC-CUSUM analysis an examination was considered to be a failure when there was an absolute error in birth weight estimation >/= 15%. Fetal biometry measurements (head circumference, abdominal circumference (AC) and femur length (FL)) from 227 routine ultrasound scans of one examiner were separately transformed into z-scores and double CUSUM charts were generated to assess the systematic errors for each determinant. RESULTS: The LC-CUSUM charts revealed that different numbers of scans are required for different examiners to achieve competence in estimating birth weight. AC and FL deviated most significantly from expected values (P < 0.05). The double CUSUM charts revealed exact periods of systematic errors in the measurement of biometry determinants, clearly reflecting errors of fetal weight estimation. CONCLUSIONS: The use of CUSUM techniques in the analysis of sonographic data allows observation of the development of an examiner's skill and maintenance of competence. The CUSUM technique not only allows the reasons for impaired fetal weight estimation to be revealed but also allows determination of the exact time when inaccurate measurements start to occur. We suggest that CUSUM charts should be implemented in routine clinical practice as a measure of objective quality evaluation of sonographic fetal biometry. Copyright 2009 ISUOG. Published by John Wiley & Sons, Ltd.
OBJECTIVE: To apply the cumulative summation (CUSUM) technique for an evaluation of the learning process of sonographic fetal weight estimation at term in combination with the z-scores of biometry determinants and to assess the time of appearance and sources of errors. METHODS: Learning curve (LC-CUSUM) and double CUSUM charts for systematic error detection based on absolute and signed mean percentage error were generated to retrospectively estimate the longitudinal accuracy of sonographic fetal weight estimation conducted by three trainees and one experienced examiner. For LC-CUSUM analysis an examination was considered to be a failure when there was an absolute error in birth weight estimation >/= 15%. Fetal biometry measurements (head circumference, abdominal circumference (AC) and femur length (FL)) from 227 routine ultrasound scans of one examiner were separately transformed into z-scores and double CUSUM charts were generated to assess the systematic errors for each determinant. RESULTS: The LC-CUSUM charts revealed that different numbers of scans are required for different examiners to achieve competence in estimating birth weight. AC and FL deviated most significantly from expected values (P < 0.05). The double CUSUM charts revealed exact periods of systematic errors in the measurement of biometry determinants, clearly reflecting errors of fetal weight estimation. CONCLUSIONS: The use of CUSUM techniques in the analysis of sonographic data allows observation of the development of an examiner's skill and maintenance of competence. The CUSUM technique not only allows the reasons for impaired fetal weight estimation to be revealed but also allows determination of the exact time when inaccurate measurements start to occur. We suggest that CUSUM charts should be implemented in routine clinical practice as a measure of objective quality evaluation of sonographic fetal biometry. Copyright 2009 ISUOG. Published by John Wiley & Sons, Ltd.
Authors: Vejay N Vakharia; Roman Rodionov; Andrew W McEvoy; Anna Miserocchi; Rachel Sparks; Aidan G O'Keeffe; Sebastien Ourselin; John S Duncan Journal: J Neurosurg Date: 2018-02-16 Impact factor: 5.115