PMID- 9291452
OWN - NLM
STAT- MEDLINE
DCOM- 19971001
LR  - 20190512
IS  - 0002-9173 (Print)
IS  - 0002-9173 (Linking)
VI  - 108
IP  - 3
DP  - 1997 Sep
TI  - Optimal procedures for detecting analytic bias using patient samples.
PG  - 254-68
AB  - We recently described the performance characteristics of the exponentially 
      adjusted moving mean (EAMM), a patient-data, moving block mean procedure, which 
      is a generalized algorithm that unifies Bull's algorithm and the classic average 
      of normals (AON) procedure. Herein we describe the trend EAMM (TEAMM), a 
      continuous signal analog of the EAMM procedure related to classic trend analysis. 
      Using computer simulation, we have compared EAMM and TEAMM over a range of biases 
      for various sample sizes (N or equivalent smoothing factor alpha) and exponential 
      parameters (P) under conditions of equivalent false rejection (fixed on a per 
      patient sample basis). We found optimal pairs of N and P for each level of bias 
      by determination of minimum mean patient samples to rejection. Overall optimal 
      algorithms were determined through calculation of undetected lost medical utility 
      (ULMU), a novel function that quantifies the medical damage due to analytic bias. 
      The ULMU function was calculated based on lost test specificity in a normal 
      population. We found that optimized TEAMM was superior to optimized EAMM for all 
      levels of analytic bias. If these observations hold true for non-Gaussian 
      populations, TEAMM procedures are the method of choice for detecting bias using 
      patient samples or as an event gauge to trigger use of known-value control 
      materials.
FAU - Smith, F A
AU  - Smith FA
AD  - Department of Pathology, Northwestern University Medical School, Chicago, 
      Illinois, USA.
FAU - Kroft, S H
AU  - Kroft SH
LA  - eng
PT  - Comparative Study
PT  - Journal Article
PL  - England
TA  - Am J Clin Pathol
JT  - American journal of clinical pathology
JID - 0370470
SB  - IM
MH  - *Algorithms
MH  - Clinical Laboratory Information Systems
MH  - *Computer Simulation
MH  - Humans
MH  - Laboratories, Hospital/organization & administration/*standards
MH  - *Models, Statistical
MH  - Pathology, Clinical/organization & administration/*standards
MH  - Quality Control
MH  - Reproducibility of Results
MH  - *Selection Bias
EDAT- 1997/09/18 00:00
MHDA- 1997/09/18 00:01
CRDT- 1997/09/18 00:00
PHST- 1997/09/18 00:00 [pubmed]
PHST- 1997/09/18 00:01 [medline]
PHST- 1997/09/18 00:00 [entrez]
AID - 10.1093/ajcp/108.3.254 [doi]
PST - ppublish
SO  - Am J Clin Pathol. 1997 Sep;108(3):254-68. doi: 10.1093/ajcp/108.3.254.