Literature DB >> 23505267

Historical data decrease complete blood count reflex blood smear review rates without missing patients with acute leukaemia.

Esther Rabizadeh1, Itay Pickholtz, Mira Barak, Paul Froom.   

Abstract

INTRODUCTION: The availability of historical data decreases the rate of blood smear review rates in outpatients, but we are unaware of studies done at referral centres. In the following study, we determined the effect of historical data on the rates of peripheral blood smears over a 3-month period and then the detection rate of patients with acute leukaemia.
METHODS: All results of complete blood counts (CBCs) tested on three ADVIA 120 analyzers at the regional Rabin Medical Centre, Beilinson Campus over a 3-month period were accessed on a computerised laboratory information system. Over a 3-month period, we determined the proportion of total CBC and patients with criteria for a manual differential count and the actual number of peripheral blood smears done. Finally, we determined the proportion of 100 consecutive patients with acute leukaemia detected using our criteria that included limiting reflex testing according to historical data.
RESULTS: Over the 3-month period, there were 34,827 tests done in 12,785 patients. Without historical data, our smear rate would have been 24.5%, but with the availability of historical data, the blood smear review rate was 5.6%. The detection rate for cases of acute leukaemia was 100%.
CONCLUSIONS: We conclude that the availability of previous test results significantly reduces the need for blood smear review without missing any patients with acute leukaemia.

Entities:  

Keywords:  COMPUTER SYSTEMS; HAEMATOLOGY; LEUKAEMIA

Mesh:

Year:  2013        PMID: 23505267     DOI: 10.1136/jclinpath-2012-201423

Source DB:  PubMed          Journal:  J Clin Pathol        ISSN: 0021-9746            Impact factor:   3.411


  2 in total

1.  Rate of manual leukocyte differentials in dog, cat and horse blood samples using ADVIA 120 cytograms.

Authors:  Martina Stirn; Andreas Moritz; Natali Bauer
Journal:  BMC Vet Res       Date:  2014-06-05       Impact factor: 2.741

2.  Use of Middleware Data to Dissect and Optimize Hematology Autoverification.

Authors:  Rachel D Starks; Anna E Merrill; Scott R Davis; Dena R Voss; Pamela J Goldsmith; Bonnie S Brown; Jeff Kulhavy; Matthew D Krasowski
Journal:  J Pathol Inform       Date:  2021-04-07
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.