Preanalytical phase for transfusion medicine and blood bank laboratory – tasks to complete

2021 ◽  
Vol 3 (1) ◽  
pp. 063-069
Author(s):  
Ramune Sepetiene ◽  
Vaiva Patamsyte ◽  
Ninette F Robbins ◽  
Mohamed Ali ◽  
Alexander Carterson
Keyword(s):  
Literature Review ◽  
Information Technologies ◽  
Blood Bank ◽  
Medical Laboratory ◽  
Laboratory Diagnostics ◽  
Transfusion Medicine ◽  
Human Errors ◽  
Preanalytical Phase ◽  
Regulatory Guidelines ◽  
Routine Procedures

Background: This review describes and evaluates the most relevant preanalytical errors and their impact on subsequent laboratory diagnostics. Quality management for laboratory processes remains extremely important, despite current advancements in information technologies and fully automated routine procedures. Methods: This review is focused on specific preanalytical requirements for the blood bank and transfusion laboratory. Conclusions are done based on literature review. Results: Human errors, or lack of procedures, continue to be the cause of many errors within laboratory processes. The medical laboratory needs an impetus and stipulation to improve processes, to help eliminate errors, and meet regulatory guidelines. Conclusions: General preanalytical rules exist for clinical and research laboratories but differences in laboratory specialty and provided services influence compliance

Organization of the work of the medical laboratory service in accordance with the requirements of the standard GOST ISO 15189–2015 «Medical laboratories. Particular requirements for quality and competence»

2020 ◽  
pp. 15-22
Author(s):  
Elena Vitalievna Perminova
Keyword(s):  
Clinical Laboratory ◽  
Medical Laboratory ◽  
Laboratory Research ◽  
Laboratory Diagnostics ◽  
Clinical Diagnostic Laboratory ◽  
Diagnostic Laboratory ◽  
Iso 15189 ◽  
Laboratory Service ◽  
Medical Laboratories

Clinical laboratory diagnostics is a medical specialty, which is based on in vitro diagnostic studies of biomaterial obtained from an individual. At the present stage, there are three main types of organization of the laboratory research process — a laboratory service as part of a medical and preventive institution, a centralized laboratory where biomaterials are delivered for research from various healthcare institutions, as well as mobile laboratories that allow conducting the research directly at the patient’s bedside. This discipline involves the use of a wide variety of diagnostic research methods and the use of a huge number of specific techniques. Their list should include carrying out hematological, microbiological, virological, immunological, serological, parasitic, and biochemical studies. Also, when organizing laboratory diagnostic activities, a number of other studies (cytological, histological, toxicological, genetic, molecular biological, etc.) are provided. A laboratory report is formulated after obtaining clinical data and comparing them with the obtained test results. The quality of laboratory tests is ensured through the systematic implementation of internal laboratory control, as well as participation in a national program for external quality assessment. The activities of the clinical diagnostic laboratory should be organized in accordance with the requirements of the standard GOST R ISO 15189–2015 «Medical laboratories. Particular requirements for quality and competence», which is based on the provisions of two more fundamental standards — ISO 9001 and ISO 17025, and adds a number of special requirements related to medical laboratories.

scholarly journals Diagnostic Challenges in Newborns and Infants with Coagulation Disorders

2020 ◽  
Vol 40 (01) ◽  
pp. 084-087
Author(s):  
Wolfgang Eberl
Keyword(s):  
Children And Adolescents ◽  
Small Sample ◽  
Laboratory Diagnostics ◽  
Coagulation Disorders ◽  
Small Children ◽  
Preanalytical Phase ◽  
Coagulation Tests ◽  
Strategy Performance ◽  
Performance And Evaluation ◽  
The Individual

AbstractLaboratory diagnostics in children and adolescents, especially in newborns and very small children, differ considerably compared with laboratory diagnostics in adults. This applies to all individual steps of the examination (i.e., the indication, the preanalytical phase, the analysis itself, and interpretation of the findings). This is particularly true in the diagnostics of hemostasis, in which small sample volumes and relatively error prone coagulation tests are posing particular challenges to the strategy, performance, and evaluation of the tests. Differences in the individual steps are illustrated below.

The Impact of Information Technology in Healthcare Privacy

2011 ◽  
pp. 186-227
Author(s):  
Maria Yin Ling Fung ◽  
John Paynter
Keyword(s):  
New Zealand ◽  
Web Sites ◽  
Information Technologies ◽  
Social Engineering ◽  
The Internet ◽  
Communication Services ◽  
Human Errors ◽  
Privacy Concerns ◽  
Use Of The Internet ◽  
Reducing Costs

The increased use of the Internet and latest information technologies such as wireless computing is revolutionizing the healthcare industry by improving services and reducing costs. The advances in technology help to empower individuals to understand and take charge of their healthcare needs. Patients can participate in healthcare processes, such as diagnosis and treatment, through secure electronic communication services. Patients can search healthcare information over the Internet and interact with physicians. The same advances in technology have also heightened privacy awareness. Privacy concerns include healthcare Web sites that do not practice the privacy policies they preach, computer break-ins, insider and hacker attacks, temporary and careless employees, virus attacks, human errors, system design faults, and social engineering. This chapter looks at medical privacy issues and how they are handled in the U.S. and New Zealand. A sample of 20 New Zealand health Web sites was investigated.

The Impact of Information Technology in Healthcare Privacy

2011 ◽  
pp. 1071-1101 ◽  
Author(s):  
Maria Yin Ling Fung
Keyword(s):  
New Zealand ◽  
Web Sites ◽  
Information Technologies ◽  
Social Engineering ◽  
The Internet ◽  
Communication Services ◽  
Human Errors ◽  
Privacy Concerns ◽  
Use Of The Internet ◽  
Reducing Costs

The increased use of the Internet and latest information technologies such as wireless computing is revolutionizing the healthcare industry by improving services and reducing costs. The advances in technology help to empower individuals to understand and take charge of their healthcare needs. Patients can participate in healthcare processes, such as diagnosis and treatment, through secure electronic communication services. Patients can search healthcare information over the Internet and interact with physicians. The same advances in technology have also heightened privacy awareness. Privacy concerns include healthcare Web sites that do not practice the privacy policies they preach, computer break-ins, insider and hacker attacks, temporary and careless employees, virus attacks, human errors, system design faults, and social engineering. This chapter looks at medical privacy issues and how they are handled in the U.S. and New Zealand. A sample of 20 New Zealand health Web sites was investigated.

Anti-D from alloimmunization versus RhIG: detective work in the blood bank and transfusion medicine services

Transfusion ◽  
2018 ◽  
Vol 58 (11) ◽  
pp. 2490-2494
Author(s):  
Debra Berry ◽  
Margaret DiGuardo ◽  
Yunchuan Delores Mo ◽  
Gay Wehrli
Keyword(s):  
Blood Bank ◽  
Transfusion Medicine

scholarly journals A Domain-Oriented Analysis of the Impact of Machine Learning—The Case of Retailing

2019 ◽  
Vol 3 (1) ◽  
pp. 11 ◽  
Author(s):  
Felix Weber ◽  
Reinhard Schütte
Keyword(s):  
Machine Learning ◽  
Literature Review ◽  
Empirical Study ◽  
Information Technologies ◽  
Machine Learning Techniques ◽  
Specific Domain ◽  
Learning Improvement ◽  
Artifical Intelligence ◽  
Current Prevalence ◽  
The Impact

Information technologies in general and artifical intelligence (AI) in particular try to shift operational task away from a human actor. Machine learning (ML) is a discipline within AI that deals with learning improvement based on data. Subsequently, retailing and wholesaling, which are known for their high proportion of human work and at the same time low profit margins, can be regarded as a natural fit for the application of AI and ML tools. This article examines the current prevalence of the use of machine learning in the industry. The paper uses two disparate approaches to identify the scientific and practical state-of-the-art within the domain: a literature review on the major scientific databases and an empirical study of the 10 largest international retail companies and their adoption of ML technologies in the domain are combined with each other. This text does not present a prototype using machine learning techniques. Instead of a consideration and comparison of the particular algorythms and approaches, the underling problems and operational tasks that are elementary for the specific domain are identified. Based on a comprehensive literature review the main problem types that ML can serve, and the associated ML techniques, are evaluated. An empirical study of the 10 largest retail companies and their ML adoption shows that the practical market adoption is highly variable. The pioneers have extensively integrated applications into everyday business, while others only show a small set of early prototypes. However, some others show neither active use nor efforts to apply such a technology. Following this, a structured approach is taken to analyze the value-adding core processes of retail companies. The current scientific and practical application scenarios and possibilities are illustrated in detail. In summary, there are numerous possible applications in all areas. In particular, in areas where future forecasts and predictions are needed (like marketing or replenishment), the use of ML today is both scientifically and practically highly developed.

Skill differences in medical laboratory diagnostics

1995 ◽  
Vol 9 (3) ◽  
pp. 235-247
Author(s):  
Stephanie M. Clancy Dollinger ◽  
William J. Hoyer
Keyword(s):  
Medical Laboratory ◽  
Laboratory Diagnostics
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