Knowledge-based test result interpretation in laboratory medicine

1998 ◽  
Vol 278 (2) ◽  
pp. 229-242 ◽  
Author(s):  
Chr Trendelenburg ◽  
O Colhoun ◽  
A Wormek ◽  
K.L Massey
Keyword(s):  
Laboratory Medicine ◽  
Knowledge Based ◽  
Result Interpretation ◽  
Test Result

scholarly journals Phlebotomy and quality in the African laboratory

2014 ◽  
Vol 3 (1) ◽  
Author(s):  
Henry A. Mbah
Keyword(s):  
Quality Improvement ◽  
Critical Appraisal ◽  
Laboratory Medicine ◽  
Medical Procedures ◽  
Specimen Collection ◽  
Patient Preparation ◽  
Specimen Quality ◽  
Analytical Phase ◽  
And Storage ◽  
Test Result

Phlebotomy, the act of drawing blood through venepuncture, is one of the most common medical procedures in healthcare, as well as being a basis for diagnosis and treatment. A review of the available research has highlighted the dearth of information on the phlebotomy practice in Africa. Several studies elsewhere have shown that the pre-analytical phase (patient preparation, specimen collection and identification, transportation, preparation for analysis and storage) is the most error-prone process in laboratory medicine. The validity of any laboratory test result hinges on specimen quality; thus, as the push for laboratory quality improvement in Africa gathers momentum, the practice of phlebotomy should be subjected to critical appraisal. This article offers several suggestions for the improvement of phlebotomy in Africa.

What is the return on investment for laboratory medicine? The antidote to silo budgeting in diagnostics

2020 ◽  
Vol 26 (6) ◽  
pp. 1-8
Author(s):  
Christopher P Price ◽  
Patrick McGinley ◽  
Andrew St John
Keyword(s):  
Return On Investment ◽  
Care Pathway ◽  
Laboratory Medicine ◽  
Value Proposition ◽  
Clinical Process ◽  
A Value ◽  
Laboratory Services ◽  
The Cost ◽  
The Impact ◽  
Test Result

Procuring and managing diagnostic services, such as laboratory medicine, is generally based on cost and activity. Improving productivity of laboratory services therefore tends to focus on reducing the cost per test. However, this approach fails to recognise the impact of the test result on the other stakeholders involved in delivering care to the patient across the care pathway. Any assessment of the return on investment from a diagnostic service therefore needs to be undertaken together with a value proposition established for the service. This will enable the clinical, process and economic impact for all stakeholders to be assessed, which can then be used to develop an implementation plan that ensures the expectations of all stakeholders can be addressed.

Obtaining reference intervals traceable to reference measurement systems: is it possible, who is responsible, what is the strategy?

2012 ◽  
Vol 50 (5) ◽  
Author(s):  
Mauro Panteghini ◽  
Ferruccio Ceriotti
Keyword(s):  
Reference Values ◽  
Reference System ◽  
Laboratory Medicine ◽  
Reference Intervals ◽  
Multicenter Studies ◽  
Reference Measurement ◽  
Measurement Systems ◽  
Experimental Protocols ◽  
Definition Of ◽  
Result Interpretation

AbstractAn issue associated with standardization efforts is the need to develop useful reference intervals (RI). Lack of proper RI may hamper the implementation of standardization in Laboratory Medicine as standardization can modify analyte results and, without adequate RI, this can impair the result interpretation. Once defined, RI obtained with analytical procedures that produce results traceable to the corresponding reference system can be transferred among laboratories, providing that they use commercial assays that produce results traceable to the same reference system and populations have the same characteristics. Multicenter studies are needed for a robust definition of traceable RI, using experimental protocols that include well defined prerequisites. Particularly, employed methods must produce results that are traceable to the reference system for that specific analyte. Thus, the trueness of laboratories producing reference values should be verified and, if necessary, experimental results corrected in accordance with correlation results with the selected reference. If requirements in the adoption of traceable RI are fulfilled, the possibility of providing RI that are applicable to any laboratory, able to produce results traceable to the reference system, is realistic. The definition of traceable RI should hopefully cause the disappearance of different RI employed for the same analyte, providing more effective information to clinicians.

scholarly journals Using artificial intelligence to improve COVID-19 rapid diagnostic test result interpretation

2021 ◽  
Vol 118 (12) ◽  
pp. e2019893118
Author(s):  
David-A. Mendels ◽  
Laurent Dortet ◽  
Cécile Emeraud ◽  
Saoussen Oueslati ◽  
Delphine Girlich ◽  
...  
Keyword(s):  
Smartphone Application ◽  
Rapid Diagnostic Tests ◽  
Laboratory Staff ◽  
Test Models ◽  
Self Testing ◽  
Rapid Diagnostic Test Result ◽  
Result Interpretation ◽  
Accuracy Performance ◽  
Diagnostic Test Result ◽  
Test Result

Serological rapid diagnostic tests (RDTs) are widely used across pathologies, often providing users a simple, binary result (positive or negative) in as little as 5 to 20 min. Since the beginning of the COVID-19 pandemic, new RDTs for identifying SARS-CoV-2 have rapidly proliferated. However, these seemingly easy-to-read tests can be highly subjective, and interpretations of the visible “bands” of color that appear (or not) in a test window may vary between users, test models, and brands. We developed and evaluated the accuracy/performance of a smartphone application (xRCovid) that uses machine learning to classify SARS-CoV-2 serological RDT results and reduce reading ambiguities. Across 11 COVID-19 RDT models, the app yielded 99.3% precision compared to reading by eye. Using the app replaces the uncertainty from visual RDT interpretation with a smaller uncertainty of the image classifier, thereby increasing confidence of clinicians and laboratory staff when using RDTs, and creating opportunities for patient self-testing.

Errors in clinical laboratory test selection and result interpretation: commonly unrecognized mistakes as a cause of poor patient outcome

Diagnosis ◽  
2014 ◽  
Vol 1 (1) ◽  
pp. 85-87 ◽  
Author(s):  
Michael Laposata
Keyword(s):  
Laboratory Test ◽  
Clinical Laboratory ◽  
Diagnostic Errors ◽  
Laboratory Medicine ◽  
Test Selection ◽  
The Past ◽  
Poor Patient ◽  
Clinical Laboratory Test ◽  
Financial Consequences ◽  
Result Interpretation

AbstractOver the past decade, the test menu in the clinical laboratory has increased dramatically in size, cost, and complexity. Most practicing physicians would agree that it is a challenge to select the appropriate tests, and only the appropriate tests, with a clinical laboratory test menu of thousands of assays, many of which are genetic tests. This results in delayed diagnoses or incorrect diagnoses from errors in test selection and a failure to interpret tests correctly. Teams of diagnostic experts in a variety of specialty areas in laboratory medicine to aid treating physicians in test selection and result interpretation are being implemented to address this growing problem which frequently leads to significant diagnostic errors and the associated financial consequences.

scholarly journals Prospective observational study to evaluate the performance of the BioSure HIV Self-Test in the hands of lay users

2017 ◽  
Vol 94 (3) ◽  
pp. 169-173 ◽  
Author(s):  
John Saunders ◽  
Nataliya Brima ◽  
Marzena Orzol ◽  
Laura Phillips ◽  
Ana Milinkovic ◽  
...  
Keyword(s):  
Observational Study ◽  
Prospective Observational Study ◽  
Evaluation Study ◽  
Test Results ◽  
Valid Result ◽  
Sexual Health Service ◽  
Self Test ◽  
Test Outcomes ◽  
Result Interpretation ◽  
Test Result

ObjectivesIn order to assess whether the BioSure HIV Self-Test could be reliably performed by users at home and to determine whether they were able to perform and correctly interpret the test, we carried out an evaluation study among attendees at a sexual health service.MethodsA prospective observational study of clinic attendees to determine their ability to follow the instructions, complete the test on themselves and correctly interpret the results. The evaluation included interpretation of three dummy (contrived) devices, chosen at random from a sample of 12 devices, to ensure that a sufficient number of all possible test outcomes were included.ResultsTwo hundred participants were recruited. 97.0% (95% CI 93.5 to 98.9) conducted the test so as to achieve a valid result. 99.5% correctly identified the test result. Participants correctly interpreted the result of 94.0% (95% CI 91.4 to 95.9) of 586 contrived devices.ConclusionsThe majority of participants were able to follow the instructions and perform the test in order to get a valid result. Interpretation of the test results was good and the majority of participants were able to correctly read the result of their own and contrived tests. The availability of HIV self-tests will provide another option to increase access to testing particularly for those who may not wish or are unable to access clinical services.

scholarly journals Laboratory test result interpretation for primary care doctors in South Africa

2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Naadira Vanker ◽  
Norman H.B. Faull
Keyword(s):  
South Africa ◽  
Primary Care ◽  
Diagnostic Errors ◽  
Error Rates ◽  
Patient Specific ◽  
Test Results ◽  
Phone Line ◽  
Primary Care Doctors ◽  
Result Interpretation ◽  
Test Result

Background: Challenges and uncertainties with test result interpretation can lead to diagnostic errors. Primary care doctors are at a higher risk than specialists of making these errors, due to the range in complexity and severity of conditions that they encounter.Objectives: This study aimed to investigate the challenges that primary care doctors face with test result interpretation, and to identify potential countermeasures to address these.Methods: A survey was sent out to 7800 primary care doctors in South Africa. Questionnaire themes included doctors’ uncertainty with interpreting test results, mechanisms used to overcome this uncertainty, challenges with appropriate result interpretation, and perceived solutions for interpreting results.Results: Of the 552 responses received, the prevalence of challenges with result interpretation was estimated in an average of 17% of diagnostic encounters. The most commonly-reported challenges were not receiving test results in a timely manner (51% of respondents) and previous results not being easily available (37%). When faced with diagnostic uncertainty, 84% of respondents would either follow-up and reassess the patient or discuss the case with a specialist, and 67% would contact a laboratory professional. The most useful test utilisation enablers were found to be: interpretive comments (78% of respondents), published guidelines (74%), and a dedicated laboratory phone line (72%).Conclusion: Primary care doctors acknowledge uncertainty with test result interpretation. Potential countermeasures include the addition of patient-specific interpretive comments, the availability of guidelines or algorithms, and a dedicated laboratory phone line. The benefit of enhanced test result interpretation would reduce diagnostic error rates. 

Pro. M. D. - A Diagnostic Expert System Shell for Clinical Chemistry Test Result Interpretation

1988 ◽  
Vol 27 (03) ◽  
pp. 111-117 ◽  
Author(s):  
B. Pohl ◽  
Chr. Trendelenburg
Keyword(s):  
Expert System ◽  
Clinical Chemistry ◽  
Knowledge Bases ◽  
Function Evaluation ◽  
Illustrative Case ◽  
Expert System Shell ◽  
Different Types ◽  
Result Interpretation ◽  
Disorders Of Lipid Metabolism ◽  
Test Result

SummaryThe history and main features of the diagnostic expert system Pro. M. D. are presented. An illustrative case report from a knowledge base for the evaluation of disorders of lipid metabolism helps to explain Pro. M. D.’s functions. The knowledge representation syntax is explained for the different types of rules. Knowledge bases currently in development are outlined. A new concept of probability reasoning and other recent improvements are discussed briefly. Implementation details are described with special regard to the inference function. Evaluation problems are discussed and Pro. M. D. is compared to other known diagnostic computer systems.

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