Evaluation of Techniques for the Presentation of Laboratory Data. II: Accuracy of Interpretation

1997 ◽  
Vol 36 (01) ◽  
pp. 17-19 ◽  
Author(s):  
J. O. O. Hoeke ◽  
B. Bonke ◽  
R. van Strik ◽  
E. S. Gelsema ◽  
R. Verheij
Keyword(s):  
Reaction Time ◽  
Laboratory Test ◽  
Clinical Experience ◽  
Laboratory Tests ◽  
Laboratory Data ◽  
Reaction Time Experiment ◽  
Test Results ◽  
Laboratory Test Results

Abstract:Four tabular and two graphical techniques for the presentation of laboratory test results were evaluated in a reaction time experiment with 25 volunteers. Artificial variables and values were used to represent sets of 12 laboratory tests to eliminate the possible effects of clinical experience. Analyses focused on four types of errors in interpretation. Color-coded tables and one of the color-coded graphs greatly (2.8 times or better) reduced the number of incorrectly classified test results, as compared to the reference presentation technique. This was mainly due to a reduction of the number of abnormal test results that were not noticed by the subjects when using these presentation techniques.

Evaluation of Techniques for the Presentation of Laboratory Data: Support of Pattern Recognition

2000 ◽  
Vol 39 (01) ◽  
pp. 88-92 ◽  
Author(s):  
J. O. O. Hoeke ◽  
B. Bonke ◽  
R. van Strik ◽  
E. S. Gelsema
Keyword(s):  
Pattern Recognition ◽  
Reaction Time ◽  
Response Times ◽  
Laboratory Data ◽  
The Other ◽  
Experimental Setup ◽  
Reaction Time Experiment ◽  
Test Results ◽  
Median Response ◽  
Laboratory Test Results

Abstract:Two tabular and two graphical techniques for the presentation of laboratory test results were compared in a reaction-time experiment with 22 volunteers. The experimental setup was designed to determine whether one or more of the presentation techniques facilitated the recognition of four predefined combinations of abnormal test results. Using a conventional, tabular presentation technique as a reference, faster median response times were obtained with each of the other three presentation techniques, irrespective of pattern. The effect on accuracy was less clear, possibly due to the small number of errors made.

Evaluation of Techniques for the Presentation of Laboratory Data. I: Time Needed for Interpretation

1997 ◽  
Vol 36 (01) ◽  
pp. 11-16 ◽  
Author(s):  
J. O. O. Hoeke ◽  
B. Bonke ◽  
R. van Strik ◽  
E. S. Gelsema ◽  
R. Verheij
Keyword(s):  
Reaction Time ◽  
Laboratory Tests ◽  
Laboratory Data ◽  
Reaction Times ◽  
Data Sets ◽  
Comparable Data ◽  
Test Results ◽  
Median Reaction Time ◽  
Improvement Rate ◽  
Laboratory Test Results

Abstract:Four tabular and two graphical techniques for the presentation of laboratory test results were evaluated in a reaction-time experiment with 25 volunteers. Artificial variables and values were used to represent sets of 12 laboratory tests to eliminate the possible effects of clinical experience. Analyses focused on reaction times for correctly classified sets of data. For comparable data sets, Presentation Techniques (PT) that use color, always allow faster interpretation than PTs that do not use color, or use only a simple marker. Color-coded tables yielded an improvement in median reaction time of approximately six times or better, as compared to the reference PT (a tabular PT without any hints). For the color-coded graphs, the improvement rate was approximately 2.5 or better.

scholarly journals Coding of Electronic Laboratory Reports for Biosurveillance, Selected United States Hospitals, 2011

2015 ◽  
Vol 7 (2) ◽  
Author(s):  
Sanjaya Dhakal ◽  
Sherry L. Burrer ◽  
Carla A. Winston ◽  
Achintya Dey ◽  
Umed Ajani ◽  
...  
Keyword(s):  
Public Health ◽  
Laboratory Test ◽  
No Value ◽  
Laboratory Data ◽  
Test Results ◽  
Snomed Ct ◽  
Syndromic Surveillance System ◽  
Coding Systems ◽  
Surveillance And Response ◽  
Laboratory Test Results

ObjectiveElectronic laboratory reporting has been promoted as a public health priority. The Office of the U.S. National Coordinator for Health Information Technology has endorsed two coding systems: Logical Observation Identifiers Names and Codes (LOINC) for laboratory test orders and Systemized Nomenclature of Medicine-Clinical Terms (SNOMED CT) for test results.  Materials and MethodsWe examined LOINC and SNOMED CT code use in electronic laboratory data reported in 2011 by 63 non-federal hospitals to BioSense electronic syndromic surveillance system.  We analyzed the frequencies, characteristics, and code concepts of test orders and results.ResultsA total of 14,028,774 laboratory test orders or results were reported. No test orders used SNOMED CT codes. To describe test orders, 77% used a LOINC code, 17% had no value, and 6% had a non-informative value, “OTH”. Thirty-three percent (33%) of test results had missing or non-informative codes. For test results with at least one informative value, 91.8% had only LOINC codes, 0.7% had only SNOMED codes, and 7.4% had both. Of 108 SNOMED CT codes reported without LOINC codes, 45% could be matched to at least one LOINC code.ConclusionMissing or non-informative codes comprised almost a quarter of laboratory test orders and a third of test results reported to BioSense by non-federal hospitals. Use of LOINC codes for laboratory test results was more common than use of SNOMED CT. Complete and standardized coding could improve the usefulness of laboratory data for public health surveillance and response.

Reduction of Laboratory Utilization in the Intensive Care Unit

2016 ◽  
Vol 32 (8) ◽  
pp. 500-507 ◽  
Author(s):  
Samih Raad ◽  
Rachel Elliott ◽  
Evan Dickerson ◽  
Babar Khan ◽  
Khalil Diab
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Laboratory Test ◽  
Laboratory Tests ◽  
Routine Laboratory ◽  
Test Results ◽  
Staff Education ◽  
Arterial Blood ◽  
Laboratory Test Results ◽  
Order Sets

Objective: In our academic intensive care unit (ICU), there is excess ordering of routine laboratory tests. This is partially due to a lack of transparency of laboratory-processing costs and to the admission order plans that favor daily laboratory test orders. We hypothesized that a program that involves physician and staff education and alters the current ICU order sets will lead to a sustained decrease in routine laboratory test ordering. Design: Prospective cohort study. Setting: Academic closed medical ICU (MICU). Patients: All patients admitted to the MICU. Methods: We consistently educated residents, faculty, and staff about laboratory test costs. We removed the daily laboratory test option from the admission order sets and asked residents to order needed laboratory test results every day. We only allowed the G3+I-STAT (arterial blood gas only) cartridges in the MICU in hopes of decreasing duplicative laboratory test results. We added laboratory review to the daily rounding checklist. Measurement and Main Results: Total number of laboratory tests per patient-day decreased from 39.43 to an average of 26.74 ( P <.001) over a 9-month period. The number of iSTAT laboratory tests per patient-day decreased from 7.37 to an average of 1.16 ( P < .001) over the same time period. The number of iSTAT/central laboratory processing duplicative laboratory tests per patient-day decreased from 0.17 to an average of 0.01 ( P < .001). The percentage of patients who have daily laboratory test orders decreased from 100% to an average of 11.94% ( P <. 001). US$123 436 in direct savings and US$258 035 dollars in indirect savings could be achieved with these trends. Intensive care unit morbidity and mortality were not impacted. Conclusion: A simple technique of resident, nursing, and ancillary staff education, combined with alterations in order sets using electronic medical records, can lead to a sustained reduction in laboratory test utilization over time and to significant cost savings without affecting patient safety.

scholarly journals Graphical display of diagnostic test results in electronic health Records: a comparison of 8 systems

2015 ◽  
Vol 22 (4) ◽  
pp. 900-904 ◽  
Author(s):  
Dean F Sittig ◽  
Daniel R Murphy ◽  
Michael W Smith ◽  
Elise Russo ◽  
Adam Wright ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Laboratory Test ◽  
Clinical Laboratory ◽  
Negative Impact ◽  
Laboratory Data ◽  
Test Results ◽  
Health Records ◽  
Laboratory Test Results ◽  
Data Points ◽  
Electronic Health

Abstract Accurate display and interpretation of clinical laboratory test results is essential for safe and effective diagnosis and treatment. In an attempt to ascertain how well current electronic health records (EHRs) facilitated these processes, we evaluated the graphical displays of laboratory test results in eight EHRs using objective criteria for optimal graphs based on literature and expert opinion. None of the EHRs met all 11 criteria; the magnitude of deficiency ranged from one EHR meeting 10 of 11 criteria to three EHRs meeting only 5 of 11 criteria. One criterion (i.e., the EHR has a graph with y-axis labels that display both the name of the measured variable and the units of measure) was absent from all EHRs. One EHR system graphed results in reverse chronological order. One EHR system plotted data collected at unequally-spaced points in time using equally-spaced data points, which had the effect of erroneously depicting the visual slope perception between data points. This deficiency could have a significant, negative impact on patient safety. Only two EHR systems allowed users to see, hover-over, or click on a data point to see the precise values of the x–y coordinates. Our study suggests that many current EHR-generated graphs do not meet evidence-based criteria aimed at improving laboratory data comprehension.

scholarly journals Association of Test Results for 33 Frequently Used Laboratory Tests with Body Mass Index (BMI)

2020 ◽  
pp. 1-4
Author(s):  
Anders Larsson ◽  
Anders Larsson ◽  
Johan Ärnlöv ◽  
Johanna Helmersson-Karlqvist ◽  
Lars Lind ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Laboratory Test ◽  
Body Mass ◽  
Cystatin C ◽  
Apolipoprotein B ◽  
Laboratory Tests ◽  
Hdl Cholesterol ◽  
Apolipoprotein A1 ◽  
Test Results ◽  
Laboratory Test Results

Once considered a problem only for high-income countries, obesity rates are now rising worldwide. When evaluating test results from obese patients it is important to be aware of the effect of obesity on individual laboratory test results. The aim of the present study was to study the association between body mass index (BMI) and a group of frequently requested laboratory tests to evaluate which of these analytes that are affected by BMI. We analyzed the association between body mass index (BMI) and Alanine aminotransaminase (ALT), Albumin, Alkaline phosphatase, Pancreatic amylase, Apolipoprotein A1, Apolipoprotein B, Apolipoprotein B/Apolipoprotein A1 ratio, Aspartate aminotransferase (AST), AST/ALT ratio, Bilirubin, Calcium, Calprotectin, Cholesterol, HDL-cholesterol, Creatinine kinase (CK), Creatinine, C-reactive protein, Cystatin C, Gamma-glutamyl transferase (GGT), Iron, Iron saturation, Lactate dehydrogenase (LDH), Magnesium, Phosphate, Transferrin, Triglycerides, Urate, Urea, Zink, Hemoglobin, Platelet count and White blood cell count in an 80-year old population (n=531, 266 females and 265 males). There were significant Spearman rank associations between BMI and laboratory test results for several of the studied markers in both females and males. The strongest associations with BMI were noted for ALT, Apolipoprotein A1, HDL-cholesterol, Hemoglobin, CRP, Cystatin C, Triglycerides and Urate. In conclusion, several of the most frequently used laboratory markers are significantly associated with BMI. To be able to correctly interpret a test result it is important to be aware of the effects of BMI on the test results.

scholarly journals Reminders of Drug Effects on Laboratory Test Results

2000 ◽  
Vol 46 (9) ◽  
pp. 1395-1400 ◽  
Author(s):  
Marita Kailajärvi ◽  
Timo Takala ◽  
Paula Grönroos ◽  
Nils Tryding ◽  
Jorma Viikari ◽  
...  
Keyword(s):  
Laboratory Test ◽  
Laboratory Tests ◽  
Drug Effects ◽  
Study Drug ◽  
Test Results ◽  
Potential Drug ◽  
Reminder System ◽  
Patient Medication ◽  
Laboratory Test Results ◽  
Laboratory Results

Abstract Drug effects on laboratory test results are difficult to take into account without an online decision support system. In this study, drug effects on hormone test results were coded using a drug-laboratory effect (DLE) code. The criteria that trigger the reminders were defined. To issue reminders, it was necessary to write a computer program linking the DLE knowledge base with databases containing individual patient medication and laboratory test results. During the first 10 months, 11% of the results from hormone samples were accompanied by one or more DLE reminders. The most common drugs to trigger reminders were glucocorticoids, furosemide, and metoclopramide. Physicians facing the reminders completed a questionnaire on the usefulness of the reminders. All respondents considered them useful. In addition, DLE reminders had caused 74% of respondents to refrain from additional, usually performed examinations. In conclusion, drug effects on laboratory tests should always be considered when interpreting laboratory results. An online reminder system is useful in displaying potential drug effects alongside test results.

The Usefulness of Laboratory Tests in Health-Screening Programs

1973 ◽  
Vol 19 (4) ◽  
pp. 366-372 ◽  
Author(s):  
David L Sackett
Keyword(s):  
Laboratory Test ◽  
Laboratory Tests ◽  
Health Screening ◽  
Test Results ◽  
Screening Programs ◽  
Laboratory Screening ◽  
Rare Exception ◽  
Laboratory Test Results ◽  
The Mean ◽  
Regression Toward The Mean

Abstract I discuss pitfalls in laboratory-screening programs: regression toward the mean on repeated biochemical determinations; the problem of defining normalcy in the interpretation of laboratory test results; and a remarkable professional myopia in which clinical chemists have, with rare exception, failed to accept responsibility for evaluating whether the programs in which they are engaged are of benefit to patients.

scholarly journals Redundant laboratory testing on referral from general practice to the outpatient clinic

BJGP Open ◽  
2021 ◽  
pp. BJGPO.2021.0134
Author(s):  
Bram EL Vrijsen ◽  
Maarten J ten Berg ◽  
Wouter W van Solinge ◽  
Jan Westerink
Keyword(s):  
General Practitioner ◽  
Laboratory Test ◽  
Outpatient Clinic ◽  
Laboratory Testing ◽  
Laboratory Tests ◽  
Referral Letter ◽  
Test Results ◽  
Normal Test ◽  
Laboratory Test Results ◽  
High Level

BackgroundInappropriately repeated laboratory testing is a commonly occurring problem. However, this has not been studied extensively in the outpatient clinic after referral by general practitioners.AimThe aim of this study was to investigate how often laboratory tests ordered by the general practitioner were repeated on referral to the outpatient clinic, and how many of the normal test results remained normal on repetition.Design & settingThis is a post hoc analysis of a study on laboratory testing strategies in patients newly referred to the outpatient clinic.MethodAll patients who had a referral letter including laboratory test results ordered by the general practitioner were included. These results were compared to the laboratory test results ordered in the outpatient clinic.ResultsData were available for 295 patients, 191 of which had post-visit testing done. In this group, 56% of tests ordered by the general practitioner were repeated. Tests with abnormal results were repeated more frequently than tests with normal results (65% vs 53%; P<0.001). A longer test interval was associated with slightly smaller odds of tests being repeated (OR 0.97 [0.95–0.99]; P=0.003). Of the tests with normal test results that were repeated, 90% remained normal. This was independent of testing interval or testing strategy.ConclusionLaboratory tests ordered by the general practitioner are commonly repeated on referral to the outpatient clinic. The number of test results remaining normal on repetition suggests a high level of redundancy in laboratory test repetition.

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