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

Author(s):  
Sanjaya Dhakal ◽  
Sherry L. Burrer ◽  
Carla A. Winston ◽  
Achintya Dey ◽  
Umed Ajani ◽  
...  

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.

2015 ◽  
Vol 22 (4) ◽  
pp. 900-904 ◽  
Author(s):  
Dean F Sittig ◽  
Daniel R Murphy ◽  
Michael W Smith ◽  
Elise Russo ◽  
Adam Wright ◽  
...  

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.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
B E Dixon ◽  
Y A Ho ◽  
A A Broyles ◽  
A Wiensch ◽  
J N Arno

Abstract Background Public health researchers seek to use administrative health data captured in digital health systems to examine outcomes for individuals with sexually transmitted infections (STIs). Yet the International Classification of Diseases, Tenth Revision (ICD-10) codes used to identify cases of chlamydia and gonorrhea have not been validated. Objective We sought to assess the validity of using ICD-10 codes to identify cases of chlamydia and gonorrhea. Methods We utilized data from electronic health records gathered from private and public health systems from 1 October, 2015 to 31 December, 2016. Patients were included if they were aged 13-44 and received either 1) laboratory testing for chlamydia or gonorrhea or 2) an ICD-10 diagnosis of chlamydia, gonorrhea, or an unspecified STI. To validate ICD-10 codes, we calculated positive and negative predictive values, sensitivity, and specificity based on the presence of a laboratory test result, or any STI laboratory test results in case of unspecified STI. We further examined the timing of clinical diagnosis relative to laboratory testing. Results A total of 238,876 individuals (16.0% of population) were either tested for chlamydia or gonorrhea, or diagnosed with an ICD-10 code of interest, during the study period. For cases in which a patient was diagnosed with chlamydia or gonorrhea, 82% and 78% of cases were confirmed, respectively. The positive predictive values for chlamydia, gonorrhea, and unspecified STI ICD-10 codes were 87.6%, 85.0%, and 32.0%, respectively. Negative predictive values were high (>92%). Sensitivity for chlamydia diagnostic codes was 10.6% and gonorrhea was 9.7%. Specificity was 99.9% for both chlamydia and gonorrhea. Conclusions Disease specific ICD-10 codes accurately identify cases of chlamydia and gonorrhea. However, low sensitivities suggest that most gonorrhea and chlamydia cases could not be identified in administrative data alone without laboratory test results. Key messages Disease specific ICD-10-CM codes accurately identify cases of chlamydia and gonorrhea. Low sensitivities suggest that most gonorrhea and chlamydia cases could not be identified in administrative data alone without laboratory test results.


2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Wilfred Bonney ◽  
Sandy F Price ◽  
Roque Miramontes

Objective: The objective of this presentation is to use a congruence of standardization protocols to effectively ensure that the quality of the data elements and exchange formats within the NTSS are optimal for users of the system.Introduction: Disease surveillance systems remain the best quality systems to rely on when standardized surveillance systems provide the best data to understand disease occurrence and trends. The United States National Tuberculosis Surveillance System (NTSS) contains reported tuberculosis (TB) cases provided by all 50 states, the District of Columbia (DC), New York City, Puerto Rico, and other U.S.-affiliated jurisdictions in the Pacific Ocean and Caribbean Sea [1]. However, the NTSS currently captures phenotypic drug susceptibility testing (DST) data and does not have the ability to collect the rapid molecular DST data generated by platforms such as Cepheid GeneXpert MTB/RIF, Hain MTBDRplus and MTBDRsl, Pyrosequencing, and Whole Genome Sequencing [2-6]. Moreover, the information exchanges within the NTSS (represented in HL7 v2.5.1 [7]) are missing critical segments for appropriately representing laboratory test results and data on microbiological specimens.Methods: The application of the standardization protocols involves: (a) the revision of the current Report of Verified Case of Tuberculosis (RCVT) form to include the collection of molecular DST data; (b) the enhancement of the TB Case Notification Message Mapping Guide (MMG) v2.03 [8] to include segments for appropriately reporting laboratory test results (i.e., using Logical Observation Identifiers Names and Codes (LOINC) as a recommended vocabulary) and microbiology related test results (i.e., using Systematized Nomenclature of Medicine -- Clinical Terms (SNOMED CT) as a recommended vocabulary); and (c) the standardization of the laboratory testing results generated by the variety of molecular DST platforms, reported to TB health departments through electronic laboratory results (ELR), using those same standardized LOINC and SNOMED CT vocabularies in HL7 v2.5.1 [7].Results: The application of the standardization protocols would optimize early detection and reporting of rifampin-resistant TB cases; provide a high-quality data-driven decision-making process by public health administrators on TB cases; and generate high-quality datasets to enhance reporting or analyses of TB surveillance data and drug resistance.Conclusions: This study demonstrates that it is possible to apply standardized protocols to improve the quality of data, specifications and exchange formats within the NTSS, thereby streamlining the seamless exchange of TB incident cases in an integrated public health environment supporting TB surveillance, informatics, and translational research.


1997 ◽  
Vol 36 (01) ◽  
pp. 17-19 ◽  
Author(s):  
J. O. O. Hoeke ◽  
B. Bonke ◽  
R. van Strik ◽  
E. S. Gelsema ◽  
R. Verheij

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.


2020 ◽  
pp. 86-90
Author(s):  
V. G. Akimov

The diagnosis is the result of the physician’s synthesis of all anamnestic, clinical and instrumental data from the patient’s examination. However, for various reasons, the putative clinical diagnosis is not always supported by laboratory test results. The article discusses the main reasons for such discrepancies, emphasizes the responsibility of the attending physician for reliable diagnosis of the disease.


1983 ◽  
Vol 40 (6) ◽  
pp. 1025-1034
Author(s):  
Carol L. Colvin ◽  
Raymond J. Townsend ◽  
William R. Gillespie ◽  
Kenneth S. Albert

2015 ◽  
Vol 25 (3) ◽  
pp. 307-316 ◽  
Author(s):  
Dukyong Yoon ◽  
Martijn J. Schuemie ◽  
Ju Han Kim ◽  
Dong Ki Kim ◽  
Man Young Park ◽  
...  

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