The Experts below are selected from a list of 240903 Experts worldwide ranked by ideXlab platform
Shaun J. Grannis - One of the best experts on this subject based on the ideXlab platform.
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electronic health information quality challenges and interventions to improve public health surveillance data and practice
Public Health Reports, 2013Co-Authors: Brian E. Dixon, Jason Siegel, Tanya V Oemig, Shaun J. GrannisAbstract:Objective.We examined Completeness, an attribute of data quality, in the context of electronic laboratory reporting (ELR) of notifiable disease information to public health agencies.Methods.We extracted more than seven million ELR messages from multiple clinical information systems in two states We calculated and compared the Completeness of various data fields within the messages that were identified to be important to public health reporting processes We compared unaltered, original messages from source systems with similar messages from another state as well as messages enriched by a health information exchange (HIE). Our analysis focused on calculating Completeness (i e, the number of nonmissing values) for fields deemed important for inclusion in notifiable disease case reports.Results.The Completeness of data fields for laboratory transactions varied across clinical information systems and jurisdictions. Fields identifying the patient and test results were usually complete (97%–100%). Fields contain...
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electronic laboratory data quality and the value of a health information exchange to support public health reporting processes
American Medical Informatics Association Annual Symposium, 2011Co-Authors: Brian E. Dixon, Julie J. Mcgowan, Shaun J. GrannisAbstract:There is increasing interest in leveraging electronic health data across disparate sources for a variety of uses. A fallacy often held by data consumers is that clinical data quality is homogeneous across sources. We examined one attribute of data quality, Completeness, in the context of electronic laboratory reporting of notifiable disease information. We evaluated 7.5 million laboratory reports from clinical information systems for their Completeness with respect to data needed for public health reporting processes. We also examined the impact of health information exchange (HIE) enhancement methods that attempt to improve Completeness. The laboratory data were heterogeneous in their Completeness. Fields identifying the patient and test results were usually complete. Fields containing patient demographics, patient contact information, and provider contact information were suboptimal. Data processed by the HIE were often more complete, suggesting that HIEs can support improvements to existing public health reporting processes.
Brian E. Dixon - One of the best experts on this subject based on the ideXlab platform.
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electronic health information quality challenges and interventions to improve public health surveillance data and practice
Public Health Reports, 2013Co-Authors: Brian E. Dixon, Jason Siegel, Tanya V Oemig, Shaun J. GrannisAbstract:Objective.We examined Completeness, an attribute of data quality, in the context of electronic laboratory reporting (ELR) of notifiable disease information to public health agencies.Methods.We extracted more than seven million ELR messages from multiple clinical information systems in two states We calculated and compared the Completeness of various data fields within the messages that were identified to be important to public health reporting processes We compared unaltered, original messages from source systems with similar messages from another state as well as messages enriched by a health information exchange (HIE). Our analysis focused on calculating Completeness (i e, the number of nonmissing values) for fields deemed important for inclusion in notifiable disease case reports.Results.The Completeness of data fields for laboratory transactions varied across clinical information systems and jurisdictions. Fields identifying the patient and test results were usually complete (97%–100%). Fields contain...
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electronic laboratory data quality and the value of a health information exchange to support public health reporting processes
American Medical Informatics Association Annual Symposium, 2011Co-Authors: Brian E. Dixon, Julie J. Mcgowan, Shaun J. GrannisAbstract:There is increasing interest in leveraging electronic health data across disparate sources for a variety of uses. A fallacy often held by data consumers is that clinical data quality is homogeneous across sources. We examined one attribute of data quality, Completeness, in the context of electronic laboratory reporting of notifiable disease information. We evaluated 7.5 million laboratory reports from clinical information systems for their Completeness with respect to data needed for public health reporting processes. We also examined the impact of health information exchange (HIE) enhancement methods that attempt to improve Completeness. The laboratory data were heterogeneous in their Completeness. Fields identifying the patient and test results were usually complete. Fields containing patient demographics, patient contact information, and provider contact information were suboptimal. Data processed by the HIE were often more complete, suggesting that HIEs can support improvements to existing public health reporting processes.
Benjamin Schlein - One of the best experts on this subject based on the ideXlab platform.
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asymptotic Completeness for compton scattering
Communications in Mathematical Physics, 2004Co-Authors: Jurg Frohlich, Marcel Griesemer, Benjamin SchleinAbstract:Scattering in a model of a massive quantum-mechanical particle, an ‘‘electron’’, interacting with massless, relativistic bosons, ‘‘photons’’, is studied. The interaction term in the Hamiltonian of our model describes emission and absorption of ‘‘photons’’ by the ‘‘electron’’; but ‘‘electron-positron’’ pair production is suppressed. An ultraviolet cutoff and an (arbitrarily small, but fixed) infrared cutoff are imposed on the interaction term. In a range of energies where the propagation speed of the dressed ‘‘electron’’ is strictly smaller than the speed of light, unitarity of the scattering matrix is proven, provided the coupling constant is small enough; (asymptotic Completeness of Compton scattering). The proof combines a construction of dressed one–electron states with propagation estimates for the ‘‘electron’’ and the ‘‘photons’’.
Tim Adair - One of the best experts on this subject based on the ideXlab platform.
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how reliable are self reported estimates of birth registration Completeness comparison with vital statistics systems
PLOS ONE, 2021Co-Authors: Tim Adair, Alan D LopezAbstract:Background The widely-used estimates of Completeness of birth registration collected by Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) and published by UNICEF primarily rely on registration status of children as reported by respondents. However, these self-reported estimates may be inaccurate when compared with Completeness as assessed from nationally-reported official birth registration statistics, for several reasons, including over-reporting of registration due to concern about penalties for non-registration. This study assesses the concordance of self-reported birth registration and certification Completeness with Completeness calculated from civil registration and vital statistics (CRVS) systems data for 57 countries. Methods Self-reported estimates of birth registration and certification Completeness, at ages less than five years and 12-23 months, were compiled and calculated from the UNICEF birth registration database, DHS and MICS. CRVS birth registration Completeness was calculated as birth registrations reported by a national authority divided by estimates of live births published in the United Nations (UN) World Population Prospects or the Global Burden of Disease (GBD) Study. Summary measures of concordance were used to compare Completeness estimates. Findings Birth registration Completeness (based on ages less than five years) calculated from self-reported data is higher than that estimated from CRVS data in most of the 57 countries (31 countries according to UN estimated births, average six percentage points (p.p.) higher; 43 countries according to GBD, average eight p.p. higher). For countries with CRVS Completeness less than 95%, self-reported Completeness was higher in 26 of 28 countries, an average 13 p.p. and median 9-10 p.p. higher. Self-reported Completeness is at least 30 p.p. higher than CRVS Completeness in three countries. Self-reported birth certification Completeness exhibits closer concordance with CRVS Completeness. Similar results are found for self-reported Completeness at 12-23 months. Conclusions These findings suggest that self-reported Completeness figures over-estimate Completeness when compared with CRVS data, especially at lower levels of Completeness, partly due to over-reporting of registration by respondents. Estimates published by UNICEF should be viewed cautiously, especially given their wide usage.
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estimating the Completeness of death registration an empirical method
PLOS ONE, 2018Co-Authors: Tim Adair, A LopezAbstract:Introduction Many national and subnational governments need to routinely measure the Completeness of death registration for monitoring and statistical purposes. Existing methods, such as death distribution and capture-recapture methods, have a number of limitations such as inaccuracy and complexity that prevent widespread application. This paper presents a novel empirical method to estimate Completeness of death registration at the national and subnational level. Methods Random-effects models to predict the logit of death registration Completeness were developed from 2,451 country-years in 110 countries from 1970–2015 using the Global Burden of Disease 2015 database. Predictors include the registered crude death rate, under-five mortality rate, population age structure and under-five death registration Completeness. Models were developed separately for males, females and both sexes. Findings All variables are highly significant and reliably predict Completeness of registration across a wide range of registered crude death rates (R-squared 0.85). Mean error is highest at medium levels of observed Completeness. The models show quite close agreement between predicted and observed Completeness for populations outside the dataset. There is high concordance with the Hybrid death distribution method in Brazilian states. Uncertainty in the under-five mortality rate, assessed using the dataset and in Colombian departmentos, has minimal impact on national level predicted Completeness, but a larger effect at the subnational level. Conclusions The method demonstrates sufficient flexibility to predict a wide range of Completeness levels at a given registered crude death rate. The method can be applied utilising data readily available at the subnational level, and can be used to assess Completeness of deaths reported from health facilities, censuses and surveys. Its utility is diminished where the adult mortality rate is unusually high for a given under-five mortality rate. The method overcomes the considerable limitations of existing methods and has considerable potential for widespread application by national and subnational governments.
Sukil Kim - One of the best experts on this subject based on the ideXlab platform.
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the effects of an electronic medical record on the Completeness of documentation in the anesthesia record
International Journal of Medical Informatics, 2013Co-Authors: Junghwa Jang, Chunbae Kim, Youngkyu Moon, Sukil KimAbstract:Abstract Objectives The purpose of this study is to evaluate the Completeness of anesthesia recording before and after the introduction of an electronic anesthesia record. Methods The study was conducted in a Korean teaching hospital where the EMR was implemented in October 2008. One hundred paper anesthesia records from July to September 2008 and 150 electronic anesthesia records during the same period in 2009 were randomly sampled. Thirty-four essential items were selected out of all the anesthesia items and grouped into automatically transferred items and manual entry items. 1, .5 and 0 points were given for each item of complete entry, incomplete entry and no entry respectively. The Completeness of documentation was defined as the sum of the scores. The influencing factors on the Completeness of documentation were evaluated in total and by the groups. Results The average Completeness score of the electronic anesthesia records was 3.15% higher than that of the paper records. A multiple regression model showed the type of the anesthesia record was a significant factor on the Completeness of anesthesia records in all items ( β =.98, p β =.56, p Conclusions The Completeness of an anesthesia record was improved after the implementation of the electronic anesthesia record. The reuse of the data from the EMR was the main contributor to the improved Completeness.
