aolivamd.blogspot.com
Thoughts on Medical Informatics: Deciding When to Change the SDTM
http://aolivamd.blogspot.com/2016/08/deciding-when-to-change-sdtm.html
Thoughts on Medical Informatics. Deciding When to Change the SDTM. I frequently come across proposals to change or upgrade the SDTM. Experience has shown that changes to the SDTM are a big deal. That hopefully will result in a more stable standard (see my previous post. We recognize that some change is inevitable, but change that can be accomplished through other means should be pursued. Stakeholders need a stable standard. Here are some working definitions:. Here I use the HIMSS definition. A good excha...
aolivamd.blogspot.com
Thoughts on Medical Informatics: September 2016
http://aolivamd.blogspot.com/2016_09_01_archive.html
Thoughts on Medical Informatics. Rethinking the Three CDISC General Observation Classes. Please note this post has been updated to reflect updates to some clinical definitions referenced in this post. The links have been updated as well. These do not change the overall message and conclusions. The CDISC Study Data Tabulation Model ( SDTM. Here are some thoughts. I certainly welcome comments. The Events class . captures planned protocol milestones such as randomization and study completion, and occurr...
aolivamd.blogspot.com
Thoughts on Medical Informatics: March 2016
http://aolivamd.blogspot.com/2016_03_01_archive.html
Thoughts on Medical Informatics. Distinguishing Clinical Observations and Medical Conditions. As the pharmaceutical industry moves quickly towards standardized clinical study data, I continue to see confusion in how clinical observations and medical conditions are represented. In clinical medicine there is a sharp distinction between these two concepts, yet in standardized study data submissions they are often lumped together. Herein lies the major distinction between clinical observations and medical co...
aolivamd.blogspot.com
Thoughts on Medical Informatics: Distinguishing Clinical Observations and Medical Conditions
http://aolivamd.blogspot.com/2016/03/distinguishing-clinical-observations.html
Thoughts on Medical Informatics. Distinguishing Clinical Observations and Medical Conditions. As the pharmaceutical industry moves quickly towards standardized clinical study data, I continue to see confusion in how clinical observations and medical conditions are represented. In clinical medicine there is a sharp distinction between these two concepts, yet in standardized study data submissions they are often lumped together. Herein lies the major distinction between clinical observations and medical co...
aolivamd.blogspot.com
Thoughts on Medical Informatics: Aristotle and How Best to Define Things
http://aolivamd.blogspot.com/2015/12/aristotle-and-how-best-to-define-things.html
Thoughts on Medical Informatics. Aristotle and How Best to Define Things. The great challenge in automating analysis of biomedical data is the fact the people use different words for the same thing and the same word for different things. Having clear, unambiguous definitions, or semantics, is of course critical. I wrote a bit about this in a post on the Interoperability Problem. Also in a previous post. It turns out that the Open Biomedical Ontologies. Provides an Ontology for Biomedical Investigations.
aolivamd.blogspot.com
Thoughts on Medical Informatics: Rethinking the Three CDISC General Observation Classes
http://aolivamd.blogspot.com/2016/09/rethinking-three-cdisc-general.html
Thoughts on Medical Informatics. Rethinking the Three CDISC General Observation Classes. Please note this post has been updated to reflect updates to some clinical definitions referenced in this post. The links have been updated as well. These do not change the overall message and conclusions. The CDISC Study Data Tabulation Model ( SDTM. Here are some thoughts. I certainly welcome comments. The Events class . captures planned protocol milestones such as randomization and study completion, and occurr...
aolivamd.blogspot.com
Thoughts on Medical Informatics: October 2016
http://aolivamd.blogspot.com/2016_10_01_archive.html
Thoughts on Medical Informatics. Definition of Common Clinical Terms v2. I proposed some working definitions of common clinical terms. Since then additional thinking and feedback has led to some refinements. I'm reposting and cross-referencing the two versions. The changes are highlighted in bold and red. We all use these words in clinical medicine: observations, assessments, diagnosis, medical condition, adverse event, outcome measure, endpoint. But what do they really mean? I have come up with the foll...
aolivamd.blogspot.com
Thoughts on Medical Informatics: Observations, Assessments, and BRIDG
http://aolivamd.blogspot.com/2015/08/observations-assessment-and-bridg.html
Thoughts on Medical Informatics. Observations, Assessments, and BRIDG. In a previous post, I discussed my view of how clinical data are generated and used (see Modeling Clinical Data. I discussed the differences between an observation and an assessment. This is an important distinction in clinical medicine. Eg 30-4.5 mg/dL). Are there other clinical observations suggesting clinical hyperkalemia (e.g. EKG findings)? Could it be laboratory error (is a repeat measurement necessary)? An important clinical di...
aolivamd.blogspot.com
Thoughts on Medical Informatics: August 2016
http://aolivamd.blogspot.com/2016_08_01_archive.html
Thoughts on Medical Informatics. Deciding When to Change the SDTM. I frequently come across proposals to change or upgrade the SDTM. Experience has shown that changes to the SDTM are a big deal. That hopefully will result in a more stable standard (see my previous post. We recognize that some change is inevitable, but change that can be accomplished through other means should be pursued. Stakeholders need a stable standard. Here are some working definitions:. Here I use the HIMSS definition. A good excha...
aolivamd.blogspot.com
Thoughts on Medical Informatics: December 2015
http://aolivamd.blogspot.com/2015_12_01_archive.html
Thoughts on Medical Informatics. Aristotle and How Best to Define Things. The great challenge in automating analysis of biomedical data is the fact the people use different words for the same thing and the same word for different things. Having clear, unambiguous definitions, or semantics, is of course critical. I wrote a bit about this in a post on the Interoperability Problem. Also in a previous post. It turns out that the Open Biomedical Ontologies. Provides an Ontology for Biomedical Investigations.
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