ATLAS Tutorial: Data Sources - Condition Occurrence
Summary
TLDRThis video script introduces the Conditioned Reporting feature in Atlas, a tool for analyzing data sources standardized to the OMOP Common Data Model. It showcases a tree map and tabular view to visualize the prevalence and intensity of health conditions, such as type 2 diabetes and essential hypertension, across a database. Detailed graphs provide insights into concept prevalence trends, seasonal variations, and age distribution, highlighting Atlas's ability to drill down into specific health concepts for a comprehensive analysis.
Takeaways
- 🗺️ The video introduces the 'conditioned reporting' feature within the data sources capability in Atlas, which helps in analyzing and visualizing data.
- 📊 The 'condition occurrence report' is selected to demonstrate the tree map representation, where the size of boxes indicates the prevalence of a condition within the database.
- 🌡 The color in the tree map represents the intensity of the condition, as measured by the number of records per person with that concept.
- 🔍 Selecting a box, such as 'Type 2 diabetes mellitus', reveals detailed information about the prevalence and average records per person affected by the condition.
- 📝 There is also a tabular view available that lists concept ID, name, person counts, prevalence, and records per person in a more traditional format.
- 📊 The report includes graphs that show the prevalence of a condition stratified by year, age, and gender, indicating trends over time.
- 📈 The prevalence graph for 'essential hypertension' shows an increase over time and a higher prevalence in older adults, with relative similarity between genders.
- 📅 Another graph highlights the prevalence by month, showing a spike in October 2015, which may reflect a change in data source vocabularies from ICD-9 to ICD-10.
- 📋 The report also details the type of records for a concept, such as outpatient claims, and the distribution of age at the first occurrence of the concept, stratified by gender.
- 🔎 The condition occurrence report allows for detailed exploration of any concept, with the ability to sort and search the table for specific conditions.
- 🔑 The tool is described as powerful for understanding the occurrence of concepts within a condition domain and for comparing different data sources.
Q & A
What is the purpose of the 'Condition Occurrence' report in Atlas?
-The 'Condition Occurrence' report in Atlas is used to analyze and visualize the prevalence and intensity of various health conditions within a database, standardized to the OMOP Common Data Model.
How is the tree map representation in the 'Condition Occurrence' report helpful?
-The tree map representation provides a graphical display of the prevalence and intensity of conditions, where the size of the boxes indicates the prevalence and the color represents the intensity, measured by the number of records per person.
What does the prevalence percentage in the tree map signify?
-The prevalence percentage signifies the proportion of patients within the database that have a particular condition, such as 7.28% for type 2 diabetes mellitus affecting over 6.2 million patients.
How can the 'records per person' metric be interpreted in the context of the report?
-The 'records per person' metric indicates the average number of records associated with a specific condition for each patient who has that condition, reflecting the intensity of the condition's documentation.
What additional information is available in the tabular view of the report?
-The tabular view, or 'table' tab, offers a line listing of concepts with their IDs, names, person counts, prevalence, and records per person, allowing for a detailed examination of condition occurrence data.
How does one explore a specific condition in more detail within the report?
-By clicking on a row in the tabular view or selecting a box in the tree map, users can drill down into a detailed report for that specific condition, revealing additional graphs and data.
What does the first graph in the detailed report represent?
-The first graph in the detailed report represents the concept prevalence of a selected condition, stratified by year, age, and gender, providing insights into the condition's distribution over time and among different demographics.
What does the prevalence by month graph indicate about the stability of a condition?
-The prevalence by month graph shows the concept prevalence per thousand persons, indicating the stability or changes in the condition's occurrence over different months, which can reveal trends or anomalies like the spike in October 2015.
Why might there be a spike in condition prevalence in a specific month, as seen in the example?
-A spike in condition prevalence in a specific month, such as October 2015, might reflect changes in the data source vocabularies, like a transition from ICD-9 to ICD-10, rather than an actual increase in the condition's occurrence.
What does the 'records for this concept stratified by their type' graph show?
-This graph shows the distribution of concept records by their type, such as outpatient claims in primary or secondary diagnosis fields, and inpatient claims, indicating where the majority of the data for a condition is coming from.
How can the 'age at the first occurrence' graph help in understanding the condition's impact?
-The 'age at the first occurrence' graph, stratified by gender, provides insights into the median age and distribution of the first occurrence of a condition, helping to understand its impact across different age groups and genders.
What functionalities does the 'Condition Occurrence' report offer for data analysis?
-The 'Condition Occurrence' report allows for sorting based on prevalence or records per person and searching for specific concepts, enabling users to compare and contrast data across different sources.
Outlines
📊 Condition Occurrence Reporting in Atlas
The video script introduces the conditioned reporting feature within the data sources capability of Atlas. It begins by selecting the data sources report from the left-hand side menu, where users can choose from various standardized sources following the O mob common data model. The script focuses on the 'condition occurrence' report, which presents data in a tree map format. The tree map's size of boxes indicates the prevalence of a condition within the database, while the color intensity represents the number of records per person for that condition. For instance, type 2 diabetes mellitus is highlighted with its prevalence and average records per person. The script also mentions a tabular view for a more detailed listing of concepts, including concept ID, name, person counts, prevalence, and records per person. Further exploration is possible by clicking on rows to drill down into more detailed reports, including graphs that show concept prevalence stratified by year, age, gender, and other factors. The script notes an interesting spike in prevalence for essential hypertension in October 2015, likely due to a transition in data source vocabularies from ICD-9 to ICD-10.
🔍 In-depth Analysis with Condition Occurrence Report
The second paragraph delves deeper into the condition occurrence report's capabilities, allowing for a detailed analysis of specific concepts within the condition domain. It describes the ability to sort and search the condition occurrence table based on prevalence or records per person. The script provides an example of searching for 'diabetes mellitus', which leads to a drill-down report for type 2 diabetes mellitus. This report includes various graphs that offer insights into the concept's prevalence, such as age at first occurrence stratified by gender, and the distribution of age within that gender. The report is praised as a powerful tool for understanding the occurrence of concepts across different data sources and for making comparisons. The script concludes by directing viewers to Odyssey.org for more information about Atlas, its data sources reporting, and other features.
Mindmap
Keywords
💡Conditioned Reporting
💡Data Sources
💡Omop Common Data Model
💡Tree Map
💡Prevalence
💡Concept
💡Tabular View
💡Drill Down
💡Trellis Plots
💡ICD-9 and ICD-10
💡Concept Records
Highlights
Introduction to conditioned reporting in data sources capability within Atlas.
Selection of data sources standardized to the O mob common data model.
Condition occurrence report selection leads to a tree map representation.
Tree map size indicates the prevalence of a condition concept within the database.
Color in the tree map represents the intensity of the condition concept.
Example of type 2 diabetes mellitus concept prevalence and records per person.
Tabular view provides a line listing of concepts with ID, name, person counts, prevalence, and records per person.
Drilling down on rows provides additional information on the concept.
Graphs represent concept prevalence stratified by year, age, and gender.
Trellis plots show the prevalence of essential hypertension over time and across different demographics.
Concept prevalence can reflect changes in data source vocabularies, such as the transition from ICD-9 to ICD-10.
Prevalence by month graph shows stability with a notable spike in October 2015.
Records for the concept are stratified by type and concept ID.
Outpatient claims are a significant source of concept records.
Age at first occurrence graph provides insights into the distribution by gender and age.
Median age and interquartile range for essential hypertension concept by gender.
Condition occurrence report allows for sorting and searching within the table for specific concepts.
Drill-down report for type 2 diabetes mellitus provides detailed graphs and information.
The condition occurrence report is a powerful tool for understanding and comparing concepts across different data sources.
For more information, visit Odyssey.org.
Transcripts
[Music]
today we're going to introduce the
conditioned reporting inside of the data
sources capability within Atlas on the
left-hand side I will select the data
sources report and here we can select
any of our sources that have been
standardized to the O mob common data
model and configured inside of Atlas and
we're going to select any of a series of
data sources reports today we've
selected condition occurrence when you
select the condition occurrence report
you will be brought to this tree map
representation where you see a large
series of boxes hovering over the boxes
will reveal the information about what
they share here the size of the box
represents the prevalence of a condition
concept within the database and the
color represents his intensity as
represented by the number of records per
person who have that concept so for
example here I've selected a box which
is the type 2 diabetes mellitus concept
the prevalence of that concept in this
database is 7.2 8% which is over 6.2
million patients in this data source and
for people who have a dykon cept of type
2 diabetes mellitus we can see that
those people on average have 15.5
records per person this tree map
representation provides you a graphical
display to see which concepts occur more
or less frequently as well as a general
sense of the intensity there's also a
tabular view represented in this tab
called table which provides you the same
information as a tabular line listing so
here each row provides you the concept
ID the concept name and then the person
counts prevalence and records per person
here we can see this first row shows the
concept of essential hypertension in
this data source occurs in 15.6 million
patients which is a prevalence cot of
the concept of 18 percent and on average
people who have this essential
hypertension concept have it eleven
point three times
each of these rows can be explored
further by clicking on the row and
drilling down to the report here I've
selected the essential hypertension
concept and so I can scroll down to see
the additional information that is made
available the first graph represents the
concept prevalence of the concept of
essential hypertension the graph is
stratifying that prevalence by year age
and gender in each of these trellis
plots we can see the x-axis represents
the year of observation here this data
sources showing me information from 2000
to 2017 each trellis is representing an
age decile and the y axis of each of
these plots represents the concept
prevalence per thousand persons so on
this graph we can see for essential
hypertension that the prevalent concept
prevalence of that is higher in older
adults it seems to be growing over time
and it seems to be relatively similar
between men and women represented by the
colored line series if I scroll down
further we see a graph here representing
prevalence by month the x-axis is
showing us the calendar month the y-axis
is showing us the concept prevalence per
thousand persons this graph is showing
us a relative stability of this
particular concept in the data source
here we can see it is growing at a
relatively constant clip over time until
there seems to be an interesting spike
at October 2015 here we can see in
October 2015 the prevalence is 60
persons per per thousand persons it's
important to reinforce that the
information provided here is a concept
prevalence not a disease or phenotype
prevalence in this particular case the
illustration of the change in October of
2015 may be a reflection of the source
data source vocabularies and in this
particular case transition from icd-9 to
icd-10
the next graph down below represents the
records for this concept stratified by
their type concept ID here we can see in
this data source that 68% of the concept
records come from an outpatient claim in
a secondary diagnosis field while 27% of
the data is coming from an outpatient
claim in a primary diagnosis field we
can additionally see information coming
from inpatient claims as well
finally the graph to the right shows us
the age at the first occurrence of this
concept here we can see stratified by
gender on the x-axis and age represented
on the y axis and if hovering over any
of these box plots provides me
information about the distribution of
age within that particular gender so
here we can see that the median age of
people who are females who receive a
essential hypertension concept is 60 and
the distribution represented by the 10th
and 90th percentile in the interquartile
range the 25th and 75th percentile the
condition occurrence report here allows
drill down on any particular concept of
interest in the condition occurrence
table this table allows for both sorting
based on the prevalence or records per
person as well as searching for any
particular concept if I search for
diabetes mellitus we can see that the
concept of type 2 diabetes mellitus
appears in the table and selecting that
row will again bring up a drill down
report once the report is loaded for
that particular concept again we can
scroll down to see each of those same
graphs represented consistently in this
tool the condition occurs report is a
powerful tool to allow you to understand
what concepts are occurring in the
condition domain within a particular
source and to be able to compare and
contrast across different sources
you may have available in your
environment for more information about
Atlas in the data sources reporting and
the rest of Odyssey check us out at
Odyssey org
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