11. hhs.gov/idealab
OpenFDA
More data available in more useful
formats via API and raw structured file
download
• Medical Device Adverse Events
• Recall reports
• Prescription Drug, OTC Drug,
Biological Product Labeling
14. hhs.gov/idealab
Catalyzing and testing new ideas
rapidly
Accelerating proven ideas through
investment
HHS Ignite Accelerator
HHS Ventures Fund
Recognizing HHS employees’
innovations
HHS Innovates Awards
15. hhs.gov/idealab
Partnering with not-for-profits to
recruit external talent to work on a
shared problem
Recruiting external talent to work
on high-risk, high-reward projects
over a 12-month period
HHS Entrepreneurs-in-
Residence
HHS Innovators-in-
Residence
17. Demand-Driven Open Data
An introduction for data owners
http://demand-driven-open-data.github.io
David.Portnoy@HHS.gov
18. Evaluation &
feedback
Complete
use cases
Implem
ent
Prioritized
use cases
PrioritizeIncoming
use cases
Prioritization is at the level of program owner
Consider implementation cost, savings from avoided future
requests (such as FOIA), revenue opportunity for future cost
recovery, risk of PII/PHI, risk of misinterpretation
Including strategic relevance, agency mission,
org priorities, recognition
The decision to implement is not binary. It involves
requirements management for potentially multiple
interested parties
① ② ③
All prioritization and implementation decisions are made by Data Owners.
We found there are typically 3 drivers.
But we are living in a health care system where data is driving change.
Data is changing how we interact, experience, and manage health care.
Data is fueling changes like payment reform – where we will pay for the quality of the care we receive and not the quantity of procedures
Data is changing how the average American interacts and manages their own health – changing it from something that was only addressed when sick, to something that is monitored and managed daily through personal devices and access to electronic health records
Data is changing how physicians provide care – from the integration of personal monitoring device data, to the use of predictive analytics to give a patient the best treatment plan
In a 2011 report from McKinsey and Company, the value of data in health care is identified as having the potential to remove billions of dollars in costs from the nation’s health care system and significantly increase the quality of care.
This is the Department of Health and Human Services.
There are roughly 80,000 employees, organized into 11 operating divisions.
And in one of those institutes, in this case, the National Cancer Institute, there can be a number of Offices, Divisions and Centers. At the National Cancer Institute, there are a total of 28 – and in those 28, there can be even more division based on offices, branches and groups.
I would also like to point out the ridiculous number of acronyms on the screen right now. Welcome to government!
FDA DATA
A team at the Food and Drug Administration has been working to not only liberate more data, but to make the data available in more useful formats via API and raw structured file download.
They are doing this through the openFDA project, a project that is being led by Presidential Innovation Fellow Sean Herron.
Examples of the types of data that is becoming available for use in application development or inclusion in existing tools are:
First release was Adverse Events Data – On June 2 open FDA released information on adverse event and medication error reports submitted to the FDA. The database is designed to support the FDA’s post-marketing safety surveillance program for drug and therapeutic biological products.
Recall Data – Which includes food, drug, medical devices, cosmetics, biologics and pet food
Structured Product Labeling Data – This information includes information that is on drug labels
FDA DATA
A team at the Food and Drug Administration has been working to not only liberate more data, but to make the data available in more useful formats via API and raw structured file download.
They are doing this through the openFDA project, a project that is being led by Presidential Innovation Fellow Sean Herron.
Examples of the types of data that is becoming available for use in application development or inclusion in existing tools are:
First release was Adverse Events Data – On June 2 open FDA released information on adverse event and medication error reports submitted to the FDA. The database is designed to support the FDA’s post-marketing safety surveillance program for drug and therapeutic biological products.
Recall Data – Which includes food, drug, medical devices, cosmetics, biologics and pet food
Structured Product Labeling Data – This information includes information that is on drug labels
FDA DATA
A team at the Food and Drug Administration has been working to not only liberate more data, but to make the data available in more useful formats via API and raw structured file download.
They are doing this through the openFDA project, a project that is being led by Presidential Innovation Fellow Sean Herron.
Examples of the types of data that is becoming available for use in application development or inclusion in existing tools are:
First release was Adverse Events Data – On June 2 open FDA released information on adverse event and medication error reports submitted to the FDA. The database is designed to support the FDA’s post-marketing safety surveillance program for drug and therapeutic biological products.
Recall Data – Which includes food, drug, medical devices, cosmetics, biologics and pet food
Structured Product Labeling Data – This information includes information that is on drug labels
FDA DATA
A team at the Food and Drug Administration has been working to not only liberate more data, but to make the data available in more useful formats via API and raw structured file download.
They are doing this through the openFDA project, a project that is being led by Presidential Innovation Fellow Sean Herron.
Examples of the types of data that is becoming available for use in application development or inclusion in existing tools are:
First release was Adverse Events Data – On June 2 open FDA released information on adverse event and medication error reports submitted to the FDA. The database is designed to support the FDA’s post-marketing safety surveillance program for drug and therapeutic biological products.
Recall Data – Which includes food, drug, medical devices, cosmetics, biologics and pet food
Structured Product Labeling Data – This information includes information that is on drug labels
This is the Department of Health and Human Services.
There are roughly 80,000 employees, organized into 11 operating divisions.
This is the Department of Health and Human Services.
There are roughly 80,000 employees, organized into 11 operating divisions.
“Demand Driven Open Data” (DDOD) is a collection of tools and methods that provide external data users (such as industry, researchers, nonprofits, and media) with a systematic, ongoing and transparent mechanism to tell HHS what data they need to be managed, measured and executed in terms of use cases, which enables allocation of limited resources based on value delivered.
