SlideShare une entreprise Scribd logo
1  sur  27
Research Data Browser
UCSF ITS - Academic Research Systems
Research Data Browser
The goal is to accelerate the clinical scientific discovery process for UCSF
investigators by enabling:
• Accelerated hypothesis generation to a wider audience, prior to CHR
approval, using de-identified data
• Rapid Query – all data in memory, not disk
• Visual Profiling of selected patients
• Export to Excel or Flat File
Overall Goal of Research Data Browser
When you access the Research Data Browser, the Select View is the first page
displayed. There are two separate views of the same data: Patient View and
Encounter View.
Select View Page
Data as of: –
displays the
production date.
Most times this
field is two days
behind production.
Patient View – All Selections Tab
The “All Selections” tab displays all variables that may be used for selecting patients
Patient View – All Selections Tab
• Query for a Sex = Female by clicking the drop-down box
for “Sex” and selecting “Female”
Patient View – All Selections Tab
• The Total Patients matching your query conditions
is always displayed
• The “Current Selection” window summarizes what
conditions you have already placed in your current
query
• You can use the Eraser icon to remove conditions
• You can use “Clear Selections” to clear the query
and start again
• The variables that you have used in your selection
will be displayed in Green
Patient View – All Selections Tab
• For Diagnosis Name, type “Diabetes Mellitus”
(quotes included) and it will select all diagnoses
that contain “Diabetes” and “Mellitus” in the
same name
• You can accept the whole list, or click-and-drag the
diagnosis names you want
Patient View – All Selections Tab
• For selecting on lab values, you first select the lab
test(s) such as “Creatinine”
• Then select a value range such as “>3”. Using the
“>” or “<“ symbol limits resulting values to only
numeric, and only within the requested range
Patient View – All Selections Tab
• Use the “?” Icon to show a definition of each
variable in the selection box
Add Bookmark
Make a Bookmark of the Current Selection.
In the future, Bookmark applies query to the new dataset
Patient View Home Tab
The first tab of the Patient View profiles your currently selected patients by age, diagnosis, discharge
disposition and ordered medications
Using a Graph to Change Search Criteria
1. Click on the Skilled
Nursing Homes
(the green pie
piece) on the Top 5
Discharge
Disposition graph.
2. The Top 5
Discharge
Disposition graph
now only displays
Skilled Nursing
Homes
information.
NOTE: As you select your criteria on one tab, it
carries over to all the other tabs.
Demographics Tab
Profile Selected Patients by Demographics
Select the Demographics Tab
Note: All Tabs reflect the same Current
Selection
Use the Toggle button to switch
between Age and Age Group
Encounters Tab
Diagnoses Tab
Medications Tab
Labs Tab
Procedures Tab
Exploration Tab – Custom Visualization and Export
Exploration Tab – Bar Chart of Creatinines > 3
Exploration Tab – Tabulate all Creatinines > 3
Exploration Tab – Export all Creatinines > 3
HIPAA De-Identified Data
• Data has been de-identified per HIPPA Safe-Harbor definition
• Patient ID, Encounter ID and other identifiers have been replaced by randomly
generated numbers
• Dates have a random offset of up to a year in the past and each patient has
the same offset for all dates
• Ages over 90 are shown as 90
• De-identified data is sensitive information. User’s agree to:
• Not attempt to re-identify the data
• Not share data with unauthorized individuals
Limitations of the Research Data Browser
• Only data from encounters after June 1, 2012 are included (APeX go-live date)
• Data is typically one day old – see the Data as of: field
• Procedures and Med Orders are limited to orders manually entered in APeX
by a provider
(ORDER_METRICS):
 No child orders
 No orders created by an interface
 No pending orders
 No historical orders
 No cabinet overrides
Why We Are Excited About RDB
• Unleash the creativity of world-class clinical and informatics
scientists
• Quickly ask questions any time of day, without CHR approval or
programmers or funding
• Visually Discover things you weren’t looking for
• We discover errors in the data
• Analyze your (De-identified) data in your own way, with your
own favorite tools, with individual data element-level export
• SAS
• SPSS
• Stata
In order to access the Research Data Browser, you need to submit a request
through the ARF – Account Request Form system and complete an Account
Request Form (ARF).
The link to the ARF system is http://arf.ucsfmedicalcenter.org
Accessing the Research Data Browser
Giving Feedback to ARS
Your feedback is important to us.
Our goal is to:
• Make the Research Data Browser as useful as possible. Your feedback as to
how we can make the tool and underlying data more useful is appreciated.
• Let us know how we can improve the tool, data training and other related
materials
The Academic Research Systems (ARS) staff is here to assist you in using the tool,
validating your results and to help document any issues.
Please use the Report an Issue link located in the upper right-hand corner of
each page to report any issues or questions. You may also contact ARS at its-
arssupport@ucsf.edu

Contenu connexe

Tendances

Data Preparation and Visualization for Monitoring NCDs Mortality
Data Preparation and Visualization for Monitoring NCDs MortalityData Preparation and Visualization for Monitoring NCDs Mortality
Data Preparation and Visualization for Monitoring NCDs MortalityRamon Martinez
 
Simulation Modelling in Healthcare: Challenges and Trends
Simulation Modelling in Healthcare: Challenges and TrendsSimulation Modelling in Healthcare: Challenges and Trends
Simulation Modelling in Healthcare: Challenges and TrendsHCI Lab
 
lecture 11B
lecture 11Blecture 11B
lecture 11BCMDLMS
 
Medical Coding_Katalyst HLS
Medical Coding_Katalyst HLSMedical Coding_Katalyst HLS
Medical Coding_Katalyst HLSKatalyst HLS
 
Using IDEA to Create a Sampling Methodology
Using IDEA to Create a Sampling MethodologyUsing IDEA to Create a Sampling Methodology
Using IDEA to Create a Sampling MethodologyAuditWare Systems Ltd.
 
C606 the pan american health organizations health information and intelligenc...
C606 the pan american health organizations health information and intelligenc...C606 the pan american health organizations health information and intelligenc...
C606 the pan american health organizations health information and intelligenc...Ramon Martinez
 
Xcellerate® Monitoring
Xcellerate® Monitoring Xcellerate® Monitoring
Xcellerate® Monitoring Covance
 
Nursing Resources
Nursing ResourcesNursing Resources
Nursing Resourcesdoug suarez
 
HPD library resources for clinical affiliates
HPD library resources for clinical affiliates HPD library resources for clinical affiliates
HPD library resources for clinical affiliates jsarpy
 
Artificial Intelligence in Medicine Market Report Size 2021 ppt
Artificial Intelligence in Medicine Market Report Size 2021 pptArtificial Intelligence in Medicine Market Report Size 2021 ppt
Artificial Intelligence in Medicine Market Report Size 2021 pptShadab Pathan
 
10-3 Clinical Informatics System Selection & Implementation
10-3 Clinical Informatics System Selection & Implementation10-3 Clinical Informatics System Selection & Implementation
10-3 Clinical Informatics System Selection & ImplementationCorinn Pope
 
UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"
UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"
UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"CTSI at UCSF
 
Final version of_nursing276_cinahl_tut2
Final version of_nursing276_cinahl_tut2Final version of_nursing276_cinahl_tut2
Final version of_nursing276_cinahl_tut2Virginia Desouky
 
clinical data management
clinical data managementclinical data management
clinical data managementsopi_1234
 
Thoughts on Machine Learning and Artificial Intelligence
Thoughts on Machine Learning and Artificial IntelligenceThoughts on Machine Learning and Artificial Intelligence
Thoughts on Machine Learning and Artificial IntelligenceMaarten van Smeden
 
Epic presentation
Epic presentationEpic presentation
Epic presentationpshaw0682
 
Safti net overview ahrq stakeholders mtg oct 2011
Safti net overview ahrq stakeholders mtg oct 2011Safti net overview ahrq stakeholders mtg oct 2011
Safti net overview ahrq stakeholders mtg oct 2011Marion Sills
 
Machine learning in health data analytics and pharmacovigilance
Machine learning in health data analytics and pharmacovigilanceMachine learning in health data analytics and pharmacovigilance
Machine learning in health data analytics and pharmacovigilanceRevathi Boyina
 
Clinical Data Management
Clinical Data ManagementClinical Data Management
Clinical Data ManagementShray Jali
 

Tendances (20)

Data Preparation and Visualization for Monitoring NCDs Mortality
Data Preparation and Visualization for Monitoring NCDs MortalityData Preparation and Visualization for Monitoring NCDs Mortality
Data Preparation and Visualization for Monitoring NCDs Mortality
 
Simulation Modelling in Healthcare: Challenges and Trends
Simulation Modelling in Healthcare: Challenges and TrendsSimulation Modelling in Healthcare: Challenges and Trends
Simulation Modelling in Healthcare: Challenges and Trends
 
lecture 11B
lecture 11Blecture 11B
lecture 11B
 
Medical Coding_Katalyst HLS
Medical Coding_Katalyst HLSMedical Coding_Katalyst HLS
Medical Coding_Katalyst HLS
 
Using IDEA to Create a Sampling Methodology
Using IDEA to Create a Sampling MethodologyUsing IDEA to Create a Sampling Methodology
Using IDEA to Create a Sampling Methodology
 
C606 the pan american health organizations health information and intelligenc...
C606 the pan american health organizations health information and intelligenc...C606 the pan american health organizations health information and intelligenc...
C606 the pan american health organizations health information and intelligenc...
 
Xcellerate® Monitoring
Xcellerate® Monitoring Xcellerate® Monitoring
Xcellerate® Monitoring
 
Expert system mycin
Expert system   mycinExpert system   mycin
Expert system mycin
 
Nursing Resources
Nursing ResourcesNursing Resources
Nursing Resources
 
HPD library resources for clinical affiliates
HPD library resources for clinical affiliates HPD library resources for clinical affiliates
HPD library resources for clinical affiliates
 
Artificial Intelligence in Medicine Market Report Size 2021 ppt
Artificial Intelligence in Medicine Market Report Size 2021 pptArtificial Intelligence in Medicine Market Report Size 2021 ppt
Artificial Intelligence in Medicine Market Report Size 2021 ppt
 
10-3 Clinical Informatics System Selection & Implementation
10-3 Clinical Informatics System Selection & Implementation10-3 Clinical Informatics System Selection & Implementation
10-3 Clinical Informatics System Selection & Implementation
 
UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"
UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"
UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"
 
Final version of_nursing276_cinahl_tut2
Final version of_nursing276_cinahl_tut2Final version of_nursing276_cinahl_tut2
Final version of_nursing276_cinahl_tut2
 
clinical data management
clinical data managementclinical data management
clinical data management
 
Thoughts on Machine Learning and Artificial Intelligence
Thoughts on Machine Learning and Artificial IntelligenceThoughts on Machine Learning and Artificial Intelligence
Thoughts on Machine Learning and Artificial Intelligence
 
Epic presentation
Epic presentationEpic presentation
Epic presentation
 
Safti net overview ahrq stakeholders mtg oct 2011
Safti net overview ahrq stakeholders mtg oct 2011Safti net overview ahrq stakeholders mtg oct 2011
Safti net overview ahrq stakeholders mtg oct 2011
 
Machine learning in health data analytics and pharmacovigilance
Machine learning in health data analytics and pharmacovigilanceMachine learning in health data analytics and pharmacovigilance
Machine learning in health data analytics and pharmacovigilance
 
Clinical Data Management
Clinical Data ManagementClinical Data Management
Clinical Data Management
 

En vedette

CER 2016 Goldman CTSI CER Resources
CER 2016 Goldman CTSI CER ResourcesCER 2016 Goldman CTSI CER Resources
CER 2016 Goldman CTSI CER ResourcesCTSI at UCSF
 
CER 2016 Jacoby stakeholder engagement
CER 2016 Jacoby stakeholder engagementCER 2016 Jacoby stakeholder engagement
CER 2016 Jacoby stakeholder engagementCTSI at UCSF
 
UCSF Informatics Day 2014 - Mark Pletcher, "Making EHR Data Useful for the Le...
UCSF Informatics Day 2014 - Mark Pletcher, "Making EHR Data Useful for the Le...UCSF Informatics Day 2014 - Mark Pletcher, "Making EHR Data Useful for the Le...
UCSF Informatics Day 2014 - Mark Pletcher, "Making EHR Data Useful for the Le...CTSI at UCSF
 
Building Your Professional Network with LinkedIn
Building Your Professional Network with LinkedInBuilding Your Professional Network with LinkedIn
Building Your Professional Network with LinkedInCTSI at UCSF
 
Data Reproducibility in Preclinical Discovery, Is It a Real Problem? 09/17/15
Data Reproducibility in Preclinical Discovery, Is It a Real Problem? 09/17/15Data Reproducibility in Preclinical Discovery, Is It a Real Problem? 09/17/15
Data Reproducibility in Preclinical Discovery, Is It a Real Problem? 09/17/15CTSI at UCSF
 
CER 2016 Hernandez patient engagement
CER 2016 Hernandez patient engagementCER 2016 Hernandez patient engagement
CER 2016 Hernandez patient engagementCTSI at UCSF
 
CER 2016 Dohan EQUIP
CER 2016 Dohan EQUIPCER 2016 Dohan EQUIP
CER 2016 Dohan EQUIPCTSI at UCSF
 
How to Harness the Power of Google Analytics, Email Marketing & Vanity to Inc...
How to Harness the Power of Google Analytics, Email Marketing & Vanity to Inc...How to Harness the Power of Google Analytics, Email Marketing & Vanity to Inc...
How to Harness the Power of Google Analytics, Email Marketing & Vanity to Inc...CTSI at UCSF
 
CER 2016 Nguyen ctsi collaborative research
CER 2016 Nguyen ctsi collaborative researchCER 2016 Nguyen ctsi collaborative research
CER 2016 Nguyen ctsi collaborative researchCTSI at UCSF
 
UCSF Informatics Day 2014 - Ida Sim, "Informatics Technologies: From a Data-C...
UCSF Informatics Day 2014 - Ida Sim, "Informatics Technologies: From a Data-C...UCSF Informatics Day 2014 - Ida Sim, "Informatics Technologies: From a Data-C...
UCSF Informatics Day 2014 - Ida Sim, "Informatics Technologies: From a Data-C...CTSI at UCSF
 
CER 2016 Goldman Intro
CER 2016 Goldman IntroCER 2016 Goldman Intro
CER 2016 Goldman IntroCTSI at UCSF
 
UCSF Informatics Day 2014 - Elizabeth St. Lezin, "Blood Transfusion Research ...
UCSF Informatics Day 2014 - Elizabeth St. Lezin, "Blood Transfusion Research ...UCSF Informatics Day 2014 - Elizabeth St. Lezin, "Blood Transfusion Research ...
UCSF Informatics Day 2014 - Elizabeth St. Lezin, "Blood Transfusion Research ...CTSI at UCSF
 
CER 2016 Srivastava
CER 2016 Srivastava CER 2016 Srivastava
CER 2016 Srivastava CTSI at UCSF
 
CER 2016 Phillips cer symposium pcori 2016 from 012716
CER 2016 Phillips cer symposium pcori 2016 from 012716CER 2016 Phillips cer symposium pcori 2016 from 012716
CER 2016 Phillips cer symposium pcori 2016 from 012716CTSI at UCSF
 
VIVO 2014: Google Analytics, Email Marketing & Vanity to Increase User Engage...
VIVO 2014: Google Analytics, Email Marketing & Vanity to Increase User Engage...VIVO 2014: Google Analytics, Email Marketing & Vanity to Increase User Engage...
VIVO 2014: Google Analytics, Email Marketing & Vanity to Increase User Engage...CTSI at UCSF
 
CER 2016 Trontell pcori cer presentation 2016 02 02 final
CER 2016 Trontell pcori cer presentation 2016 02 02 finalCER 2016 Trontell pcori cer presentation 2016 02 02 final
CER 2016 Trontell pcori cer presentation 2016 02 02 finalCTSI at UCSF
 
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"CTSI at UCSF
 
UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"
UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"
UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"CTSI at UCSF
 
UCSF Informatics Day 2014 - Lindsey Watt Alami, "Study Management throughout ...
UCSF Informatics Day 2014 - Lindsey Watt Alami, "Study Management throughout ...UCSF Informatics Day 2014 - Lindsey Watt Alami, "Study Management throughout ...
UCSF Informatics Day 2014 - Lindsey Watt Alami, "Study Management throughout ...CTSI at UCSF
 

En vedette (19)

CER 2016 Goldman CTSI CER Resources
CER 2016 Goldman CTSI CER ResourcesCER 2016 Goldman CTSI CER Resources
CER 2016 Goldman CTSI CER Resources
 
CER 2016 Jacoby stakeholder engagement
CER 2016 Jacoby stakeholder engagementCER 2016 Jacoby stakeholder engagement
CER 2016 Jacoby stakeholder engagement
 
UCSF Informatics Day 2014 - Mark Pletcher, "Making EHR Data Useful for the Le...
UCSF Informatics Day 2014 - Mark Pletcher, "Making EHR Data Useful for the Le...UCSF Informatics Day 2014 - Mark Pletcher, "Making EHR Data Useful for the Le...
UCSF Informatics Day 2014 - Mark Pletcher, "Making EHR Data Useful for the Le...
 
Building Your Professional Network with LinkedIn
Building Your Professional Network with LinkedInBuilding Your Professional Network with LinkedIn
Building Your Professional Network with LinkedIn
 
Data Reproducibility in Preclinical Discovery, Is It a Real Problem? 09/17/15
Data Reproducibility in Preclinical Discovery, Is It a Real Problem? 09/17/15Data Reproducibility in Preclinical Discovery, Is It a Real Problem? 09/17/15
Data Reproducibility in Preclinical Discovery, Is It a Real Problem? 09/17/15
 
CER 2016 Hernandez patient engagement
CER 2016 Hernandez patient engagementCER 2016 Hernandez patient engagement
CER 2016 Hernandez patient engagement
 
CER 2016 Dohan EQUIP
CER 2016 Dohan EQUIPCER 2016 Dohan EQUIP
CER 2016 Dohan EQUIP
 
How to Harness the Power of Google Analytics, Email Marketing & Vanity to Inc...
How to Harness the Power of Google Analytics, Email Marketing & Vanity to Inc...How to Harness the Power of Google Analytics, Email Marketing & Vanity to Inc...
How to Harness the Power of Google Analytics, Email Marketing & Vanity to Inc...
 
CER 2016 Nguyen ctsi collaborative research
CER 2016 Nguyen ctsi collaborative researchCER 2016 Nguyen ctsi collaborative research
CER 2016 Nguyen ctsi collaborative research
 
UCSF Informatics Day 2014 - Ida Sim, "Informatics Technologies: From a Data-C...
UCSF Informatics Day 2014 - Ida Sim, "Informatics Technologies: From a Data-C...UCSF Informatics Day 2014 - Ida Sim, "Informatics Technologies: From a Data-C...
UCSF Informatics Day 2014 - Ida Sim, "Informatics Technologies: From a Data-C...
 
CER 2016 Goldman Intro
CER 2016 Goldman IntroCER 2016 Goldman Intro
CER 2016 Goldman Intro
 
UCSF Informatics Day 2014 - Elizabeth St. Lezin, "Blood Transfusion Research ...
UCSF Informatics Day 2014 - Elizabeth St. Lezin, "Blood Transfusion Research ...UCSF Informatics Day 2014 - Elizabeth St. Lezin, "Blood Transfusion Research ...
UCSF Informatics Day 2014 - Elizabeth St. Lezin, "Blood Transfusion Research ...
 
CER 2016 Srivastava
CER 2016 Srivastava CER 2016 Srivastava
CER 2016 Srivastava
 
CER 2016 Phillips cer symposium pcori 2016 from 012716
CER 2016 Phillips cer symposium pcori 2016 from 012716CER 2016 Phillips cer symposium pcori 2016 from 012716
CER 2016 Phillips cer symposium pcori 2016 from 012716
 
VIVO 2014: Google Analytics, Email Marketing & Vanity to Increase User Engage...
VIVO 2014: Google Analytics, Email Marketing & Vanity to Increase User Engage...VIVO 2014: Google Analytics, Email Marketing & Vanity to Increase User Engage...
VIVO 2014: Google Analytics, Email Marketing & Vanity to Increase User Engage...
 
CER 2016 Trontell pcori cer presentation 2016 02 02 final
CER 2016 Trontell pcori cer presentation 2016 02 02 finalCER 2016 Trontell pcori cer presentation 2016 02 02 final
CER 2016 Trontell pcori cer presentation 2016 02 02 final
 
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"
 
UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"
UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"
UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"
 
UCSF Informatics Day 2014 - Lindsey Watt Alami, "Study Management throughout ...
UCSF Informatics Day 2014 - Lindsey Watt Alami, "Study Management throughout ...UCSF Informatics Day 2014 - Lindsey Watt Alami, "Study Management throughout ...
UCSF Informatics Day 2014 - Lindsey Watt Alami, "Study Management throughout ...
 

Similaire à UCSF Informatics Day 2014 - Dana Ludwig, "Research Data Browser"

Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...
Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...
Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...Wellbe
 
4 Statistical Software.pptx
4 Statistical Software.pptx4 Statistical Software.pptx
4 Statistical Software.pptxkaleabtegegne
 
Dk net webinar tutorial pen
Dk net webinar tutorial penDk net webinar tutorial pen
Dk net webinar tutorial penMaryann Martone
 
CoArtha Technolsolutions IT for Meaningful Use
CoArtha Technolsolutions IT for Meaningful UseCoArtha Technolsolutions IT for Meaningful Use
CoArtha Technolsolutions IT for Meaningful UseMapRecruit.com
 
Project ECHO QI: Communicating and Advocating Using Data June 29, 2016
Project ECHO QI: Communicating and Advocating Using Data June 29, 2016Project ECHO QI: Communicating and Advocating Using Data June 29, 2016
Project ECHO QI: Communicating and Advocating Using Data June 29, 2016CHC Connecticut
 
Advancing Team-Based Care:Data Driven Dashboards to Support Team Based Care
Advancing Team-Based Care:Data Driven Dashboards to Support Team Based Care Advancing Team-Based Care:Data Driven Dashboards to Support Team Based Care
Advancing Team-Based Care:Data Driven Dashboards to Support Team Based Care CHC Connecticut
 
Library resources for clinical faculty
Library resources for clinical facultyLibrary resources for clinical faculty
Library resources for clinical facultyKristin Kroger
 
How BrackenData Leverages Data on Over 250,000 Clinical Trials
How BrackenData Leverages Data on Over 250,000 Clinical TrialsHow BrackenData Leverages Data on Over 250,000 Clinical Trials
How BrackenData Leverages Data on Over 250,000 Clinical TrialsBracken
 
Sharing and standards christopher hart - clinical innovation and partnering...
Sharing and standards   christopher hart - clinical innovation and partnering...Sharing and standards   christopher hart - clinical innovation and partnering...
Sharing and standards christopher hart - clinical innovation and partnering...Christopher Hart
 
2010 E-Library Resources GR June 29 2010
2010 E-Library Resources GR June 29 20102010 E-Library Resources GR June 29 2010
2010 E-Library Resources GR June 29 2010Mary Jo Devereaux, MLS
 
Steffen Frederiksen: DATA, DITA, DOCX
Steffen Frederiksen: DATA, DITA, DOCXSteffen Frederiksen: DATA, DITA, DOCX
Steffen Frederiksen: DATA, DITA, DOCXJack Molisani
 
Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...
Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...
Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...Data Con LA
 
Library resources for clinical faculty
Library resources for clinical facultyLibrary resources for clinical faculty
Library resources for clinical facultyKristin Kroger
 
Using the Electronic Medical Record to Drive Improved Patient Outcomes
Using the Electronic Medical Record to Drive Improved Patient Outcomes Using the Electronic Medical Record to Drive Improved Patient Outcomes
Using the Electronic Medical Record to Drive Improved Patient Outcomes Group Health Cooperative
 
The OneSource Initiative: An Approach to Structured Sourcing of Key Clinical ...
The OneSource Initiative: An Approach to Structured Sourcing of Key Clinical ...The OneSource Initiative: An Approach to Structured Sourcing of Key Clinical ...
The OneSource Initiative: An Approach to Structured Sourcing of Key Clinical ...Mike Hogarth, MD, FACMI, FACP
 
Powering Medical Research With Data: The Research Analytics Adoption Model
Powering Medical Research With Data: The Research Analytics Adoption ModelPowering Medical Research With Data: The Research Analytics Adoption Model
Powering Medical Research With Data: The Research Analytics Adoption ModelHealth Catalyst
 

Similaire à UCSF Informatics Day 2014 - Dana Ludwig, "Research Data Browser" (20)

Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...
Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...
Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...
 
4 Statistical Software.pptx
4 Statistical Software.pptx4 Statistical Software.pptx
4 Statistical Software.pptx
 
EMR
EMREMR
EMR
 
Search for evidence
Search for evidenceSearch for evidence
Search for evidence
 
Dk net webinar tutorial pen
Dk net webinar tutorial penDk net webinar tutorial pen
Dk net webinar tutorial pen
 
Query basics
Query basicsQuery basics
Query basics
 
CoArtha Technolsolutions IT for Meaningful Use
CoArtha Technolsolutions IT for Meaningful UseCoArtha Technolsolutions IT for Meaningful Use
CoArtha Technolsolutions IT for Meaningful Use
 
Project ECHO QI: Communicating and Advocating Using Data June 29, 2016
Project ECHO QI: Communicating and Advocating Using Data June 29, 2016Project ECHO QI: Communicating and Advocating Using Data June 29, 2016
Project ECHO QI: Communicating and Advocating Using Data June 29, 2016
 
Advancing Team-Based Care:Data Driven Dashboards to Support Team Based Care
Advancing Team-Based Care:Data Driven Dashboards to Support Team Based Care Advancing Team-Based Care:Data Driven Dashboards to Support Team Based Care
Advancing Team-Based Care:Data Driven Dashboards to Support Team Based Care
 
Library resources for clinical faculty
Library resources for clinical facultyLibrary resources for clinical faculty
Library resources for clinical faculty
 
How BrackenData Leverages Data on Over 250,000 Clinical Trials
How BrackenData Leverages Data on Over 250,000 Clinical TrialsHow BrackenData Leverages Data on Over 250,000 Clinical Trials
How BrackenData Leverages Data on Over 250,000 Clinical Trials
 
Sharing and standards christopher hart - clinical innovation and partnering...
Sharing and standards   christopher hart - clinical innovation and partnering...Sharing and standards   christopher hart - clinical innovation and partnering...
Sharing and standards christopher hart - clinical innovation and partnering...
 
2010 E-Library Resources GR June 29 2010
2010 E-Library Resources GR June 29 20102010 E-Library Resources GR June 29 2010
2010 E-Library Resources GR June 29 2010
 
Steffen Frederiksen: DATA, DITA, DOCX
Steffen Frederiksen: DATA, DITA, DOCXSteffen Frederiksen: DATA, DITA, DOCX
Steffen Frederiksen: DATA, DITA, DOCX
 
Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...
Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...
Data Con LA 2019 - Best Practices for Prototyping Machine Learning Models for...
 
Library resources for clinical faculty
Library resources for clinical facultyLibrary resources for clinical faculty
Library resources for clinical faculty
 
Epoch Research Institute : Introduction to CR
Epoch Research Institute : Introduction to CREpoch Research Institute : Introduction to CR
Epoch Research Institute : Introduction to CR
 
Using the Electronic Medical Record to Drive Improved Patient Outcomes
Using the Electronic Medical Record to Drive Improved Patient Outcomes Using the Electronic Medical Record to Drive Improved Patient Outcomes
Using the Electronic Medical Record to Drive Improved Patient Outcomes
 
The OneSource Initiative: An Approach to Structured Sourcing of Key Clinical ...
The OneSource Initiative: An Approach to Structured Sourcing of Key Clinical ...The OneSource Initiative: An Approach to Structured Sourcing of Key Clinical ...
The OneSource Initiative: An Approach to Structured Sourcing of Key Clinical ...
 
Powering Medical Research With Data: The Research Analytics Adoption Model
Powering Medical Research With Data: The Research Analytics Adoption ModelPowering Medical Research With Data: The Research Analytics Adoption Model
Powering Medical Research With Data: The Research Analytics Adoption Model
 

Plus de CTSI at UCSF

AMIA Joint Summits 2017: Building Research Data Mart from UCSF OMOP Database ...
AMIA Joint Summits 2017: Building Research Data Mart from UCSF OMOP Database ...AMIA Joint Summits 2017: Building Research Data Mart from UCSF OMOP Database ...
AMIA Joint Summits 2017: Building Research Data Mart from UCSF OMOP Database ...CTSI at UCSF
 
UCSF Informatics Day 2014 - Robert Nussbaum, "The Genomic Medicine Initiative...
UCSF Informatics Day 2014 - Robert Nussbaum, "The Genomic Medicine Initiative...UCSF Informatics Day 2014 - Robert Nussbaum, "The Genomic Medicine Initiative...
UCSF Informatics Day 2014 - Robert Nussbaum, "The Genomic Medicine Initiative...CTSI at UCSF
 
UCSF Informatics Day 2014 - Sayan Chatterjee, "APeX Reporting"
UCSF Informatics Day 2014 - Sayan Chatterjee, "APeX Reporting"UCSF Informatics Day 2014 - Sayan Chatterjee, "APeX Reporting"
UCSF Informatics Day 2014 - Sayan Chatterjee, "APeX Reporting"CTSI at UCSF
 
UCSF Informatics Day 2014 - Sorena Nadaf, "Translational Informatics OnCore C...
UCSF Informatics Day 2014 - Sorena Nadaf, "Translational Informatics OnCore C...UCSF Informatics Day 2014 - Sorena Nadaf, "Translational Informatics OnCore C...
UCSF Informatics Day 2014 - Sorena Nadaf, "Translational Informatics OnCore C...CTSI at UCSF
 
UCSF Informatics Day 2014 - Sam Hawgood, "Informatics at UCSF"
UCSF Informatics Day 2014 - Sam Hawgood, "Informatics at UCSF"UCSF Informatics Day 2014 - Sam Hawgood, "Informatics at UCSF"
UCSF Informatics Day 2014 - Sam Hawgood, "Informatics at UCSF"CTSI at UCSF
 
UCSF Informatics Day 2014 - Sue Dubman and Alexandra Solomon, "Innovative inf...
UCSF Informatics Day 2014 - Sue Dubman and Alexandra Solomon, "Innovative inf...UCSF Informatics Day 2014 - Sue Dubman and Alexandra Solomon, "Innovative inf...
UCSF Informatics Day 2014 - Sue Dubman and Alexandra Solomon, "Innovative inf...CTSI at UCSF
 
UCSF Informatics Day 2014 - Sayan Chatterjee and Jennifer Clarke, "APeX Sense...
UCSF Informatics Day 2014 - Sayan Chatterjee and Jennifer Clarke, "APeX Sense...UCSF Informatics Day 2014 - Sayan Chatterjee and Jennifer Clarke, "APeX Sense...
UCSF Informatics Day 2014 - Sayan Chatterjee and Jennifer Clarke, "APeX Sense...CTSI at UCSF
 
UCSF Informatics Day 2014 - Wylie Burke, "Bioethical Issues in Genomics and E...
UCSF Informatics Day 2014 - Wylie Burke, "Bioethical Issues in Genomics and E...UCSF Informatics Day 2014 - Wylie Burke, "Bioethical Issues in Genomics and E...
UCSF Informatics Day 2014 - Wylie Burke, "Bioethical Issues in Genomics and E...CTSI at UCSF
 
UCSF Informatics Day 2014 - Michael Blum, "Digital Health"
UCSF Informatics Day 2014 - Michael Blum, "Digital Health"UCSF Informatics Day 2014 - Michael Blum, "Digital Health"
UCSF Informatics Day 2014 - Michael Blum, "Digital Health"CTSI at UCSF
 
UCSF Informatics Day 2014 - Doug Berman, "A Brief Tour of UCSF’s Clinical Dat...
UCSF Informatics Day 2014 - Doug Berman, "A Brief Tour of UCSF’s Clinical Dat...UCSF Informatics Day 2014 - Doug Berman, "A Brief Tour of UCSF’s Clinical Dat...
UCSF Informatics Day 2014 - Doug Berman, "A Brief Tour of UCSF’s Clinical Dat...CTSI at UCSF
 

Plus de CTSI at UCSF (10)

AMIA Joint Summits 2017: Building Research Data Mart from UCSF OMOP Database ...
AMIA Joint Summits 2017: Building Research Data Mart from UCSF OMOP Database ...AMIA Joint Summits 2017: Building Research Data Mart from UCSF OMOP Database ...
AMIA Joint Summits 2017: Building Research Data Mart from UCSF OMOP Database ...
 
UCSF Informatics Day 2014 - Robert Nussbaum, "The Genomic Medicine Initiative...
UCSF Informatics Day 2014 - Robert Nussbaum, "The Genomic Medicine Initiative...UCSF Informatics Day 2014 - Robert Nussbaum, "The Genomic Medicine Initiative...
UCSF Informatics Day 2014 - Robert Nussbaum, "The Genomic Medicine Initiative...
 
UCSF Informatics Day 2014 - Sayan Chatterjee, "APeX Reporting"
UCSF Informatics Day 2014 - Sayan Chatterjee, "APeX Reporting"UCSF Informatics Day 2014 - Sayan Chatterjee, "APeX Reporting"
UCSF Informatics Day 2014 - Sayan Chatterjee, "APeX Reporting"
 
UCSF Informatics Day 2014 - Sorena Nadaf, "Translational Informatics OnCore C...
UCSF Informatics Day 2014 - Sorena Nadaf, "Translational Informatics OnCore C...UCSF Informatics Day 2014 - Sorena Nadaf, "Translational Informatics OnCore C...
UCSF Informatics Day 2014 - Sorena Nadaf, "Translational Informatics OnCore C...
 
UCSF Informatics Day 2014 - Sam Hawgood, "Informatics at UCSF"
UCSF Informatics Day 2014 - Sam Hawgood, "Informatics at UCSF"UCSF Informatics Day 2014 - Sam Hawgood, "Informatics at UCSF"
UCSF Informatics Day 2014 - Sam Hawgood, "Informatics at UCSF"
 
UCSF Informatics Day 2014 - Sue Dubman and Alexandra Solomon, "Innovative inf...
UCSF Informatics Day 2014 - Sue Dubman and Alexandra Solomon, "Innovative inf...UCSF Informatics Day 2014 - Sue Dubman and Alexandra Solomon, "Innovative inf...
UCSF Informatics Day 2014 - Sue Dubman and Alexandra Solomon, "Innovative inf...
 
UCSF Informatics Day 2014 - Sayan Chatterjee and Jennifer Clarke, "APeX Sense...
UCSF Informatics Day 2014 - Sayan Chatterjee and Jennifer Clarke, "APeX Sense...UCSF Informatics Day 2014 - Sayan Chatterjee and Jennifer Clarke, "APeX Sense...
UCSF Informatics Day 2014 - Sayan Chatterjee and Jennifer Clarke, "APeX Sense...
 
UCSF Informatics Day 2014 - Wylie Burke, "Bioethical Issues in Genomics and E...
UCSF Informatics Day 2014 - Wylie Burke, "Bioethical Issues in Genomics and E...UCSF Informatics Day 2014 - Wylie Burke, "Bioethical Issues in Genomics and E...
UCSF Informatics Day 2014 - Wylie Burke, "Bioethical Issues in Genomics and E...
 
UCSF Informatics Day 2014 - Michael Blum, "Digital Health"
UCSF Informatics Day 2014 - Michael Blum, "Digital Health"UCSF Informatics Day 2014 - Michael Blum, "Digital Health"
UCSF Informatics Day 2014 - Michael Blum, "Digital Health"
 
UCSF Informatics Day 2014 - Doug Berman, "A Brief Tour of UCSF’s Clinical Dat...
UCSF Informatics Day 2014 - Doug Berman, "A Brief Tour of UCSF’s Clinical Dat...UCSF Informatics Day 2014 - Doug Berman, "A Brief Tour of UCSF’s Clinical Dat...
UCSF Informatics Day 2014 - Doug Berman, "A Brief Tour of UCSF’s Clinical Dat...
 

Dernier

Pests of Blackgram, greengram, cowpea_Dr.UPR.pdf
Pests of Blackgram, greengram, cowpea_Dr.UPR.pdfPests of Blackgram, greengram, cowpea_Dr.UPR.pdf
Pests of Blackgram, greengram, cowpea_Dr.UPR.pdfPirithiRaju
 
Davis plaque method.pptx recombinant DNA technology
Davis plaque method.pptx recombinant DNA technologyDavis plaque method.pptx recombinant DNA technology
Davis plaque method.pptx recombinant DNA technologycaarthichand2003
 
Microteaching on terms used in filtration .Pharmaceutical Engineering
Microteaching on terms used in filtration .Pharmaceutical EngineeringMicroteaching on terms used in filtration .Pharmaceutical Engineering
Microteaching on terms used in filtration .Pharmaceutical EngineeringPrajakta Shinde
 
OECD bibliometric indicators: Selected highlights, April 2024
OECD bibliometric indicators: Selected highlights, April 2024OECD bibliometric indicators: Selected highlights, April 2024
OECD bibliometric indicators: Selected highlights, April 2024innovationoecd
 
Environmental Biotechnology Topic:- Microbial Biosensor
Environmental Biotechnology Topic:- Microbial BiosensorEnvironmental Biotechnology Topic:- Microbial Biosensor
Environmental Biotechnology Topic:- Microbial Biosensorsonawaneprad
 
Dubai Calls Girl Lisa O525547819 Lexi Call Girls In Dubai
Dubai Calls Girl Lisa O525547819 Lexi Call Girls In DubaiDubai Calls Girl Lisa O525547819 Lexi Call Girls In Dubai
Dubai Calls Girl Lisa O525547819 Lexi Call Girls In Dubaikojalkojal131
 
The dark energy paradox leads to a new structure of spacetime.pptx
The dark energy paradox leads to a new structure of spacetime.pptxThe dark energy paradox leads to a new structure of spacetime.pptx
The dark energy paradox leads to a new structure of spacetime.pptxEran Akiva Sinbar
 
GenBio2 - Lesson 1 - Introduction to Genetics.pptx
GenBio2 - Lesson 1 - Introduction to Genetics.pptxGenBio2 - Lesson 1 - Introduction to Genetics.pptx
GenBio2 - Lesson 1 - Introduction to Genetics.pptxBerniceCayabyab1
 
User Guide: Orion™ Weather Station (Columbia Weather Systems)
User Guide: Orion™ Weather Station (Columbia Weather Systems)User Guide: Orion™ Weather Station (Columbia Weather Systems)
User Guide: Orion™ Weather Station (Columbia Weather Systems)Columbia Weather Systems
 
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...lizamodels9
 
Harmful and Useful Microorganisms Presentation
Harmful and Useful Microorganisms PresentationHarmful and Useful Microorganisms Presentation
Harmful and Useful Microorganisms Presentationtahreemzahra82
 
Topic 9- General Principles of International Law.pptx
Topic 9- General Principles of International Law.pptxTopic 9- General Principles of International Law.pptx
Topic 9- General Principles of International Law.pptxJorenAcuavera1
 
RESPIRATORY ADAPTATIONS TO HYPOXIA IN HUMNAS.pptx
RESPIRATORY ADAPTATIONS TO HYPOXIA IN HUMNAS.pptxRESPIRATORY ADAPTATIONS TO HYPOXIA IN HUMNAS.pptx
RESPIRATORY ADAPTATIONS TO HYPOXIA IN HUMNAS.pptxFarihaAbdulRasheed
 
Speech, hearing, noise, intelligibility.pptx
Speech, hearing, noise, intelligibility.pptxSpeech, hearing, noise, intelligibility.pptx
Speech, hearing, noise, intelligibility.pptxpriyankatabhane
 
《Queensland毕业文凭-昆士兰大学毕业证成绩单》
《Queensland毕业文凭-昆士兰大学毕业证成绩单》《Queensland毕业文凭-昆士兰大学毕业证成绩单》
《Queensland毕业文凭-昆士兰大学毕业证成绩单》rnrncn29
 
Pests of safflower_Binomics_Identification_Dr.UPR.pdf
Pests of safflower_Binomics_Identification_Dr.UPR.pdfPests of safflower_Binomics_Identification_Dr.UPR.pdf
Pests of safflower_Binomics_Identification_Dr.UPR.pdfPirithiRaju
 
Pests of soyabean_Binomics_IdentificationDr.UPR.pdf
Pests of soyabean_Binomics_IdentificationDr.UPR.pdfPests of soyabean_Binomics_IdentificationDr.UPR.pdf
Pests of soyabean_Binomics_IdentificationDr.UPR.pdfPirithiRaju
 
Bioteknologi kelas 10 kumer smapsa .pptx
Bioteknologi kelas 10 kumer smapsa .pptxBioteknologi kelas 10 kumer smapsa .pptx
Bioteknologi kelas 10 kumer smapsa .pptx023NiWayanAnggiSriWa
 

Dernier (20)

Pests of Blackgram, greengram, cowpea_Dr.UPR.pdf
Pests of Blackgram, greengram, cowpea_Dr.UPR.pdfPests of Blackgram, greengram, cowpea_Dr.UPR.pdf
Pests of Blackgram, greengram, cowpea_Dr.UPR.pdf
 
Davis plaque method.pptx recombinant DNA technology
Davis plaque method.pptx recombinant DNA technologyDavis plaque method.pptx recombinant DNA technology
Davis plaque method.pptx recombinant DNA technology
 
Microteaching on terms used in filtration .Pharmaceutical Engineering
Microteaching on terms used in filtration .Pharmaceutical EngineeringMicroteaching on terms used in filtration .Pharmaceutical Engineering
Microteaching on terms used in filtration .Pharmaceutical Engineering
 
Hot Sexy call girls in Moti Nagar,🔝 9953056974 🔝 escort Service
Hot Sexy call girls in  Moti Nagar,🔝 9953056974 🔝 escort ServiceHot Sexy call girls in  Moti Nagar,🔝 9953056974 🔝 escort Service
Hot Sexy call girls in Moti Nagar,🔝 9953056974 🔝 escort Service
 
OECD bibliometric indicators: Selected highlights, April 2024
OECD bibliometric indicators: Selected highlights, April 2024OECD bibliometric indicators: Selected highlights, April 2024
OECD bibliometric indicators: Selected highlights, April 2024
 
Environmental Biotechnology Topic:- Microbial Biosensor
Environmental Biotechnology Topic:- Microbial BiosensorEnvironmental Biotechnology Topic:- Microbial Biosensor
Environmental Biotechnology Topic:- Microbial Biosensor
 
Dubai Calls Girl Lisa O525547819 Lexi Call Girls In Dubai
Dubai Calls Girl Lisa O525547819 Lexi Call Girls In DubaiDubai Calls Girl Lisa O525547819 Lexi Call Girls In Dubai
Dubai Calls Girl Lisa O525547819 Lexi Call Girls In Dubai
 
The dark energy paradox leads to a new structure of spacetime.pptx
The dark energy paradox leads to a new structure of spacetime.pptxThe dark energy paradox leads to a new structure of spacetime.pptx
The dark energy paradox leads to a new structure of spacetime.pptx
 
Volatile Oils Pharmacognosy And Phytochemistry -I
Volatile Oils Pharmacognosy And Phytochemistry -IVolatile Oils Pharmacognosy And Phytochemistry -I
Volatile Oils Pharmacognosy And Phytochemistry -I
 
GenBio2 - Lesson 1 - Introduction to Genetics.pptx
GenBio2 - Lesson 1 - Introduction to Genetics.pptxGenBio2 - Lesson 1 - Introduction to Genetics.pptx
GenBio2 - Lesson 1 - Introduction to Genetics.pptx
 
User Guide: Orion™ Weather Station (Columbia Weather Systems)
User Guide: Orion™ Weather Station (Columbia Weather Systems)User Guide: Orion™ Weather Station (Columbia Weather Systems)
User Guide: Orion™ Weather Station (Columbia Weather Systems)
 
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
Best Call Girls In Sector 29 Gurgaon❤️8860477959 EscorTs Service In 24/7 Delh...
 
Harmful and Useful Microorganisms Presentation
Harmful and Useful Microorganisms PresentationHarmful and Useful Microorganisms Presentation
Harmful and Useful Microorganisms Presentation
 
Topic 9- General Principles of International Law.pptx
Topic 9- General Principles of International Law.pptxTopic 9- General Principles of International Law.pptx
Topic 9- General Principles of International Law.pptx
 
RESPIRATORY ADAPTATIONS TO HYPOXIA IN HUMNAS.pptx
RESPIRATORY ADAPTATIONS TO HYPOXIA IN HUMNAS.pptxRESPIRATORY ADAPTATIONS TO HYPOXIA IN HUMNAS.pptx
RESPIRATORY ADAPTATIONS TO HYPOXIA IN HUMNAS.pptx
 
Speech, hearing, noise, intelligibility.pptx
Speech, hearing, noise, intelligibility.pptxSpeech, hearing, noise, intelligibility.pptx
Speech, hearing, noise, intelligibility.pptx
 
《Queensland毕业文凭-昆士兰大学毕业证成绩单》
《Queensland毕业文凭-昆士兰大学毕业证成绩单》《Queensland毕业文凭-昆士兰大学毕业证成绩单》
《Queensland毕业文凭-昆士兰大学毕业证成绩单》
 
Pests of safflower_Binomics_Identification_Dr.UPR.pdf
Pests of safflower_Binomics_Identification_Dr.UPR.pdfPests of safflower_Binomics_Identification_Dr.UPR.pdf
Pests of safflower_Binomics_Identification_Dr.UPR.pdf
 
Pests of soyabean_Binomics_IdentificationDr.UPR.pdf
Pests of soyabean_Binomics_IdentificationDr.UPR.pdfPests of soyabean_Binomics_IdentificationDr.UPR.pdf
Pests of soyabean_Binomics_IdentificationDr.UPR.pdf
 
Bioteknologi kelas 10 kumer smapsa .pptx
Bioteknologi kelas 10 kumer smapsa .pptxBioteknologi kelas 10 kumer smapsa .pptx
Bioteknologi kelas 10 kumer smapsa .pptx
 

UCSF Informatics Day 2014 - Dana Ludwig, "Research Data Browser"

  • 1. Research Data Browser UCSF ITS - Academic Research Systems Research Data Browser
  • 2. The goal is to accelerate the clinical scientific discovery process for UCSF investigators by enabling: • Accelerated hypothesis generation to a wider audience, prior to CHR approval, using de-identified data • Rapid Query – all data in memory, not disk • Visual Profiling of selected patients • Export to Excel or Flat File Overall Goal of Research Data Browser
  • 3. When you access the Research Data Browser, the Select View is the first page displayed. There are two separate views of the same data: Patient View and Encounter View. Select View Page Data as of: – displays the production date. Most times this field is two days behind production.
  • 4. Patient View – All Selections Tab The “All Selections” tab displays all variables that may be used for selecting patients
  • 5. Patient View – All Selections Tab • Query for a Sex = Female by clicking the drop-down box for “Sex” and selecting “Female”
  • 6. Patient View – All Selections Tab • The Total Patients matching your query conditions is always displayed • The “Current Selection” window summarizes what conditions you have already placed in your current query • You can use the Eraser icon to remove conditions • You can use “Clear Selections” to clear the query and start again • The variables that you have used in your selection will be displayed in Green
  • 7. Patient View – All Selections Tab • For Diagnosis Name, type “Diabetes Mellitus” (quotes included) and it will select all diagnoses that contain “Diabetes” and “Mellitus” in the same name • You can accept the whole list, or click-and-drag the diagnosis names you want
  • 8. Patient View – All Selections Tab • For selecting on lab values, you first select the lab test(s) such as “Creatinine” • Then select a value range such as “>3”. Using the “>” or “<“ symbol limits resulting values to only numeric, and only within the requested range
  • 9. Patient View – All Selections Tab • Use the “?” Icon to show a definition of each variable in the selection box
  • 10. Add Bookmark Make a Bookmark of the Current Selection. In the future, Bookmark applies query to the new dataset
  • 11. Patient View Home Tab The first tab of the Patient View profiles your currently selected patients by age, diagnosis, discharge disposition and ordered medications
  • 12. Using a Graph to Change Search Criteria 1. Click on the Skilled Nursing Homes (the green pie piece) on the Top 5 Discharge Disposition graph. 2. The Top 5 Discharge Disposition graph now only displays Skilled Nursing Homes information. NOTE: As you select your criteria on one tab, it carries over to all the other tabs.
  • 13. Demographics Tab Profile Selected Patients by Demographics Select the Demographics Tab Note: All Tabs reflect the same Current Selection Use the Toggle button to switch between Age and Age Group
  • 19. Exploration Tab – Custom Visualization and Export
  • 20. Exploration Tab – Bar Chart of Creatinines > 3
  • 21. Exploration Tab – Tabulate all Creatinines > 3
  • 22. Exploration Tab – Export all Creatinines > 3
  • 23. HIPAA De-Identified Data • Data has been de-identified per HIPPA Safe-Harbor definition • Patient ID, Encounter ID and other identifiers have been replaced by randomly generated numbers • Dates have a random offset of up to a year in the past and each patient has the same offset for all dates • Ages over 90 are shown as 90 • De-identified data is sensitive information. User’s agree to: • Not attempt to re-identify the data • Not share data with unauthorized individuals
  • 24. Limitations of the Research Data Browser • Only data from encounters after June 1, 2012 are included (APeX go-live date) • Data is typically one day old – see the Data as of: field • Procedures and Med Orders are limited to orders manually entered in APeX by a provider (ORDER_METRICS):  No child orders  No orders created by an interface  No pending orders  No historical orders  No cabinet overrides
  • 25. Why We Are Excited About RDB • Unleash the creativity of world-class clinical and informatics scientists • Quickly ask questions any time of day, without CHR approval or programmers or funding • Visually Discover things you weren’t looking for • We discover errors in the data • Analyze your (De-identified) data in your own way, with your own favorite tools, with individual data element-level export • SAS • SPSS • Stata
  • 26. In order to access the Research Data Browser, you need to submit a request through the ARF – Account Request Form system and complete an Account Request Form (ARF). The link to the ARF system is http://arf.ucsfmedicalcenter.org Accessing the Research Data Browser
  • 27. Giving Feedback to ARS Your feedback is important to us. Our goal is to: • Make the Research Data Browser as useful as possible. Your feedback as to how we can make the tool and underlying data more useful is appreciated. • Let us know how we can improve the tool, data training and other related materials The Academic Research Systems (ARS) staff is here to assist you in using the tool, validating your results and to help document any issues. Please use the Report an Issue link located in the upper right-hand corner of each page to report any issues or questions. You may also contact ARS at its- arssupport@ucsf.edu