The goal of seminar is to detect when the distributor’s sensitive data has been leaked by agents, and show the probability for identifying the agent that leaked the data. We study unobtrusive techniques for detecting leakage of a set of objects or records.
My keynote presentation on investing in big data application companies. The presentation was made in December at the Brand Innovators conference in NY. (http://www.brandinnovatorsbigdata.com/)
The goal of seminar is to detect when the distributor’s sensitive data has been leaked by agents, and show the probability for identifying the agent that leaked the data. We study unobtrusive techniques for detecting leakage of a set of objects or records.
My keynote presentation on investing in big data application companies. The presentation was made in December at the Brand Innovators conference in NY. (http://www.brandinnovatorsbigdata.com/)
Health Data Exchange:. Still a Pipe Dream? A Presentation from 2009David Lee Scher, MD
This presentation discussing interoperability was given at the European Society of Cardiology in 2009.This remains an important topic for healthcare worldwide. Addendum: All names shown are fictitious and not real patients.
Organizations must onboard new data sources more frequently and quickly. In this presentation, you will learn about practices that rapidly deliver business value, while shrinking time to business value from months to days.
Business decisions are becoming increasingly dependent on analyzing an ever-greater volume of data coming from a growing number of sources. Mobile technology is providing immediate access to data whenever and wherever it is needed. Users, customers, and business partners are waiting for answers, and the organization must reduce the time required to collect, understand, and analyze the data needed to provide those answers. Modern enterprises need to increase the agility, flexibility, and speed with which they can analyze a growing volume, variety, and velocity of data.
This presentation discusses a method for rapid data integration and curation:
- Techniques for light data integration of new data with existing data assets
- Framework for data quality management
- Refining data integration through evolutionary modeling
- Managing curation processes
- Validating business value
Timely delivery of new data assets allows users to begin asking questions earlier and getting answers more quickly, allowing the organization to uncover the new insights that drive lasting business benefits.
Standard Safeguarding Dataset - overview for CSCDUG.pptxRocioMendez59
13 July, 2023 - CSCDUG Online Event
Presenting the Sector-led Standard Safeguarding Dataset
Colleagues from Data to Insight, the LA-led service for children’s safeguarding data professionals, are delivering a DfE-funded project in partnership with LAs to define a new “standard safeguarding dataset” which all LAs will be able to produce from their safeguarding information systems.
At this session, they shared what they’ve learned so far from user research with LA colleagues and discussed their early thinking about what a better standard dataset might look like. Participants shared their own thoughts about how to improve these systems and processes.
Presenters
Alistair Herbert
Alistair is the lead officer for Data to Insight, the LA-led service for children’s safeguarding data professionals. With a career focused on local authority children’s services data work, he knows about safeguarding data, information systems, and cross-organisation collaboration.
John Foster
John is a Data Manager for Data to Insight. He has supported a range of children’s services data work, most recently at Shropshire Council. He led Data to Insight’s project to introduce the first national benchmarking dataset for Early Help, and is the user research lead for Data to Insight’s Standard Safeguarding Dataset project.
Rob Harrison and Joe Cornford-Hutchings
Rob and Joe are new Data Managers joining Data to Insight from the private and public sector respectively. They bring between them a wealth of experience and technical expertise, and will be working together to support design and implementation of the new Standard Safeguarding Dataset through 2023-24.
The latest changes from CMS regarding Meaningful Use Stage 3 , CCDA and reporting measures. We discuss the effort required, estimates in terms of cost and timelines.
Despite massive investment in both people and technology, health systems are still struggling to maximize the value of their greatest asset: their data. Delivering high-quality, valuable insight from data and pushing those insights to the frontline healthcare professionals remains challenging and expensive. According to a recent survey conducted by HealthLeaders Media, health systems are hiring more analytics staff than almost any other role in health care. We know there’s an alternative to the massive hiring of analytics staff, a better way to dramatically increase the efficiency of your existing resources and provide an ROI that grows over time. The better way is the Rapid Response Analytics Solution.
Rapid Response Analytics Solution (RRA Solution) consists of two elements: curated, modular data called DOS™ Marts and Population Builder, a powerful self-service tool that lets any type of user, from physician executive to frontline nurses and population health teams explore their data and quickly build and share populations without needing to know how to write SQL and data science code. RRA Solution increases an analytics team’s productivity by up to 10x and reduces its time to develop analytics by as much as 90 percent. Analysts can spend more time focusing on key strategic analysis and less time on repetitive tasks that can lead to inconsistent results and a backlog of requests.
Learning Objectives:
- Discover how RRA Solution allows you to take components and customize them to quickly tailor and deliver meaningful insights.
- Learn about DOS™ Marts and Population Builder and how they drive consistency and efficiency, without needing to know SQL and data science coding.
- Understand how to use RRA Solution to increase the value of your analytics team and get them operating at the top of their function.
View this webinar and learn how RRA Solution can help you achieve a 10x increase in productivity and reduce your time to develop new analytics reports by more than 90 percent.
Microsoft: A Waking Giant In Healthcare Analytics and Big DataHealth Catalyst
In 2005, Northwestern Memorial Healthcare embarked upon a strategic Enterprise Data Warehousing (EDW) initiative with the Microsoft technology platform as the foundation. Dale Sanders was CIO at Northwestern and led the development of Northwestern’s Microsoft-based EDW. At that time, Microsoft as an EDW platform was not en vogue and there were many who doubted the success of the Northwestern project. While other organizations were spending millions of dollars and years developing EDW’s and analytics on other platforms, Northwestern achieved great and rapid value at a fraction of the cost of the more typical technology platforms. Now, there are more healthcare data warehouses built around Microsoft products than any other vendor. The risky bet on Microsoft in 2005 paid off.
Ten years ago, critics didn’t believe that Microsoft could scale in the second generation of relational data warehouses, but they did. More recently, many of these same pundits have criticized Microsoft for missing the technology wave du jour in cloud offerings, mobile technology, and big data. But, once again, Microsoft has been quietly reengineering its culture and products, and as a result, they now offer the best value and most visionary platform for cloud services, big data, and analytics in healthcare.
In this context, Dale will talk about:
His up and down journey with Microsoft as an Air Force and healthcare CIO, and why he is now more bullish on Microsoft like never before
A quick review of the Healthcare Analytics Adoption Model and Closed Loop Analytics in healthcare, and how Microsoft products relate to both
The rise of highly specialized, cloud-based analytic services and their value to healthcare organizations’ analytics strategies
Microsoft’s transformation from a closed-system, desktop PC company to an open-system consumer and business infrastructure company
The current transition period of enterprise data warehouses between the decline of relational databases and the rise of non-relational databases, and the new Microsoft products, notably Azure and the Analytic Platform System (APS), that bridge the transition of skills and technology while still integrating with core products like Office, Active Directory, and System Center
Microsoft’s strategy with its PowerX product line, and geospatial analysis and machine learning visualization tools
Trends changed from Non compliance to RR --> Gap to RR --> Data Integrity --> DIB --> Smart Audit & Smart Data.
RR = Regulatory Requirements
DIB = Data Integrity Breach
Take a serious Note for Data Integrity whether you are small or big organization. Your Data is the Heart of your business. Regulatory bodies are highly conscious about such issues. For beginners in this path, my small note can help you a lot.
Michigan Health Information Network Shared Services MiHIN ADT Admit Discharge Transfer ONC Office of the National Coordinator for Health Information Technolgy HIT HIE
Health Data Exchange:. Still a Pipe Dream? A Presentation from 2009David Lee Scher, MD
This presentation discussing interoperability was given at the European Society of Cardiology in 2009.This remains an important topic for healthcare worldwide. Addendum: All names shown are fictitious and not real patients.
Organizations must onboard new data sources more frequently and quickly. In this presentation, you will learn about practices that rapidly deliver business value, while shrinking time to business value from months to days.
Business decisions are becoming increasingly dependent on analyzing an ever-greater volume of data coming from a growing number of sources. Mobile technology is providing immediate access to data whenever and wherever it is needed. Users, customers, and business partners are waiting for answers, and the organization must reduce the time required to collect, understand, and analyze the data needed to provide those answers. Modern enterprises need to increase the agility, flexibility, and speed with which they can analyze a growing volume, variety, and velocity of data.
This presentation discusses a method for rapid data integration and curation:
- Techniques for light data integration of new data with existing data assets
- Framework for data quality management
- Refining data integration through evolutionary modeling
- Managing curation processes
- Validating business value
Timely delivery of new data assets allows users to begin asking questions earlier and getting answers more quickly, allowing the organization to uncover the new insights that drive lasting business benefits.
Standard Safeguarding Dataset - overview for CSCDUG.pptxRocioMendez59
13 July, 2023 - CSCDUG Online Event
Presenting the Sector-led Standard Safeguarding Dataset
Colleagues from Data to Insight, the LA-led service for children’s safeguarding data professionals, are delivering a DfE-funded project in partnership with LAs to define a new “standard safeguarding dataset” which all LAs will be able to produce from their safeguarding information systems.
At this session, they shared what they’ve learned so far from user research with LA colleagues and discussed their early thinking about what a better standard dataset might look like. Participants shared their own thoughts about how to improve these systems and processes.
Presenters
Alistair Herbert
Alistair is the lead officer for Data to Insight, the LA-led service for children’s safeguarding data professionals. With a career focused on local authority children’s services data work, he knows about safeguarding data, information systems, and cross-organisation collaboration.
John Foster
John is a Data Manager for Data to Insight. He has supported a range of children’s services data work, most recently at Shropshire Council. He led Data to Insight’s project to introduce the first national benchmarking dataset for Early Help, and is the user research lead for Data to Insight’s Standard Safeguarding Dataset project.
Rob Harrison and Joe Cornford-Hutchings
Rob and Joe are new Data Managers joining Data to Insight from the private and public sector respectively. They bring between them a wealth of experience and technical expertise, and will be working together to support design and implementation of the new Standard Safeguarding Dataset through 2023-24.
The latest changes from CMS regarding Meaningful Use Stage 3 , CCDA and reporting measures. We discuss the effort required, estimates in terms of cost and timelines.
Despite massive investment in both people and technology, health systems are still struggling to maximize the value of their greatest asset: their data. Delivering high-quality, valuable insight from data and pushing those insights to the frontline healthcare professionals remains challenging and expensive. According to a recent survey conducted by HealthLeaders Media, health systems are hiring more analytics staff than almost any other role in health care. We know there’s an alternative to the massive hiring of analytics staff, a better way to dramatically increase the efficiency of your existing resources and provide an ROI that grows over time. The better way is the Rapid Response Analytics Solution.
Rapid Response Analytics Solution (RRA Solution) consists of two elements: curated, modular data called DOS™ Marts and Population Builder, a powerful self-service tool that lets any type of user, from physician executive to frontline nurses and population health teams explore their data and quickly build and share populations without needing to know how to write SQL and data science code. RRA Solution increases an analytics team’s productivity by up to 10x and reduces its time to develop analytics by as much as 90 percent. Analysts can spend more time focusing on key strategic analysis and less time on repetitive tasks that can lead to inconsistent results and a backlog of requests.
Learning Objectives:
- Discover how RRA Solution allows you to take components and customize them to quickly tailor and deliver meaningful insights.
- Learn about DOS™ Marts and Population Builder and how they drive consistency and efficiency, without needing to know SQL and data science coding.
- Understand how to use RRA Solution to increase the value of your analytics team and get them operating at the top of their function.
View this webinar and learn how RRA Solution can help you achieve a 10x increase in productivity and reduce your time to develop new analytics reports by more than 90 percent.
Microsoft: A Waking Giant In Healthcare Analytics and Big DataHealth Catalyst
In 2005, Northwestern Memorial Healthcare embarked upon a strategic Enterprise Data Warehousing (EDW) initiative with the Microsoft technology platform as the foundation. Dale Sanders was CIO at Northwestern and led the development of Northwestern’s Microsoft-based EDW. At that time, Microsoft as an EDW platform was not en vogue and there were many who doubted the success of the Northwestern project. While other organizations were spending millions of dollars and years developing EDW’s and analytics on other platforms, Northwestern achieved great and rapid value at a fraction of the cost of the more typical technology platforms. Now, there are more healthcare data warehouses built around Microsoft products than any other vendor. The risky bet on Microsoft in 2005 paid off.
Ten years ago, critics didn’t believe that Microsoft could scale in the second generation of relational data warehouses, but they did. More recently, many of these same pundits have criticized Microsoft for missing the technology wave du jour in cloud offerings, mobile technology, and big data. But, once again, Microsoft has been quietly reengineering its culture and products, and as a result, they now offer the best value and most visionary platform for cloud services, big data, and analytics in healthcare.
In this context, Dale will talk about:
His up and down journey with Microsoft as an Air Force and healthcare CIO, and why he is now more bullish on Microsoft like never before
A quick review of the Healthcare Analytics Adoption Model and Closed Loop Analytics in healthcare, and how Microsoft products relate to both
The rise of highly specialized, cloud-based analytic services and their value to healthcare organizations’ analytics strategies
Microsoft’s transformation from a closed-system, desktop PC company to an open-system consumer and business infrastructure company
The current transition period of enterprise data warehouses between the decline of relational databases and the rise of non-relational databases, and the new Microsoft products, notably Azure and the Analytic Platform System (APS), that bridge the transition of skills and technology while still integrating with core products like Office, Active Directory, and System Center
Microsoft’s strategy with its PowerX product line, and geospatial analysis and machine learning visualization tools
Trends changed from Non compliance to RR --> Gap to RR --> Data Integrity --> DIB --> Smart Audit & Smart Data.
RR = Regulatory Requirements
DIB = Data Integrity Breach
Take a serious Note for Data Integrity whether you are small or big organization. Your Data is the Heart of your business. Regulatory bodies are highly conscious about such issues. For beginners in this path, my small note can help you a lot.
Similar to Michigan HIE Model- Cynthia Edwards (20)
Michigan Health Information Network Shared Services MiHIN ADT Admit Discharge Transfer ONC Office of the National Coordinator for Health Information Technolgy HIT HIE
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
2. Unraveling the Current Information Tangle
Insurance
Companies
Physicians
Specialty
Providers
Hospitals & Clinics
Patients
& Families
Lab tests &
XRAYs
Medications
Public Health
2
* One Directional
* Not Real-Time
* Lacks Standards
3. Desired Solution
Health Information Exchange
Insurance
Companies
Physicians
Specialty
Providers
Hospitals & Clinics
Patients
& Families
Lab tests &
XRAYs
Medications
Public Health
HIE
3
Standards govern:
Form, Content and Response
5. 5
SOM HIE
Doctors EHRs
SUB-STATE HIE
Michigan HIE Model
Early 2012
SOM HIE Phase I
* Implement interim solution for HL7 messages
* Direct Connect to SOM HIE
* Send immunization records to MCIR
* Compliance with CDC Grant
* Send hospital reportable labs to MDSS
* Ability to send message acknowledgements
6. 6
SOM HIE
Medicaid
Doctors &
Community
Providers EHRs
SUB-STATE HIEs
Michigan HIE Model
Current
Doctors &
Local PH Dept EHRs
SOM HIE Phase II
* Implement production solution
* Establish MiHIN – SOM HIE connection
* Continued Infrastructure Development
* Gather new functional requirements
7. 7
Medicaid
DW
MSSS
SOM HIE Phase III
*MiHIN – SOM HIE – connection via
VPN
*Next SOM Use Cases
* MSSS
* MCIR forecast/history
* State Labs (StarLIMS)
*HPD – Health Provider Directory
* Not Limited to Licensed Providers
Michigan HIE Model
Planning
State Labs
StarLIMS
8. 8
Medicaid
DW
MSSS
*Match person-level
records across data sets
*Link data from multiple
data sources for an
individual person
*Include data sets beyond
HIE
*Phased implementation
approach
SOM Master Person Index
State Labs
StarLIMS
9. *
*Affordable Care Act and other healthcare
initiatives are driving data sharing
*Comprehensive view of individuals in multiple
programs making it possible to
*effectively assess and analyze healthcare
program data
*make better and faster decisions
*manage and measure programs
*reduce costs
*improve outcomes
9
11. *
*Completed March 2012
*Deployed the Initiate Citizen Hub
*Implemented Initiate Inspector for data
resolution
*Replaced Data Warehouse UCI
*UCI originally implemented 2001
*Configured single input and output streams
combining 17 data sources
*Initial conversion included 38 million records
11
12. 12
MPI Phase II
SSHIE
- PID
DC -
PID
SSO
- PID
SSO -
DDE
* Establish real-time interface
between MCIR and MPI
* Data Warehouse to accept
MCIR updates from MPI
* Establish process to add
additional MDCH systems
MPI Future Phases
* MDSS and StarLIMS
* other SOM systems
* Household identification
13. 13
Step 1: Optimizes data for statistical comparisons
– Normalizes & compacts data, creates derived data layer,
source data remains intact
– Phonetic equivalences, tokenization, nicknames, etc.
Step 2: Finds all the potential matches
– Casts a wide net – all matches on current or historical attributes, prevents misses
– Partial matches, reversals, anonymous values, etc.
Step 3: Scores accurately via probabilistic statistics
– Compares attributes one-by-one and produces
a weighted score (likelihood ratio)
– Frequency weights specific to your business
– Edit distance, proximity of match
– Allows custom deterministic rules
Step 4: Custom threshold settings
– Single or dual threshold models
– Link, don’t link, don’t know – “learns”
from manual input
– Manage cost/quality trade-offs
– Manage the linkages, workflow review
Manual Review
Lowest
Possible
Score
Highest
Possible
Score
Don’t
Link Link
Lowest
Threshold
Upper
Threshold
Should be linked
Should not be linked
*
14. *
14
Alerts data stewards to potential data quality
and relationship issues delivering the ability
to collaboratively inspect data, visualize
relationships and resolve issues
Inspect and resolve data
quality issues
Resolve duplicates within same
source
Manually link records across multiple
systems
Visualize and manage relationships
Centralize and leverage data across the
enterprise…with a single tool
IBM® INITIATE® INSPECTORIBM® INITIATE® INSPECTOR
Issue
Resolution
Hierarchy/
Relationship
Management
Central
Data Store
15. 15
CONSUMING
SOURCES
DATA
SOURCES
Source 1 Source 2 Source ‘n’Source 3
System 1 System 2 System 3
Catherine Lamb
763543Dr Kath J. Jones 1:N4456 15/06/1970 9263462232 Sussex St 0415266721
763543Dr Kate Lamb 2:2736 Female 02-9263-4622
763543Mrs. K. Jones 3:S7846 15/06/1970 9263-4622Level 1, 32 Sussex Rd +61415266721
763543n:97662 15/06/2006 Female 92630-6000 0415-266-721
60558
60558
60558
Local ID: EID:Name: DOB: Sex: Home Phone:Address 1: Mobile:Zip Code:
763543Dr Kath J. Jones 15/06/1970 Female 02 9263 4622 0415 266 721Level 1, 32 Sussex St 60558
System ‘n’
*
16. *
*Administrators
*Assign tasks to data stewards
*Resolve tasks
*Link records
*Identify target record
*Assign trusted source
*Data Stewards
*Review potential linkages
*Resolve data integrity issues
*Ensure source-record quality
*Monitor and maintain data accuracy
16
17. *
*Limited to authorized users (data stewards)
and to specific data/levels of information
*Identifier information is not shared
*Data can be linked without being visible
*Oversight by MDCH Security Office
17
18. *
*Collaboration with MiHIN for development of
Health Provider Directory
*Leverage development to expand to Provider
Index
*Include provider/organizations beyond HIE
18
