Shakir Consulting provides a 20-year history and agenda. It was created in 2001 after the founder worked at Kaiser Permanente and IDX Corporation. The company focuses on population health, healthcare delivery, finance, and research projects. Recent clients include the CDC, various state health departments, and healthcare organizations. Major milestones include the first client in 2001 and longest engagement with CDC. The company aims to continue its work over the next 20 years.
In this presentation, Shaheen Gauher talks about two things: (1) How data science and machine learning can be used to manage and control escalating healthcare costs, and (2) How to create a Population Health Management Solution using state of the art Azure Data Lake Analytics and Population Health Report with real time visualization capability using Power BI. The solution presented can be deployed on Azure through a one-click deployment option in https://gallery.cortanaintelligence.com/
The document discusses healthcare informatics and big data in healthcare. It provides an introduction to healthcare informatics, the advantages and disciplines involved. It then discusses big data in healthcare, including the sources and types of healthcare data, challenges in big data analytics, and conceptual architectures. Tools for big data analytics are also outlined, including Hadoop, Pig, Hive and others. Finally, it provides an example case study of a systematic review on the effectiveness of mobile health technology interventions.
Big Data Analytics - Opportunities, Enablers, Challenges and Risks to Conside...Innovation Enterprise
The document discusses big data analytics opportunities, enablers, challenges and risks in healthcare. It provides examples of big data analytics being used successfully in healthcare settings to predict disease outbreaks, detect infections in premature babies, assist with cancer treatment selection, and predict hospital readmissions. Key enablers for big data analytics include appropriate governance, skills, and technical infrastructure. While progress has been slow, big data analytics is gaining traction in healthcare with early applications including cancer, chronic disease management, remote patient monitoring and predictive analytics.
This document discusses how big data and analytics can help address the COVID-19 pandemic. It begins by defining big data and describing its key characteristics of volume, velocity, and variety. It then discusses how the pandemic has led to a large volume of health data and different data types. The document proposes a framework for collecting, analyzing and applying this data through descriptive, diagnostic, predictive and prescriptive analytics. This framework could help with tasks like epidemic monitoring, early warning, tracing virus sources, and recommending best courses of action. In closing, the document lists several references on big data applications for public health surveillance, resource allocation, and investigating COVID-19 symptoms.
This document discusses applications of big data and data analytics in healthcare. It provides two case studies: 1) a rural clinically integrated network in Kansas that uses data analytics to identify at-risk patients and reduce costs, and 2) an analysis of billing data for a Department of Justice investigation. The document also outlines other healthcare data analytics projects and discusses growing demand for data analytics expertise and the potential for analytics to improve healthcare outcomes and reduce costs.
This document provides a summary of Darin P. Gonzalez's education and professional experience. He has a Masters in Health Policy and Administration from the University of Illinois School of Public Health and undergraduate degrees in Biology and Chemistry. His professional experience includes roles in quality improvement, research, project management, and clinical work at various hospitals and healthcare organizations. He has authored several publications in peer-reviewed journals and been involved in clinical research studies related to areas like infectious disease, trauma care, and cancer treatment.
In this presentation, Shaheen Gauher talks about two things: (1) How data science and machine learning can be used to manage and control escalating healthcare costs, and (2) How to create a Population Health Management Solution using state of the art Azure Data Lake Analytics and Population Health Report with real time visualization capability using Power BI. The solution presented can be deployed on Azure through a one-click deployment option in https://gallery.cortanaintelligence.com/
The document discusses healthcare informatics and big data in healthcare. It provides an introduction to healthcare informatics, the advantages and disciplines involved. It then discusses big data in healthcare, including the sources and types of healthcare data, challenges in big data analytics, and conceptual architectures. Tools for big data analytics are also outlined, including Hadoop, Pig, Hive and others. Finally, it provides an example case study of a systematic review on the effectiveness of mobile health technology interventions.
Big Data Analytics - Opportunities, Enablers, Challenges and Risks to Conside...Innovation Enterprise
The document discusses big data analytics opportunities, enablers, challenges and risks in healthcare. It provides examples of big data analytics being used successfully in healthcare settings to predict disease outbreaks, detect infections in premature babies, assist with cancer treatment selection, and predict hospital readmissions. Key enablers for big data analytics include appropriate governance, skills, and technical infrastructure. While progress has been slow, big data analytics is gaining traction in healthcare with early applications including cancer, chronic disease management, remote patient monitoring and predictive analytics.
This document discusses how big data and analytics can help address the COVID-19 pandemic. It begins by defining big data and describing its key characteristics of volume, velocity, and variety. It then discusses how the pandemic has led to a large volume of health data and different data types. The document proposes a framework for collecting, analyzing and applying this data through descriptive, diagnostic, predictive and prescriptive analytics. This framework could help with tasks like epidemic monitoring, early warning, tracing virus sources, and recommending best courses of action. In closing, the document lists several references on big data applications for public health surveillance, resource allocation, and investigating COVID-19 symptoms.
This document discusses applications of big data and data analytics in healthcare. It provides two case studies: 1) a rural clinically integrated network in Kansas that uses data analytics to identify at-risk patients and reduce costs, and 2) an analysis of billing data for a Department of Justice investigation. The document also outlines other healthcare data analytics projects and discusses growing demand for data analytics expertise and the potential for analytics to improve healthcare outcomes and reduce costs.
This document provides a summary of Darin P. Gonzalez's education and professional experience. He has a Masters in Health Policy and Administration from the University of Illinois School of Public Health and undergraduate degrees in Biology and Chemistry. His professional experience includes roles in quality improvement, research, project management, and clinical work at various hospitals and healthcare organizations. He has authored several publications in peer-reviewed journals and been involved in clinical research studies related to areas like infectious disease, trauma care, and cancer treatment.
1) The document discusses NCHS's participation in health information technology and electronic health record standards development to support the adoption of EHRs.
2) NCHS has developed and maintained many critical classification standards used in healthcare and is engaged in several initiatives to develop standards for exchanging birth/death data with vital records systems and public health reporting from EHRs.
3) The presentation outlines NCHS's future directions, which include gaining experience receiving standardized administrative and EHR-derived data for its surveys as electronic health records become more widely adopted and able to exchange data.
National Services Scotland Business IntelligenceInvestnet
The document discusses a business intelligence tech refresh at National Services Scotland (NSS). It provides an overview of NSS and the current BI platform, which includes 45+ data marts. Drivers for change include health and social care integration, open data needs, and aging technology. The proposed solution is a logical data warehouse that would provide benefits like joining up data without moving or duplicating, timelier access, and greater agility.
Joanna Turner presented on how the State Health Access Data Assistance Center (SHADAC) helps states use federal survey data like the American Community Survey (ACS) and Current Population Survey (CPS) to inform state health policy decisions. SHADAC enhances the data to address policy questions on issues like health insurance coverage, creates easy to use data products and tools, conducts education and outreach, and provides suggestions to the Census Bureau to improve data accessibility and usefulness for states. The goal is to help bridge the gap between available health data and how states can apply it for decision making.
EHR guidelines from CDC SS-08_WILLIAMSON_GUGERTY.pptxanjalatchi
The document summarizes a presentation on the Centers for Disease Control and Prevention's involvement in health information technology and electronic health record standards development. It discusses how CCDC is participating in initiatives to define public health reporting requirements and support the adoption of EHR systems. It also provides an overview of CCDC's core health care surveys and plans to increasingly utilize electronic health data from sources like EHRs, claims, and administrative systems to conduct research more efficiently as adoption of digital health records increases.
Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...Wellbe
This document provides an overview of registry participation and collecting patient-reported outcome measures through a registry. It discusses the University of Wisconsin's process for collecting PROs in their orthopedic clinics in two phases: a pilot phase and a full implementation phase. The pilot involved collecting PROs in 6 clinics using Epic and tablet computers. Lessons learned included that an integrated tablet/portal solution and coordinated project management were important. The full implementation will expand PRO collection to all orthopedic locations and improve reporting automation.
NACCHO 2018 National Conference – Health Data Portal: Aboriginal and Torres S...NACCHOpresentations
The document discusses the Health Data Portal, which is a new system for Aboriginal and Torres Strait Islander health reporting that will replace OCHREStreams. It provides automatic data validation, analytics dashboards, and was co-designed with Indigenous health services and sectors over numerous workshops. A trial in July 2018 was successful. Transition from OCHREStreams to the Health Data Portal will occur from November 2018, and information sessions are being held to help health services prepare.
This document provides an overview of a healthcare information analytics course. It includes:
1. An introduction to the class and instructor with an overview of course materials, software requirements, and housekeeping items.
2. A review of current healthcare challenges around rising costs, quality of care, and system pressures to improve outcomes.
3. A history of the evolution of hospital information systems from the 1960s to present day, covering drivers in healthcare and IT and how they resulted in health information technology.
Health Information Analytics: Data Governance, Data Quality and Data StandardsFrank Wang
The document discusses key concepts related to health data governance, including data governance, data quality, data standards, and master data management. It provides definitions and explanations of these topics, as well as their importance in enabling effective health information analytics. It also discusses different roles and responsibilities in data governance committees and outlines approaches to master data management.
Netta Hollings (Programme Manager - Mental Health and Community Care) discusses how you can get the most out of the Maternity Services Data Set (MSDS) and the Child Health Data Sets.
The data sets provide comparative, mother and child-centric data that will be used to improve clinical quality and service efficiency; and to commission services in a way that improves health and reduce inequalities.
Improvement Story session at the 2013 Saskatchewan Health Care Quality Summit. For more information about the summit, visit www.qualitysummit.ca. Follow @QualitySummit on Twitter.
The implementation and on-going enhancement of the eHealth Saskatchewan Clinical Portal to complement existing systems to support improved health care province-wide through electronic access to important clinical information.
Better Health
Kevin Kidney
Making use of All-Payer Claims Databases for Health Care Reform Evaluationsoder145
This document discusses the uses of all-payer claims databases (APCDs) for health care reform evaluation. APCDs contain claims data from multiple payers and can be used to monitor health care costs, identify cost drivers, foster price transparency, and track quality measures. The document outlines several state case studies that demonstrate how APCDs have been used to monitor statewide spending, evaluate transformation efforts, and promote price transparency. It concludes by discussing future directions for APCDs, including data linkages and payment reform evaluation.
This document discusses big data analytics in healthcare. It begins by defining translational bioinformatics and discussing the challenges and opportunities of big data. It then outlines how big data is generated from a variety of clinical, administrative, and other sources. Technologies like Hadoop and NoSQL databases are important for analyzing large and diverse healthcare datasets. The document argues that big data analytics can help innovate and accelerate healthcare by enabling predictive analytics, personalized medicine, and improving outcomes while reducing costs.
Oncology Big Data: A Mirage or Oasis of Clinical Value? Michael Peters
The title of the presentation, Oncology Big Data: A Mirage or Oasis of Clinical Value, reflects what I believe the field of Oncology is challenged with on a growing basis, from a clinical and business side perspective.
The document provides an overview of the Florida Health Information Exchange (HIE). It describes two key HIE services - Direct Secure Messaging (DSM), which allows participants to securely share encrypted health information, and Patient Look-Up (PLU), which allows clinicians to query and retrieve patient records. It notes that over 4,000 Florida users are connected through DSM, including connections being established to other states. The HIE also supports disaster preparedness by allowing out-of-state providers to request patient information from Florida providers.
1. The document discusses evaluating the impact of analytics on data quality at the NT Community Health organization.
2. It describes issues with Community Health's current information systems including disparate databases, a lack of data integration and documentation, and outdated data.
3. The document evaluates different analytics tools and their ability to help transform data into useful business insights to address Community Health's data quality and integration challenges.
The document discusses Cleveland Clinic's strategy for managing patient populations beyond meaningful use requirements. It provides an overview of Cleveland Clinic including its size and services. It then summarizes the history of Cleveland Clinic's patient portal called MyChart, highlighting growth in usage and new features added over time. Finally, it outlines Cleveland Clinic's growth strategy, which includes increasing transparency by providing access to medical records and surveys, improving access to care through online services, and engaging patients through collection of patient entered data.
The document discusses the efforts of the Center for Population Health Improvement (CPHI) in Santa Clara County to improve population health outcomes. CPHI was established to better integrate and analyze data across the county's various health systems. It has recruited a multidisciplinary team with skills in public health, IT, data analytics and more. Initial CPHI projects focused on high utilizers of services by developing tools to identify at-risk patients and coordinate interventions across systems. The goal is to reduce unnecessary utilization and improve care for vulnerable populations.
In the intricate tapestry of life, connections serve as the vibrant threads that weave together opportunities, experiences, and growth. Whether in personal or professional spheres, the ability to forge meaningful connections opens doors to a multitude of possibilities, propelling individuals toward success and fulfillment.
Eirini is an HR professional with strong passion for technology and semiconductors industry in particular. She started her career as a software recruiter in 2012, and developed an interest for business development, talent enablement and innovation which later got her setting up the concept of Software Community Management in ASML, and to Developer Relations today. She holds a bachelor degree in Lifelong Learning and an MBA specialised in Strategic Human Resources Management. She is a world citizen, having grown up in Greece, she studied and kickstarted her career in The Netherlands and can currently be found in Santa Clara, CA.
1) The document discusses NCHS's participation in health information technology and electronic health record standards development to support the adoption of EHRs.
2) NCHS has developed and maintained many critical classification standards used in healthcare and is engaged in several initiatives to develop standards for exchanging birth/death data with vital records systems and public health reporting from EHRs.
3) The presentation outlines NCHS's future directions, which include gaining experience receiving standardized administrative and EHR-derived data for its surveys as electronic health records become more widely adopted and able to exchange data.
National Services Scotland Business IntelligenceInvestnet
The document discusses a business intelligence tech refresh at National Services Scotland (NSS). It provides an overview of NSS and the current BI platform, which includes 45+ data marts. Drivers for change include health and social care integration, open data needs, and aging technology. The proposed solution is a logical data warehouse that would provide benefits like joining up data without moving or duplicating, timelier access, and greater agility.
Joanna Turner presented on how the State Health Access Data Assistance Center (SHADAC) helps states use federal survey data like the American Community Survey (ACS) and Current Population Survey (CPS) to inform state health policy decisions. SHADAC enhances the data to address policy questions on issues like health insurance coverage, creates easy to use data products and tools, conducts education and outreach, and provides suggestions to the Census Bureau to improve data accessibility and usefulness for states. The goal is to help bridge the gap between available health data and how states can apply it for decision making.
EHR guidelines from CDC SS-08_WILLIAMSON_GUGERTY.pptxanjalatchi
The document summarizes a presentation on the Centers for Disease Control and Prevention's involvement in health information technology and electronic health record standards development. It discusses how CCDC is participating in initiatives to define public health reporting requirements and support the adoption of EHR systems. It also provides an overview of CCDC's core health care surveys and plans to increasingly utilize electronic health data from sources like EHRs, claims, and administrative systems to conduct research more efficiently as adoption of digital health records increases.
Registry Participation 101: A Step-by-Step Guide to What You Really Need to K...Wellbe
This document provides an overview of registry participation and collecting patient-reported outcome measures through a registry. It discusses the University of Wisconsin's process for collecting PROs in their orthopedic clinics in two phases: a pilot phase and a full implementation phase. The pilot involved collecting PROs in 6 clinics using Epic and tablet computers. Lessons learned included that an integrated tablet/portal solution and coordinated project management were important. The full implementation will expand PRO collection to all orthopedic locations and improve reporting automation.
NACCHO 2018 National Conference – Health Data Portal: Aboriginal and Torres S...NACCHOpresentations
The document discusses the Health Data Portal, which is a new system for Aboriginal and Torres Strait Islander health reporting that will replace OCHREStreams. It provides automatic data validation, analytics dashboards, and was co-designed with Indigenous health services and sectors over numerous workshops. A trial in July 2018 was successful. Transition from OCHREStreams to the Health Data Portal will occur from November 2018, and information sessions are being held to help health services prepare.
This document provides an overview of a healthcare information analytics course. It includes:
1. An introduction to the class and instructor with an overview of course materials, software requirements, and housekeeping items.
2. A review of current healthcare challenges around rising costs, quality of care, and system pressures to improve outcomes.
3. A history of the evolution of hospital information systems from the 1960s to present day, covering drivers in healthcare and IT and how they resulted in health information technology.
Health Information Analytics: Data Governance, Data Quality and Data StandardsFrank Wang
The document discusses key concepts related to health data governance, including data governance, data quality, data standards, and master data management. It provides definitions and explanations of these topics, as well as their importance in enabling effective health information analytics. It also discusses different roles and responsibilities in data governance committees and outlines approaches to master data management.
Netta Hollings (Programme Manager - Mental Health and Community Care) discusses how you can get the most out of the Maternity Services Data Set (MSDS) and the Child Health Data Sets.
The data sets provide comparative, mother and child-centric data that will be used to improve clinical quality and service efficiency; and to commission services in a way that improves health and reduce inequalities.
Improvement Story session at the 2013 Saskatchewan Health Care Quality Summit. For more information about the summit, visit www.qualitysummit.ca. Follow @QualitySummit on Twitter.
The implementation and on-going enhancement of the eHealth Saskatchewan Clinical Portal to complement existing systems to support improved health care province-wide through electronic access to important clinical information.
Better Health
Kevin Kidney
Making use of All-Payer Claims Databases for Health Care Reform Evaluationsoder145
This document discusses the uses of all-payer claims databases (APCDs) for health care reform evaluation. APCDs contain claims data from multiple payers and can be used to monitor health care costs, identify cost drivers, foster price transparency, and track quality measures. The document outlines several state case studies that demonstrate how APCDs have been used to monitor statewide spending, evaluate transformation efforts, and promote price transparency. It concludes by discussing future directions for APCDs, including data linkages and payment reform evaluation.
This document discusses big data analytics in healthcare. It begins by defining translational bioinformatics and discussing the challenges and opportunities of big data. It then outlines how big data is generated from a variety of clinical, administrative, and other sources. Technologies like Hadoop and NoSQL databases are important for analyzing large and diverse healthcare datasets. The document argues that big data analytics can help innovate and accelerate healthcare by enabling predictive analytics, personalized medicine, and improving outcomes while reducing costs.
Oncology Big Data: A Mirage or Oasis of Clinical Value? Michael Peters
The title of the presentation, Oncology Big Data: A Mirage or Oasis of Clinical Value, reflects what I believe the field of Oncology is challenged with on a growing basis, from a clinical and business side perspective.
The document provides an overview of the Florida Health Information Exchange (HIE). It describes two key HIE services - Direct Secure Messaging (DSM), which allows participants to securely share encrypted health information, and Patient Look-Up (PLU), which allows clinicians to query and retrieve patient records. It notes that over 4,000 Florida users are connected through DSM, including connections being established to other states. The HIE also supports disaster preparedness by allowing out-of-state providers to request patient information from Florida providers.
1. The document discusses evaluating the impact of analytics on data quality at the NT Community Health organization.
2. It describes issues with Community Health's current information systems including disparate databases, a lack of data integration and documentation, and outdated data.
3. The document evaluates different analytics tools and their ability to help transform data into useful business insights to address Community Health's data quality and integration challenges.
The document discusses Cleveland Clinic's strategy for managing patient populations beyond meaningful use requirements. It provides an overview of Cleveland Clinic including its size and services. It then summarizes the history of Cleveland Clinic's patient portal called MyChart, highlighting growth in usage and new features added over time. Finally, it outlines Cleveland Clinic's growth strategy, which includes increasing transparency by providing access to medical records and surveys, improving access to care through online services, and engaging patients through collection of patient entered data.
The document discusses the efforts of the Center for Population Health Improvement (CPHI) in Santa Clara County to improve population health outcomes. CPHI was established to better integrate and analyze data across the county's various health systems. It has recruited a multidisciplinary team with skills in public health, IT, data analytics and more. Initial CPHI projects focused on high utilizers of services by developing tools to identify at-risk patients and coordinate interventions across systems. The goal is to reduce unnecessary utilization and improve care for vulnerable populations.
In the intricate tapestry of life, connections serve as the vibrant threads that weave together opportunities, experiences, and growth. Whether in personal or professional spheres, the ability to forge meaningful connections opens doors to a multitude of possibilities, propelling individuals toward success and fulfillment.
Eirini is an HR professional with strong passion for technology and semiconductors industry in particular. She started her career as a software recruiter in 2012, and developed an interest for business development, talent enablement and innovation which later got her setting up the concept of Software Community Management in ASML, and to Developer Relations today. She holds a bachelor degree in Lifelong Learning and an MBA specialised in Strategic Human Resources Management. She is a world citizen, having grown up in Greece, she studied and kickstarted her career in The Netherlands and can currently be found in Santa Clara, CA.
We recently hosted the much-anticipated Community Skill Builders Workshop during our June online meeting. This event was a culmination of six months of listening to your feedback and crafting solutions to better support your PMI journey. Here’s a look back at what happened and the exciting developments that emerged from our collaborative efforts.
A Gathering of Minds
We were thrilled to see a diverse group of attendees, including local certified PMI trainers and both new and experienced members eager to contribute their perspectives. The workshop was structured into three dynamic discussion sessions, each led by our dedicated membership advocates.
Key Takeaways and Future Directions
The insights and feedback gathered from these discussions were invaluable. Here are some of the key takeaways and the steps we are taking to address them:
• Enhanced Resource Accessibility: We are working on a new, user-friendly resource page that will make it easier for members to access training materials and real-world application guides.
• Structured Mentorship Program: Plans are underway to launch a mentorship program that will connect members with experienced professionals for guidance and support.
• Increased Networking Opportunities: Expect to see more frequent and varied networking events, both virtual and in-person, to help you build connections and foster a sense of community.
Moving Forward
We are committed to turning your feedback into actionable solutions that enhance your PMI journey. This workshop was just the beginning. By actively participating and sharing your experiences, you have helped shape the future of our Chapter’s offerings.
Thank you to everyone who attended and contributed to the success of the Community Skill Builders Workshop. Your engagement and enthusiasm are what make our Chapter strong and vibrant. Stay tuned for updates on the new initiatives and opportunities to get involved. Together, we are building a community that supports and empowers each other on our PMI journeys.
Stay connected, stay engaged, and let’s continue to grow together!
About PMI Silver Spring Chapter
We are a branch of the Project Management Institute. We offer a platform for project management professionals in Silver Spring, MD, and the DC/Baltimore metro area. Monthly meetings facilitate networking, knowledge sharing, and professional development. For more, visit pmissc.org.
Success is often not achievable without facing and overcoming obstacles along the way. To reach our goals and achieve success, it is important to understand and resolve the obstacles that come in our way.
In this article, we will discuss the various obstacles that hinder success, strategies to overcome them, and examples of individuals who have successfully surmounted their obstacles.
Joyce M Sullivan, Founder & CEO of SocMediaFin, Inc. shares her "Five Questions - The Story of You", "Reflections - What Matters to You?" and "The Three Circle Exercise" to guide those evaluating what their next move may be in their careers.
A Guide to a Winning Interview June 2024Bruce Bennett
This webinar is an in-depth review of the interview process. Preparation is a key element to acing an interview. Learn the best approaches from the initial phone screen to the face-to-face meeting with the hiring manager. You will hear great answers to several standard questions, including the dreaded “Tell Me About Yourself”.
Learnings from Successful Jobs SearchersBruce Bennett
Are you interested to know what actions help in a job search? This webinar is the summary of several individuals who discussed their job search journey for others to follow. You will learn there are common actions that helped them succeed in their quest for gainful employment.
5. IDX – The Huntington Group
Client Name Project Begin End < J F M A M J J A S O N D >
Kaiser Permanente Electronic Data Interchange Planning Jun-1998 Jul-1998 • •
Columbia HCA Physician Services Data Warehouse Jul-1998 Feb-2000 • • • • • • >
Straub Clinic and Hospital Analytical Reporting Assessment Aug-1998 Oct-1998 • • •
Columbia HCA Physician Services Data Warehouse Jul-1998 Feb-2000 < • • • • • • • • • • • • >
Center for Disease Control and Prevention Develop the Public Health Conceptual Data Model May-1999 Jul-2000 • • • • • • • • • • >
Columbia HCA Physician Services Data Warehouse Jul-1998 Feb-2000 < • •
Center for Disease Control and Prevention Develop the Public Health Conceptual Data Model May-1999 Jul-2000 < • • • • • • •
Columbia HCA Enterprise Data Warehouse Planning Feb-2000 Apr-2000 • • •
Columbia HCA Informatics and Data Model Training Jun-2000 Jun-2000 •
Wake Forrest University North Carolina Baptist Hospital Enterprise Data Warehouse Planning Jul-2000 Oct-2000 • • • •
Center for Disease Control and Prevention Assist States with the Use of the PHCDM in designing IDR Jul-2000 May-2001 • • • • • • >
Wake Forrest University North Carolina Baptist Hospital Pharmacy Datamart Project Oct-2000 May-2001 • • • >
Center for Disease Control and Prevention Assist States with the Use of the PHCDM in designing IDR Jul-2000 May-2001 < • • • • •
Wake Forrest University North Carolina Baptist Hospital Pharmacy Datamart Project Oct-2000 May-2001 < • • • • •
Healthcare Partners Enterprise Data Warehouse Planning Apr-2001 Oct-2001 • • • • • • •
Center for Disease Control and Prevention Assist with Development of the NEDSS Base System Logical Data Model Jun-2001 Sep-2001 • • • •
Healthcare Partners Enterprise Data Warehouse Planning Nov-2001 Dec-2001 • •
Utah Department of Health Assessment of the Utah NEDSS IDR Logical Data Model Dec-2001 Jan-2002 • >
2001
1998
1999
2000
8. Types of Clients and Lines of Business
• Healthcare quality
measures
• Accountable care and
care coordination
• Information sharing
incentive programs
• Protocol driven
biomedical clinical
studies
• Evidence-base best
practices
• Genomics and Precision
medicine
• Electronic medical
record systems
• Clinical decision support
systems
• Disease Surveillance
• Vital Records
• Social Determinants of
Health
Population
Health
Healthcare
Delivery
Healthcare
Finance
Healthcare
Research
9. Client Locations
Country USA State City Country USA State City Country USA State City
Australia N/A Sydney USA CA Sacramento USA MD Gaithersburg
Brazil N/A Rio de Janeiro USA CA San Diego USA MD Hyattsville
Canada N/A Ottawa USA CA San Jose USA MD Silver Spring
Canada N/A Toronto USA CA San Rafael USA MI Ann Arbor
Canada N/A Vancouver USA CA Torrance USA MN Minneapolis
France N/A Paris USA DC Washington USA NC Winston-Salem
Germany N/A Stuttgart USA FL Buena Vista USA TN Nashville
Israel N/A Omer USA FL Orlando USA TX Austin
Saudi Arabia N/A Riyadh USA GA Atlanta USA TX Houston
Switzerland N/A Basel USA GA Marietta USA TX San Antonio
USA AZ Phoenix USA HI Honolulu USA UT Salt Lake City
USA CA Duarte USA IL Chicago USA VA Richmond
USA CA Irvine USA IL Springfield USA VT Burlington
USA CA Los Angeles USA MA Cambridge USA WA Seattle
USA CA Oakland USA MD Baltimore
USA CA Richmond USA MD Bethesda
10. Our Initial Set of Projects
Client Name Project Begin End < J F M A M J J A S O N D >
Healthcare Partners Enterprise Data Warehouse Planning Nov-2001 Dec-2001 • •
Utah Department of Health Assessment of the Utah NEDSS IDR Logical Data Model Dec-2001 Jan-2002 • >
Utah Department of Health Assessment of the Utah NEDSS IDR Logical Data Model Dec-2001 Jan-2002 < • • >
Health Level Seven HL7 Development Framework – HDF Metamodel and UML Profile Jan-2002 Dec-2002 • • • • • • • • • • • •
MedQuist DecisionNet HL7 Messaging Performance Mar-2002 Apr-2002 • •
MedVirginia MedVirginia Health Information Exchange Solution Mar-2002 Apr-2002 • •
Center for Disease Control and Prevention Model Extensions to the NBSLDM to Support Bioterrorism Response Management Mar-2002 May-2002 • • •
California Department of Health – CLPPB Assist with development of the RASSCLE Logical Data Model May-2002 Jul-2002 • • •
Center for Disease Control and Prevention Construct the Public Health Logical Data Model (PHLDM) Jul-2002 Nov-2002 • • • • •
California Department of Health Services Assist with applicable standards related to Public Health Case Management Sep-2002 Sep-2002 •
Center for Disease Control and Prevention Construct the Public Health Domain Information Model (PHDIM) Oct-2002 Dec-2002 • •
Center for Disease Control and Prevention Publication of the Public Health Domain Information Model (PHDIM) Jan-2003 Jun-2003 • • • • • •
Illinois Department of Public Health Trauma Registry Export using HL7 Messaging Mar-2003 Jun-2003 • • • •
California Department of Health – CLPPB Assist with development of the RASSCLE Database Design Model Jun-2003 Oct-2003 • • • • •
Oracle Corporation Healthcare Transaction Base HL7 Messaging - Orders and Observations Jul-2003 Oct-2003 • • • •
Oracle Corporation Healthcare Transaction Base HL7 Messaging - Pharmacy Sep-2003 Oct-2003 • •
Health Level Seven HL7 Development Framework – Development Methodology Reference Manual Sep-2003 Mar-2004 • • • • >
Los Angeles County Department of Health Services Los Angeles County Bioterrorism Response Management System Dec-2003 Nov-2005 • >
Health Level Seven HL7 Development Framework – Development Methodology Reference Manual Sep-2003 Mar-2004 < • • •
Los Angeles County Department of Health Services Los Angeles County Bioterrorism Response Management System Dec-2003 Nov-2005 < • • • • • • • • • • • • >
California Department of Health Services Assessment of the Public Health Sentinel Surveillance System Database Design Mar-2004 Mar-2004 •
California Department of Health Services Assist with development of PHS3 functions of CADHS Jul-2004 Mar-2005 • • • • • • >
California Department of Health – CLPPB Assist with implementation of the RASSCLE Physical Data Model Jul-2004 Jun-2005 • • • • • • >
Los Angeles County Department of Health Services Los Angeles County Bioterrorism Response Management System Dec-2003 Nov-2005 < • • • • • • • • • • •
California Department of Health Services Assist with development of PHS3 functions of CADHS Jul-2004 Mar-2005 < • • •
California Department of Health – CLPPB Assist with implementation of the RASSCLE Physical Data Model Jul-2004 Jun-2005 < • • • • •
City of Hope National Medical Center Assist with development of the AERS Domain Analysis Model May-2005 Sep-2005 • • • • • • •
California Department of Health – Immunization Branch Assist with project planning for the State Immunization Integration Project Jun-2005 Dec-2005 • • • • • • •
City of Hope National Medical Center Cancer Adverse Event Reporting System Oct-2005 Jun-2006 • • • >
2002
2003
2004
2005
11. Our Most Recent Projects
Client Name Project Begin End < J F M A M J J A S O N D >
University of California – Irvine Terminology Harmonization in Exercise Medicine and Exercise Science (THEMES) Mar-2016 Mar-2018 < • • • • • • • • • • • • >
The American College of Cardiology Unified Model and Transaction Specification - Phase IV Apr-2016 Jan-2017 < •
Los Angeles Network for Enhanced Services LANES health information exchange Health Information Architecture Apr-2016 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Mortality Reporting FHIR IG - Phase I (STU 1) May-2016 Apr-2019 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Domain Analysis Model Sep-2016 Jun-2017 < • • • • • •
University of California – Irvine Terminology Harmonization in Exercise Medicine and Exercise Science (THEMES) Mar-2016 Mar-2018 < • • •
Los Angeles Network for Enhanced Services LANES health information exchange Health Information Architecture Apr-2016 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Mortality Reporting FHIR IG - Phase I (STU 1) May-2016 Apr-2019 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Domain Analysis Model Mapping and Continuous Maintenance Jan-2018 Dec-2018 • • • • • • • • • • • •
Kingdom of Saudi Arabia Ministry of Health KSA MOH LOINC Tutorial and Mapping Dec-2018 Feb-2019 • >
Los Angeles Network for Enhanced Services LANES health information exchange Health Information Architecture Apr-2016 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Mortality Reporting FHIR IG - Phase I (STU 1) May-2016 Apr-2019 < • • • •
Kingdom of Saudi Arabia Ministry of Health KSA MOH LOINC Tutorial and Mapping Dec-2018 Feb-2019 < • •
National Center for Health Statistics Vital Records Death Reporting FHIR IG - Phase II (STU 2) May-2019 Sep-2021 • • • • • • • • >
National Center for Health Statistics Vital Records Domain Analysis Model R4 Aug-2019 Nov-2020 • • • • • >
Los Angeles Network for Enhanced Services LANES health information exchange Health Information Architecture Apr-2016 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Death Reporting FHIR IG - Phase II (STU 2) May-2019 Sep-2021 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Domain Analysis Model R4 Aug-2019 Nov-2020 < • • • • • • • • • • •
California Department of Public Health CDPH Death Reporting Interface Jan-2020 Feb-2021 • • • • • • • • • • • • >
Vermont Health Information Exchange HL7 FHIR Implementation Architectural Assessment Sep-2020 • • • • >
Los Angeles Network for Enhanced Services LANES health information exchange Health Information Architecture Apr-2016 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Death Reporting FHIR IG - Phase II (STU 2) May-2019 Sep-2021 < • • • • • • • • •
California Department of Public Health CDPH Death Reporting Interface Jan-2020 Feb-2021 < • •
Vermont Health Information Exchange HL7 FHIR Implementation Architectural Assessment Sep-2020 < • • • • • • • • • • • • >
National Center for Health Statistics Vital Records Domain Analysis Model R5 Mar-2021 • • • • • • • • • • >
NCI Center for Biomedical Informatics and Information Technology CCDI Information Architecture Jul-2021 • • • • • • >
National Center for Health Statistics Vital Records Death Reporting FHIR IG - Phase III (STU 2.1) Oct-2021 • • • >
2020
2021
2017
2018
2019
12. Major Milestones
Our first client –
Health Care
Partners
Our longest
engaged client –
Center for Disease
Control and
Prevention
CAL2CAL – Los
Angeles Public
Health Department
Hi3 Solutions - Our
venture into product
development
LANES – The most
impactful
engagement of all