The HEALTHieR Cloud is the world's first Global Electronic Healthcare Repository (GEHR). We believe that full adoption may reduce R&D costs by 90%. Researchers, Hospitals, Providers, and Patients can access the system to view patient information.
HXR 2016: Data Insights: Mining, Modeling, and Visualizations- Niraj KatwalaHxRefactored
This document provides an overview of Talix's HealthData Engine and related products and services. It discusses Talix's team of 60 medical and technical professionals and its Coding InSight and HealthSearch products. It then describes the HealthData Engine and how it leverages natural language processing, a robust taxonomy, and clinical rules to extract and normalize data from unstructured patient information. Use cases like risk adjustment, clinical decision support, and content search are discussed. The challenges of risk adjustment are outlined and how Coding InSight addresses them through automated coding, integration into clinical workflows, and improved analytics. An example is given showing how optimizing coded data could increase CMS payments.
Client is a California based healthcare company, they uniquely combine technology, services and analytics to produce scalable, high touch care models that enrich the patient-provider experience and reduce the cost of care.
The digital care management platform empowers people with personalized actionable data and consultations to help them achieve better health.
The Hive Think Tank: Unpacking AI for Healthcare The Hive
In this The Hive Think Tank talk, Ash Damle, CEO of Lumiata takes a deep dive into Lumiata’s core technological engine - the Lumiata Medical Graph, which applies graph-based machine learning to compute the complex relationships between health data in the same way that a physician would, and how this medical AI engine powers personalization and automation within risk and care management.
1) Hackensack University Medical Center is part of a large healthcare network in New Jersey serving over 6 million people. It has received numerous awards and recognition for clinical excellence.
2) The presentation discusses HackensackUMC's strategies for managing risk-based care and consumerism, which includes a focus on patient engagement, care coordination across settings, and using technology like EHRs and analytics to improve outcomes and reduce costs.
3) HackensackUMC is managing care for over 100,000 beneficiaries through its Medicare ACO, a Blue Cross ACO, and an Aetna Medicare Advantage plan. It aims to shift care toward prevention and meet the growing demands of consumerism through increased access,
Because everyone matters.
IBM Health and Social Programs Summit, October 2014
Stephen Morgan
Senior Vice President and Chief Medical Officer
Carilion Clinic
Jianying Hu
Research Staff Member and Manager of Healthcare Analytics Research
IBM
Paul Grundy
Global Director of Healthcare Transformation
IBM
As the author of “Big Data in Healthcare Hype and Hope,” Dr. Feldman has interviewed over 180 emerging tech and healthcare companies, always asking, “How can your new approach help patients?” Her research shows that data, as an enabling tool, has the power to give us critical new insights into not only what causes disease, but what comprises normal. Despite this promise, few patients have reaped the benefits of personalized medicine. A panel of leading big data innovators will discuss the evolving health data ecosystem and how big data is being leveraged for research, discovery, clinical trials, genomics, and cancer care. Case studies and real-life examples of what’s working, what’s not working, and how we can help speed up progress to get patients the right care at the right time will be explored and debated.
• Bonnie Feldman, DDS, MBA - Chief Growth Officer, @DrBonnie360
• Colin Hill - CEO, GNS Healthcare
• Jonathan Hirsch - Founder & President, Syapse
• Andrew Kasarskis, PhD - Co-Director, Icahn Institute for Genomics & Multiscale Biology; Associate Professor, Genetics & Genomic Studies, Icaahn School of Medicine at Mt. Sinai
• William King - CEO, Zephyr Health
New York eHealth Collaborative Digital Health Conference
November 18, 2014
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.
HXR 2016: Data Insights: Mining, Modeling, and Visualizations- Niraj KatwalaHxRefactored
This document provides an overview of Talix's HealthData Engine and related products and services. It discusses Talix's team of 60 medical and technical professionals and its Coding InSight and HealthSearch products. It then describes the HealthData Engine and how it leverages natural language processing, a robust taxonomy, and clinical rules to extract and normalize data from unstructured patient information. Use cases like risk adjustment, clinical decision support, and content search are discussed. The challenges of risk adjustment are outlined and how Coding InSight addresses them through automated coding, integration into clinical workflows, and improved analytics. An example is given showing how optimizing coded data could increase CMS payments.
Client is a California based healthcare company, they uniquely combine technology, services and analytics to produce scalable, high touch care models that enrich the patient-provider experience and reduce the cost of care.
The digital care management platform empowers people with personalized actionable data and consultations to help them achieve better health.
The Hive Think Tank: Unpacking AI for Healthcare The Hive
In this The Hive Think Tank talk, Ash Damle, CEO of Lumiata takes a deep dive into Lumiata’s core technological engine - the Lumiata Medical Graph, which applies graph-based machine learning to compute the complex relationships between health data in the same way that a physician would, and how this medical AI engine powers personalization and automation within risk and care management.
1) Hackensack University Medical Center is part of a large healthcare network in New Jersey serving over 6 million people. It has received numerous awards and recognition for clinical excellence.
2) The presentation discusses HackensackUMC's strategies for managing risk-based care and consumerism, which includes a focus on patient engagement, care coordination across settings, and using technology like EHRs and analytics to improve outcomes and reduce costs.
3) HackensackUMC is managing care for over 100,000 beneficiaries through its Medicare ACO, a Blue Cross ACO, and an Aetna Medicare Advantage plan. It aims to shift care toward prevention and meet the growing demands of consumerism through increased access,
Because everyone matters.
IBM Health and Social Programs Summit, October 2014
Stephen Morgan
Senior Vice President and Chief Medical Officer
Carilion Clinic
Jianying Hu
Research Staff Member and Manager of Healthcare Analytics Research
IBM
Paul Grundy
Global Director of Healthcare Transformation
IBM
As the author of “Big Data in Healthcare Hype and Hope,” Dr. Feldman has interviewed over 180 emerging tech and healthcare companies, always asking, “How can your new approach help patients?” Her research shows that data, as an enabling tool, has the power to give us critical new insights into not only what causes disease, but what comprises normal. Despite this promise, few patients have reaped the benefits of personalized medicine. A panel of leading big data innovators will discuss the evolving health data ecosystem and how big data is being leveraged for research, discovery, clinical trials, genomics, and cancer care. Case studies and real-life examples of what’s working, what’s not working, and how we can help speed up progress to get patients the right care at the right time will be explored and debated.
• Bonnie Feldman, DDS, MBA - Chief Growth Officer, @DrBonnie360
• Colin Hill - CEO, GNS Healthcare
• Jonathan Hirsch - Founder & President, Syapse
• Andrew Kasarskis, PhD - Co-Director, Icahn Institute for Genomics & Multiscale Biology; Associate Professor, Genetics & Genomic Studies, Icaahn School of Medicine at Mt. Sinai
• William King - CEO, Zephyr Health
New York eHealth Collaborative Digital Health Conference
November 18, 2014
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.
Challenges and Opportunities Around Integration of Clinical Trials DataCitiusTech
Conducting a Clinical Trial is a complex process, consisting of activities such as protocol preparation, site selection, approval of various authorities, meticulous collection and management of data, analysis and reporting of the data collected
Each activity is benefited from the development of point applications which ease the process of data collection, reporting and decision making. The recent advancements in mobile technologies and connectivity has enabled the generation and exchange of a lot more data than previously anticipated. However, the lack of interoperability and proper planning to leverage this data, still acts as a roadblock in allowing organizations truly harness their data assets. This document will help life sciences IT professionals and decision makers understand challenges and opportunities around clinical data integration
Approach to enable your IT systems for FHIR (HL7 standards) complianceShubaS4
This summary deck discusses a practical, step-by-step approach to transform your IT systems for FHIR (HL7 standards) compliance, API-enablement of your legacy for an accelerated go to market using a library of tools and frameworks under the DigitMarket umbrella. It outlines different integration challenges such initiatives encounter and equips you to plan your compliance roadmap for FHIR.
Patient centricity and digital solutionsAhmed Graouch
Beyond product offerings, it also positions Medtech companies to help hospitals and health systems transition to the future of health through services.
The term “digital twin” refers to the digital version of a physical device or process. By bridging the physical and the virtual worlds, data is transmitted seamlessly allowing the virtual entity to exist simultaneously with the physical device or process. Digital twins are emerging as virtual test beds for
possible solutions before they implement physical devices. These computer-based models are fed individual and population data and mimic the electrical and physical properties of an object.
Medical device companies are using this technology to simulate how their devices are being used in the
clinical setting.
In our view of the future of health, radically interoperable data is likely to play a huge role in transforming health care. Data from medical technologies such as wearables, remote monitors, and
sensors will be standardized, stored, updated, and aggregated with other sources of information such as social media platforms, retailers, and electronic health records.
The combined data will create a complete personal profile that physicians and health systems can use to help ensure that
I deliver health services in an appropriate fashion.
Emerging technologies like smartphones, wearable devices, virtual reality, big data, and cloud computing are enabling a more connected global healthcare system. Smartphones provide personalized health information and tools like medical apps. Wearable devices allow for continuous, unobtrusive health monitoring. Virtual reality and 3D gaming can simulate real-world medical scenarios for education and training. Big data, machine learning, and cloud computing collectively support unlimited data storage, advanced analytics, and on-demand access and sharing of healthcare information on a global scale. These emerging technologies are helping to transition the world toward more informed, connected, and effective healthcare.
Revenue opportunities in the management of healthcare data delugeShahid Shah
Healthcare data is hard to deal with and getting even harder and more expensive. In this presentation, Shahid Shah covers why:
* Healthcare data is going from hard to nearly impossible to manage.
* Applications come and go, data lives forever.
* Data integration is notoriously difficult, even in the best of circumstances, and requires sophisticated tools and attention to detail.
And, then talks about how new techniques are needed to store and manage healthcare data.
Will Yu of Lumiata provides an overview of using real-time big analytics with ever-learning graph combining hundreds of healthcare data sets. Presented at YTH Live 2014 plenary session "Mapping Big Data, Infographics and other Good Stuff."
Big data is impacting the healthcare industry by enhancing efficiency, increasing productivity, and helping anticipate potential issues. The document outlines how big data plays a role in healthcare through benefits like detecting illnesses early, customized treatment, and reducing waste. It also discusses challenges like privacy concerns, fragmented data from different sources, and ensuring data integrity when sharing information.
Development and implementation of a system to support prediction of suicide risk in the Department of Veterans Affairs - DR. Robert Bossarte and Paul Bradley
The use of artificial intelligence in healthcare has the potential to assist healthcare providers in many aspects of patient care and administrative processes as well as improve patient outcomes.
AI analyzes data throughout a healthcare system to mine, automate and predict processes. Some of the use cases are :
1. Early Diagnosis of diseases
2. Improved clinical trial processes
3. Mental health apps etc.
This document discusses big data solutions for healthcare. It outlines trends driving huge increases in healthcare data from sources like medical imaging, patient monitoring, and genomics. This data holds value for personalized medicine, clinical decision support, and fraud detection. However, managing such varied and voluminous data presents challenges around volume, variety, and velocity. The document proposes methods for managing big data through distributed storage, optimization, security, and specialized platforms. Use cases are highlighted for connecting new analytics to healthcare applications and services.
Improving Clinical and Operational Outcomes by Leveraging Healthcare Data Ana...NUS-ISS
Presented by Mr. Sandeep Makhijani, Regional Director for Asia Pacific (APAC), Truven Health Analytics at ISS Seminar: How Analytics is Transforming Healthcare on 31 Oct 2014.
The data explosion along the care cycle (Dell Healthcare)Eric Van 't Hoff
The data explosion along the care cycle
Healthcare data is growing exponentially due to increased digitization of patient records, medical images, lab results, and other clinical information. This data deluge is creating new challenges for healthcare organizations. Specifically:
- Clinicians are overwhelmed by the huge amount of data generated for each patient. Too much information can slow decision making.
- Growing storage in silos makes it difficult to share critical patient data across different systems, which can affect care. Storage and IT costs are rising dramatically.
- Caregivers lack resources to integrate technologies due to being overloaded by growing patient demands.
Dell aims to address these challenges by optimizing healthcare storage architectures. Dell's portfolio includes high performance
HealthSaaS Overview Deck October 2014 (RPM, Home Health)HealthSaaS, Inc.
The HealthSaaS Connected Outcomes Platform removes silo barriers to connect, aggregate and integrate disparate data from mHealth applications and Remote Patient Monitoring (RPM) devices.
Our services provide HIPAA secure data to the “point of care” wherever the clinician is located. Enabling clinicians to rapidly respond to clinically relevant patient health information can facilitate early interventions, reduce hospital admissions, improve outcomes and lower costs.
Our passion empowers us to create eHealth collaboration tools that enhance provider efficiencies, track outcomes and improve the quality of life for patients throughout the continuum of care.
The document discusses how AI and machine learning can help address challenges in healthcare by analyzing complex medical data. It provides examples of how AI can help with tasks like analyzing medical images to assist radiologists, predicting drug response from scans, and using electronic health records to better understand diseases and patient heterogeneity. The document also acknowledges challenges like the need for large labeled datasets and ensuring interpretability and avoidance of bias.
Medical Mobile Apps: The Regulatory StoryNadja Bester
What's life sciences' take on the booming app industry? If regulatory has anything to do with it, it'll start with a whole lot of responsible development.
- Healthcare spending in the US is concentrated among a small portion of the population and must be reduced to control costs. Chronic conditions are a major driver of spending and will continue growing.
- There is an explosion of healthcare data from a variety of sources, but most of this data is unstructured and difficult for computers to interpret. Leveraging this data through analytics could provide insights to improve care and reduce costs.
- Continuous care that extends beyond traditional clinical settings will be needed to effectively manage chronic conditions, which account for most US healthcare costs and 157 million Americans by 2020. Big and small data analytics that incorporate lifestyle, behavioral and socioeconomic factors may help with continuous care and population health management.
At RavenTek, we help healthcare providers secure what matters most, build organizational resilience against cyberattacks and maximize provider Return On Life. We combine world-class technologies, innovative security ideas and a forward-thinking team of problem solvers and consultants to secure healthcare providers. We believe enterprise visibility and persistent, always-on security testing is the essential foundation of every cybersecurity program.
Ryan Coleman is Vice President of Healthcare Cybersecurity at RavenTek.
Providers need to move towards real-time analytics that have become critical to demonstrate their quality of care, as reimbursement by government programs can be contingent upon how providers are measured in “Quality of Care”. For example, the Medicare Access and CHIP Reauthorization Act (MACRA) of 2015, also called the Permanent Doc Fix, changes the way Medicare doctors are reimbursed with the implementation of a merit based incentive. The performance-based pressure is huge, which makes it imperative that every provider consider technology solutions. Read more at https://www.solix.com/solutions/data-driven-solutions/healthcare/
Challenges and Opportunities Around Integration of Clinical Trials DataCitiusTech
Conducting a Clinical Trial is a complex process, consisting of activities such as protocol preparation, site selection, approval of various authorities, meticulous collection and management of data, analysis and reporting of the data collected
Each activity is benefited from the development of point applications which ease the process of data collection, reporting and decision making. The recent advancements in mobile technologies and connectivity has enabled the generation and exchange of a lot more data than previously anticipated. However, the lack of interoperability and proper planning to leverage this data, still acts as a roadblock in allowing organizations truly harness their data assets. This document will help life sciences IT professionals and decision makers understand challenges and opportunities around clinical data integration
Approach to enable your IT systems for FHIR (HL7 standards) complianceShubaS4
This summary deck discusses a practical, step-by-step approach to transform your IT systems for FHIR (HL7 standards) compliance, API-enablement of your legacy for an accelerated go to market using a library of tools and frameworks under the DigitMarket umbrella. It outlines different integration challenges such initiatives encounter and equips you to plan your compliance roadmap for FHIR.
Patient centricity and digital solutionsAhmed Graouch
Beyond product offerings, it also positions Medtech companies to help hospitals and health systems transition to the future of health through services.
The term “digital twin” refers to the digital version of a physical device or process. By bridging the physical and the virtual worlds, data is transmitted seamlessly allowing the virtual entity to exist simultaneously with the physical device or process. Digital twins are emerging as virtual test beds for
possible solutions before they implement physical devices. These computer-based models are fed individual and population data and mimic the electrical and physical properties of an object.
Medical device companies are using this technology to simulate how their devices are being used in the
clinical setting.
In our view of the future of health, radically interoperable data is likely to play a huge role in transforming health care. Data from medical technologies such as wearables, remote monitors, and
sensors will be standardized, stored, updated, and aggregated with other sources of information such as social media platforms, retailers, and electronic health records.
The combined data will create a complete personal profile that physicians and health systems can use to help ensure that
I deliver health services in an appropriate fashion.
Emerging technologies like smartphones, wearable devices, virtual reality, big data, and cloud computing are enabling a more connected global healthcare system. Smartphones provide personalized health information and tools like medical apps. Wearable devices allow for continuous, unobtrusive health monitoring. Virtual reality and 3D gaming can simulate real-world medical scenarios for education and training. Big data, machine learning, and cloud computing collectively support unlimited data storage, advanced analytics, and on-demand access and sharing of healthcare information on a global scale. These emerging technologies are helping to transition the world toward more informed, connected, and effective healthcare.
Revenue opportunities in the management of healthcare data delugeShahid Shah
Healthcare data is hard to deal with and getting even harder and more expensive. In this presentation, Shahid Shah covers why:
* Healthcare data is going from hard to nearly impossible to manage.
* Applications come and go, data lives forever.
* Data integration is notoriously difficult, even in the best of circumstances, and requires sophisticated tools and attention to detail.
And, then talks about how new techniques are needed to store and manage healthcare data.
Will Yu of Lumiata provides an overview of using real-time big analytics with ever-learning graph combining hundreds of healthcare data sets. Presented at YTH Live 2014 plenary session "Mapping Big Data, Infographics and other Good Stuff."
Big data is impacting the healthcare industry by enhancing efficiency, increasing productivity, and helping anticipate potential issues. The document outlines how big data plays a role in healthcare through benefits like detecting illnesses early, customized treatment, and reducing waste. It also discusses challenges like privacy concerns, fragmented data from different sources, and ensuring data integrity when sharing information.
Development and implementation of a system to support prediction of suicide risk in the Department of Veterans Affairs - DR. Robert Bossarte and Paul Bradley
The use of artificial intelligence in healthcare has the potential to assist healthcare providers in many aspects of patient care and administrative processes as well as improve patient outcomes.
AI analyzes data throughout a healthcare system to mine, automate and predict processes. Some of the use cases are :
1. Early Diagnosis of diseases
2. Improved clinical trial processes
3. Mental health apps etc.
This document discusses big data solutions for healthcare. It outlines trends driving huge increases in healthcare data from sources like medical imaging, patient monitoring, and genomics. This data holds value for personalized medicine, clinical decision support, and fraud detection. However, managing such varied and voluminous data presents challenges around volume, variety, and velocity. The document proposes methods for managing big data through distributed storage, optimization, security, and specialized platforms. Use cases are highlighted for connecting new analytics to healthcare applications and services.
Improving Clinical and Operational Outcomes by Leveraging Healthcare Data Ana...NUS-ISS
Presented by Mr. Sandeep Makhijani, Regional Director for Asia Pacific (APAC), Truven Health Analytics at ISS Seminar: How Analytics is Transforming Healthcare on 31 Oct 2014.
The data explosion along the care cycle (Dell Healthcare)Eric Van 't Hoff
The data explosion along the care cycle
Healthcare data is growing exponentially due to increased digitization of patient records, medical images, lab results, and other clinical information. This data deluge is creating new challenges for healthcare organizations. Specifically:
- Clinicians are overwhelmed by the huge amount of data generated for each patient. Too much information can slow decision making.
- Growing storage in silos makes it difficult to share critical patient data across different systems, which can affect care. Storage and IT costs are rising dramatically.
- Caregivers lack resources to integrate technologies due to being overloaded by growing patient demands.
Dell aims to address these challenges by optimizing healthcare storage architectures. Dell's portfolio includes high performance
HealthSaaS Overview Deck October 2014 (RPM, Home Health)HealthSaaS, Inc.
The HealthSaaS Connected Outcomes Platform removes silo barriers to connect, aggregate and integrate disparate data from mHealth applications and Remote Patient Monitoring (RPM) devices.
Our services provide HIPAA secure data to the “point of care” wherever the clinician is located. Enabling clinicians to rapidly respond to clinically relevant patient health information can facilitate early interventions, reduce hospital admissions, improve outcomes and lower costs.
Our passion empowers us to create eHealth collaboration tools that enhance provider efficiencies, track outcomes and improve the quality of life for patients throughout the continuum of care.
The document discusses how AI and machine learning can help address challenges in healthcare by analyzing complex medical data. It provides examples of how AI can help with tasks like analyzing medical images to assist radiologists, predicting drug response from scans, and using electronic health records to better understand diseases and patient heterogeneity. The document also acknowledges challenges like the need for large labeled datasets and ensuring interpretability and avoidance of bias.
Medical Mobile Apps: The Regulatory StoryNadja Bester
What's life sciences' take on the booming app industry? If regulatory has anything to do with it, it'll start with a whole lot of responsible development.
- Healthcare spending in the US is concentrated among a small portion of the population and must be reduced to control costs. Chronic conditions are a major driver of spending and will continue growing.
- There is an explosion of healthcare data from a variety of sources, but most of this data is unstructured and difficult for computers to interpret. Leveraging this data through analytics could provide insights to improve care and reduce costs.
- Continuous care that extends beyond traditional clinical settings will be needed to effectively manage chronic conditions, which account for most US healthcare costs and 157 million Americans by 2020. Big and small data analytics that incorporate lifestyle, behavioral and socioeconomic factors may help with continuous care and population health management.
At RavenTek, we help healthcare providers secure what matters most, build organizational resilience against cyberattacks and maximize provider Return On Life. We combine world-class technologies, innovative security ideas and a forward-thinking team of problem solvers and consultants to secure healthcare providers. We believe enterprise visibility and persistent, always-on security testing is the essential foundation of every cybersecurity program.
Ryan Coleman is Vice President of Healthcare Cybersecurity at RavenTek.
Providers need to move towards real-time analytics that have become critical to demonstrate their quality of care, as reimbursement by government programs can be contingent upon how providers are measured in “Quality of Care”. For example, the Medicare Access and CHIP Reauthorization Act (MACRA) of 2015, also called the Permanent Doc Fix, changes the way Medicare doctors are reimbursed with the implementation of a merit based incentive. The performance-based pressure is huge, which makes it imperative that every provider consider technology solutions. Read more at https://www.solix.com/solutions/data-driven-solutions/healthcare/
Demand connected medical devices to improve military EHRsShahid Shah
This document summarizes a presentation about improving military electronic health records (EHRs) by procuring connected medical devices. The presentation argues that medical devices are the best sources of clinical data but current devices are not designed for connectivity. It recommends changing procurement policies to require devices support inherent connectivity using open standards. This would help fill EHRs with more useful data for research and interoperability.
Healthcare is currently undergoing a transformational metamorphosis. A new era of patient care that is more effective, precise, and patient-centered has arrived because of technological advancements.
Hitachi provides connected health solutions across the patient care continuum from devices and data to analytics and population health management. Their portfolio includes infrastructure, clinical data exchange, mobility and analytics solutions. The goal is to improve patient outcomes by connecting stakeholders and providing actionable insights from data. Population health management is the ultimate aim of reducing healthcare costs through preventative and personalized care enabled by Hitachi's connected health offerings.
Hadoop and Data Virtualization - A Case Study by VHADenodo
Access to full webinar: http://goo.gl/dQjxRe
This webinar by Hortonworks, VHA and Denodo provides information about the functionalities and benefits of Hadoop in Modern Data Architectures; how Hadoop along with data virtualization simplify data management and enable faster data discovery; and what data virtualization can offer in big data projects. VHA explains how they deployed data virtualization and Hadoop together and presents their lessons learned and best practices for data lake and data virtualization deployment.
1) The role of health care data analysts is evolving as the volume of available data grows exponentially. With zettabytes of data being generated, analysts must make sense of both structured and unstructured information.
2) Data analytics can provide insights to improve patient outcomes, lower costs, and enhance the health care experience. Examples show how visualizing data helps health systems better understand utilization and identify at-risk patients.
3) As incentives shift from fee-for-service to value-based models, health systems must transform to focus on population health. Advanced analytics and predictive modeling will be crucial to achieving the goals of better care, lower costs, and improved health.
A look at the key trends and challenges in applying Big Data to transform healthcare by supporting research, self care, providers and building ecosystems. Purchase the report here: https://gumroad.com/l/PlXP
Rise of on demand apps and services in healthcareZymr Inc
As convenience and comfort have become buzzwords among healthcare marketers, the adoption of “on-demand service” model has become a necessity. This presentation highlights the advantages of on-demand medicine apps and sheds some light upon Zymr's Healthcare services.
2016 IBM Interconnect - medical devices transformationElizabeth Koumpan
Emerging technologies such as Internet of Things, 3D Printing are driving the creation of new business models and forcing the Industry for transformation. The product centric model where the Industry main objective was to develop the device, is moving to software and services model, with the focus on Big Data & Analytics, Integration and Cloud.
The maturation of technologies such as social, mobile, analytics, cloud, 3D printing, bio- and nanotechnology are rapidly shifting the competitive landscape. These emerging technologies create an environment that is connected and open, simple and intelligent, fast and scalable. Organizations must embrace disruptive technologies to drive innovation
The document discusses the role of data lakes in healthcare. It defines a data lake as a system that holds large amounts of raw data from various sources in its original format to enable analysis. Data lakes allow healthcare organizations to gain insights from patient outcomes, fraud detection, clinical trials, and more. Examples of potential use cases in healthcare include genomic analytics, improving clinical trials, predictive healthcare costs, creating a 360-degree view of patients, identifying billing opportunities from unstructured text, and psychographic prescriptive modeling. The document outlines best practices for assessing the need for a data lake, planning, implementing, and governing a data lake project in a healthcare organization.
SunflowerLAb - IOT, Big Data Analytics & AI Empowered Digital Healthcare Solu...Sunflower Lab
We, Sunflower Lab, are committed to being your partner from ideation to deployment while we work with you to revolutionize healthcare delivery by offering life-enhancing healthcare product development services. We are a healthcare software development company dedicated to helping you create HIPAA-compliant products that are secure & efficient.
WV transformation slide show may conference2Jack Shaffer
The document discusses West Virginia's vision for transforming its Medicaid program and healthcare system through the use of health information technology and electronic health records by 2020. It outlines strategies around collaboration, open solutions, and innovation to achieve an integrated system with interconnected EHRs, personal health records, telehealth, and mobile access to patient information. Key goals include widespread adoption of EHRs, health information exchange networks, and use of open-source software by 2020.
www.panorama.com
Panorama Necto uncovers the hidden insights in your data and presents them in beautiful dashboards powered with KPI Alerts, which is managed by a the most secure, centralized & state of the art BI solution.
This document discusses healthcare analytics. It begins by defining healthcare analytics as focusing on technologies and processes that measure, manage, and analyze healthcare data to enable more effective and efficient operational and clinical decisions. It then outlines the objectives of healthcare analytics as making decisions data-driven, transparent, verifiable, and robust. The document describes the main types of analytics as descriptive, predictive, diagnostic, and prescriptive. It also lists some common sources of healthcare data and how healthcare companies use analytics to reduce costs, improve patient outcomes, and conduct randomized clinical trials. Emerging technologies discussed include big data, AI/ML, blockchain, and AR/VR. Finally, some existing healthcare analytics tools on the market are briefly described.
How to Choose the Best Healthcare Analytics Software Solution in a Crowded Ma...Health Catalyst
There’s a new trend in the healthcare industry to adopt analytics software solutions to help organizations achieve clinical and financial success. Because of the high demand for analytics, there are many players touting their ability to delivery comprehensive solutions. With so many options available, health systems need to be able to cut through the marketing hype to find tools that provide the best value for their needs. Key solutions include an enterprise data warehouse and analytics software applications (from foundational to discovery to advanced). Other considerations include the organization’s readiness for cultural change, the total cost of ownership required, and the viability of the company providing the technology.
Apervita received Frost & Sullivan's 2015 New Product Innovation Award for its secure, self-service analytics platform that allows healthcare organizations to easily publish, access, and commercialize clinical decision support rules, quality measures, and other analytics. The platform addresses the growing need for affordable, customizable analytics solutions. Apervita received high scores in Frost & Sullivan's evaluation for its strong match to customer needs, ease of use, and ability to empower sharing of best practices.
This presentation summarizes our research on 40 companies from around the world that are leveraging Artificial Intelligence to improve the Healthcare Industry. They are all well-funded, have highly qualified CEOs & Boards, and are poised to achieve their product development milestones.
The I-Square Ventures proprietary rating algorithm indicates that almost all of these companies will receive more funding, and/or be acquired by larger companies.
Connected Health Interoperability Platform_White Paper_Cisco UCSF_2016Wernhard Berger
The document discusses the Connected Health Interoperability Platform (CHIP) being developed by UC San Francisco's Center for Digital Health Innovation and Cisco. The CHIP aims to break down barriers to digital health innovation by creating a platform that connects digital health applications to dispersed patient data through a secure, cloud-hosted system with API services. This will allow applications to access and share data across EHRs, devices, and apps to improve referral management, care collaboration and the patient experience. The platform will include a health applications marketplace, core data and security services, and tools for application development.
Artificial Intelligence and Machine Learning in Healthcare: Four Real-World I...Health Catalyst
This document discusses how artificial intelligence (AI) and machine learning (ML) are improving healthcare outcomes in four key areas:
1) Augmenting leadership decisions by helping identify issues and make future-oriented decisions
2) Overcoming data security challenges by detecting potential privacy violations or attacks
3) Resolving uncompensated care costs by using propensity-to-pay tools to target unpaid accounts
4) Improving patient flow by reducing wait times and avoiding delays through predictive models
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At Apollo Hospital, Lucknow, U.P., we provide specialized care for children experiencing dehydration and other symptoms. We also offer NICU & PICU Ambulance Facility Services. Consult our expert today for the best pediatric emergency care.
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TEST BANK For Accounting Information Systems, 3rd Edition by Vernon Richardso...rightmanforbloodline
TEST BANK For Accounting Information Systems, 3rd Edition by Vernon Richardson, Verified Chapters 1 - 18, Complete Newest Version
TEST BANK For Accounting Information Systems, 3rd Edition by Vernon Richardson, Verified Chapters 1 - 18, Complete Newest Version
TEST BANK For Accounting Information Systems, 3rd Edition by Vernon Richardson, Verified Chapters 1 - 18, Complete Newest Version
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1. DYNAMICS INTELLIGENCE
“The US federal government estimates that
federal health care spending will increase 80
percent from $918B in 2015 to $1.7T in 2025.”
HEALTHIER CLOUD
PATENT PENDING
2. OUR TEAM
Copyright 2018 – Dynamics Intelligence Inc http://www.dynamicsintelligence.us
Jenna Bourgeois, CEO & Lead Technical Architect, MCT
Arthur Burris Jr, MBA
• Global IT Exec, General Motors
Karen Wainwright
• Partner Success Mgr, Visibility Software
Diane Moore, MBA, Healthcare
• CEO, Big Bend Regional Hospital
Mylene Salamero, MBA
• Market Development Lead, Medtronic
Marylyn Harris, RN, MBA, MSN
CEO, Harrland Companies
David Sterling
• Principle, Sterling International Consulting Group
Lisa Litherland, MBA
Business Architect (IoT), CDW
Mahjoubeh Jalali, PhD
• Scientist, Pacific Northwest Research Institute
Surabhi Maheshwari, PhD
• Scientist, Pacific Northwest Research Institute
Debra Mahan, MSN
• Healthcare Management Consultant, JRM Consulting
Stan Spotts, MBA
• Technical Architect, Reed Tech
Jenna Bourgeois, CEO & Lead Technical Architect,
MCT
Dev Ramsumair
Ellen Pekilis, Attorney
Susan Underhill, MBA
Consultant, Lough Barnes Consulting Group
Christian Millar, MCT
• CEO, Systems Center Consultants
Chiraq Kariya, PhD
• Clinical Trials Mgr, University of British Columbia & BC Children’s
Hospital Research Institute
Alexander Maxan, PhD Candidate
• Neuroscientist, Universite de Laval
Edwin Gershom, PhD
• Co-founder, RXFulcrum
USA Canada
Diversity
Statistics:
USA
Women - 9
Men - 3
CANADA
Women - 3
Men – 5
50% visible
minority
27.8% LGBTQ
PhD’S – 6
Master’s
Degrees - 14
3. 500,000
Children under 5
die by the end of
this year due to lack
of adequate
healthcare
Only 1/3
of people Have
Universal Heath
Coverage
40
Million
of the 56 million
global deaths in
2015 were due to
NCDs
<50% of
Children
with suspected
pneumonia are
taken to an
appropriate
healthcare provider
About
40%
of WHO Member
States report to
have less than 1
physician per 1000
population
17 Million
Is how many
healthcare workers
are needed globally
80%
of premature heart
disease, stroke and
diabetes can be
prevented.
Noncommunicable
Diseases On the Rise
GLOBAL HEALTH CHECKUP
- Heart
disease
- Stroke
- Cancer
- Diabetes
- Chronic
Respiratory
Source: World Health Organization
4. TODAY’S HEALTHCARE PROBLEM
250,000
Patients die due to
medical error each
year (US). 3rd
leading cause of
death
Garbage In
/ Garbage
Out
Existing EHR’s are
useless for AI
Costly & Time
Consuming
Identifying research
patient populations
takes weeks and
months
Lack of
Interoperability
Patient records
aren’t portable
between hospitals
Non-
Patient
Centric
Patients don’t own
or control their data
Wrong
Diagnosis
No way to identify
a wrong diagnosis
in current data
standards skewing
AI/Machine
Learning
Data
Separation
Today, research
data is not
commingled with
clinical data making
digital inferences
more difficult
Data
Silos
prevent
comprehensive
data analysis
TODAY’S HEALTHCARE PROBLEM
Copyright 2018 – Dynamics Intelligence Inc http://www.dynamicsintelligence.us
6. OUR APPROACH
•Emphasize a global solution as opposed to a US-centric one
•Data Science As A Service
Global Solution From Day 1
•Continually Add Functionality to Support Customer Needs
•Users will populate data because they receive high value from uploads
Listen to Customers
•Microsoft AzureLeverage Latest Technology
•Simple percentage added to transactions that run through the system
•Recurring revenue model
Pricing Strategy
•Strategic Partnership with Microsoft is Critical and presents a competitive advantage over Google, Apple,
and Amazon
•This industry will transition within 3 years, so we have to move fast and focus on grabbing market share.
Competitive Strategy
8. HEALTHieR
Cloud
(Researcher
View)
Manage Global
Population
Queries
Manage
Studies
Manage Study
Participants
Publish
Research
Manage
Machine
Learning
Manage
Research
Database
Queries
Spatial
Epidemiology
BioMarker
Database
Curated
Databases
RESEARCHER VIEW
Today, it takes a significant
amount of a researcher’s time to
locate and obtain patient data.
Having access to good quality data
is critical to the success of any
machine learning or artificial
intelligence routine. When
researchers publish, it amounts to
a pdf file along with a link to a
website containing data files from
a wide variety of formats.
Dynamics Intelligence HEALTHieR
Cloud changes how researchers
publish. With HEALTHieR Cloud,
researchers will publish using a set
of tools resulting in algorithms and
data that is available to other
researchers immediately.
Using HEALTHieR Cloud’s global
population clinical data,
researchers can quickly identify
patients who have an Alzheimer’s
biomarker as well as a diabetes
biomarker, for example.
9. HEALTHieR
Cloud (Hospital
View)
Manage Global
Population Queries
Upload/Download
Patient EHR
Upload/Download
Workflows
Reporting/Analytics
Global Logistics
• Organ Transplants
• 3rd Party Supplies
Ordering
EMS Interoperability
3rd Party Integration
Regional
Compliance
Automatic Data
Archiving
HEALTHieR Cloud doesn’t replace existing clinical
systems. Rather, it enhances the clinical systems
that are already there. HEALTHieR Cloud exposes a
series of API’s that contain research data and other
information such as clinical workflows from
specialty hospitals.
Hospitals can upload and download data using
industry standards such as FHIR. Using the global
logistics features, hospitals can leverage the
HEALTHieR Cloud to facilitate business to business
transactions with suppliers.
Administrators will enjoy the variety of analytics
and reports that they can generate from the system
for comparative analysis. Having access to better
patient data will reduce hospital operating costs.
Complying with regulations is made easier through
HEALTHieR Cloud’s compliance tools. HEALTHieR
Cloud is HIPAA and GDPR Compliant.
Integration with EMS will increase the real-time
data integration between hospitals and EMS.
HOSPITAL VIEW
10. HEALTHieR
Cloud (Provider
View)
Query Global
Population
View Latest Research
5 Similar Cases from
Global Population
(Artificial
Intelligence)
Analytics
Virtual Reality
(Hololens)
Augmented Reality
(Hololens)
Manage Voice
Commands
View Patient EHR
Review Auto-
diagnosis
Create Your Own
Mobile App
HEALTHieR Cloud is designed with providers in
mind. Physicians today are overworked, tired, and
frustrated at how complicated systems have
become. With the HEALTHieR Cloud, physicians can
connected the clinical system of their choice or
create their own mobile app with no coding.
Treating patients has never been easier with the
assistance of artificial intelligence that
automatically recommends five similar cases from
the global population that detail the diagnosis,
treatment, and prognosis. Physicians can peruse
the research data to treat rare cases.
For specialists and surgeons, how we provide health
has changed forever. While most are concentrated
in the US, through the HEALTHieR Cloud, they will
be able to serve a global population. Imagine part
of a Da Vinci robotic surgery machine in the US and
the other part in Zimbabwe. Or, images scanned in
Moldava will be interpreted in real-time by
specialists in the US. With HEALTHieR Cloud,
healthcare becomes a distributed paradigm.
PROVIDER VIEW
11. HEALTHieR
Cloud (Patient
View)
Manage EHR
Learn About Your
Condition
Share Your Data
With Your Provider
Participate In
Research Study
Attach Your Favorite
FHIR Device
Voice Patient
Check-In
Provide Feedback
View Health
Recommendations
Connect Your
Biometric
Diagnostic Device
PATIENT VIEW
We designed HEALTHieR Cloud so that patients
own and control their own data. No one will have
access to a patient’s records unless they choose to
share them. Patients will be able to share their data
with any provider in the world.
With the massive amount of research data available,
patients can drill down and learn about their own
condition and may participate in research studies
with the click of a button using their favorite FHIR
compatible device.
Voice enabled patient check-in, captures the
patient’s testimony, automatically analyzes the text
and attaches it to the patient’s clinical record.
Patients can provide feedback about provider
performance.
By connecting their biometric diagnostic device,
patients can attach real-time data to their clinical
record, something that is not possible today.
HEALTHieR Cloud will increase the likelihood of
positive patient outcomes, potentially saving
thousands of lives.
12. HEALTHieR
Cloud
(Government
View)
Report Builder
Analytics
Manage Public
Health
Warnings
Publish
Approved
Medications
Publish
Approved
Medical
Devices
Disease
Notification
Event Hub
HEALTHieR Cloud simplifies national health by
providing real-time data analytics, alerts,
information, and the ability to regulate by
publishing to the HEALTHieR Cloud’s business rules
environment. With the Global Disease Notification
Hub, public officials can monitor spatial
epidemiology in real-time. Researchers can quickly
attend to rare outbreaks, since the clinical data is
readily accessible from the HEALTHieR Cloud.
Using the report builder, public policy makers can
generate reports in real-time or analyze data using
Microsoft Power BI.
Public administrators can stop prescription
medications in real-time by leveraging the
HEALTHieR Cloud’s business rules engine.
HEALTHieR Cloud stores patient data in the region
where it originated. To comply with regional
regulations, HEALTHieR Cloud de-identifies any
data used for research purposes.
GOVERNMENT VIEW
13. HEALTHieR
Cloud (System
View)
Global
Predictive
Analysis
Global
Analytics
Regional
Analytics
Patient EHR
De-
identification
Encryption
Authentication
Authorization
Data Archiving
Research Data
FHIR
Global
Electronic
Health Record
Schema (GEHR)
Patient Survey
EHR language
translation
Workflow
Repository
Hololens
Repository
Device Data
Repository
Prescription
Drug
Repository
Algorithms
Repository
Protocols
Repository
Regulatory
Compliance
Cyber Threat
Detection
Anatomy SYSTEM VIEW
The Dynamics Intelligence HEALTHieR Cloud is
designed to be the most sophisticated global health
repository on the planet and represents the next
generation internet. Powered by Microsoft Azure,
the HEALTHieR Cloud is built upon the most secure
cloud infrastructure in the world and is available to
the global population through state of the art data
centers in 140 countries.
With over $1 billion USD spent on Azure security,
patients can rest assured that their data is protected.
All records in the HEALTHieR Cloud are archived
according to regional regulations.
Patient records are automatically translated for up
to 60 languages, so that providers can review
records in their preferred language.
16. Customer Name Work Performed
Best Doctors Provided technical training to their IT staff
Cambia Health Provided technical training to their IT staff
IOD Dynamics CRM Consulting
Marshfield Clinic Wrote and published custom course materials for nursing staff.
Provided instructor led training in two sessions.
Logistics Health Jenna Bourgeois, CEO, was Logistics Health's Enterprise Architect
responsible for their clinical management system.
Mayo Clinic Wrote an auto-diagnosis system for the Mayo Clinic's molecular
genetics laboratory
Nelson Labs Dynamics CRM Consulting
Oklahoma Heart Hospital Provided technical training to their IT staff
Affinity Health Provided technical training to their IT staff
Gundersen Lutheran Provided technical training to their IT staff
Lakeview Medical Center Provided technical consulting and training
Wausau Benefits Provided technical training to their IT staff
Thermo Fischer Provided technical training to their IT staff
17. Electronic Health Record Comparison Dynamics Intelligence
HEALTHieR Cloud
(Powered by Microsoft)
Apple
Health Record
Google
FHIR Compatible Yes Yes Yes
Doctors Can Design Their Own App
With No Coding
Yes No No
Integrated Research Data Yes No No
Automatic Language Translation Yes No No
Global Electronic Health Record Yes No No
Available in 140 Countries Yes No No
Ability to Attach 3rd Party AI Yes No No
Auto Pre-diagnosis Yes No No
Research Publishing Yes No No
Faceted Search Yes No No
GDPR Compliant Yes No No
Connect Your Own App Yes No No
Auto Archiving Yes No No
Enhanced Patient Data Schema Yes No No
Highly Secure Yes No No
Alexa, Cortana Voice Integration Yes No No
Integrate with existing 3rd Party Medical Apps Yes No No
HIPAA Compliance Yes No No
Patients Own Their Data Yes No No
IoT Integration Yes No No
18. FURTHER READING
1. The Role of Big Data and Mobile Apps in Healthcare
2. Leveraging Natural Language Processing Uncover Social Determinants Health
Insights
3. Microsoft AI to Build A Lung Disease Prediction Model Using Chest XRay
4. Gene Editing
5. Which Healthcare Data Is Important for Population Health Management
6. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3679597/
7. Cloud Cost Control Means Teaming Vendors
8. A Tale of Two Hospitals That Adopted Apple's Health Record App
9. Epic Isn't As Epic As It Thinks
10. Q&A with Stanford Dean Dr. Lloyd
11. Big Data Is the Future of Healthcare
12. EHR Market Needs Competition
13. Detecting Breast Cancer with a Deep Learning