HealthSaaS is a thought leader in healthcare interoperability solutions that enable
meaningful exchange of patient-driven data. The HealthSaaS Cognitive Patient
Monitoring Platform* combines sophisticated technology with simplicity and ease
of use for patient and provider populations. Its cloud‐based IoT services, powered
by Microsoft Azure* and based on the Intel® Health Application Platform and Flex*
Edge Compute Engine, are designed to meet the specific requirements of health IT
companies, clinicians, hospitals, pharmacies, and home health organizations. The
result is a secure, vendor‐neutral infrastructure that provides just-in-time data to
facilitate interventions and reduce readmissions for the chronic condition patient.
At eClinicalWorks, we are 5,000 employees dedicated to improving healthcare together with our customers. More than 130,000 physicians nationwide — and more than 850,000 medical professionals around the globe — rely upon us for comprehensive clinical documentation, along with solutions for Practice Management, Population Health, Patient Engagement, and Revenue Cycle Management.
This document discusses trends in digitizing healthcare, including adopting electronic medical records and mobile health technologies. It describes investment in healthcare IT in various countries and regions, focusing on China. The opportunities of transforming healthcare through more integrated systems with better quality of care and outcomes are outlined. The document promotes using multifunction printers and analytics platforms to capture paper documents, simplify workflows, and unlock insights from structured and unstructured clinical data through searching, automated outputs, and personalized patient engagement.
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.
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.
Big data in healthcare refers to large, diverse, and complex datasets that are difficult to analyze using traditional methods. The healthcare industry generates huge amounts of data from sources like electronic health records, medical imaging, and fitness trackers. Analyzing this big data can help improve patient outcomes, reduce costs, and advance personalized medicine. However, healthcare also faces challenges like data silos, privacy concerns, and resistance to change. Opportunities include disease prediction and prevention, reducing readmissions and fraud, and optimizing care through remote monitoring. Some organizations are starting to see benefits from big data initiatives focused on areas like evidence-based treatment and integrated health records.
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
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.
In today’s healthcare market, financial challenges rank as the number one issue hospitals face. To maintain a margin to support their mission, hospital CEOs must always be on the lookout for opportunities to boost revenue through improved reimbursement. In this webinar, Thibodaux Regional Medical Center’s Greg Stock, president and chief executive officer, and Mikki Fazzio, director, HIM and clinical documentation improvement, as they share how Thibodaux Regional leveraged analytics to provide actionable feedback to continuously improve the process, and how you can too.
Managing ‘discharged not final billed’ (DNFB) cases is one important way hospitals can improve financial performance by increasing collection on bills with incomplete payment due to coding or documentation gaps. Historically, Thibodaux Regional’s DNFB caseload had reached 500 cases per month, with about a third of patients discharged without a completed bill due either to missing documentation or incomplete coding. Thibodaux Regional tackled this process problem by expanding the use of analytics to measure and track every aspect of their billing services. The results were impressive and sustainable. Three years after launching its initial DNFB redesign effort, Thibodaux Regional has realized $2.4M in additional annual reimbursement and a 61% relative reduction in DNFB dollars, as well as a 6.2 reduction in AR days, resulting in significantly improved cash flow.
View this webinar to learn how to:
- Increase reimbursement levels by optimizing workflow analytics
- Ease the documentation burden on overloaded physicians with time-efficient communication
- Provide critical analytics visibility to key stakeholders
At eClinicalWorks, we are 5,000 employees dedicated to improving healthcare together with our customers. More than 130,000 physicians nationwide — and more than 850,000 medical professionals around the globe — rely upon us for comprehensive clinical documentation, along with solutions for Practice Management, Population Health, Patient Engagement, and Revenue Cycle Management.
This document discusses trends in digitizing healthcare, including adopting electronic medical records and mobile health technologies. It describes investment in healthcare IT in various countries and regions, focusing on China. The opportunities of transforming healthcare through more integrated systems with better quality of care and outcomes are outlined. The document promotes using multifunction printers and analytics platforms to capture paper documents, simplify workflows, and unlock insights from structured and unstructured clinical data through searching, automated outputs, and personalized patient engagement.
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.
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.
Big data in healthcare refers to large, diverse, and complex datasets that are difficult to analyze using traditional methods. The healthcare industry generates huge amounts of data from sources like electronic health records, medical imaging, and fitness trackers. Analyzing this big data can help improve patient outcomes, reduce costs, and advance personalized medicine. However, healthcare also faces challenges like data silos, privacy concerns, and resistance to change. Opportunities include disease prediction and prevention, reducing readmissions and fraud, and optimizing care through remote monitoring. Some organizations are starting to see benefits from big data initiatives focused on areas like evidence-based treatment and integrated health records.
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
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.
In today’s healthcare market, financial challenges rank as the number one issue hospitals face. To maintain a margin to support their mission, hospital CEOs must always be on the lookout for opportunities to boost revenue through improved reimbursement. In this webinar, Thibodaux Regional Medical Center’s Greg Stock, president and chief executive officer, and Mikki Fazzio, director, HIM and clinical documentation improvement, as they share how Thibodaux Regional leveraged analytics to provide actionable feedback to continuously improve the process, and how you can too.
Managing ‘discharged not final billed’ (DNFB) cases is one important way hospitals can improve financial performance by increasing collection on bills with incomplete payment due to coding or documentation gaps. Historically, Thibodaux Regional’s DNFB caseload had reached 500 cases per month, with about a third of patients discharged without a completed bill due either to missing documentation or incomplete coding. Thibodaux Regional tackled this process problem by expanding the use of analytics to measure and track every aspect of their billing services. The results were impressive and sustainable. Three years after launching its initial DNFB redesign effort, Thibodaux Regional has realized $2.4M in additional annual reimbursement and a 61% relative reduction in DNFB dollars, as well as a 6.2 reduction in AR days, resulting in significantly improved cash flow.
View this webinar to learn how to:
- Increase reimbursement levels by optimizing workflow analytics
- Ease the documentation burden on overloaded physicians with time-efficient communication
- Provide critical analytics visibility to key stakeholders
Explains about Evolution of IT in Healthcare, how analytics can make a difference and evolution of IT in healtcare. For more information visit: http://www.transformhealth-it.org/
Evidence Based Clinical Decision Support – An Enabler for Clinicians in 21st Century by Dr. Lalit Singh, Director for Content & Product Strategy, Elsevier, India
Effective Population Health Management Means Being Able to Predict the FutureCitiusTech
This document discusses predictive analytics in population health management. It begins by stating that predictive analytics can reduce expenditures and enhance patient quality of life. It then outlines the key components of predictive analytics for PHM including patient data integration, data cleansing, building predictive models using artificial intelligence, and creating dashboards. Examples of applying predictive analytics include predicting mortality for heart patients, influenza outbreaks, and reducing hospital readmissions. Challenges to implementing predictive analytics in healthcare include lack of budget, incomplete data, and lack of skilled employees. The document concludes that predictive analytics has potential to revolutionize healthcare by predicting future health issues.
A Reference Architecture for Digital Health: The Health Catalyst Data Operati...Health Catalyst
The document discusses Health Catalyst's Data Operating System (DOSTM) which is a digital health platform designed to integrate data from over 300 different sources and support analytics, clinical workflows, and data interoperability/portability. The DOSTM aims to provide a single consistent platform for healthcare data to enable improved analytics, reduce total cost of ownership compared to disparate systems, and advance the vision of a comprehensive digital understanding of patient health. The document outlines some of the strategic options and challenges for building a healthcare digital platform at this scale and discusses how the DOSTM addresses these challenges through its design and capabilities.
AI in Healthcare | Future of Smart Hospitals Renee Yao
In this talk, I specifically talk about how NVIDIA healthcare AI software and hardware were used to support healthcare AI startups' innovation. Three startups featured: Caption Health, Artisight, and Hyperfine. Audience: healthcare systems CXOs.
The Learning Health System: Thinking and Acting Across ScalesPhilip Payne
A Learning Health System (LHS) can be defined as an environment in which knowledge generation processes are embedded into daily clinical practice in order to continually improve the quality, safety, and outcomes of healthcare delivery. While still largely an aspirational goal, the promise of the LHS is a future in which every patient encounter is an opportunity to learn and improve that patient’s care, as well as the care their family and broader community receives. The foundation for building such an LHS can and should be the Electronic Health Record (EHR), which provides the basis for the comprehensive instrumentation and measurement of clinical phenotypes, as well as a means of delivering new evidence at the patient- and population levels. In this presentation, we will explore the ways in which such EHR-derived phenotypes can be combined with complementary data across a spectrum from biomolecules to population level trends, to both generate insights and deliver such knowledge in the right time, place, and format, ultimately improving clinical outcomes and value.
This document discusses using MQTT, Hadoop, and machine learning DSLs for large scale health telemetry and analytics. It presents an architecture using sensors, devices, and data streams to ingest data and perform predictive analytics and visualization. Demos are shown for telemetry/visualization, regression on allergies, and predictive analytics using DSLs. The document concludes by discussing opportunities in digital health trends like predictive analytics and the Internet of Medical Things, and next steps in interoperability, precision medicine, and population health.
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 survey polled over 50 health systems to understand AI/ML adoption, challenges, and outlook. Key findings include:
- AI/ML adoption is higher among large health systems (> $1B revenue), with 71% of systems over $4B having adopted it
- Lack of clear use cases and ROI, skills shortage, and technology selection are top challenges for CIOs
- Clinical performance and operational improvements are top priority domains for seeing ROI from AI/ML
- While few health systems have large dedicated AI/ML teams now, 75% of large systems plan significant team growth in 3 years
What the ONC's Proposed Rule on Information Blocking Means for Your WorkHealth Catalyst
Information blocking has been a hot-button issue for years as it has impeded innovation and patient healthcare options for too long. The 21st Century Cures Act (Cures Act) sought to eliminate these problems but information blocking persisted. However, in February 2019 the Office of the National Coordinator for Health Information Technology (ONC) announced a proposed rule with consequences to non-compliance with the Cures Act that may finally force true interoperability. As a healthcare decision maker you have a real opportunity to build an innovation strategy around these changes. To learn how, view this webinar.
True data interoperability enables innovation and better patient experience. In aggregate, both of these activities have the potential to accelerate the shift away from fee-for-service and towards fee-for-value healthcare. Dan Orenstein has spent much of his career providing legal counsel to healthcare organizations on regulatory and risk management issues as well as how to implement growth initiatives that comply with healthcare laws and regulations. That experience has made him an expert in applying policy to healthcare strategy. He has studied the proposed rule and in this webinar he will provide a summary of the existing legislation, implications of non-compliance with the proposed rule as well as insight into putting it into practice.
View this webinar and learn:
- To identify information blocking practices
- Seven exceptions to the information blocking provision and how they may apply to your work
- Summary of the public comments about the proposed rule and the overall perception of it in the industry
- The potential impact to your healthcare organization
Link to the recorded webinar - https://youtu.be/RE6j3tF1MHA
Topics for this webinar include:
• How to integrate existing HIE data in the Health Catalyst analytics platform, DOS™ (Data Operating System)
• Gaining insights from HIE data that can drive outcome improvements
• Existing applications and tools available that can leverage HIE data
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.
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.
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/
Platforms and Partnerships: The Building Blocks for Digital InnovationHealth Catalyst
Virtually all service-oriented industries have experienced massive disruption and transformation, resulting from the confluence of digital, mobile, cloud, data, and consumerization. And then there’s healthcare…
In this webinar Ryan Smith, executive advisor at Health Catalyst, shares practical insights gained from his combined 25 years of IT and digital leadership roles at Banner Health and Intermountain Healthcare. He explores why our industry is struggling to provide the tools and self-service experiences that patients and consumers have come to expect in every other aspect of their lives. To attract and retain patients and members, healthcare organizations need to “shift gears” and go on the digital offensive to sustain brand loyalty; however, decades of siloed, monolithic approaches to implementing technology and managing data continue to hamper industry progress.
During this session, Ryan shares his approach for building business support to enable digital transformation.
By viewing this webinar, you will learn key digitization concepts:
- How to conceptualize a digital enablement framework.
- Ten strategic guiding principles for technology leaders.
- Why it’s vital to create business-driven technology governance.
- Why building strategic vendor partnerships really matters.
- How to apply case studies to bolster digital investments.
Your EMR/EHR is implemented, what’s next?Sally Akers
This document discusses next steps for organizations after implementing an electronic health record (EHR) system. It outlines a three-phase approach:
1) Stabilize the EHR system in the near term by focusing on speed, reliability and user interface to allow clinicians to work efficiently.
2) Create a comprehensive health record in the mid-term by integrating all patient data into a single longitudinal record.
3) Continuously enhance care in the long term by using data to improve quality and efficiency of healthcare delivery.
The document also discusses enabling nationwide health information exchange and providing tools to optimize use of clinical data and evidence for decision-making.
HIS EHR Assessment Framework has come out of my doing HIS EHR Assessments again and again over the past 2 decades across North America, Germany, GCC, Indonesia and India. It is a Heuristic check that tells me the breadth and depth of the HIS EHR system in question. I have Excel checklists to support this framework. Though it is not an exhaustive checklist covering everything out there in the field of HIS EHR. Sharing it here for my fellows. Feel free to use it. Just pass the credits back to me with every use. Give me feedback to enhance and improve it further. Knowledge is the only form of power that grows by using it.
Cloud Platform for Remote Patient Monitoring. Case: Stroke Remote Care.pselonen
Presentation at AI morning in April 13th at Tampere University of Technology Kampusklubi.
"AI Morning in April 13th experiments with a new distinctive concept and remixes together machine learning and analytics in the two verticals of healthcare and industry! There is a huge common ground in diagnostics of people and machines, and the same algorithms can be used in both. The presenters from healthcare and industry keynote a conversational networking forum in theme: 'Health: analytics'."
See http://www.aiaamu.fi/
This document discusses machine learning and artificial intelligence. It defines machine learning as using algorithms to learn from data without being explicitly programmed, while artificial intelligence is defined as machines exhibiting human-like intelligence. The document discusses typical uses of each and differences between them. It also covers machine learning misconceptions, when models learn and should be retrained, common pitfalls, and potential healthcare applications of machine learning techniques. Polls are included to gauge audience experience with and perspectives on machine learning.
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.
Healthcare and AWS: The Power of Cloud in Patient Care and Data ManagementSuccessiveDigital
1. The document discusses how cloud platforms like AWS can help healthcare organizations better manage patient data and deliver advanced patient care. It provides examples of how moving to the cloud improves data accessibility, analytics, mobility and enables telehealth solutions.
2. Key benefits of cloud-based healthcare data management include dismantling data silos, facilitating data sharing and integration, providing scalability, and allowing data to be easily accessible anywhere to support new care delivery models.
3. The cloud empowers patient engagement through tools that collect health data from devices. It also improves care management by enabling real-time communication and collaboration between healthcare providers.
This document discusses the importance of databases in healthcare information systems (HIS). Databases allow for efficient collection and storage of patient data, easy exchange of information between healthcare providers, and monitoring to improve quality of care. They enable quick access to patient records, reduce paperwork, and help with diagnosis, treatment, and billing. Overall, well-designed healthcare databases improve efficiency, care quality, and health outcomes.
Explains about Evolution of IT in Healthcare, how analytics can make a difference and evolution of IT in healtcare. For more information visit: http://www.transformhealth-it.org/
Evidence Based Clinical Decision Support – An Enabler for Clinicians in 21st Century by Dr. Lalit Singh, Director for Content & Product Strategy, Elsevier, India
Effective Population Health Management Means Being Able to Predict the FutureCitiusTech
This document discusses predictive analytics in population health management. It begins by stating that predictive analytics can reduce expenditures and enhance patient quality of life. It then outlines the key components of predictive analytics for PHM including patient data integration, data cleansing, building predictive models using artificial intelligence, and creating dashboards. Examples of applying predictive analytics include predicting mortality for heart patients, influenza outbreaks, and reducing hospital readmissions. Challenges to implementing predictive analytics in healthcare include lack of budget, incomplete data, and lack of skilled employees. The document concludes that predictive analytics has potential to revolutionize healthcare by predicting future health issues.
A Reference Architecture for Digital Health: The Health Catalyst Data Operati...Health Catalyst
The document discusses Health Catalyst's Data Operating System (DOSTM) which is a digital health platform designed to integrate data from over 300 different sources and support analytics, clinical workflows, and data interoperability/portability. The DOSTM aims to provide a single consistent platform for healthcare data to enable improved analytics, reduce total cost of ownership compared to disparate systems, and advance the vision of a comprehensive digital understanding of patient health. The document outlines some of the strategic options and challenges for building a healthcare digital platform at this scale and discusses how the DOSTM addresses these challenges through its design and capabilities.
AI in Healthcare | Future of Smart Hospitals Renee Yao
In this talk, I specifically talk about how NVIDIA healthcare AI software and hardware were used to support healthcare AI startups' innovation. Three startups featured: Caption Health, Artisight, and Hyperfine. Audience: healthcare systems CXOs.
The Learning Health System: Thinking and Acting Across ScalesPhilip Payne
A Learning Health System (LHS) can be defined as an environment in which knowledge generation processes are embedded into daily clinical practice in order to continually improve the quality, safety, and outcomes of healthcare delivery. While still largely an aspirational goal, the promise of the LHS is a future in which every patient encounter is an opportunity to learn and improve that patient’s care, as well as the care their family and broader community receives. The foundation for building such an LHS can and should be the Electronic Health Record (EHR), which provides the basis for the comprehensive instrumentation and measurement of clinical phenotypes, as well as a means of delivering new evidence at the patient- and population levels. In this presentation, we will explore the ways in which such EHR-derived phenotypes can be combined with complementary data across a spectrum from biomolecules to population level trends, to both generate insights and deliver such knowledge in the right time, place, and format, ultimately improving clinical outcomes and value.
This document discusses using MQTT, Hadoop, and machine learning DSLs for large scale health telemetry and analytics. It presents an architecture using sensors, devices, and data streams to ingest data and perform predictive analytics and visualization. Demos are shown for telemetry/visualization, regression on allergies, and predictive analytics using DSLs. The document concludes by discussing opportunities in digital health trends like predictive analytics and the Internet of Medical Things, and next steps in interoperability, precision medicine, and population health.
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 survey polled over 50 health systems to understand AI/ML adoption, challenges, and outlook. Key findings include:
- AI/ML adoption is higher among large health systems (> $1B revenue), with 71% of systems over $4B having adopted it
- Lack of clear use cases and ROI, skills shortage, and technology selection are top challenges for CIOs
- Clinical performance and operational improvements are top priority domains for seeing ROI from AI/ML
- While few health systems have large dedicated AI/ML teams now, 75% of large systems plan significant team growth in 3 years
What the ONC's Proposed Rule on Information Blocking Means for Your WorkHealth Catalyst
Information blocking has been a hot-button issue for years as it has impeded innovation and patient healthcare options for too long. The 21st Century Cures Act (Cures Act) sought to eliminate these problems but information blocking persisted. However, in February 2019 the Office of the National Coordinator for Health Information Technology (ONC) announced a proposed rule with consequences to non-compliance with the Cures Act that may finally force true interoperability. As a healthcare decision maker you have a real opportunity to build an innovation strategy around these changes. To learn how, view this webinar.
True data interoperability enables innovation and better patient experience. In aggregate, both of these activities have the potential to accelerate the shift away from fee-for-service and towards fee-for-value healthcare. Dan Orenstein has spent much of his career providing legal counsel to healthcare organizations on regulatory and risk management issues as well as how to implement growth initiatives that comply with healthcare laws and regulations. That experience has made him an expert in applying policy to healthcare strategy. He has studied the proposed rule and in this webinar he will provide a summary of the existing legislation, implications of non-compliance with the proposed rule as well as insight into putting it into practice.
View this webinar and learn:
- To identify information blocking practices
- Seven exceptions to the information blocking provision and how they may apply to your work
- Summary of the public comments about the proposed rule and the overall perception of it in the industry
- The potential impact to your healthcare organization
Link to the recorded webinar - https://youtu.be/RE6j3tF1MHA
Topics for this webinar include:
• How to integrate existing HIE data in the Health Catalyst analytics platform, DOS™ (Data Operating System)
• Gaining insights from HIE data that can drive outcome improvements
• Existing applications and tools available that can leverage HIE data
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.
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.
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/
Platforms and Partnerships: The Building Blocks for Digital InnovationHealth Catalyst
Virtually all service-oriented industries have experienced massive disruption and transformation, resulting from the confluence of digital, mobile, cloud, data, and consumerization. And then there’s healthcare…
In this webinar Ryan Smith, executive advisor at Health Catalyst, shares practical insights gained from his combined 25 years of IT and digital leadership roles at Banner Health and Intermountain Healthcare. He explores why our industry is struggling to provide the tools and self-service experiences that patients and consumers have come to expect in every other aspect of their lives. To attract and retain patients and members, healthcare organizations need to “shift gears” and go on the digital offensive to sustain brand loyalty; however, decades of siloed, monolithic approaches to implementing technology and managing data continue to hamper industry progress.
During this session, Ryan shares his approach for building business support to enable digital transformation.
By viewing this webinar, you will learn key digitization concepts:
- How to conceptualize a digital enablement framework.
- Ten strategic guiding principles for technology leaders.
- Why it’s vital to create business-driven technology governance.
- Why building strategic vendor partnerships really matters.
- How to apply case studies to bolster digital investments.
Your EMR/EHR is implemented, what’s next?Sally Akers
This document discusses next steps for organizations after implementing an electronic health record (EHR) system. It outlines a three-phase approach:
1) Stabilize the EHR system in the near term by focusing on speed, reliability and user interface to allow clinicians to work efficiently.
2) Create a comprehensive health record in the mid-term by integrating all patient data into a single longitudinal record.
3) Continuously enhance care in the long term by using data to improve quality and efficiency of healthcare delivery.
The document also discusses enabling nationwide health information exchange and providing tools to optimize use of clinical data and evidence for decision-making.
HIS EHR Assessment Framework has come out of my doing HIS EHR Assessments again and again over the past 2 decades across North America, Germany, GCC, Indonesia and India. It is a Heuristic check that tells me the breadth and depth of the HIS EHR system in question. I have Excel checklists to support this framework. Though it is not an exhaustive checklist covering everything out there in the field of HIS EHR. Sharing it here for my fellows. Feel free to use it. Just pass the credits back to me with every use. Give me feedback to enhance and improve it further. Knowledge is the only form of power that grows by using it.
Cloud Platform for Remote Patient Monitoring. Case: Stroke Remote Care.pselonen
Presentation at AI morning in April 13th at Tampere University of Technology Kampusklubi.
"AI Morning in April 13th experiments with a new distinctive concept and remixes together machine learning and analytics in the two verticals of healthcare and industry! There is a huge common ground in diagnostics of people and machines, and the same algorithms can be used in both. The presenters from healthcare and industry keynote a conversational networking forum in theme: 'Health: analytics'."
See http://www.aiaamu.fi/
This document discusses machine learning and artificial intelligence. It defines machine learning as using algorithms to learn from data without being explicitly programmed, while artificial intelligence is defined as machines exhibiting human-like intelligence. The document discusses typical uses of each and differences between them. It also covers machine learning misconceptions, when models learn and should be retrained, common pitfalls, and potential healthcare applications of machine learning techniques. Polls are included to gauge audience experience with and perspectives on machine learning.
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.
Healthcare and AWS: The Power of Cloud in Patient Care and Data ManagementSuccessiveDigital
1. The document discusses how cloud platforms like AWS can help healthcare organizations better manage patient data and deliver advanced patient care. It provides examples of how moving to the cloud improves data accessibility, analytics, mobility and enables telehealth solutions.
2. Key benefits of cloud-based healthcare data management include dismantling data silos, facilitating data sharing and integration, providing scalability, and allowing data to be easily accessible anywhere to support new care delivery models.
3. The cloud empowers patient engagement through tools that collect health data from devices. It also improves care management by enabling real-time communication and collaboration between healthcare providers.
This document discusses the importance of databases in healthcare information systems (HIS). Databases allow for efficient collection and storage of patient data, easy exchange of information between healthcare providers, and monitoring to improve quality of care. They enable quick access to patient records, reduce paperwork, and help with diagnosis, treatment, and billing. Overall, well-designed healthcare databases improve efficiency, care quality, and health outcomes.
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.
The document discusses various topics related to information systems in healthcare, including electronic medical records, hospital information systems, intranets, telemedicine, picture archiving and communication systems, and clinical decision support systems. It provides details on the objectives, capabilities and benefits of these systems, highlighting how they can improve various aspects of healthcare delivery such as quality, efficiency, cost and accessibility.
maatGeHealth offers enhanced connectivity between clinicians and patients with a focus on data privacy and security to enable sharing of health information. This can help increase efficiency, reduce errors, and improve health outcomes. Their solutions connect disparate healthcare systems to share clinical data like medication history, lab results, and images between providers. This gives doctors a more complete view of patients to improve care. Their patient health records, health information sharing, structured clinical views, and patient matching help deliver value to clinicians and patients.
The healthcare industry has quietly shed the laggards tag and has quickly emerged as frontrunners in digitization. Hospitals are driving technology advancements by creating a digital framework for seamless integration of all aspects of patient care and administration. There are 5 major themes that are seen as critical in the hospital IT ecosystem – Smart Care, Patient Information Management, Remote Care, Medical Devices, and Intelligent Enterprise Systems.
Large enterprises such as Microsoft and Accenture are collaborating with healthcare providers to address a variety of use cases such as chronic disease management, virtual care solutions, risk scoring, patient tracking and monitoring, precision medicine, and patient on/off-boarding. Accenture and Microsoft helped Spain’s Basque Country Health Centre build a remote elderly patient monitoring system. Athenahealth’s cloud-based network system helps Minnie Hamilton Health System identify bottlenecks and streamline the revenue cycle.
Download the report as we provide an overview of the hospital IT landscape, understand digital transformation trends across these 5 major themes and the opportunities available for vendors and service providers.
This document discusses clinical information systems and their role in healthcare. It begins with background on healthcare and how information technology has helped address issues with declining resources and rapid knowledge growth. It then defines and discusses hospital information systems, clinical information systems, clinical decision support systems, and electronic medical records. It explains how these systems help with tasks like data management, decision making, and improving quality of care. The document also covers healthcare strategy making and how clinical information systems are developed and integrated.
This document discusses decision support systems (DSS) in healthcare. It begins by defining DSS as computer-based systems that aid decision-making. It then explains how DSS can help ensure correct medical diagnoses and reduce risks of drug reactions. The document also discusses how data warehousing and data mining are important components of DSS, allowing trends to be discovered in large datasets. Finally, it outlines some challenges in implementing DSS, such as high costs and debates around calculating costs and benefits.
Unit VI Case StudyAnimal use in toxicity testing has long been .docxdickonsondorris
Unit VI: Case Study
Animal use in toxicity testing has long been a controversial issue; however, there can be benefits. Read “The Use of Animals in Research,” which is an article that can be retrieved from http://www.toxicology.org/pubs/docs/air/AIR_Final.pdf.
Evaluate the current policies outlined in the Position Statement on page 5 of the article. Use the SOT Guiding Principles in the Use of Animals in Toxicology to guide you in your analysis. Feel free to use additional information and avenues of information, including the textbook, to critically analyze this policy.
In addition, answer the following questions:
How do toxicologists determine which exposures may cause adverse health effects?
How does the information apply to what you are learning in the course?
What were the objectives of this toxicity testing?
What were the endpoints of this toxicity testing?
Finally, include whether or not you agree with the Society of Toxicology's position on animal testing.
Your Case Study assignment should be three to four pages in length. Use APA style guidelines in writing this assignment, following APA rules for formatting, quoting, paraphrasing, citing, and referencing.
Adventure Works Marketing Plan
Centralizing Medical Information To Improve Patient Care
(
Centralizing Medical Information To Improve patient Care
)
Contents
Centralizing Medical Information To Improve patient Care0
Contents1
History2
Executive Summary2
High-Level Functional Requirements:4
Project Charter4
Business Problem Statement5
Project Scope5
Budget and Schedule6
Strategy6
SWOT ANALYSIS6
Technology Constraints7
Project Documentation and Communication9
Project Organization and Staffing Approach9
Project Value Statement9
History
The Affordable Care Act law was passed to improve healthcare for its citizens in the United States by increasing the people that have health insurance and by decreasing healthcare cost. A benefactor to this law is the Medicare/Medicaid program which provides medical coverage to the poor, elderly and disabled individuals which is funded by the federal government. The Federal government covers funding for Medicare programs while it provides reimbursement funds for Medicaid programs provided by the states. (The National Federation Of Independent Business V Sebellius, Secretary Of Health And Human Services, 2012). The primary benefits of the Affordable Care Act Law are covering more consumers with improved quality of services while reducing healthcare cost, access to healthcare, and consumer protection. (ASPA, 2014) Centers For Medicare and Medicaid Services (CMS) manages both of these programs and by modernizing and strengthening the current system they will be lowering cost and providing quality care. Executive Summary
The Center for Medicare and Medicaid (CMS) is the federal office to organized the integration of Medicaid and Medicare services across multiple agencies nationwide. Its purpose is to improve access to services, ...
Healthcare Technology & Medical InnovationsS A Tabish
The document discusses how technology has changed and impacted healthcare. It covers several key areas:
1) Technology has transformed how clinicians perform their jobs and expanded options for medical treatments through improvements in networking and computers.
2) As demands on healthcare organizations increase, technology solutions are helping to improve performance, increase collaboration, manage costs, streamline processes, automate tasks and improve workflows.
3) Technologies like AI, blockchain, cloud computing, telehealth, and interoperability solutions are further helping to improve patient care, experiences and outcomes while reducing costs.
HARMAN Digital Transformation and Technology SolutionsHarman DTS
The document discusses barriers to digital transformation in healthcare and introduces HARMAN's Intelligent Healthcare Platform as a solution. Some key barriers include lack of interoperability between disparate data sources, difficulties with data quality and analysis, and gaps in patient-provider communication. The platform aims to overcome these by providing modules for data management, analytics, AI/ML capabilities, and governance to facilitate insights-driven and patient-centric care. Example use cases showed it helped predict readmissions and patient attrition to improve outcomes.
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.
Key Takeaways from the first IDC Pan European Healthcare Summit . Post event ...Silvia Piai
This slide deck summarizes the key takeaways from the first Pan European Healthcare Executive Event. Focused on the three themes of the Summit ( Personalization,Integration and Industrialization), the Summit has explored the different dimensions in which ICT is an enabler of a new business model for sustainable healthcare in Europe
Building blockchain based Healthcare infrastructure with beyond block labsBeyond Block Labs
The Current healthcare ecosystem mainly consists of seven key stakeholders –
patient, provider, payer, pharma, medical technology, technology vendors and
suppliers, and the government and healthcare regulator.
Addressing the Healthcare Connectivity ChallengeTodd Winey
In healthcare, information accessibility can impact the outcome of a medical decision, or the success of a bundled payment initiative. To ensure that the right information is available at the right place and time, healthcare organizations typically have used HL7® interface engines to share data among clinical applications. But the demands on healthcare information technology are changing so rapidly that these simple engines are no longer sufficient.
The area of Health Informatics is Revolutionizing Healthcare, is one that blends aspects of healthcare with computer science and information technology in order to manage and analyze data pertaining to healthcare.
Similar to HealthSaaS Delivers Cognitive Patient Monitoring with the Intel Health Application Platform (20)
The facial nerve, also known as cranial nerve VII, is one of the 12 cranial nerves originating from the brain. It's a mixed nerve, meaning it contains both sensory and motor fibres, and it plays a crucial role in controlling various facial muscles, as well as conveying sensory information from the taste buds on the anterior two-thirds of the tongue.
Letter to MREC - application to conduct studyAzreen Aj
Application to conduct study on research title 'Awareness and knowledge of oral cancer and precancer among dental outpatient in Klinik Pergigian Merlimau, Melaka'
TEST BANK FOR Health Assessment in Nursing 7th Edition by Weber Chapters 1 - ...rightmanforbloodline
TEST BANK FOR Health Assessment in Nursing 7th Edition by Weber Chapters 1 - 34.
TEST BANK FOR Health Assessment in Nursing 7th Edition by Weber Chapters 1 - 34.
TEST BANK FOR Health Assessment in Nursing 7th Edition by Weber Chapters 1 - 34.
Chandrima Spa Ajman is one of the leading Massage Center in Ajman, which is open 24 hours exclusively for men. Being one of the most affordable Spa in Ajman, we offer Body to Body massage, Kerala Massage, Malayali Massage, Indian Massage, Pakistani Massage Russian massage, Thai massage, Swedish massage, Hot Stone Massage, Deep Tissue Massage, and many more. Indulge in the ultimate massage experience and book your appointment today. We are confident that you will leave our Massage spa feeling refreshed, rejuvenated, and ready to take on the world.
Visit : https://massagespaajman.com/
Call : 052 987 1315
Michigan HealthTech Market Map 2024. Includes 7 categories: Policy Makers, Academic Innovation Centers, Digital Health Providers, Healthcare Providers, Payers / Insurance, Device Companies, Life Science Companies, Innovation Accelerators. Developed by the Michigan-Israel Business Accelerator
PET CT beginners Guide covers some of the underrepresented topics in PET CTMiadAlsulami
This lecture briefly covers some of the underrepresented topics in Molecular imaging with cases , such as:
- Primary pleural tumors and pleural metastases.
- Distinguishing between MPM and Talc Pleurodesis.
- Urological tumors.
- The role of FDG PET in NET.
Hypertension and it's role of physiotherapy in it.Vishal kr Thakur
This particular slides consist of- what is hypertension,what are it's causes and it's effect on body, risk factors, symptoms,complications, diagnosis and role of physiotherapy in it.
This slide is very helpful for physiotherapy students and also for other medical and healthcare students.
Here is summary of hypertension -
Hypertension, also known as high blood pressure, is a serious medical condition that occurs when blood pressure in the body's arteries is consistently too high. Blood pressure is the force of blood pushing against the walls of blood vessels as the heart pumps it. Hypertension can increase the risk of heart disease, brain disease, kidney disease, and premature death.
MBC Support Group for Black Women – Insights in Genetic Testing.pdfbkling
Christina Spears, breast cancer genetic counselor at the Ohio State University Comprehensive Cancer Center, joined us for the MBC Support Group for Black Women to discuss the importance of genetic testing in communities of color and answer pressing questions.
HealthSaaS Delivers Cognitive Patient Monitoring with the Intel Health Application Platform
1. Executive summary
HealthSaaS is a thought leader in healthcare interoperability solutions that enable
meaningful exchange of patient-driven data. The HealthSaaS Cognitive Patient
Monitoring Platform* combines sophisticated technology with simplicity and ease
of use for patient and provider populations. Its cloud‐based IoT services, powered
by Microsoft Azure* and based on the Intel® Health Application Platform and Flex*
Edge Compute Engine, are designed to meet the specific requirements of health IT
companies, clinicians, hospitals, pharmacies, and home health organizations. The
result is a secure, vendor‐neutral infrastructure that provides just-in-time data to
facilitate interventions and reduce readmissions for the chronic condition patient.
Challenges
US spending on healthcare accounts for nearly 18 percent of the GDP.2 Chronic
conditions—such as diabetes, hypertension, heart failure, COPD, and asthma—
are rapidly accelerating. These chronic conditions are responsible for more than
86 percent of the annual spend on healthcare.3
Patients frequently suffer from
multiple diseases resulting in complex treatment and medication profiles from
multiple caregivers. In addition, a move toward value-based care provided by
accountable care organizations (ACOs) is reshaping healthcare as providers seek
to close gaps in care coordination and reach underserved populations. Success is
directly linked to limiting lost revenue from unnecessary ER visits and avoidable
hospital readmissions.
HealthSaaS Delivers Cognitive
Patient Monitoring with the
Intel®
Health Application Platform
Healthcare
Cognitive Patient Monitoring Platform
Simplifying data collection and analytics for outcome-based healthcare
“At HealthSaaS, we have a
genuine curiosity that inspires us
to think differently. We exist to
challenge the status quo and are
driven by a sense of purpose to
empower every segment of the
healthcare industry.”
—Frank Ille, CEO, HealthSaaS, Inc.
Remote patient monitoring helps reduce heart failure readmissions by up to
50 percent1
51% reduction in hospitalizations (30 day)1
37% reduction in hospitalizations (60 day)1
36% reduction in hospitalizations (90 day)1
Solution brief
2. Solution Brief | HealthSaaS Delivers Cognitive Patient Monitoring with the Intel® Health Application Platform
Many healthcare organizations lack the technology integration
connected systems require. Often, they have siloed data and
are unable to access and analyze a holistic multicaregiver
patient profile in a timely manner. Healthcare organizations
that reject the ACO model and fail to implement the necessary
technology and practices to support better patient outcomes
risk long-term clinical and financial failure.
In addition, more hospitals are managing patients on an
outpatient basis. As the volume of outpatients increases,
organizations are under pressure to expand geographically.
New outpatient clinics can cost millions of dollars to build
and maintain.
Solution
The HealthSaaS Cognitive Patient Monitoring Platform
technologies collect clinical data from patients’ prescribed
devices and then transmit the information to clinicians
for clinical review, patient interventions, and education.
Widespread deployment of the technology may result in
considerable cost savings due to decreased readmissions
to hospitals, avoidance of unnecessary visits to physicians,
enhanced medication compliance, and improved commu-
nication between patients and clinicians.
Health organizations are leveraging telehealth for post
discharge care including medication adherence, follow up
visits, and late-night and weekend care. The HealthSaaS
platform is an easy-to-use, home-based IoT monitoring
solution for patients who have chronic or critical medical
conditions, such as diabetes, hypertension, atrial fibrillation,
heart failure, COPD, and asthma.
The platform easily integrates with connected devices used for
home healthcare, including blood pressure monitors, activity
trackers, pillboxes, pulse oximeters, and scales measuring
both weight and body fat. A new Bluetooth Low Energy* (BLE*)
medication adherence device manufactured by Zewa Medical
Technology was recently added to the HealthSaaS platform.
HealthSaaS integration of AkēLex* cognitive computing
tools adds the ability to incorporate complex effects of past
history, medications, labs, and more into the generation of
alerts and secure messages. In place of simple threshold
messaging, it offers nuanced, tailored messaging covering a
broad range of clinical behaviors, and provides the clinician
the relevant literature-based rationale.
When a potential problem pattern is detected, the AkēLex
system can provide directed questions aimed at elimination
of false positive responses or collect a more detailed data
set to enhance clinician decision-making. This reduces
alert fatigue by lowering the dependence on simple
scalar thresholds for messaging and providing complete
transparency about the cause for the alert or message.
• Earlier detection of worrisome trends
• More useful messaging backed by literature
• Support for a greater number of clinical scenarios
Says Sandra Elliott, director of consumer technology and
service development at Meridian Health, “The HealthSaaS
platform enables Meridian Health to offer solution-based
information to the clinicians in an actionable manner. The
ability to provide a low-cost, end-to-end solution will
ultimately create the most value for providers and patients.”
HealthSaaS connects previously siloed data from multiple
devices and systems to provide unified, clinically relevant
data to clinicians and payers. Data from home monitoring
devices is secured and filtered using the Intel Health
Application Platform software and transmitted to HealthSaaS
portals or other cloud-based services. Device data is
collected, stored, and forwarded in near real time, without
requiring patients to do anything but use their physician-
recommended devices. The data is parsed and displayed
visually to simplify patient access and speed clinician
decision-making.
Bluetooth Low Energy* (BLE*) medication adherence device
KEY FEATURES OF THE HEALTHSAAS PLATFORM
FDA cleared. HITECH and HIPAA compliant. Hardware agnostic.
FOR PATIENTS FOR PROVIDERS FOR HEALTHCARE IT
• Provisions, connects,
and manages patient
devices
• Medication
management
• Patient portal with
easy-to-understand
visual data
• Physicians can
prescribe patient
devices
• HIPAA-compliant
clinician/provider
portal aligned with
healthcare best
practices
• Dashboard and
reporting tools
visualize actionable
data for clinicians
• Cognitive triage
notification services
• HIPAA-secure
messaging
• Health IT data relay
services
• Agnostic BLE* smart
device hub (support
for Android*,
Windows*, iOS*)
• Hierarchical security
to manage portal
access
• Customized
for unique
requirements
• Optional white label
solution
■ 5% of patients4
■ 50% of dollars4
Total healthcare spending is severely disproportionate4
2
3. Solution Brief | HealthSaaS Delivers Cognitive Patient Monitoring with the Intel® Health Application Platform
A robust set of management capabilities is available through
the HealthSaaS platform. Developed in consultation with
healthcare organizations, they reflect the realities and
specific requirements of home-based patient care. Ongoing
support from HealthSaaS provides not only technology
support, but consultative expertise to continually improve the
platform for a healthcare organization’s evolving needs.
HEALTHSAAS PLATFORM
An affordable platform for smart home healthcare.
Benefits that impact the bottom line.
Reduce unnecessary
hospital
readmissions
One in five Medicare patients returns to the
hospital within 30 days of discharge with costs
totaling more than $17 billion dollars annually.5
Telehealth can reduce avoidable hospital
readmissions by up to 70 percent.6
Redirect
inappropriate
ER utilization
Between 14 and 27 percent of all ER visits are
for non-urgent care. Alternative care services
could save $4.4 billion annually in healthcare
costs.7
Limit capital
expenditure
Telehealth expands reach and projects care
into the community at a substantially lower
investment with no brick- and-mortar costs.8
HIPAA-secure,
clinically actionable data
to the point of care
Caregiver contacts patient
to discuss care plan triage
Patient
Cognitive rules engine
sends secure messages
to caregivers for early
intervention
Device data is
relayed to portal
Patient assigned
devices transmit data
to hub
The HealthSaaS platform allows for near-real time, two-way communication between clinicians and patients
Practice-based management capabilities align HealthSaaS
with provider requirements and processes
3
4. Solution Brief | HealthSaaS Delivers Cognitive Patient Monitoring with the Intel® Health Application Platform
Addressing Patient Privacy and Data Security
Security is at the core of the HealthSaaS platform. From
public-facing portals to private APIs, every access method
is safeguarded with authentication and encryption. All data
transmission occurs over SSL (HTTPS), which encrypts all
transmitted data.
HealthSaaS meets or exceeds all Health Information
Technology for Economic and Clinical Health (HITECH) Act
and HIPAA guidelines and requirements.
This applies to data security, integrity, and protection, as well
as to data that is shared or transmitted from the HealthSaaS
platform to any other system. Security and data systems
are partitioned, which means they are hosted by separate
database servers for added protection. Screens showing
pertinent data can “black out” or redact personal information
for sharing with patients and other providers. The redactor
feature helps curb the unintentional disclosure of personal
identification information.
The redactor feature works on any page that has been tagged
with PII tags
Customizable physician dashboard
Patient dashboard
How It Works in Brief
For the cloud, the HealthSaaS platform is developed and built
using Microsoft .NET* tools and hosted on Microsoft Azure.
This simplifies implementation for healthcare organizations
while providing benefits, including:
• Control for healthcare organizations of their sensitive data
at all times
• Physical, administrative, and technical safeguards to assist
covered entities with HIPAA compliance requirements via
Microsoft online services and data centers
• Data center certification for SAS 70 Type II, FISMA, and ISO
27001, with audits by independent, third-party security
organizations
At the edge, the platform transmits Bluetooth* and BLE data
from patient devices through phones, tablets, and the Intel IoT
healthcare reference platform to HealthSaaS portals or other
cloud-based services. The solution supports connectivity
with multiple device manufacturers and is biometric device
and manufacturer agnostic. It is also smart device agnostic,
supporting Android, Apple*, and Microsoft phones and tablets.
4