To lower health costs, physician networks and medical homes must employ a closed loop population management program that focus on patient SOH stratification, chronic disease management, care coordination and incentive management. This approach will enable them to consistently reduce ER and inpatient admissions, which are the greatest expenditures in health care today.
The Affordable Care Act of 2010 (ACA) opens the door to a wealth of opportunities for hospitals and physician groups. They are beginning to adapt to the new pay-for-performance and bundled payment systems and develop population-based care management programs. While the goal of ACA is to hold hospitals and physicians jointly responsible for quality and cost of care, the new payment models span the entire care continuum, including primary care physicians (PCPs), specialists, hospitals, post-acute care, and re-admissions. The biggest winners will be those who can improve quality of care while driving down costs. Those that focus first on preventive care for top chronic illnesses will be the first to cross the finish line.
To lower health costs, physician networks and medical homes must employ a closed loop population management program that focus on patient SOH stratification, chronic disease management, care coordination and incentive management. This approach will enable them to consistently reduce ER and inpatient admissions, which are the greatest expenditures in health care today.
Patient Centered Medical home talk at WVUPaul Grundy
To employers the cost of healthcare is now a business issue and this talk is about what one large buyer IBM did to drive transformation via broad coalition with other large employers to form the Patient Centered Medical Home movement and the covenant between buyer and provider away from the garbage we now buy episodic uncoordinated disintegrated care. In the change of convenient conversation we have worked with the Primary care providers to give us coordinated, integrated, accessible and compressive care with a set of principles know as the Patient centered medical home.
A Patient Centered Medical Home (PCMH) happens when primary care healers keeping that core healing relationship with their patients step up to become specialists in Family and Community Medicine. The move is to the discipline of leading a team that delivers population health management, patent centered prevention, care that is coordination, comprehensive accessible 24/7 and integrated across a deliver system. PCMH happens when the specialists in Family and Community Medicine wake up every morning and ask the question how will my team improve the health of my community today?
All over the world three huge factors are in play that is driving the concept of Patient Centered Medical Home. They are:
1) Cost and demography
2) Information technology and data (information that is actionable will equal a demand for accountability by the payer or buyer of the care)
3) Consumer demand to engage healthcare differently (at least as well as they can their bank- on line) have a question about lab results why not e-mail?
But at its core it is a move toward integration of a healing relationship in primary care and population management all at the point of care with the tools to do just that.
Validity and bias in epidemiological studyAbhijit Das
Validity and bias are essential aspects of any research—a brief description of internal and external validity and different types of bias related to the epidemiological study.
The Affordable Care Act of 2010 (ACA) opens the door to a wealth of opportunities for hospitals and physician groups. They are beginning to adapt to the new pay-for-performance and bundled payment systems and develop population-based care management programs. While the goal of ACA is to hold hospitals and physicians jointly responsible for quality and cost of care, the new payment models span the entire care continuum, including primary care physicians (PCPs), specialists, hospitals, post-acute care, and re-admissions. The biggest winners will be those who can improve quality of care while driving down costs. Those that focus first on preventive care for top chronic illnesses will be the first to cross the finish line.
To lower health costs, physician networks and medical homes must employ a closed loop population management program that focus on patient SOH stratification, chronic disease management, care coordination and incentive management. This approach will enable them to consistently reduce ER and inpatient admissions, which are the greatest expenditures in health care today.
Patient Centered Medical home talk at WVUPaul Grundy
To employers the cost of healthcare is now a business issue and this talk is about what one large buyer IBM did to drive transformation via broad coalition with other large employers to form the Patient Centered Medical Home movement and the covenant between buyer and provider away from the garbage we now buy episodic uncoordinated disintegrated care. In the change of convenient conversation we have worked with the Primary care providers to give us coordinated, integrated, accessible and compressive care with a set of principles know as the Patient centered medical home.
A Patient Centered Medical Home (PCMH) happens when primary care healers keeping that core healing relationship with their patients step up to become specialists in Family and Community Medicine. The move is to the discipline of leading a team that delivers population health management, patent centered prevention, care that is coordination, comprehensive accessible 24/7 and integrated across a deliver system. PCMH happens when the specialists in Family and Community Medicine wake up every morning and ask the question how will my team improve the health of my community today?
All over the world three huge factors are in play that is driving the concept of Patient Centered Medical Home. They are:
1) Cost and demography
2) Information technology and data (information that is actionable will equal a demand for accountability by the payer or buyer of the care)
3) Consumer demand to engage healthcare differently (at least as well as they can their bank- on line) have a question about lab results why not e-mail?
But at its core it is a move toward integration of a healing relationship in primary care and population management all at the point of care with the tools to do just that.
Validity and bias in epidemiological studyAbhijit Das
Validity and bias are essential aspects of any research—a brief description of internal and external validity and different types of bias related to the epidemiological study.
Presentation given by Eric C. Schneider, MD, Senior Vice President for Policy and Research of The Commonwealth Fund at the University of Michigan Institute for Healthcare Policy and Innovation in Ann Arbor, MI on December 7, 2017.
Patients and their loved ones often hold critical knowledge that informs diagnosis. This toolkit from the Institute of Medicine offers patients, families and clinicians guidance on how they can collaborate to improve diagnosis.
Partnering with Patients, Families and Communities for Health: A Global Imper...EngagingPatients
Engagement is an essential tool to improving global health. This report introduces a new framework for engagement to help countries assess current programs and think strategically about future engagement opportunities. It spotlights barriers to engagement and offers concrete examples of effective engagement from around the globe.
The Paradigm Shift from Healthcare to Population HealthPractical Playbook
The Practical Playbook
National Meeting 2016
www.practicalplaybook.org
Bringing Public Health and Primary Care Together: The Practical Playbook National Meeting was at the Hyatt Regency in Bethesda, MD, May 22 - 24, 2016. The meeting was a milestone event towards advancing robust collaborations that improve population health. Key stakeholders from across sectors – representing professional associations, community organizations, government agencies and academic institutions – and across the country came together at the National Meeting to help catalyze a national movement, accelerate collaborations by fostering skill development, and connect with like-minded individuals and organizations to facilitate the exchange of ideas to drive population health improvement.
The National Meeting was also a significant source of tools and resources to advance collaboration. These tools and resources are available below and include:
Session presentations and materials
Poster session content
Photos from the National Meeting
The conversation started at the National Meeting is continuing in a LinkedIn Group "Working Together for Population Health" and Twitter. Use #PPBMeeting to provide feedback on the National Meeting.
The Practical Playbook was developed by the de Beaumont Foundation, the Duke University School of Medicine Department of Community and Family Medicine, the Centers for Disease Control and Prevention (CDC), and the Health Resources & Services Administration (HRSA).
The future of patient data the danish perspective 2018Future Agenda
The Danish perspective on implications from the future of patient data - insights from discussions in Copenhagen
Denmark is recognised as one of the leading nations for healthcare and is at the forefront of digital transformation in the sector. As new challenges and opportunities emerge over the next decade this article considers what the core drivers of change may be and explores how developments in the availability and use of more and better patient data may impact the Danish health system. Linking together previous research, a recent related Future Agenda initiative and insights from a number of expert discussions in Copenhagen, it then examines the pivotal issues that will affect healthcare providers in the future and considers how the wider sharing of exemplary data can change delivery models.
Given the overall dynamics, many conclude that Denmark is one of the most connected, well-funded and healthy nations in the world. The advent of more and better health data should therefore have additional impact. So, what about the future? How will the global changes underway impact and enhance the Danish system? Moreover, what will be the national vs regional response?
A recent global project exploring the future of patient data was undertaken by Future Agenda in partnership with leading organisations around the world. (www.futureofpatientdata.org) Twelve events across many different healthcare systems brought together over 300 experts to debate the primary shifts for the next decade as well as explore their implications. Within this, several shared ambitions in a number of different countries were identified – many of which can already be seen as existing assets of the Danish system: Good quality patient data, common access to it, and means of interacting with both the information and the different communities who form the full care system.
As the first phase of a subsequent series of more regional, national dialogues, in June 2018 additional discussions were undertaken with healthcare experts in Copenhagen to uncover more detail. Hosted by DTU Business, the aim was to both respond to the global context from the Future of Patient Data project and debate what the implications may be for Denmark. In particular, a core objective was to identify what are the primary issues for the Danish healthcare system for the next decade.
Reducing Readmissions and Length of Stay | VITAS HealthcareVITAS Healthcare
Pain management is first and foremost in a hospice patient’s plan of care. Hospice provides comfort and quality of life near the end of life, and hospice providers are experts at managing pain. The goal of this webinar is to help healthcare professionals understand all aspects of a patient’s pain as a symptom near the end of life, and how to utilize an interdisciplinary approach to provide the most effective pain management.
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Predictive Risk Stratification: Using Analytics to Empower Change with Action...Health Catalyst
Effective population health initiatives are challenging to implement for a variety of reasons. Care teams are already overburdened, and healthcare data is challenging to aggregate and analyze. These factors make it difficult to accurately identify patients who are high-risk or have rising risk for poor outcomes and provide appropriate intervention. To manage patient populations effectively and efficiently, healthcare organizations must be able to automate predictive risk stratification based on claims data, clinical data, and social determinants of health. When care teams know which patients need the most help, which patients have rising risk, and which patients are healthy, they can focus their valuable time where it’s needed most. In this webinar, Dr. Welch shares best practice strategies for utilizing analytics that empower change with actionable workflows, like patient engagement, to ensure that clinically integrated entities can manage high-risk populations appropriately, while also caring for those with rising risk, and engaging with healthy populations mapped to the right targeted interventions.
Presentation given by Eric C. Schneider, MD, Senior Vice President for Policy and Research of The Commonwealth Fund at the University of Michigan Institute for Healthcare Policy and Innovation in Ann Arbor, MI on December 7, 2017.
Patients and their loved ones often hold critical knowledge that informs diagnosis. This toolkit from the Institute of Medicine offers patients, families and clinicians guidance on how they can collaborate to improve diagnosis.
Partnering with Patients, Families and Communities for Health: A Global Imper...EngagingPatients
Engagement is an essential tool to improving global health. This report introduces a new framework for engagement to help countries assess current programs and think strategically about future engagement opportunities. It spotlights barriers to engagement and offers concrete examples of effective engagement from around the globe.
The Paradigm Shift from Healthcare to Population HealthPractical Playbook
The Practical Playbook
National Meeting 2016
www.practicalplaybook.org
Bringing Public Health and Primary Care Together: The Practical Playbook National Meeting was at the Hyatt Regency in Bethesda, MD, May 22 - 24, 2016. The meeting was a milestone event towards advancing robust collaborations that improve population health. Key stakeholders from across sectors – representing professional associations, community organizations, government agencies and academic institutions – and across the country came together at the National Meeting to help catalyze a national movement, accelerate collaborations by fostering skill development, and connect with like-minded individuals and organizations to facilitate the exchange of ideas to drive population health improvement.
The National Meeting was also a significant source of tools and resources to advance collaboration. These tools and resources are available below and include:
Session presentations and materials
Poster session content
Photos from the National Meeting
The conversation started at the National Meeting is continuing in a LinkedIn Group "Working Together for Population Health" and Twitter. Use #PPBMeeting to provide feedback on the National Meeting.
The Practical Playbook was developed by the de Beaumont Foundation, the Duke University School of Medicine Department of Community and Family Medicine, the Centers for Disease Control and Prevention (CDC), and the Health Resources & Services Administration (HRSA).
The future of patient data the danish perspective 2018Future Agenda
The Danish perspective on implications from the future of patient data - insights from discussions in Copenhagen
Denmark is recognised as one of the leading nations for healthcare and is at the forefront of digital transformation in the sector. As new challenges and opportunities emerge over the next decade this article considers what the core drivers of change may be and explores how developments in the availability and use of more and better patient data may impact the Danish health system. Linking together previous research, a recent related Future Agenda initiative and insights from a number of expert discussions in Copenhagen, it then examines the pivotal issues that will affect healthcare providers in the future and considers how the wider sharing of exemplary data can change delivery models.
Given the overall dynamics, many conclude that Denmark is one of the most connected, well-funded and healthy nations in the world. The advent of more and better health data should therefore have additional impact. So, what about the future? How will the global changes underway impact and enhance the Danish system? Moreover, what will be the national vs regional response?
A recent global project exploring the future of patient data was undertaken by Future Agenda in partnership with leading organisations around the world. (www.futureofpatientdata.org) Twelve events across many different healthcare systems brought together over 300 experts to debate the primary shifts for the next decade as well as explore their implications. Within this, several shared ambitions in a number of different countries were identified – many of which can already be seen as existing assets of the Danish system: Good quality patient data, common access to it, and means of interacting with both the information and the different communities who form the full care system.
As the first phase of a subsequent series of more regional, national dialogues, in June 2018 additional discussions were undertaken with healthcare experts in Copenhagen to uncover more detail. Hosted by DTU Business, the aim was to both respond to the global context from the Future of Patient Data project and debate what the implications may be for Denmark. In particular, a core objective was to identify what are the primary issues for the Danish healthcare system for the next decade.
Reducing Readmissions and Length of Stay | VITAS HealthcareVITAS Healthcare
Pain management is first and foremost in a hospice patient’s plan of care. Hospice provides comfort and quality of life near the end of life, and hospice providers are experts at managing pain. The goal of this webinar is to help healthcare professionals understand all aspects of a patient’s pain as a symptom near the end of life, and how to utilize an interdisciplinary approach to provide the most effective pain management.
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Predictive Risk Stratification: Using Analytics to Empower Change with Action...Health Catalyst
Effective population health initiatives are challenging to implement for a variety of reasons. Care teams are already overburdened, and healthcare data is challenging to aggregate and analyze. These factors make it difficult to accurately identify patients who are high-risk or have rising risk for poor outcomes and provide appropriate intervention. To manage patient populations effectively and efficiently, healthcare organizations must be able to automate predictive risk stratification based on claims data, clinical data, and social determinants of health. When care teams know which patients need the most help, which patients have rising risk, and which patients are healthy, they can focus their valuable time where it’s needed most. In this webinar, Dr. Welch shares best practice strategies for utilizing analytics that empower change with actionable workflows, like patient engagement, to ensure that clinically integrated entities can manage high-risk populations appropriately, while also caring for those with rising risk, and engaging with healthy populations mapped to the right targeted interventions.
A few months ago I wrote an article entitled Unplanned Readmissions: Are They Quality Measures or Utilization Measures? It explained the Hospital Readmissions Reduction Program (HRRP) that began in October 2012 as part of the Affordable Care Act (ACA). That article explained the program and its results over the past 5 years. However, more and more healthcare leaders and organizations are beginning to question whether HRRP is a valuable program or whether it is time to move on to something that focuses on quality of care and clinical outcomes, rather than cost savings. This article will address those issues. (In this article “readmissions” mean unplanned or preventable readmissions).
This e-book focuses on Health Management Solutions the value it adds alongside other systems that are already in place throughout the care lifecycle...
Data Science Reveals Patients at Risk for Adverse Outcomes Due to COVID-19 Ca...Health Catalyst
One of the biggest challenges health systems have faced since the onset of COVID-19 is the disruption to routine care. These care disruptions, such as halted routine checkups and primary care visits, place some patients at a higher risk for adverse outcomes. Health systems can rely on data science, based on past care disruption, to identify vulnerable patients and the short- and long-term effects these care disruptions could have on their health. Data science can also inform the care team which care disruptions to address first. With comprehensive information about care disruption on patients, health systems can apply the right interventions before it’s too late.
Today it’s critical for providers to devote time to patient education; inform patients about their conditions and how to prevent, treat, and manage them. Proper management of chronic conditions extends well beyond episodic and infrequent visits to a provider’s office. This population health white paper discusses why patients must become responsible for their day-to-day disease management. Patients will frequently be required to self-monitor their health indicators, observe symptoms, and note behavior, but they must also adhere to complex medication regimens
Case Study "Using Real Time Clinical Data To Support Patient Risk Stratification in The Clinical Care Setting"
HealthInfoNet operates the statewide health information exchange in Maine. The exchange currently manages clinical and patient care encounter information on 97 percent of the residents of the State of Maine. The information is gathered in real time, standardized, and aggregated at a patient specific level to support treatment. For the past three years, HealthInfoNet has worked with HBI Solutions, Inc of Palo Alto, CA to utilize this real time clinical and encounter data to support the development of predictive analytic tools that risk stratify patient populations and individual patients for future incidence of disease, cost, and both inpatient and ambulatory care encounters. These real time predictive models have now been used in clinical care settings for a year. The presentation will cover both lessons learned to date from implementing and optimizing real time predictive analytic tools and the early finding of the impact that the use of these tools is having on patient care management, utilization and outcome.
Devore Culver
Executive Director & CEO
HealthInfoNet
PSCI Case Study - Population Predictive Risk Analytics from PSCIpscisolutions
The challenges for ACOs are Population health management across the continuum-of-care , Patient attribution, Demand planning for its specialist resources, procedures and facilities, Keeping patients within the Network with better access to care.
Medication non-adherence is a growing concern, as it is increasingly associated with negative health outcomes and higher cost of care. Tackling the burden of non-adherence requires a collaborative, patient-centric approach that considers individual patient needs and results in intelligent interventions that combine high-tech with high-touch.
Peer response’s # 2Rules Please try not to make the responses s.docxdanhaley45372
Peer response’s # 2
Rules: Please try not to make the responses super lengthy, contribute one fact AND include references
HMGT 420
· Wk#3
Talar posted Jun 4, 2016 11:57 PM
Patients who have complex health needs require not only medical. But also social services and support from a variety of caregivers and providers. Facility managers who are part of care coordination could assist patient in receiving optimal care by addressing the challenges in coordinating care for these patients, and offer programmatic changes and policies that help deliver the best services to all patients.
Facility managers can come up with strategic plans based on prior data and make necessary changes based on preexisting conditions. “Patient- centered, comprehensive, coordinated, and accessible care that continuously improved through a systems-based approach to quality and safety” (AHRQ, 2012) are what’s needed to achieve the highest quality care possible in any health care facility.
Patient centered care can’t be achieved with providers only. It requires team work and collaboration among all stakeholders. To improve the quality and safety of patients, health care facility managers can work hand and hand with the coordinated team to provide a system based approach by drawing on decision-support tools, taking into account patient experience, and using population health management approach. Patient preference and needs on what aspects of care to be improved.
Respond to Talar here:
· Vanscoy, Week 3
Sarah posted Jun 5, 2016 11:07 AM
As a facility manager, and part of the care coordination team, I would look into models of care that would assist our situation. With the Affordable Care Act in place, there are accountable care organizations (ACOs), which provide models of care (“Promise,” 2013). There are many different definitions and perspectives on care coordination, but all lead to the goal of meeting patient needs and providing adequate healthcare (“Care,” 2014).
Care coordination is essential because each patient can interact with a variety of professionals each visit. For example, for a routine physical appointment, the patient could meet with the scheduling staff, medical assistants, nurses, doctors, pharmacists, and the billing staff. If each one of these member fails to coordinate as a whole, the patient could be harmed or neglected. As a care coordinator, I would be responsible for discussing an individualized care plan with each patient and ensuring that they understand their responsibilities. All barriers should be identified, such as financial, social (language), psychological, and anything that would effect the patient from following their correct plan of care and interacting with the staff (“Promise,” 2013). Another key point is to ensure the medical staff has reviewed the patient’s medical records and ensure that everyone is on the same page. These are just a few examples, because each case is different and each patient will have different needs. .
Care coordination synchronizes the delivery of a patient’s health care from multiple providers and specialists. The goals of coordinated care are to improve health outcomes by ensuring that care from disparate providers is not delivered in silos, and to help reduce health care costs by eliminating redundant tests and procedures.
Medication non-adherence is a growing concern, as it is increasingly associated with negative health outcomes and higher cost of care. Tackling the burden of non-adherence requires a collaborative, patient-centric approach that considers individual patient needs and results in intelligent interventions that combine high-tech with high-touch.
Partners’ Care Management Strategy: A 10-Year JourneyHealth Catalyst
Chronic diseases are responsible for seven out of 10 deaths each year, killing more than 1.7 million Americans annually. Additionally, 133 million Americans—approximately 45 percent of the population—have at least one chronic disease. Partners HealthCare believes that chronically ill patients with multiple medical conditions often need the most help coordinating their care, which is why this well-respected health system has spent the last 10 years perfecting an integrated care management program (iCMP).
Key elements of the iCMP at Partners include access to specialized resources (e.g., mental health, palliative care), involvement through the continuum of care, patient self-management, IT-enabled systems to improve care coordination, data-driven analytics to support strategic decision making, a payer-blind approach, and ongoing support and training for its teams and staff.
Attendees will learn how to:
Identify the essential elements of an effective care management program for chronically ill patients
Recognize how care management plays a key role in an effective population health management strategy
Determine how to use information to identify and effectively manage complex, chronically ill patients
Read the scenario that you will use for the Individual Projects in ea.pdfashokarians
Read the scenario that you will use for the Individual Projects in each week of the course. The
Centers for Medicare and Medicaid Services (CMS) has taken on a more visible role in health
care delivery. Many changes have transpired to improve patient safety along with the
implementation of additional quality metrics, and these changes impact reimbursement rates
Likewise, the Patient Protection and Affordable Care Act has changed the reimbursement fee
structure of Medicare and Medicaid reimbursement for health care services. Other legislation
including the HITECH Act and the Medicare Authorization and CHIP Reactivation Act of 2015
(MACRA) all impact how healthcare organizations receive reimbursement and demonstrate use
of data to improve quality and delivery of patient care Mr. Magone, CEO of Healing Hands
Hospital, has asked you to join the \"Future of Healing Hands Task Force, and your first
assignment is to work with the Hospital Chief Financial Officer, Mr. Johnson, and provide a
summary of the current regulations regarding Medicare reimbursement including how MACR
impact reimbursement if/when Healing Hands coordinates delivery of services by affiliating with
physician practices For this assignment, write a 2-3 page report that you will deliver to Mr.
Magone on how the new CMS initiatives and regulations impact the organization\'s revenue
structure. In your presentation, address the following questions: Why did CMS become more
involved in the reimbursement component of health care? How does CMS\'s involvement impact
the reimbursement model for Healing Hands Hospital and other health care organizations If
CMS reimbursement regulations for Medicare and Medicaid change, does it follow that other
insurance providers change heir policies on reimbursement? What tools can be implemented to
ensure organizations such as Healing Hands Hospital and physician practices are meeting the
policies and procedures set forth by CMS? Identify 3 tools from the CMS Web site that are
helpful in meeting the requirements for Medicare reimbursement set forth by CMS
Solution
Part-a & part-b:
The physician’s work, practice expense, and malpractice, RVU values, CMS (centers for
Medicare and Medicaid services) is required to control overall expenditures in health care
organization. Therefore, CMS become highly involved in the reimbursement component of
health care to patients as per their \"insurance packages\". The CMS\' involvement in “budget
Neutrality” & the reimbursement model at Healing Hand hospital & other health care
organizations is mainly for physician RVU based payments from Medicare & Medicare that can
control its physician costs by adjusting physician payment rates based on “previous periods in a
calendar year” as per federal acts and regulations. The Medicare is going to control physicians
costs according to “medical procedures and medical visits of their record” in a Jan- 1 ending Dec
31. Conversion Factor is main basis to control the physician costs ac.
In October 2014, INTEGRATED's Bill Jessee presented "Where Is Healthcare Going? And How Will We Get There?" at Iowa Hospital Association's annual meeting. The presentation focuses on the forces shaping healthcare today, the delivery system changing in response to the environment, and what this all means for hospitals and physicians.
HCC Coding and Risk Adjustment Tool model is specially designed to estimate future health care costs for patients. its main objective is to consider the well-being of the executives alongside exact repayments from medicare Advantage Plans.
Regulatory changes, plus advances in cloud computing and analytic technologies, are making it possible for U.S. healthcare providers, payers and patients to connect, commmunicate and collaborate seamlessly, and ensure that the right care is provided at the right place, at the right time.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
Population health management real time state-of-health analysis
1. Page 1 www.PSCISolutions.com
White Paper
April 2012
Population Health Management:
Real-Time State-of-Health Analysis Solutions
Leveraging EMR Data to design and execute provider-driven care management programs.
The Affordable Care Act opens the door to a wealth of opportunity for hospitals and physician
groups. They are beginning to adapt to the new pay-for performance and bundled payment
systems, and develop population-based care management programs. While the goal of this piece
of legislation is to hold hospitals and physicians jointly responsible for quality and cost of care, the
new payment models span the entire care continuum including primary care physicians, specialists,
hospitals, and other medical professionals. The biggest winners will be the ones who can improve
quality of care while driving down costs. Those that focus first on preventive care for top chronic
illnesses will be the first to reach the finish line.
Innovative healthcare providers take the lead by
developing coordinated care systems that embody
the core principles of preventive care: Patient-
Centric Medical Homes (PCMHs) and Accountable
Care Organizations (ACOs). Physician networks
are adopting the PCMH model, relying on primary
care physicians (PCPs) and care coordinators as
the central hub for care, and looking to specialists
when necessary. Medical homes deliver
preventive care to the entire spectrum of patients,
from healthy to chronic, with the goal of avoiding
admissions to acute care facilities.
WHY CHRONIC CONDITIONS FIRST?
Chronic diseases account for the majority of acute
care costs (in-patient, out-patient, and ER).
Controlling acute care admissions for chronic disease is essential to control healthcare costs.
Therefore, the effort to minimize healthcare costs must begin with managing top chronic conditions.
According to the CDC, “Chronic diseases are the leading cause of death and disability in the US,”
1
and Healthcare Cost Monitor underscores this fact revealing that, “Seventy-six percent of Medicare
1
"Chronic disease and health promotion." Centers for Disease Control and Prevention. Center for Disease
Control, 2010. Web. 26 Feb 2012. http://www.cdc.gov/chronicdisease/overview/index.htm.
CDC on Chronic Diseases
7 out of 10 deaths among Americans each year
are from chronic diseases. Heart disease, cancer
and stroke account for more than 50% of all
deaths each year.
In 2005, 133 million Americans – almost 1 out of
every 2 adults – had at least one chronic illness.
Obesity has become a major health concern. 1 in
every 3 adults is obese and almost 1 in 5 youth
between the ages of 6 and 19 is obese (BMI ≥
95th percentile of the CDC growth chart).
Diabetes continues to be the leading cause of
kidney failure, non-traumatic lower-extremity
amputations, and blindness among adults, aged
20-74.
http://www.cdc.gov/chronicdisease/overview/index
.htm
2. Page 2 www.PSCISolutions.com
spending is on patients with five or more chronic diseases.”
2
The Agency of Healthcare Research
and Quality also emphasizes the high cost of chronic conditions.
3
Regardless of which payment model becomes
predominant (shared savings, bundled payment, or
ACO), in order to bend the health care cost curve,
health care providers must focus on preventive
care for chronic care patients. Provider
organizations will need an innovative approach to
redesign care processes, with a focus on keeping
chronic care patients healthy and out of ERs and
hospitals.
YESTERDAY | CLAIMS-BASED PREDICTIVE MODELS
For years, healthcare insurance companies (payers) have mined claims data for chronic patients
and have built predictive models to identify high-risk patients. Armed with historical reports, case
managers designed intervention programs that were meant to prevent complications among
chronic patients and reduce ER visits and hospitalizations.
While this approach has seen some success,
limitations far outweigh merits. Data used by
payers to flag high risk patients is historical claims
data — primarily costs, admissions, and diagnoses.
Because this view is retrospective and heavily
biased toward cost, patients with past high acute
care costs are flagged as “risky”, regardless of their
current state of health. Furthermore, regression
and time series risk models are typically updated
only annually.
Most physicians are highly skeptical of claims-
based predictive models because they have no
clinical basis, and give no consideration to an
individual’s current state of health. Moreover, there
is a complete lack of causation, “Why is a patient
considered high-risk? What are the clinical reasons for the score? How do we lower the patient’s
risk score? How does the score measure the effectiveness of my care management program?”
2
Swartz, Kimberly. "Projected Cost of Chronic Diseases." Health Care Cost Monitor. Health Care Cost Monitor,
n.d. Web. 26 Feb 2012. http://healthcarecostmonitor.thehastingscenter.org/kimberlyswartz/projected-costs-of-
chronic-diseases/.
3
Stanton, M. W.. "The High Concentration of US HealthCare Expenditures." Agency for Healthcare Research and Quality.
AHRQ, 2006. Web. 26 Feb 2012. http://www.ahrq.gov/research/ria19/expendria.htm.
Health Care Cost Monitor on Chronic Disease
Spending
Seventy-six percent of Medicare spending is on
patients with five or more chronic diseases.
Currently 10% of health care dollars are spent on
overall direct costs related to diabetes, amounting
to $92 billion a year (1.5 times the amount spent
on stroke or heart disease). The Centers for
Disease Control and Prevention predicts that
spending on diabetes care will reach $192 billion
in 2020.
According to the Milken institute, overall cost of
heart disease is predicted to reach $186 billion in
2023.
http://healthcarecostmonitor.thehastingscenter.org
/kimberlyswartz/projected-costs-of-chronic-
diseases/
AHRQ on Cost of Chronic Conditions
The 15 most expensive health conditions account
for 44 percent of total health care expenses.
Patients with multiple chronic conditions cost up to
seven times as much as patients with only one
chronic condition.
http://www.ahrq.gov/research/ria19/expendria.htm
3. Page 3 www.PSCISolutions.com
These models lack a correlation to clinical information. For example, a physician will acknowledge
a high risk score if there is evidence that the patient has a high BMI, and the HbA1C has been
consistently high over the past year and is trending higher. The score becomes even more credible
when there is evidence of ER admissions or acute care inpatient admissions.
Unfortunately, an individual’s current state of health has no bearing on his or her claims-based risk
score. Claims-based risk scores are created with regression analysis at a population level to
predict scores at the patient level. Individual scores are relative to the population, therefore could
change as the population changes, even with no change in the individual’s state of health.
Not only are today’s calculations unsuitable for determining a patient’s true risk, they provide no
insight on how an individual’s score improves or deteriorates after each clinical visit. Information
lags so far behind; physicians are given no insight to actively manage ongoing care. Claims-based
risk scores are not actionable – they provide no insight for care at the provider level.
Claims-based risk scores are also deficient because they do not adequately represent the
population. Reports provided by payers are used primarily by case managers, who in most cases
work for a payer. Physicians reject these reports as a basis for their own effectiveness in
managing patients, because they are only a subset of their total population. Furthermore, payer
reports are not typically useful for evidence-based care, to identify and implement clinical best
practices. Finally, they are inadequate for measuring physician performance to design incentive
programs.
In order to use payer reports across an entire population, a provider would first need to normalize
multiple payers’ risk scoring systems, then aggregate the information. Because each payer has a
unique methodology, there is little chance that the resulting information would be accurate or
meaningful for developing care management programs.
Considering today’s approach to developing care management programs and understanding
physician effectiveness, it’s important to remember that CMS does not provide patient risk scores.
The fact that Medicare patients account for the majority of chronic patients and populations, other
payers’ risk reports incorporate only a small fraction all chronic patients. Therefore, the impact of
using individual (or even combined) claims-based payer risk reports is minimal in any effort to bend
the overall patient population health care cost curve at the provider level.
FURTHER CONSIDERATIONS FOR A NEW APPROACH
Current thinking and efforts create a disproportionate focus on existing chronic patients. The
intervention approach is designed specifically for this group, while wellness programs reflect only
the hope that the healthy population will remain so. Because today’s healthy patients are largely
ignored, yet will become tomorrow’s chronic patients, this approach is deeply flawed. If providers
delay uncovering and examining causes until a chronic diagnosis emerges, there is no opportunity
to avoid a chronic scenario. A better approach is to monitor all patients, healthy and chronic, for
risk of hospitalizations. Unfortunately, current claims-based predictive risk models allow no room
for this approach.
4. Page 4 www.PSCISolutions.com
Claims-based risk models create a grave conflict for today’s physicians. To realize bonuses, they
must choose cost of care over effective care. To make matters worse, incentives do not reward
every health care professional that has an impact on patient health. Conversely, payers strive to
minimize bonuses to physicians and networks. Physicians perceive that payers have an “upper
hand” and can deny bonuses as models change, and assert that costs were higher than
“reasonable” against the statistical model. As a result, there is inherent conflict between physicians
and payers.
Progressive medical groups do not use claims-based patient risk reports created by payers to
develop care management programs. And, until today, there has been a stark absence of credible
decision support hindering proactive care management. As a result, health professionals have not
had the ability to focus on population state of health as a means to reduce ER and hospital
admissions.
VITAL PROGRESS | CLINICAL MODELS FOR POPULATION MANAGEMENT
Today, most large physician groups and medical homes already use at least a basic EMR system.
CMS predicts that by 2014, more than fifty percent of all eligible medical professionals in the U.S.
will use EMR. According to Frost & Sullivan, the ambulatory EMR market will explode to $3 billion
by 2013. This is a transformational shift, because for the first time in history, clinical information is
digitally available in real time, with reasonable availability of laboratory results and patient vital
data.
In this age of EMR, the healthcare industry is proclaiming a new wave of decision support for
primary and acute care, leveraging data from EMR applications. The new generation of primary
care management solutions delivers real-time meaningful use clinical data from EMR records.
These systems use patient medical records to measure state of health, and evaluate the
effectiveness of care programs and evidence-based medicine. Real-time clinical data from EMR
records is also being used to create sustainable, repeatable programs to reduce the number of
high-risk patients, and design individualized care management programs. Using current clinical
data for analysis rather than historical claim data means that health care providers create programs
that are meaningful and effective for their specific population.
The new care management decision support systems use actual clinical data, and there is little or
no analysis or interpretation required by the physician. As a result, a care coordinator can take
ownership of care management, so that primary physicians can focus on delivering patient care. In
light of predictions for the short supply of doctors over the next few years, this is good news for
patients and providers alike.
5. Page 5 www.PSCISolutions.com
CLOSED-LOOP CARE MANAGEMENT PROGRAMS
Using real-time clinical data from EMR records,
health care providers now have the capacity to
design a closed-loop population care management
program (Figure 1). A well-designed program
delivers primary care to drive higher quality, reduce
costs, and deliver greater value in health care.
The very foundation of the well-designed program is
population state of health stratification, the ability to
categorize patients into high (red), moderate
(yellow), and low (green) risk groups by chronic condition.
Population stratification makes it possible to design customized programs for high-risk patients,
execute and monitor programs, and measure the performance of clinical teams for incentive
management.
Population State of Health (SOH) Stratification
State of health stratification provides actionable and measurable information about actual health
status at the population and patient levels, with visibility of controllable and non-controllable factors.
An SOH model takes into consideration every patient’s age, gender, ethnicity, family history, all
clinical factors (like BMI, lipid panel, blood HM, PFTs) and co-morbidities, and delivers an accurate
SOH score for every encounter and for the entire population (score ranges 0 to 100). A low score
indicates excellent health, and as the number increases so does the likelihood of complication(s)
and hospitalization within 12 to 18 months. SOH is a “risk predictor”.
However, it is also an indicator of the quality of care delivered. If the score trends down, the quality
of care is good, because health is improving. In this sense, the trend of the SOH score is a
measure for quality of primary care.
While payers have their own calculation and definition for “risk”, the remainder of this article uses
the terms “Risk” and “State of Health” interchangeably.
Origins of State of Health (SOH) Models
Nationally accepted clinical models are the basis for state of health models. In some cases, when
the data did not contain all the parameters required to compute SOH scores, assumptions and
approximations were considered and validated with physicians to ensure the integrity of the
models. The SOH models were then validated against historical data.
Figure 1 - Closed-Loop Care Management Program
6. Page 6 www.PSCISolutions.com
SOH scores are calculated at the patient level and rolled up to a population level (Figure 2). In this
example, each row corresponds to a physician's patient population. It shows the patient count, the
number of office visits (encounter) and the average population SOH score for each chronic
disease. “Red” signifies “high risk” scores. Physicians and care coordinators use the easy-to-
digest visual information to focus on high risk populations, and drill down to individual patients to
understand factors that contribute to scores.
Figure 2 Population SOH (Risk) Stratification by Physician.
Focus on prevention and screening; monitor compliance for chronic conditions.
This approach allows health care providers to design meaningful preventive care programs for the
exact population, and create individualized programs for specific patients.
Chronic Disease Management
Patients who comply with prescribed care programs are typically more successful in managing
chronic conditions. This is where care coordinators play an important role. Leveraging state of
health scores, care coordinators pinpoint high risk patients by chronic condition, and best evidence
guidelines become the basis for customized care management programs. The care management
program is integrated with the care management execution system that includes patient
scheduling, outbound call centers, home visits, patient portals and emails. While the disease
management program identifies needs, the execution system promotes compliance with
treatments, medications, scheduling laboratory tests, attending educational counseling sessions,
and other prescribed activities.
7. Page 7 www.PSCISolutions.com
Monitoring gaps in care established by evidence-based care, patients’ SOH trends, and underlying
clinical drivers over time, care coordinators can identify patients that need their attention.
Care Coordination
Physicians who improved the state of health for their population (i.e. lower the score) over a one to
three year period established and used better clinical protocols (i.e. best practice care management
programs). In one instance, one physician’s CHF population risk increased to 55%, while another’s
dropped to 5% (Figure 3). Analyzing SOH population trend by physician population, the team of
physicians identified the most effective clinical protocols for the patient population and standardized
around best evidence care. The physician team also used SOH scores as a measure of quality of
primary care, resource utilization, costs, and patient experience to establish best evidence care
protocols, to lower cost and improve patient experience. (Figure 4).
Figure 3 - Effectiveness of two physician CHF populations.
Use best practices within the risk group for evidence-based care coordination: medicines, treatment levels,
frequency of visits; by risk group.
8. Page 8 www.PSCISolutions.com
Figure 4 - Population Chart / Cost-Quality Grid, High-Medium-Low Risk
Population performance: Map patients on quality and total cost across the continuum-of-care
(ambulatory and acute). Identify optimal preventive care levels to minimize lifecycle cost over a time period
by chronic condition.
Incentive management
It is not enough to simply design and launch new programs. If financial incentives for health care
professionals are not aligned with performance, success may be temporary and hard to sustain.
Effective incentive programs distinctly drive higher quality and reduce costs for greater value in
health care:
Align team incentives with population quality and cost performance targets (physicians
and care coordinators)
Establish and share best evidence practices by chronic condition
Encourage teamwork to lower healthcare costs
Illustrate accurate physician and clinical coordinator population performance, and the
impact to incentives
Incentive programs reward care teams for reducing population risk scores, improving patient
satisfaction scores, and reducing overall patient costs. Continuum of care dashboards (ambulatory
and acute) are useful in designing incentive programs and illustrate risk-cost-quality details for each
patient (Figure 5).
9. Page 9 www.PSCISolutions.com
Figure 5 - Continuum of Care Analysis by Patient, Preventive Care Impact on Acute Care Costs
Monitor how much total inpatient and outpatient care (cost and quality) is being provided to the risk panel;
identify patient outliers.
Patient SOH scores can be rolled up to population averages. For example, one incentive program
dashboard maps physician/care coordinator teams on a cost-quality grid (Figure 6). In this case,
the quality metric captures population SOH, ACO quality measures, and patient satisfaction scores.
The intersection of the crosshairs is the target for quality and cost for the specific patient
population. Each bubble corresponds to a specific physician- care coordinator team, and the size
of the bubble illustrates the size of the population they manage. The distance of each bubble from
the crosshair indicates the positive or negative variance from the target and is proportional to each
team’s bonus or penalty.
Figure 6 – Physician value index used for incentive management for care teams.
Report shared savings by plan by physician on a periodic basis and show the impact of actions on their
“pocketbook”.
10. Page 10 www.PSCISolutions.com
Results | Validating the SOH Model APPROACH
Using SOH models as a surrogate for primary care quality and the indicator of possible
hospitalization is a new concept and will become the contemporary paradigm for chronic disease
management. Therefore, it was important to understand how effectively the model and scores
could predict hospitalizations against historical patient population data. To validate the models,
researchers compared the new SOH model against that of a leading claims-based risk model (the
payer model).
The insurance payer used claims data (patient age, gender, ethnicity, previous ER, IP admissions,
costs, diagnosis and other claims files data). They calculated a risk score, a number between 0
and 5000.
For the SOH model, researchers used real-time clinical data (patient age, gender, ethnicity, vital
signs, lab results and treatment medications). The SOH model did not include past ER or IP
admissions data. The SOH model established a risk score between 0 and 100 for diabetes (Table
1).
Total diabetes patients
(type 1 and 2, complicated and uncomplicated)
737
Time period (2010) 1 year
IP admissions 53
ER visits 95
Table 1 - SOH Validation
Next, researchers calculated a SOH score for each patient using historical data over two years
(2008-2009), and stratified the population based on SOH scores. Researchers compared SOH
scores to actual IP admissions and ER visits.
Inpatient Admissions
Figure 7 shows total hospitalized patients as a ratio of the total diabetic patients for that SOH band.
For example, in the SOH band 50-60, 20% of all patients were hospitalized. As the score
increased, the ratio of patients within that band also increased. At very high scores, all patients
were hospitalized. Thus, Figure 7 validates the accuracy and predictive power of the SOH score.
11. Page 11 www.PSCISolutions.com
Figure 7- Ratio of Hospitalized Patients to Total Diabetic Patients
Next, researchers compared the SOH results to the payer’s claims-based actuarial model. Figure 8
shows the relationship between the payer risk scores and IP admissions. In the 250-500 risk band,
the ratio of admitted patients is higher than the SOH model. Since most patients are in this band,
the predictive power of the payer’s model at low risk scores is diminished. Similarly, at higher risk
scores, the predictive power of the payer’s model is only 50% whereas the researchers’ SOH
model is closer to 100% accurate.
12. Page 12 www.PSCISolutions.com
Figure 8 - Relationship between the payer risk scores and IP admissions.
ER visits
Figure 9 shows a similar comparison, SOH bands and ER visits. This comparison and the uniform
curve further substantiates the SOH model as a valid and accurate predictor of ER admissions.
Similarly, Figure 10 shows the payer’s model for ER admissions, which is clearly weak at both low
and high risk bands.
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EVERYONE WORKS SMARTER USING SOH MODELS
State of health models are highly accurate and predictive, and ideally suited for chronic care
population management by chronic condition. Using SOH scores, care coordinators can correctly
identify and focus on high risk patients with a great risk of hospitalization in the short term. Given
the rapid adoption of EMRs among primary care physicians and groups, the data required to build
SOH models is readily available now, and will continue to expand over the next two years.
Healthcare providers can enable continuous improvement using SOH models together with care
management programs. This approach has already been institutionalized in a number of leading
medical homes like Medical Clinic of North Texas (MCNT). Within these organizations, there are a
wide variety of individuals who actively use these models in their daily work, and can be described
as:
Administrators & Management, to quantify the effectiveness of care management
programs, measure productivity, and monitor incentive programs.
Physicians, to define and/or leverage best practices in managing disease, in line with their
desire for evidence-based care. By analyzing SOH scores and understanding drivers,
they have more insight to deliver better care.
Care coordinators, who are primarily interested in identifying high risk patients, to
understand risk factors, develop individual care programs, and monitor patient
compliance.
Medical Clinic of North Texas (MCNT), a Level 3 Recognition by the National Committee for Quality
Assurance (NCQA) Physician Practice Connections ® - Patient Centered Medical Home™ (PPC-
PCMH) has been a pioneer user of SOH based population management approach.
MCNT demonstrated a stellar FY 2010 performance with Total Medical Cost trend for their
managed population of 2.4% better than market, is a culmination of various quality of care drivers:
Potential avoidable ER visits decreased by 13.3%
OP Diagnostics trended only 1.9% vs. market trend of 9.7%
OP Surgical trended 5.6% vs. market trend of 15%
Utilization of CCD Specialists increased by 18.3% while drugs administered trended 10%
less than market
High tech scans/1000 decreased by 12%
Overall performance index improved in Facility Outpatient (-5%), Other Medical Services
(-6%) and Professional (-1%) relative to the market
An enviable performance considering the challenges the healthcare provider markets are facing
with influx of changes in the market.