Posts Tagged ‘healthcare data’

Infographic: Overcoming Today’s Healthcare Data Protection Challenges

October 18th, 2019 by Melanie Matthews

By protecting patient data and ensuring it’s available to everyone who needs it, healthcare organizations are helping to safeguard patient care, according to a new infographic by Arcserve (USA) LLC.

The infographic examines healthcare data storage challenges, the financial consequences of not protecting data properly and the biggest barriers to IT transformation.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results documents the accomplishments of CHS’s 24 ACOs under the MSSP program, the crucial role of data analytics in CHS operations, and the many lessons learned as an early trailblazer in value-based care delivery.

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Infographic: Unlocking Data-Driven Excellence in Healthcare

May 1st, 2019 by Melanie Matthews

Despite the growth of data and analytics to improve patient outcomes and optimize revenue, the majority of hospitals have work to do in democratizing analytics, according to a new infographic by Alteryx, Inc.

The infographic examines three top data analytics priorities, the number of data sources needed to create meaningful analytics and data analytics obstacles.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results documents the accomplishments of CHS’s 24 ACOs under the MSSP program, the crucial role of data analytics in CHS operations, and the many lessons learned as an early trailblazer in value-based care delivery.

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Infographic: How To Establish Your Healthcare Data Task Force

January 7th, 2019 by Melanie Matthews

Reaching electronic medical record (EMR) interoperability in healthcare begins with selecting the right data to share, according to a new infographic by HULFT.

The infographic illustrates the key players healthcare organizations should include on a healthcare data task force team to ensure that the data strategy gets the right data to the right people at the right time.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results documents the accomplishments of CHS’s 24 ACOs under the MSSP program, the crucial role of data analytics in CHS operations, and the many lessons learned as an early trailblazer in value-based care delivery.

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Infographic: How Big Data Will Unlock the Potential of Healthcare

August 6th, 2018 by Melanie Matthews

The amount of medical data generated each year is rising astronomically. Understanding how to connect that data for new growth opportunities, greater efficiency and better serving consumer needs is a pressing challenge for healthcare organizations, according to a new infographic by Publicis Health.

The infographic examines these data trends and how healthcare organizations can successfully activate data.

UnityPoint Health has moved from a siloed approach to improving the patient experience at each of its locations to a system-wide approach that encompasses a consistent, baseline experience while still allowing for each institution to address its specific needs.

Armed with data from its Press Ganey and CAHPS® Hospital Survey scores, UnityPoint’s patient experience team developed a front-line staff-driven improvement action plan.

Improving the Patient Experience: Engaging Front-line Staff for a System-Wide Action Plan, a 45-minute webinar on July 27th, now available for replay, Paige Moore, director, patient experience at UnityPoint Health—Des Moines, shares how the organization switched from a top-down, leadership-driven patient experience improvement approach to one that engages front-line staff to own the process.

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Guest Post: 5 Steps To Prepare for Real-Time Enterprise Healthcare Data

July 2nd, 2018 by Melanie Matthews

The right real-time enterprise data infrastructure allows the information to be routed to a data lake where enterprises can employ modern business intelligence solutions to derive actionable insights.

Recent trends and emerging technologies are converging and a truly real-time enterprise will soon be an achievable possibility. As we move beyond traditional batch data to include streaming data, healthcare systems are seeing an unlimited and unyielding flow of data. This constant flow gives enterprises the ability to act on the information as it originates. Additionally, the right infrastructure allows the information to be routed to a data lake where enterprises can employ modern business intelligence solutions to derive actionable insights.

Of course, not every organization will need to be able to utilize truly real-time data, all organizations need to consider how they can best manage the increasing flow of data. Following are five steps to consider as you develop your enterprise information management (EIM) strategy:

  1. Define/identify business objectives – Is real-time data needed?: While the use cases are innumerable, real-time applications of data by their nature require a much higher level of network resources than data that is sent every hour or every day, as batch processes often are. Consider this: do you need data immediately or is once per hour sufficient? Organizations must first consider how frequently information is needed and then set the strategy.

  2. Find your edge and manage devices: Advancements in integration, messaging software, and Internet of Things (IoT) are building a new edge of the network. Mobile devices in the modern context can be virtually anywhere. To have success organizations need a data and device strategy to ensure that they can “read” the data they need, when they need it. Asset management strategies are also necessary for these devices to ensure that the information on them is controlled, secured, and properly maintained. An increasingly common example of device management at the edge is in healthcare, where tablets and mobile phones are increasingly used at the point of care.

  3. Let Data Streams Flow into Lakes: As organizations gather and use different kinds of often completely unrelated data forms, it makes a lot of sense to create a data lake. Whether this is required goes back to the context of use and the business objective, but in all cases, it is crucial to develop a strategy to consolidate, store, protect and back up the data.

  4. How Do Users Consume the Data?: Information for the sake of information can be distracting. Real-time data is no exception. Again, it is critical that its use be considered in the development of strategy. Let’s use monitoring again as an example. Do users need to know what is happening all of the time, or just when something is wrong, or some other key milestone? If they only need to know at certain points (problem detected, report generated, etc.), what is the best way to relay that information—an alert, a color-coded dashboard? The possibilities are limitless but should reflect a keen understanding of how the information will be used when needed most.

  5. Build in Analytics to Mine That Gold: Information is dynamic and so are the use cases that motivate different users to seek and apply it. For many, the information they gain is descriptive, for some it’s diagnostic in nature, and for others it’s predictive. An example can be found in the predictive analytics used to proactively identify equipment failure and to guide the resulting maintenance and repairs. For others it is prescriptive and informs what is happening currently to help define what should be happening. Regardless, the enormous range of use demands that organizations seeking to benefit from real-time data first establish the infrastructure necessary to run analytics in a way that pulls out actionable, relevant information.

A move to real-time enterprise will require changes to virtually every part of an organization. It will take a great deal of time, attention and hard work; however, the benefits will be significant. The five steps discussed here can help healthcare organizations find and stay on the right path to becoming a real-time enterprise.

About the Author:

Jennifer Schwartz

Jennifer Schwartz is an accomplished professional with special expertise in enterprise information programs, consulting, strategic planning, and mobile solution architecture. She has 18 years of experience with improving operational efficiency, reducing costs, and formulating strategic plans for her clients. As the Enterprise Information Management solution lead for CTG, Ms. Schwartz focuses on business process management and automation, providing best practice guidance, and executing special projects that help transform data into action. Jennifer works across industries, advising clients on the execution of projects to realize efficiencies.

Infographic: 7 Steps for Healthcare Interoperability

June 29th, 2018 by Melanie Matthews

Healthcare interoperability will lead to a collaborative environment with accessible data for all users to gain meaningful insights, according to a new infographic by Liaison.

Healthcare organizations can move from an environment with siloed information and limited data access to one that is truly collaborative with accessible data for all user with the seven interoperability steps outlined in the infographic.

A New Vision for Remote Patient Monitoring: Creating Sustainable Financial, Operational and Clinical OutcomesAs healthcare moves out of the brick-and-mortar traditional setting into patients’ homes and their workplaces, and becomes much more proactive, the University of Pittsburgh Medical Center (UPMC) has been expanding its remote patient monitoring program. The remote patient monitoring program at UPMC has its roots in the heart failure program but has since expanded to additional disease states across the integrated delivery system’s continuum of care.

A New Vision for Remote Patient Monitoring: Creating Sustainable Financial, Operational and Clinical Outcomes delves into the evolution of UPMC’s remote patient monitoring program from its initial focus on heart failure to how the program was scaled vertically and horizontally. Click here for more information.

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Guest Post: As Mergers Continue, Healthcare Industry Faces New Data Consolidation Realities

June 12th, 2018 by Christian Puff

As if the healthcare system wasn’t confusing enough, construction signs are now popping for consolidations.

As if navigating the twists and turns of the U.S. healthcare system highway wasn’t confusing enough, construction signs are now popping up all over the place in the form of consolidations. Why is this happening? What does this mean for consumers? And, how will this change the way consumers receive care?

The United State’s annual medical spend has risen to over $3.4 trillion and is only projected to grow. This spend accounts for roughly 18 percent of the U.S. GDP. Some want a piece of the incredibly large pie, while others are focused on reducing its size. Then, there are those who have accepted the need for a smaller pie but want the biggest piece possible. It’s in this third group where we’re seeing many of the industry consolidations. From Aetna and CVS to Cigna and Express Scripts and, most recently, Walmart and Humana, these big-name players are intent on controlling the largest portion of the multi-trillion dollar industry they can.

If these consolidations are successful, the way insurers and healthcare providers interact will change because of one word: data. Data is king, and many believe it is the key to reducing healthcare costs in this country.

Aetna is one of the largest health insurers. Its plan to merge with CVS, the largest national retail pharmacy chain that also happens to own the largest pharmacy benefit manager, Caremark, will give the consolidated healthcare giant access to an incredible amount of member, patient and provider data. The same is true for Cigna and Express Scripts, although to a slightly lesser extent. While this consolidated entity would not, at this time, have brick-and-mortar pharmacies, together, they will reap the benefits of combining member, patient and provider data. However, the proposed Walmart and Humana merger could prove the most impressive in terms of data consolidation, followed by Aetna and CVS. Not only will the newly combined company know whether their members and patients fill their prescriptions, they’ll know what those same members and patients purchased while waiting for their prescriptions. Did the depressed, hypertensive diabetic buy ice cream, red meat and cigarettes? They will now have those answers.

So why is this important? According to the Centers for Disease Control and Prevention (CDC), over 86 percent of the healthcare spend is due to those suffering from chronic disease. More importantly, however, is over 50 percent of these costs are attributable to patient behavior. As a result, having access to both medical and behavioral data allows the depressed, hypertensive diabetic purchasing ice cream, red meat and cigarettes to become an opportunity for outreach and case management.

These companies will attempt to capitalize on the data available to them to help manage the cost of care. Perhaps it will be in the form of a letter or phone call to the member. Perhaps it will come in the form of a highly personalized clinical program where the member receives access to nicotine replacement therapy, a gym membership and nutritionist services.

These organizations alone cannot and will not be able to force patients and members into participating in programs designed to improve health and reduce the cost of care.

Okay, so now what? Let’s assume for an instant all of this data conglomeration works to drive down the cost of care to a more reasonable $2.5 trillion. Will consumers benefit from the savings? This is yet to be determined. In reviewing the proposed consolidations, the federal antitrust enforcers will attempt to discern the impact on the consumers. Undoubtedly, these entities will argue the proposed mergers will reduce costs by increasing efficiencies and allowing them to positively affect the medical spend trend. Critics, however, predict individual consumers will never see the savings projected by these organizations. Who’s right? That’s a question that can only be answered with time.

This article is educational in nature and is not intended as legal advice. Always consult your legal counsel with specific legal matters.

Christian Puff

Christian Puff

About the Author:

Christian Puff is an attorney with Hall, Render, Killian, Heath & Lyman, P.C., the largest healthcare-focused law firm in the country. Please visit the Hall Render Blog at http://blogs.hallrender.com/ for more information on topics related to healthcare law.

HIN Disclaimer: The opinions, representations and statements made within this guest article are those of the author and not of the Healthcare Intelligence Network as a whole. Any copyright remains with the author and any liability with regard to infringement of intellectual property rights remains with them. The company accepts no liability for any errors, omissions or representations.

Infographic: Healthcare Colocation Myths

April 27th, 2018 by Melanie Matthews


The average healthcare organization stores well over one petabyte of data (1,000,000 gigabytes) leading many organizations to store data off premise, according to a new infographic by CoreSite.

The infographic explores some of the myths surrounding off premise data hosting.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results documents the accomplishments of CHS’s 24 ACOs under the MSSP program, the crucial role of data analytics in CHS operations, and the many lessons learned as an early trailblazer in value-based care delivery.

Get the latest healthcare infographics delivered to your e-inbox with Eye on Infographics, a bi-weekly, e-newsletter digest of visual healthcare data. Click here to sign up today.

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Infographic: 7 Reasons to Retire Legacy Healthcare Data to the Cloud

April 6th, 2018 by Melanie Matthews

Moving healthcare legacy data to the cloud can ease data lifecycle management challenges, according to a new infographic by Flatirons Jouve.

The infographic summarizes seven reasons why more healthcare organizations are adopting hosted solutions, including ones for application decommissioning and data archiving.

2018 Healthcare Benchmarks: Telehealth & Remote Patient MonitoringArtificial intelligence. Automation. Blockchain. Robotics. Once the domain of science fiction, these telehealth technologies have begun to transform the fabric of healthcare delivery systems. As further proof of telehealth’s explosive growth, the use of wearable health-tracking devices and remote patient monitoring has proliferated, and the Centers for Medicare and Medicaid Services (CMS) has added several new provider telehealth billing codes for calendar year 2018.

2018 Healthcare Benchmarks: Telehealth & Remote Patient Monitoring delivers the latest actionable telehealth and remote patient monitoring metrics on tools, applications, challenges, successes and ROI from healthcare organizations across the care spectrum. This 60-page report, now in its fifth edition, documents benchmarks on current and planned telehealth and remote patient monitoring initiatives as well as the use of emerging technologies in the healthcare space.

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Infographic: The Current State of Healthcare Predictive Analytics

March 12th, 2018 by Melanie Matthews

Most organizations sit on a wealth of healthcare data but raw data in itself is not enough to drive down costs and reduce risk, according to a new infographic by Advanced Plan for Health.

The infographic examines how to leverage predictive analytics to improve key areas of cost and risk including wellness programs, case management and telehealth use.

Predictive Healthcare Analytics: Four Pillars for SuccessWith an increasing percentage of at-risk healthcare payments, the Allina Health System’s Minneapolis Heart Institute began to drill down on the reasons for clinical variations among its cardiovascular patients. The Heart Institute’s Center for Healthcare Delivery Innovation, charged with analyzing and reducing unnecessary clinical variation, has saved over $155 million by reducing this unnecessary clinical variation through its predictive analytics programs.

During Predictive Healthcare Analytics: Four Pillars for Success, a 45-minute webinar on March 29th at 1:30 p.m. Eastern, Pam Rush, cardiovascular clinical service line program director at Allina Health, and Dr. Steven Bradley, cardiologist, Minneapolis Heart Institute (MHI) and associate director, MHI Healthcare Delivery Innovation Center, will share their organization’s four pillars of predictive analytics success…addressing population health issues, reducing clinical variation, testing new processes and leveraging an enterprise data warehouse. Click here for more information.

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