Posts Tagged ‘Data Analytics’

Infographic: 5 Ways Data Analytics Can Help the Healthcare Industry

August 22nd, 2018 by Melanie Matthews

Using data analytics, healthcare providers can take charge of the information from multiple sources and convert it into meaningful insights that can lead to timely and strategic decisions, according to a new infographic by Snuvik Technologies.

The infographic looks at how data sources can help deliver next-level insights to patients using big data analytics.

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: Three Steps To Controlling Healthcare Costs with Data

June 21st, 2018 by Will Herold

Three Steps To Controlling Healthcare Costs with Data

Data analytics is key to reaching the goal of controlling healthcare costs.

Data analysis plays a key role controlling and potentially lowering healthcare costs, according to DHS Group.

DHS Group, an employer and health plan solutions provider based in Houston and Cleveland, provides three steps to reach the goal of controlling healthcare costs:

  1. Invest in your partners: If data, and the information you gather from accessing, reading and interpreting it, is important to you, then the company you work for to get the job done should be too. Don’t underestimate the value of investing in a partner that will go above and beyond in making sure the money you’re investing is put to good use and you’re able to access and understand the information you’re looking to gain.

  2. See data as actionable information: If you’re taking the time, and spending the money, to gain access to your data, consider the idea that the “data” is more meaningful when viewed as a place where actionable information resides. Look for partners that will translate your data into “Key Health Metrics” or information that you can make real decisions with based on your goals and benchmarks.

  3. Integrate your systems: Use the actionable information you have gained from your data to make informed decisions on the health and wellbeing of your employees – expanding programs to include areas like mental health and financial wellbeing. Data-driven benefits programs work best alongside health and wellbeing programs that are being driven by the same numbers and facts.

“Most people don’t realize all that can be done with regular access to claims data,” Jim Pritchett, DHS Group CEO, said. “Better plan design, discovery of preventative initiatives, empowering your members to better manage their health, identifying hard-dollar pharmacy savings, improving engagement and measuring ROI.”

Will Herold

About the Author: With years of experience in HR and benefits industries, Will Herold leads DHS Group’s Business Development team with a strong understanding of the HR and benefits marketplace. As a sales leader, he is responsible for managing DHS Group’s revenue and working with other professionals to assist corporations in establishing clear, aligned strategies for impactful, cost-effective benefit and wellbeing program outcomes.

Guest Post: Lab Data is the Missing Link in Healthcare Risk Adjustment

June 19th, 2018 by Jason Bhan, MD

Data informing risk adjustment programs is critical under value-based healthcare reimbursement models.

For health plans, value-based care means a continuous need to innovate and improve their risk adjustment, clinical quality, and care management programs. Unless payers identify and receive the correct amount of reimbursement, it is difficult for them to invest appropriately into member care programs for better outcomes while remaining financially successful.

The data informing risk adjustment programs are critical, as they build the foundation for accurate member risk stratification. In that respect, those data sources are directly related to the correct amount of reimbursement payers receive and can invest in proactive care management. In other words, high-quality clinical data delivered quickly enough for a plan to get a member into a care management program early enough is important to the health of the member and the business. The approach leads to improved clinical outcomes and reduced costs in emergency room visits, hospitalizations and chronic condition management.

Lab Data: An Untapped Resource

To achieve such clinical granularity, at scale, plans can turn to diagnostics—or lab—data. Lab data drives approximately 70 percent of medical decisions and, unlike claims data, is available in near real-time. It also provides an unrivaled level of specificity for clinical conditions. When lab data is integrated into plans’ claims- and chart-based programs, it enables earlier, more comprehensive and accurate clinical insights to benefit care management of both existing and new members. Utilizing the same information that clinicians use to make decisions, within the same timeframe, provides a powerful and unique opportunity to intervene and impact a patient’s health.

What Can Lab Data Do for You?

Expanding and improving their clinical data supply with diagnostics data can help health plans to:

  • Provide historical insights on members where claims are unavailable to improve risk adjustment. For new enrollees, this enables the health plan to get new members into the appropriate care/disease management programs from day one.
  • Serve as an early detection system for care management of all enrollees. Plans can identify patients in need of additional or alternative therapy from lab data earlier than from any other data source. For existing members, the detailed results uncover needs that may have been overlooked based on a claims analysis alone.
  • Identify high-risk members for case management and provider interventions from lab data. Optimized risk adjustment aligns reimbursements to health status, enabling the plan to more heavily invest in member care programs.

Applying AI Solutions

When it comes to gaining actionable insights from diagnostics data, plans can benefit from partnering with healthcare artificial intelligence (AI) specialists in the field. Healthcare AI organizations use techniques such as machine learning and natural language processing—coupled with massive computational power—on big data sets, to make sense out of non-standard, complex, and heterogeneous data.

Healthcare AI, when applied to diagnostics clinical lab data, improves risk stratification by identifying diagnoses earlier in the year versus waiting for the claim or searching charts. Rich in clinical details, it presents a more complete picture of the member’s health. Better risk stratification leads to better care management programs; and successful programs have been shown to reduce costs by targeting those most likely to benefit and keeping intervention costs low.

Dr. Jason Bhan

About the Author: Jason Bhan, MD, is co-founder and Chief Medical Officer at Prognos, an innovator in applying AI to clinical lab diagnostics. More than half of the Prognos team is made of engineers, data scientists, and clinicians. Prognos aims to increase the usefulness of disparate healthcare data to better inform clinical decisions and ultimately improve patient outcomes.

Infographic: Unlock Your Data To Optimize Your EMR

June 6th, 2018 by Melanie Matthews

As healthcare shifts from volume to value, imaging clinicians need intelligent solutions that help them leverage the data available in the EMR at the point of care for faster, more accurate diagnoses, according to a new infographic by Change Healthcare.

The infographic examines how to mine clinical information and leverage it in a way that provides more efficient care.

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: Enabling a 360-degree View of Patient Data

May 2nd, 2018 by Melanie Matthews

As healthcare organizations move toward more integrated and personalized service delivery, they need the ability to securely access and analyze all data along the patient journey, according to a new infographic by BridgeHead.

The infographic examines how an Application Independent Clinical Archive (AICA) provides this type of patient-data view.

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: 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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Infographic: Hospital CIOs’ 2018 Priorities

January 15th, 2018 by Melanie Matthews

Hospital CIOs are wrestling with a wide range of technology challenges, according to a new infographic by Spok.

The infographic details the trop priorities of hospital CIOs this year, including the progress toward a mobile health strategy.

Remote Patient Monitoring for Chronic Condition Management: Leveraging Technology in a Value-Based System Encouraged by early success in coaching 23 patients to wellness at home via remote monitoring, CHRISTUS Health expanded its remote patient monitoring (RPM) enrollment to 170 high-risk, high-cost patients. At that scaling-up juncture, the challenge for CHRISTUS shifted to balancing its mission of keeping patients healthy and in their homes with maintaining revenue streams sufficient to keep its doors open in a largely fee-for-service environment.

Remote Patient Monitoring for Chronic Condition Management: Leveraging Technology in a Value-Based System chronicles the evolution of the CHRISTUS RPM pilot, which is framed around a Bluetooth®-enabled monitoring kit sent home with patients at hospital discharge.

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Infographic: The Prescription for Getting ROI From Analytics

July 26th, 2017 by Melanie Matthews

As the amount of patient data increases, healthcare organizations are investing in healthcare analytics solutions, according to a new infographic by IBM. To allow organizations to draw complex data insights from intricate, personal and rapidly changing data, healthcare organizations can benefit from a complete business intelligence (BI) solution.

The infographic looks at the trends driving this investment in analytics.

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.

Have an infographic you’d like featured on our site? Click here for submission guidelines.

Infographic: Healthcare Analytics and Big Data

April 12th, 2017 by Melanie Matthews

There is an estimated 50 Petabytes of data in the healthcare realm, predicted to grow to 25,000 Petabytes by 2020, according to a new infographic by Oracle. Analyzing this data powers decision-making from preventive care to disease
management to population health.

The infographic examines how data analytics can support the continuum of care and improve the patient experience.

2016 Healthcare Benchmarks: Data Analytics and IntegrationThe 2016 Healthcare Benchmarks: Data Analytics and Integration assembles hundreds of metrics on data analytics and integration from hospitals, health plans, physician practices and other responding organizations, charting the impact of data analytics on population health management, health outcomes, utilization and cost.

2016 Healthcare Benchmarks: Data Analytics and Integration examines the goals, data types, collection processes, program elements, challenges and successes shared by healthcare organizations responding to the January 2016 Data Analytics survey by the Healthcare Intelligence Network. Click here for more information.

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