Healthcare Reform: Is Bipartisan Legislation Possible?

The effort to repeal and replace the ACA in 2017 failed, leaving the industry wondering if bipartisan healthcare reform is possible in today’s political climate. This article explains why it is possible, by taking a close look at why repeal and replace failed, and why the 21st Century Cures Act and MACRA have been successful. To stand a chance of being successful, proposed bipartisan healthcare legislation will most likely have one (or more) of five features: Driven by practical need rather than politics. Focuses on cost control/cost reduction. Targets areas that are expected to save money. Doesn’t involve creating new programs. Stabilizes the ACA. There are many bipartisan healthcare legislation opportunities, from expanding the use of HSAs to innovation waivers;…

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The Top Three Healthcare Financial Trends in 2017: Payment Transitions, Disruption, and New Skills

Influential healthcare financial trends in 2017 emerged in three areas: Transitions in payment. Disruption from familiar players and newcomers. Emerging data skillsets. Uncertainty has been a common theme for 2017. Organizations continue waiting for clarity on the future of the Affordable Care Act (ACA), while working to implement value-based care. Changes from established healthcare organizations as well as the arrival of prominent newcomers (e.g., Amazon) add to the unsettled outlook, as do emerging data skillsets. Amid the uncertainty, however, healthcare is clearly continuing on the path to patient-centered care. Organizations best positioned for 2018 will understand their performance in 2017’s top three healthcare financial trends as they evaluate their preparedness for the coming year.

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Machine Learning in Healthcare: How it Supports Clinician Decisions—and Why Clinicians are Still in Charge

Machine learning in healthcare is transforming healthcare with its ability to tackle data variability and complexity. Everyone in healthcare should embrace this new technology and its ability to deliver more precise, faster, data-driven insight to clinical teams. But just as machine learning has benefits, it also has limitations; for example, it loses its impact when implemented without realistic expectations or without thorough integration with existing clinical processes. As the FDA works to publish guidance on digital health services, including governance regarding the use of algorithms to support clinical decisions, it’s important for everyone in the industry to hold themselves accountable for the quality of the data and the processes that put this data in front of clinicians. Machine learning is…

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Communication in Healthcare Culture: Eight Steps to Uphold Outcomes Improvement

Healthcare leaders looking to establish and sustain a culture of large-scale outcomes improvement must communicate their health system’s values, beliefs, and norms throughout the entire organization. Effective communication spreads understanding of outcomes improvement, ensuring broad engagement and ongoing progress toward shared goals. An eight-step strategy describes essential elements of organizational outcomes improvement communication plan: Include a communications specialist on the outcomes improvement leadership team.  Analyze the stakeholders early and often. Craft the central message around shared values. Be a constant champion. Commit to regular times and mechanisms for communication. Make sure communication flows both ways. Be transparent. Be creative.

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Medical Libraries: An Essential Resource in Outcomes Improvement

In healthcare outcomes improvement work, where best-practice insight and evidence-based knowledge are critical, medical libraries are an essential resource. Medical libraries are more valuable than ever in today’s digital world, in which information is readily available, but accessing accurate, focused evidence requires specialized skill and means. Organizations aiming to improve quality and move successfully toward value-based care need both data from the enterprise data warehouse (EDW) and evidence from the medical library. While data identifies opportunities for improvement, evidence furnished by the medical library shows whether proposed solutions are viable. Together, both knowledge bases drive pragmatic, sustainable improvement.

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Transitional Care Management: Five Steps to Fewer Readmissions, Improved Quality, and Lower Cost

Reducing readmissions is an important metric for health systems, representing both quality of care across the continuum and cost management. Under the Affordable Care Act, organizations can be penalized for unreasonably high readmission rates, making initiatives to avoid re-hospitalization a quality and cost imperative. A transitional care management plan can help organizations avoid preventable readmissions by improving care through all levels in five steps: Start discharge at the time of admission. Ensure medication education, access, reconciliation, and adherence. Arrange follow-up appointments. Arrange home healthcare. Have patients teach back the transitional care plan.

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8 in 10 Hospitals Stand Pat on Population Health Strategy, Despite Uncertainty Over the Affordable Care Act’s Future

A 2017 survey by Health Catalyst shows that despite uncertainty about the future of the Affordable Care Act, 80 percent of healthcare executives have not paused or otherwise changed their population health management strategy. 68 percent said that PHM is “very important” to their healthcare delivery strategy, while fewer than 3 percent said it was not important at all. The results show that executives view the move to value-based care as inevitable, and they view a PHM strategy as an integral part of their future efforts.

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A Behind-the-Scenes Look at Healthcare IT Analyst Rankings and Reports: What You Should Know

Healthcare leaders often turn to healthcare IT analyst rankings and reports for information that drives vendor-related decision making. Knowing the key differences between several notable healthcare and cross-industry IT analysts—what methodologies they employ to gather data, their missions and goals (ranking vs. consulting), and how much of their own opinions they interject (unbiased vs. opinionated)—will help healthcare leaders be more educated consumers of the reports and rankings that saturate healthcare. This article provides a high-level overview of the key differences between several healthcare IT analysts: KLAS Research (ranking focus) Black Book Rankings (ranking focus) Chilmark Research (ranking and consulting focus) Advisory Board (consulting focus) It also looks at the most notable cross-industry IT analysts that apply a healthcare-specific lens to…

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How to Evaluate a Clinical Analytics Vendor: A Checklist

Based on 25 years of healthcare IT experience, Dale outlines a detailed set of criteria for evaluating clinical analytic vendors. These criteria include 1) completeness of vision, 2) culture and values of senior leadership, 3) ability to execute, 4) technology adaptability and supportability, 5) total cost of ownership, 6) company viability, and 7) nine elements of technical specificity including data modeling, master data management, metadata, white space data, visualization, security, ETL, performance and utilization metrics, hardware and software infrastructure.

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HAS 17 Metrics—From Attendee Experience to Superheroes

Using survey results from the 2017 Healthcare Analytics Summit™ (HAS) conference, the HAS team has compiled an infographic of key insights. Featured metrics include: Overall satisfaction: 99.4 percent Likelihood of recommending to a friend: 98.4 percent. Attendee metrics, such as healthcare experience (27.6 percent with 11 to 20 years) and type of organizations represented (healthcare, 45.7 percent). Organizational population health status (successful initiatives, 63.2 percent). Organizational level of analytics adoption (intermediate, 49.7 percept). Combined, the HAS 17 metrics revealed high overall satisfaction with what attendees viewed as a true educational experience. Participants also reported deep healthcare expertise, a positive outlook on population health and value-based care.

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Population Health Documentary Highlights Three Success Stories Transforming Healthcare

The documentary, “A Coalition of the Willing: Data-Driven Population Health and Complex Care Innovation in Low-Income Communities” shows how precision medicine and care management can be effective tools for successful population health. The film highlights three programs that use data to hotspot populations of high-risk, high-need patients, and then deploy unique, targeted care management inventions. The documentary, which initially aired during the 2017 Healthcare Analytics Summit, presents hopeful solutions, scalable across diverse patient populations, that are leading to exceptional results and the future of healthcare transformation.

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Machine Learning 101: 5 Easy Steps for Using it in Healthcare

Machine learning, used in the context of healthcare, is not about computers replacing doctors or rolling robots dispensing bedside care to patients. Perhaps a better term would be data-driven healthcare because it is the process of using historical patient data in a predictive model to determine the likelihood of a healthcare-related outcome. The black box that is the machine is no more than an algorithm trained by data. Most importantly, the predictions can be used by doctors to optimize decision making in real time, thus reducing readmissions, infection rates, and other complications that drive up costs and lower the quality of care. This article explains some machine learning basics, dispels some misconceptions, and outlines five steps to its implementation: Define…

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Use ACE Scores in Machine Learning to Predict Disease Earlier and Improve Outcomes

The Adverse Childhood Experience (ACE) study conducted by the CDC and Kaiser Permanent showed a strong correlation between ACEs and negative health outcomes later in life (e.g., risky health behaviors, chronic health conditions, and early death). ACE scores help paint a more complete picture of a person’s health history—a more comprehensive data snapshot of the entire patient. Given that ACE scores build better data sets and machine learning relies on high-quality data, health systems should incorporate these nutrient-rich data sources into their machine learning models to better predict negative health outcomes, allow for earlier interventions, and improve outcomes. Healthcare machine learning is evolving to use ACE scores and lifestyle data (e.g., eating habits) to improve population health management.

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On the Population Health and Cost Transformation Stage, Care Management Is the Star

Joe’s story isn’t a unique one in the U.S. Having been admitted to the hospital five times in one month, Joe isn’t taking his medications and doesn’t exercise. In short, he struggles to follow his care plan. The Care Management Show, an entertaining, interactive theatrical performance, demonstrates why health systems need to adopt innovative, data-driven approaches to care management that prevent patients from falling through the cracks by integrating all aspects of patient care: Data integration. Patient stratification and intake. Care coordination. Patient engagement. Performance measurement. Throughout the show, the audience witnesses how care management done right transforms not only Joe’s life, but also Millrock Hospital’s profitability. We see how health systems can leverage technology to engage their “Joes” to…

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Healthcare Analytics Summit 2017 Final Day: Thursday Recap

On Thursday, the last day of the Healthcare Analytics Summit, attendees learned about a “flipped” health system from Maureen Bisognano; found out from Robert DeMichiei that we “have a cost problem” (but it’s not what you think); discovered the four ways healthcare got into this predicament—and what to do about it—according to David Nash, MD; and saw what a “Coalition of the Willing” can do in low-income communities with the HAS Documentary.

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Healthcare Culture: Choosing a Systems-Based Approach Over Punishment and Reward

It’s often human nature to look for a culprit or hero when there’s a setback or success. In healthcare, however, this punishment-and-reward formula puts patient outcomes at risk, as it doesn’t consider all factors that contribute to a result and lead to a better process. The key to failure or success is most likely a chain of events, and not an individual action. To avoid the same mistake again or build on good practices, healthcare leaders must look at the system, not the individual or their actions. Effective improvement leadership will standby a systems approach, even under the most challenging circumstances.

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Healthcare Decision Support: A Modern Tool for Today's Chief Nursing Officer

Chief Nursing Officers (CNOs), essential members of health system C-Suite teams, need healthcare decision support to align nursing resources with systemwide goals. Although nursing’s purpose hasn’t changed, the tools and skills needed to achieve it have. In today’s data-driven, increasingly complex care environment, nursing leaders rely on skills that extend beyond their initial training as nurses; they need expertise in finance, IT, and analytics, among other areas. CNOs, like Faye of Pennington Health, depend on healthcare decision support systems for easy access to data that helps them identify and prioritize the best opportunities, address challenges, and improve outcomes. CNOs who embrace the fact that advanced analytical tools are critical to improving care quality and reducing care costs are poised to…

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Chilmark Report Studies the 2017 Healthcare Analytics Market Trends and Vendors

Chilmark’s 2017 Healthcare Analytics Market Trends Report is a trove of insights to the analytics solutions driving the management of population health and the transition to new reimbursement models. The report reviews the analytics market forces at work, such as: The need to optimize revenue under diverse payment models. The increasing importance of analytics in general, and a platform in specific, that can aggregate all data. Continuing confusion about how to react to MIPS and APMs. The growing importance of providing a comprehensive set of open and standard APIs. The need for better tools to create analytics-ready data stores. The report is also a succinct guide to the 17 leading analytics vendors (which represent EHR, HIE, payer, and independent categories)…

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Investing in Partnerships for Outcomes Improvement

Many healthcare organizations invest for financial, strategic, and operational reasons. These investments cover a broad spectrum of opportunities, from medical technology, to delivery models, to promising new research. Health Catalyst follows these investment avenues, building long-term relationships, and connecting with its partners in three ways: As owners. As innovators. As customers. The sole focus of these investments and partnerships is outcomes improvement—a unique approach in healthcare—supported by the operating principles of ownership, pragmatic innovation, and transparency. In this first article of a series, Kyle Salyers, Health Catalyst Senior Vice President of Business Development, explores the partnership “flywheel” and the collaborative nature that underscores a successful healthcare investment platform.

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Healthcare Analytics Summit 2017 Kicks Off: Wednesday Recap

The 2017 Healthcare Analytics Summit started Tuesday night with the Analytics Walkabout, the Products and Services Showcase, and the Care Management Show. Wednesday morning featured a fascinating keynote addresses from Thomas Davenport, Eric Topol, and Dale Sanders. Attendees were also treated to the HAS 17 Edition of “Hollywood Squares” with Tom Burton.

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HAS 17 Session Shares Strategy for Achieving Triple Aim

Like many U.S. health systems, Allina Health understands the importance of the Triple Aim in today’s healthcare environment—as the industry confronts rising costs along with inadequate quality of care. With the move toward value-based care, these factors will increasingly impact market share. Allina is responding with its Clinical Value Process initiative. The organization uses this fully integrated multidisciplinary strategy to make outcomes improvement decisions and measure both the quality and fiscal performance of improvement projects. Key elements of Clinical Value Process include: Reducing variation. Organizing for a systemwide improvement plan. Using data to identify improvement opportunities and monitor progress.

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Closed-Loop Analytics Approach: Making Healthcare Data Actionable

Healthcare organizations rely on data to support informed decisions. To be truly valuable, data must be high quality and meet two criteria for end-users: Data must be transformed from its raw, obscure form into actionable insights. Data-driven insights must be immediately accessible at the point of care (versus in static dashboards or buried on the intranet). Closed-Loop Analytics™ methodology transforms raw data into actionable, accessible insight—providing physicians and nurses with critical insight into their patients’ situation and how they can effectively intervene. A Closed-Loop Analytics approach will become increasingly essential as healthcare becomes more systems dependent.

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Why Healthcare Decision Support Is No Longer Optional for Chief Operating Officers

Without daily access to healthcare decision support, health system COOs struggle to make rapid, meaningful decisions. Healthcare decision support systems are no longer optional for these highly visible leaders, who play critical roles in their organizations’ success, for many reasons: Aggregates reliable, up-to-date information from all available sources. Presents information in user-friendly, user-configurable ways. Makes trends and important conclusions more recognizable and understandable. Enhances C-Suite’s ability to drill down into data in search of a problem’s root cause. Improves C-Suite communication and collaboration. Unites C-suites around a common vision and strategy. Healthcare COOs (and other C-Suites) need healthcare decision support to be data-driven problem solvers and collaborative leaders who achieve clinical, financial, and operational success for their systems. Given the…

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A Landmark, 12-Point Review of Population Health Management Companies (Executive Report)

Population health management (PHM) is in its early stages of maturity, suffering from inconsistent definitions and understanding, overhyped by vendors and ill-defined by the industry. Healthcare IT vendors are labeling themselves with this new and popular term, quite often simply re-branding their old-school, fee-for-service, and encounter-based analytic solutions.  Even the analysts —KLAS, Chilmark, IDC, and others—are also having a difficult time classifying the market. In this paper, I identify and define 12 criteria that any health system will want to consider in evaluating population health management companies.  The reality of the market is that there is no single vendor that can provide a complete PHM solution today.  However there are a group of vendors that provide a subset of capabilities…

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HAS 17 Keynote, Eric Topol, Signals New Era in Digital Healthcare

Healthcare is poised for groundbreaking change, in which the fusion of unprecedented access to mobile technology and advanced understanding of disease brings in the era of truly individualized medicine. Eric Topol, M.D., a leader in digital medicine, will share his vision for the wireless medicine revolution at the 2017 Healthcare Analytics Summit™ conference. In the next data-driven generation of democratized healthcare, consumers will monitor personal health information—from vital signs to fetal heartrate—directly on their smartphones. Real-time access to health status will make consumers true partners in their own care, enabling them to make proactive decisions to improve their health and prevent or respond to critical events.

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