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How to Assess the ROI of Your Population Health Initiative

In the brave new world of value-based healthcare, investing in population health management (PHM) is a requirement for success. Defining PHM isn’t easy, but there is one common term that appears among all the diverse interpretations—outcomes. Assessing the potential ROI for investments in PHM using a clear, understandable framework, can help organizations methodically identify and prioritize their PHM investments. While not every PHM intervention makes sense for every situation, it is important to determine which programs provide the most benefit, as well as determining when the investment will begin paying dividends, to achieve success in the era of PHM.

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A Guide to Successful Outcomes Using Population Health Analytics

There seem to be a lot of definitions for population health management and population health analytics. But all these definitions share one thing: outcomes. The goal is to provide quality care outcomes with good patient experience outcomes at a low cost outcome. So, how can organizations systematically improve their outcomes? The answer lies in three key questions: What should be done to provide optimal care? How well are those best practices being followed? And how do those best practices move into everyday care for patients? Using a systematic approach to answering these three questions will lead organizations toward becoming an outcomes improvement machine.

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The Formula for Optimizing the Value-Based Healthcare Equation

Two variables are required in the value-based healthcare equation if it is to add up to a profitable contract. One variable, optimizing the care for the patient population, is commonly included and is a focus for most healthcare systems involved in managing population health. However, a second variable, getting the right dollars in order to care for that population, is often overlooked. And yet this variable is easier to attain. It’s a matter of appropriately assessing the risk of the population by addressing inaccurate diagnoses coding. Here, we offer four methods for solving this variable: identifying high-risk gaps over time, persistent diagnosis tracking, identifying code adequacy, and identifying likely diagnoses.

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Three Essential Systems for Effective Population Health Management

An effective population health management program must include three systems: Healthcare Analytics, Best Practice, and Adoption. Organizations with only one or two of these systems often display symptoms of weak and ineffective capability for population health management.  But when you have a analytics foundation based upon a data warehouse, combined with evidence-based practices contained in a best practice system, and the ability to deploy and implement systematic changes to healthcare processes, health systems are truly prepared to manage population of patients.

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Employer Health Plans: Keys to Lowering Cost, Boosting Benefits

Employers that offer robust employee health plans at affordable costs are more likely to attract and retain a great workforce. Healthcare, however, is often a top expense for organizations, making balancing attractive benefits with attractive costs a complex undertaking. Employers need a deep understanding of employee populations and opportunities to manage health plan costs without sacrificing quality. An analytics-driven approach to employee population health management gives employers insight into two key steps to lower healthcare costs and enhance benefits:

  1. Manage easily fixed cost issues.
  2. Use healthcare cost savings to fund expanded benefits.

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Six Challenges to Becoming a Data-Driven Payer Organization

As healthcare transitions from fee-for-service to value-based payment, payer organizations are increasingly looking to population health management strategies to help them lower costs. To manage individuals within their populations, payers must become data driven and establish the technical infrastructure to support expanding access to and reliance on data from across the continuum of care. To fully leverage the breadth and depth of data that an effective health management strategy requires, payers must address six key challenges of becoming data driven:

  1. Data availability.
  2. Data access.
  3. Data aggregation.
  4. Data analysis.
  5. Data adoption.
  6. Data application.

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Episode Analytics Now Mission Critical as Outcomes Meet Incomes: Partners HealthCare Paves Volume-To-Value Path With Late-Binding Data Warehouse

In this reprint from Microsoft, Dennis Schmuland, MD, FAAFP (Chief Health Strategy Officer, Microsoft US Health & Life Sciences), sits down with Sree Chaguturu, MD (Vice President and Chief Population Health Officer, Partners HealthCare) to learn how Partners HealthCare has prepared for the tipping point of value-based care.

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Four Population Health Management Strategies that Help Organizations Improve Outcomes

Population health management (PHM) strategies help organizations achieve sustainable outcomes improvement by guiding transformation across the continuum of care, versus focusing improvement resources on limited populations and acute care. Because population health comprises the complete picture of individual and population health (health behaviors, clinical care social and economic factors, and the physical environment), health systems can use PHM strategies to ensure that improvement initiatives comprehensively impact healthcare delivery. Organizations can leverage four PHM strategies to achieve sustainable improvement:

  1. Data transformation
  2. Analytic transformation
  3. Payment transformation
  4. Care transformation

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Custom Care Management Algorithms that Actually Reveal Risk

Care management is a tool for population health that focuses scarce healthcare resources on the sickest patients. Care management leaders need to know who those sickest patients are (or may be). The static risk models typically used for stratifying patients into risk categories only paint a partial picture of health and are ineffective for modern care management programs. Custom algorithms are now capable of predicting risk based on multiple risk models and multiple data sources. They help care management teams confidently stratify patient populations to paint a complete picture of care needs and efficiently deliver care to those who need it most. This article explains how custom algorithms work on static risk models to normalize risk scores and improve patient stratification, care management, and, ultimately, population health management.

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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:

  1. Transitions in payment.
  2. Disruption from familiar players and newcomers.
  3. 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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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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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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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 that are certainly useful for the next three years.  In this paper, I discuss the criteria and try my best to share an unbiased evaluation of sample of the PHM companies in this space.

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Patient Registries Turn Knowledge into Outcomes Improvements

In today’s data-rich healthcare environment, patient registries put knowledge in front of the people who will use it to improve outcomes and population health. Non-IT professionals (e.g., clinicians and researchers) often don’t have direct, timely access to operational and clinical data. As a result, organizations miss out on important improvement opportunities and data-driven point-of-care decisions. Knowledge too often remains siloed in the enterprise data warehouse (EDW) or among specialized groups. Patient registries remove these barriers. It allows clinicians and researchers to make informed choices and frees up data analysts to focus on their priority areas.

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A Critical Role for Better Population Health Management

Unnecessary barriers to practice and licensing limitations have severe consequences for health systems’ population health initiatives, especially as the nationwide shortage of healthcare practitioners continues to grow:

  • Delayed access to clinicians.
  • Decreased access to care, particularly primary care and care in rural areas.
  • Limited labor supply.
  • Increased costs of services.
  • Loss of potential revenue for healthcare organizations.
Using clinical nurse specialists as an example—one of many critical roles in population health management—effectively demonstrates the importance of removing unnecessary barriers to practice, from reductions in unnecessary readmissions and reduced length of stay (LOS), to less frequent ED visits and higher patient satisfaction. The bottom line, when it comes to barriers to practice, is that removing them (with solutions like uniform regulations) will do more than improve population health management—it will also reduce costs and improve patient outcomes.

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How Care Management Done Right Improves Patient Satisfaction and ROI

A comprehensive care management program organizes many moving parts into an efficient workflow and brings order to the complex, often messy, world of healthcare. Care coordination harmonizes the workflow of clinicians, patients, family, social workers, and therapists, to name a few. It facilitates medication reconciliation, care compliance, appointment scheduling, and communication with patients, as well as engagement between patients and the care team. Care coordination concentrates on the highest-utilization, highest-cost patients to produce better clinical, operational, and financial outcomes, the bottom line goals for healthcare systems involved in population health and value-based care. This article details the benefits of, and barriers to, care management and coordination, their role in population health, and the technology that’s helping to automate this area of healthcare.

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Three Essential Systems for Effective Population Health Management

An effective population health management program must include three systems: Healthcare Analytics, Best Practice, and Adoption. Organizations with only one or two of these systems often display symptoms of weak and ineffective capability for population health management.  But when you have a analytics foundation based upon a data warehouse, combined with evidence-based practices contained in a best practice system, and the ability to deploy and implement systematic changes to healthcare processes, health systems are truly prepared to manage population of patients.

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Understanding Risk Stratification, Comorbidities, and the Future of Healthcare

Risk stratification is essential to effective population health management. To know which patients require what level of care, a platform for separating patients into high-risk, low-risk, and rising-risk is necessary. Several methods for stratifying a population by risk include: Hierarchical Condition Categories (HCCs), Adjusted Clinical Groups (ACG), Elder Risk Assessment (ERA), Chronic Comorbidity Count (CCC), Minnesota Tiering, and Charlson Comorbidity Measure. At Health Catalyst, we use an analytics application called the Risk Model Analyzer to stratify patients into risk categories. This becomes a powerful tool for filtering populations to find higher-risk patients.

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Improve Patient Engagement with Five Public Health-Inspired Principles

Patient engagement is critical as we move toward population health—as patients who engage in their own care by following medical recommendations and making healthy nutrition and lifestyle choices will have better outcomes and experiences. There isn’t, however, a clear path to successful patient engagement. Fortunately, public health can lend several established principles that may help us better involve patients in their own care:

  1. Using systematic, population-level solutions that require less individual effort.
  2. Engaging patients on interpersonal and community levels as well as personal.
  3. Identifying root-cause, assessing and capitalizing on strengths, and engaging stakeholders.
  4. Using strategies from behavioral economics to help individuals make good choices.
  5. Anticipating failure and learning from it.

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The 6 Critical Components of Population Health

This article examines how to define population health through a review of the top analytics research firms. It lands on a single theme, but in the process it uncovers six common categories of IT capabilities required to successfully manage population health:

  1. Data Aggregation
  2. Patient Stratification
  3. Care Coordination
  4. Patient Engagement
  5. Performance Reporting
  6. Administrative/Business
These six strategic components define the population health ecosystem, and successful organizations must multitask across these domains, working with an enterprise data warehouse, if they hope to thrive in value-based healthcare and become true partners and assets in their respective communities.

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