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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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Value-Based Purchasing: Four Need-to-Know Domains for 2018

Health systems that meet the 2018 Hospital Value-Based Purchasing Program measures stand to benefit from CMS’s $1.9 billion incentive pool. Under the 2018 regulations, CMS continues to emphasize quality. To reduce the risk of penalty and vie for bonuses, it’s increasingly critical that organizations leverage data to build skills and processes that meet more demanding reimbursement measures. To thrive under value-based payment, healthcare systems must understand CMS’s four quality domains, and their associated measures, for 2018:

  1. Clinical Care
  2. Patient- and Caregiver-Centered Experience of Care/Care Coordination
  3. Efficiency and Cost Reduction
  4. Safety

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A Guide to Applying Quality Improvement to Healthcare: Five Principles

Healthcare is an art and a science. What many in the industry don’t understand is that systems and processes can coexist with personalized care. Quality improvement methods can be as effective in healthcare as they have been in other industries (e.g., agriculture, manufacturing, etc.). Quality improvement in healthcare is not just achievable, it’s an absolute necessity given the amount of wasteful spending in the U.S. on healthcare. Organizations can reduce this wasteful spending while improving their processes by applying these five guiding principles:

  1. Facilitate adoption through hands-on improvement projects.
  2. Define quality and get agreement.
  3. Measure for improvement, not accountability.
  4. Use a quality improvement framework and PDSA cycles.
  5. Learn from variation in data.
By using these principles and starting small, organizations can quicken the pace of quality improvement in healthcare.

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Quality Data Is Essential for Doctors Concerned with Patient Engagement

It might be a bit of a leap to associate quality data with improving the patient experience. But the pathway is apparent when you consider that physicians need data to track patient diagnoses, treatments, progress, and outcomes. The data must be high quality (easily accessible, standardized, comprehensive) so it simplifies, rather than complicates, the physician’s job. This becomes even more important in the pursuit of population health, as care teams need to easily identify at-risk patients in need of preventive or follow-up care. Patients engaged in their own care via portals and personal peripherals contribute to the volume and quality of data and feel empowered in the process. This physician and patient engagement leads to improved care and outcomes, and, ultimately, an improved patient experience.

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Why Health Systems Must Use Data Science to Improve Outcomes

In today’s improvement-driven healthcare environment, organizations must ensure that improvement measures help them reach desired outcomes and focus on the opportunities with optimal ROI. With data science-based analysis, health systems leverage machine learning to determine if improvement measures align with specific outcomes and avoid the risk and cost of carrying out interventions that are unlikely to support their goals. There are four essential reasons that insights from data science help health systems implement and sustain improvement:

  1. Measures aligned with desired outcomes drive improvement.
  2. Improvement teams focus on processes they can impact.
  3. Outcome-specific interventions might impact other outcomes.
  4. Identifies opportunities with optimal ROI.

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Prioritizing Healthcare Projects to Optimize ROI

Healthcare organizations have long relied on traditional benchmarking to compare their performance to others and determine where they can do better; however, to identify the highest ROI improvement opportunities and understand how to take action, organizations need more comprehensive data. Next-generation opportunity analysis tools, such as Health Catalyst® Touchstone™, use machine learning to identify projects with the greatest need for improvement and the greatest potential ROI. Because Touchstone determines prioritization with data from across the continuum of care, users can drive improvement decisions with information appropriate to their patient population and the domains they’re addressing.

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Care Management Analytics: Six Ways Data Drives Program Success

To succeed in improving outcomes and lowering costs, care management leaders must begin by selecting the patients most likely to benefit from their programs. To identify the right high-risk and rising-risk patients, care managers need data from across the continuum of care and tools to help them access that knowledge when they need it. Analytics-driven technology helps care managers identify patients for their programs and manage their care to improve outcomes and lower costs in six key ways:

  1. Identifies rising-risk patients.
  2. Uses a specific social determinant assessment to capture factors beyond claims data.
  3. Integrates EMR data to achieve quality measures.
  4. Identifies patients for palliative or hospice care.
  5. Identifies patients with chronic conditions.
  6. Increases patient engagement.

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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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The Real Opportunity of Precision Medicine and How to Not Miss Out

Precision medicine, defined as a new model of patient-powered research that will give clinicians the ability to select the best treatment for an individual patient, holds the key that will allow health IT to merge advances in genomics research with new methods for managing and analyzing large data sets. This will accelerate research and biomedical discoveries. However, clinical improvements are often designed to reduce variation. So, how do systems balance tailoring medicine to each patient with standardizing care? The answer is precise registries. For example, using registries that can account for the most accurate, specific patients and disease, clinicians can use gene variant knowledge bases to provide personalized care.

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Measuring the Value of Care Management: Five Tools to Show Impact

To earn legitimacy and resources within a healthcare organization, care management programs need objective, data-driven ways to demonstrate their success. The value of care management isn’t always obvious; while these programs may, in fact, be responsible for improvements in critical metrics, such as reducing readmissions, C-suite leaders need visibility into care management’s impact and processes to understand precisely how they’re improving care and lowering costs at their organizations. Five analytics-driven technologies give healthcare leaders a comprehensive understanding of care management performance:

  1. The Patient Stratification Application
  2. The Patient Intake Tool
  3. The Care Coordination Application
  4. The Care Companion Application
  5. The Care Team Insights Tool

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