How to Use Text Analytics in Healthcare to Improve Outcomes—Why You Need More than NLP

Given the fact that up to 80 percent of clinical data is stored in unstructured text, healthcare organizations need to harness the power of text analytics. But, surprisingly, less than five percent of health systems use it due to resource limitations and the complexity of text analytics. But given the industry’s necessity to use text analytics to create precise patient registries, enhance their understanding of high-risk patient populations, and improve outcomes, this executive report explains why systems must start using it—and explains how to get started. Health systems can start using text analytics to improve outcomes by focusing on four key components:

  1. Optimize text search (display, medical terminologies, and context).
  2. Enhance context and extract values with an NLP pipeline.
  3. Always validate the algorithm.
  4. Focus on interoperability and integration using a Late-Binding approach.
This broad approach with position health systems for clinical and financial success.

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Why Patient-Reported Outcomes Are the Future of Healthcare—and the Key to Ruth’s Independence

Patient-reported outcomes (PROs), defined as “any report of the status of a patient’s health condition that comes directly from the patient, without interpretation of the patient’s response by a clinician or anyone else,” are the future of healthcare. In addition to helping people like 80-year-old-Ruth continue to live interpedently, PROs—interchangeable with the term patient-generated health data (PGHD)—have several benefits:

  1. Effectively supplement existing clinical data, filling in gaps in information and providing a more comprehensive picture of ongoing patient health.
  2. Provide important information about how patients are doing between medical visits.
  3. Gather information on an ongoing basis—rather than just one point in time—and provide information relevant to preventive and chronic care management.
The new technologies that enable PROs and PGHD (e.g., sensors that detect whether Ruth takes food out of her refrigerator on a regular basis), generate important data outside of patients’ traditional care environments, sharing it with care teams to expand the depth, breadth, and continuity of information available to improve healthcare and outcomes.

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Introducing Health Catalyst MACRA Measures & Insights—Addresses Top Physician Concern: Capturing Compliance Measures

A recent Health Catalyst®/Peer60 survey revealed that compiling quality metrics is the top concern for physicians—a regulatory burden expected to worsen in 2017 as physicians struggle to report quality metrics for the Medicare Access & CHIP Reauthorization Act (MACRA)—the federal law that changes the way Medicare pays doctors. MACRA Measures & Insights™—Health Catalyst’s new MACRA solution—does so much more than alleviate this reporting burden:

  • Helps health systems track and monitor all MACRA measures across multiple departments.
  • Helps systems maximize Medicare reimbursement and monitor performance against measures year over year.
  • Enables healthcare organizations to tactically and strategically identify the optimal measures to include within multi-year, value-based care contracts with commercial payers.
Powered by the Health Catalyst Analytics Platform™, which can integrate virtually all of the granular data in a healthcare system, including claims and other external data, MACRA Measures & Insights gives health systems deep insight into performance measures at the degree of detail required for measurement and performance improvement.

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Are Health Systems Ready for MACRA? Survey Reveals the Number One MACRA Concern and Varying Degrees of Readiness

The Medicare Access and Chip Reauthorization Act (MACRA) replaces a number of value-based reimbursement programs and will use 2017 as its first reporting year. But, despite being right around the corner, a survey of healthcare professionals around the country reveals only one-third are ready. But while only 35 percent of respondents have a strategy and believe they’re prepared for MACRA, most will participate in the new program. A majority of surveyed hospitals believe MACRA will benefit their physicians (or that they’ll at least break even). MACRA is new, complicated, and rife with uncertainties given the new administration. According to the survey, the top concern for health systems is compiling MACRA quality measures. But despite the industry’s slow movement towards MACRA, the bottom line is that it’s right around the corner, so hospitals must start preparing for MACRA today.

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Health Catalyst Introduces Machine Learning in Healthcare Is Now for Everyone

Despite its prevalence in many other industries (and its use by most Americans every single day), machine learning in healthcare is far behind. But not for long, because Health Catalyst® is bringing this life-saving technology to healthcare with™—a new machine learning technology initiative that helps healthcare organizations of any size use predictive analytics to transform healthcare. The clinical, operational, and financial opportunities gives health systems are limitless:

  • Prevent hospital acquired infections.
  • Predict chronic disease.
  • Reduce readmissions
  • Reduce hospital Length-of-Stay.
  • Predict propensity-to-pay.
  • Predict no-shows.™ (machine learning models built into every Health Catalyst application) together with™ (a collaborative, open source repository of standardized machine learning methodologies and production-quality code that makes it easy to deploy machine learning in any environment), represents a new era of powerful predictive analytics that will not only improve outcomes, but also save lives.

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Against the Odds: How this Small Community Hospital Used Six Strategies to Succeed in Value-Based Care

The constant thread weaving through every healthcare organizational strategy should be adherence to the Triple Aim. But with uncertainty generated by the changes at the federal level, healthcare organizations may be tempted to put their value-based care plans on hold. This article explains why that’s not necessary and lists six strategies for thriving under a fee-for-value model: 1.) Use Leadership and Team Structure to Support Improvement 2.) Drive Down Costs 3.) Reduce Unnecessary Waste 4.) Encourage the Learning Organization 5.) Prioritize Patient Education 6.) Track Data and Outcomes This blog cites one small medical center with odds stacked against it, and how it is managing to not only weather the changes, but also distinguish itself by staying true to the values of the Triple Aim.

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The 3 Must-Have Qualities of a Care Management System

Care management systems are defined in many ways, but the only effective system comprises three qualities:

1.) It’s comprehensive and includes a suite of tools to address all five core competencies of care management. 2.) It’s inclusive of all EMRs and other data sources to enable thorough communication and analysis. 3.) It’s analytics-driven design facilitates clinical decision making and workflow.

Ultimately, an effective system improves outcomes and becomes an indispensable tool for managing population health. This article describes what drives successful care management, and reveals a suite of applications that aid care team members and patients through advanced algorithms and embedded analytics. Learn how technology is helping to develop appropriate interventions and improve clinical and financial outcomes.

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Reducing Unwanted Variation in Healthcare Clears the Way for Outcomes Improvement

According to statistician W. Edwards Deming, “Uncontrolled variation is the enemy of quality.” The statement is particularly true of outcomes improvement in healthcare, where variation threatens quality across processes and outcomes. To improve outcomes, health systems must recognize where and how inconsistency impacts their outcomes and reduce unwanted variation. There are three key steps to reducing unwanted variation:

  1. Remove obstacles to success on a communitywide level.
  2. Maintain open lines of communication and share lessons learned.
  3. Decrease the magnitude of variation.

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Why Clinicians Are the Missing Link in Healthcare Quality Improvement and Three Principles to Solve the Problem

When it comes to successful quality improvement (QI) in healthcare, clinicians tend to be the missing link. Fortunately, the disconnect between QI initiatives and the day-to-day work of clinicians can be explained and resolved if health systems adopt and embrace three clinician-focused principles:

  • Principle #1: QI starts at the front line (initiatives should be identified and driven by clinicians).
  • Principle #2: QI makes it easy for clinicians to do the right thing (removes barriers to good work rather than increasing the amount of work clinicians do).
  • Principle #3: QI empowers clinicians to adapt care (even if it’s not QI protocol).
Although some clinicians are enthusiastic advocates of their systems’ QI efforts, most are suspicious because they’re frequently cut out of the decision-making process or forced to ignore their best clinical judgement. Health systems that work to close the gap between leaders and clinicians by embracing these three principles will add the missing link—clinicians—back into successful healthcare QI.

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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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