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Using Improvement Science in Healthcare to Create True Change

With improvement science combined with analytics, health systems can better understand how, as they implement new process changes, to use theory to guide their practice, and which improvement strategy will help increase the likelihood of success. The 8-Step Improvement Model is a framework that health systems can follow to effectively apply improvement science:

  1. Analyze the opportunity for improvement and define the problem.
  2. Scope the opportunity and set SMART goals.
  3. Explore root causes and set SMART process aims.
  4. Design interventions and plan initial implementation.
  5. Implement interventions and measure results.
  6. Monitor, adjust, and continually learn.
  7. Diffuse and sustain.
  8. Communicate Quantitative and Qualitative Results.
With the right approach, an improvement team can measure the results and know if the changes they made will actually lead to the desired impact.

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How to Design an Effective Clinical Measurement System (And Avoid Common Pitfalls)

As healthcare organizations strive to provide better care for patients, they must have an effective clinical measurement system to monitor their progress. First, there are only two potential aims when designing a clinical measurement system: measurement for selection or measurement for improvement. Understanding the difference between these two aims, as well as the connection between clinical measurement and improvement, is crucial to designing an effective system. This article walks through the distinct difference between these two aims as well as how to avoid the common pitfalls that come with clinical measurement. It also discusses how to identify and track the right data elements using a seven-step process.

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Three Must-Haves for a Successful Healthcare Data Strategy

Healthcare is confronting rising costs, aging and growing populations, an increasing focus on population health, alternative payment models, and other challenges as the industry shifts from volume to value. These obstacles drive a growing need for more digitization, accompanied by a data-centric improvement strategy. To establish and maintain data as a primary strategy that guides clinical, financial, and operational transformation, organizations must have three systems in place:

  1. Best practices to identify target behaviors and practices.
  2. Analytics to accelerate improvement and identify gaps between best practices and analytic results.
  3. Adoption processes to outline the path to transformation.
 

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Using Improvement Science in Healthcare to Create True Change

With improvement science combined with analytics, health systems can better understand how, as they implement new process changes, to use theory to guide their practice, and which improvement strategy will help increase the likelihood of success. The 8-Step Improvement Model is a framework that health systems can follow to effectively apply improvement science:

  1. Analyze the opportunity for improvement and define the problem.
  2. Scope the opportunity and set SMART goals.
  3. Explore root causes and set SMART process aims.
  4. Design interventions and plan initial implementation.
  5. Implement interventions and measure results.
  6. Monitor, adjust, and continually learn.
  7. Diffuse and sustain.
  8. Communicate Quantitative and Qualitative Results.
With the right approach, an improvement team can measure the results and know if the changes they made will actually lead to the desired impact.

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Improving Strategic Engagement for Healthcare CIOs with Five Key Questions

A healthcare CIO’s role can demand such an intense focus on technology that IT leaders may struggle to find natural opportunities to engage with their C-suite peers in non-technical conversations. To bridge the gap, healthcare CIOs can answer five fundamental questions to better align their programs with organizational strategic goals and guide IT services to their full potential:

  1. Whom do we serve?
  2. What services do we provide?
  3. How do we know we are doing a great job?
  4. How do we provide the services?
  5. How do we organize?

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Survey Points to Major Burnout Concerns Among Clinicians

According to a November 2019 survey, 62 percent of clinicians and other healthcare professionals view burnout as a major problem industrywide. When asked for the best way to address clinician burnout problems, the most popular solution was less-complex workflows, which is the aim of emerging point-of-care analytics solutions. Responses to additional questions reveal more about clinician burnout experience and views on the technology designed to help:

  1. At your organization, how big of a problem is clinician burnout?
  2. What is the best way to solve clinician burnout problems?
  3. What are the biggest barriers to adopting closed-loop, point-of-care analytics capabilities at your organization
  4. What are the biggest problems arising from a lack of adopting closed-loop, point-of-care analytics capabilities?

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Healthcare Quality Improvement: A Foundational Business Strategy

Waste is a $3 trillion problem in the U.S. Fortunately, quality improvement theory (per W. Edwards Deming) intrinsically links high-quality care with financial performance and waste reduction. According to Deming, better outcomes eliminate waste, thereby reducing costs. To improve quality and process and ultimately financial performance, an industry must first determine where it falls short of its theoretic potential. Healthcare fails in five critical areas:

  1. Massive variation in clinical practices.
  2. High rates of inappropriate care.
  3. Unacceptable rates of preventable care-associated patient injury and death.
  4. A striking inability to “do what we know works.”
  5. Huge amounts of waste.

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Machine Learning Tools Unlock the Most Critical Insights from Unstructured Health Data

Patient comments such as “I feel dizzy” or “my stomach hurts” can tell clinicians a lot about an individual’s health, as can additional background, including zip code, employment status, access to transportation, and more. This critical information, however, is captured as free text, or unstructured data, making it impossible for traditional analytics to leverage. Machine learning tools (e.g., NLP and text mining) help health systems better understand the patient and their circumstances by unlocking valuable insights residing unstructured data:

  1. NLP analyzes large amounts of natural language data for human users.
  2. Text mining derives value through the analysis of mass amounts of text (e.g., word frequency, length of words, etc.).

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When the Promise of Prehabilitation Meets the Power of Healthcare Analytics

Patients who undergo surgery frequently follow a rehabilitation program afterwards to promote recovery. However, starting this program before the procedure may help further accelerate recovery time. Prehabilitation is defined as physical or lifestyle preparation that happens before surgery and is designed to help patients regain function in less time. Prehabilitation includes the following four main components:

  1. Medical optimization of pre-existing medical conditions.
  2. Physical fitness.
  3. Nutritional status.
  4. Psychological support.
Providing coordinated care from the pre-surgery period to post-operative recovery helps ensure the best patient outcomes. Additionally, health systems can glean important insights about best practices when they effectively follow the patient journey and capture relevant data throughout.

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How Healthcare Cost-Per-Case Improvements Deliver Big Bottom-Line Savings

As health systems face more pressure than ever to deliver cost savings, they’re turning their attention to cost-per-case improvement projects. These strategies can produce quick wins for improvement teams looking to gain momentum and buy-in. This article addresses the following topics:

  1. How to identify areas of opportunity.
  2. The importance of costing accuracy.
  3. Four strategies for implementing cost-per-case improvement projects.
  4. Example projects for new teams.
  5. How to sustain results.

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Continuity of Care Documents: Today’s Top Solution for Healthcare Interoperability Demands

While healthcare waits for the expanded data interoperability that FHIR promises, the industry needs an immediate solution for accessing and using disparate data from across the continuum of care. With FHIR potentially several years away, continuity of care documents (CCDs) are the best option for acquiring the ambulatory clinical care data health systems need to close quality gaps today. Because organizations that rely only on claims data to drive quality improvement risk missing out on more that 80 percent of patient information, CCDs are the current must-have answer to interoperability for successful quality improvement.

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The Top Six Examples of Quality Improvement in Healthcare

In order to thrive in an increasingly challenging healthcare environment, undertaking quality improvement projects is more important than ever for healthcare systems’ continued survival. However, health systems need to tackle the right projects at the right time to maximize the impact to their organization. This article shares both clinical and financial and operational examples of quality improvement in healthcare that may help others as they tackle improvement projects. Some examples shared include:

  • Pharmacist-led Medication Therapy Management (MTM) reduces total cost of care.
  • Optimizing sepsis care improves early recognition and outcomes.
  • Boosting readiness and change competencies successfully reduces clinical variation.
  • New generation Activity-Based Costing (ABC) accelerates timeliness of decision support.
  • Systematic, data-driven approach lowers length of stay (LOS) and improves care coordination.
  • Clinical and financial partnership reduces denials and write-offs by more than $3 million.

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The Top Five 2019 Healthcare Trends

Bobbi Brown, MBA, and Stephen Grossbart, PhD have analyzed the biggest changes in the healthcare industry and 2018 and forecasted the trends to watch for in 2019. This report, based on their January 2019, covers the biggest 2019 healthcare trends, including the following:

  • The business of healthcare including new market entrants, business models and shifting strategies to stay competitive.
  • Increased consumer demand for more transparency
  • Continuous quality and cost control monitoring across populations.
  • CMS proposals to push ACOs into two-sided risk models.
  • Fewer process measures but more quality outcomes scrutiny for providers.

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Is a Medical Writer the Missing Accelerant to Your Outcome Improvement Efforts?

Quality improvement efforts are more important than ever. However, even improvement efforts that have the right people, processes, and technology can struggle to make progress.  A medical writer with healthcare knowledge and strong information design skills may be the missing ingredient that can help speed time to adoption and value. This article discusses the functions a medical writer can fulfill, and why they matter. You will also learn:

  • The four skills that a medical writer with strong information design skills brings to an improvement team.
  • Examples of output of medical writers in a healthcare setting.
  • The skills a medical writer needs.
Additionally, you will learn how to find this unique skill set and where you might find this key person.

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Unlocking the Power of Patient-Reported Outcome Measures (PROMs)

Health systems attempt to measure an ever-increasing amount of clinical measures, these often miss the mark of what matters to patients. Patient-Reported Outcomes (PROs) are the missing link in empowering patients and helping to define good outcomes.  This article walks through how patient-reported outcome measures (PROMs) can help identify best practices and drive system-wide quality improvement. PROMs can help health systems do the following:

  • Serve as a guide for appropriateness and efficiency.
  • Lead to better shared decision-making.
  • Demonstrate value and transparency
This article also discusses the effect of PROMs on providers in a culture of “one more thing,” and tips for effective implementation.

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ACOs: Four Ways Technology Contributes to Success

With an increasing emphasis on value-based care, Accountable Care Organizations (ACOs) are here to stay. In an ACO, healthcare providers and hospitals come together with the shared goals of reducing costs and increasing patient satisfaction by providing high-quality coordinated healthcare to Medicare patients. However, many ACOs lack direction and experience difficulty understanding how to use data to improve care. Implementing a robust data analytics system to automate the process of data gathering and analysis as well as aligning data with ACO quality reporting measures. The article walks through four keys to effectively implementing technology for ACO success:

  1. Build a data repository with an analytics platform.
  2. Bring data to the point of care.
  3. Analyze claims data, identify outliers, including successes and failures.
  4. Combine clinical claims, and quality data to identify opportunities for improvement.

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How to Run Your Healthcare Analytics Operation Like a Business

A robust data analytics operation is necessary for healthcare systems’ survival. Just like any business, the analytics enterprise needs to be well managed using the principles of successful business operations. This article walks through how to run an analytics operation like a business using the following five-question framework:

  1. Who does the analytics team serve and what are those customers trying to do?
  2. What services does the analytics team provide to help customers accomplish their goals?
  3. How does the analytics team know they’re doing a great job and how do they communicate that effectively to the leadership team?
  4. What is the most efficient way to provide analytics services?
  5. What is the most effective way to organize?

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