Clinical Workflow News Improving clinical workflows is always a hot topic, especially as pressure on clinicians continues to mount. This week’s roundup features healthcare workflow news, including ways to protect provider productivity, the importance of user feedback in software usability, how analytics, workflow, and physician education aids sepsis care at Allina Health, and how ACO measures performance improved with data and analytics. MedStar Launches EHR Usability Campaign, With Videos Showing UX, Workflow Challenges Effective software depends on user feedback, with developers rely on a culture of open communication …
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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:
- Build a data repository with an analytics platform.
- Bring data to the point of care.
- Analyze claims data, identify outliers, including successes and failures.
- Combine clinical claims, and quality data to identify opportunities for improvement.
Author Douglas Laney is now tackling the topic of Infonomics: the practice of information economics. In his 2017 book, Infonomics: How to Monetize, Manage, and Measure Information as an asset for competitive advantage, Laney provides detailed rationale as well as a thoughtful framework for treating information as a modern-day organization’s most valuable asset. This article walks through how healthcare organizations can leverage data to its full potential using this framework and the three principles of infonomics:
- Measure - How much data does the organization have? What is it worth?
- Manage - What data does the organization have? Where is it stored?
- Monetize - How does the organization use data?
Join the webinar to learn:
- Why a predictive or prescriptive model endeavor is more a change management challenge than a technical one
- How to apply three types of model understanding to a use case in your own organization
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:
- Who does the analytics team serve and what are those customers trying to do?
- What services does the analytics team provide to help customers accomplish their goals?
- How does the analytics team know they’re doing a great job and how do they communicate that effectively to the leadership team?
- What is the most efficient way to provide analytics services?
- What is the most effective way to organize?
Healthcare Tech Funding in the News Healthcare tech companies have been capturing the attention (and pocketbooks) of investors this week. Namely, Health Catalyst (ahem) reached unicorn status with a $1 billion latest valuation, Devoted Health–a start-up selling health insurance to seniors–raised $300 million at a $1.8 billion valuation, healthcare startup Lytic got a funding boost to help patients pinpoint their health condition and get the next steps for obtaining care, and Healthy.io raised $18 million to bring smartphone urinalysis technology to the U.S. Cloud Unicorn: Health Catalyst Reaches …
Opportunity analysis uses data to identify potential improvement initiatives and quantifies the value of these initiatives—both in terms of patient care benefits and financial impact. This process is an effective way to find unwarranted and costly clinical variation and, in turn, develop strategies to reduce it, improving outcomes and saving costs along the way. Standardizing the opportunity analysis process makes it repeatable and prioritizes actionable opportunities. Quarterly opportunity analysis should follow four steps:
- Kicking off the analysis by getting analysts together to do preliminary analysis and brainstorm.
- Engaging with clinicians to identify opportunities and, in the process, get clinician buy in.
- Digging deeper into the suggested opportunities to prioritize those that offer the greatest benefits.
- Presenting findings to the decision makers.
Nearly half of all Americans use at least one prescription drug, and with high prescription usage comes medication-related problems. More than 1.5 million preventable medication-related adverse events occur each year, costing more than $177 billion in medication-related morbidity and mortality. This week’s news roundup covers medication-related patient safety news including a case for better after-hours palliative care, a success story featuring a significant cost of care reduction at Allina Health, a day in the life of a medication safety officer, and the terrifying story of an Ohio physician who …
Many health systems have a hospital capacity problem as demand for patient beds rises. When the supply of usable patient beds can’t meet demand, the negative impact on patients and staff can be significant. Hospitals can solve capacity problems with four key concepts:
- Using data, start with the problem and the ideal solution.
- Be sure the analytics team works with teams throughout the organization—including leadership.
- Have leaders spend time with the operations team to understand workflow.
- Focus on the impact, not the tool.
Health systems feel mounting pressure to demonstrate ROI from analytics investments but are faced with inefficacies and delays. Fortunately, the Rapid Response Analytics Solution delivers a 10x increase in analytics productivity and a 90 percent decrease in the time required to develop new analytic insights. The Rapid Response Analytics Solution solves these tough analytics problems through two primary elements: curated, modular data kits called DOS Marts; and Population Builder, a powerful self-service tools that lets any time of user, from physician executive to frontline nurse, explore data and quality build cohorts of patients without relying on IT staff and with no need for sophisticated and customized SQL and data science coding.
Healthcare today is in the midst of a massive transformation. The opportunities for improvement are great if healthcare systems can do the following:
- Reduce clinical variation.
- Reduce rates of inappropriate care and care-associated patient injury and death.
- Follow accepted best care practices.
- Eliminate waste.
Addressing the Opioid Epidemic With Analytics With the opioid epidemic continuing to ravage the country, U.S. healthcare professionals are searching for answers. This week’s news roundup includes tools to help combat an epidemic, best practice opioid interventions, and recent news addressing the problem, such as how healthcare executives can use IT to stem the crisis, why it’s time to use machine learning to combat it, and a new study linking opioid deaths to painkiller marketing. How Top Healthcare Executives Can Use IT to Stem the Opioid Crisis …
Learn how Allina Health leveraged its analytics platform and Health Catalyst professional services to perform an analysis demonstrating the impact of pharmacist-led medication therapy management (MTM).
As healthcare systems are pressured to cut costs and still provide high-quality care, they will need to look across the care continuum for answers, reduce variation in care, and look to emerging technologies. This article walks through how to evaluate the safety and effectiveness and of emerging healthcare technology and prioritize high-impact improvement projects using a robust data analytics platform. Topics covered include:
- The importance of identifying variation in innovation.
- Ways to improve outcomes and decrease costs.
- The value of an analytics platform.
- The reliable information that produce sparks for innovation.
- Identifying and evaluating emerging healthcare technology.
- Knowing what data to use.
- The difference between efficacy and effectiveness in evaluation of emerging healthcare technology.
Health systems continue to prioritize reducing hospital readmissions as part of their value-based payment and population health strategies. But organizations that aren’t fully integrating analytics into their readmission reduction workflows struggle to meet improvement goals. By embedding predictive models across the continuum of care, versus isolated them in episodes of care, health systems can leverage analytics for meaningful improvement. Organizations that integrate predictive models into readmissions reduction workflows have achieved as much as a 40 percent reduction in risk-adjusted readmissions indexes. Effective analytics integration strategies use a multidisciplinary development approach to meet the needs of a patient’s entire care team and deliver common tools for all involved in the patient’s healthcare journey.
Healthcare Project Management in the News Project management is increasingly important to the healthcare industry because it can help control costs, manage risk, and speed improvement project outcomes. This week, we’re sharing news about healthcare project management, from the age-old debate of agile vs. waterfall methodologies to pragmatic approaches to project management in outcomes improvement projects. Healthcare Project Management Techniques: A Pragmatic Approach to Outcomes Improvement Healthcare leaders are working hard to continuously refine and advance their processes in order to improve patient care, reduce costs, …
In today’s high-pressured world of healthcare, health systems don’t need report writers. They need highly valuable healthcare data analysts. A top healthcare data analyst becomes a partner for clinical and operational improvement by using a five-step method for solving complex problems. This article walks through this step-by-step approach and demonstrates its application using the real-world example of building a diabetes registry. In addition to this specialized approach to solving problems, the article discusses the five essential skills for data analysts needed in the diabetes registry example:
- Data query
- Data movement
- Data modeling
- Data analysis
- Data visualization
Rapid Response Analytics (RRA) Solution, an application suite that consists of two elements: curated, modular data kits called DOS™ Marts and Population Builder, a powerful self-service tool that lets any type of user, from physician executive to frontline nurses and population health teams explore their data and quickly build populations without needing to know how to write SQL and data science code. RRA Solution increases an analytics team’s productivity by up to 10x and reduces its time to develop analytics by as much as 90 percent. Analysts can spend more time focusing on key strategic analysis and less time on repetitive tasks that can lead to inconsistent results and a backlog of requests. Learning Objectives:
- Discover how RRA Solution allows you to take components and customize them to quickly tailor and deliver meaningful insights.
- Learn about DOS™ Marts and Population Builder and how they drive consistency and efficiency, without needing to know SQL and data science coding.
- Understand how to use RRA Solution to increase the value of your analytics team and get them operating at the top of their function.
Overcrowding in the emergency department has been associated with increased inpatient mortality, increased length of stay, and increased costs for admitted patients. ED wait times and patients who leave without seeing a qualified medical provider are indicators of overcrowding. A data-driven system approach is needed to address these problems and redesign the delivery of emergency care. This article explores common problems in emergency care and insights into embarking on a successful quality improvement journey to transform care delivery in the ED, including an exploration of the following topics:
- A four-step approach to redesigning the delivery of emergency care.
- Understanding ED performance.
- Revising High-Impact Workflows.
- Revising Staffing Patterns.
- Setting Leadership Expectations.
- Improving the Patient Experience.