This week, the CDC issued interim guidelines for antibody testing in clinical and public health settings, which will be used for monitoring and responding to the COVID-19 pandemic. But, antibody tests may be raising more questions than they're answering. In this week's news roundup: why the CDC says "less than half" of antibody tests may be correct; why immunity to COVID-19 is so complicated; maps and dashboards show new coronavirus hotspots and reopening dates; and more.
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Able Health combines all claims and clinical data from a health system’s data sources (inside and outside of the hospital) into one location, allowing healthcare leaders to focus more on improving care and less on data management. The combination of a measures engine that calculates performance, a performance dashboard that displays measure performance, and a submission engine that submits data to payers, all powered by the Health Catalyst® Data Operating System (DOS™), enables health systems to identify areas for improvement based on one complete picture of quality performance.
As Health Catalyst continues to engage its health system partners in their COVID-19 journeys through virtual client huddles, topics are delving further into restarting ambulatory care and elective procedures. The May 21, 2020, forum explored how organizations are responding to the pandemic and planning for the next phases. Participants explored two vital topics in the COVID-19 era:
- How virtual care analytics supports rapid change in ambulatory care delivery.
- How analytic insights help drive a COVID-19 financial recovery plan.
As states across the country ease stay-at-home orders, healthcare organizations look to restart elective procedures and develop financial recovery strategies. In this week's news roundup: hospitals begin the road to recovery; understanding the implications of the stimulus relief package; how one health system used advanced analytics in their financial recovery plan; and more.
More than 100 attendees joined the first of a series of Health Catalyst virtual client huddles designed to support client partners and aid collaboration and direct client connections in this time of unprecedented change. According to an April 2020 survey of Health Catalyst clients, 72.6 percent said they had a strong interest in examples, guidance, and tools from other health systems. In the client-only session, insights shared included the most common COVID-19 analytic projects and one health system’s elective surgery plan. The health system shared the challenges they faced in understanding the financial impact of halting elective surgeries as well as creating a plan for working through their backlog. They also shared the tools and strategies they are using to aid their financial recovery.
As the COVID-19 pandemic continues to threaten millions of lives around the world, new realities are significantly impacting every aspect of healthcare, from how care is delivered to how we work and communicate. In this week's news roundup: using remote patient monitoring to drive pandemic communication; how virtual care analytics supports rapid change in ambulatory care delivery; remote healthcare work best practices; and more.
Effective, sustainable healthcare transformation rests in the organizational operations that power care delivery. Operations include the administrative, financial, legal, and clinical activities that keep health systems running and caring for patients. With operations so critical to care delivery, forward-thinking organizations continuously strive to improve their operational outcomes. Health systems can follow thought leadership that addresses common industry challenges—including waste reduction, obstacles in process change, limited hospital capacity, and complex project management—to inform their operational improvement strategies. Five top insights address the following aspects of healthcare operational outcomes improvement:
- Quality improvement as a foundational business strategy.
- Using improvement science for true change.
- Increasing hospital capacity without construction.
- Leveraging project management techniques.
- Features of highly effective improvement projects.
As the country moves toward the next phase of its COVID-19 response, leaders will need to leverage data analytics to stay ahead of the virus and safely reopen. In this week's news roundup: how big data analytics will factor into the next phase of COVID-19; restarting elective surgery in the COVID-19 era; how one health system used analytics to understand the financial impacts of COVID-19 and aid their elective surgery restart; and more.
The focus on analytics is contributing to the “EHR problem”—doctors prioritizing the EHR over patients. The Healthcare Analytics Adoption Model (HAAM) walks healthcare organizations through nine levels that lay the framework to fully leverage analytic capabilities to improve patient outcomes: Level 1. Enterprise Data Operating System Level 2. Standardized Vocabulary & Patient Registries Level 3. Automated Internal Reporting Level 4. Automated External Reporting Level 5. Waste and Care Variability Reduction Level 6. Population Health Management & Suggestive Analytics Level 7. Clinical Risk Intervention & Predictive Analytics Level 8. Personalized Medicine & Prescriptive Analytics Level 9. Direct-To-Patient Analytics & Artificial Intelligence Analytics are crucial to becoming a data-driven organization, but providers and administrators can’t forget about the why behind the data—to improve outcomes. Following the HAAM enables organizations to build a sustainable, analytic platform and empower patients to become data-driven when it comes to their own care.
As value-based care (VBC) definitions and goals continue to shift, organizations struggle to create a roadmap for population health management (PHM) and to track associated costs and revenue. However, health systems can move forward with PHM amid the uncertainty by following the best practices of a path to value:
- Begin with Medicare Advantage—a good growth opportunity with low barriers to entry.
- Focus on ambulatory, not acute, care as it delivers more value.
- Leverage registries based on utilization to identify the most impactable 3 to 10 percent of utilizers.
- Simplify the physician burden by focusing on reasonable measures.
Improving healthcare interoperability is a top priority for health systems today. Fundamental problems around improving interoperability include standardization of terminology and normalization of data to those standards. And, the volume of data healthcare IT systems produce exacerbates these problems. While interoperability regulations focus on trying to make it easy to find and exchange patient data across multiple organizations and HIEs, the legislation’s lack of fine print and aggressive implementation timelines nearly ensures the proliferation of existing interoperability problems. This article discusses the biggest barriers to interoperability, possible solutions to interoperability problems, and why it matters.
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:
- Analyze the opportunity for improvement and define the problem.
- Scope the opportunity and set SMART goals.
- Explore root causes and set SMART process aims.
- Design interventions and plan initial implementation.
- Implement interventions and measure results.
- Monitor, adjust, and continually learn.
- Diffuse and sustain.
- Communicate Quantitative and Qualitative Results.
With no known end to the COVID-19 social distancing directives, many healthcare organizations are shifting some team members to remote work arrangements. Clinicians offering telehealth services, case managers, as well as administrative, financial, and IT teams and others contributing away from the frontlines of care are candidates to work from home while continuing to support their organization’s operations. Though a shift in normal processes, research has shown that remote workers can be as or more productive as they are in the office setting and often report high levels of job satisfaction. Following best practices for remote-first work will help team members, managers, and organizations transition to and thrive in a distributed setting.
The year 2020 marks a decade since the passage of the Affordable Care Act in 2010 and healthcare’s first transitional steps from volume to value. The 10-year progress report is mixed. On one hand, CMS’s emphasis on quality and cost is driving an upward trend for patients and providers, with substantial improvement in readmissions; on the other hand, organizations still need to simplify and consolidate value-based programs for more widespread positive impact. As the industry enters into another decade of value, it’s time for health systems to consider the impacts of these programs so far and make sure they have the processes and tools in place to succeed in an increasingly value-driven industry.
Social distancing, effective hand-washing techniques, sneezing into elbows, and the like are critical means of mitigating the spread and impact of COVID-19, but the pandemic has also prompted another area of concern: cybersecurity. A growing remote workforce, more collective time online, and increasingly frequent social engineering attacks that take advantage of public curiosity about and fear of the novel coronavirus are exposing system and network vulnerabilities. Remote workers can increase their online safety by refreshing and ramping up cyber-hygiene best practices, including learning to recognize and report suspicious emails and protecting home internet connections.
Compared to industries such as aerospace and automotive, healthcare lags behind in decision support innovation. Following the aerospace and automotive arenas, healthcare can learn critical lessons about improving its clinical decision support capabilities to help clinicians make more efficient, data-informed decisions:
- Achieve widespread digitization: Healthcare must digitize its assets and operations (patient registration, scheduling, encounters, diagnosis, orders, billings, and claims) for effective CDS similarly to how aerospace digitized the aircraft, air traffic control, baggage handling, ticketing, maintenance, and manufacturing.
- Build data volume and scope: Healthcare must collect socioeconomic, genomic, patient-reported outcomes, claims data, and more to truly understand the patient at the center of the human health data ecosystem.