Improving the future of global healthcare requires a shift towards a real-time, digital learning healthcare ecosystem—a goal that data-driven action will help achieve. Elia Stupka, Health Catalyst senior vice president and general manager, life sciences business, shared his insights with HealthManagement.org on the structure of this ecosystem and its power to improve individual patient health around the world. According to Stupka, “If we can all shift towards the massively transformational purpose of a real-time, connected, digital learning healthcare ecosystem, our children and grandchildren will hopefully see a world where most diseases will be prevented, diagnosed and treated for all citizens and hospital stays will be a thing of the past for most patients.”
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In this new, data-rich healthcare environment, clinicians have greater abilities than ever to provide tailored treatments for specific patients's needs. However, personalized healthcare is easier said than done. In this week's news roundup: how real-world data can help advance clinical trials; the power of analytics and AI in the new era of personalized medicine; four trends to make precision medicine possible; and more.
Healthcare is looking towards an era of personalized medicine in which providers customize treatments for the individual patient. Realizing this tailored level of care s a new level of data volume and analytics and AI capabilities that, while novel to healthcare, other industries are thriving in. Choosing the right role models as healthcare works towards the analytics- and AI-driven territory of personalized medicine will guide informed strategies and establish best practices. With experience and expertise in these key areas, the military, aerospace, and automotive industries can serve as healthcare’s best examples:
- The human cognitive processes of complex decision making.
- The digitization of their industries, with the “health” of their assets as key drivers.
- Operating in a “big data” ecosystem.
The healthcare industry is under scrutiny for its treatment of different groups including residents, women in leadership (or lack thereof), and the LGBTQ+ community. In this week's news roundup: how health systems can leverage data to improve care delivery to the LGBTQ+ community; female residents report higher rates of discrimination leading to higher rates of burnout; how to improve the skewed ratio of entry level female employees to the number of women at the top in the healthcare industry; and a new alliance in the Northwest focuses on achieving health equity in seven states over the next two years.
LGBTQ+ community members face unique challenges when accessing healthcare. Lack of knowledge among providers about the LGBTQ+ community leads to stigma, discrimination, and stereotypes that result in higher risk for cancers and substance abuse and higher rates of smoking. Poor health outcomes occur for multiple reasons—clinicians don’t know the best way to collect accurate health information and LGBTQ+ members don’t feel safe sharing personal health information. The best way for health systems to improve healthcare delivery for the LGBTQ+ community is to rework the way they collect sexual orientation/gender identity data and educate clinicians about the health disparities LGBTQ+ members face.
Healthcare organizations increasingly rely on technology to help improve efficiency, reduce costs, and advance surgical outcomes. In this week's news roundup: prehabilitation and the power of healthcare analytics; four things patients can do to make surgery go more smoothly; big data and healthcare decision making; and how prehabilitation can lower episode costs under bundled payment models.
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:
- Medical optimization of pre-existing medical conditions.
- Physical fitness.
- Nutritional status.
- Psychological support.
Optimizing the patient experience and improving patient outcomes are two top priorities for many healthcare organizations in 2019. In this week's news roundup: the top five recommendations for improving the patient experience; how technology is improving patient experiences; data-driven patient engagement solutions for payers; and more.
Improving patient satisfaction scores and the overall patient experience of care is a top priority for health systems. It’s a key quality domain in the CMS Hospital Value-Based Purchasing (VBP) Program (25 percent) and it’s an integral part of the IHI Triple Aim. But, despite the fact that health systems realize the importance of improving the patient experience of care, they often use patient satisfaction as a driver for outcomes. This article challenges this notion, instead recommending that they use patient satisfaction as a balance measure; one of five key recommendations for improving the patient experience:
- Use patient satisfaction as a balance measure—not a driver for outcomes.
- Evaluate entire care teams—not individual providers.
- Use healthcare analytics to understand and act on data.
- Leverage innovative technology.
- Improve employee engagement.
Health systems are facing increasing pressure to deliver cost savings. To build sustainability, healthcare organizations must identify waste and reduce the total cost of care. In this week's news roundup: why activity-based costing is healthcare's secret to doing more with less; why more hospitals are calculating actual cost of care; and more.
Delivering high-quality, cost-efficient care to specific patient populations within a service line is nearly impossible without a sophisticated costing methodology. Activity-based costing (ABC) provides a nuanced, comprehensive view of cost throughout a patient’s journey and reveals the “true cost” of care—the real cost for each product and service based on its actual consumption—which traditional costing systems don’t provide. With the true cost of care at their fingertips, healthcare leaders can identify at-risk populations earlier—such as pregnant women diagnosed with gestational diabetes mellitus—and more quickly implement effective interventions (e.g., more scrupulous monitoring and earlier screenings). Health systems that leverage the actionable insight from ABC further benefit by implementing the same, or similar, process/clinical improvement measures across other service lines.
Healthcare organizations face provider dissatisfaction, lack of data integration, and excessive clicks to perform basic functions within the EHR. Closed-Loop Analytics™ aggregates data, circulates that data into new or existing workflows, and then surfaces best practice alerts at the decision point for physicians, clinical providers, and financial and operational teams. With clear calls to action throughout the workflow, organizations improve the utilization and effectiveness of analytics tools, yielding simplified workflows, decreased clicks, and improved outcomes.
The 2019 Healthcare Analytics Summit™ (HAS) was packed full of insightful discussions about data democratization, delivering healthcare in a digital age, and the future of analytics and AI. The 2019 HAS infographic reveals 1,600 industry leaders attended, with 60 percent of attendees from the IT/analyst industry, discussing trending data topics, interacting with presenters through polling mechanisms, and utilizing networking opportunities to share solutions and problem-solving methods.
Healthcare data security is complex issue, and the industry has been slow in determining how to handle new technology. In this week's news roundup: improving healthcare data security with AI; advertising, Amazon, and artificial intelligence; Google's controversial takeover of DeepMind Health; and, confusing laws and bad actors just some of the challenges facing healthcare data safety and patient privacy.
How Artificial Intelligence Can Overcome Healthcare Data Security Challenges and Improve Patient Trust
As healthcare organizations today face more security threats than ever, artificial intelligence (AI) combined with human judgment is emerging as the perfect pair to improve healthcare data security. Together, they power a highly accurate privacy analytics model that allows organizations to review access points to patient data and detect when a system’s EHR is potentially exposed to a privacy violation, attack, or breach. With specific techniques, including supervised and unsupervised machine learning and transparent AI methods, health systems can advance toward more predictive, analytics-based, collaborative privacy analytics infrastructures that safeguard patient privacy.
HAS attendees are accustomed to innovation and projections for the future of digital health. But on the final day of HAS 19, they met the next generation of transformation in person: teenager Justin Aronson presented a keynote on how data democratization will empower him and his peers to solve the challenges of coming decades. Other keynotes—Google’s Marianne Slight, former Bayer CDO Jessica Federer, and Beth Israel Deaconess System CIO Dr. John Halamka—contributed their visions for healthcare’s next era, and presenters in 20 breakout sessions shared the experiences, processes, and technologies that will carry digital transformation forward.