Will Ellaissi’s Post

👏 Great article by Brian Spisak, PhD and Todd Norwood! They address the need to improve data quality to find value from AI in healthcare and lay out ✨ 10 KPIs ✨ that healthcare organizations can pursue to take advantage of the AI Revolution. Great work here!

Had a great time talking to the great Varoon Mathur! We talked about how he got to be the Senior Advisor on ML Ops at the VA and the challenges to overcome to make data actionable in healthcare. #datacleaning #datacuration #healthcaredata #FullsteamHealth

Data extraction and data harmonization currently consume 43% of the total IT staff time in healthcare organizations. Cutting this by 75% could save $ millions each year. That's a lot of money. Our team is currently reducing the need for a ton of external data processing systems and approaches in favor of a singular tool that cleans, manages and delivers insights without adding a bunch of duplicative time and effort for your analysts. What initiatives would your organization be able to deliver if 43% of staff time was spent on being value creators and not data janitors? https://lnkd.in/eZF3Yixx

Just released the first episode of the Healthcare Data Room! Thanks to Mark Sendak, our inaugural guest, your contributions have set a high bar for the quality and depth of discussions we aim to continue in future episodes. In this episode, we talked to Mark about the current state of data science in healthcare and the work of the Duke Institute for Health Innovation and Health AI Partnership to drive effective AI within health systems. I tried to limit the cringe of the intro, you can be the judge 😂

A startling 38% of data analyst’s time is wasted on cleaning and organizing data before it can even be used (2022). This doesn't even include the amount of time required to maintain the quality of the data consistently. Or the time and resources to perform these tasks for EVERY data use initiative. What would your team do with 38% more time? Healthcare leaders, check out Fullsteam Health and help your data teams gain that 38% of their time back. #DataQuality #HealthcareInnovation #FullsteamHealth Source: https://lnkd.in/eS-QpJFt

Poor data quality costs businesses, including those in healthcare, up to $14.2 million annually. At Fullsteam Health, our platform aims to cut these losses by enhancing data reliability and usability through fully automating end to end data curation--from extraction to use. Healthcare leaders: any examples you are willing to share of the impact of costly data errors? What are your strategies for mitigating data quality challenges? Source: https://buff.ly/3BuBEoX

A fantastic article by Brian R. Spisak, PhD about a “tech comes last” approach to digital transformation. A couple of points that stood out to me: 1. “A “tech comes last” approach highlights the importance of prioritizing strategy, people, and processes. While technology plays a crucial role in digital transformation, it’s an enabler, not the sole focus” This is spot on and while it has been preached, this is why so many Chief Data and Analytics Officers talk about building machine learning models or AI that never gets adopted. Tech is valuable in creating efficiencies but if you don’t focus intently on the workflow for how you will use the tech to change decision-making, the tech is relegated to a poster presentation or an article but will have no bearing on changing outcomes. 2. “Healthcare leaders also need to define clear and actionable goals to alleviate systemic tensions.” The organizational strategy must be clear. Without a clear institutional strategy or “north star”, it is difficult to know where to innovate and if you try, leadership will create barriers to adoption because it “doesn’t align” without being clear on what alignment means. Organizational strategy and the tactics to achieve the strategy must be clear to everyone. 3. “By harnessing cross-functional talent—from front-line managers to organizational psychologists—and prioritizing strategy, people and processes, computational leaders pave the way for successful transformation.” Spot on. The key to solving problems is to deeply understand what is causing the problem. For instance, if someone says “readmissions is a problem”, they’ll never solve it. Readmissions is not a problem, the reasons why patients readmit is the problem and deeply understanding these reasons from front-line employees is critical to create the QI initiatives that will have the effect the organization desires. https://lnkd.in/ed2ZzDtk

95% of my virtual meetings are on Zoom or Teams...which makes me wonder When will the Harvard Business Review article be written about how Webex was given the biggest business gift in March 2020 and squandered it?

The World Economic Forum's latest report, "Transforming Healthcare: Navigating Digital Health with a Value-Driven Approach" identifies the challenges facing our health systems but also underscores the critical role of data and AI in creating a path toward sustainable, value-driven healthcare solutions. The report offers some high-level thoughts on the role of data in healthcare: - Data as a Keystone for Healthcare Transformation: emphasizing the pivotal role of data and AI in addressing our most pressing challenges (resource constraints, burden of chronic diseases, inequitable outcomes and access) - Breaking Down Data Silos: highlighting seamless data flow and interoperability but also underscoring the strain of siloed and unstructured data (while I would say we have an even bigger problem with the quality of the data that is structured that renders it inadequate to make data-driven decisions) At Fullsteam Health, we tackle the part that has hampered data use in healthcare -- data curation. By automating historical and real-time data extraction, cleaning, normalization, and concept grouping, we enable health systems to transform raw, inconsistent data into high-quality, actionable insights. This not only enhances clinical and operational performance but also facilitates the seamless (and faster) integration of AI/ML and advanced analytics, propelling health systems into a future where they now make data-driven decisions from reliable, consistent, and curated data instead of trying to make these critical data-driven decisions from the poor-quality data they ingest and maintain. The WEF report is a reminder that the journey toward digital transformation in healthcare is not a solitary endeavor, it requires partnerships with companies that have validated technologies that remove barrier to making high-quality decisions quickly. #DigitalHealth #HealthcareInnovation #DataCuration #AIinHealthcare #WEF #FullsteamHealth You can read the report here: https://lnkd.in/dPtGaXAm