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5 Digital Health Executives Share Their Key Takeaways from HIMSS23

John Erwin, CEO of Carenet Health I was pleased with the robust turnout at HIMSS this year; it does seem like the healthcare industry is making up…

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This article was originally published by HIT Consultant

John ErwinCEO of Carenet Health

I was pleased with the robust turnout at HIMSS this year; it does seem like the healthcare industry is making up for the lost time from the pandemic. The topics that dominated the conference included teasing out the nuanced approach to safely deploying Chat GPT/AI into the industry (and when not to), health equity, and the patient journey. Workforce burnout continues to be a major issue in healthcare, though I think we could have spent even more time discussing solutions here, given its profound impact on every aspect and stakeholder of the care continuum. While this is not a new phenomenon, it is certainly the biggest challenge to the industry currently. Current policies will have to evolve to ensure job stability and staffing for healthcare, which is where the innovative use of AI and technology can bridge the gaps. 

Adam Mariano, President & General Manager of Healthcare, LexisNexis Risk Solutions:

The big opportunity at HIMSS this year is that everyone is finally talking about social determinants of health, bias in care and health disparities in a way that is not just theoretical but is actually ‘let’s take action’. I’m really pleased to see lots of our partners, competitors,  providers, payers, life science folks really engaged and willing to participate in these types of conversations this year.

Kimberly O’Loughlin, CEO of HRS

HIMSS is always an energizing event. It’s a wonderful venue to connect with customers, be inspired by what others are doing, and share stories and ideas for innovation. It was especially meaningful to have our customers present the wonderful results they are achieving by leveraging our remote patient monitoring and care platform. 

Solutions providers who can provide turn-key capabilities and wrap-around services and be true partners with clients are what is needed. The only way we are going to enable real performance improvements and address critical issues like clinician shortages and burnout is if we simplify and streamline workflows for clinicians. Artificial intelligence/machine learning and the power of what it can do was another key topic of discussion at HIMSS. We are excited about what it can bring to remote care delivery to drive patient engagement, improved outcomes, and clinical workflow efficiencies to even higher levels.

8 Executive Key Takeaways from JP Morgan Healthcare Conference

BJ Schaknowski, CEO at symplr

The potential to save on streamlined architecture was a significant theme at HIMSS this year. Many agreed that hospitals are only taking advantage of a small percentage of the multi-million-dollar systems available to them. And as financial pressures increase, healthcare leaders are implementing more deliberate decision-making to better leverage vendor partnerships and optimize software purchases. Spending is focused on enterprise-wide solutions as opposed to best-in-breed and price sensitivity is a major factor in software purchasing. 

Nicole Rogas, President at symplr

Health equity was a cornerstone of conversation this year at HIMSS, and rightfully so. Together, as healthcare vendors and providers, we need to come together to provide a solution. Every person should have access to care, regardless of race, ethnicity, age, socio-economic status, etc. Organizations emphasized the potential for digital health to bridge the health equity gap by increasing access for patients and eliminating barriers to care. In support of health equity initiatives, interoperability remains top of mind for industry leaders. When health equity is a key objective in data strategies amongst providers and vendors we can develop and deliver solutions that pave the way toward more equitable care, improving health outcomes, and reducing health disparities.   

digital health
artificial intelligence

machine learning
remote patient monitoring

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