SOLUTION PROVIDER Q&A
Overcoming AI Adoption Hurdles in Healthcare
What have been the biggest learnings around data analytics and artificial intelligence (AI) for you and your clients during the
pandemic? The COVID-19 pandemic has really high- lighted the need for data integration from a health system perspective. As healthcare data continues to grow exponentially, it’s an ongoing challenge to integrate pertinent data and develop meaningful insights to provide better patient care while improving operational efficiencies. Data analytics and AI can drive more value from these mas- sive amounts of data, which can support healthcare providers, for example, to track and respond to trends in utilization, bed needs, COVID patient management and much more. Another area where COVID-19 acceler-
ated trends is in managing care for patients outside of the hospital. The industry has seen a surge in the use of telehealth and remote patient monitoring out of necessity. Throughout the crisis, providers advanced the use of virtual care and patients readily accepted it. To optimize experiences and deliver the best care possible, providers need to align their technology solutions with this growing mode of care delivery. As the fund- ing models adapt to that trend, I think it is likely we will see more use of telehealth after the pandemic than we saw before it.
Has COVID-19 changed the perception around how important data scientists and analytics are?
If so, in which ways? In my opinion, data scientists and analyt- ics are fundamental to healthcare organi- zations’ abilities to derive value from their data, and the significance of these resources has only become clearer during this period of disruption. Health systems must develop a core infrastructure that enables collabora- tion among the care team and key stake- holders, while providing security to safely manage and share data. These capabilities will enable organiza-
tions to identify risk, ensure data integrity and transparency, analyze trends against benchmarks, and deliver meaningful predic- tive modeling. Data scientists and analytics are extremely important to the overall health
of these organizations and their ability to manage clinical, operational and financial performance.
What are the most productive use cases for AI in healthcare today? Where have there been recent
promising breakthroughs? A strong use case for AI in hospitals, physi- cian group and health systems is for imag- ing. For example, imaging solutions can review retrospective data in the EHR to help providers make accurate, timely and coordi- nated care decisions or combine image and text analytics capabilities to analyze medi- cal imaging studies to providers identify potential missed findings. Another use case for AI is around disease
management and progression. We are start- ing to see the industry develop intelligent care pathways that support identifying patients at risk for developing and progress- ing through chronic conditions. AI can help healthcare providers ingest evidence and data to determine the best interventions for patients during their care progression.
What do you see as some of the biggest challenges facing patient care organization leaders in these areas in the next few
years? I think there are three significant challenges for many healthcare organizations. The first is cost. Healthcare organizations must con- tinue to identify and improve efficiencies to manage their costs. As the pandemic placed further demands and reduced revenue, lead- ers must continue to find ways to improve their bottom line to sustain and support their communities. Second, hospitals and health systems are
facing new challenges in data security, as healthcare data is increasingly vulnerable. Just recently IBM created a threat intelli- gence task force to track down COVID-19 cyber threats against organizations that are impacting the vaccine supply chain. As part of these efforts, this team uncovered a global phishing campaign targeting organizations associated with a COVID-19 cold chain. Third, interoperability also remains a
challenge for healthcare organizations. Fragmented data makes it difficult for
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providers to deliver a truly patient-centered experience. While regulations and commit- ment from stakeholders have helped the industry make progress towards a more interoperable system, there is still more to achieve in this area.
Looking ahead, what are some areas where you believe AI can be especially valuable for the
future of healthcare? I believe that AI will be essential in health- care’s digital transformation – including financial, operational and clinical experi- ences across the continuum. In the future AI in medicine can derive more value from vast amounts of data by enabling provid- ers to provide more personalized treatment options for each patient, facilitating more efficiencies in supply chain, and optimizing resource/staffing plans.
Ekta Punwani, Leader 100 Top Hospitals Program
IBM Watson Health
Sara Atwell, Associate Partner Provider Consulting
IBM Watson Health
Betsy Block, Senior Consulting Leader IBM Watson Health
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