HCLS/ The Cloud, Data, And AI Imperative For Healthcare
Healthcare has embraced hybrid cloud operating models. Driven by increased IT demands and the need for improved security, hospitals have adopted a hybrid mix of public and private cloud services. Healthcare organizations use cloud-native vendors for an increasing number of client-facing apps, while back-office technologies less sensitive to latency issues are more often hosted on public clouds than on-premises.
Healthcare organizations overestimate their effectiveness at data security. While 85% of healthcare decision makers rated their organizations as effective at securing patient data, the frequency and severity of industry data breaches suggest overconfidence. Cybercriminals are conducting ransomware attacks that are increasing in sophistication and volume, risking patient saftey and core hospital operations.
Large health systems struggle with data management. Data management is a limiting factor to deploying more advanced analytics and AI/machine learning (ML) capabilities. Both technical expertise and access to appropriate data rank as top challenges and barriers in AI implementation. Without appropriate data access — or clinically reliable, clean data — integrating insights into existing clinical workflows remains elusive.
Cloud and AI technology usage benefits patients and providers. More than one-third of existing cloud users have improved patient care, and three-quarters of AI users have improved both patient care and patient experience. Technology adoption is also correlated with Hospital Consumer Assessment of Healthcare, Providers, and Systems (HCAHPS) scores. Hospitals with higher HCAHPS scores are 1.6 times more likely to value availability of comprehensive, endto-end solution-to-support hosting, analytics, AI, and application development/insight delivery as a critical vendor capability. Highscoring organizations are also twice as likely to be very effective at abstracting insights from data.