Survey: For Many Health System Execs, Enabling AI-Based Reporting a Major Factor in Shift to the Cloud

For three-quarters of senior patient care organization leaders in the U.S., enabling artificial intelligence is a “primary” or “prominent” factor in their development of their cloud deployment strategies. That’s one of the major findings of a survey whose results have just been published by the Chicago-based Healthcare Information & Systems Society (HIMSS), and conducted on behalf of the New York City-based Logicalis solutions provider company, in conjunction with the Sunnyvale, Calif.-based Net App. The Executive Brief on the survey, “Cloud Adoption Advancing Artificial Intelligence Initiatives in Healthcare,” can be found here. Meanwhile, the level of adoption of artificial intelligence varies dramatically across different areas of endeavor in patient care organizations, with the highest levels in IT security/cybersecurity and clinical decision support (39 percent), and the lowest, in employee engagement (15 percent). That said, clear majorities of respondents said that they were planning to put AI into production in a wide range of areas within the next 12 months, across not only cybersecurity and clinical decision support, but also applied to workflow improvement, finance/reimbursement, medication management, image processing, diagnosis support, COVID-19-related projections, population health management, and patient engagement.

HIMSS conducted the research in July 2020 on behalf of Logicalis, eliciting over 100 qualified responses to the online survey. The research was conducted to provide thought leadership to help healthcare organizations accelerate their implementation of AI initiatives. Specifically, the survey was designed to elicit the current status of AI adoption, as well as its anticipated level of adoption within the next 12 months; the challenges that patient care leaders are facing in their adoption of AI; and the impact of the transition to the cloud on the ability to take advantage of AI capabilities. Survey respondents were contacted by HIMSS as an organization, not by Logicalis.

Asked “How does the potential for enabling AI, machine learning, or deep learning initiatives figure into your organization’s cloud deployment strategy?” 28 percent of respondents said that it is a “primary” factor; an additional 47 percent said it’s a “prominent” factor; 22 percent said it’s a contributing factor; and only 3 percent said it’s not a contributing factor.

In terms of areas of activity in which artificial intelligence has already actively been adopted, the results were: 39 percent in IT security/cybersecurity and clinical decision support; 32 percent in workflow improvements and in finance/reimbursement; 28 percent in medication management; 26 percent in image processing; 25 percent in diagnosis support; 23 percent in COVID-related projections; 22 percent in population health management; 20 percent in patient engagement; and 15 percent in employee engagement. Meanwhile, within the next 12 months, a far higher percentage of organizations will move forward with AI, as follows: 41 percent in image processing; 40 percent in population health management; 38 percent in diagnosis support; 37 percent in patient engagement; 35 percent in COVID-related projections; 35 percent in workflow improvements; 34 percent in medication management; 32 percent in clinical decision support; 30 percent in employee engagement; 28 percent in IT security/cybersecurity; and 26 percent in financial/reimbursement.

In terms of the benefits they expect to see from transitioning to cloud-based computing, respondents cited the following: lower overall costs, 66 percent; higher data processing capacity, 58 percent; better enablement of in-house AI initiatives, 57 percent; streamlined workflows for clinicians and/or other patient-facing roles, 55 percent; easily gain access to backup copies of data and files, 51 percent; improved data normalization, 50 percent; maintain business continuity with space-efficient backup service, 46 percent; better interoperability among systems, 42 percent; more access to flex computing, 42 percent; increased networking speeds, 41 percent; new platforms to connect data with third-party AI assistance, 35 percent; and fewer data silos, 32 percent.

Meanwhile, what concrete steps are organizations taking around data organization, as they move forward with AI? Fifty-nine percent are increasing data storage capacity; 49 percent are integrating with third-party AI solutions; 48 percent are normalizing data from/across disparate systems; 46 percent are creating an enterprise-wide strategy for AI; 45 percent are investing in faster computing and network infrastructure; 43 percent are drawing on data science knowledge across the organization; 40 percent are building custom AI solutions to fill specific organizational needs; 39 percent are turning to third-party organizations or consultants for expertise; 36 percent are developing a dedicated data science team; 35 percent are deploying multi-cloud infrastructure solutions; and 30 percent are consolidating data into data lakes or ponds.

But what are the main factors slowing AI adoption in patient care organizations? The top concerns are as follows: concerns about data security/privacy (46 percent); interoperability issues ()42 percent); unproven or uncertain ROI (39 percent); and concerns about regulatory compliance (31 percent).