Almost 80% of provider organizations spent more on IT systems and software this year than last, yet only 6% have a plan in hand to incorporate generative AI into their digital ecosystem.
On the other hand, approximately 50% are either formulating a generative AI strategy or planning to get one going in the near future.
The figures are from a survey conducted by the Boston-based consultancy Bain & Company with an assist from KLAS Research. The duo queried 201 provider executives in June and posted their key findings Sep. 12.
Here are seven more nuggets from their summary, co-authored by Aaron Feinberg and Eric Berger of Bain with Rebecca Hammond of KLAS.
1. More than half the respondents, 56%, have software and technology as one of their top three strategic priorities.
That’s a 22% bounce over 2022’s 34%.
2. Around 75% expect growth in software and technology spending to continue over the next 12 months.
Across provider types, academic medical centers and large hospitals and health systems expect a stronger increase in their own spending than smaller operators due to a greater focus on innovation and financial flexibility.
3. Topping the list of spending drivers are technological advances and new solutions.
Patient engagement and cybersecurity solutions are much in demand, and new spending is additionally goosed by labor shortages and financial pressures.
4. About 70% of health system execs believe AI will have a greater impact on their organization this year than last.
This may signify that AI strategies are migrating from the IT department to the C-suite, possibly spurred by the emergence of generative AI in the months since the release of ChatGPT by OpenAI last fall.
5. Executives at academic medical centers tend to be further along with AI strategies and regard AI more positively.
Academics’ upbeat AI outlook manifests as expectations for better operational efficiencies, patient outcomes and cost savings.
6. Execs at less well-resourced orgs tend to worry more than their enthusiastic peers about security, privacy, cost and ethics.
Regarding barriers to deeper AI adoption, academic medical centers and large health systems worry more about clinical risk and regulatory considerations. Smaller providers fret more about iffy returns on investment, lack of internal expertise and resource constraints.
7. Across the board, top priorities for AI use cases—present and projected—tend to include those that support accurate diagnostics and sound clinical decision-making.
Additionally, as is the case with overall IT investment priorities, providers prefer AI use cases with a strong bottom-line impact, such as predictive analytics and workflow optimization.
Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.