Health systems are heavily dependent on procedures and thus will incentivize physicians to continue using them as first-line for treating patients. This can include investments in technologies such as AI to assist in performing colonoscopies. Increased physician satisfaction and productivity will be a major driver of the use cases even without reimbursement.
Optimal performance of AI systems will require ongoing investments, not only in generating and using increasing amounts of patient data, but also in updating software algorithms and ensuring hardware operability. Equipment upgrades may also be needed to support software updates. All of this maintenance activity will require not only significant effort in human capital, but also a funding mechanism. Funding will be critical to ensuring successful implementation and ongoing process improvement, and currently it is not clear how use of AI technologies will be reimbursed
While business incentives are by no means the only way to advance healthcare, historically they have played a key role in facilitating change. The question of whether AI-based technologies actually bring added value to healthcare with improved outcomes is unanswered. Large-scale clinical trials with the emerging algorithms have not been done yet. As such, the benefits of these algorithms are speculative. The notion of advanced technology with incredible potential that is not yet fully realized is not new. For example, gene therapy, genomic-driven personalized medicine, and EHRs are all technologies that were purported to deliver revolutionary improvements in the delivery of healthcare, but thus far many feel that their potential has exceeded their performance. However, those fields are delivering ongoing advancements with continuing promise for the future.
Similarly, the application of AI-based technologies to medicine is still in its early stages. While the initial investments from government, academia, and industry are growing, whether these will sustain into the future remains to be seen and in part may depend on the successes of the early algorithms. As such, the near-term implementation of AI in Healthcare is by no means certain and we may encounter another AI Winter, even if only in healthcare.
