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Sponsored Content Provided By Consensus Cloud Solutions
This content was created by and paid for by an advertiser. The Crain's editorial department was not involved in the creation of this content.
March 21, 2022 01:01 AM

Transparency is key to encourage wider adoption of artificial intelligence

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    Jeffrey Sullivan

    Jeffrey Sullivan
    Chief Technology Officer
    Consensus Cloud Solutions

    Jeffrey Sullivan has served as chief technology officer for Consensus Cloud Solutions since February 2019 (formerly J2 Global). Prior to joining Consensus, Sullivan was chief technology officer for Demandforce (formerly Internet Brands) and vice president of technology for the health market segment at Internet Brands.

    Sullivan is a professional writer in the areas of technology and creative writing, with more than 200 published magazine articles and book chapters to his credit.

    More healthcare leaders are leaning into AI investments. Can you offer an example of how AI technology is positively impacting the healthcare delivery system?

    JS: We saw the impact of this technology within a state-run healthcare organization, which was managing thousands of incoming unstructured documents. They needed a better solution to manage Medicare and Medicaid insurance claims for processing and approval. Natural Language Processing (NLP) and AI found these claims forms among the trove of documents and identified and structured the most important information, then routed all that information to the most appropriate workflow.

    What is your advice to healthcare executives and boards integrating AI solutions at their organization?

    JS: For many organizations, skepticism often accompanies the acquisition of AI solutions. However, skepticism should not deter progress. Paired with human and automated review mechanisms, AI can build trust. It can be piloted with high-effort manual workflows (e.g., extracting data from fax transmissions) to deliver early benefits. AI can incrementally deliver organizational value rather than shooting for the stars with the first implementation.

    How can healthcare leaders establish trust in AI technology among their patients and staff?

    JS: There is no silver bullet to this question. The best way to drive adoption and trust is transparency. Share the results, warts and all. Start small, establish guardrails and build on successes. Adapt technology to existing workflows, not the other way around. When technology improves outcomes, especially without forcing major changes to existing workflows, trust will be built, and adoption increased. It’s a win for everyone, including patients.

    Biases in AI solutions, such as racial and gender biases, are a concern. How should the industry go about addressing this issue?

    JS: Biases in AI models are mostly a result of poor selection of training populations, which are not representative of the population they address. Our industry must keep the roots of racial and gender biases in mind when exploring the basis of models and algorithms in AI systems. Much like documentation of treatment populations in drug studies, documentation of algorithmic derivations should be part of the evaluation process for AI systems.

    What guidance would you offer for ensuring the clinical data leveraged within AI technology is secure?

    JS: AI poses several challenges that the industry has not had to address in the past. The AI itself should adhere to the same standards as any other protected health information (PHI) application, but the implementation of responsible and ethical AI practices must also be addressed. Best practices such as the HITRUST CSF certification and similar security frameworks should be applied to both the development systems producing the AI solutions and the production environments in which they run.

    Hospitals and health systems typically partner with technology companies to implement and deploy AI technology. What qualities should healthcare leaders look for in a partner?

    JS: A quick Google search for “AI partner” will yield about 865 million results, leaving many feeling like selecting one will be daunting. Healthcare is unlike many other industries, it’s personal, which is why you need the right one for you. Any AI partner must: understand the nature of your business; be able to support the high level of protecting electronic protected health information (ePHI); own a proven track record of innovation; possess the ability to automate and understand your business model.

    Which clinical and operational applications of AI do you think are most promising for the future of healthcare?

    JS: AI will take some time to permeate all areas within healthcare. Administrative functions will be the first adopters, including order requests for equipment, case prioritization and routing, and linking images, such as faxes, scans and PDFs, to patient records. Early adopters will still blend an element of human touch with more fully integrated AI applications. Over time, we will see epidemiological models for early diagnosis bearing more and more fruit.

    This Executive Insight was produced and brought to you by:

    consensus

    To learn more, visit www.consensus.com

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