(US & Canada) VIDEO | We Want to Do Everything Safely, Ethically, and Responsibly — Cincinnati Children's Hospital Medical Center Data and Analytics AVP

Bhavna Mehta, AVP of Data and Analytics at Cincinnati Children's Hospital Medical Center, speaks about roadmaps to formulating data strategies, staying updated and integrating tools, the scope of AI and ML, and challenges as a pediatric organization.

Bhavna Mehta, AVP of Data and Analytics at Cincinnati Children's Hospital Medical Center, speaks with Mike Kaiser, Data and Analytics Practice Lead at Centric Consulting, in a video interview about roadmaps to formulating data strategies, staying updated and integrating tools, the scope of AI and ML, and challenges as a pediatric organization.

Speaking about formulating data strategies, Mehta mentions following two roadmaps, one that focuses on capabilities and architecture, while the other is about the projects and initiatives. She notes that both roadmaps are interconnected but are treated separately for better progress.

Elaborating further, Mehta lays down the four pillars of the infrastructure and capability roadmap – People, Process, Technology, and Data.

She maintains that the right tooling and technology stack requires the right people with the accurate skill sets to leverage the technology. Further, the process aspect involves maintaining, supporting, and updating the strategy and the fourth pillar of data revolves around increasing organizational data literacy, to build the capabilities.

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To create the infrastructure, the organization is working to implement a data fabric and data mesh architecture focused on leveraging AI and ML at scale, says Mehta. Next comes data literacy, governance, and processes. Then, the organization focuses on the modernization of tools and is on its journey to the cloud, she adds.

One of the goals, says Mehta, is access, as the hospital wants children to come, and getting appointments is difficult. Elaborating further, she mentions projects wherein the organization stratifies the children by the risks and then assigns the right resources that help to close equity gaps.

Adding on, Mehta says that data strategy is about maintaining a balance between the two parallel paths of strategic priorities and technologies.

When asked about staying updated and integrating tools, she says that it requires continuous learning to stay updated. Further, Mehta mentions leaning on leaders, teams, and partners for prioritizing.

Moving forward, Mehta affirms that the organization tries to stay aligned with the partner roadmaps, assess their progressions, and leverage the technology the partners bring forth. She specifies working with Microsoft on OpenAI and with EPIC as an early adopter with its generative AI features.

Furthermore, Mehta assures that while the organization is open to innovation, there is a standard process for deploying new technology. She reveals that on many occasions, the organization did not deploy technology after the proof of concept (POC) stage as it does not fit in the enterprise architecture.

Commenting on the scope of AI and ML in the hospital, Mehta expresses that healthcare is transforming, and AI is here to innovate care delivery. Computational Medicine techniques are not new to the academic medical center, she adds and refers to its research section where the scientists have been developing new cures.

The promise of AI with technology is that it can reduce the time taken by the organization to go from bench to bedside, thus increasing operational efficiency, says Mehta. She mentions assessing various reimbursement value-based models, moving away from service fees.

With the increase in clinician burnout and staff shortages, the organization is partnering with startups to automate preoperative phone calls from a conversational AI perspective, reveals Mehta.

On top of that, she mentions automating information collection to assess risks. Mehta also mentions how the research scientists have worked on a model to detect early anxiety, which is ready to be tested in primary care spaces.

However, one of the challenges of being a pediatric organization is that there are many available models, that are not tested on pediatrics, confirms Mehta. Therefore, the organization has put processes in place for ethical testing.

Concluding, Mehta affirms having an AI Governance Council and Framework to ensure that the models or AI-embedded technologies go through appropriate processes before being deployed.

CDO Magazine appreciates Bhavna Mehta for sharing her invaluable data insights with our global community.

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