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Harnessing AI for Healthcare Philanthropy

Olivia Hairfield
Published:  06/13/2024

Artificial Intelligence (AI) is revolutionizing numerous sectors, and healthcare philanthropy is no exception. By leveraging AI, healthcare institutions can enhance their fundraising efforts, ensuring they can continue to provide top-tier care and services. In a recent webinar, Michigan Medicine's Senior Associate Vice President and Chief Development Officer Eric Barritt, Mayo Clinic's Development Operations Vice Chair Alex Bradspies, and Providence St. Joseph Health Foundation's Chief Operating Officer Matt Turkington shared their insights on how their organizations are leveraging AI to enhance operations.


AI at Michigan Medicine, Mayo Clinic, and Providence 

Mayo Clinic and Providence have developed their own versions of generative AI tools. Alex detailed how Mayo Clinic, in collaboration with Google, has created a customized GPT model that meets their specific requirements, ensuring stringent data privacy. Meanwhile, Matt described Providence's "Providence Chat," an internal tool designed to keep sensitive information secure and prevent it from leaking to public models, underscoring the critical importance of privacy and security in healthcare AI applications.

Eric highlighted Michigan Medicine’s comprehensive AI approach, which integrates consumer-facing generative products like ChatGPT with customized support through the University of Michigan's U-M GPT. This tailored solution addresses the unique needs of students, faculty, and staff.

How You Can Use AI 

AI offers several transformative opportunities for healthcare philanthropy, including predictive analytics, personalized donor engagement, and streamlined operational efficiency.

1. Predictive Analytics

Predictive analytics involves using historical data to predict future outcomes. In healthcare philanthropy, this can mean identifying potential major donors based on their interactions with the healthcare system. For example, the Mayo Clinic uses its in-house model to measure patient gratitude, which helps identify individuals who may be more inclined to donate. This model aggregates data, like a patient's frequency of appointments, to pinpoint those who have had life-changing experiences at the clinic, making them likely candidates for philanthropic engagement.

Similarly, Providence has created custom models that assess the relationship between donors and patients to prioritize outreach efforts efficiently. These models can process large volumes of data—up to 30,000 patient visits per day—ensuring that researchers and fundraisers can focus on the most promising leads.

2. Personalized Donor Engagement

AI can also facilitate highly personalized engagement strategies. By analyzing vast amounts of data, AI can generate tailored content and proposals for potential benefactors. At the Mayo Clinic, AI models are being trained not only on patient data but also on the organization's collateral, such as mailers and emails. This dual approach allows the clinic to generate personalized fundraising opportunities that resonate more deeply with prospective donors.

Providence's partnership with Microsoft and its use of tools like Microsoft's Copilot further enhance personalized engagement. Copilot, an AI tool integrated with internal organizational knowledge, enables fundraisers to access comprehensive information about donors, crafting more effective and individualized communication strategies.

3. Streamlined Operations

AI streamlines many operational aspects of healthcare philanthropy, from sorting and categorizing data to managing day-to-day tasks. This operational efficiency is crucial in handling large healthcare organizations' sheer volume of data. For instance, Providence uses AI to triage patient inquiries and prioritize tasks, allowing human staff to focus on higher-level strategic activities.

Staff at Michigan Medicine uses AI tools to draft notes and messages, aiding fundraisers who might struggle with writer's block. However, while AI-generated content can be helpful, human oversight is still required to ensure personalization and relevance.


Strategic Partnerships in AI Implementation

Strategic partnerships with companies like Google and Microsoft have been pivotal in advancing AI use in healthcare philanthropy. These collaborations provide healthcare organizations with access to cutting-edge AI technologies and expertise. For example:

  • Mayo Clinic and Google: The Mayo Clinic benefits from its enterprise relationship with Google, particularly in AI ethics and data management. This partnership has enabled Mayo to act as a convenor, bringing together various stakeholders to develop and deploy AI models across its global platform.
  • Providence and Microsoft: Providence's strategic partnership with Microsoft has been instrumental in integrating AI tools like Copilot into the foundation's fundraising efforts. This collaboration has given Providence unique access to advanced AI capabilities, enabling them to host ideation sessions with Microsoft experts and apply AI solutions to specific fundraising challenges.

Ethical Considerations and Data Privacy

When considering AI, it's essential to consider ethical implications and data privacy issues. Both Alex and Matt emphasized the importance of using internal models to safeguard sensitive information. Alex noted that Mayo Clinic mandates the use of their internal GPT model to prevent the leakage of protected health information (PHI) and business confidential data.

External AI models often pose risks due to their exposure to broader networks where unauthorized parties could potentially access data. Using internal AI systems ensures that all data processing remains within the organization's secure environment, thus minimizing the risk of data breaches.

Furthermore, Alex explained that the internal GPT model at Mayo Clinic undergoes rigorous testing and validation to ensure compliance with strict data privacy regulations such as HIPAA. This model is designed with advanced encryption and access control measures, ensuring only authorized personnel can access sensitive information.

When deciding to implement AI at your shop, also consider the broader ethical implications, such as bias in AI algorithms and the importance of transparency in AI decision-making processes. Ongoing monitoring and auditing of AI systems to identify and mitigate any biases that could affect patient care.

AI in 2024

AI is a present reality that can significantly enhance the efficiency and effectiveness of healthcare fundraising. By leveraging both generative and predictive AI, organizations can better understand and engage with their donors, optimize their strategies, and ultimately achieve their fundraising goals. However, it is crucial to carefully navigate the ethical and privacy challenges to ensure that foundations use AI tools responsibly and effectively.

As AI continues to evolve, its role in healthcare fundraising will likely expand, offering new possibilities for innovation and improvement in how organizations connect with and support their donors.

NEWS  /04/10/24
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Meet The Author

Olivia Hairfield
Marketing Senior Manager
Association for Healthcare Philanthropy

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