Online Program

Data Science During a Crisis: Serving Organizational Needs and High-Risk Patients in the COVID-19 Pandemic (304185)

Keywords: statistics, data science, analytical infrastructure, strategic management, leadership, COVID-19, health care, nonprofit management

A crisis can disrupt an organization's deliberative process of management. Existing models may lose their relevance among changing priorities. The organization's analytical staff is necessarily operating on a limited time frame. Providing timely and relevant information is a challenge for data science amid rapidly changing circumstances.

During the COVID-19 pandemic, the nonprofit organization AIRnyc rapidly adapted its home-based health interventions to a remote model. Nearly every aspect of the organization's operations, including program design, staffing, and partnerships with health care systems, required significant revision. Its programs provided critical support to thousands of high risk patients.

A new analytical infrastructure was rapidly constructed and continually evolved based on emerging needs, in turn inspiring new initiatives for the organization. It played a role in increasing productivity, streamlining interventions, and improving the quality of care. This presentation will highlight AIRnyc's use of data to inform its strategic decisions during the crisis, including the technologies, methods, and collaborations that facilitated successful programs.