Service Bundle Recommendation for Person-Centered Care Planning in Cities.

Area of Science:

• Healthcare Management
• Data Science
• Operations Research

Background:

• Supporting vulnerable populations presents significant societal and economic challenges.
• Balancing cost, effectiveness, and patient experience in care services is complex.
• Care teams require tools to navigate vast amounts of information for optimal decision-making.

Purpose of the Study:

• To present a novel system designed to assist care teams in selecting optimal provider combinations for services.
• To address the challenge of balancing cost, effectiveness, and care recipient experience.
• To demonstrate the feasibility of advanced technologies in supporting care planning.

Main Methods:

• Open Data processing and semantic processing for information integration.
• Faceted exploration and visual analytics for data interaction.
• Transportation analytics and multi-objective optimization for decision support.
• Implementation using New York City data.

Main Results:

• The system facilitates the selection of optimal provider combinations for care services.
• Demonstrated feasibility of integrating diverse data processing and optimization techniques.
• The system provides guidance for care workers in care planning.

Conclusions:

• The developed system offers a viable solution for optimizing care service provider selection.
• Advanced data analytics and optimization techniques can effectively guide care planning.
• This approach has the potential to improve support for vulnerable individuals.