A Capacity Allocation Planning Model for Integrated Care and Access Management.

Area of Science:

• Healthcare Operations Research
• Health Systems Engineering
• Clinical Informatics

Background:

• Current first-come, first-served outpatient scheduling fails to account for patient urgency.
• This leads to suboptimal appointment access, with urgent cases sometimes experiencing longer delays than non-urgent ones.
• Integrated care environments with multiple specialties exacerbate scheduling complexities.

Purpose of the Study:

• To develop and evaluate a capacity allocation optimization methodology for outpatient appointments.
• To prioritize urgent patient access and reduce overall waiting times in complex healthcare networks.
• To improve efficiency and patient flow within integrated care systems.

Main Methods:

• Formulated the problem as a queueing network optimization.
• Approximated the optimization using deterministic linear programming.
• Developed a methodology to reserve appointment slots based on urgency.
• Reallocated network capacity to minimize access delays for initial and downstream appointments, differentiated by urgency.

Main Results:

• Reduced mean access delay for urgent patients by 27%.
• Achieved this with only a 7% increase in mean access delay for non-urgent patients.
• Increased overall patient throughput by 31% while maintaining service levels and limiting overtime.

Conclusions:

• Urgency-based capacity allocation is an effective strategy for improving outpatient appointment scheduling.
• This optimization methodology can significantly reduce delays for urgent patients in complex healthcare settings.
• The approach enhances system efficiency and throughput without compromising service levels for non-urgent patients.