Capacity planning for effective cohorting of hemodialysis patients during the coronavirus pandemic: A case study

Area of Science:

• Healthcare Operations Research
• Infectious Disease Management
• Public Health Policy

Background:

• The COVID-19 pandemic created significant challenges for hemodialysis clinics, increasing patient demand and operational uncertainties.
• Effective capacity planning is crucial for hemodialysis clinics managing diverse patient groups (infected, uninfected, suspected) with limited resources.
• Current cohorting strategies struggle to minimize infection spread risk and treatment session overlaps due to daily patient number fluctuations.

Purpose of the Study:

• To develop a stochastic programming approach for optimizing dialysis machine allocation in a hemodialysis clinic during the COVID-19 pandemic.
• To support capacity planning decisions by minimizing overlapping treatment sessions for different patient cohorts.
• To evaluate the effectiveness of different cohorting strategies (three vs. two patient cohorts).

Main Methods:

• A stochastic programming model was formulated to represent patient number uncertainties using scenarios.
• The model was applied to a real-world case study using data from a major public hospital's hemodialysis clinic in Istanbul.
• The proposed model's effectiveness was demonstrated by comparing different cohorting strategies.

Main Results:

• The stochastic programming approach effectively supports capacity allocation decisions for hemodialysis clinics facing patient number uncertainties.
• The model demonstrated the ability to minimize overlapping treatment sessions across different patient cohorts.
• Comparison of strategies indicated the performance variations between three- and two-patient cohort approaches.

Conclusions:

• The proposed stochastic programming model offers a robust solution for optimizing hemodialysis clinic capacity planning amidst pandemic-related uncertainties.
• Effective resource allocation and cohorting strategies are vital for maintaining patient safety and operational efficiency in healthcare settings.
• This research provides valuable insights for improving hemodialysis clinic management and preparedness for future public health crises.