Using Return on Investment Operational and Monte Carlo Modeling Techniques to Predict Financial Performance in a...

Area of Science:

• Healthcare Management
• Financial Modeling
• Operations Research

Background:

• Quality improvement studies often lack robust financial analysis for return on investment (ROI) prediction.
• Accurate financial forecasting is crucial for evaluating healthcare initiatives.

Purpose of the Study:

• To test the hypothesis that ROIC operational mapping and Monte Carlo simulation can predict institutional costs and operational metrics.
• To validate these financial modeling techniques in an outpatient urology clinic setting.

Main Methods:

• Developed a process map of outpatient clinic visits and conducted time studies.
• Adapted the process map into an ROIC-tree for financial modeling.
• Utilized Monte Carlo simulation for stochastic modeling of financial metrics.

Main Results:

• The combined ROIC-Monte Carlo simulation model generated accurate financial and operational estimates.
• Estimates for 2017-2018 showed a difference of <4.31% from actual financial values.
• Estimates for 2018-2019 showed a difference of <7.67% from actual financial statement line items.

Conclusions:

• The study demonstrated the predictive capability of ROIC-operational mapping and Monte Carlo simulation for financial metrics in a tertiary care clinic.
• Common business tools can effectively support healthcare financial and operational performance evaluations.
• This approach aids clinicians in assessing the financial implications of quality improvement investments.