Researchers are encouraging Nigerian hospitals and clinics to start using computational risk pooling. This method can help reduce financial losses and improve the quality of care for patients.
A study published in the *Journal of Research in Engineering and Computer Sciences* found that using risk pooling has helped healthcare centres make more money and lose less financially. However, the effect on costs and patient satisfaction is still mixed.
The study, called “Enhancing Risk Management in Healthcare Administration: A Computational Approach to Risk Pooling,” suggests that risk pooling should be used along with other modern healthcare strategies to help hospitals stay financially stable and improve patient care.
To carry out the study, researchers collected data from hospitals, clinics, and care centres using a method called stratified sampling. They used a software tool called SPSS to analyze the data and showed that computational tools can help predict risks and manage resources better in complex health systems.
The researchers found some improvement in patient care, like shorter hospital stays and fewer readmissions. However, many healthcare providers still face challenges in fully using these computer-based models for managing risk.
Some of the main problems include staff who resist change, not enough training, and weak systems that don’t work well together. Some hospital leaders also said they don’t get enough support from upper management.
The study used the Swiss Cheese Model and Human Factors Engineering theories to explain how combining computer systems with human-focused design can help prevent medical mistakes and system failures.
Speaking to Reporters the lead researcher, Tosin Clement, said computational risk pooling uses advanced data tools to manage risks across different hospitals. She said this method can reduce financial pressure and make hospital operations more efficient.
Tosin added that the study, which involved 150 healthcare centres, found that those using computational risk pooling lost less money and saw some improvement in patient results.
This approach helps hospital managers better predict problems and use their resources more wisely.
Even though the method has benefits, Tosin said there are still big problems preventing it from being used everywhere.
These problems include limited resources, strict rules, not enough skilled workers, and staff not wanting to change how they work.
Tosin urged health leaders and government officials to invest in training, tools, and leadership support. She warned that without these, computational risk pooling will not reach its full potential.
Tosin is a data expert with over five years of experience in consulting, healthcare, and online business. She helps companies understand data and make smart decisions.
She is skilled in tools like SQL, Power BI, Tableau, and Python. She’s good at collecting and cleaning data, making predictions, and creating clear visuals that help teams make better choices.
In her career, she has led many projects to improve reports, track financial performance, and make healthcare operations run more smoothly.
