The Role of Machine Learning Algorithms in Enhancing Wellness Programs and Reducing Healthcare Costs

Authors

  • Ramanakar Reddy Danda

Keywords:

Wellness programs, Organizational strategy, Healthcare costs, Work-life balance, Employee satisfaction, Nutrition monitoring, Fitness counseling, Smoking cessation, Weight management, Vaccination programs, Employee mental wellness, Recruitment and retention, Return on investment (ROI), Employee incentives, Engagement strategies, Machine learning algorithms, Rewards and recognition, Healthy workforce, Strategic wellness tools, Risks and opportunities in wellness programs.

Abstract

The use of wellness programs as organizational strategic tools is becoming more prevalent as healthcare costs continue to increase and more employees feel dissatisfied with their work-life balance. In the past, these programs consisted of nutrition and fitness monitoring and counseling, smoking cessation, weight management, vaccination, making changes to transportation, assessment of healthcare medical results, and improved attention to employee mental wellness. Small to medium-sized organizations have been able to achieve significant gains in recruitment, retention, and return on investment with incentives for their employees to use these programs, up to about 30%. The challenge for organizations is to use wellness programs as a strategic tool to increase engagement, reduce healthcare costs, and attain the other benefits of having a healthy workforce. This paper looks at how wellness programs have been used, and the impacts of machine learning algorithms in both rewards and recognition programs. The paper also outlines the risks and opportunities for organizations that become involved with these two strategic wellness programs.

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Published

2024-11-19

How to Cite

Ramanakar Reddy Danda. (2024). The Role of Machine Learning Algorithms in Enhancing Wellness Programs and Reducing Healthcare Costs. Utilitas Mathematica, 121, 352–364. Retrieved from https://utilitasmathematica.com/index.php/Index/article/view/2078

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