Strategic Integration of Artificial Intelligence in Health-care Systems: Assessing Costs, Technological Upgrades, and Training Timelines

Abstract

BACKGROUND: In recent years, the evaluation of artificial intelligence (AI) in health-care sector has undergone significant growth and is substantially helpful in supporting clinical decision-making based on evidence. The primary aim of the study is to investigate the strategic integration of AI in health-care systems, specifically focusing on assessing costs, technological upgrades, and training timelines. MATERIALS AND METHODS: This study followed quantitative techniques to explore the AI integration’s importance in the systems of health care highlighting training timelines, upgradation of technology, and associated costs. Using descriptive statistics, data were evaluated and a survey was performed on the professionals of emergency medical care. The study employed a combination of descriptive statistics analysis, such as mean and median calculations, to analyze the data. To select participants, this study applied purposive sampling. The selected sample size of the study was 242 from the Indian health-care context. RESULT: The results of this study indicated that clear training timelines establishment, technological upgradation, and cost assessments are important for successfully integrating AI technologies. In addition, the discussion explored the acceptance of the significance of stakeholders’ collaboration, cost-effective strategies for training, and information technology infrastructure enhancements. The training costs for AI implementation in health care, with 66.12%–69.83% of respondents selecting “strongly agree” and 25.21%–29.75% selecting “agree.” Strong consensus on the necessity of providing specific timelines for AI implementation in emergency departments, with “strongly agree” responses ranging from 66.12% to 68.60%, and “agree” responses from 26.45% to 29.75%. Issues including timeline adherence and funding constraints were discovered, focusing on the necessity for proactive management. CONCLUSION: This research highlighted comprehensive planning’s major role in the integration of AI. Health-care organizations by addressing training timelines, technological upgradation, and cost optimize the incorporation of AI. However, engagement with different financial experts and collaboration with stakeholders are necessary for successfully achieving organizational goals.

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