Advanced Business Analytics in Healthcare Enhancing Clinical Decision Support and Operational Efficiency

Sonia Nashid · Sonia Khan Papia · Niladry Chowdhury · Md Sakib Mia · Md Iqbal Hossain

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Big Data and Business Intelligence Electronic Health Records Systems Artificial Intelligence in Healthcare

Abstract

Background: The healthcare industry undergoes a rapid transformation because of advanced business analytics which drives data-based choices and improves operational effectiveness along with clinical decision support (CDS). The healthcare industry shows diverse rates of adoption and implementation success because of technical and organizational and human-related factors. Methods: A cross-sectional study took place in July 2023 where 130 healthcare professionals from hospitals, clinics and public health agencies and private healthcare providers participated. The researchers gathered data through a structured questionnaire which participants completed either online or through face-to-face interaction. The questionnaire evaluated organizational attributes along with analytics adoption levels and tool usage as well as benefits experienced and obstacles encountered. The study used SPSS v26 to conduct descriptive statistics along with cross-tabulations and correlation analyses for analyzing adoption trends and connections between analytics usage and reported outcomes. Results: Advanced analytics tools actively support 78% of respondents while 65% apply analytics to their CDS systems and 58% use analytics for operational optimization purposes. Improved diagnostic accuracy along with better operational efficiency and increased patient satisfaction stood out as the primary advantages reported by participants. Data interoperability issues represented the primary challenge according to 68% of respondents while 64% cited privacy and security issues and 59% reported insufficient staff training. Conclusion: Healthcare organizations need to prioritize interoperability solutions and implement robust data governance while investing in workforce training for analytics capability development and sustainable adoption of these solutions.

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References

2018Ensuring Fairness in Machine Learning to Advance Health Equity 2016Big Data Application in Biomedical Research and Health Care: A Literature Review 2015Behavioral Implications of Big Data's Impact on Audit Judgment and Decision Making and Future Research Directions 2004Expected Value of Sample Information Calculations in Medical Decision Modeling 2005The Effects of Strategic Decision Making on Entrepreneurial Self–Efficacy 2017Business analytics-enabled decision-making effectiveness through knowledge absorptive capacity in health care 2010Improving productivity and firm performance with enterprise resource planning 2014Applications of business analytics in healthcare

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