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Review Papers | Information Technology | United States of America | Volume 13 Issue 7, July 2024 | Rating: 5.6 / 10
Leveraging Data Analytics with Artificial Intelligence to Detect and Close Health Care Gaps
Jinesh Kumar Chinnathambi
Abstract: The healthcare sector is transforming significantly, driven by extensive data sets and advanced Technology. This research focuses on the interaction between data analytics and artificial intelligence (AI) to identify and address care gaps that hinder healthcare quality and effectiveness. These gaps often stem from fragmented services, communication breakdowns, and overlooked blind spots in healthcare, resulting in diminished patient care quality and potential strain on the healthcare system. The fusion of AI's predictive capabilities and adaptability with advanced data analytics can provide a comprehensive operational overview, recognizing areas for improvement and potential risks. Machine learning models can analyze extensive and diverse data, uncover patterns, trends, and predicting future care gaps. Integrating data analytics and AI can help healthcare organizations in risk stratification, personalized care, preventive healthcare, and optimal resource allocation. The potential of these technologies extends to reshaping care pathways, enhancing patient outcomes, and improving healthcare delivery standards. This analysis offers a comprehensive look at how data analytics with artificial intelligence could revolutionize the healthcare industry by detecting and addressing care gaps. Effective care gap programs should consider the numerous factors contributing to care delays, which COVID-19 has exacerbated. Rural communities throughout the United States lack access to health care. While only 14% of Americans?almost 46 million people?live in rural areas, rural communities represent nearly two-thirds of primary care health professional shortage areas (HPSAs) in the country.[1] In recent years, fear of COVID-19 exposure has led to a reduction in primary care visits, with 11% of adults choosing to delay or forgo care due to COVID-19.
Keywords: Healthcare data analytics, Artificial intelligence in healthcare, Patient care improvement, Technology in healthcare, Care gap analysis, Preventive healthcare, Value-based care, Patient outcomes, Closing care gaps, Healthcare cost reduction, Telemedicine, Health data insights, Provider-payer collaboration, Addressing healthcare challenges, Patient engagement
Edition: Volume 13 Issue 7, July 2024
Pages: 1325 - 1330