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Enhancing Quality Management in the Health Care Industry through Machine Learning Techniques
  • Raghavi Bhujang ,
  • Nilakash Paul
Raghavi Bhujang
MS Ramaiah Institute of Management

Corresponding Author:[email protected]

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Nilakash Paul
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Abstract

Quality management is of utmost importance in the healthcare industry as it directly impacts service efficiency and patient outcomes. In recent years, machine learning has emerged as a game-changing innovation in this field. This paper aims to delve into the various applications of machine learning in healthcare, including predictive analytics, clinical decision-making, patient monitoring, and healthcare quality assessment. While machine learning offers numerous advantages, its implementation poses certain challenges, such as concerns regarding data privacy, security, validation, and result interpretation. To address these challenges and explore the effectiveness of machine learning in healthcare management, this study focuses on two hypotheses. Hypothesis 1 investigates the influence of technical components on individuals visiting hospitals for health checkups. The results indicate that, despite the relatively low frequency of health checkups, respondents hold a positive perception of the investigative diagnosis process. This suggests the successful implementation of technical management components in healthcare settings. Moving on to Hypothesis 2, this hypothesis examines the relationship between the availability of medical advice by phone and patient satisfaction with their doctor's treatment. The findings indicate that the availability of telephonic medical advice does not significantly influence patient satisfaction. This highlights the need to explore additional factors that contribute to patient happiness beyond telephonic medical advice alone. The t-test results also support this conclusion, further emphasizing that telephonic medical advice is not a major determinant of patient happiness. Consequently, further research is necessary to identify the key factors that significantly impact patient satisfaction within healthcare settings. In summary, this paper sheds light on the significance of quality management in healthcare, the transformative potential of machine learning, and its applications in various areas of healthcare. The study's findings contribute to a better understanding of the impact of technical components on health checkups and the relationship between telephonic medical advice and patient satisfaction. Further research in this field will help identify and address the critical factors that shape patient satisfaction in healthcare environments. Please note that the above summary is a condensed version of the original text.