Data harnessing to nurture the human mind for a tailored approach to the child

Saheli Chatterjee Misra1, Kaushik Mukhopadhyay2

  • 1Pediatrics ESIC PGIMSR & ESIC Medical College, Diamond Harbour Road, Joka, Kolkata, 104, West Bengal, India. saheli2069@gmail.com.

Pediatric Research
|September 30, 2022
PubMed

Insights

Big data analysis in pediatrics extracts vital information from diverse datasets to enhance clinical decision-making, diagnosis, and therapy. This evolving field integrates data to improve patient health outcomes and healthcare system performance.

Area of Science:

  • Pediatric Medicine
  • Health Informatics
  • Data Science

Background:

  • Pediatric healthcare generates vast amounts of structured and unstructured data.
  • Effective analysis of this big data is crucial for advancing child health.
  • Current applications are transforming clinical practice and health system operations.

Purpose of the Study:

  • To review the impact and applications of big data in pediatrics.
  • To highlight the integration of big data analytics into clinical decision-making and patient care.
  • To discuss the future potential of big data in pediatric specialties.

Main Methods:

  • Review of existing literature and implemented big data projects in pediatrics.
  • Analysis of the types of data utilized, including omics, social, and clinical data.
  • Examination of the role of big data in diagnosis, therapy, and health system surveillance.

Main Results:

  • Big data analytics provides critical insights for pediatricians, improving diagnosis and targeted therapies.
  • Applications range from health surveillance and prevention to enhancing healthcare system performance.
  • Significant progress has been made, with ongoing development for broader clinical integration.

Conclusions:

  • Big data is revolutionizing pediatric care by enabling precision medicine and evidence-based practice.
  • Physicians must understand and utilize big data outcomes for improved patient health.
  • Future advancements include common data models and integrated diagnostic/prediction tools for targeted pediatric care.

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