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Pooling of clinical data is used by all Pharmaceutical companies. Submission to Health Authorities of a new compound is one of the main reasons to pool data but there are multiple of others needs for pooling data such as ongoing safety review and publications.
Pooling data from different studies can improve the precision of an incidence estimate (i.e., narrow the confi-dence intervals by enlarging the sample size). Pooling can be done across all phases, within a compound, or across compounds and provide the larger da-tabase that will allow explorations of possible drug analysis.
9 Οκτ 2023 · In healthcare, health information (HI) professionals encounter various types of data essential for effective management, analysis, and utilization in healthcare delivery, decision-making, and research.
29 Μαρ 2024 · Data analytics in healthcare is defined as the process of collecting, analyzing, and interpreting large volumes of healthcare data to derive actionable insights and inform decision-making aimed at improving patient care, enhancing operational efficiency, and driving organizational performance.
Big data (BD) is of high interest for research and practice purposes because it has the potential to provide insights into the population served and healthcare practices. Much progress has been made in collecting BD and creating tools for big data analytics (BDA).
The purpose of this article is to describe how simple pooling differs from meta-analysis, provide a detailed analysis of why simple pooling can be a poor procedure, and show that combining by meta-analytic methods avoids such problems.
What is healthcare data analytics? At its heart, healthcare data analytics is the uncovering of patterns and insights from raw healthcare data like patient histories, bloodwork and genetic trackers to help healthcare providers determine the best course of treatment.
