Exploratory multivariate analysis of hospital admissions data in conjunction with workforce data

Area of Science:

• Health Services Research
• Health Informatics
• Healthcare Management

Background:

• Electronic health records offer insights into hospital admissions.
• Limited research integrates admission data with environmental factors like staffing and hospital type.
• Understanding these combined factors is crucial for healthcare dynamics.

Purpose of the Study:

• To investigate the relationship between hospital admission records and workforce data.
• To explore the influence of environmental factors on hospital admission patterns.
• To identify key variables contributing to the typology of hospital admissions.

Main Methods:

• Utilized exploratory multivariate analysis.
• Applied principal component analysis (PCA).
• Employed multiple correspondence analysis (MCA) to analyze admission and workforce data.

Main Results:

• Identified significant variables associated with hospital admissions and workforce data.
• Exploratory analysis revealed contributions of these variables to admission typologies.
• Shed light on the complex interplay between hospital environment and patient admissions.

Conclusions:

• Hospital admission patterns are influenced by a combination of patient data and environmental factors.
• Multivariate analysis effectively identifies key drivers in hospital admission typologies.
• Further research integrating diverse data sources can enhance understanding of healthcare dynamics.