Primary health care appointments and hospital stay: an impact analysis

Abstract

The study of avoidable hospitalizations has gained international prom-inence due to its potential to assess the performance of healthcare systems. In Canada and Spain, these hospitalizations are analyzed through Ambulatory Care Sensitive Conditions (ACSC), indicating situations that could have been pre-vented or treated without hospitalization. In Portugal, this concept is represented by the term ICSCSP, focusing on care provided in Primary Health Care (PHC). The data analysis in this study aims to determine the impact that medical ap-pointments at PHC may have on the number of hospitalizations, namely, to de-termine whether where the number of medical appointments is greater, the num-ber of hospital stays is lower. During the COVID-19 pandemic in Portugal, many hospitalizations of the elderly were due to the decompensation of chronic diseases, highlighting the importance of access to PHC during health emergen-cies. Data pre-processing was carried out using the Pandas library in Python, merging two datasets monitoring the evolution of hospitalizations and medical appointments in PHC. Despite some challenges encountered during the analysis, such as population bias in district comparisons and the need to adjust metrics to properly reflect the relationship between appointments and hospital stays, it was concluded that the number of appointments in PHC does not have a direct im-pact on hospitalizations. For a more accurate analysis, it would be necessary to consider other factors, such as patient and district characteristics, and conduct more targeted studies, especially after disruptive events like the COVID-19 pan-demic. This more detailed analysis would allow for a better understanding of the relationship between medical appointments and hospitalizations, contributing to improvements in the healthcare system.