Study of work absenteeism for the period January 2017 to June 2018 of the Instituto Universitario de la Paz (UNIPAZ)

Abstract

This study is the product of a quantitative investigation of descriptive scope and of a Non-Experimental Transversal Deductive nature, whose objective allowed us to describe work absenteeism in employees linked by payroll of the University Institute of Peace, in the city of Barrancabermeja - Santander, and classified by the institute as administrative and teaching staff, during the period January 2017 - June 2018. For data collection, second-source information was used, provided by the Institute's Human Management Office, thus building a database that grouped all the variables, such as: gender, dependency, type of payroll, days of absence, type of event that generates the absence, medical classification of disabilities, among others, and that were the input for the statistical analysis; Therefore, a multivariate descriptive analysis was carried out, where the indicators were calculated

Colombian Technical Standards NTC-3701 and NTC-3793, at the time of the investigation the resolution was still in force, but at the date of publication of the article resolution 1111 of 2017 has been repealed by resolution 0312 of 2019. The means used to collect and process the information is a computer tool, of its own authorship, developed in Microsoft Excel, thus providing reliability in the results of the data obtained, presenting the information through histograms, tables, graphs and tables, that of work absenteeism to show which were the predominant causes and the representation of the costs.

The study's conclusions reveal that health-related causes, such as illness and maternity, are the main reasons for absenteeism at the Institute. This suggests that the prevalence of illnesses leads to the initial absences. In addition, it was identified that personal leave is the main cause of non-health related absenteeism. The study population included all official employees who worked at the educational center between January 2017 and June 2018. An average of 235 absentee workers were identified, which meant 1,464 absences and 4,405 days of absence. Of these, 3,057 days were due to medical leave, and the majority of absentee employees were women.