Avaliação do algoritmo da distribuição da carga de trabalho para técnicos e auxiliares de enfermagem em unidades de clínica médica e cirúrgica

• Ano de defesa: 2011
• Autor(a) principal: Nishio, Elizabeth Akemi [UNIFESP]
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Paulo (UNIFESP)
• Palavras-chave em Português: Dimensionamento de pessoal; Enfermagem; Tomada decisão; Avaliação carga de trabalho; Carga de trabalho; Downsizing organizacional; Saúde do trabalhador; Auxiliares de enfermagem/organização & administração; Nursing; Workload; Personnel Downsizing; Occupational health; Nurses' aides/organization & administration; Decision making
• Link de acesso: http://repositorio.unifesp.br/handle/11600/9074

Aims: To identify the nursing hours spent by technicians and nursing assistants in the Units of Clínical Medicine (CM) and Units of Clínical Surgery (CC) for the comple-tion of nursing care in different shifts, morning, noon and night. Method: This is an original study prospective, analytical approach to quantitative standard time and mo-tion. Four nurses from the General Hospital Pirajussara (HGP) observed and meas-ured the time spent by technicians and nursing assistants for care provided to pa-tients hospitalized in units CM and CC. At the beginning of each work period (morn-ing, afternoon and evening) for seven days a week, nurse’s observers randomly chose eight nursing technicians (TE) and nursing assistants (AE) (four for each). In parallel, we carried out the distribution of patients for each employee using the rec-ommendation of the Nursing Care Model of Experimental HGP (MAEE-HGP). Cate-gorical variables were described through absolute and relative frequencies and quan-titative variables were presented as means and standard deviations.Results: We identified the hours spent by TE/AE by type of patient within 24 hours: 3.5 hours (± 1.0) for minimal care, 3.9 hours (± 0.9) for intermediate care, 5.1 hour (± 1.4) for high dependency care, 6.7 hours (± 1.0) for semi-intensive care and 3.1 hours (±1.0) for joint care. As the distribution of patients by type recommended by the MAEE-HGP, the hours spent between TE/AE, for six hours were minimal care 4.9 hours (± 0.7), intermediate care 5.2 hours (± 0.5), high dependency care 4.9 hours (± 0.5), semi-intensive care 5.1 hours (± 0.6) and mixed care 4.3 hours (±0.3). Conclusion: The study results showed that the distribution of workload by TE/AE, by using the algo-rithm MAEE-HGP, resulting in a balanced distribution of hours. These may be ob-tained actual hours used as the basis for development of computerized decision-making for homogeneous distribution of hours for the AE/TE in units medical and surgical.