Prevalent nursing diagnosis of patients in palliative care: a data mining
DOI:
https://doi.org/10.33448/rsd-v10i17.24725Keywords:
Data mining; Palliative care; Nursing diagnosis.Abstract
Introduction: palliative care is patient-centered and includes approaches to symptom relief and physiological reduction and psychological distress associated with the disease. In this context, the nursing diagnosis (ND) establishes bases for the selection of nursing interventions to achieve results in this population, for which the nurse is responsible. Objective: to identify the prevalent NDs in palliative care patients, sociodemographic and clinical profile of hospitalized adult patients who received palliative care consultations in clinical and surgical units registered in electronic medical records. Method: retrospective observational study with secondary use of data. The study population consisted of all adults admitted to the clinical and surgical units of a university hospital between June 2014 and July 2019, totaling approximately 51,000 unique records. The sample comprised patients who received consultations in palliative care during hospitalization. Data analysis was performed using Structured Query Language (SQL). Results: 91 different nursing diagnoses were chosen for the study sample. Of these, three ND were prevalent: Risk of falls was present in the prescription of 1350 patients, Impaired tissue integrity in 1073 prescriptions and Acute pain in 1032. Conclusion: it is expected that the methodology adopted in this research supports the decision-making process of professionals in order to improve effectiveness in palliative care and optimize the patient safety process.
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Copyright (c) 2021 Aline Tsuma Gaedke Nomura; Miriam de Abreu Almeida; Lisiane Pruinelli; Ana Cristina Pretto Báo; Natália Felix Gasperini; Luciana Nabinger Menna Barreto
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