Nursing care complexity as a predictor of adverse events in patients transferred from ICU to hospital ward after general surgery.

OBJECTIVES: Predicting the likelihood of adverse events following discharge from the intensive care unit (ICU) can contribute to improving the quality of surgical care. This study aimed to evaluate the impact of nursing care complexity as a predictor of adverse event development in general surgery patients transferred from the ICU to the hospital ward. METHODS: A prospective observational study was conducted with 100 patients in the ICU and general surgical inpatient unit of a training and research hospital in Istanbul, Turkey. The Nursing Care Complexity tool was used by ICU and hospital ward nurses to measure nursing complexity. RESULTS: A total of 65 adverse events developed in 51 patients during hospital ward hospitalization after discharge from the ICU. Nursing care complexity evaluations by the ICU nurses predicted overall and some specific adverse events, while hospital ward nurses' evaluations predicted ICU readmission and some follow-up abnormalities such as patients' blood pressure, pulse rate, and laboratory results. CONCLUSION: The results of the current study validate that nursing care complexity can serve as a valuable tool for predicting the risk of adverse events and ICU readmission following discharge from the ICU. IMPLICATIONS FOR CLINICAL PRACTICE: The use of the Nursing Care complexity tool by the ICU and even hospital ward nurses after ICU discharge may have a significant impact on patient outcomes and contribute to the recognition of nursing efforts.

"Sleep Quality and Depression Level in Nurses in COVID-19 Pandemic".

The COVID-19 spread rapidly all over the world and pandemic process has negatively affected nurses. Sleep disorders and depression are among these negative effects. Managers' awareness of problems experienced by nurses and taking precautions will increase employee and patient satisfaction and provide quality patient care. The study was conducted in descriptive, cross-sectional and correlational design to explain nurses' sleep quality and depression levels and relationship between them during the COVID-19 pandemic with 142 nurses who completed Personel Information Form, Pittsburgh Sleep Quality Index (PSQI) and Beck Depression Index (BDI). Sleep quality of nurses (64.8%) was poor, 33.1% had depression, and high school education, having a chronic illness and PSQI score increased the risk of depression level of nurses. Results highlight COVID-19 pandemic affected nurses' sleep quality and depression levels. All managers should be pioneers in providing psychological support to nurses and preparing and implementing a program for prevention of insomnia and depression.

The Most Commonly Determined Nursing Diagnoses According to NANDA-I Taxonomy and Difficulties Using the Nursing Process in COVID-19 Outbreak.

The study was planned to determine the most common nursing diagnoses according to NANDA International (NANDA-I) taxonomy and difficulties experienced in using of nursing process in COVID-19 outbreak. The sample of the descriptive cross-sectional study consisted of nurses cared for patients with COVID-19 (n = 114). Average age of nurses is 26.86 ± 6.68. Commonly determined nursing diagnoses according to NANDA-I taxonomy in patients with COVID-19 were imbalanced nutrition (66.7%), impaired gas exchange (40.4%), insomnia (21.1%), acute confusion (31.6%), hopelessness (96.5%), difficulty playing caregiver (84.2%), anxiety (38.6%) willingness to strengthen religious bond (71.9%), risk for infection (64.9%), nausea (49.1%). Twenty-four-years old and younger, high school graduates, caring for intubated patients, and those who stated that they did not use nursing diagnosis had more difficulty in using nursing process (<0.05). The use of nursing diagnoses and process for patients with COVID-19 is extremely important in ensuring individual and qualified nursing care.