Associations between respiratory nursing diagnoses and nursing interventions in patients submitted to thoracic or upper abdominal surgery

Standardized Nursing Diagnoses in a Surgical Hospital Setting: A Retrospective Study Based on Electronic Health Data

Introduction

In electronic health records (EHRs), standardized nursing terminologies (SNTs), such as nursing diagnoses (NDs), are needed to demonstrate the impact of nursing care on patient outcomes. Unfortunately, the use of NDs is not common in clinical practice, especially in surgical settings, and is rarely included in EHRs.

Objectives

The aim of the study was to describe the prevalence and trend of NDs in a hospital surgical setting by also analyzing the relationship between NDs and hospital outcomes.

Methods

A retrospective study was conducted. All adult inpatients consecutively admitted to one of the 15 surgical inpatient units of an Italian university hospital across 1 year were included. Data, including the Professional Assessment Instrument and the Hospital Discharge Register, were collected retrospectively from the hospital's EHRs.

Results

The sample included 5,027 surgical inpatients. There was a mean of 6.3 ± 4.3 NDs per patient. The average distribution of NDs showed a stable trend throughout the year. The most representative NANDA-I ND domain was safety/protection. The total number of NDs on admission was significantly higher for patient whose length of stay was longer. A statistically significant correlation was observed between the number of NDs on admission and the number of intra-hospital patient transfers. Additionally, the mean number of NDs on admission was higher for patients who were later transferred to an intensive care unit compared to those who were not transferred.

Conclusion

NDs represent the key to understanding the contribution of nurses in the surgical setting. NDs collected upon admission can represent a prognostic factor related to the hospital's key outcomes.

Application of Deep Neural Network Factor Analysis Model in Operating Room Management Nursing Analysis of Postoperative Infection Nursing after Thoracic Surgery

Thoracic surgery is the main surgical method for the treatment of respiratory diseases and lung diseases, but infections caused by improper care are prone to occur during the operation, which can induce pulmonary edema and lung injury and affect the effect of the operation and the subsequent recovery. Therefore, it is necessary to control the disease in time and adopt more scientific and comprehensive nursing measures. Based on the neural network algorithm, this paper constructs a neural network-based factor analysis model and applies the operating room management nursing to postoperative infection nursing after thoracic surgery and verifies the effect through the neural network model. The statistical parameters in this article mainly include the postoperative infection rate of thoracic surgery, patient satisfaction, postoperative rehabilitation effect, and complications. Through statistical analysis, it can be known that operating room management and nursing can play an important role in postoperative infection nursing after thoracic surgery, effectively reducing postoperative infection nursing after thoracic surgery, and improving the recovery effect of patients after infection.

Analysis Model of the Impact of Refined Intervention in Operating Room on Patients' Recovery Quality and Complications after Thoracic Surgery Based on Deep Neural Network

To improve the nursing effect in patients after thoracic surgery, this paper proposes a refined intervention method in the operating room based on traditional operating room nursing and applies this method to the nursing of patients after thoracic surgery. Moreover, this paper improves the traditional neural network algorithm and uses the deep neural network algorithm to process test data. In addition, it includes patients accepted by the hospital as samples for test analysis and formulates detailed intervention methods for the operating room. Finally, this paper collects the corresponding test data by setting up test and control groups and visually displays the data using mathematical statistics. The statistical parameters of the experiment in this paper include the quality of recovery, complications, satisfaction score, and recovery effect. The comparative test shows that the refined intervention in the operating room based on the neural network proposed in this paper can achieve a certain effect in the postoperative nursing of thoracic surgery, effectively promote the quality of recovery, and reduce the possibility of complications.

Application of Rapid Rehabilitation Nursing in Thoracic Surgery Nursing

To study the application effect of rapid rehabilitation nursing intervention in thoracic surgery nursing, this paper researches controlled trials. First, this paper sets up a control group and a test group. The control group uses traditional nursing methods for thoracic surgical nursing intervention, and the test group adds rapid rehabilitation nursing intervention based on traditional nursing intervention. In addition, the operation and rehabilitation conditions of the control group and the test group are the same. Moreover, this paper records rehabilitation information in real time, performs data processing through statistical methods, and conducts follow-up surveys on the rehabilitation process of patients. In addition, this paper compares nursing effects through data comparison and histogram comparison. From the research results, various parameters of the patient's recovery process and the user satisfaction of the rapid rehabilitation can be seen. Furthermore, nursing is higher than those of the control group, which shows that the rapid rehabilitation nursing method can positively affect the nursing of thoracic surgery.

Content analysis of clinical indicators for Impaired gas exchange

OBJECTIVE

To analyze the relevance of clinical indicators and the clarity and precision of conceptual and operational definitions of the diagnosis Impaired gas exchange.

METHODS

Content analysis, by 39 nurse judges, divided into the phases of conceptual definition of the phenomenon of interest, construction of the structure of the phenomenon of interest and analysis of the judges on the built structure.

RESULTS

From the 22 indicators, 21 were considered relevant Impaired gas exchange. The indicators that obtained absolute relevance were Cyanosis, Hypercapnia, Hypoxemia and Tachycardia. The indicator Headache upon waking did not show any statistically significant relevance for the diagnosis. All conceptual and operational definitions were clear and precise.

CONCLUSION

The indicators listed for Impaired gas exchange were relevant to the phenomenon, except Headache upon waking because it does not correspond to a safe manifestation to identify the diagnosis, according to the analysis of the judges. Each conceptual and operational definition was adequate for its indicator.