Utilization of Nursing Defect Management Evaluation and Deep Learning in Nursing Process Reengineering Optimization

It was to explore the application of nursing defect management evaluation and deep learning in nursing process reengineering optimization. This study first selects the root cause analysis method to analyse the nursing defect management, then realizes the classification of data features according to the convolution neural network (CNN) in deep learning (DL) and uses the constructed training set and verification set to obtain the required plates and feature extraction. Based on statistical analysis and data mining, this study makes statistical analysis of nursing data from a macroperspective, improves Apriori algorithm through simulation, and analyses nursing data mining from a microperspective. The constructed deep learning model is used, CNN network training is conducted on the selected SVHN dataset, the required data types are classified, the data are analysed by using the improved Apriori algorithm, and nurses’ knowledge of nursing process rules is investigated and analysed. The cognition of nursing staff on process optimization and their participation in training were analyzed, the defects in the nursing process were summarized, and the nursing process reengineering was analyzed. The results show that compared with Apriori algorithm, the running time difference of the improved Apriori algorithm is relatively small. With the increase of data recording times, the line trend of the improved algorithm gradually eases, the advantages gradually appear, and the efficiency of data processing is more obvious. The results showed that after the optimization of nursing process, the effect of long-term specialized nursing was significantly higher than that of long-term nursing. Health education was improved by 7.57%, clinical nursing was improved by 6.55%, ward management was improved by 9.85%, and service humanization was improved by 8.97%. In summary, the reoptimization of nursing process is conducive to reduce the defects in nursing. In the data analysis and rule generation based on deep learning network, the reoptimization of nursing process can provide reference for decision-making departments to improve long-term nursing, improve the quality and work efficiency of clinical nurses, and is worthy of clinical promotion.

Postoperative mobilisation as an indicator for the quality of surgical nursing care

Background: Postoperative mobilisation is an important part of fundamental care. Increased mobilisation has positive effect on recovery, but immobilisation is still a challenge in postoperative care. Aims: To report how the establishment of a national nursing database was used to measure postoperative mobilisation in patients undergoing surgery for ovarian cancer. Methods: ‘Mobilisation’ was defined as at least 3 hours out of bed on postoperative day 1, with the goal set at achieving this in 60% of patients. Data entry was performed by clinical nurses on 4400 patients with ovarian cancer. Findings: 46.7% of patients met the goal for mobilisation on the first postoperative day, but variations in duration and type of mobilisation were observed. Of those mobilised, 51.8% had been walking in the hallway. Conclusions: A national nursing database creates opportunities to optimise fundamental care. By comparing nursing data with oncological, surgical and pathology data it became possible to study mobilisation in relation to cancer stage, comorbidity, treatment and extent of surgery.

School Nursing Data Collection During COVID-19

COVID-19 has affected the 2020-2021 school year for everyone and thrust school nurses into the spotlight. Some school nurses are too overwhelmed to even think about data; others want to collect data differently to illustrate the value of the role of the school nurse. This article provides guidance on data collection during this unique time period. The article is based on a blog originally posted on National Association of School Nurses’s website.

The State of Data Science in Genomic Nursing

Nurse scientists are generating, acquiring, distributing, processing, storing, and analyzing greater volumes of complex omics data than ever before. To take full advantage of big omics data, to address core biological questions, and to enhance patient care, however, genomic nurse scientists must embrace data science. Intended for readership with limited but expanding data science knowledge and skills, this article aims to provide a brief overview of the state of data science in genomic nursing. Our goal is to introduce key data science concepts to genomic nurses who participate at any stage of the data science lifecycle, from research patient recruitment to data wrangling, preprocessing, and analysis to implementation in clinical practice to policy creation. We address three major components in this review: (1) fundamental terminology for the field of genomic nursing data science, (2) current genomic nursing data science research exemplars, and (3) the spectrum of genomic nursing data science roles as well as education pathways and training opportunities. Links to helpful resources are included throughout the article.

Scrutiny of Digital Video Watermarking and QR Codes

The economic activity on the internet and media require safeguard to enhance the sanctuary to the data. Digital watermarking is an information masking technique wherever Associate in Nursing data or message is cloaked within a symbol clear to the user. This research includes the discussion about the watermarking concepts, Barcodes and QR codes, and algorithms used for the watermarking emerging better robustness, data security and increasing embedding capability. Here we also discussed about the software’s used for watermarking.

PROCESSO DE DELIBERAÇÃO MORAL DOS ENFERMEIROS DE COMPETÊNCIA GERENCIAL E FISCALIZATÓRIA DOS CONSELHOS DE ENFERMAGEM

Objetivo: descrever o processo e os valores implicados na deliberação moral dos profissionais de competência gerencial e fiscais, considerando suas atribuições e os problemas éticos encontrados. Metodologia: estudo descritivo e exploratório, abordagem qualitativa, realizado durante o período de novembro 2013 a novembro de 2014, cujas informações foram coletadas por meio de questionário. Participaram da pesquisa 28 profissionais de competência gerencial e 113 profissionais de competência fiscalizatória dos departamentos de fiscalização do exercício profissional de enfermagem brasileira. Os dados foram organizados e analisados segundo a técnica de análise textual discursiva. Resultados: o itinerário proposto pelos participantes revela certa maturidade e conhecimento, constatado através das etapas eleitas. Conclusão: o estudo apontou que os trâmites do processo são fortemente vinculados a aspectos burocráticos e organizacionais. Convém ressaltar que os valores implicados no processo estão relacionados às dimensões ética, legal, subjetiva e profissional.Descritores: Regulação e Fiscalização em Saúde; Enfermagem; Deliberação.MORAL DELIBERATION PROCESS OF MANAGEMENT AND SUPERVISORY COMPETENCIES OF THE NURSING COUNCILS IN BRAZILObjective: describe the process and values involved in the moral deliberation of professionals with managerial and fiscal competencies, considering their responsibilities and ethical problems encountered. Methodology: Descriptive and exploratory study, qualitative approach, conducted from November 2013 to November 2014 and whose information was collected through questionnaire. There was a participation of 28 management professionals and 113 supervisory professionals from the professional inspection departments of the Brazilian nursing. Data were organized and analyzed according to the technique of discursive and textual analysis. Results: the itinerary proposed by the participants revealed certain maturity and knowledge, which was verified through the elected steps. Conclusion: the study pointed out that the process formalities are strongly linked to bureaucratic and organizational aspects. It is worth mentioning that the values involved in the process are related to ethical, legal, subjective and professional dimensions.Descriptors: Regulation and Supervision in Health; Nursing; Deliberation.PROCESO DE DELIBERACIÓN MORAL DE LOS PROFESIONALES CON COMPETENCIA GERENCIAL Y FISCALIZADORA DE LOS CONSEJOS DE ENFERMERÍA DEL BRASILObjetivo: describir el proceso y los valores implicados en la deliberación moral de los profesionales de competencia gerencial y fiscal, considerando sus atribuciones y los problemas éticos encontrados. Metodología: Estudio descriptivo y exploratorio, enfoque cualitativo, realizado durante el período de Noviembre del 2013 hasta Noviembre del 2014 y cuyas informaciones fueron obtenidas por medio de cuestionario. Participaron de la investigación 28 profesionales de competencia gerencial y 113 profesionales de competencia fiscalizadora de los departamentos de fiscalización del ejercicio profesional de la enfermería brasileña. Los datos fueron organizados y analizados según la técnica del análisis textual discursivo. Resultados: el itinerario propuesto por los participantes revela cierta madurez y conocimiento, lo que fue constatado a través de las etapas elegidas. Conclusión: el estudio determinó que los trámites del proceso están fuertemente vinculados a los aspectos burocráticos y organizacionales. Vale resaltar que los valores implicados en el proceso están relacionados con las dimensiones éticas, legales, subjetivas y profesionales.Descriptores: Regulación y Fiscalización en Salud; Enfermería; Deliberación.