Nursing documentation is essential to communicate patient care delivery. This review explores available evidence on the contribution of nursing documentation toward quality care delivery during the COVID-19 pandemic. Nine articles were evaluated for at least one of the 6 factors of quality (eg, safe, timely, equitable, patient-centered, effective, and efficient). Analysis suggests that right-sizing documentation for optimal care quality requires continued efforts to reinforce the value and need of nursing documentation as a primary data source. Continued practice and research efforts are needed to reframe nursing documentation\'s essential role in benefiting a patient\'s current and future health care needs.

Nurses who provide the majority of hands-on care for hospitalized patients are disproportionately affected by the current state of electronic health records (EHRs), and little is known about their lived perception of EHR use. Using a mixed-methods research design, we conducted an in-depth analysis and synthesis of data from EHR usage log files, interviews, and surveys and assessed factors contributing to the nurse documentation burden in acute and critical at a large academic medical center. There remain substantial spaces where we can develop viable solutions for enhancing the usability of multi-component EHR systems.

This literature review explores the impact of Speech Recognition Technology (SRT) on nursing documentation within electronic health records (EHR). A search across PubMed, CINAHL, and Google Scholar identified 156 studies, with seven meeting the inclusion criteria. These studies investigated the impact of SRT on documentation time, accuracy, and user satisfaction. Findings suggest SRT, particularly when integrated with artificial intelligence can speed up documentation by up to 15%. However, challenges remain in its implementation in real-world clinical settings and existing EHR workflows. Future studies should focus on developing SRT systems that process conversational nursing assessments and integrate into current EHRs.

This study aimed to develop a mapping table that connects nursing notes with standard terminology, focusing on nurses\' concerns for ICU patients. After extracting nursing notes from a publicly accessible database, a research team, including a nursing informatics professor and researchers with ICU experience, developed a mapping table through a four-step process: initially reviewing literature on nurses\' concerns, then extracting nursing notes from MIMIC IV and filtering the duplicate notes, subsequently defining and coding these concerns, and finally mapping them according to the CCC. Of 11,430,637 unstructured nursing notes from MIMIC IV, 265 unique notes remained after deduplication, with 208 notes reflecting nurses\' concerns and categorized into 15 groups aligned with CCC. This mapping table will be a fundamental tool for predicting clinical deterioration in ICU patients by identifying important lexicons through natural language processing.

Amidst the current healthcare workforce crisis, nurses continue to experience burnout, with one contributor being the growing amount of required documentation and other electronic health record (EHR) tasks that must be completed. This study aims to identify ways in which nurses can be better supported through consideration for the burden that EHR systems may present due to increasing documentation requirements and areas of inefficient use. This study leverages nursing engagement to ensure the needs of nurses are identified and EHR efficiency is improved. Practical strategies and EHR system improvements will be proposed based on the recommendations and guidance of nursing staff.

This study investigates how to reduce nurses\' repetitive electronic nursing record tasks. We applied generative AI by learning nursing record data practiced with virtual patient data. We aim to evaluate generative AI\'s usefulness, usability, and availability when applied to nursing record creation tasks. The nursing record data collected through the electronic nursing record system for nursing students without privacy issues is in the form of NANDA, FocusDAR, SOAPIE, and narrative records. We trained 50,000 nursing record data and upgraded the performance through generative AI and fine-tuning. A separate API was used to connect with the practice electronic nursing record system, and 40 experienced nurses from a university hospital conducted tests. The electronic nursing record, through generative AI, is expected to contribute to easing the workload of nurses.

This study evaluates the impact of Clinical Decision Support System (CDSS) integration into the Nursing Information System 2.0 on nursing records and nurse satisfaction. Longitudinal data collection employs questionnaires and nursing records audits. Findings show improved electronic signature integration and nursing problem identification, benefiting real-time patient information access and record completeness. Younger, less experienced, highly educated nurses exhibit higher CDSS usage and acceptance. Overall, 80.2% agreement rate confirms CDSS\'s positive impact, highlighting the importance of user effectiveness evaluation in system implementation for nursing innovation.

This study aimed to develop ICU mortality prediction models using a conceptual framework, focusing on nurses\' concerns reflected in nursing records from the MIMIC IV database. We included 46,693 first-time ICU admissions of adults over 18 years with a minimum 24-hour stay, excluding those receiving hospice or palliative care. Predictors included demographics, clinical characteristics, and nursing documentation frequencies related to nurses\' concerns. Four models were trained with 10-fold cross-validation after adjusting class imbalance. The random forest (RF) model was identified as the best-performing, with key predictors of mortality in this model being the frequency of vital signs, the frequency of nursing note documentation, and the frequency of monitoring-related nursing notes. This suggests that predictive models using nursing records, which reflect nurses\' concerns as represented by the frequency of nursing documentation, may be integrated into clinical decision support tools, potentially enhancing patient outcomes in ICUs.

Documentation burden within the United States has grown to unprecedented proportions. Poor usability of the electronic health record has been identified as one of the root causes of documentation burden. By using a structured review process, the nursing informatics team at Northwestern Medicine Healthcare identified opportunities for improved usability. Solutions were generated and proposed to a team of nurse experts for review and approval. The approved solutions were implemented into the electronic health record through this efficient and agile process. Project RENEW impacted documentation burden by reducing unnecessary nursing tasks, improving usability of flowsheets, and reducing clicks to complete documentation.

In response to findings indicating poor standardisation and quality in nursing documentation, NHS Wales embarked on a transformative journey with the National Electronic Nursing Documentation Programme in 2014. Evolving into the Welsh Nursing Care Record (WNCR) by 2019, this initiative sought to streamline practices and enhance accuracy, compliance, and efficiency through a standardised digital platform. The case study explores the comprehensive project design, emphasising evidence-based practices, governance processes and the introduction of National Nursing Informatics roles. Accomplished from April 2021 to September 2023, the WNCR implementation achieved a 79% roll out across eligible wards, marked by strategic investments, robust training, and phased deployment. Evaluations to date show positive impacts on key performance indicators, exemplified by a 9-minute time saving per patient. Lessons learned noted the significance of user engagement, cultural transformation, and ongoing staff development, paving the way for future strategies including nationwide implementation, benefits realisation, and data visualisation initiatives.