An example of leveraging AI for documentation: ChatGPT-generated nursing care plan for an older adult with lung cancer.

OBJECTIVE: Our article demonstrates the effectiveness of using a validated framework to create a ChatGPT prompt that generates valid nursing care plan suggestions for one hypothetical older patient with lung cancer. METHOD: This study describes the methodology for creating ChatGPT prompts that generate consistent care plan suggestions and its application for a lung cancer case scenario. After entering a nursing assessment of the patient's condition into ChatGPT, we asked it to generate care plan suggestions. Subsequently, we assessed the quality of the care plans produced by ChatGPT. RESULTS: While not all the suggested care plan terms (11 out of 16) utilized standardized nursing terminology, the ChatGPT-generated care plan closely matched the gold standard in scope and nature, correctly prioritizing oxygenation and ventilation needs. CONCLUSION: Using a validated framework prompt to generate nursing care plan suggestions with ChatGPT demonstrates its potential value as a decision support tool for optimizing cancer care documentation.

Standardizing nursing data extracted from electronic health records for integration into a statewide clinical data research network.

BACKGROUND: Care plans documented by nurses in electronic health records (EHR) are a rich source of data to generate knowledge and measure the impact of nursing care. Unfortunately, there is a lack of integration of these data in clinical data research networks (CDRN) data trusts, due in large part to nursing care being documented with local vocabulary, resulting in non-standardized data. The absence of high-quality nursing care plan data in data trusts limits the investigation of interdisciplinary care aimed at improving patient outcomes. OBJECTIVE: To map local nursing care plan terms for patients' problems and goals in the EHR of one large health system to the standardized nursing terminologies (SNTs), NANDA International (NANDA-I), and Nursing Outcomes Classification (NOC). METHODS: We extracted local problems and goals used by nurses to document care plans from two hospitals. After removing duplicates, the terms were independently mapped to NANDA-I and NOC by five mappers. Four nurses who regularly use the local vocabulary validated the mapping. RESULTS: 83% of local problem terms were mapped to NANDA-I labels and 93% of local goal terms were mapped to NOC labels. The nurses agreed with 95% of the mapping. Local terms not mapped to labels were mapped to the domains or classes of the respective terminologies. CONCLUSION: Mapping local vocabularies used by nurses in EHRs to SNTs is a foundational step to making interoperable nursing data available for research and other secondary purposes in large data trusts. This study is the first phase of a larger project building, for the first time, a pipeline to standardize, harmonize, and integrate nursing care plan data from multiple Florida hospitals into the statewide CDRN OneFlorida+ Clinical Research Network data trust.

The impact of spiritual care delivered by nurses on patients' comfort: A propensity score matched cohort utilizing electronic health record data.

BACKGROUND: Spiritual care has been associated with better health outcomes. Despite increasing evidence of the benefits of spiritual care for older patients coping with illness and aggressive treatment, the role of spirituality is not well understood and implemented. Nurses, as frontline holistic healthcare providers, are in a position to address patients' spiritual needs and support them in finding meaning in life. This study aimed to identify spiritual care by analyzing nursing data and to compare the psychological and physical comfort between older chronically ill patients who received spiritual care versus those who did not receive spiritual care. MATERIAL AND METHODS: A propensity score matched cohort utilizing nursing care plan data was used to construct balanced groups based on patient characteristics at admission. 45 older patients (≥65 years) with chronic illnesses received spiritual care with measured psychological or physical comfort and 90 matched controls. To ensure the robustness of our results, two sensitivity analyses were performed. Group comparisons were performed to assess the average treatment effect of spiritual care on psychological and physical comfort outcomes. RESULTS: The mean psychological comfort was 4.3 (SD = 0.5) for spiritual care receivers and 3.9 (SD = 0.9) for non-receivers. Regression analysis showed that spiritual care was associated with better psychological comfort (estimate = 0.479, std. error = 0.225, p = 0.041). While its effect on physical comfort was not statistically significant (estimate = -0.265, std. error = 0.234, p = 0.261). This study provides suggestive evidence of the positive impact of nurses' spiritual care in improving psychological comfort for older patients with chronic illnesses. CONCLUSION: Using interoperable nursing data, our findings suggest that spiritual care improves psychological comfort in older patients facing illness. This finding suggests that nurses may integrate spiritual care into their usual care to support patients experiencing distress.

The relationship between electronic health records user interface features and data quality of patient clinical information: an integrative review.

OBJECTIVES: Electronic health records (EHRs) user interfaces (UI) designed for data entry can potentially impact the quality of patient information captured in the EHRs. This review identified and synthesized the literature evidence about the relationship of UI features in EHRs on data quality (DQ). MATERIALS AND METHODS: We performed an integrative review of research studies by conducting a structured search in 5 databases completed on October 10, 2022. We applied Whittemore & Knafl's methodology to identify literature, extract, and synthesize information, iteratively. We adapted Kmet et al appraisal tool for the quality assessment of the evidence. The research protocol was registered with PROSPERO (CRD42020203998). RESULTS: Eleven studies met the inclusion criteria. The relationship between 1 or more UI features and 1 or more DQ indicators was examined. UI features were classified into 4 categories: 3 types of data capture aids, and other methods of DQ assessment at the UI. The Weiskopf et al measures were used to assess DQ: completeness (n = 10), correctness (n = 10), and currency (n = 3). UI features such as mandatory fields, templates, and contextual autocomplete improved completeness or correctness or both. Measures of currency were scarce. DISCUSSION: The paucity of studies on UI features and DQ underscored the limited knowledge in this important area. The UI features examined had both positive and negative effects on DQ. Standardization of data entry and further development of automated algorithmic aids, including adaptive UIs, have great promise for improving DQ. Further research is essential to ensure data captured in our electronic systems are high quality and valid for use in clinical decision-making and other secondary analyses.

Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review.

PURPOSE: The purpose of this systematic review was to assess risk of bias in existing prognostic models of hospital-induced delirium for medical-surgical units. METHODS: APA PsycInfo, CINAHL, MEDLINE, and Web of Science Core Collection were searched on July 8, 2022, to identify original studies which developed and validated prognostic models of hospital-induced delirium for adult patients who were hospitalized in medical-surgical units. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was used for data extraction. The Prediction Model Risk of Bias Assessment Tool was used to assess risk of bias. Risk of bias was assessed across four domains: participants, predictors, outcome, and analysis. RESULTS: Thirteen studies were included in the qualitative synthesis, including ten model development and validation studies and three model validation only studies. The methods in all of the studies were rated to be at high overall risk of bias. The methods of statistical analysis were the greatest source of bias. External validity of models in the included studies was tested at low levels of transportability. CONCLUSIONS: Our findings highlight the ongoing scientific challenge of developing a valid prognostic model of hospital-induced delirium for medical-surgical units to tailor preventive interventions to patients who are at high risk of this iatrogenic condition. With limited knowledge about generalizable prognosis of hospital-induced delirium in medical-surgical units, existing prognostic models should be used with caution when creating clinical practice policies. Future research protocols must include robust study designs which take into account the perspectives of clinicians to identify and validate risk factors of hospital-induced delirium for accurate and generalizable prognosis in medical-surgical units.

Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses' Graph Literacy: National, Web-Based Randomized Controlled Trial.

BACKGROUND: The proliferation of health care data in electronic health records (EHRs) is fueling the need for clinical decision support (CDS) that ensures accuracy and reduces cognitive processing and documentation burden. The CDS format can play a key role in achieving the desired outcomes. Building on our laboratory-based pilot study with 60 registered nurses (RNs) from 1 Midwest US metropolitan area indicating the importance of graph literacy (GL), we conducted a fully powered, innovative, national, and web-based randomized controlled trial with 203 RNs. OBJECTIVE: This study aimed to compare care planning time (CPT) and the adoption of evidence-based CDS recommendations by RNs randomly assigned to 1 of 4 CDS format groups: text only (TO), text+table (TT), text+graph (TG), and tailored (based on the RN's GL score). We hypothesized that the tailored CDS group will have faster CPT (primary) and higher adoption rates (secondary) than the 3 nontailored CDS groups. METHODS: Eligible RNs employed in an adult hospital unit within the past 2 years were recruited randomly from 10 State Board of Nursing lists representing the 5 regions of the United States (Northeast, Southeast, Midwest, Southwest, and West) to participate in a randomized controlled trial. RNs were randomly assigned to 1 of 4 CDS format groups-TO, TT, TG, and tailored (based on the RN's GL score)-and interacted with the intervention on their PCs. Regression analysis was performed to estimate the effect of tailoring and the association between CPT and RN characteristics. RESULTS: The differences between the tailored (n=46) and nontailored (TO, n=55; TT, n=54; and TG, n=48) CDS groups were not significant for either the CPT or the CDS adoption rate. RNs with low GL had longer CPT interacting with the TG CDS format than the TO CDS format (P=.01). The CPT in the TG CDS format was associated with age (P=.02), GL (P=.02), and comfort with EHRs (P=.047). Comfort with EHRs was also associated with CPT in the TT CDS format (P<.001). CONCLUSIONS: Although tailoring based on GL did not improve CPT or adoption, the study reinforced previous pilot findings that low GL is associated with longer CPT when graphs were included in care planning CDS. Higher GL, younger age, and comfort with EHRs were associated with shorter CPT. These findings are robust based on our new innovative testing strategy in which a diverse national sample of RN participants (randomly derived from 10 State Board of Nursing lists) interacted on the web with the intervention on their PCs. Future studies applying our innovative methodology are recommended to cost-effectively enhance the understanding of how the RN's GL, combined with additional factors, can inform the development of efficient CDS for care planning and other EHR components before use in practice.

Nurses' preferences for the format of care planning clinical decision support coded with standardized nursing languages.

Current electronic health records (EHRs) are often ineffective in identifying patient priorities and care needs requiring nurses to search a large volume of text to find clinically meaningful information. Our study, part of a larger randomized controlled trial testing nursing care planning clinical decision support coded in standardized nursing languages, focuses on identifying format preferences after random assignment and interaction to 1 of 3 formats (text only, text+table, text+graph). Being assigned to the text+graph significantly increased the preference for graph (P = .02) relative to other groups. Being assigned to the text only (P = .06) and text+table (P = .35) was not significantly associated with preference for their assigned formats. Additionally, the preference for graphs was not significantly associated with understanding graph content (P = .19). Further studies are needed to enhance our understanding of how format preferences influence the use and processing of displayed information.

Influence of Sociodemographic and Occupational Factors on Safety Culture in Neonatal Intensive Care in Brazil.

BACKGROUND: Patient safety culture is influenced by factors such as professional category, experience, and age. Understanding these factors can inform initiatives to improve safety. PURPOSE: To evaluate the relationship between sociodemographic and occupational characteristics on health professionals' perception of patient safety culture. METHODS: A cross-sectional study involving 514 health care professionals from Brazilian neonatal intensive care units was conducted using the Hospital Survey on Patient Safety Culture. RESULTS: Several sociodemographic and occupational characteristics were associated with higher perceptions of safety culture, including older age and having a higher level of education. CONCLUSION: Sociodemographic and occupational factors may influence the safety culture in neonatal intensive care units and should be considered when developing and implementing strategies to improve safety.

Assessing the Usability of a Clinical Decision Support System: Heuristic Evaluation.

BACKGROUND: Poor usability is a primary cause of unintended consequences related to the use of electronic health record (EHR) systems, which negatively impacts patient safety. Due to the cost and time needed to carry out iterative evaluations, many EHR components, such as clinical decision support systems (CDSSs), have not undergone rigorous usability testing prior to their deployment in clinical practice. Usability testing in the predeployment phase is crucial to eliminating usability issues and preventing costly fixes that will be needed if these issues are found after the system's implementation. OBJECTIVE: This study presents an example application of a systematic evaluation method that uses clinician experts with human-computer interaction (HCI) expertise to evaluate the usability of an electronic clinical decision support (CDS) intervention prior to its deployment in a randomized controlled trial. METHODS: We invited 6 HCI experts to participate in a heuristic evaluation of our CDS intervention. Each expert was asked to independently explore the intervention at least twice. After completing the assigned tasks using patient scenarios, each expert completed a heuristic evaluation checklist developed by Bright et al based on Nielsen's 10 heuristics. The experts also rated the overall severity of each identified heuristic violation on a scale of 0 to 4, where 0 indicates no problems and 4 indicates a usability catastrophe. Data from the experts' coded comments were synthesized, and the severity of each identified usability heuristic was analyzed. RESULTS: The 6 HCI experts included professionals from the fields of nursing (n=4), pharmaceutical science (n=1), and systems engineering (n=1). The mean overall severity scores of the identified heuristic violations ranged from 0.66 (flexibility and efficiency of use) to 2.00 (user control and freedom and error prevention), in which scores closer to 0 indicate a more usable system. The heuristic principle user control and freedom was identified as the most in need of refinement and, particularly by nonnursing HCI experts, considered as having major usability problems. In response to the heuristic match between system and the real world, the experts pointed to the reversed direction of our system's pain scale scores (1=severe pain) compared to those commonly used in clinical practice (typically 1=mild pain); although this was identified as a minor usability problem, its refinement was repeatedly emphasized by nursing HCI experts. CONCLUSIONS: Our heuristic evaluation process is simple and systematic and can be used at multiple stages of system development to reduce the time and cost needed to establish the usability of a system before its widespread implementation. Furthermore, heuristic evaluations can help organizations develop transparent reporting protocols for usability, as required by Title IV of the 21st Century Cures Act. Testing of EHRs and CDSSs by clinicians with HCI expertise in heuristic evaluation processes has the potential to reduce the frequency of testing while increasing its quality, which may reduce clinicians' cognitive workload and errors and enhance the adoption of EHRs and CDSSs.

Spiritual Interventions Delivered by Nurses to Address Patients' Needs in Hospitals or Long-Term Care Facilities: A Systematic Review.

Introduction: Despite increasing evidence of the benefits of spiritual care and nurses' efforts to incorporate spiritual interventions into palliative care and clinical practice, the role of spirituality is not well understood and implemented. There are divergent meanings and practices within and across countries. Understanding the delivery of spiritual interventions may lead to improved patient outcomes. Aim: We conducted a systematic review to characterize spiritual interventions delivered by nurses and targeted outcomes for patients in hospitals or assisted long-term care facilities. Methodology: The systematic review was developed following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, and a quality assessment was performed. Our protocol was registered on PROSPERO (Registration No. CRD42020197325). The CINAHL, Embase, PsycINFO, and PubMed databases were searched from inception to June 2020. Results: We screened a total of 1005 abstracts and identified 16 experimental and quasi-experimental studies of spiritual interventions delivered by nurses to individuals receiving palliative care or targeted at chronic conditions, such as advanced cancer diseases. Ten studies examined existential interventions (e.g., spiritual history, spiritual pain assessment, touch, and psychospiritual interventions), two examined religious interventions (e.g., prayer), and four investigated mixed interventions (e.g., active listening, presence, and connectedness with the sacred, nature, and art). Patient outcomes associated with the delivery of spiritual interventions included spiritual well-being, anxiety, and depression. Conclusion: Spiritual interventions varied with the organizational culture of institutions, patients' beliefs, and target outcomes. Studies showed that spiritual interventions are associated with improved psychological and spiritual patient outcomes. The studies' different methodological approaches and the lack of detail made it challenging to compare, replicate, and validate the applicability and circumstances under which the interventions are effective. Further studies utilizing rigorous methods with operationalized definitions of spiritual nursing care are recommended.

NANDA-I, NOC, and NIC linkages to SARS-CoV-2 (COVID-19): Part 3. Family response.

PURPOSE: To provide guidance to nurses caring for families with COVID-19, we developed linkages using interoperable standardized nursing terminologies: NANDA International (NANDA-I) nursing diagnoses, Nursing Interventions Classification (NIC), and Nursing Outcomes Classification (NOC). In addition, we wanted to identify gaps in the terminologies and potential new nursing diagnoses, outcomes, and interventions for future development related to nurse roles in family care during a pandemic. METHODS: Using a consensus process, seven nurse experts created the linkages focused on families during the COVID-19 pandemic using the following steps: (1) creating an initial list of potential nursing diagnoses, (2) selecting and categorizing outcomes that aligned with all components of each nursing diagnosis selected, and (3) identifying relevant nursing interventions. FINDINGS: We identified a total of seven NANDA-I nursing diagnoses as the basis for the linkage work. These are distributed in three NANDA-I Domains and based in the psychosocial dimension of the Nursing Care in Response to Pandemics model. Eighty-nine different NOC outcomes were identified to guide care based on the nursing diagnoses, and 54 different NIC interventions were suggested as possible interventions. Fifteen new proposed concepts were identified for future development across the three classifications. CONCLUSIONS: The linkages of nursing diagnoses, outcomes, and interventions provide a guide to enhance nursing practice and care documentation that could quantify the impact of nursing care to patient outcomes for families at risk for or infected by COVID-19. IMPLICATIONS FOR NURSING PRACTICE: NANDA-I, NOC, and NIC linkages identified in this paper provide resources to support clinical decisions and guide critical thinking for nurses encountering care needs of families with COVID-19. Documentation of these linkages provides data that can create new knowledge to enhance the care of families impacted by COVID-19.

Nurses' Perceptions of Recommended Fall Prevention Strategies: A Rapid Review.

BACKGROUND: Limited studies have synthesized evidence on nurses' perceptions of recommended fall prevention strategies and potential differences between those and the practiced strategies. PURPOSE: To synthesize evidence about nurses' perceptions of recommended fall prevention strategies for hospitalized adults. METHODS: Using PubMed, 50 records underwent abstract and full-text screening, and 10 studies were retained. Narrative synthesis was conducted to identify common themes across studies. Quality assessment was not performed. RESULTS: Nurses are aware of effective fall prevention strategies but identified unit-level barriers and facilitators to implementing these in their practice. Unit culture and policies, educational offerings, nursing interventions, and style of communication and collaboration were seen to influence fall prevention. CONCLUSIONS: Nurses recognize falls as a multifactorial issue suggesting that prevention efforts be tailored to the unit and involve all employees. We recommend that future research emphasize identifying and understanding the combination of factors that produce successful unit-level fall prevention strategies.

Use of machine learning to transform complex standardized nursing care plan data into meaningful research variables: a palliative care exemplar.

The aim of this article was to describe a novel methodology for transforming complex nursing care plan data into meaningful variables to assess the impact of nursing care. We extracted standardized care plan data for older adults from the electronic health records of 4 hospitals. We created a palliative care framework with 8 categories. A subset of the data was manually classified under the framework, which was then used to train random forest machine learning algorithms that performed automated classification. Two expert raters achieved a 78% agreement rate. Random forest classifiers trained using the expert consensus achieved accuracy (agreement with consensus) between 77% and 89%. The best classifier was utilized for the automated classification of the remaining data. Utilizing machine learning reduces the cost of transforming raw data into representative constructs that can be used in research and practice to understand the essence of nursing specialty care, such as palliative care.

Nursing Care for Hospitalized Older Adults With and Without Cognitive Impairment.

BACKGROUND: The presence of cognitive impairment (CI) among hospitalized older adults (aged 85 years and older) could interfere with the identification and treatment of other important symptoms experienced by these patients. Little is known, however, about the nursing care provided to this group. Contrasting the nursing care provided to patients with and without CI may reveal important insights about symptom treatment in the CI population. OBJECTIVE: The aim of this study was to examine the relationship of CI to nursing care provided and length of stay for hospitalized older adults using standardized nursing data retrieved from electronic health records. METHODS: We conducted a comparative secondary data analysis. A data set of standardized nursing plan of care data retrieved from electronic health record data of nine units at four hospitals was analyzed. The plan of care data for this study were previously transformed into one of eight categories (family, well-being, mental comfort, physical comfort, mental, safety, functional, and physiological care). Fisher exact tests were used to compare the differences in the nursing care for hospitalized older adults with and without CI. Mixed-effects models were used to examine associations of patient's cognitive status and nursing care, and cognitive status and length of stay. RESULTS: We identified 4,354 unique patients; 746 (17%) had CI. We observed that older adults with CI were less likely to receive physical comfort care than those without CI for seven of nine units. Older adults' cognitive status was associated with the delivery of mental comfort care. In addition, a worsening in cognitive status was associated with an increase in length of stay for older adults with CI. DISCUSSION: Older adults with CI appeared to be undertreated for symptoms of pain when compared to those without CI across units. There is a need for further research to improve symptom recognition and management for this population. The presence of CI was associated with variation in nursing care provided and length of stay. Future studies that include the analysis of nursing data merged with elements stored in the electronic health record representing the contributions of other health professions are expected to provide additional insights into this gap.

Towards implementing SNOMED CT in nursing practice: A scoping review.

BACKGROUND: Currently, it is rare for nursing data to be available in data repositories due to the quality of nursing data collected in clinical practice. To improve the quality of nursing data, the American Nurses Association recommends the use of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) for coding nursing problems, interventions, and observations in electronic health records. OBJECTIVE: To determine "what is known about the use of SNOMED terminology (Pre-SNOMED CT and SNOMED CT) in nursing". METHODS: We searched four databases and two search engines. We identified 29 articles for review. A modified version of System Development Life Cycle (SDLC), and Mapping Evaluation Assessment (MEA), created by the authors were used for quality assessment. RESULTS: All 29 studies mapped standardized (n = 19) or local nursing terms (n = 10) to the SNOMED terminology. MEA scores ranged from 2-8 (range 0-11) with 25 receiving scores from 5-8. On the modified SDLC (range 0-5), all studies exhibited activities of stage 0 (pre-application integration), with two studies describing integration and preliminary testing of SNOMED CT coded nursing content in applications (stage 2). CONCLUSION: Though efforts are underway to ensure adequate coverage of nursing in SNOMED CT, there were no studies indicating use in nursing practice. The authors offer recommendations for achieving the widespread collection of interoperable SNOMED CT coded nursing data in clinical applications to evaluate nursing's impact on patient outcomes. These include creating a clear professional vision and path to our data goals that builds on sound rationale and evidence, abundant stakeholder engagement, and sufficient resources.

Human Factors Associated with Continuous Glucose Monitor Use in Patients with Diabetes: A Systematic Review.

Consistent continuous glucose monitor (CGM) use is associated with substantial improvements in glycemic control, yet the uptake and continued use of these technologies remains low. This systematic review aims to identify and summarize the state of science on human factors and their association with CGM use to inform training methods and best practices that support adherence to CGM use and automated insulin delivery systems. A literature search was conducted in PubMed, CINAHL, The Cochrane Library, and PsychInfo databases using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify studies that reported psychological human factors related to CGM or sensor-augmented pump use in patients with type 1 diabetes. In total, 389 records were identified through our database search and 26 studies published between 2010 and 2017 were included. Articles underwent quality appraisal using the Effective Public Health Practice Project Quality Assessment Tool and were categorized according to study outcomes. Identified human factors with a potential association with CGM use were treatment satisfaction, quality of life, emotional distress, and self-efficacy. Eight patient-reported barriers to CGM use were identified as a subcomponent of satisfaction. To date, studies of human factors associated with CGM use generally lack standardized measures and sufficient methodological rigor necessary to establish causation. A more robust understanding of how identified human factors influence CGM use is necessary. Future studies should test interventions that target human factors to improve consistency of use and establish best practices for enhancing patients' experience and acceptance of these technologies, especially within adolescents and young adults.

Secondary use of standardized nursing care data for advancing nursing science and practice: a systematic review.

OBJECTIVE: The study sought to present the findings of a systematic review of studies involving secondary analyses of data coded with standardized nursing terminologies (SNTs) retrieved from electronic health records (EHRs). MATERIALS AND METHODS: We identified studies that performed secondary analysis of SNT-coded nursing EHR data from PubMed, CINAHL, and Google Scholar. We screened 2570 unique records and identified 44 articles of interest. We extracted research questions, nursing terminologies, sample characteristics, variables, and statistical techniques used from these articles. An adapted STROBE (Strengthening The Reporting of OBservational Studies in Epidemiology) Statement checklist for observational studies was used for reproducibility assessment. RESULTS: Forty-four articles were identified. Their study foci were grouped into 3 categories: (1) potential uses of SNT-coded nursing data or challenges associated with this type of data (feasibility of standardizing nursing data), (2) analysis of SNT-coded nursing data to describe the characteristics of nursing care (characterization of nursing care), and (3) analysis of SNT-coded nursing data to understand the impact or effectiveness of nursing care (impact of nursing care). The analytical techniques varied including bivariate analysis, data mining, and predictive modeling. DISCUSSION: SNT-coded nursing data extracted from EHRs is useful in characterizing nursing practice and offers the potential for demonstrating its impact on patient outcomes. CONCLUSIONS: Our study provides evidence of the value of SNT-coded nursing data in EHRs. Future studies are needed to identify additional useful methods of analyzing SNT-coded nursing data and to combine nursing data with other data elements in EHRs to fully characterize the patient's health care experience.

The Use of Simulation to Teach Nursing Students and Clinicians Palliative Care and End-of-Life Communication: A Systematic Review.

OBJECTIVES: To present the findings of a systematic review on the use of simulation-based learning experiences (SBLEs) to teach communication skills to nursing students and clinicians who provide palliative and end-of-life care to patients and their families. BACKGROUND: Palliative care communication skills are fundamental to providing holistic patient care. Since nurses have the greatest amount of direct exposure to patients, building such communication competencies is essential. However, exposure to patients and families receiving palliative and end-of-life care is often limited, resulting in few opportunities to learn these skills in the clinical setting. Simulation-based learning experiences can be used to supplement didactic teaching and clinical experiences to build the requisite communication skills. METHODS: Searches of CINAHL, MEDLINE, PsychINFO, ERIC, and Web of Science electronic databases and Grey Literature returned 442 unique records. Thirty articles met the established criteria, including the SBLE must contain a nursing role. RESULTS: Simulation-based learning experience are being used to teach palliative and end-of-life communication skills to nursing students and clinicians. Lack of standardization, poor evaluation methods, and limited exposure to the entire interprofessional team makes it difficult to identify and disseminate validated best practices. CONCLUSION: While the need for further research is acknowledged, we recommend this evidence be augmented by training programs that utilize SBLEs through (1) applying standards, (2) clearly specifying goals and objectives, (3) integrating externally validated scenarios, and (4) employing rigorous evaluation methods and measures that link the SBLE to the training objectives and desired clinician practice behaviors and patient outcomes.

A Shovel-Ready Solution to Fill the Nursing Data Gap in the Interdisciplinary Clinical Picture.

PURPOSE: To critically evaluate 2014 American Academy of Nursing (AAN) call-to-action plan for generating interoperable nursing data. DATA SOURCES: Healthcare literature. DATA SYNTHESIS: AAN's plan will not generate the nursing data needed to participate in big data science initiatives in the short term because Logical Observation Identifiers Names and Codes and Systematized Nomenclature of Medicine - Clinical Terms are not yet ripe for generating interoperable data. Well-tested viable alternatives exist. CONCLUSIONS: Authors present recommendations for revisions to AAN's plan and an evidence-based alternative to generating interoperable nursing data in the near term. These revisions can ultimately lead to the proposed terminology goals of the AAN's plan in the long term.

Evidence of Progress in Making Nursing Practice Visible Using Standardized Nursing Data: a Systematic Review.

Nursing care documentation in electronic health records (EHRs) with standardized nursing terminologies (SNTs) can facilitate nursing's participation in big data science that involves combining and analyzing multiple sources of data. Before merging SNTs data with other sources, it is important to understand how such data are being used and analyzed to support nursing practice. The main purpose of this systematic review was to identify studies using SNTs data, their aims and analytical methods. A two-phase systematic process resulted in inclusion and review of 35 publications. Aims of the studies ranged from describing most popular nursing diagnoses, outcomes, and interventions on a unit to predicting outcomes using multi-site data. Analytical techniques varied as well and included descriptive statistics, correlations, data mining, and predictive modeling. The review underscored the value of developing a deep understanding of the meaning and potential impact of nursing variables before merging with other sources of data.