Using interoperable nursing care data to improve outcomes for multiple traumas patients with Impaired Physical Mobility.

AIM(S): To demonstrate how interoperable nursing care data can be used by nurses to create a more holistic understanding of the healthcare needs of multiple traumas patients with Impaired Physical Mobility. By proposing and validating linkages for the nursing diagnosis of Impaired Physical Mobility in multiple trauma patients by mapping to the Nursing Outcomes Classification (NOC) and Nursing Interventions Classification (NIC) equivalent terms using free-text nursing documentation. DESIGN: A descriptive cross-sectional design, combining quantitative analysis of interoperable data sets and the Kappa's coefficient score with qualitative insights from cross-mapping methodology and nursing professionals' consensus. METHODS: Cross-mapping methodology was conducted in a Brazilian Level 1 Trauma Center using de-identified records of adult patients with a confirmed medical diagnosis of multiple traumas and Impaired Physical Mobility (a nursing diagnosis). The hospital nursing free-text records were mapped to NANDA-I, NIC, NOC and NNN linkages were identified. The data records were retrieved for admissions from September to October 2020 and involved medical and nursing records. Three expert nurses evaluated the cross-mapping and linkage results using a 4-point Likert-type scale and Kappa's coefficient. RESULTS: The de-identified records of 44 patients were evaluated and then were mapped to three NOCs related to nurses care planning: (0001) Endurance; (0204) Immobility Consequences: Physiological, and (0208) Mobility and 13 interventions and 32 interrelated activities: (6486) Environmental Management: Safety; (0840) Positioning; (3200) Aspiration Precautions; (1400) Pain Management; (0940) Traction/Immobilization Care; (3540) Pressure Ulcer Prevention; (3584) Skincare: Topical Treatment; (1100) Nutrition Management; (3660) Wound Care; (1804) Self-Care Assistance: Toileting; (1801) Self-Care Assistance: Bathing/Hygiene; (4130) Fluid Monitoring; and (4200) Intravenous Therapy. The final version of the constructed NNN Linkages identified 37 NOCs and 41 NICs. CONCLUSION: These valid NNN linkages for patients with multiple traumas can serve as a valuable resource that enables nurses, who face multiple time constraints, to make informed decisions efficiently. This approach of using evidence-based linkages like the one developed in this research holds high potential for improving patient's safety and outcomes. NO PATIENT OR PUBLIC CONTRIBUTION: In this study, there was no direct involvement of patients, service users, caregivers or public members in the design, conduct, analysis and interpretation of data or preparation of the manuscript. The study focused solely on analysing existing de-identified medical and nursing records to propose and validate linkages for nursing diagnoses.

Nurse and Physician Perceptions and Decision Making During Interdisciplinary Communication: Factors That Influence Communication Channel Selection.

Errors in decision making and communication play a key role in poor patient outcomes. Safe patient care requires effective decision making during interdisciplinary communication through communication channels. Research on factors that influence nurse and physician decision making during interdisciplinary communication is limited. Understanding influences on nurse and physician decision making during communication channel selection is needed to support effective communication and improved patient outcomes. The purpose of the study was to explore nurse and physician perceptions of and decision-making processes for selecting interruptive or noninterruptive interdisciplinary communication channels in medical-surgical and intermediate acute care settings. Twenty-six participants (10 RNs, 10 resident physicians, and six attending physicians) participated in semistructured interviews in two acute care metropolitan hospitals for this qualitative descriptive study. The Practice Primed Decision Model guided interview question development and early data analysis. Findings include a core category, Development of Trust in the Communication Process, supported by three main themes: (1) Understanding of Patient Status Drives Communication Decision Making; (2) Previous Interdisciplinary Communication Experience Guides Channel Selection; and (3) Perceived Usefulness Influences Communication Channel Selection. Findings from this study provide support for future design and research of communication channels within the EHR and clinical decision support systems.

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.

Improved readability and functions needed for mHealth apps targeting patients with heart failure: An app store review.

To maintain their quality of life and avoid hospitalization and early mortality, patients with heart failure must recognize and respond to symptoms of exacerbation. A promising method for engaging patients in their self-care is through mobile health applications (mHealth apps). However, for mHealth to have its greatest chance for improving patient outcomes, the app content must be readable, provide useful functions and be based in evidence. The study aimed to determine: (1) readability, (2) types of functions, and (3) linkage to authoritative sources of evidence for self-care focused mHealth apps targeting heart failure patients that are available in the Apple and Google Play Stores. We systematically searched for mHealth apps targeting patients with heart failure in the Apple and Google Play Stores and applied selection criteria. Readability of randomly selected informational paragraphs were determined using Flesch-Kincaid grade level test tool in Microsoft Word. Ten mHealth apps met our criteria. Only one had a reading grade level at or below the recommended 6th grade reading level (average 9.35). The most common functions were tracking, clinical data feedback, and non-data-based reminders and alerts. Only three had statements that clearly linked the mHealth app content to trustworthy, evidence-based sources. Only two had interoperability with the electronic health record and only one had a communication feature with clinicians. Future mHealth designs that are tailored to patients' literacy level and have advanced functions may hold greater potential for improving patient outcomes.

Required data elements for interprofessional rounds through the lens of multiple professions.

The lack of a proper system for ongoing open interprofessional communication among care providers increases miscommunications and medical errors. Seamless access to patient information is important for care providers to prevent miscommunication and improve patient safety. A shared understanding of the information needs of different care providers in an interprofessional team is lacking. Our purpose is to identify care providers' information needs from the perspective of different professions for communication, shared understanding about the patient, and decision-making. We conducted semi-structured interviews with 10 subject matter experts representing eight professions, including dentistry, dietetics, medicine, nursing, occupational therapy, pharmacy, physical therapy, and social work in a 465-bed academic hospital at a large urban Midwestern city. We used an in-house rounding tool presenting physicians' information needs and a hypothetical patient scenario to collect participants' feedback. Interview notes were coded using direct content analysis. We identified 22 additional essential data elements for an interprofessional rounding tool. We categorized those into six domains: discharge-related, social determinants of health, hospital safety, nutrition, interprofessional situation awareness, and patient history. A well-designed validated rounding tool that includes an interprofessional team of care providers' information needs could improve communication, care planning, and decision-making among them.

Effects of Individual Nurse and Hospital Characteristics on Patient Adverse Events and Quality of Care: A Multilevel Analysis.

PURPOSE: This study aimed to investigate effects of individual nurse and hospital characteristics on patient adverse events and quality of care using a multilevel approach. DESIGN: This is a secondary analysis of a combination of nurse survey data (N = 1,053 nurses) and facility data (N = 63 hospitals) in Canada. METHODS: Multilevel ordinal logistic regression was employed to examine effects of individual nurse and hospital characteristics on patient adverse events. Multilevel linear regressions were used to investigate effects of individual nurse and hospital characteristics on quality of care. FINDINGS: Organizational safety culture was associated with patient adverse events and quality of care. Controlling for effects of nurse and hospital characteristics, nurses in hospitals with a stronger safety culture were 64% less likely to report administration of wrong medication, time, or dose; 58% less likely to report patient falls with injury; and 60% less likely to report urinary tract infections; and were more likely to report higher levels of quality of care. Additionally, the effects of individual-level baccalaureate education and years of experience on quality of care differed across hospitals, and hospital-level nurse education interacted with individual-level baccalaureate education. CONCLUSIONS: This study makes significant contributions to existing knowledge regarding the positive effect of organizational safety culture on patient adverse events and quality of care. CLINICAL RELEVANCE: Healthcare organizations should strive to improve their safety culture by creating environments where healthcare providers trust each other, work collaboratively, and share accountability for patient safety and care quality.

The Iowa Health Data Resource (IHDR): an innovative framework for transforming the clinical health data ecosystem.

IMPORTANCE: This manuscript will be of interest to most Clinical and Translational Science Awards (CTSA) as they retool for the increasing emphasis on translational science from translational research. This effort is an extension of the EDW4R work that most CTSAs have done to deploy infrastructure and tools for researchers to access clinical data. OBJECTIVES: The Iowa Health Data Resource (IHDR) is a strategic investment made by the University of Iowa to improve access to real-world health data. The goals of IHDR are to improve the speed of translational health research, to boost interdisciplinary collaboration, and to improve literacy about health data. The first objective toward this larger goal was to address gaps in data access, data literacy, lack of computational environments for processing Personal Health Information (PHI) and the lack of processes and expertise for creating transformative datasets. METHODS: A three-pronged approach was taken to address the objective. The approach involves integration of an intercollegiate team of non-informatics faculty and staff, a data enclave for secure patient data analyses, and novel comprehensive datasets. RESULTS: To date, all five of the health science colleges (dentistry, medicine, nursing, pharmacy, and public health) have had at least one staff and one faculty member complete the two-month experiential learning curriculum. Over the first two years of this project, nine cohorts totaling 36 data liaisons have been trained, including 18 faculty and 18 staff. IHDR data enclave eliminated the need to duplicate computational infrastructure inside the hospital firewall which reduced infrastructure, hardware and human resource costs while leveraging the existing expertise embedded in the university research computing team. The creation of a process to develop and implement transformative datasets has resulted in the creation of seven domain specific datasets to date. CONCLUSION: The combination of people, process, and technology facilitates collaboration and interdisciplinary research in a secure environment using curated data sets. While other organizations have implemented individual components to address EDW4R operational demands, the IHDR combines multiple resources into a novel, comprehensive ecosystem IHDR enables scientists to use analysis tools with electronic patient data to accelerate time to science.

Expanding potential of radiofrequency nurse call systems to measure nursing time in patient rooms.

OBJECTIVE: The objective of this study was to determine the utility and feasibility of using data from a nurse call system equipped with radiofrequency identification data (RFID) to measure nursing time spent in patient rooms. BACKGROUND: Increasing the amount of time nurses spend with hospitalized patients has become a focus after several studies demonstrating that nurses spend most of their time in nondirect care activities rather than delivering patient care. Measurement of nursing time spent in direct care often involves labor-intensive time and motion studies, making frequent or continuous monitoring impractical. METHODS: Mixed methods were used for this descriptive study. We used 30 days of data from an RFID nurse call system collected on 1 unit in a community hospital to examine nurses time spent in patient rooms. Descriptive statistics were applied to calculate this percentage by role and shift. Data technologists were surveyed to assess how practical the access of data would be in a hospital setting for use in monitoring nursing time spent in patient rooms. RESULTS: The system captured 7393 staff hours. Of that time, 7% did not reflect actual patient care time, so these were eliminated from further analysis. The remaining 6880 hours represented 91% of expected worked time. RNs and nursing assistants spent 33% to 36% of their time in patient rooms, presumably providing direct care. CONCLUSIONS: Radiofrequency identification data technology was found to provide feasible and accurate means for capturing and evaluating nursing time spent in patient rooms. Depending on the outcomes per unit, leaders should work with staff to maximize patient care time.

FHIR-up! Advancing knowledge from clinical data through application of standardized nursing terminologies within HL7® FHIR®.

Health Level 7®'s (HL7) Fast Healthcare Interoperability Resources® (FHIR®) is leading new efforts to make data available to healthcare clinicians, administrators, and leaders. Standardized nursing terminologies were developed to enable nursing's voice and perspective to be visible within the healthcare data ecosystem. The use of these SNTs has been shown to improve care quality and outcomes, and to provide data for knowledge discovery. The role of SNTs in describing assessments and interventions and measuring outcomes is unique in health care, and synergistic with the purpose and goals of FHIR. FHIR acknowledges nursing as a discipline of interest and yet the use of SNTs within the FHIR ecosystem is rare. The purpose of this article is to describe FHIR, SNTs, and the potential for synergy in the use of SNTs with FHIR. Toward improving understanding how FHIR works to transport and store knowledge and how SNTs work to convey meaning, we provide a framework and examples of SNTs and their coding for use within FHIR solutions. Finally, we offer recommendations for the next steps to advance FHIR-SNT collaboration. Such collaboration will advance both nursing specifically and health care in general, and most importantly, improve population health.

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.

Future advancement of health care through standardized nursing terminologies: reflections from a Friends of the National Library of Medicine workshop honoring Virginia K. Saba.

OBJECTIVE: To honor the legacy of nursing informatics pioneer and visionary, Dr. Virginia Saba, the Friends of the National Library of Medicine convened a group of international experts to reflect on Dr. Saba's contributions to nursing standardized nursing terminologies. PROCESS: Experts led a day-and-a-half virtual update on nursing's sustained and rigorous efforts to develop and use valid, reliable, and computable standardized nursing terminologies over the past 5 decades. Over the course of the workshop, policymakers, industry leaders, and scholars discussed the successful use of standardized nursing terminologies, the potential for expanded use of these vetted tools to advance healthcare, and future needs and opportunities. In this article, we elaborate on this vision and key recommendations for continued and expanded adoption and use of standardized nursing terminologies across settings and systems with the goal of generating new knowledge that improves health. CONCLUSION: Much of the promise that the original creators of standardized nursing terminologies envisioned has been achieved. Secondary analysis of clinical data using these terminologies has repeatedly demonstrated the value of nursing and nursing's data. With increased and widespread adoption, these achievements can be replicated across settings and systems.

Using artificial intelligence to improve pain assessment and pain management: a scoping review.

CONTEXT: Over 20% of US adults report they experience pain on most days or every day. Uncontrolled pain has led to increased healthcare utilization, hospitalization, emergency visits, and financial burden. Recognizing, assessing, understanding, and treating pain using artificial intelligence (AI) approaches may improve patient outcomes and healthcare resource utilization. A comprehensive synthesis of the current use and outcomes of AI-based interventions focused on pain assessment and management will guide the development of future research. OBJECTIVES: This review aims to investigate the state of the research on AI-based interventions designed to improve pain assessment and management for adult patients. We also ascertain the actual outcomes of Al-based interventions for adult patients. METHODS: The electronic databases searched include Web of Science, CINAHL, PsycINFO, Cochrane CENTRAL, Scopus, IEEE Xplore, and ACM Digital Library. The search initially identified 6946 studies. After screening, 30 studies met the inclusion criteria. The Critical Appraisals Skills Programme was used to assess study quality. RESULTS: This review provides evidence that machine learning, data mining, and natural language processing were used to improve efficient pain recognition and pain assessment, analyze self-reported pain data, predict pain, and help clinicians and patients to manage chronic pain more effectively. CONCLUSIONS: Findings from this review suggest that using AI-based interventions has a positive effect on pain recognition, pain prediction, and pain self-management; however, most reports are only pilot studies. More pilot studies with physiological pain measures are required before these approaches are ready for large clinical trial.

Removing the roadblocks to promoting health equity: finding the social determinants of health addressed in standardized nursing classifications.

Providing 80% of healthcare worldwide, nurses focus on physiologic and psychosocial aspects of health, which incorporate social determinants of health (SDOH). Recognizing their important role in SDOH, nurse informatics scholars included standardized measurable terms that identify and treat issues with SDOH in their classification systems, which have been readily available for over 5 decades. In this Perspective, we assert these currently underutilized nursing classifications would add value to health outcomes and healthcare, and to the goal of decreasing disparities. To illustrate this, we mapped 3 rigorously developed and linked classifications: NANDA International (NANDA-I), Nursing Interventions Classification (NIC), and Nursing Outcomes Classification (NOC) called NNN (NANDA-I, NIC, NOC), to 5 Healthy People 2030 SDOH domains/objectives, revealing the comprehensiveness, usefulness, and value of these classifications. We found that all domains/objectives were addressed and NNN terms often mapped to multiple domains/objectives. Since SDOH, corresponding interventions and measurable outcomes are easily found in standardized nursing classifications (SNCs), more incorporation of SNCs into electronic health records should be occurring, and projects addressing SDOHs should integrate SNCs like NNN into their ongoing work.

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.

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.

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.

Electronic health record usability and workload changes over time for provider and nursing staff following transition to new EHR.

The ubiquity of EHRs in healthcare means that small EHR inefficiencies can have a major impact on clinician workload. We conducted a sequential explanatory mixed methods study to: 1) identify EHR-associated workload and usability effects for clinicians following an EHR change over time, 2) determine workload and usability differences for providers (MD and Advance Practice Nurses) versus nurses (RNs and MAs), 3) determine if usability predicts workload, 4) identify potential sources of EHR design flaws. Workload (NASA-Task Load Index) and usability (System Usability Scale) measures were administered pre, 6-8 month and 30-32 months post-implementation. We found significant increase in perceived workload post-implementation that persisted for 2.5 years (p < .001). The workload increase was associated with usability ratings, which in turn may relate to EHR interface design violations identified by a heuristic evaluation. Our findings suggest further innovation and attention to interface design flaws are needed to improve EHR usability and reduce clinician workload.