Surge Planning and Implementation: A Required Competency for Today's Nurse Leaders.

The ability to respond effectively and efficiently during times of crisis, including a pandemic, has emerged as a competency for nurse leaders. This article describes one institution's experience using the American Organization of Nurse Leaders Competencies for Nurse Executives in operationalizing the concept of surge capacity.

COVID-19 and Nurse-Sensitive Indicators: Using Performance Improvement Teams to Address Quality Indicators During a Pandemic.

BACKGROUND: Nurse-sensitive quality indicators have historically been used as a metric of nursing care quality in health care organizations. PROBLEM: At our academic medical center, critically ill COVID-19 patients led to a dramatic change in the organizational standard of care resulting in an increase in nurse-sensitive health care-associated infections. APPROACH: Nursing performance improvement teams provided the structure for development of innovative strategies implemented in real time by our frontline clinicians to address the quality and safety issues found with these elevated health care-associated infections. OUTCOMES: A new COVID-19 CLABSI (central line-associated bloodstream infection) Tip Sheet and a Prone Positioning Kit for HAPI Prevention are strategies developed to address quality of care issues experienced with the COVID-19 patients. CONCLUSIONS: Deployment of these innovative practice strategies has led to a decline in health care-associated infections and instituted a new care standard for the COVID-19 patients.

A short report on an interprofessional mobilizer team: innovation and impact during the COVID-19 pandemic.

The response to a pandemic crisis requires strong preparedness and an action plan that is well defined yet flexible enough to address the uncertainties that accompany an infectious disease outbreak. Interprofessional collaboration is an integral component when implementing a robust and comprehensive response to such a crisis. As the needs of our academic medical center evolved during the COVID-19 pandemic, the COVID-19 Mobilizer Team used an interprofessional approach to respond to the diverse and complex needs of the organization. Team members included employees deployed from diverse departments such as Physical and Occupational Therapy, Nursing Education, Hospital Operations, and Advance Practice Providers. The team's function transitioned from ensuring compliance with infection control policy and procedure and use of personal protective equipment to ensuring a two way channel of communication between front line staff and the Hospital Incident Command System (HICS) concerning testing and isolation procedures, supplies, visitor restrictions, and staff wellness issues. The Mobilizer Team members became integral contributors to the HICS and provided members of our staff outside of the COVID-19 care units an opportunity to partner with colleagues from professions they may have never worked with and the chance to contribute to the COVID-19 pandemic response.

Toward Meaningful Care Plan Clinical Decision Support: Feasibility and Effects of a Simulated Pilot Study.

BACKGROUND: Clinical decision support (CDS) tools-with easily understood and actionable information, at the point of care-are needed to help registered nurses (RNs) make evidence-based decisions. Not clear are the optimal formats of CDS tools. Thorough, preclinical testing is desirable to avoid costly errors associated with premature implementation in electronic health records. OBJECTIVE: The aims of this study were to determine feasibility of the protocol designed to compare multiple CDS formats and evaluate effects of numeracy and graph literacy on RN adoption of best practices and care planning time in a simulated environment. METHODS: In this pilot study, 60 RNs were randomly assigned to one of four CDS conditions (control, text, text + graph, and text + table) and asked to adjust the plan of care for two patient scenarios over three shifts. Fourteen best practices were identified for the two patients and sent as suggestions with evidence to the three CDS groups. Best practice adoption rates, care planning time, and their relationship to the RN's numeracy and graph literacy scores were assessed. RESULTS: CDS groups had a higher adoption rate of best practices (p < .001) across all shifts and decreased care planning time in shifts 2 (p = .01) and 3 (p = .02) compared with the control group. Higher numeracy and graph literacy were associated with shorter care planning times under text + table (p = .05) and text + graph (p = .01) conditions. No significant differences were found between the three CDS groups on adoption rate and care planning time. DISCUSSION: This pilot study shows the feasibility of our protocol. Findings show preliminary evidence that CDS improves the efficiency and effectiveness of care planning decisions and that the optimal format may depend on individual RN characteristics. We recommend a study with sufficient power to compare different CDS formats and assess the impact of potential covariates on adoption rates and care planning time.

Bringing the OhioHealth Nursing Strategic Plan to Life With the AONE Care Innovation and Transformation Program.

Contemporary CNOs are committed to developing the next generation of nurse leaders. At OhioHealth, the nursing strategic vision includes the belief that every nurse will be a leader in improving health across the care continuum. In 2016, the OhioHealth System partnered with AONE to participate in the Care Innovation and Transformation program resulting in bedside nurses living this strategic vision and creating positive changes in quality, safety, and satisfaction for patients and families.

Nurses' Numeracy and Graphical Literacy: Informing Studies of Clinical Decision Support Interfaces.

We present findings of a comparative study of numeracy and graph literacy in a representative group of 60 practicing nurses. This article focuses on a fundamental concern related to the effectiveness of numeric information displayed in various features in the electronic health record during clinical workflow. Our findings suggest the need to consider numeracy and graph literacy when presenting numerical information as well as the potential for tailoring numeric display types to an individual's cognitive strengths.

Nurse Continuity and Hospital-Acquired Pressure Ulcers: A Comparative Analysis Using an Electronic Health Record "Big Data" Set.

BACKGROUND: Little research demonstrating the association between nurse continuity and patient outcomes exists despite an intuitive belief that continuity makes a difference in care outcomes. OBJECTIVE: The aim of this study was to examine the association of nurse continuity with the prevention of hospital-acquired pressure ulcers (HAPU). METHODS: A secondary use of data from the Hands on Automated Nursing Data System (HANDS) was performed for this comparative study. The HANDS is a nursing plan of care data set containing 42,403 episodes documented by 787 nurses, on nine units, in four hospitals and includes nurse staffing and patient characteristics. The HANDS data set resides in a "big data" relational database consisting of 89 tables and 747 columns of data. Via data mining, we created an analytic data set of 840 care episodes, 210 with and 630 without HAPUs, matched by nursing unit, patient age, and patient characteristics. Logistic regression analysis determined the association of nurse continuity and additional nurse-staffing variables on HAPU occurrence. RESULTS: Poor nurse continuity (unit mean continuity index = .21-.42 [1.0 = optimal continuity]) was noted on all nine study units. Nutrition, mobility, perfusion, hydration, and skin problems on admission, as well as patient age, were associated with HAPUs (p < .001). Controlling for patient characteristics, nurse continuity, and the interactions between nurse continuity and other nurse-staffing variables were not significantly associated with HAPU development. DISCUSSION: Patient characteristics including nutrition, mobility, and perfusion were associated with HAPUs, but nurse continuity was not. We demonstrated a high level of variation in the degree of continuity between patient episodes in the HANDS data, showing that it offers rich potential for future study of nurse continuity and its effect on patient outcomes.

Use of Simulation to Study Nurses' Acceptance and Nonacceptance of Clinical Decision Support Suggestions.

Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record-based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse's belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice.

Infomarkers for transition to goals consistent with palliative care in dying patients.

OBJECTIVE: Electronic health records (EHRs) may contain infomarkers that identify patients near the end of life for whom it would be appropriate to shift care goals to palliative care. Discovery and use of such infomarkers could be used to conduct effectiveness research that ultimately could help to reduce the monumental cost of caring for the dying. The aim of our study was to identify changes in the plans of care that represent infomarkers, which signal a transition of care goals from nonpalliative care ones to those consistent with palliative care. METHOD: Using an existing electronic health record database generated during a two-year longitudinal study of nine diverse medical-surgical units from four Midwest hospitals and a known group approach, we evaluated patient care episodes for 901 patients who died (mean age = 74.5 ± 14.6 years). We used ANOVA and Tukey's post-hoc tests to compare patient groups. RESULTS: We identified 11 diagnoses, including Death Anxiety and Anticipatory Grieving, whose addition to the care plan, some of which also occurred with removal of nonpalliative care diagnoses, represent infomarkers of transition to palliative care goals. There were four categories of patients, those who had: no infomarkers on plans (n = 507), infomarkers added on the admission plan (n = 194), infomarkers added on a post-admission plan (minor transitions, n = 109), and infomarkers added and nonpalliative care diagnoses removed on a post-admission plan (major transition, n = 91). Age, length of stay, and pain outcomes differed significantly for these four categories of patients. SIGNIFICANCE OF RESULTS: EHRs contain pertinent infomarkers that if confirmed in future studies could be used for timely referral to palliative care for improved focus on comfort outcomes and to identify palliative care subjects from data repositories in order to conduct big-data research, comparative effectiveness studies, and health-services research.

Academic-Practice Partnerships: Building a sustainable model for Doctor of Nursing Practice (DNP) projects.

BACKGROUND: DNP programs should follow the Academic-Practice Partnership guiding principles developed by the AACN-AONE Task Force of Academic Practice Partnerships (2012) to support students educational and practice experiences. This paper outlines the collaboration between a college of nursing (CON) and academic medical center in establishing a formal process for identification and vetting of student DNP projects. METHODS: A collaborative committee called DNP Project Oversight Committee (DNPPOC) was formed. DNPPOC members outlined a number of processes to facilitate DNP project review, key stakeholder input, and developed several tools to accomplish the committee's goals. A survey was sent to DNPPOC members to solicit their feedback on meeting the committees overall goals. RESULTS: Medical center leadership reported improvements in the collection of key DNP project information and the distribution of DNP projects across facilitators and geographic locations. There was also report of perceived improvement in the overall quality of student learning opportunities, strategic direction of DNP projects, and alignment between CON and healthcare system goals. CONCLUSIONS: Processes developed by the DNPPOC have allowed the organization to handle the increase in DNP projects and maximize organizational resources. The DNPPOC structure has ensured high-quality DNP projects and that DNP students are prepared to be leaders in quality improvement.

Continuity Index Measures in the Acute Care Hospital Setting: An Analytic Review and Tests Using Electronic Health Record Data and Computer Simulation.

BACKGROUND AND PURPOSE: Multiple continuity indexes are available; however, their properties are insufficiently understood for examining the influence of nurse staffing patterns on patient outcomes. We conceptually and analytically examined continuity measures to reveal their properties and relationships with each other and identify potential limitations. METHODS: We examined behavior of continuity indexes as applied to clinical practice data that were collected with the HANDS (Hands-On Automated Nursing Data System) and data from computer simulation. RESULTS: Studied continuity measures exhibited very different statistical characteristics. Most importantly, many continuity measures contain a length-of-stay dependent term that is uncorrelated with continuity. CONCLUSION: Findings provide a deep understanding of the conceptual foundations and properties of various continuity measures. Using findings, researchers can select proper measures and better interpret analysis outcomes.

Acceptability of Clinical Decision Support Interface Prototypes for a Nursing Electronic Health Record to Facilitate Supportive Care Outcomes.

PURPOSE: To determine the acceptability, usefulness, and ease of use for four nursing clinical decision support interface prototypes. METHODS: In a simulated hospital environment, 60 registered nurses (48 female; mean age = 33.7 ± 10.8; mean years of experience = 8.1 ± 9.7) participated in a randomized study with four study groups. Measures included acceptability, usefulness, and ease of use scales. FINDINGS: Mean scores were high for acceptability, usefulness, and the ease of use for all four groups. Inexperienced participants (<1 year) reported higher perceived ease of use (p = .05) and perceived usefulness (p = .01) than those with experience of 1 year or more. CONCLUSIONS: Participants completed the protocol and reported that all four interfaces, including the control (HANDS), were acceptable, easy to use, and useful. IMPLICATIONS FOR NURSING KNOWLEDGE: Further study is warranted before clinical implementation within the electronic health record.

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.

Toward a More Robust and Efficient Usability Testing Method of Clinical Decision Support for Nurses Derived From Nursing Electronic Health Record Data.

PURPOSE: To develop methods for rapid and simultaneous design, testing, and management of multiple clinical decision support (CDS) features to aid nurse decision-making. METHODS: We used quota sampling, think-aloud and cognitive interviews, and deductive and inductive coding of synchronized audio video data and archival libraries. FINDINGS: Our methods and organizational tools allowed us to rapidly improve the usability, understandability, and usefulness of CDS in a generalizable sample of practicing nurses. CONCLUSIONS: The method outlined allows the rapid integration of nursing terminology based electronic health record data into routine workflow and holds strong potential for improving patient outcomes. IMPLICATIONS FOR NURSING PRACTICE: The methods and organizational tools for development of multiple CDS system features can be used to translate knowledge into practice.

Proposing a New Conceptual Model and an Exemplar Measure Using Health Information: Technology to Examine the Impact of Relational Nurse Continuity on Hospital-Acquired Pressure Ulcers.

The influence of the staffing variable relational nurse continuity on patient outcomes has been rarely studied and with inconclusive results. Multiple definitions and an absence of systematic methods for measuring the influence of continuity have resulted in its exclusion from nurse-staffing studies and conceptual models. We present a new conceptual model and an innovative use of health information technology to measure relational nurse continuity and to demonstrate the potential for bringing the results of big data science back to the bedside. Understanding the power of big data to address critical clinical issues may foster a new direction for nursing administration theory development.

Predictive Modeling for End-of-Life Pain Outcome using Electronic Health Records.

Electronic health record (EHR) systems are being widely used in the healthcare industry nowadays, mostly for monitoring the progress of the patients. EHR data analysis has become a big data problem as data is growing rapidly. Using a nursing EHR system, we built predictive models for determining what factors influence pain in end-of-life (EOL) patients. Utilizing different modeling techniques, we developed coarse-grained and fine-grained models to predict patient pain outcomes. The coarse-grained models help predict the outcome at the end of each hospitalization, whereas fine-grained models help predict the outcome at the end of each shift, thus providing a trajectory of predicted outcomes over the entire hospitalization. These models can help in determining effective treatments for individuals and groups of patients and support standardization of care where appropriate. Using these models may also lower the cost and increase the quality of end-of-life care. Results from these techniques show significantly accurate predictions.

Validation of the Quality of Diagnoses, Interventions, and Outcomes (Q-DIO) instrument for use in Brazil and the United States.

PURPOSE: To assess the reliability and validity of Quality of Diagnoses, Interventions, and Outcomes (Q-DIO) in Brazil and in the United States. METHODS: The sample comprised 180 records: centers 1 (electronic records and standardized language) and 2 (paper-based records without standardized language in Brazil, and center 3 (electronic records without standardized language) in the United States. Reliability and discriminant construct validity was analyzed. FINDINGS: Cronbach's alpha for all 29 Q-DIO items were greater than or equal to 0.70 for all centers; construct validity was significantly different between the three study centers. CONCLUSIONS: These results indicate that Q-DIO is valid and reliable for assessing the quality of nursing records. IMPLICATIONS FOR NURSING PRACTICE: The Q-DIO may be useful to assess the quality and accuracy of nursing records.

Evaluating a Clinical Decision Support Interface for End-of-Life Nurse Care.

Clinical Decision Support Systems (CDSS) are tools that assist healthcare personnel in the decision-making process for patient care. Although CDSSs have been successfully deployed in the clinical setting to assist physicians, few CDSS have been targeted at professional nurses, the largest group of health providers. We present our experience in designing and testing a CDSS interface embedded within a nurse care planning and documentation tool. We developed four prototypes based on different CDSS feature designs, and tested them in simulated end-of-life patient handoff sessions with a group of 40 nurse clinicians. We show how our prototypes directed nurses towards an optimal care decision that was rarely performed in unassisted practice. We also discuss the effect of CDSS layout and interface navigation in a nurse's acceptance of suggested actions. These findings provide insights into effective nursing CDSS design that are generalizable to care scenarios different than end-of-life.