Gail Powell-Cope

Background: New graduate registered nurse (RN) competencies are complex and difficult to measure. Psychometrically sound tools are needed to evaluate competencies for nurses participating in nurse residencies. Purpose: Project aims were to develop an item pool for a tool to measure new graduate RN competencies for the Veterans Health Administration RN Transition-to-Practice Residency Program; validate item pool content; and use consensus methods to improve item pool content validity. Methods: A sequential, mixed-methods design was used. Item pool creation, content validation, and revisions included a collaborative process with the evaluation team, operational stakeholders, and subject matter experts (SMEs). Results: Inclusion of SMEs in item development enhanced item pool content validity to measure nurse competency. Stakeholder feedback ensured programmatic logistical and evaluation concerns were met. Conclusions: Engaging SMEs in conceptualization, item development, and aligning existing standards enhanced item pool content validity to measure nurse competencies for new graduate RNs.

Study design A 5-year longitudinal, retrospective, cohort study. Objectives Develop a prediction model based on electronic health record (EHR) data to identify veterans with spinal cord injury/diseases (SCI/D) at highest risk for new pressure injuries (PIs). Setting Structured (coded) and text EHR data, for veterans with SCI/D treated in a VHA SCI/D Center between October 1, 2008, and September 30, 2013. Methods A total of 4709 veterans were available for analysis after randomly selecting 175 to act as a validation (gold standard) sample. Machine learning models were created using ten-fold cross validation and three techniques: (1) two-step logistic regression; (2) regression model employing adaptive LASSO; (3) and gradient boosting. Models based on each method were compared using area under the receiver-operating curve (AUC) analysis. Results The AUC value for the gradient boosting model was 0.62 (95% CI = 0.54–0.70), for the logistic regression model it was 0.67 (95% CI = 0.59–0.75), and for the adaptive LASSO model it was 0.72 (95% CI = 0.65–80). Based on these results, the adaptive LASSO model was chosen for interpretation. The strongest predictors of new PI cases were having fewer total days in the hospital in the year before the annual exam, higher vs. lower weight and most severe vs. less severe grade of injury based on the American Spinal Cord Injury Association (ASIA) Impairment Scale. Conclusions While the analyses resulted in a potentially useful predictive model, clinical implications were limited because modifiable risk factors were absent in the models.

This article is part of a series, Supporting Family Caregivers: No Longer Home Alone, published in collaboration with the AARP Public Policy Institute. Results of focus groups, conducted as part of the AARP Public Policy Institute's No Longer Home Alone video project, supported evidence that family caregivers aren't given the information they need to manage the complex care regimens of family members. This series of articles and accompanying videos aims to help nurses provide caregivers with the tools they need to manage their family member's health care at home. The articles in this new installment of the series explain principles for promoting safe mobility that nurses should reinforce with family caregivers. Each article also includes an informational tear sheet—Information for Family Caregivers—that contains links to instructional videos. To use this series, nurses should read the article first, so they understand how best to help family caregivers, and then encourage the caregivers to watch the videos and ask questions. For additional information, see Resources for Nurses.

This article is part of a series, Supporting Family Caregivers: No Longer Home Alone, published in collaboration with the AARP Public Policy Institute. Results of focus groups, conducted as part of the AARP Public Policy Institute's No Longer Home Alone video project, supported evidence that family caregivers aren't given the information they need to manage the complex care regimens of family members. This series of articles and accompanying videos aims to help nurses provide caregivers with the tools they need to manage their family member's health care at home. The articles in this new installment of the series explain principles for promoting safe mobility that nurses should reinforce with family caregivers. Each article also includes an informational tear sheet—Information for Family Caregivers—that contains links to instructional videos. To use this series, nurses should read the article first, so they understand how best to help family caregivers, and then encourage the caregivers to watch the videos and ask questions. For additional information, see Resources for Nurses.

Background: Patient falls are the most common adverse events reported in hospitals. Although it is well understood that the physical hospital environment contributes to nearly 40% of severe or fatal hospital falls, there are significant gaps in the knowledge about the relationship between inpatient unit design and fall rates. The few studies that have examined unit design have been conducted in a single hospital (non-Veterans Health Administration [VHA]) or a small number of inpatient units, limiting generalizability. The goal of this study is to identify unit design factors contributing to inpatient falls in the VHA. Objective: The first aim of the study is to investigate frontline and management perceptions of and experiences with veteran falls as they pertain to inpatient environmental factors. An iterative rapid assessment process will be used to analyze the data. Interview findings will directly inform the development of an environmental assessment survey to be conducted as part of aim 2 and to contribute to interpretation of aim 2. The second aim of this study is to quantify unit design factors and compare spatial and environmental factors of units with higher- versus lower-than-expected fall rates. Methods: We will first conduct walk-through interviews with facility personnel in 10 medical/surgical units at 3 VHA medical centers to identify environmental fall risk factors. Data will be used to finalize an environmental assessment survey for nurse managers and facilities managers. We will then use fall data from the VA Inpatient Evaluation Center and patient data from additional sources to identify 50 medical/surgical nursing units with higher- and lower-than-expected fall rates. We will measure spatial factors by analyzing computer-aided design files of unit floorplans and environmental factors from the environmental assessment survey. Statistical tests will be performed to identify design factors that distinguish high and low outliers. Results: The VA Health Services Research and Development Service approved funding for the study. The research protocol was approved by institutional review boards and VA research committees at both sites. Data collection started in February 2018. Results of the data analysis are expected by February 2022. Data collection and analysis was completed for aim 1 with a manuscript of results in progress. For aim 2, the medical/surgical units were categorized into higher- and lower-than-expected fall categories, the environmental assessment surveys were distributed to facility managers and nurse managers. Data to measure spatial characteristics are being compiled. Conclusions: To our knowledge, this study is the first to objectively identify spatial risks for falls in hospitals within in a large multihospital system. Findings can contribute to evidence-based design guidelines for hospitals such as those of the Facility Guidelines Institute and the Department of Veterans Affairs. The metrics for characterizing spatial features are quantitative indices that could be incorporated in larger scale contextual studies examining contributors to falls, which to date often exclude physical environmental factors at the unit level. Space syntax measures could be used as physical environmental factors in future research examining a range of contextual factors—social, personal, organizational, and environmental—that contribute to patient falls. International Registered Report Identifier (IRRID): DERR1-10.2196/24974

BACKGROUND Patient falls are the most common adverse events reported in hospitals. Although it is well understood that the physical hospital environment contributes to nearly 40% of severe or fatal hospital falls, there are significant gaps in the knowledge about the relationship between inpatient unit design and fall rates. The few studies that have examined unit design have been conducted in a single hospital (non-Veterans Health Administration [VHA]) or a small number of inpatient units, limiting generalizability. The goal of this study is to identify unit design factors contributing to inpatient falls in the VHA. OBJECTIVE The first aim of the study is to investigate frontline and management perceptions of and experiences with veteran falls as they pertain to inpatient environmental factors. An iterative rapid assessment process will be used to analyze the data. Interview findings will directly inform the development of an environmental assessment survey to be conducted as part of aim 2 and to contribute to interpretation of aim 2. The second aim of this study is to quantify unit design factors and compare spatial and environmental factors of units with higher- versus lower-than-expected fall rates. METHODS We will first conduct walk-through interviews with facility personnel in 10 medical/surgical units at 3 VHA medical centers to identify environmental fall risk factors. Data will be used to finalize an environmental assessment survey for nurse managers and facilities managers. We will then use fall data from the VA Inpatient Evaluation Center and patient data from additional sources to identify 50 medical/surgical nursing units with higher- and lower-than-expected fall rates. We will measure spatial factors by analyzing computer-aided design files of unit floorplans and environmental factors from the environmental assessment survey. Statistical tests will be performed to identify design factors that distinguish high and low outliers. RESULTS The VA Health Services Research and Development Service approved funding for the study. The research protocol was approved by institutional review boards and VA research committees at both sites. Data collection started in February 2018. Results of the data analysis are expected by February 2022. Data collection and analysis was completed for aim 1 with a manuscript of results in progress. For aim 2, the medical/surgical units were categorized into higher- and lower-than-expected fall categories, the environmental assessment surveys were distributed to facility managers and nurse managers. Data to measure spatial characteristics are being compiled. CONCLUSIONS To our knowledge, this study is the first to objectively identify spatial risks for falls in hospitals within in a large multihospital system. Findings can contribute to evidence-based design guidelines for hospitals such as those of the Facility Guidelines Institute and the Department of Veterans Affairs. The metrics for characterizing spatial features are quantitative indices that could be incorporated in larger scale contextual studies examining contributors to falls, which to date often exclude physical environmental factors at the unit level. Space syntax measures could be used as physical environmental factors in future research examining a range of contextual factors—social, personal, organizational, and environmental—that contribute to patient falls. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/24974

Background: Numerous studies of community reintegration (CR) in traumatic brain injury (TBI) have been conducted in civilian populations, but research is limited in veteran and military service member populations. Little is known about how knowledge from civilian studies translates into veterans’ experiences and needs. The US Department of Veterans Health Administration (VHA) recognizes the distinctive health care needs of post-9/11 veteran and military service members, particularly with TBI, including the need to bridge health and rehabilitation-related services from acute care and inpatient settings to veteran and military service members’ homes and communities to facilitate CR. Objective: The goal of this study is to better understand the experiences of veterans with complicated mild, moderate, or severe TBI; their families; and CR workers as veterans and servicemembers transition to and sustain living in communities. This paper describes the rationale, design, and methods used to reach this goal. Methods: This five-year longitudinal mixed methods study uses both a community-engaged research (CEnR) approach and an ethnographic approach. The sample includes 30 veterans and service members with TBI, 13 family caregivers, 11 CR specialists, 16 key stakeholders, and 82 community events. Interviews and observations are coded and analyzed using hierarchical coding schemes and thematic analysis. Analyses include data from surveys, interviews, and participant observations. Content analysis is used to highlight the complex social context of reintegration and to triangulate quantitative data. Egocentric (personal) social network analysis is used to examine the support system a veteran or service member has in place to facilitate reintegration. Results: Study enrollment and data collection are completed. Data analyses are underway. Conclusions: The results of this study may provide a heightened understanding of environmental factors affecting CR in complicated mild, moderate, or severe TBI. Veteran, servicemember and family voices and insights provide VHA clinicians and policy makers with an ecological view of CR that is grounded in the life experiences of veterans, military service members, and families. The results of this study provide a roadmap for designing and testing interventions to maximize CR in a variety of domains. The longitudinal ethnographic approach allows for capturing detailed experiences within the naturalistic context. CEnR allows collaborative assessment of the social context of reintegration with community members. International Registered Report Identifier (IRRID): DERR1-10.2196/14170