Collaborative to Increase Lethal Means Counseling for Caregivers of Youth With Suicidality.

BACKGROUND: The number of youth presenting to hospitals with suicidality and/or self-harm has increased substantially in recent years. We implemented a multihospital quality improvement (QI) collaborative from February 1, 2018 to January 31, 2019, aiming for an absolute increase in hospitals' mean rate of caregiver lethal means counseling (LMC) of 10 percentage points (from a baseline mean performance of 68% to 78%) by the end of the collaborative, and to evaluate the effectiveness of the collaborative on LMC, adjusting for secular trends. METHODS: This 8 hospital collaborative used a structured process of alternating learning sessions and action periods to improve LMC across hospitals. Electronic medical record documentation of caregiver LMC was evaluated during 3 phases: precollaborative, active QI collaborative, and postcollaborative. We used statistical process control to evaluate changes in LMC monthly. Following collaborative completion, interrupted time series analyses were used to evaluate changes in the level and trend and slope of LMC, adjusting for covariates. RESULTS: In the study, 4208 children and adolescents were included-1314 (31.2%) precollaborative, 1335 (31.7%) during the active QI collaborative, and 1559 (37.0%) postcollaborative. Statistical process control analyses demonstrated that LMC increased from a hospital-level mean of 68% precollaborative to 75% (February 2018) and then 86% (October 2018) during the collaborative. In interrupted time series analyses, there were no significant differences in LMC during and following the collaborative beyond those expected based on pre-collaborative trends. CONCLUSIONS: LMC increased during the collaborative, but the increase did not exceed expected trends. Interventions developed by participating hospitals may be beneficial to others aiming to improve LMC for caregivers of hospitalized youth with suicidality.

VA nursing home compare metrics as an indicator of skilled nursing facility quality for veterans.

BACKGROUND: The Veterans Administration (VA) provides several post-acute care (PAC) options for Veterans, including VA-owned nursing homes (called Community Living Centers, CLCs). In 2016, the VA released CLC Compare star ratings to support decision-making. However, the relationship between CLC Compare star ratings and Veterans CLC post-acute outcomes is unknown. METHODS: Retrospective observational study using national VA and Medicare data for Veterans discharged to a CLC for PAC. We used a multivariate regression model with hospital random effects to examine the association between CLC Compare overall star ratings and PAC outcomes while controlling for patient, facility, and hospital factors. Our sample included Veteran enrollees age 65+ who were community-dwelling, experienced a hospitalization, and were discharged to a CLC in 2016-2017. PAC outcomes included 30-day unplanned hospital readmission, 30-day mortality, 100-day successful community discharge, and a secondary composite outcome of unplanned readmission or death within 30-days of the hospital discharge. RESULTS: Of the 25,107 CLC admissions, 4088 (16.3%) experienced an unplanned readmission, 4069 (16.2%) died within 30-days of hospital discharge, and 12,093 (48.2%) had a successful 100-day community discharge. Admission to a lower-quality (1-star) facility was associated with lower odds of successful community discharge (OR 0.78; 95% CI 0.66, 0.91) and higher odds of a combined endpoint of 30-day mortality and readmission (OR 1.27; 95% CI 1.09, 1.49), compared to 5-star facilities. However, outcomes were not consistently different between 5-star and 2, 3, or 4-star facilities. Star ratings were not associated with individual readmission or mortality outcomes when considered separately. CONCLUSION: These findings suggest comparisons of 1-star and 5-star CLCs may provide meaningful information for Veterans making decisions about post-acute care. Identifying ways to alter the star ratings so they are differentially associated with outcomes meaningful to Veterans at each level is essential. We found that 1-star facilities had higher rates of 30-day unplanned hospital readmission/death, and lower rates of 100-day successful community discharges compared to 5-star facilities. Yet, like past work on CMS Nursing Home Compare ratings, these relationships were found to be inconsistent or not meaningful across all star levels. CLC Compare may provide useful information for discharge and organizational planning, with some limitations.

Facilitators and barriers to Children's Advocacy Center-based multidisciplinary teamwork.

BACKGROUND: Children's Advocacy Centers (CACs) use a multidisciplinary team (MDT) approach to initiate, coordinate, and provide essential multisector services for children and families who experience child abuse. Despite rapid dissemination of the CAC model across the world, little is known about characteristics associated with CAC-based teamwork. OBJECTIVE: Given that teamwork characteristics may impact the outcomes of child and families who interact with CACs, the purpose of this qualitative study was to explore experiences, facilitators, and barriers to CAC-based multidisciplinary teamwork. PARTICIPANTS, SETTING, & METHODS: We conducted semi-structured interviews with members of a MDT at a Midwestern CAC. RESULTS: Findings suggest that MDT teamwork was fostered by clear communication, responsiveness, commitment, openness, and appropriate resources whereas MDT teamwork was hindered by role confusion, conflicting perspectives, poor communication, low staffing, complex politics, and structural barriers. CONCLUSIONS: Characteristics of CAC-based teamwork may vary from the teamwork of other types of child protection teams. Interventions that enhance CAC-based teamwork may optimize the function of CAC MDTs and improve outcomes for children and families who engage with CACs.

Ready to Go Home? Assessment of Shared Mental Models of the Patient and Discharging Team Regarding Readiness for Hospital Discharge.

BACKGROUND: A critical task of the inpatient interprofessional team is readying patients for discharge. Assessment of shared mental model (SMM) convergence can determine how much team members agree about patient discharge readiness and how their mental models align with the patient's self-assessment. OBJECTIVE: Determine the convergence of interprofessional team SMMs of hospital discharge readiness and identify factors associated with these assessments. DESIGN: We surveyed interprofessional discharging teams and each team's patient at time of hospital discharge using validated tools to capture their SMMs. PARTICIPANTS: Discharge events (N = 64) from a single hospital consisting of the patient and their team (nurse, coordinator, physician). MEASURES: Clinician and patient versions of the validated Readiness for Hospital Discharge Scales/Short Form (RHDS/SF). We measured team convergence by comparing the individual clinicians' scores on the RHDS/SF, and we measured team-patient convergence as the absolute difference between the Patient-RHDS/SF score and the team average score on the Clinician-RHDS/SF. RESULTS: Discharging teams assessed patients as having high readiness for hospital discharge (mean score, 8.5 out of 10; SD, 0.91). The majority of teams had convergent SMMs with high to very high interrater agreement on discharge readiness (mean r*wg(J), 0.90; SD, 0.10). However, team-patient SMM convergence was low: Teams overestimated the patient's self-assessment of readiness for discharge in 48.4% of events. We found that teams reporting higher-quality teamwork (P = .004) and bachelor's level-trained nurses (P < .001) had more convergent SMMs with the patient. CONCLUSION: Measuring discharge teams' SMM of patient discharge readiness may represent an innovative assessment tool and potential lever to improve the quality of care transitions.

Online Ratings of Facial Plastic Surgeons: Worthwhile Additions to Conventional Patient Experience Surveys.

Background: Physician review websites are now commonly used by patients. However, in facial plastic surgery, the trends and content in these websites are not well studied. We examined online reviews for U.S. facial plastic surgeons, and compared comment content with the most commonly used patient experience survey, the Consumer Assessment of Healthcare Providers and Systems (CAHPS) administered by Press Ganey. Methods: A retrospective mixed method study was employed to quantitatively compare online ratings and comments of 100 randomly selected U.S. facial plastic surgeons on vitals.com, healthgrades.com, google.com and zocdoc.com. Qualitative content analysis was utilized to categorize themes present in 957 patient-generated (unverified) comments, and compare these with CAHPS survey questions and themes. Results: The physician review websites had favorable ratings of facial plastic surgeons with 84.55% five-star reviews on Healthgrades and 78.40% on Vitals. These ratings were similar across surgeon age (p = 0.44), gender (p = 0.85), and geographic region (p = 0.29). Of sites examined, Healthgrades and Vitals were most frequently used. Analysis of patient comments identified themes aligning with CAHPS content (e.g., physician interactions, efficiency, and recommendation likelihood), as well as additional themes such as patient's outcome perception (55.28% of comments) and finances (86% of negatively rated reviews). Conclusions: These exploratory results suggest that facial plastic surgeons are generally rated positively online, and the comments left on these websites provide additional feedback that is not currently included in CAHPS surveys. In evaluating the patient experience with facial plastic surgery practices, these websites may prove to be useful.

Differences in transitional care processes among high-performing and low-performing hospital-SNF pairs: a rapid ethnographic approach.

BACKGROUND: Despite the increased focus on improving patient's postacute care outcomes, best practices for reducing readmissions from skilled nursing facilities (SNFs) are unclear. The objective of this study was to observe processes used to prepare patients for postacute care in SNFs, and to explore differences between hospital-SNF pairs with high or low 30-day readmission rates. DESIGN: We used a rapid ethnographic approach with intensive multiday observations and key informant interviews at high-performing and low-performing hospitals, and their most commonly used SNF. We used flow maps and thematic analysis to describe the process of hospitals discharging patients to SNFs and to identify differences in subprocesses used by high-performing and low-performing hospitals. SETTING AND PARTICIPANTS: Hospitals were classified as high or low performers based on their 30-day readmission rates from SNFs. The final sample included 148 hours of observations with 30 clinicians across four hospitals (n=2 high performing, n=2 low performing) and corresponding SNFs (n=5). FINDINGS: We identified variation in five major processes prior to SNF discharge that could affect care transitions: recognising need for postacute care, deciding level of care, selecting an SNF, negotiating patient fit and coordinating care with SNF. During each stage, high-performing sites differed from low-performing sites by focusing on: (1) earlier, ongoing, systematic identification of high-risk patients; (2) discussing the decision to go to an SNF as an iterative team-based process and (3) anticipating barriers with knowledge of transitional and SNF care processes. CONCLUSION: Identifying variations in processes used to prepare patients for SNF provides critical insight into the best practices for transitioning patients to SNFs and areas to target for improving care of high-risk patients.

How Context Influences Hospital Readmissions from Skilled Nursing Facilities: A Rapid Ethnographic Study.

INTRODUCTION: Improving hospital discharge processes and reducing adverse outcomes after hospital discharge to skilled nursing facilities (SNFs) are gaining national recognition. However, little is known about how the social-contextual factors of hospitals and their affiliated SNFs may influence the discharge process and drive variations in patient outcomes. We sought to categorize contextual drivers that vary between high- and low-performing hospitals in older adult transition from hospitals to SNFs. DESIGN: To identify contextual drivers, we used a rapid ethnographic approach with interviews and direct observations of hospital and SNF clinicians involved in discharging patients. We conducted thematic analysis to categorize contextual factors and compare differences in high- and low-performing sites. SETTING AND PARTICIPANTS: We stratified hospitals on 30-day hospital readmission rates from SNFs and used convenience sampling to identify high- and low-performing sites and associated SNFs. The final sample included 4 hospitals (n = 2 high performing, n = 2 low performing) and affiliated SNFs (n = 5) with 148 hours of observations. MEASURES: Central themes related to how contextual factors influence variations in high- and low-performing hospitals. RESULTS: We identified 3 main contextual factors that differed across high- and low-performing hospitals and SNFs: team dynamics, patient characteristics, and organizational context. First, we observed high-quality communication, situational awareness, and shared mental models among team members in high-performing sites. Second, the types of patients cared for at high-performing hospitals had better insurance coverage that made it feasible for clinicians to place patients based on their needs instead of financial abilities. Third, at high-performing hospitals a more engaged staff in the transition process and building rapport with SNFs characterized smooth transitions from hospitals to SNFs. CONCLUSIONS AND IMPLICATIONS: Contextual factors distinguish high- and low-performing hospitals in transitions to SNF and can be used to develop interventions to reduce adverse outcomes in transitions.

External Validation of the Skilled Nursing Facility Prognosis Score for Predicting Mortality, Hospital Readmission, and Community Discharge in Veterans.

BACKGROUND/OBJECTIVES: Prognostic tools are needed to identify patients at high risk for adverse outcomes receiving post-acute care in skilled nursing facilities (SNFs) and provide high-value care. The SNF Prognosis Score was developed in a Medicare sample to predict a composite of long-term SNF stay, hospital readmission, or death during the SNF stay. Our goal was to evaluate the score's performance in an external validation cohort. DESIGN: Retrospective observational analysis. SETTING: We used a Veterans Administration (VA) Residential History File that concatenates VA, Medicare, and Medicaid claims to identify care trajectories across settings and payers for individual veterans. PARTICIPANTS: Previously community-dwelling veterans receiving post-acute care in a SNF after hospitalization from January 1, 2012, to December 31, 2014. Both VA and non-VA hospitals and SNFs were included. MEASUREMENTS: We calculated the five-item SNF Prognosis Score for all eligible veterans in our sample and determined its discrimination (using a receiver operating characteristic curve) and calibration (plotting observed and expected events). RESULTS: The 386,483 veterans in our sample had worse physical function, more comorbidities, and were more likely to be treated for heart failure, but they had shorter index hospital lengths of stay and fewer catheters than the original Medicare cohort. The SNF Prognosis Score had similar discrimination (C-statistic = .70; .75 in the derivation cohort) and calibration at low to moderate levels of risk; at high levels, calibration was poorer with the score overestimating risks of adverse events. CONCLUSION: The SNF Prognosis Score has reasonable discrimination and calibration, and it is simple to calculate using an admission SNF assessment and a nomogram. Future work embedding the score into practice is needed to determine real-world feasibility, acceptability, and effectiveness.

Association of Online Consumer Reviews of Skilled Nursing Facilities With Patient Rehospitalization Rates.

Importance: There are areas of skilled nursing facility (SNF) experience of importance to the public that are not currently included in public reporting initiatives on SNF quality. Whether patients, hospitals, and payers can leverage the information available from unsolicited online reviews to reduce avoidable rehospitalizations from SNFs is unknown. Objectives: To assess the association between rehospitalization rates and online ratings of SNFs; to compare the association of rehospitalization with ratings from a review website vs Medicare Nursing Home Compare (NHC) ratings; and to identify specific topics consistently reported in reviews of SNFs with the highest vs lowest rehospitalization rates using natural language processing. Design, Setting, and Participants: A retrospective cross-sectional study of 1536 SNFs with online reviews on Yelp (a website that allows consumers to rate and review businesses and services, scored on a 1- to 5-star rating scale, with 1 star indicating the lowest rating and 5 stars indicating the highest rating) posted between January 1, 2014, and December 31, 2018. The combined data set included 1536 SNFs with 8548 online reviews, NHC ratings, and readmission rates. Main Outcomes and Measures: A mean rating from the review website was calculated through the end of each year. Risk-standardized rehospitalization rates were obtained from NHC. Linear regression was used to measure the association between the rehospitalization rate of a SNF and the online ratings. Natural language processing was used to identify topics associated with reviews of SNFs in the top and bottom quintiles of rehospitalization rates. Results: The 1536 SNFs in the sample had a median of 6 reviews (interquartile range, 3-13 reviews), with a mean (SD) review website rating of 2.7 (1.1). The SNFs with the highest rating on both the review website and NHC had 2.0% lower rehospitalization rates compared with the SNFs with the lowest rating on both websites (21.3%; 95% CI, 20.7%-21.8%; vs 23.3%; 95% CI, 22.7%-24.0%; P = .04). Compared with the NHC ratings alone, review website ratings were associated with an additional 0.4% of the variation in rehospitalization rates across SNFs (adjusted R2 = 0.009 vs adjusted R2 = 0.013; P = .003). Thematic analysis of qualitative comments on the review website for SNFs with high vs low rehospitalization rates identified several areas of importance to the reviewers, such as the quality of physical infrastructure and equipment, staff attitudes and communication with caregivers. Conclusions and Relevance: Skilled nursing facilities with the best rating on both a review website and NHC had slightly lower rehospitalization rates than SNFs with the best rating on NHC alone. However, there was marked variation in the volume of reviews, and many SNF characteristics were underrepresented. Further refinement of the review process is warranted.

Using Evidence to Create a Toolkit to Enable Sleep Among Hospitalized Patients.

Studies show sleep deprivation impacts patients' ability to perform physical activities and can lead to delirium, depression, and other psychiatric impairments. One of the Choosing Wisely® recommendations is "Do not wake the patient for routine care unless the patient's condition requires it." The authors discuss the development of an evidence-based toolkit to facilitate opportunities for patients to sleep during hospitalization, exemplifying the translation of a Choosing Wisely recommendation into clinical practice.

Exploring the Hidden Functions of Nursing Bedside Shift Report: A Performance, Ritual, and Sensemaking Opportunity.

BACKGROUND: Implementing Nursing Bedside Shift Report (NBSR) is challenging for nurse leaders. Before implementing or improving NBSR, nurse leaders need a clear understanding of the process and functions of nursing shift report. However, the social-cultural latent functions (unrecognized or unintended uses) of NBSR are poorly understood. PURPOSE: The purpose of this qualitative study was to describe the latent functions of NBSR from the perspectives of frontline nurses. METHODS: Thematic analysis of previously collected semistructured interviews with nurses (n = 13) about NBSR was used to explore NBSR's latent functions. RESULTS: Three latent functions emerged; nurses used bedside shift report as a performance, ritual, and sensemaking opportunity. The latent functions are described, and corresponding recommendations for successful implementation of NBSR are provided. CONCLUSIONS: Nurse leaders can use this study's findings to inform the development or improvement of an efficient, effective, and sustainable NBSR process at their local institution.

Handing Off Safety at the Bedside.

The study purpose was to describe how bedside nurses can use nursing bedside shift report (NBSR) to keep patients safe. NBSR has been recommended as a means of increasing patient safety, but little is known about how or whether it does so. Grounded theory methods were used. Data were collected from 2014 to 2015 with bedside nurses in a pediatric unit with an established NBSR process. The primary process by which bedside nurses use NBSR to keep patients safe is reducing risk of harm through conveying the patient story from shift to shift. Having a perspective from the bedside is a key antecedent to reducing risk of harm, as it supports the nurses' ability to subsequently identify and address risks. Although often seen as a routine exchange of information, how nursing shift report is conducted can impact patient safety. The study reinforces the value of targeting nursing communication to improve patient safety.

Empowering Sustained Patient Safety: The Benefits of Combining Top-down and Bottom-up Approaches.

Implementation of TeamSTEPPS for improving patient safety is examined via descriptive qualitative analysis of semistructured interviews with 21 informants at 12 hospitals. Implementation approaches fit 3 strategies: top-down, bottom-up, and combination. The top-down approach failed to develop enough commitment to spread implementation. The bottom-up approach was unable to marshal the resources necessary to spread implementation. Combining top-down and bottom-up processes best facilitated the implementation and spread of the TeamSTEPPS safety initiative.