Hospital-to-Home-Health Transition Quality (H3TQ) Index: Further Evidence on its Validity and Recommendations for Implementation.

BACKGROUND: We developed the Hospital-to-Home-Health Transition Quality (H3TQ) Index for skilled home healthcare (HH) agencies to identify threats to safe, high-quality care transitions in real time. OBJECTIVE: Assess the validity of H3TQ in a large sample across diverse communities. RESEARCH DESIGN: A survey of recently hospitalized older adults referred for skilled HH services and their HH provider at two large HH agencies in Baltimore, MD, and New York, NY. SUBJECTS: There were five hundred eighty-seven participants (309 older adults, 141 informal caregivers, and 137 HH providers). Older adults, caregivers, and HH providers rated 747 unique transitions. Of these, 403 were rated by both the older adult/caregiver and their HH provider, whereas the remaining transitions were rated by either party. MEASURES: Construct, concurrent, and predictive validity were assessed via the overall H3TQ rating, correlation with the care transition measure (CTM), and the Medicare Outcome and Assessment Information Set (OASIS). RESULTS: Proportion of transitions with quality issues as identified by HH providers and older adults/caregivers, respectively; Baltimore 55%, 35%; NYC 43%, 32%. Older adults/caregivers across sites rated their transitions as higher quality than did providers (P<0.05). H3TQ summed scores showed construct validity with the CTM-3 and concurrent validity with OASIS measures. Summed H3TQ scores were not significantly correlated with 30-day ED visits or rehospitalization. CONCLUSIONS: The H3TQ identifies care transition quality issues in real-time and demonstrated construct and concurrent validity, but not predictive validity. Findings demonstrate value in collecting multiple perspectives to evaluate care transition quality. Implementing the H3TQ could help identify transition-quality intervention opportunities for HH patients.

Health Coaching Improves Outcomes of Informal Caregivers of Adults With Chronic Heart Failure: A Randomized Controlled Trial.

BACKGROUND: Caring for someone with heart failure takes an emotional and physical toll. Engaging in self-care may decrease stress and improve the health of informal caregivers. We conducted a randomized controlled trial testing the efficacy of a virtual health coaching intervention, compared with health information alone, on the self-care, stress, coping, and health status of heart failure caregivers. METHODS: We enrolled 250 caregivers providing care at least 8 hours/week, reporting poor self-care, and able to use technology. All received a tablet device programmed with websites providing vetted information on heart failure and caregiving. Half were randomized to also receive 10 synchronous support sessions virtually with a health coach over 6 months. Data on self-care, stress, coping, and health status were collected at baseline and 3 and 6 months. Linear mixed-effects models were used to assess the interaction between time and treatment group. RESULTS: The sample was majority female (85.2%), White (62.2%), spouses (59.8%), and aged 55±13.6 years. Many were employed full time (41.8%). They had been caring for the patient 8 hours/day for a median of 3.25 years. In the intention-to-treat analysis, caregivers who received the health coach intervention had statistically and clinically greater improvement across 6 months compared with the control group in the primary outcome of self-care maintenance (5.05±1.99; P=0.01) and stress (-4.50±1.00; P<0.0001). Self-care neglect declined significantly (-0.65±0.32; P=0.04), but the difference between the treatment arms disappeared when the results were adjusted for multiple comparisons. Mental health status improved statistically but not clinically (3.35±1.61; P=0.04). Active coping improved in both groups but not significantly more in the intervention group (P=0.10). Physical health status was unchanged (P=0.27). CONCLUSIONS: This virtual health coaching intervention was effective in improving self-care and stress in heart failure caregivers.

Using the Outcome and Assessment Information Set to Measure Patient Health Status in Research: A Systematic Review.

OBJECTIVES: To review, evaluate, and synthesize existing literature on how health status changes were measured using the Outcome and Assessment Information Set (OASIS). DESIGN: Systematic review. SETTING AND PARTICIPANTS: Studies were included if they examined the health status of adult patients at 2 or more time points using OASIS, which is a comprehensive assessment tool mandated for home health (HH) patients. METHODS: A systematic search was conducted in PubMed, CINAHL, Embase, and Scopus. The methodological quality of the included studies was appraised using the National Institutes of Health quality assessment tool. RESULTS: The initial search yielded 1587 citations, resulting in 27 eligible studies published between 2005 and 2022. All included studies were retrospective cohort studies, with overall quality ranging from good to fair. These studies primarily targeted patients with heart failure, with sample sizes between 40 and 6,637,497 and mean ages of 61.2 to 82.4 years. OASIS version C was the most used version, comparing health status at admission and discharge. Patient health status outcomes encompassed functional (n = 24), physiological (n = 6), emotional/behavioral (n = 4), and cognitive (n = 2) outcomes. Various techniques were employed for scale standardization, compositing individual scores, measuring changes, and reporting outcomes. The predominant methods for assessing change included the corrected Likert scale for standardization, composite change scores for change calculation, and continuous outcomes for reporting. CONCLUSION AND IMPLICATIONS: Researchers have used OASIS to assess patient health status changes in functional, physiological, emotional/behavioral, and cognitive outcomes during the HH episode. Variations in OASIS items and assessment methods across studies have been observed. Our findings underscore the need to standardize item application in research, enabling researchers to synthesize evidence effectively and enhance understanding of patient recovery and HH services. For policymakers and health care providers, these insights could inform resource allocation, care planning, and tailored interventions, ultimately improving health care quality and efficiency.

Home Health Care Use and Outcomes After Coronary Artery Bypass Grafting Among Medicare Beneficiaries.

BACKGROUND: Home health care (HHC) has been increasingly used to improve care transitions and avoid poor outcomes, but there is limited data on its use and efficacy following coronary artery bypass grafting. The purpose of this study was to describe HHC use and its association with outcomes among Medicare beneficiaries undergoing coronary artery bypass grafting. METHODS: Retrospective analysis of 100% of Medicare fee-for-service files identified 77 331 beneficiaries undergoing coronary artery bypass grafting and discharged to home between July 2016 and December 2018. The primary exposure of HHC use was defined as the presence of paid HHC claims within 30 days of discharge. Hierarchical logistic regression identified predictors of HHC use and the percentage of variation in HHC use attributed to the hospital. Propensity-matched logistic regression compared mortality, readmissions, emergency department visits, and cardiac rehabilitation enrollment at 30 and 90 days after discharge between HHC users and nonusers. RESULTS: A total of 26 751 (34.6%) of beneficiaries used HHC within 30 days of discharge, which was more common among beneficiaries who were older (72.9 versus 72.5 years), male (79.4% versus 77.4%), White (90.2% versus 89.2%), and not Medicare-Medicaid dual eligible (6.7% versus 8.8%). The median hospital-level rate of HHC use was 31.0% (interquartile range, 13.7%-54.5%) and ranged from 0% to 94.2%. Nearly 30% of the interhospital variation in HHC use was attributed to the discharging hospital (intraclass correlation coefficient, 0.296 [95% CI, 0.275-0.318]). Compared with non-HHC users, those using HHC were less likely to have a readmission or emergency department visit, were more likely to enroll in cardiac rehabilitation, and had modestly higher mortality within 30 or 90 days of discharge. CONCLUSIONS: A third of Medicare beneficiaries undergoing coronary artery bypass grafting used HHC within 30 days of discharge, with wide interhospital variation in use and mixed associations with clinical outcomes and health care utilization.

Characterizing changes to older adults' care transition patterns from hospital to home care in the initial year of COVID-19.

BACKGROUND: Skilled home healthcare (HH) provided in-person care to older adults during the COVID-19 pandemic, yet little is known about the pandemic's impact on HH care transition patterns. We investigated pandemic impact on (1) HH service volume; (2) population characteristics; and (3) care transition patterns for older adults receiving HH services after hospital or skilled nursing facility (SNF) discharge. METHODS: Retrospective, cohort, comparative study of recently hospitalized older adults (≥ 65 years) receiving HH services after hospital or SNF discharge at two large HH agencies in Baltimore and New York City (NYC) 1-year pre- and 1-year post-pandemic onset. We used the Outcome and Assessment Information Set (OASIS) and service use records to examine HH utilization, patient characteristics, visit timeliness, medication issues, and 30-day emergency department (ED) visit and rehospitalization. RESULTS: Across sites, admissions to HH declined by 23% in the pandemic's first year. Compared to the year prior, older adults receiving HH services during the first year of the pandemic were more likely to be younger, have worse mental, respiratory, and functional status in some areas, and be assessed by HH providers as having higher risk of rehospitalization. Thirty-day rehospitalization rates were lower during the first year of the pandemic. COVID-positive HH patients had lower odds of 30-day ED visit or rehospitalization. At the NYC site, extended duration between discharge and first HH visit was associated with reduced 30-day ED visit or rehospitalization. CONCLUSIONS: HH patient characteristics and utilization were distinct in Baltimore versus NYC in the initial year of the COVID-19 pandemic. Study findings suggest some older adults who needed HH may not have received it, since the decrease in HH services occurred as SNF use decreased nationally. Findings demonstrate the importance of understanding HH agency responsiveness during public health emergencies to ensure older adults' access to care.

Novel avenues of tau research.

INTRODUCTION: The pace of innovation has accelerated in virtually every area of tau research in just the past few years. METHODS: In February 2022, leading international tau experts convened to share selected highlights of this work during Tau 2022, the second international tau conference co-organized and co-sponsored by the Alzheimer's Association, CurePSP, and the Rainwater Charitable Foundation. RESULTS: Representing academia, industry, and the philanthropic sector, presenters joined more than 1700 registered attendees from 59 countries, spanning six continents, to share recent advances and exciting new directions in tau research. DISCUSSION: The virtual meeting provided an opportunity to foster cross-sector collaboration and partnerships as well as a forum for updating colleagues on research-advancing tools and programs that are steadily moving the field forward.

Application of a Human Factors and Systems Engineering Approach to Explore Care Transitions of Sepsis Survivors From Hospital to Home Health Care.

STUDY AIM: This study aims to describe the transition-in-care work process for sepsis survivors going from hospitals to home health care (HHC) and identify facilitators and barriers to enable practice change and safe care transitions using a human factors and systems engineering approach. BACKGROUND: Despite high readmission risk for sepsis survivors, the transition-in-care work process from hospitals to HHC has not been described. METHODS: We analyzed semi-structured needs assessment interviews with 24 stakeholders involved in transitioning sepsis survivors from two hospitals and one affiliated HHC agency participating in the parent implementation science study, I-TRANSFER. The qualitative data analysis was guided by the Systems Engineering Initiative for Patient Safety (SEIPS) framework to describe the work process and identify work system elements. RESULTS: We identified 31 tasks characterized as decision making, patient education, communication, information, documentation, and scheduling tasks. Technological and organizational facilitators lacked in HHC compared to the hospitals. Person and organization elements in HHC had the most barriers but few facilitators. Additionally, we identified specific task barriers that could hinder sepsis information transfer from hospitals to HHC. CONCLUSION: This study explored the complex transition-in-care work processes for sepsis survivors going from hospitals to HHC. We identified barriers, facilitators, and critical areas for improvement to enable implementation and ensure safe care transitions. A key finding was the sepsis information transfer deficit, highlighting a critical issue for future study. APPLICATION: We recommend using the SEIPS framework to explore complex healthcare work processes before the implementation of evidence-based interventions.

Feasibility, usability, and acceptability of psychoeducational videoconferencing interventions for informal caregivers: A systematic review of randomized controlled trials.

Psychoeducational videoconferencing interventions bypass traditional in-person barriers to attendance and are effective in improving caregiving skills, self-care, and wellness among informal caregivers. Information on their feasibility, usability, and acceptability from the caregivers' perspective is needed to inform future designs and developments. This systematic review follows PRISMA 2020 guidelines to integrate this information. Five databases were systematically searched for relevant randomized control trials published between January 2012 and December 2022. Reference lists were cross-checked for additional studies. Relevant studies were appraised and had their data extracted. This review contains 14 randomized controlled trials. Retention rates ranged from 55.56% to 100%, and major reasons for withdrawing include deteriorating patient health, lack of interest, and technical difficulties (feasibility). Caregivers found the videoconference technology usable, although participants in one intervention experienced poor connectivity and persistent technical issues (usability). Most caregivers were satisfied with videoconferencing interventions, found their content applicable to their situation, and appreciated their structure (acceptability). Those in videoconferencing group interventions were satisfied with small caregiver group sizes (acceptability). Adding respite care to interventions and incorporating short and regular videoconferencing sessions may improve feasibility. Ensuring small group sizes in videoconferencing group interventions and using participatory design may enhance acceptability. Advocacy is needed for employees identifying as informal caregivers to receive employer support and for quality connectivity within underserved areas. This may improve the feasibility and usability of interventions, allowing caregivers to receive the support they need. In future studies, power analyses and recruiting more caregivers may better assess feasibility.

Utilizing patient-nurse verbal communication in building risk identification models: the missing critical data stream in home healthcare.

BACKGROUND: In the United States, over 12 000 home healthcare agencies annually serve 6+ million patients, mostly aged 65+ years with chronic conditions. One in three of these patients end up visiting emergency department (ED) or being hospitalized. Existing risk identification models based on electronic health record (EHR) data have suboptimal performance in detecting these high-risk patients. OBJECTIVES: To measure the added value of integrating audio-recorded home healthcare patient-nurse verbal communication into a risk identification model built on home healthcare EHR data and clinical notes. METHODS: This pilot study was conducted at one of the largest not-for-profit home healthcare agencies in the United States. We audio-recorded 126 patient-nurse encounters for 47 patients, out of which 8 patients experienced ED visits and hospitalization. The risk model was developed and tested iteratively using: (1) structured data from the Outcome and Assessment Information Set, (2) clinical notes, and (3) verbal communication features. We used various natural language processing methods to model the communication between patients and nurses. RESULTS: Using a Support Vector Machine classifier, trained on the most informative features from OASIS, clinical notes, and verbal communication, we achieved an AUC-ROC = 99.68 and an F1-score = 94.12. By integrating verbal communication into the risk models, the F-1 score improved by 26%. The analysis revealed patients at high risk tended to interact more with risk-associated cues, exhibit more "sadness" and "anxiety," and have extended periods of silence during conversation. CONCLUSION: This innovative study underscores the immense value of incorporating patient-nurse verbal communication in enhancing risk prediction models for hospitalizations and ED visits, suggesting the need for an evolved clinical workflow that integrates routine patient-nurse verbal communication recording into the medical record.

The Role and Initiatives Led by the Sepsis Coordinator to Improve Sepsis Bundle Compliance and Care Across the Continuum.

A dedicated sepsis coordinator role at Penn Medicine Lancaster General Hospital led initiatives to improve sepsis core measure compliance by 40% during the course of 4 years with submission of all sepsis cases. Chart abstraction and analysis of noncompliant cases identified areas for improvement: early recognition education, order set revisions, documentation support, and the implementation of a nurse-driven 24/7 sepsis monitoring process. The cooperative work with Penn Medicine affiliates, sharing best practices, improves overall sepsis bundle compliance and transitions of care. Ongoing achievements acknowledge the value of building relationships and leading improvements through the collaborative efforts of interprofessional teams.

Social Risk Factors are Associated with Risk for Hospitalization in Home Health Care: A Natural Language Processing Study.

OBJECTIVE: This study aimed to develop a natural language processing (NLP) system that identified social risk factors in home health care (HHC) clinical notes and to examine the association between social risk factors and hospitalization or an emergency department (ED) visit. DESIGN: Retrospective cohort study. SETTING AND PARTICIPANTS: We used standardized assessments and clinical notes from one HHC agency located in the northeastern United States. This included 86,866 episodes of care for 65,593 unique patients. Patients received HHC services between 2015 and 2017. METHODS: Guided by HHC experts, we created a vocabulary of social risk factors that influence hospitalization or ED visit risk in the HHC setting. We then developed an NLP system to automatically identify social risk factors documented in clinical notes. We used an adjusted logistic regression model to examine the association between the NLP-based social risk factors and hospitalization or an ED visit. RESULTS: On the basis of expert consensus, the following social risk factors emerged: Social Environment, Physical Environment, Education and Literacy, Food Insecurity, Access to Care, and Housing and Economic Circumstances. Our NLP system performed "very good" with an F score of 0.91. Approximately 4% of clinical notes (33% episodes of care) documented a social risk factor. The most frequently documented social risk factors were Physical Environment and Social Environment. Except for Housing and Economic Circumstances, all NLP-based social risk factors were associated with higher odds of hospitalization and ED visits. CONCLUSIONS AND IMPLICATIONS: HHC clinicians assess and document social risk factors associated with hospitalizations and ED visits in their clinical notes. Future studies can explore the social risk factors documented in HHC to improve communication across the health care system and to predict patients at risk for being hospitalized or visiting the ED.

Is the patient speaking or the nurse? Automatic speaker type identification in patient-nurse audio recordings.

OBJECTIVES: Patient-clinician communication provides valuable explicit and implicit information that may indicate adverse medical conditions and outcomes. However, practical and analytical approaches for audio-recording and analyzing this data stream remain underexplored. This study aimed to 1) analyze patients' and nurses' speech in audio-recorded verbal communication, and 2) develop machine learning (ML) classifiers to effectively differentiate between patient and nurse language. MATERIALS AND METHODS: Pilot studies were conducted at VNS Health, the largest not-for-profit home healthcare agency in the United States, to optimize audio-recording patient-nurse interactions. We recorded and transcribed 46 interactions, resulting in 3494 "utterances" that were annotated to identify the speaker. We employed natural language processing techniques to generate linguistic features and built various ML classifiers to distinguish between patient and nurse language at both individual and encounter levels. RESULTS: A support vector machine classifier trained on selected linguistic features from term frequency-inverse document frequency, Linguistic Inquiry and Word Count, Word2Vec, and Medical Concepts in the Unified Medical Language System achieved the highest performance with an AUC-ROC = 99.01 ± 1.97 and an F1-score = 96.82 ± 4.1. The analysis revealed patients' tendency to use informal language and keywords related to "religion," "home," and "money," while nurses utilized more complex sentences focusing on health-related matters and medical issues and were more likely to ask questions. CONCLUSION: The methods and analytical approach we developed to differentiate patient and nurse language is an important precursor for downstream tasks that aim to analyze patient speech to identify patients at risk of disease and negative health outcomes.

Improved Protocol for Reproducible Human Cortical Organoids Reveals Early Alterations in Metabolism with MAPT Mutations.

Cerebral cortical-enriched organoids derived from human pluripotent stem cells (hPSCs) are valuable models for studying neurodevelopment, disease mechanisms, and therapeutic development. However, recognized limitations include the high variability of organoids across hPSC donor lines and experimental replicates. We report a 96-slitwell method for efficient, scalable, reproducible cortical organoid production. When hPSCs were cultured with controlled-release FGF2 and an SB431542 concentration appropriate for their TGFBR1 / ALK5 expression level, organoid cortical patterning and reproducibility were significantly improved. Well-patterned organoids included 16 neuronal and glial subtypes by single cell RNA sequencing (scRNA-seq), frequent neural progenitor rosettes and robust BCL11B+ and TBR1+ deep layer cortical neurons at 2 months by immunohistochemistry. In contrast, poorly-patterned organoids contain mesendoderm-related cells, identifiable by negative QC markers including COL1A2 . Using this improved protocol, we demonstrate increased sensitivity to study the impact of different MAPT mutations from patients with frontotemporal dementia (FTD), revealing early changes in key metabolic pathways.

Predicting emergency department visits and hospitalizations for patients with heart failure in home healthcare using a time series risk model.

OBJECTIVES: Little is known about proactive risk assessment concerning emergency department (ED) visits and hospitalizations in patients with heart failure (HF) who receive home healthcare (HHC) services. This study developed a time series risk model for predicting ED visits and hospitalizations in patients with HF using longitudinal electronic health record data. We also explored which data sources yield the best-performing models over various time windows. MATERIALS AND METHODS: We used data collected from 9362 patients from a large HHC agency. We iteratively developed risk models using both structured (eg, standard assessment tools, vital signs, visit characteristics) and unstructured data (eg, clinical notes). Seven specific sets of variables included: (1) the Outcome and Assessment Information Set, (2) vital signs, (3) visit characteristics, (4) rule-based natural language processing-derived variables, (5) term frequency-inverse document frequency variables, (6) Bio-Clinical Bidirectional Encoder Representations from Transformers variables, and (7) topic modeling. Risk models were developed for 18 time windows (1-15, 30, 45, and 60 days) before an ED visit or hospitalization. Risk prediction performances were compared using recall, precision, accuracy, F1, and area under the receiver operating curve (AUC). RESULTS: The best-performing model was built using a combination of all 7 sets of variables and the time window of 4 days before an ED visit or hospitalization (AUC = 0.89 and F1 = 0.69). DISCUSSION AND CONCLUSION: This prediction model suggests that HHC clinicians can identify patients with HF at risk for visiting the ED or hospitalization within 4 days before the event, allowing for earlier targeted interventions.

Home Healthcare Patients With Distinct Psychological, Cognitive, and Behavioral Symptom Profiles and At-Risk Subgroup for Hospitalization and Emergency Department Visits Using Latent Class Analysis.

One-third of home healthcare patients are hospitalized or visit emergency departments during a 60-day episode of care. Among all risk factors, psychological, cognitive, and behavioral symptoms often remain underdiagnosed or undertreated in older adults. Little is known on subgroups of older adults receiving home healthcare services with similar psychological, cognitive, and behavioral symptom profiles and an at-risk subgroup for future hospitalization and emergency department visits. Our cross-sectional study used data from a large, urban home healthcare organization (n = 87,943). Latent class analysis was conducted to identify meaningful subgroups of older adults based on their distinct psychological, cognitive, and behavioral symptom profiles. Adjusted multiple logistic regression was used to understand the association between the latent subgroup and future hospitalization and emergency department visits. Descriptive and inferential statistics were conducted to describe the individual characteristics and to test for significant differences. The three-class model consisted of Class 1: "Moderate psychological symptoms without behavioral issues," Class 2: "Severe psychological symptoms with behavioral issues," and Class 3: "Mild psychological symptoms without behavioral issues." Compared to Class 3, Class 1 patients had 1.14 higher odds and Class 2 patients had 1.26 higher odds of being hospitalized or visiting emergency departments. Significant differences were found in individual characteristics such as age, gender, race/ethnicity, and insurance. Home healthcare clinicians should consider the different latent subgroups of older adults based on their psychological, cognitive, and behavioral symptoms. In addition, they should provide timely assessment and intervention especially to those at-risk for hospitalization and emergency department visits.

Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care.

OBJECTIVE: This study aimed to identify temporal risk factor patterns documented in home health care (HHC) clinical notes and examine their association with hospitalizations or emergency department (ED) visits. MATERIALS AND METHODS: Data for 73 350 episodes of care from one large HHC organization were analyzed using dynamic time warping and hierarchical clustering analysis to identify the temporal patterns of risk factors documented in clinical notes. The Omaha System nursing terminology represented risk factors. First, clinical characteristics were compared between clusters. Next, multivariate logistic regression was used to examine the association between clusters and risk for hospitalizations or ED visits. Omaha System domains corresponding to risk factors were analyzed and described in each cluster. RESULTS: Six temporal clusters emerged, showing different patterns in how risk factors were documented over time. Patients with a steep increase in documented risk factors over time had a 3 times higher likelihood of hospitalization or ED visit than patients with no documented risk factors. Most risk factors belonged to the physiological domain, and only a few were in the environmental domain. DISCUSSION: An analysis of risk factor trajectories reflects a patient's evolving health status during a HHC episode. Using standardized nursing terminology, this study provided new insights into the complex temporal dynamics of HHC, which may lead to improved patient outcomes through better treatment and management plans. CONCLUSION: Incorporating temporal patterns in documented risk factors and their clusters into early warning systems may activate interventions to prevent hospitalizations or ED visits in HHC.

Development and Validation of the Hospital-to-Home-Health Transition Quality (H3TQ) Index: A Novel Measure to Engage Patients and Home Health Providers in Evaluating Hospital-to-Home Care Transition Quality.

BACKGROUND: Patients requiring skilled home health care (HH) after hospitalization are at high risk of adverse events. Human factors engineering (HFE) approaches can be useful for measure development to optimize hospital-to-home transitions. OBJECTIVE: To describe the development, initial psychometric validation, and feasibility of the Hospital-to-Home-Health-Transition Quality (H3TQ) Index to identify patient safety risks. METHODS: Development: A multisite, mixed-methods study at 5 HH agencies in rural and urban sites across the United States. Testing: Prospective H3TQ implementation on older adults' hospital-to-HH transitions. Populations Studied: Older adults and caregivers receiving HH services after hospital discharge, and their HH providers (nurses and rehabilitation therapists). RESULTS: The H3TQ is a 12-item count of hospital-to-HH transitions best practices for safety that we developed through more than 180 hours of observations and more than 80 hours of interviews. The H3TQ demonstrated feasibility of use, stability, construct validity, and concurrent validity when tested on 75 transitions. The vast majority (70%) of hospital-to-HH transitions had at least one safety issue, and HH providers identified more patient safety threats than did patients/caregivers. The most frequently identified issues were unsafe home environments (32%), medication issues (29%), incomplete information (27%), and patients' lack of general understanding of care plans (27%). CONCLUSIONS: The H3TQ is a novel measure to assess the quality of hospital-to-HH transitions and proactively identify transitions issues. Patients, caregivers, and HH providers offered valuable perspectives and should be included in safety reporting. Study findings can guide the design of interventions to optimize quality during the high-risk hospital-to-HH transition.

Mutations in α-synuclein, TDP-43 and tau prolong protein half-life through diminished degradation by lysosomal proteases.

BACKGROUND: Autosomal dominant mutations in α-synuclein, TDP-43 and tau are thought to predispose to neurodegeneration by enhancing protein aggregation. While a subset of α-synuclein, TDP-43 and tau mutations has been shown to increase the structural propensity of these proteins toward self-association, rates of aggregation are also highly dependent on protein steady state concentrations, which are in large part regulated by their rates of lysosomal degradation. Previous studies have shown that lysosomal proteases operate precisely and not indiscriminately, cleaving their substrates at very specific linear amino acid sequences. With this knowledge, we hypothesized that certain coding mutations in α-synuclein, TDP-43 and tau may lead to increased protein steady state concentrations and eventual aggregation by an alternative mechanism, that is, through disrupting lysosomal protease cleavage recognition motifs and subsequently conferring protease resistance to these proteins. RESULTS: To test this possibility, we first generated comprehensive proteolysis maps containing all of the potential lysosomal protease cleavage sites for α-synuclein, TDP-43 and tau. In silico analyses of these maps indicated that certain mutations would diminish cathepsin cleavage, a prediction we confirmed utilizing in vitro protease assays. We then validated these findings in cell models and induced neurons, demonstrating that mutant forms of α-synuclein, TDP-43 and tau are degraded less efficiently than wild type despite being imported into lysosomes at similar rates. CONCLUSIONS: Together, this study provides evidence that pathogenic mutations in the N-terminal domain of α-synuclein (G51D, A53T), low complexity domain of TDP-43 (A315T, Q331K, M337V) and R1 and R2 domains of tau (K257T, N279K, S305N) directly impair their own lysosomal degradation, altering protein homeostasis and increasing cellular protein concentrations by extending the degradation half-lives of these proteins. These results also point to novel, shared, alternative mechanism by which different forms of neurodegeneration, including synucleinopathies, TDP-43 proteinopathies and tauopathies, may arise. Importantly, they also provide a roadmap for how the upregulation of particular lysosomal proteases could be targeted as potential therapeutics for human neurodegenerative disease.

iCare4Me for FTD: A pilot randomized study to improve self-care in caregivers of persons with frontotemporal degeneration.

Introduction: A tremendous burden is placed on frontotemporal degeneration (FTD) caregivers who sacrifice their own self-care to manage the functional impairments of their loved one, contributing to high levels of stress and depression. Health coaching provides support for coping with stress while fostering self-care behaviors. We report on preliminary evidence for efficacy of a virtual health coach intervention aimed at increasing self-care. Methods: Thirty-one caregivers of persons with behavioral variant FTD (bvFTD) were assigned randomly to an intervention group, which included 10 coaching sessions over 6 months plus targeted health information or the control group receiving standard care augmented with the health information. Caregiver self-care (primary outcome), stress, depression, coping, and patient behavioral symptoms were collected at enrollment and 3 and 6 months. Change over time was evaluated between the intervention and control groups using linear mixed-effects models. Results: There was a significant group-by-time interaction for self-care monitoring (t58 = 2.37, p = 0.02 and self-care confidence (t58 = 2.32, p = 0.02) on the Self-Care Inventory, demonstrating that caregivers who received the intervention improved their self-care over time. Behavioral symptoms were reduced in bvFTD patients whose caregivers received the intervention (t54 = -2.15, p = 0.03). Discussion: This randomized controlled trial (RCT) shows promise for health coaching as a way to increase support that is urgently needed to reduce poor outcomes in FTD caregivers.