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Background: Organizational readiness for change, defined as the collective preparedness of organization members to enact changes, remains understudied in implementing sepsis survivor transition-in-care protocols. Effective implementation relies on collaboration between hospital and post-acute care informants, including those who are leaders and staff. Therefore, our cross-sectional study compared organizational readiness for change among hospital and post-acute care informants. Methods: We invited informants from 16 hospitals and five affiliated HHC agencies involved in implementing a sepsis survivor transition-in-care protocol to complete a pre-implementation survey, where organizational readiness for change was measured via the Organizational Readiness to Implement Change (ORIC) scale (range 12-60). We also collected their demographic and job area information. Mann-Whitney U-tests and linear regressions, adjusting for leadership status, were used to compare organizational readiness of change between hospital and post-acute care informants. Results: Eighty-four informants, 51 from hospitals and 33 from post-acute care, completed the survey. Hospital and post-acute care informants had a median ORIC score of 52 and 57 respectively. Post-acute care informants had a mean 4.39-unit higher ORIC score compared to hospital informants (p = 0.03). Conclusions: Post-acute care informants had higher organizational readiness of change than hospital informants, potentially attributed to differences in health policies, expertise, organizational structure, and priorities. These findings and potential inferences may inform sepsis survivor transition-in-care protocol implementation. Future research should confirm, expand, and examine underlying factors related to these findings with a larger and more diverse sample. Additional studiesmay assess the predictive validity of ORIC towards implementation success. [ABSTRACT FROM AUTHOR]

Objectives To explore home healthcare (HHC) clinicians' needs for Clinical Decision Support Systems (CDSS) information delivery for early risk warning within HHC workflows. Methods Guided by the CDS "Five-Rights" framework, we conducted semi-structured interviews with multidisciplinary HHC clinicians from April 2023 to August 2023. We used deductive and inductive content analysis to investigate informants' responses regarding CDSS information delivery. Results Interviews with thirteen HHC clinicians yielded 16 codes mapping to the CDS "Five-Rights" framework (right information, right person, right format, right channel, right time) and 11 codes for unintended consequences and training needs. Clinicians favored risk levels displayed in color-coded horizontal bars, concrete risk indicators in bullet points, and actionable instructions in the existing EHR system. They preferred non-intrusive risk alerts requiring mandatory confirmation. Clinicians anticipated risk information updates aligned with patient's condition severity and their visit pace. Additionally, they requested training to understand the CDSS's underlying logic, and raised concerns about information accuracy and data privacy. Discussion While recognizing CDSS's value in enhancing early risk warning, clinicians highlighted concerns about increased workload, alert fatigue, and CDSS misuse. The top risk factors identified by machine learning algorithms, especially text features, can be ambiguous due to a lack of context. Future research should ensure that CDSS outputs align with clinical evidence and are explainable. Conclusion This study identified HHC clinicians' expectations, preferences, adaptations, and unintended uses of CDSS for early risk warning. Our findings endorse operationalizing the CDS "Five-Rights" framework to optimize CDSS information delivery and integration into HHC workflows. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Community-based palliative care is a useful, but underutilized service to support seriously ill older adults to remain safely at home and improve quality of life. Clinical decision support tools can assist palliative care need assessments if presented in a way that is useful to clinicians. This case study explores the potential for generative artificial intelligence (AI) to translate diagnostic and billing codes from administrative data into a narrative format to facilitate clinical decision-making regarding palliative care need. Informatics structures for protecting patient confidentiality are described. Generative AI has the potential to support clinical decision-making but requires additional testing, validation, and refinement. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Early introduction of palliative care can improve patient-centered outcomes for older adults with complex medical conditions. However, identifying the need for and introducing palliative care with patients and caregivers is often difficult. We aim to identify how and why a multi-setting approach to palliative care discussions may improve the identification of palliative care needs and how to facilitate these conversations. Methods: Descriptive qualitative study to inform the development and future pilot testing of a model to improve recognition of, and support for, unmet palliative care needs in home health care (HHC). Thematic analysis of semi-structured interviews with providers across inpatient (n = 11), primary care (n = 17), and HHC settings (n = 10). Results: Four key themes emerged: 1) providers across settings can identify palliative care needs using their unique perspectives of the patient's care, 2) identifying palliative care needs is challenging due to infrequent communication and lack of shared information between providers, 3) importance of identifying a clinical lead of patient care who will direct palliative care discussions (primary care provider), and 4) importance of identifying a care coordination lead (HHC) to bridge communication among multi-setting providers. These themes highlight a multi-setting approach that would improve the frequency and quality of palliative care discussions. Conclusions: A lack of structured communication across settings is a major barrier to introducing and providing palliative care. A novel model that improves communication and coordination of palliative care across HHC, inpatient and primary care providers may facilitate identifying and addressing palliative care needs in medically complex older adults. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]