Leveraging home health aides to improve outcomes in heart failure: A pilot study protocol.

Heart failure (HF) affects six million people in the U.S., is associated with high morbidity, mortality, and healthcare utilization.(1, 2) Despite a decade of innovation, the majority of interventions aimed at reducing hospitalization and readmissions in HF have not been successful.(3-7) One reason may be that most have overlooked the role of home health aides and attendants (HHAs), who are often highly involved in HF care.(8-13) Despite their contributions, studies have found that HHAs lack specific HF training and have difficulty reaching their nursing supervisors when they need urgent help with their patients. Here we describe the protocol for a pilot randomized control trial (pRCT) assessing a novel stakeholder-engaged intervention that provides HHAs with a) HF training (enhanced usual care arm) and b) HF training plus a mobile health application that allows them to chat with a nurse in real-time (intervention arm). In collaboration with the VNS Health of New York, NY, we will conduct a single-site parallel arm pRCT with 104 participants (HHAs) to evaluate the feasibility, acceptability, and effectiveness (primary outcomes: HF knowledge; HF caregiving self-efficacy) of the intervention among HHAs caring for HF patients. We hypothesize that educating and better integrating HHAs into the care team can improve their ability to provide support for patients and outcomes for HF patients as well (exploratory outcomes include hospitalization, emergency department visits, and readmission). This study offers a novel and potentially scalable way to leverage the HHA workforce and improve the outcomes of the patients for whom they care. Clinical trial.gov registration: NCT04239911.

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.

Home Care Clinicians' Perspectives on Advance Care Planning for Patients at Risk for Becoming Incapacitated With No Evident Advance Directives or Surrogates.

Advance care planning is important and timely for patients receiving home health services; however, opportunities to facilitate awareness and engagement in this setting are often missed. This qualitative descriptive study elicited perspectives of home health nurses and social workers regarding barriers and facilitators to creating advance care plans in home health settings, with particular attention to patients with few familial or social contacts who can serve as surrogate decision-makers. We interviewed 15 clinicians employed in a large New York City-based home care agency in 2021-2022. Participants reported a multitude of barriers to supporting patients with advance care planning at the provider level (eg, lack of time and professional education, deferment, discomfort), patient level (lack of knowledge, mistrust, inadequate support, deferment, language barriers), and system level (eg, discontinuity of care, variations in advance care planning documents, legal concerns, lack of institutional protocols and centralized information). Participants noted that greater socialization and connection to existing educational resources regarding the intended purpose, scope, and applicability of advance directives could benefit home care patients.

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.

Covid-19: Home Health Aides' Perceived Preparedness and Self-Reported Availability for Work: Six Month Survey Results.

Throughout the COVID-19 pandemic New York City home health aides continuously provided care, including to patients actively infected or recovering from COVID-19. Analyzing survey data from 1316 aides, we examined factors associated with perceptions of how well their employer prepared them for COVID-19 and their self-reported availability for work (did they "call out" more than usual). Organizational work environment and COVID-19-related supports were predominant predictors of self-reported perceptions of preparedness. Worker characteristics and COVID-19-related stressors were predominant predictors of self-reported availability. Mental distress, satisfaction with employer communications, and satisfaction with supervisor instructions were significantly associated with both outcomes. The study uniquely describes self-reported perceptions of preparedness and availability as two separate worker outcomes potentially modifiable by different interventions. Better public health emergency training and adequate protective equipment may increase aides' perceived preparedness; more household supports could facilitate their availability. More effective employer communications and mental health initiatives could potentially improve both outcomes. Industry collaboration and systemic changes in federal, state, and local policies should enhance intervention impacts.

Having a Say Matters: The Association Between Home Health Aides' Voice and Job Satisfaction.

Purpose: Despite a rapidly growing need for home health aides (HHAs), turnover rates are high. While this is driven in large part by the demanding nature of their work and low wages, another factor may be that HHAs are often not considered part of the medical team which can leave them feeling unheard by other healthcare professionals. We sought to determine whether this concept, or HHAs' perceived voice, was associated with job satisfaction. Methods and Design: This cross-sectional survey of English- and Spanish-speaking HHAs caring for adults with heart failure (HF) was conducted from June 2020 to July 2021 in New York, NY in partnership with a labor management fund of a large healthcare union that provides benefits and training to HHAs. Voice was assessed with a validated 5-item scale (total score range 5 to 25). Job Satisfaction was assessed with the 5-item Work Domain Satisfaction Scale (total score range 5 to 35). Multivariable linear regression analysis was used to examine the association between voice and job satisfaction. Results: A total of 413 HHAs employed by 56 unique home care agencies completed the survey; they had a mean age of 48 years, 97.6% were female, 60.2% were Hispanic, and they worked as HHAs for a median of 10 years (IQR, 5, 17). They had a median Voice score of 18 (IQR 15-20) and mean job satisfaction score of 26.4 (SD 5.6). Higher levels of voice (1.75 [0.46-3.04]) were associated with greater job satisfaction (p=0.008). When adjusting for Race/Ethnicity, HF training, and HF knowledge, the association between Voice and job satisfaction remained significant ((1.77 [0.40-3.13]). Conclusion: HHAs with a voice in the care of their patients experienced greater job satisfaction. Voice may be an important target for interventions aiming to improve HHAs' retention in the field.

Community practices as coping mechanisms for mental health in Kashmir.

With a steady rise in mental health issues such as depression, anxiety, and post-traumatic stress disorder (PTSD) in Kashmir, the need to address mental health in this region becomes important. This paper reports on traditional and current community mental health coping mechanisms among residents in Kashmir. Six focus group discussions (FGD) were facilitated with key informants. Data were analyzed via a thematic analytic approach. Community coping mechanisms reported include social spaces and shared chore spaces, cultural practices, shrines and religious places, faithealers. These findings demonstrate community strengths that can leverage to build additional coping strategies and resilience among people.

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.

Continuity of Care Versus Language Concordance as an Intervention to Reduce Hospital Readmissions From Home Health Care.

BACKGROUND: Language concordance between health care practitioners and patients have recently been shown to lower the risk of adverse health events. Continuity of care also been shown to have the same impact. OBJECTIVE: The purpose of this paper is to examine the relative effectiveness of both continuity of care and language concordance as alternative or complementary interventions to improve health outcomes of people with limited English proficiency. DESIGN: A multivariable logistic regression model using rehospitalization as the dependent variable was built. The variable of interest was created to compare language concordance and continuity of care. PARTICIPANTS: The final sample included 22,103 patients from the New York City area between 2010 and 2015 who were non-English-speaking and admitted to their home health site following hospital discharge. MEASURES: The odds ratio (OR) average marginal effect (AME) of each included variable was calculated for model analysis. RESULTS: When compared with low continuity of care and high language concordance, high continuity of care and high language concordance significantly decreased readmissions (OR=0.71, 95% CI: 0.62-0.80, P<0.001, AME=-4.95%), along with high continuity of care and low language concordance (OR=0.80, 95% CI: 0.74-0.86, P<0.001, AME=-3.26%). Low continuity of care and high language concordance did not significantly impact readmissions (OR=1.04, 95% CI: 0.86-1.26, P=0.672, AME=0.64%). CONCLUSION: In the US home health system, enhancing continuity of care for those with language barriers may be helpful to address disparities and reduce hospital readmission rates.

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.

A mentored hands-on training model for scaling up implementation and intervention research in India: "connecting the dots".

Despite the high burden of mental disorders in low- and middle-income countries (LMICs), less than 25% of those in need have access to appropriate services, in part due to a scarcity of locally relevant, evidence-based interventions and models of care. To address this gap, researchers from India and the United States and the Indian Council of Medical Research (ICMR) collaboratively developed a "Grantathon" model to provide mentored research training to 24 new principal investigators (PIs). This included a week-long didactic training, a customized web-based data entry/analysis system and a National Coordination Unit (NCU) to support PIs and track process objectives. Outcome objectives were assessed via scholarly output including publications, awards received and subsequent grants that were leveraged. Multiple mentorship strategies including collaborative problem-solving approaches were used to foster single-centre and multicentre research. Flexible, approachable and engaged support from mentors helped PIs overcome research barriers, and the NCU addressed local policy and day-to-day challenges through informal monthly review meetings. Bi-annual formal review presentations by all PIs continued through the COVID-19 pandemic, enabling interim results reporting and scientific review, also serving to reinforce accountability. To date, more than 33 publications, 47 scientific presentations, 12 awards, two measurement tools, five intervention manuals and eight research grants have been generated in an open-access environment. The Grantathon is a successful model for building research capacity and improving mental health research in India that could be adopted for use in other LMICs.

Home Health Care Clinicians' Use of Judgment Language for Black and Hispanic Patients: Natural Language Processing Study.

BACKGROUND: A clinician's biased behavior toward patients can affect the quality of care. Recent literature reviews report on widespread implicit biases among clinicians. Although emerging studies in hospital settings show racial biases in the language used in clinical documentation within electronic health records, no studies have yet investigated the extent of judgment language in home health care. OBJECTIVE: We aimed to examine racial differences in judgment language use and the relationship between judgment language use and the amount of time clinicians spent on home visits as a reflection of care quality in home health care. METHODS: This study is a retrospective observational cohort study. Study data were extracted from a large urban home health care organization in the Northeastern United States. Study data set included patients (N=45,384) who received home health care services between January 1 and December 31, 2019. The study applied a natural language processing algorithm to automatically detect the language of judgment in clinical notes. RESULTS: The use of judgment language was observed in 38% (n=17,141) of the patients. The highest use of judgment language was found in Hispanic (7,167/66,282, 10.8% of all clinical notes), followed by Black (7,010/65,628, 10.7%), White (10,206/107,626, 9.5%), and Asian (1,756/22,548, 7.8%) patients. Black and Hispanic patients were 14% more likely to have notes with judgment language than White patients. The length of a home health care visit was reduced by 21 minutes when judgment language was used. CONCLUSIONS: Racial differences were identified in judgment language use. When judgment language is used, clinicians spend less time at patients' homes. Because the language clinicians use in documentation is associated with the time spent providing care, further research is needed to study the impact of using judgment language on quality of home health care. Policy, education, and clinical practice improvements are needed to address the biases behind judgment language.

An Assessment of the Training Program on Mental Health for Community Health Workers in Kashmir, India.

In recent years mental health has emerged as a major health threat in low income countries like India. In response, mental health care has been integrated into primary health care, in turn creating a rising demand for trained and skillful mental health professionals. This study was conducted in district Budgam (J&K), India with the aim of providing training to community health workers (CHWs) and measuring the change using pre- and post-training evaluations. The pre and post tests were undertaken, assessing changes in mental health literacy at three different points of time: pre-training, post-training, and three month follow-up. Mental health literacy was assessed using the interviewer-administered Mental Health Literacy Survey. The training intervention was a five-day course based on a facilitator's manual developed specifically for community health workers in India. A total of 25 community health workers from rural areas of Budgam District (mostly Integrated Child Development Service supervisors), Health Educators and Anganwadi Workers, were engaged for the study. Findings demonstrate that the training course improved participants' ability to recognize any mental health disorders. There was a clear distinction between the level of awareness pre- and post- training. The results were statistically significant on various domains Ability to recognize disorders (Pre-post P= 0.001), Knowledge of the professional help available (Pre-post p= 0.000), Attitudes that promote the recognition or appropriate help-seeking behavior (Pre-post p= 0.000) (p<0.05). Further follow up after three months was done. The mixed findings from this study, suggesting the training course has potential to improve some aspects of mental health literacy among the CHWs, including their understanding of various mental health problems.

Home Health Care Workers' Interactions with Medical Providers, Home Care Agencies, and Family Members for Patients with Heart Failure.

BACKGROUND: Despite providing frequent care to heart failure (HF) patients, home health care workers (HHWs) are generally considered neither part of the health care team nor the family, and their clinical observations are often overlooked. To better understand this workforce's involvement in care, we quantified HHWs' scope of interactions with clinicians, health systems, and family caregivers. METHODS: Community-partnered cross-sectional survey of English- and Spanish-speaking HHWs who cared for a HF patient in the last year. The survey included 6 open-ended questions about aspects of care coordination, alongside demographic and employment characteristics. Descriptive statistics were performed. RESULTS: Three hundred ninety-one HHWs employed by 56 unique home care agencies completed the survey. HHWs took HF patients to a median of 3 doctor appointments in the last year with 21.9% of them taking patients to ≥ 7 doctor appointments. Nearly a quarter of HHWs reported that these appointments were in ≥ 3 different health systems. A third of HHWs organized care for their HF patient with ≥ 2 family caregivers. CONCLUSIONS: HHWs' scope of health-related interactions is large, indicating that there may be novel opportunities to leverage HHWs' experiences to improve health care delivery and patient care in HF.

SARS-CoV-2 control on a large urban college campus without mass testing.

OBJECTIVE: A small percentage of universities and colleges conducted mass SARS-CoV-2 testing. However, universal testing is resource-intensive, strains national testing capacity, and false negative tests can encourage unsafe behaviors. PARTICIPANTS: A large urban university campus. METHODS: Virus control centered on three pillars: mitigation, containment, and communication, with testing of symptomatic and a random subset of asymptomatic students. RESULTS: Random surveillance testing demonstrated a prevalence among asymptomatic students of 0.4% throughout the term. There were two surges in cases that were contained by enhanced mitigation and communication combined with targeted testing. Cumulative cases totaled 445 for the term, most resulting from unsafe undergraduate student behavior and among students living off-campus. A case rate of 232/10,000 undergraduates equaled or surpassed several peer institutions that conducted mass testing. CONCLUSIONS: An emphasis on behavioral mitigation and communication can control virus transmission on a large urban campus combined with a limited and targeted testing strategy.

The identification of clusters of risk factors and their association with hospitalizations or emergency department visits in home health care.

AIMS: To identify clusters of risk factors in home health care and determine if the clusters are associated with hospitalizations or emergency department visits. DESIGN: A retrospective cohort study. METHODS: This study included 61,454 patients pertaining to 79,079 episodes receiving home health care between 2015 and 2017 from one of the largest home health care organizations in the United States. Potential risk factors were extracted from structured data and unstructured clinical notes analysed by natural language processing. A K-means cluster analysis was conducted. Kaplan-Meier analysis was conducted to identify the association between clusters and hospitalizations or emergency department visits during home health care. RESULTS: A total of 11.6% of home health episodes resulted in hospitalizations or emergency department visits. Risk factors formed three clusters. Cluster 1 is characterized by a combination of risk factors related to "impaired physical comfort with pain," defined as situations where patients may experience increased pain. Cluster 2 is characterized by "high comorbidity burden" defined as multiple comorbidities or other risks for hospitalization (e.g., prior falls). Cluster 3 is characterized by "impaired cognitive/psychological and skin integrity" including dementia or skin ulcer. Compared to Cluster 1, the risk of hospitalizations or emergency department visits increased by 1.95 times for Cluster 2 and by 2.12 times for Cluster 3 (all p < .001). CONCLUSION: Risk factors were clustered into three types describing distinct characteristics for hospitalizations or emergency department visits. Different combinations of risk factors affected the likelihood of these negative outcomes. IMPACT: Cluster-based risk prediction models could be integrated into early warning systems to identify patients at risk for hospitalizations or emergency department visits leading to more timely, patient-centred care, ultimately preventing these events. PATIENT OR PUBLIC CONTRIBUTION: There was no involvement of patients in developing the research question, determining the outcome measures, or implementing the study.

A Qualitative Study of Home Health Aides' Perspectives towards COVID-19 Vaccination.

Home health aides provide care to homebound older adults and those with chronic conditions. Aides were less likely to receive COVID-19 vaccines when they became available. We examined aides' perspectives towards COVID-19 vaccination. Qualitative interviews were conducted with 56 home health aides at a large not-for-profit home care agency in New York City. Results suggested that aides' vaccination decisions were shaped by (1) information sources, beliefs, their health, and experiences providing care during COVID-19; (2) perceived susceptibility and severity of COVID-19; (3) perceived benefits of vaccination including protection from COVID-19, respect from colleagues and patients, and fulfillment of work-related requirements; (4) perceived barriers to vaccination including concerns about safety, efficacy, and side effects; and (5) cues to action including access to vaccination sites/appointments, vaccination mandates, question and answer sessions from trusted sources, and testimonials. Providing tailored information with support to address vaccination barriers could lead to improved vaccine uptake.

Risk of Rehospitalization or Emergency Department Visit is Significantly Higher for Patients who Receive Their First Home Health Care Nursing Visit Later than 2 Days After Hospital Discharge.

OBJECTIVES: This study explored the association between the timing of the first home health care nursing visits (start-of-care visit) and 30-day rehospitalization or emergency department (ED) visits among patients discharged from hospitals. DESIGN: Our cross-sectional study used data from 1 large, urban home health care agency in the northeastern United States. SETTING/PARTICIPANTS: We analyzed data for 49,141 home health care episodes pertaining to 45,390 unique patients who were admitted to the agency following hospital discharge during 2019. METHODS: We conducted multivariate logistic regression analyses to examine the association between start-of-care delays and 30-day hospitalizations and ED visits, adjusting for patients' age, race/ethnicity, gender, insurance type, and clinical and functional status. We defined delays in start-of-care as a first nursing home health care visit that occurred more than 2 full days after the hospital discharge date. RESULTS: During the study period, we identified 16,251 start-of-care delays (34% of home health care episodes), with 14% of episodes resulting in 30-day rehospitalization and ED visits. Delayed episodes had 12% higher odds of rehospitalization or ED visit (OR 1.12; 95% CI: 1.06-1.18) compared with episodes with timely care. CONCLUSIONS AND IMPLICATIONS: The findings suggest that timely start-of-care home health care nursing visit is associated with reduced rehospitalization and ED use among patients discharged from hospitals. With more than 6 million patients who receive home health care services across the United States, there are significant opportunities to improve timely care delivery to patients and improve clinical outcomes.