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. To describe the development, initial psychometric validation, and feasibility of the Hospital-to-Home-Health-Transition Quality (H3TQ) Index to identify patient safety risks. 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). 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%). 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.

The purpose of this study was to understand the limited English proficiency patient experience with health care services in an urban setting in the United States. Through a narrative analysis approach, 71 individuals who spoke either Spanish, Russian, Cantonese, Mandarin, or Korean shared their experiences through semi-structured interviews between 2016 and 2018. Analyses used monolingual and multilingual open coding approaches to generate themes. Six themes illustrated patient experiences and identified sources of structural inequities perpetuating language barriers at the point of care. An important thread throughout all interviews was the sense that the language barrier with clinicians posed a threat to their safety when receiving healthcare, citing an acute awareness of additional risk for harm they might experience. Participants also consistently identified factors they felt would improve their sense of security that were specific to clinician interactions. Differences in experiences were specific to culture and heritage. The findings highlight the ongoing challenges spoken language barriers pose across multiple points of care in the United States' health care system. The multi-language nature of this study and its methodological insights are innovative as most studies have focused on clinicians or patient experiences in a single language.

ObjectivesTo characterize patient portal use among older adults receiving skilled home health (HH) care. DesignRetrospective cohort study. Setting and ParticipantsOlder adults (aged ≥65 years) who received HH care from a large, academic health system between 2017 to 2022 (n = 8409 HH episodes provided to n = 4878 unique individuals). MethodsWe captured individual and HH episode characteristics from the electronic health record and identified specific types and dates of portal use for those with an active patient portal. We calculated the proportion of episodes in which patients engaged in specific patient portal activities (eg, viewing test results, managing appointments, sending messages). We used multivariable logistic regression to model the odds of engaging in each activity as a function of patient and episode characteristics, and charted the timing of patient portal activities across the 60-day HH episode. ResultsThe patient portal was used by older adults in more than half (58%) of the episodes examined. Among those using their portal account during an HH episode, 84% viewed test results, 77% managed an existing appointment, 72% managed medications, and 55% sent a message to a provider. Adjusted odds of portal use were higher among HH patients who were married (aOR: 1.77, P < .001), receiving HH post-COVID pandemic (aOR: 2.73, P < .001), and accessing HH following a hospitalization (aOR: 1.30, P < .001) and lower among those who were Black compared with white (aOR: 0.52, P < .001). Portal use, particularly viewing test results and clinical notes and managing existing appointments, was highest during the first 10 days of an HH episode, especially among patients referred following a hospitalization. Conclusions and ImplicationsHH patients use the patient portal to perform care management tasks and access clinical information. Study findings support opportunities to harness the patient portal to bridge information gaps and care coordination during HH care.

ObjectivesA growing proportion of Medicare home health (HH) patients are “community-entry,” meaning referred to HH without a preceding hospitalization. We sought to identify factors that predict community-entry HH use among older adults to provide foundational information regarding care needs and circumstances that may prompt community-entry HH referral. DesignNationally representative cohort study. Setting and ParticipantsHealth and Retirement Study (HRS) respondents who were aged ≥65 years, community-living, and enrolled in Medicare between 2012 and 2018 (n = 11,425 unique individuals providing 27,026 two-year observation periods). MethodsHRS data were linked with standardized HH patient assessments. Community-entry HH utilization was defined as incurring one or more HH episode with no preceding hospitalization or institutional post-acute care stay (determined via assessment item indicating institutional care within 14 days of HH admission) within 2 years of HRS interview. Weighted, multivariable logistic regression was used to model community-entry HH use as a function of individual, social support, and community characteristics. ResultsThe overall rate of community-entry HH utilization across observation periods was 13.4%. Older adults had higher odds of community-entry HH use if they were Medicaid enrolled [adjusted odds ratio (aOR) = 1.49, P = .001], had fair or poor overall health (aOR = 1.48, P < .001), 3+ activities of daily living limitations (aOR = 1.47, P = .007), and had fallen in the past 2 years (aOR = 1.43, P < .001). Compared with those receiving no caregiver help, individuals were more likely to use community-entry HH if they received family or unpaid help only (aOR = 1.81, P < .001), both family and paid help (aOR = 2.79, P < .001), or paid help only (aOR: 3.46, P < .001). Conclusions and ImplicationsFindings indicate that community-entry HH serves a population with long-term care needs and coexisting clinical complexity, making this an important setting to provide skilled care and prevent avoidable health care utilization. Results highlight the need for ongoing monitoring of community-entry HH accessibility as this service is a key component of home-based care for a high-need subpopulation.

ObjectiveThis 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. DesignRetrospective cohort study. Setting and ParticipantsWe 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. MethodsGuided 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. ResultsOn 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 ImplicationsHHC 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.

BackgroundMore than 50 % of patients with Alzheimer's disease and related dementia (ADRD) remain undiagnosed. This is specifically the case for home healthcare (HHC) patients. ObjectivesThis study aimed at developing HomeADScreen, an ADRD risk screening model built on the combination of HHC patients' structured data and information extracted from HHC clinical notes. MethodsThe study’s sample included 15,973 HHC patients with no diagnosis of ADRD and 8,901 patients diagnosed with ADRD across four follow-up time windows. First, we applied two natural language processing methods, Word2Vec and topic modeling methods, to extract ADRD risk factors from clinical notes. Next, we built the risk identification model on the combination of the Outcome and Assessment Information Set (OASIS-structured data collected in the HHC setting) and clinical notes-risk factors across the four-time windows. ResultsThe top-performing machine learning algorithm attained an Area under the Curve = 0.76 for a four-year risk prediction time window. After optimizing the cut-off value for screening patients with ADRD (cut-off-value = 0.31), we achieved sensitivity = 0.75 and an F1-score = 0.63. For the first-year time window, adding clinical note-derived risk factors to OASIS data improved the overall performance of the risk identification model by 60 %. We observed a similar trend of increasing the model's overall performance across other time windows. Variables associated with increased risk of ADRD were “hearing impairment” and “impaired patient ability in the use of telephone.” On the other hand, being “non-Hispanic White” and the “absence of impairment with prior daily functioning” were associated with a lower risk of ADRD. ConclusionHomeADScreen has a strong potential to be translated into clinical practice and assist HHC clinicians in assessing patients' cognitive function and referring them for further neurological assessment.

Abstract Metal working fluids (MWFs) comprise a complex class of chemicals used in the processing and machining of metal products. A wide variety of additives are used to improve the functionality and longevity of MWFs and include detergents, antioxidants, buffering agents, anti‐foaming agents, and antimicrobials. Importantly, during the use of MWFs, the aerosolized fluids are contaminated by microbial products particularly in the water‐based MWFs. The majority of literature on the adverse human health effects associated with exposure to MWFs can be attributed to mixed exposures to predominantly water‐based fluids, with some straight oil data. Similarly, many of the experimental animal toxicology studies have also examined water‐based fluids and unfortunately, the development and production of MWFs are rapidly changing, and thus health studies have largely been conducted using MWFs that may no longer be in use. This chapter presents the current knowledge on the adverse health effects associated with exposure to water‐based, synthetic, and semi‐synthetic MWFs.

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.

More than 35% of hospice care recipients 65 and older have a dementia diagnosis. Yet family care partners of persons living with dementia report feeling unprepared to address their hospice recipient's changing needs nearing end of life. Hospice clinicians may have unique insight into the knowledge needs of family care partners and strategies for end-of-life dementia caregiving. Semi-structured interviews were conducted with 18 hospice physicians, nurse practitioners, nurses, and social workers. Interview transcripts were deductively analyzed using thematic analysis to examine clinicians' perspectives on gaps and strategies related to family care partner knowledge about end-of-life dementia caregiving. We identified 3 themes related to gaps in family care partners' knowledge: dementia is a progressive, fatal disease; end-of-life symptoms and symptom management in persons living with advanced dementia; and understanding hospice goals and guidelines. Three themes related to clinicians' strategies to increase knowledge included: providing education; teaching strategies to facilitate coping and preparedness for end-of-life care; and communicating with empathy. Clinicians perceive gaps in knowledge specific to dementia and end of life among family care partners. These gaps include a lack of understanding of Alzheimer's symptom progression and strategies to manage common symptoms. Recommendations for approaches to reduce knowledge gaps include providing education and strategies delivered with empathy toward the family care partner experience. Clinicians who work with persons living with dementia receiving hospice care have valuable insights regarding family care partners' gaps in knowledge. Implications on the training and preparation of hospice clinicians working with this care partner population are discussed.

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. 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. 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. 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.