Home Healthcare Clinicians Research Articles

Feasibility of an electronic health record web-based application to optimize medication-related communication between skilled home healthcare clinicians and primary care providers.

Feasibility of an electronic health record web-based application to optimize medication-related communication between skilled home healthcare clinicians and primary care providers.

Developing a clinical decision support framework for integrating predictive models into routine nursing practices in home health care for patients with heart failure.

The healthcare industry increasingly values high-quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations. This study aims to (1) describe important variables associated with a higher risk of ED visits and hospitalizations in HF patients receiving HHC; (2) map data requirements of a clinical decision support (CDS) tool to the exchangeable data standard for integrating a CDS tool into the care of patients with HF; (3) outline a pipeline for developing a real-time artificial intelligence (AI)-based CDS tool. We used patient data from a large HHC organization in the Northeastern US to determine the factors that can predict ED visits and hospitalizations among patients with HF in HHC (9362 patients in 12,223 care episodes). We examined vital signs, HHC visit details (e.g., the purpose of the visit), and clinical note-derived variables. The study identified critical factors that can predict ED visits and hospitalizations and used these findings to suggest a practical CDS tool for nurses. The tool's proposed design includes a system that can analyze data quickly to offer timely advice to healthcare clinicians. Our research showed that the length of time since a patient was admitted to HHC and how recently they have shown symptoms of HF were significant factors predicting an adverse event. Additionally, we found this information from the last few HHC visits before the occurrence of an ED visit or hospitalization were particularly important in the prediction. One hundred percent of clinical demographic profiles from the Outcome and Assessment Information Set variables were mapped to the exchangeable data standard, while natural language processing-driven variables couldn't be mapped due to their nature, as they are generated from unstructured data. The suggested CDS tool alerts nurses about newly emerging or rising risks, helping them make informed decisions. This study discusses the creation of a time-series risk prediction model and its potential CDS applications within HHC, aiming to enhance patient outcomes, streamline resource utilization, and improve the quality of care for individuals with HF. This study provides a detailed plan for a CDS tool that uses the latest AI technology designed to aid nurses in their day-to-day HHC service. Our proposed CDS tool includes an alert system that serves as a guard rail to prevent ED visits and hospitalizations. This tool can potentially improve how nurses make decisions and improve patient outcomes by providing early warnings about ED visits and hospitalizations.

Exploring home healthcare clinicians' needs for using clinical decision support systems for early risk warning.

To explore home healthcare (HHC) clinicians' needs for Clinical Decision Support Systems (CDSS) information delivery for early risk warning within HHC workflows. 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. 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. 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. 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.

Perspectives on supporting Veterans’ social needs during hospital to home health transitions: findings from the Transitions Nurse Program

BackgroundVeterans who need post-acute home health care (HHC) are at risk for adverse outcomes and unmet social needs. Veterans’ social needs could be identified and met by community-based HHC clinicians due to their unique perspective from the home environment, acuity of Veterans they serve, and access to Veterans receiving community care. To understand these needs, we explored clinician, Veteran, and care partner perspectives to understand Veterans’ social needs during the transition from hospital to home with skilled HHC.MethodsQualitative data were collected through individual interviews with Veterans Health Administration (VHA) inpatient & community HHC clinicians, Veterans, and care partners who have significant roles facilitating Veterans’ hospital to home with HHC transition. To inform implementation of a care coordination quality improvement intervention, participants were asked about VHA and HHC care coordination and Veterans’ social needs during these transitions. Interviews were recorded, transcribed, and analyzed inductively using thematic analysis and results were organized deductively according to relevant transitional care domains (Discharge Planning, Transition to Home, and HHC Delivery).ResultsWe conducted 35 interviews at 4 VHA Medical Centers located in Western, Midwestern, and Southern U.S. regions during March 2021 through July 2022. We organized results by the three care transition domains and related themes by VHA, HHC, or Veteran/care partner perspective. Our themes included (1) how social needs affected access to HHC, (2) the need for social needs screening during hospitalization, (3) delays in HHC for Veterans discharged from community hospitals, and (4) a need for closed-loop communication between VHA and HHC to report social needs.ConclusionsHHC is an underexplored space for Veterans social needs detection. While this research is preliminary, we recommend two steps forward from this work: (1) develop closed-loop communication and education pathways with HHC and (2) develop a partnership to integrate a social risk screener into HHC pathways.

Clinician Perception of Likelihood of Death in the Next Year Is Associated With 1-Year Mortality and Hospice Use Among Older Adults Receiving Home Health Care.

Background: Given the complex care needs of older adults receiving home health care (HHC), it is important for HHC clinicians to identify those with limited prognosis who may benefit from a transition to hospice care. Objectives: To assess the association between HHC clinician-identified likelihood of death and (1) 1-year mortality, and (2) hospice use. Methods: Prospective cohort study from the National Health and Aging Trends Study (NHATS) waves 2011-2018, linked to the Outcomes and Assessment Information Set (OASIS) HHC assessment and Medicare data among 915 community-dwelling NHATS respondents. HHC clinician-identified likelihood of death/decline was determined using OASIS item M1034. Multivariable logistic regression was used to assess the association between clinician-identified likelihood of death/decline and 1-year mortality and hospice use. Results: HHC clinicians identified 42% of the sample as at increased risk of decline or death. One year mortality was 22.3% (n = 548), and 15.88% (n = 303) used hospice within 12 months of HHC. HHC clinician-perceived likelihood of death/decline was associated with greater odds of 1-year mortality (odds ratio [OR], 6.57; confidence interval (95% CI), 2.56-16.90) and was associated with greater likelihood of hospice use (OR, 1.61; 95% CI, 1.00-2.62). Conclusion: HHC clinician perception of patients' risk of death or decline is associated with 1-year mortality. A better understanding of HHC patients at high risk for mortality can facilitate improved care planning and identification of homebound older adults who may benefit from hospice.

PATIENT-CLINICIAN RELATIONSHIPS IN HOME HEALTH CARE

Abstract Patient-clinician relationships are fundamental attributes of high-quality home health care (HHC); yet little is known about patient-clinician relationships in HHC (where 5 million Medicare beneficiaries receive care annually). The objective of the study was to describe perspectives of HHC patients and HHC clinicians about patient-clinician relationships in HHC. We conducted a secondary qualitative analysis of semi-structured interviews (n=34) from a completed qualitative study investigating perspectives of older adult HHC patients (or caregivers as proxy) and their HHC clinicians (17 pairs) on discharge preparedness in a large HHC organization in North-Carolina. A conceptual model of patient-clinician relationships guided content analysis of the interview data. HHC patients identified as White (65%) and black (35%). Most HHC patients reported female sex (53%) and average age was 83 years (range= 69-93). Clinicians were registered nurses and physical therapists. Across the patient-clinician pairs, HHC patients valued relationships with clinicians with shared commonalities and those who provided reciprocal informational exchange and respected their autonomy. HHC clinicians valued relationships in which they felt helpful and respected as a healthcare professional. Relational conflicts arose when there was discordance in expectations of care (e.g., type of HHC services provided). Conflicts also arose when organizational constraints, such as disruptive scheduling, limited HHC visit time, and when limited continuity of care prevented the formation of patient-clinician relationships. Relational conflicts and organizational constraints influence patient-clinician relationships in HHC. Multi-level interventions (targeting modifiable factors at the patient, clinician, and organizational levels) are needed to improve the patient-clinician relationships and the quality of HHC.

PERCEPTIONS OF HOME HEALTH AIDES (HHA) CARING FOR PERSONS LIVING WITH DEMENTIA (PLWD) ABOUT ADOPTION OF TELEHEALTH

Abstract Home healthcare agencies serve a large and growing population of Persons living with Dementia (PLWD). The COVID-19 pandemic led to rapid adoption and use of telehealth services in the delivery of home healthcare, allowing patients to visit with home healthcare clinicians remotely using virtual technology. Yet, concerns remain about feasibility of telehealth for PLWD on HHC, who largely depend on home health aides to communicate their care concerns with the health care teams. We interviewed 25 HHAs to PLWD between June and August 2020 about their experiences with telehealth as part of a larger study focused on HHA informed care plans for PLWD. Interviews were recorded, transcribed, translated and analyzed using conventional content analysis. We interviewed 25 HHAs employed by 4 unique home healthcare agencies. HHAs had a mean age of 49.8 (± 9.1), 24 (97%) female, 11 (44%) Black, 12 (48%) Hispanic. Twelve HHAs were interviewed in Spanish. The main themes identified were: (1) preference for telehealth platforms that include video conferencing to enhance human interactions, (2) preference for telehealth as a supplement, not substitute, for nursing visits, (3) additional burden of using the tablet or computer while care for PLWD and (4) concerns about inadequate training needed to use telehealth. HHAs expressed concerns about the need to not substitute in person home visits with Telehealth. As home healthcare agencies consider best approaches to integrate telehealth into their care delivery models, communication with HHAs remains key to develop strategies that prioritize the care needs of PLWD.

How to Deprescribe Potentially Inappropriate Medications During the Hospital-to-Home Transition: Stakeholder Perspectives on Essential Tasks

PurposeNearly all older patients receiving postacute home health care (HHC) use potentially inappropriate medications (PIMs) that carry a risk of harm. Deprescribing can reduce and optimize the use of PIMs, yet it is often not conducted among HHC patients. The objective of this study was to gather perspectives from patient, practitioner, and HHC clinician stakeholders on tasks that are essential to postacute deprescribing in HHC. MethodsA total of 44 stakeholders, including 14 HHC patients, 15 practitioners (including 9 primary care physicians, 4 pharmacists, 1 hospitalist, and 1 nurse practitioner), and 15 HHC nurses, participated. The stakeholders were from 12 US states, including New York (n = 29), Colorado (n = 2), Connecticut (n = 1), Illinois (n = 2), Kansas (n = 2), Massachusetts (n = 1), Minnesota (n = 1), Mississippi (n = 1), Nebraska (n = 1), Ohio (n = 1), Tennessee (n = 1), and Texas (n = 2). First, individual interviews were conducted by experienced research staff via video conference or telephone. Second, the study team reviewed all interview transcripts and selected interview statements regarding stakeholders’ suggestions for important tasks needed for postacute deprescribing in HHC. Third, concept mapping was conducted in which stakeholders sorted and rated selected interview statements regarding importance and feasibility. A content analysis was conducted of data collected in the individual interviews, and a mixed-method analysis was conducted of data collected in the concept mapping. FindingsFour essential tasks were identified for postacute deprescribing in HHC: (1) ongoing review and assessment of medication use, (2) patent-centered and individualized plan of deprescribing, (3) timely and efficient communication among members of the care team, and (4) continuous and tailored medication education to meet patient needs. Among these tasks, developing patient-centered deprescribing considerations was considered the most important and feasible, followed by medication education, review and assessment of medication use, and communication. ImplicationsDeprescribing during the transition of care from hospital to home requires the following: continuous medication education for patients, families, and caregivers; ongoing review and assessment of medication use; patient-centered deprescribing considerations; and effective communication and collaboration among the primary care physician, HHC nurse, and pharmacist.

HomeADScreen: Developing Alzheimer's disease and related dementia risk identification model in home healthcare

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.

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

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. 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 60days) before an ED visit or hospitalization. Risk prediction performances were compared using recall, precision, accuracy, F1, and area under the receiver operating curve (AUC). The best-performing model was built using a combination of all 7 sets of variables and the time window of 4days before an ED visit or hospitalization (AUC = 0.89 and F1 = 0.69). This prediction model suggests that HHC clinicians can identify patients with HF at risk for visiting the ED or hospitalization within 4days before the event, allowing for earlier targeted interventions.

Development and Testing of the Palliative Care-Related Knowledge, Attitudes, & Confidence (PC-KAC) Questionnaires for Home Healthcare Clinicians, Patients, and Caregivers in the United States. (Sch423)

Development and Testing of the Palliative Care-Related Knowledge, Attitudes, & Confidence (PC-KAC) Questionnaires for Home Healthcare Clinicians, Patients, and Caregivers in the United States. (Sch423)

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

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. 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. 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. 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. 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.

Identifying unmet needs of older adults transitioning from home health care to independence at home: A qualitative study

Health care practices to prepare older adults and their family caregivers for transitions from home health care (HHC) to independence at home are rarely studied. The objective of this multiple case study was to describe HHC patient and clinician perceptions of unmet needs after HHC discharge and recommendations to address them in future research. In this qualitative study, data were collected using chart-reviews and semi-structured interviews with paired patients (or caregivers as proxy) and HHC clinicians (N=17 pairs). We identified three themes: (1) low patient and caregiver engagement in care planning increased risk for preventable health events after HHC discharge, (2) limited continuity of care restricted patient and caregiver access to community-based services, and (3) gaps in patient and caregiver education influenced independent care of chronic illnesses after discharge. Findings suggest opportunities to improve care practices to prepare older adults and their caregivers for transitions from HHC to independence at home.

UNMET TRANSITIONAL CARE NEEDS OF OLDER ADULTS DISCHARGED FROM HOME HEALTH CARE: A QUALITATIVE NEEDS ASSESSMENT

Abstract Transitional care is widely recognized as a set of time-limited services to support older adults during transfers between settings and providers of care; however, little is known about services that prepare older adults and their caregivers for transitions from Home Health Care (HHC) to independent self-care at home. The objective of this study was to describe HHC patients and clinician perceptions of unmet needs after HHC discharge and recommendations to address them in future research. A multiple case-study design was used in a single large HHC organization in North Carolina. Data were collected using chart reviews of HHC records and semi-structured interviews with paired patients (or caregivers as proxy) and HHC clinicians (Nf17 pairs). A transitional care intervention model was used as a conceptual framework to guide framework analysis of interview transcripts. Most patients were White (65%) and female (53%) with mean age of 83 years. Clinicians were Registered nurses and Physical therapists. Across cases, 17 patient and clinicians pairs described three unmet needs: (1)skills for symptom management; (2)community-based support for transportation, food, social engagement, and health services; (3)in-home support to assist with safety, and activities of daily living. HHC patients recommended new services while clinicians emphasized the need for resources to improve their capacity to prepare patients for discharge. These findings will inform an innovative adaptation of transitional care and other supports to prepare older adults and caregivers for transitions from HHC to independent self-care at home. Future research should explore adding transitional care services to address these needs.

MEDICATIONS ASSOCIATED WITH GERIATRIC SYNDROMES AND HOSPITALIZATION RISK IN HOME HEALTHCARE PATIENTS

Abstract Polypharmacy is common in the home health care (HHC) setting. This study examined the prevalence, predictors, and impact of medications associated with geriatric syndromes (MAGS) use on subsequent hospitalization in HHC patients. Data from the HHC electronic medical records, the Outcome and Assessment Information Set (OASIS), and Medicare HHC claims of 6,882 adults ≥ 65 years old receiving HHC from a large, non-profit HH agency in New York State in CY 2019 were used. MAGS use was identified from active medications reconciled during HHC visits and defined as total count and in quartiles. Hospitalization during the HHC episode was operationalized as a time-to-event variable. Regression analyses were conducted to identify predictors of MAGS use, and survival analyses were conducted to examine the association between MAGS use and hospitalization. Nearly all (98%) of the HHC patients used at least one MAGS and 41% of all active medications were MAGS. A higher MAGS count was found among HHC patients who were non-white, community-referred, with more comorbidities, depressive symptoms, and functional limitations. A higher MAGS count was also related to increased risk for hospitalization. Moreover, higher quartiles of MAGS use combined with having ≥10 diagnoses predicted a 2.5-fold increase in hospitalization risk, relative to the lowest quartile of MAGS use and having < 10 diagnoses. In conclusion, over 40% of medications taken by HHC patients are MAGS, which, along with multimorbidity, increased hospitalization risk. HHC clinicians should identify MAGS use to inform deprescribing discussion with patients and their prescribers.

A DATA-BASED PROPOSITION FOR THE CREATION OF NEW ICD-10 DIAGNOSIS CODES FOR POST-ACUTE SEPSIS SURVIVORS

Abstract Sepsis survivors have the second highest readmission rate among Medicare beneficiaries, next to heart failure. I-TRANSFER is an implementation science study to improve transitions and reduce readmissions among sepsis survivors transitioning from acute to home health care (HHC). A total of 63 semi-structured interviews were conducted with stakeholders among 12 hospitals and 5 affiliated home health agencies (HHAs). The purpose of this secondary analysis was to: 1) examine how the sepsis diagnosis is reflected in HHC documentation, 2) identify barriers in sepsis information transfer to HHC, 3) recommend a documentation strategy to enhance information transfer and HHC documentation. We analyzed the diagnosis coding within a national OASIS dataset and eight I-TRANSFER interviews with hospitalists, documentation specialists, and HHC coders. Findings include: a) sepsis diagnoses were nearly invisible in HHC records being documented for only 10% of 165,000 sepsis survivors transitioned to HHC, b) sepsis information in referral documentation can be unclear to HHC coders, c) the lack of sepsis diagnosis documentation might make HHC clinicians unaware of the patient’s risk for readmission, d) HHC coders recommended improved language in the acute care discharge summary to link the need for HHC to sepsis, thereby supporting the use of ICD-10 sepsis ‘A’ codes in HHC. The use of terms, such as “History of Sepsis” or “Sepsis Resolved,” leads to HHC using non-specific codes, thus is not recommended. We highlight the need for new ICD-10 codes for “Sepsis Aftercare” and “Post-Sepsis Syndrome” to clearly communicate and document the needs of sepsis survivors.

Medications Associated With Geriatric Syndromes (MAGS) and Hospitalization Risk in Home Health Care Patients.

Polypharmacy is common in home health care (HHC). This study examined the prevalence of medications associated with geriatric syndromes (MAGS), its predictors, and association with subsequent hospitalization in HHC. Analysis of HHC electronic medical records, the Outcome and Assessment Information Set (OASIS), and Medicare HHC claims. A total of 6882 adults ≥65years old receiving HHC in 2019 from a large, not-for-profit home health agency serving multiple counties in New York State. MAGS use was identified from active medications reconciled during HHC visits (HHC electronic medical records). MAGS use was operationalized as count and in quartiles. Hospitalization during the HHC episode was operationalized as a time-to-event variable (ie, number of days from HHC admission to hospitalization). We used regression analyses to identify predictors of MAGS use, and survival analyses to examine the association between MAGS and hospitalization. Nearly all (98%) of the HHC patients used at least 1 MAGS and 41% of all active medications used by the sample were MAGS. More MAGS use was found in HHC patients who were community-referred, taking more medications, and having more diagnoses, depressive symptoms, and functional limitations. Adjusted for covariates, higher MAGS quartiles were not independently associated with the risk of hospitalization, but higher MAGS quartiles combined with multimorbidity (ie, having ≥10 diagnoses) were associated with a 2.3-fold increase in hospitalization risk (hazard ratio 2.24; 95% confidence interval: 1.61-3.13; P < .001), relative to the lowest quartile of MAGS use and having <10 diagnoses. More than 40% of medications taken by HHC patients are MAGS. Multimorbidity and MAGS use collectively increased the risk of hospitalization by up to 2.3 times. HHC clinicians should carefully review patients' medications and use information about MAGS to facilitate discussion about deprescribing with patients and their prescribers.

A Description of Persons With Alzheimer Disease and Related Dementias Receiving Home Health Care: A National Analysis.

The end-of-life period of individuals with Alzheimer disease and related dementias receiving home health care (HHC) is understudied. We sought to describe characteristics of HHC patients with Alzheimer disease and related dementias at risk of death within a year, based on clinician assessment. We conducted a secondary data analysis of a 5% random sample of the Outcome and Assessment Information Set data set for the year 2017. We used Outcome and Assessment Information Set-C item M1034 to identify HHC patients with overall status of progressive condition leading to death within a year. Multivariable logistic regression model was used to examine the association between sociodemographic, functional, clinical, and caregiving factors and likelihood of decline leading to death within a year, as identified by HHC clinicians. Clinician perception of decline leading to death within a year was higher for Whites (vs Blacks or Hispanics) (odds ratio [OR], 0.74 [95% confidence interval (CI), 0.69-0.80], and OR, 0.63 [95% CI, 0.57-0.69], respectively). Factors associated with increased odds of decline leading to death within a year included daily pain (OR, 1.11 [95% CI, 1.06-1.17]), anxiety daily or more often (OR, 1.58 [95% CI, 1.49-1.67]), shortness of breath (OR, 1.45 [95% CI, 1.34-1.57]), use of oxygen (OR, 1.60 [95% CI, 1.52-1.69]), disruptive behavior (OR, 1.26 [95% CI, 1.20-1.31]), and feeding difficulty (OR, 2.25 [95% CI, 2.09-2.43]). High symptom burden exists among HHC patients with Alzheimer disease and related dementias identified to have a status of decline leading to death within a year.

"The Crossover to Hospice": Perspectives of Home Healthcare Nurses and Social Workers.

Although home healthcare(HHC) clinicians increasingly provide care to a homebound population with advanced illness and high symptom burden, we know little about how HHC clinicians navigate discussions about hospice with patients and families in this setting. We sought to explore perspectives on transition from HHC to hospice among HHC nurses and social workers. PQualitative study using semi-structured interviews and thematic analysis. Fifteen nurses and 3 Social workers participated in the study. Four main themes emerged from the interviews: (1) Regulatory Forces of Hospice and HHC; (2) Structure of HHC; (3) Individual beliefs-Hospice means giving up; and (4) Dynamics of Communication in HHC to Facilitate Transitions to Hospice. Introducing the option of hospice to patients and families nearing end-of-life in the HHC setting is complex and challenging. Facilitators of hospice discussions in the HHC setting include interdisciplinary team-based clinical review, clinical decision support tools to identify patients who are hospice-eligible, and staff training. These factors provide targets for future interventions.

Peristomal Complications.

Patients with new ostomies are being discharged from the hospital without enough hands-on training for ostomy care. Maintaining healthy peristomal skin is one of the greatest challenges for patients with an ostomy. Unfortunately, peristomal complications are very common and affect quality of life. It is important that home healthcare clinicians maintain competency in ostomy care, so they have the knowledge and skills necessary to prevent and treat peristomal complications. This article focuses on peristomal skin assessment as well as prevention and treatment of common peristomal complications.