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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.

Patients with heart failure (HF) who actively engage in their own self-management have better outcomes. Extracting data through natural language processing (NLP) holds great promise for identifying patients with or at risk of poor self-management.To identify home health care (HHC) patients with HF who have poor self-management using NLP of narrative notes, and to examine patient factors associated with poor self-management.An NLP algorithm was applied to extract poor self-management documentation using 353,718 HHC narrative notes of 9,710 patients with HF. Sociodemographic and structured clinical data were incorporated into multivariate logistic regression models to identify factors associated with poor self-management.There were 758 (7.8%) patients in this sample identified as having notes with language describing poor HF self-management. Younger age (OR 0.982, 95% CI 0.976-0.987, p .001), longer length of stay in HHC (OR 1.036, 95% CI 1.029- 1.043, p .001), diagnosis of diabetes (OR 1.47, 95% CI 1.3-1.67, p .001) and depression (OR 1.36, 95% CI 1.09-1.68, p .01), impaired decision-making (OR 1.64, 95% CI 1.37-1.95, p .001), smoking (OR 1.7, 95% CI 1.4-2.04, p .001), and shortness of breath with exertion (OR 1.25, 95% CI 1.1-1.42, p .01) were associated with poor self-management.Patients with HF who have poor self-management can be identified from the narrative notes in HHC using novel NLP methods. Meaningful information about the self-management of patients with HF can support HHC clinicians in developing individualized care plans to improve self-management and clinical outcomes.

BACKGROUND: About one in five patients receiving home health care (HHC) services are hospitalized or visit an emergency department (ED) during a home care episode. Early identification of patients at risk can prevent these negative outcomes. However, risk indicators, including language in clinical notes that indicate a concern about a patient, are often hidden in narrative documentation throughout their HHC episode. OBJECTIVE: To develop an automated natural language processing (NLP) algorithm to identify concerning language indicative of HHC patient risk of hospitalizations or ED visits. METHODS: This study used the Omaha System—a standardized nursing terminology that describes problems/signs/symptoms that can occur in the community setting. First, five HHC experts iteratively reviewed the Omaha System and identified concerning concepts indicative of HHC patient risk of hospitalizations or ED visits. Next, we developed and tested an NLP algorithm to identify these concerning concepts in HHC clinical notes automatically. The resulting NLP algorithm was applied on a large subset of narrative notes (2.3 million notes) documented for 66,317 unique patients (n = 87,966 HHC episodes) admitted to one large HHC agency in the Northeast United States between 2015 and 2017. RESULTS: A total of 160 Omaha System signs/symptoms were identified as concerning concepts for hospitalizations or ED visits in HHC. These signs/symptoms belong to 31 of the 42 available Omaha System problems. Overall, the NLP algorithm showed good performance in identifying concerning concepts in clinical notes. More than 18% of clinical notes were detected as having at least one concerning concept, and more than 90% of HHC episodes included at least one Omaha System problem. The most frequently documented concerning concepts were pain, followed by issues related to neuro-musculoskeletal function, circulation, mental health, and communicable/infectious conditions. CONCLUSION: Our findings suggest that concerning problems or symptoms that could increase the risk of hospitalization or ED visit were frequently documented in narrative clinical notes. NLP can automatically extract information from narrative clinical notes to improve our understanding of care needs in HHC. Next steps are to evaluate which concerning concepts identified in clinical notes predict hospitalization or ED visit.

Objective This article reports a systematic review of studies containing development and validation of models predicting postacute care destination after adult inpatient hospitalization, summarizes clinical populations and variables, evaluates model performance, assesses risk of bias and applicability, and makes recommendations to reduce bias in future models. Materials and Methods A systematic literature review was conducted following PRISMA guidelines and the Cochrane Prognosis Methods Group criteria. Online databases were searched in June 2020 to identify all published studies in this area. Data were extracted based on the CHARMS checklist, and studies were evaluated based on predictor variables, validation, performance in validation, risk of bias, and applicability using the Prediction Model Risk of Bias Assessment Tool (PROBAST) tool. Results The final sample contained 28 articles with 35 models for evaluation. Models focused on surgical (22), medical (5), or both (8) populations. Eighteen models were internally validated, 10 were externally validated, and 7 models underwent both types. Model performance varied within and across populations. Most models used retrospective data, the median number of predictors was 8.5, and most models demonstrated risk of bias. Discussion and Conclusion Prediction modeling studies for postacute care destinations are becoming more prolific in the literature, but model development and validation strategies are inconsistent, and performance is variable. Most models are developed using regression, but machine learning methods are increasing in frequency. Future studies should ensure the rigorous variable selection and follow TRIPOD guidelines. Only 14% of the models have been tested or implemented beyond original studies, so translation into practice requires further investigation.

Background: Urinary incontinence is prevalent among patients receiving home hospice and presents multiple care management challenges for nurses and family caregivers. Aim: This study sought to understand how urinary incontinence influences the psychosocial care of patients receiving home hospice and the strategies that nurses employ to maximize patient and family comfort. Design: Qualitative descriptive study using semi-structured interviews. Setting/participants: Nurses employed at a large not-for-profit hospice agency in New York City. Results: Analyses of 32 interviews revealed three primary themes. First, nurses considered urinary incontinence to be associated with multiple psychosocial issues including embarrassment for patients and caregiver burden. Second, nurses described urinary incontinence as a threat to patient dignity and took steps to preserve their continence function. Third, nurses assisted patients and their families to cope with urinary incontinence through normalization, reframing incontinence as part of the disease process, mobilizing caregiving assistance, and encouraging use of continence supplies such as diapers and liners. Conclusion: Urinary incontinence influences the psychosocial care of patients receiving home hospice and nurses employ strategies to maximize patient and family comfort. Additional research is needed to examine the psychosocial benefits of facilitated discussions with patients and family members about incontinence, provision of caregiving support, and distribution of comprehensive incontinence supplies to patients with fewer resources.

Context To date, no studies have characterized the impacts of urinary incontinence (UI) at the end of life in the home hospice (HH) setting. UI is highly prevalent at the end of life and adversely affects quality of life. Objectives To characterize HH nurses’ perspectives on UI in HH patients. Methods We conducted a qualitative descriptive study of interviews between HH nurses and the study investigator. Thirty-two interviews with HH nurses were transcribed and analyzed. Nurses were mostly female, college-educated, and had several years of experience in HH nursing. Results We identified findings in four major themes: 1) HH nurses' definition and identification of UI, 2) the absence of formal guidelines for diagnosing UI in HH patients, 3) UI's adverse effect on HH patients and their families, and 4) the lack of standardized guidelines for the management of UI in the HH setting. We found that there was a general lack of clarity on the subtypes of UI and no standardized guidelines for management of UI in the HH setting. Nurses reported that UI was bothersome to HH patients and their caregivers, citing patient discomfort, loss of dignity, and additional labor burden as reasons for this. Management strategies for UI lacked standardization. Conclusion UI is a prevalent and debilitating condition in HH patients. There is a need for studies to further characterize the impacts of UI on HH patients and their caregivers. Formal training on UI subtypes and management is needed to facilitate proper documentation, research, and improve patient outcomes.

BACKGROUND The COVID-19 pandemic increased the importance of technology for all Americans, including older adults. Although a few studies have indicated that older adults might have increased their technology use during the COVID-19 pandemic, further research is needed to confirm these findings, especially among different populations, and using validated surveys. In particular, research on changes in technology use among previously hospitalized community-dwelling older adults, especially those with physical disability, is needed because older adults with multimorbidity and hospital associated deconditioning were a population greatly impacted by COVID-19 and related distancing measures. Obtaining knowledge regarding previously hospitalized older adults’ technology use, before and during the pandemic, could inform the appropriateness of technology-based interventions for vulnerable older adults. OBJECTIVE In this paper, we 1) described changes in older adult technology-based communication, technology-based phone use, and technology-based gaming during the COVID-19 pandemic, compared to before the COVID-19 pandemic and 2) tested whether technology use moderated the association between changes in in-person visits and well-being, controlling for covariates. METHODS Between December 2020 and January 2021 we conducted a telephone-based objective survey with 60 previously hospitalized older New Yorkers with physical disability. We measured technology-based communication through three questions pulled from the National Health and Aging Trends Study COVID-19 Questionnaire. We measured technology-based smart phone use and technology-based video gaming through the Media Technology Usage and Attitudes Scale. We used paired t tests and interaction models to analyze survey data. RESULTS This sample of previously hospitalized older adults with physical disability consisted of 60 participants, 63.3% of whom identified as female, 50.0% of whom identified as White, and 63.8% of whom reported an annual income of $25,000 or less. This sample had not had physical contact (such as friendly hug or kiss) for a median of 60 days and had not left their home for a median of 2 days. The majority of older adults from this study reported using the internet, owning smart phones, and nearly half learned a new technology during the pandemic. During the pandemic, this sample of older adults significantly increased their technology-based communication (mean difference=.74, P=.003), smart phone use (mean difference=2.9, P=.016), and technology-based gaming (mean difference=.52, P=.030). However, this technology use during the pandemic did not moderate the association between changes in in-person visits and well-being, controlling for covariates. CONCLUSIONS These study findings suggest that previously hospitalized older adults with physical disability are open to using or learning technology, but that technology use might not be able to replace in-person social interactions. Future research might explore the specific components of in-person visits that are missing in virtual interactions, and if they could be replicated in the virtual environment, or through other means.

Objectives Illustrate patterns of patient problem information received and documented across the home health care (HHC) admission process and offer practice, policy, and health information technology recommendations to improve information transfer. Design Observational field study. Setting and Participants Three diverse HHC agencies using different commercial point-of-care electronic health records (EHRs). Six nurses per agency each admitted 2 patients (36 total). Methods Researchers observed the admission process and photographed documents and EHR screens across 3 phases: referral, assessment, and plan of care (POC). To create a standardized data set, we mapped terms within medical diagnoses, signs, symptoms, and Problems to 5 of the 42 Omaha System Problem Classification Scheme problem terms. This created 180 problem pattern cases (5 problem patterns per patient). Results Each pattern of problem information being present or absent was observed. In 52 cases (28.9%), a problem did not appear. In 36 cases (20%), the problem appeared in all 3 phases. In 46 cases (25.6%), the problem appeared in referral and/or assessment phases and not on the POC. Conversely, in 37 cases (20.5%), the problem appeared in referral or assessment phases and on the POC. In 9 cases (5%), the problem only appeared on the POC. Within the EHRs, there were no rationale fields to clarify including Problems or not and no problem status fields to identify active, resolved, or potential ones. Conclusions and Implications Diagnosis or problem information transferred from the referral source or gathered during an in-home assessment did not appear in the POC. Because of the EHR structure, clinicians could not identify inactive problem or problem priority. Documentation or mapping of a structured problem list using a standardized interprofessional terminology such as the Omaha System coupled with identification of rationale could support the documentation of problem status and priority and reduce information loss.

Background The electronic health record (EHR) has become increasingly ubiquitous. At the same time, health professionals have been turning to this resource for access to data that is needed for the delivery of health care and for clinical research. There is little doubt that the EHR has made both of these functions easier than earlier days when we relied on paper-based clinical records. Coupled with modern database and data warehouse systems, high-speed networks, and the ability to share clinical data with others are large number of challenges that arguably limit the optimal use of the EHR Objectives Our goal was to provide an exhaustive reference for those who use the EHR in clinical and research contexts, but also for health information systems professionals as they design, implement, and maintain EHR systems. Methods This study includes a panel of 24 biomedical informatics researchers, information technology professionals, and clinicians, all of whom have extensive experience in design, implementation, and maintenance of EHR systems, or in using the EHR as clinicians or researchers. All members of the panel are affiliated with Penn Medicine at the University of Pennsylvania and have experience with a variety of different EHR platforms and systems and how they have evolved over time. Results Each of the authors has shared their knowledge and experience in using the EHR in a suite of 20 short essays, each representing a specific challenge and classified according to a functional hierarchy of interlocking facets such as usability and usefulness, data quality, standards, governance, data integration, clinical care, and clinical research. Conclusion We provide here a set of perspectives on the challenges posed by the EHR to clinical and research users.

Information does not yet exist on the characteristics and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19) who are discharged to the home setting. Using rich data from home health care (HHC), the authors describe characteristics of COVID-19 survivors upon admission to HHC, the home visits they received, and the extent of recovery among those discharged from HHC. They also profile the risk factors associated with rehospitalization and death., Background: Little is known about recovery from coronavirus disease 2019 (COVID-19) after hospital discharge. Objective: To describe the home health recovery of patients with COVID-19 and risk factors associated with rehospitalization or death. Design: Retrospective observational cohort. Setting: New York City. Participants: 1409 patients with COVID-19 admitted to home health care (HHC) between 1 April and 15 June 2020 after hospitalization. Measurements: Covariates and outcomes were obtained from the mandated OASIS (Outcome and Assessment Information Set). Cox proportional hazard models were used to estimate the hazard ratio (HR) of risk factors associated with rehospitalization or death. Results: After an average of 32 days in HHC, 94% of patients were discharged and most achieved statistically significant improvements in symptoms and function. Activity-of-daily-living dependencies decreased from an average of 6 (95% CI, 5.9 to 6.1) to 1.2 (CI, 1.1 to 1.3). Risk for rehospitalization or death was higher for male patients (HR, 1.45 [CI, 1.04 to 2.03]); White patients (HR, 1.74 [CI, 1.22 to 2.47]); and patients with heart failure (HR, 2.12 [CI, 1.41 to 3.19]), diabetes with complications (HR, 1.71 [CI, 1.17 to 2.52]), 2 or more emergency department visits in the past 6 months (HR, 1.78 [CI, 1.21 to 2.62]), pain daily or all the time (HR, 1.46 [CI, 1.05 to 2.05]), cognitive impairment (HR, 1.49 [CI, 1.04 to 2.13]), or functional dependencies (HR, 1.09 [CI, 1.00 to 1.20]). Eleven patients (1%) died, 137 (10%) were rehospitalized, and 23 (2%) remain on service. Limitations: Care was provided by 1 home health agency. Information on rehospitalization and death after HHC discharge is not available. Conclusion: Symptom burden and functional dependence were common at the time of HHC admission but improved for most patients. Comorbid conditions of heart failure and diabetes, as well as characteristics present at admission, identified patients at greatest risk for an adverse event. Primary Funding Source: No direct funding.

Background The COVID-19 pandemic increased the importance of technology for all Americans, including older adults. Although a few studies have indicated that older adults might have increased their technology use during the COVID-19 pandemic, further research is needed to confirm these findings, especially among different populations, and using validated surveys. In particular, research on changes in technology use among previously hospitalized community-dwelling older adults, especially those with physical disability, is needed because older adults with multimorbidity and hospital associated deconditioning were a population greatly impacted by COVID-19 and related distancing measures. Obtaining knowledge regarding previously hospitalized older adults’ technology use, before and during the pandemic, could inform the appropriateness of technology-based interventions for vulnerable older adults. Objective In this paper, we 1) described changes in older adult technology-based communication, technology-based phone use, and technology-based gaming during the COVID-19 pandemic, compared to before the COVID-19 pandemic and 2) tested whether technology use moderated the association between changes in in-person visits and well-being, controlling for covariates. Methods Between December 2020 and January 2021 we conducted a telephone-based objective survey with 60 previously hospitalized older New Yorkers with physical disability. We measured technology-based communication through three questions pulled from the National Health and Aging Trends Study COVID-19 Questionnaire. We measured technology-based smart phone use and technology-based video gaming through the Media Technology Usage and Attitudes Scale. We used paired t tests and interaction models to analyze survey data. Results This sample of previously hospitalized older adults with physical disability consisted of 60 participants, 63.3% of whom identified as female, 50.0% of whom identified as White, and 63.8% of whom reported an annual income of $25,000 or less. This sample had not had physical contact (such as friendly hug or kiss) for a median of 60 days and had not left their home for a median of 2 days. The majority of older adults from this study reported using the internet, owning smart phones, and nearly half learned a new technology during the pandemic. During the pandemic, this sample of older adults significantly increased their technology-based communication (mean difference=.74, P=.003), smart phone use (mean difference=2.9, P=.016), and technology-based gaming (mean difference=.52, P=.030). However, this technology use during the pandemic did not moderate the association between changes in in-person visits and well-being, controlling for covariates. Conclusions These study findings suggest that previously hospitalized older adults with physical disability are open to using or learning technology, but that technology use might not be able to replace in-person social interactions. Future research might explore the specific components of in-person visits that are missing in virtual interactions, and if they could be replicated in the virtual environment, or through other means.

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.

BACKGROUND Hospice patients with dementia are at increased risk for live discharge and long lengths of stay (>180 days), causing patient and family caregiver stress and burden. The location and timing of clinician visits are important factors influencing whether someone dies as expected, in hospice, or experiences a live discharge or long length of stay. OBJECTIVE Examine how home hospice and nurse visit frequency relate to dying in hospice within the Medicare-intended 6-month period. DESIGN Retrospective cohort study. SETTING Non-profit hospice agency. PARTICIPANTS Three thousand eight hundred and thirty seven patients with dementia who received hospice services from 2013 to 2017. METHODS Multivariable survival analyses examined the effects of receiving home hospice (vs. nursing home) and timing of nurse visits on death within 6 months of hospice enrollment, compared to live discharge or long length of stay. Models adjust for relevant demographic and clinical factors. RESULTS Thirty-nine percent (39%) of patients experienced live discharge or long length of stay. Home hospice patients were more likely to experience live discharge or long length of stays (HR for death: 0.77, 95%CI: 0.69-0.86, p

Unmet needs for family caregiver assistance threaten patient outcomes during Medicare home health care (HHC). Sepsis survivors represent a growing proportion of the HHC patient population, but little is known regarding their risk for unmet caregiving needs. We describe prevalence and underlying cause of unmet caregiving needs for sepsis survivors receiving HHC, using HHC patient assessment data for 85,851 older sepsis survivors receiving post-acute HHC in 2013–2014. Unmet caregiving needs were most common for assistance with Activities of Daily Living (ADLs) (28%) and medication administration (27%). Caregivers’ need for training accounted for more than three-fourths of all unmet caregiving needs. Those who experienced decline/no improvement in cognitive function were more likely to experience unmet caregiving needs. Findings highlight the potential value of expanding family caregiver training to improve HHC outcomes for sepsis survivors and indicate that caregivers of sepsis survivors with poor cognitive function may benefit most.

Objective Patient transitions into home health care (HHC) often occur without the transfer of information needed for critical clinical decisions and the plan of care. Owing to a lack of universally implemented standards, there is wide variation in information transfer. We sought to characterize missing information at HHC admission. Materials and Methods We conducted a mixed methods study with 3 diverse HHC agencies. Focus groups with nurses at each agency identified what information supports patient care decisions at admission. Thirty-six in-home admissions with associated documentation review determined the available information. To inform information standards development for the HHC admission process, we compared the types of information desired and available to an international standard for transitions in care information, the Continuity of Care Document (CCD) enhanced with Office of the National Coordinator for Healthcare Information Technology summary terms (CCD/S). Results Three-quarters of the items from the focus groups mapped to the CCD/S. Regarding available information at admission, no observation included all CCD/S data items. While medication information was needed and often available for 4 important decisions, concepts related to patient medication self-management appeared in neither the CCD/S nor the admission documentation. Discussion The CCD/S mostly met HHC nurses’ information needs and is recommended to begin to fill the current information gap. Electronic health record recommendations include use of a data standard: the CCD or the proposed, more parsimonious U.S. Core Data for Interoperability. Conclusions Referral source and HHC agency adoption of data standards is recommended to support structured, consistent data and information sharing.

OBJECTIVES Compare patient characteristics by hospital discharge disposition (home without services, home with home healthcare (HHC) services, or post-acute care (PAC) facilities). Examine timing and rates of 30-day healthcare utilization (rehospitalization, emergency department (ED) visit, or observation (OBS) visit) and patient characteristics associated with rehospitalization by discharge location. DESIGN Retrospective analysis of hospital administrative and clinical data. SETTING AND PARTICIPANTS A total of 3,294 older adult inpatients discharged home with or without HHC services or to a PAC facility. MEASUREMENTS Patient-level sociodemographic and clinical characteristics. Number of and time to occurrences of rehospitalization or ED/OBS visit within 30 days of hospital discharge. RESULTS Most rehospitalizations and ED/OBS visits occurred within 14 days from hospital discharge. Patients who returned within 24 hours came mostly from inpatient rehabilitation facilities (IRFs). More intense levels of PAC services were linked with higher rehospitalization risk. However, specific predictors differed by discharge location. Being unemployed, being single, and having more comorbidities were most associated with rehospitalization in those who went home with or without services, whereas patients rehospitalized from IRFs were younger, with less chronic illness burden, but greater and recent functional decline. Those discharged with HHC services had more return ED/OBS visits. CONCLUSIONS Although sicker patients were referred for more intense levels of PAC services, patients with greater chronic illness burden were still most often rehospitalized. In addition to unique patient differences, rehospitalizations from IRF within 24 hours suggest systems factors are contributory. Most return acute healthcare utilization occurred within 14 days; therefore, interventions should focus on smoothing transitions to all discharge locations. Because predictors of rehospitalization risk differed by discharge disposition, future research is necessary to study approaches aimed at matching patients' care needs with the most suitable PAC services at the right time. J Am Geriatr Soc 68:2279-2287, 2020.

Social, economic, and environmental factors contribute to patients' recovery following hospitalization. However, little is known about how home health nurses make decisions based on their assessment of these factors. The purpose of the current study was to explore the nonclinical factors that home health nurses evaluate and describe how these factors influence care planning decisions. Semi-structured interviews conducted with 20 visiting nurses from three home health agencies were analyzed using conventional content analysis. Three nonclinical factor themes emerged: Social Support , Home Environment and Neighborhood , and Finances and Insurance Barriers . Nurses' assessments guided them to include family caregivers in the plan of care, evaluate their own safety to complete home visits, and refer patients to useful resources. Findings highlight the role of home health nurses in supporting older adults with limited resources and the need to address the social determinants of health across the care continuum. [ Research in Gerontological Nursing, 13 (3), 130–137.]