A clinical classification framework for identifying persons with high social and medical needs: The COMPLEXedex-SDH.

BACKGROUND: First-generation algorithms resulted in high-cost features as a representation of need but unintentionally introduced systemic bias based on prior ability to access care. Improved precision health approaches are needed to reduce bias and improve health equity. PURPOSE: To integrate nursing expertise into a clinical definition of high-need cases and develop a clinical classification algorithm for implementing nursing interventions. METHODS: Two-phase retrospective, descriptive cohort study using 2019 data to build the algorithm (n = 19,20,848) and 2021 data to test it in adults ≥18 years old (n = 15,99,176). DISCUSSION: The COMPLEXedex-SDH algorithm identified the following populations: cross-cohort needs (10.9%); high-need persons (cross-cohort needs and other social determinants) (17.7%); suboptimal health care utilization for persons with medical complexity (13.8%); high need persons with suboptimal health care utilization (6.2%). CONCLUSION: The COMPLEXedex-SDH enables the identification of high-need cases and value-based utilization into actionable cohorts to prioritize outreach calls to improve health equity and outcomes.

Communication Openings: A Novel Approach for Serious Illness Communication in Homecare.

Serious illness communication in homecare about hospice and/or palliative care transitions is lacking due to clinical culture. The purpose of the current study was to understand communication openings using COMFORT™, a palliative care communication model used to train nurses. Qualitative, focus group interviews with 31 homecare nurses were conducted. Data were transcribed verbatim and thematically analyzed using NVivo software, followed by hand-sorting. Four themes for communication openings for initiating discussions about potential hospice and/or palliative care transitions were identified: Organizational Openings (homecare appropriateness, eligibility requirements, and staffing); Patient Openings (patient physical decline, psychosocial changes, safety concerns, and denying/stopping care); Caregiver Openings (caregiver physical changes and patient readiness); and Nurse Openings (need for hospice, checking for prognosis understanding, increasing interprofessional care needs, and providing end-of-life care). This study extends the concept of communication openings in the COMFORT model. Further development of communication openings as part of COMFORT communication is needed in educational and intervention research. [Journal of Gerontological Nursing, 49(11), 33-41.].

COMFORT communication in the ICU: Pilot test of a nurse-led communication intervention for surrogates.

AIM: This study was designed to investigate the feasibility, acceptability, and preliminary efficacy of a nurse-led communication intervention among surrogates in the intensive care unit (ICU) guided by the COMFORT (Connect; Options; Making meaning; Family caregivers; Openings; Relating; Team) communication model. BACKGROUND: As frontline communicators, nurses experience communication difficulties with surrogates who face complex informational and emotional barriers when making decisions for critically ill patients in the ICU. However, research on effective nurse communication focusing on both curative and end-of-life (EOL) care is lacking in the literature. DESIGN: A single-centre two-group pretest-posttest quasi-experiment. METHOD: The total sample included 41 surrogates of adult ventilated patients. Twenty participants were allocated to the intervention group who received a daily 20-min telephone call with content based on the COMFORT communication model. Twenty-one participants comprised the control group who received usual care. Participants completed a questionnaire before and after the study measuring satisfaction, anxiety and depression, decisional conflict, and quality of communication. The Transparent Reporting of Evaluations with Nonrandomized Designs (TREND) checklist was followed for nonrandomised controlled trials. RESULT: The intervention was feasible, with 19 of 20 surrogates completing the follow-up surveys, and 48 telephone conversations completed (48% of the planned phone calls). Surrogates' satisfaction was higher in the intervention group than in the control group after adjusting for the selected covariates (25.43 and 24.15, respectively; p = .512). Preliminary efficacy outcomes favouring the intervention included quality of communication with healthcare providers, but not surrogates' perceived depression/anxiety and decisional conflicts. CONCLUSION: Implementation of the intervention is feasible, acceptable, and favourable among surrogates to improve quality of communication with healthcare providers in the ICU. Further research is needed to determine whether the intervention could be implemented by nurses to improve surrogates' outcomes in other ICUs.

TILE-12 index: an interpretable instrument for identifying older adults at risk for transitions in living environment within the next 12-months.

Few evidence-based tools exist to support identification of older community dwelling adults at risk for unwanted transitions in living environment leading to missed opportunities to modify care plans to support aging-in-place and/or establish end-of-life care goals. An interpretable and actionable tool for assessing a person's risk of experiencing a transition is introduced. Logistic regression analysis of 14,772 transition opportunities (i.e. 12-month periods) for 4,431 respondents to the National Health and Aging Trends Study (NHATS) rounds 1-7. Results were visualized in a nomogram. Unmarried males of increasing age with chronic disease, greater functional dependence, overnight hospitalizations, not living in a single-family home, and limited social network, have elevated risk of experiencing a transition in living environment in a 12-month period. Homecare nurses are uniquely qualified to identify social determinants of health and can use this evidence-based tool to identify individuals who may benefit from transitional care assistance.

Dementia caregiver burdens predict overnight hospitalization and hospice utilization.

OBJECTIVES: To determine sociodemographics and caregiver burdens associated with overnight hospitalization, hospice utilization, and hospitalization frequency among persons with dementia (PWD). METHODS: Cross-sectional analysis of PWD (n = 899) of the National Health and Aging Trends Study linked to the National Study of Caregiving. Logistic and proportional odds regression determined the effects of caregiver burdens on overnight hospitalization, hospice use, and hospitalization frequency. Differences between PWD alive not-alive groups were compared on overnight hospitalization and frequency. RESULTS: Alive PWD (n = 804) were 2.36 times more likely to have an overnight hospital stay (p = 0.004) and 1.96 times more likely to have multiple hospitalizations when caregivers found it physically difficult to provide care (p = 0.011). Decedents aged 65-74 (n = 95) were 4.55 times more likely to experience overnight hospitalizations than 85+, hospitalizations were more frequent (odds ratio [OR] = 4.84), and there was a significant difference between PWD alive/not alive groups (p = 0.035). Decedents were 5.60 times more likely to experience an overnight hospitalization when their caregivers had financial difficulty, hospitalizations were more frequent when caregivers had too much to handle (OR = 8.44) and/or no time for themselves (OR = 10.67). When caregivers had no time for themselves, a significant difference between alive/not alive groups (p = 0.018) was detected in hospitalization frequency. PWD whose caregivers had emotional difficulty helping were 5.89 times more likely to utilize hospice than caregivers who did not report emotional difficulty. SIGNIFICANCE OF RESULTS: Care transitions among PWD at the end of life are impacted by the circumstances and experiences of their caregivers. Subjective caregiver burdens represent potentially modifiable risks for undesired care transitions and opportunities for promoting hospice use. Future work is warranted to identify and address these issues as they occur.

Homecare nurses guide goals for care and care transitions in serious illness: A grounded theory of relationship-based care.

AIMS: To identify the process that homecare nurses use when recognizing serious illness, engaging patients and families in goals-for-care discussions and guiding transitions to comfort-focused care. DESIGN: Constructivist grounded theory. METHODS: Semi-structured focus group interviews of 31 homecare Registered Nurses were recorded and transcribed (June-August 2019). Line-by-line coding using the constant comparative method until saturation was achieved and a grounded theory was identified. Credibility, transferability, and confirmability establish study rigor. RESULTS: A grounded theory of relationship-based care. Nurses cogitate and act when recognizing serious illness. They have difficult conversations and support care transitions with wisdom and knowing, by identifying changes in illness trajectories and being informed and alert to diminishing quality of life. Nurses are skilled at engaging patients, families, and the team and accommodate care in the home for as long as possible, while manoeuvring through complex systems of care; ultimately relinquishing and guiding care to other providers and settings. However, nurses feel inadequately prepared and frustrated with a fragmented healthcare system and lack of collaboration among the team. CONCLUSION: This study identifies a grounded theory to support clinical decision-making and position homecare nurses as leaders in guiding goal care discussions and transitions to comfort-focused care. These findings reinforce the importance of developing health policy that ensures care continuity in serious illness. Further research is needed to improve relationships across care settings and enhance training for the delivery of comfort-focused care in the home as changing needs emerge during serious illness management.

Mortality Risk in Homebound Older Adults Predicted From Routinely Collected Nursing Data.

BACKGROUND: Newer analytic approaches for developing predictive models provide a method of creating decision support to translate findings into practice. OBJECTIVES: The aim of this study was to develop and validate a clinically interpretable predictive model for 12-month mortality risk among community-dwelling older adults. This is done by using routinely collected nursing assessment data to aide homecare nurses in identifying older adults who are at risk for decline, providing an opportunity to develop care plans that support patient and family goals for care. METHODS: A retrospective secondary analysis of Medicare and Medicaid data of 635,590 Outcome and Assessment Information Set (OASIS-C) start-of-care assessments from January 1, 2012, to December 31, 2012, was linked to the Master Beneficiary Summary File (2012-2013) for date of death. The decision tree was benchmarked against gold standards for predictive modeling, logistic regression, and artificial neural network (ANN). The models underwent k-fold cross-validation and were compared using area under the curve (AUC) and other data science metrics, including Matthews correlation coefficient (MCC). RESULTS: Decision tree variables associated with 12-month mortality risk included OASIS items: age, (M1034) overall status, (M1800-M1890) activities of daily living total score, cancer, frailty, (M1410) oxygen, and (M2020) oral medication management. The final models had good discrimination: decision tree, AUC = .71, 95% confidence interval (CI) [.705, .712], sensitivity = .73, specificity = .58, MCC = .31; ANN, AUC = .74, 95% CI [.74, .74], sensitivity = .68, specificity = .68, MCC = .35; and logistic regression, AUC = .74, 95% CI [.735, .742], sensitivity = .64, specificity = .70, MCC = .35. DISCUSSION: The AUC and 95% CI for the decision tree are slightly less accurate than logistic regression and ANN; however, the decision tree was more accurate in detecting mortality. The OASIS data set was useful to predict 12-month mortality risk. The decision tree is an interpretable predictive model developed from routinely collected nursing data that may be incorporated into a decision support tool to identify older adults at risk for death.

Reducing Emergency Room Visits and In-Hospitalizations by Implementing Best Practice for Transitional Care Using Innovative Technology and Big Data.

BACKGROUND: Efforts to improve care transitions require coordination across the healthcare continuum and interventions that enhance communication between acute and community settings. AIMS: To improve post-discharge utilization value using technology to identify high-risk individuals who might benefit from rapid nurse outreach to assess social and behavioral determinants of health with the goal of reducing inpatient and emergency department visits. METHODS: The project employed a before and after comparison of the intervention site with similar primary care practice sites using population-level Medicaid claims data. The intervention targeted discharged persons with preexisting chronic disease and delivered a care transition alert to a nurse care coordinator for immediate telephonic outreach. The nurse assessed social determinants of health and incorporated problems into the EHR to share across settings. The project evaluated health outcomes and the value of nursing care on existing electronic claims data to compare utilization in the years before and during the intervention using negative binomial regression to account for rare events such as inpatient visits. RESULTS: Avoiding readmissions and emergency visits, and increasing timely outpatient visits improved the individual's experience of care and the work life of healthcare providers, while reducing per capita costs (Quadruple Aim). In the intervention practice, the nurse care coordinator demonstrated the value of nursing care by reducing inpatient (25%) and emergency (35%) visits, and increasing outpatient visits (27%). The estimated value of avoided encounters over the secular Medicaid trend was $664 per adult with chronic disease, generating $71,289 in revenue from additional outpatient visits. LINKING EVIDENCE TO ACTION: Using health information exchange to deliver appropriate and timely evidence-based clinical decision support in the form of care transition alerts and assessment of social determinants of health, in conjunction with data science methods, demonstrates the value of nursing care and resulted in achieving the Quadruple Aim.

Complexity of Chronic Conditions' Impact on End-of-Life Expense Trajectories of Medicare Decedents.

OBJECTIVE: The aim of this study is to determine if the pattern of monthly medical expense can be used to identify individuals at risk of dying, thus supporting providers in proactively engaging in advanced care planning discussions. BACKGROUND: Identifying the right time to discuss end of life can be difficult. Improved predictive capacity has made it possible for nurse leaders to use large data sets to guide clinical decision making. METHODS: We examined the patterns of monthly medical expense of Medicare beneficiaries with life-limiting illness during the last 24 months of life using analysis of variance, t tests, and stepwise hierarchical linear modeling. RESULTS: In the final year of life, monthly medical expense increases rapidly for all disease groupings and forms distinct patterns of change. CONCLUSION: Type of condition can be used to classify decedents into distinctly different cost trajectories. Conditions including chronic disease, system failure, or cancer may be used to identify patients who may benefit from supportive care.

Integrating social context into comprehensive shared care plans: A scoping review.

BACKGROUND: Failure to address social determinants of health (SDH) may contribute to the problem of readmissions in high-risk individuals. Comprehensive shared care plans (CSCP) may improve care continuity and health outcomes by communicating SDH risk factors across settings. PURPOSE: The purpose of this study to evaluate the state of knowledge for integrating SDH into a CSCP. Our scoping review of the literature considered 13,886 articles, of which seven met inclusion criteria. RESULTS: Identified themes were: integrate health and social sectors; interoperability; standardizing ontologies and interventions; process implementation; professional tribalism; and patient centeredness. DISCUSSION: There is an emerging interest in bridging the gap between health and social service sectors. Standardized ontologies and theoretical definitions need to be developed to facilitate communication, indexing, and data retrieval. CONCLUSIONS: We identified a gap in the literature that indicates that foundational work will be required to guide the development of a CSCP that includes SDH that can be shared across settings. The lack of studies published in the United States suggests that this is a critical area for future research and funding.

National Priorities for Dementia Care: Perspectives of Individuals Living with Dementia and Their Care Partners.

The current article reports the consensus recommendations from individuals living with dementia and their care partners on priorities for public policy and research funding, which were found using a nationwide, Delphi study. A modified snowball sample was used. Listservs, personal contacts, and advocacy groups were asked to distribute the survey. Paper versions were provided upon request. In Rounds 1 and 2 of the study, 388 and 301 responses, respectively, were received. Borda counts produced a ranked order consensus of priorities. Research ranked third, after the need for caregiver support and resources for the provision of long-term care. Education and training in person-centered practices for all care partners was also a high priority. Responses indicated that research funding should be expanded beyond its current emphasis on cure. Policymakers should reconsider the current priorities of the National Alzheimer's Project Act to better address the long-term needs of individuals living with dementia and their care partners.

"I Finally Feel Like I Have Help. Before, I Was Completely Alone": A Grounded Theory of Community-Based Hospice Transitions.

Little is known about community-based transitions to home hospice care. We used a Straussian grounded theory approach to understand the basic social process of care transitions that patients and their caregivers use when electing hospice care. Participants were recruited from hospice agencies serving 3 counties in New York State. Data were collected through 7 interviews of patients, patient-and-caregiver dyads, and a hospice nurse (n = 10). Data were analyzed using the constant comparative method. Our results generated an emerging grounded theory of the hospice care transition processes rooted in maintaining personhood and autonomy. There were 5 contemporaneous steps: (1) recognizing futility and pursuing comfort; (2) seeking help and input as health declines; (3) shopping for the right services, overcoming obstacles, and self-referring to hospice care; (4) attending to the business of dying while living; and (5) processing and expressing emotions. Although not central to the care transition process, an additional step was identified that occurred after the transition to hospice care: planning for an uncertain future. The hospice care transition process identified in the study reveals important mechanistic targets for the development of interventions that promote patient-centered hospice care transitions in the home setting.

A Telemedicine Analytic Framework for Fully and Semi-automatic Alzheimer's Disease Screening using Clock Drawing Test.

More than 6 million Americans are at risk for Alzheimer's Disease Related Dementias (ADRD), most of whom are 65 or older. The clock drawing test (CDT) is a quick, simple, and effective technique that has the potential advantage of self-management and screening for ADRD patients. Current CDT-based ADRD screening studies focus more on efficacy, involving many handcrafted features, ignoring data modalities, and lacking validation. This paper aims to propose a unified telemedicine framework for fully and semi-automatic effective early ADRD screening based on multimodal and agile data fusion, focusing on the interpretability and validation of the model by using gradient-weighted class activation mapping (Grad-CAM) and locally linear embedding (LLE). The datasets for this work include 1,662 samples of CDT images and related demographic and cognitive information. The fully automatic case involving only CDT images can achieve the highest AUC of 81% with a 75% recall rate in binary screening. The multimodal data fusion in the semi-automatic case can achieve up to 90% AUC with an 83% recall rate. The visualization of the Convolutional Neural Networks (CNN) shows that it can automatically obtain critical information about the outline, scale, and clock hands from CDT images, and the analysis of structured features shows that the memory test is key to effective ADRD screening.

Identifying High-Need Primary Care Patients Using Nursing Knowledge and Machine Learning Methods.

BACKGROUND: Patient cohorts generated by machine learning can be enhanced with clinical knowledge to increase translational value and provide a practical approach to patient segmentation based on a mix of medical, behavioral, and social factors. OBJECTIVES: This study aimed to generate a pragmatic example of how machine learning could be used to quickly and meaningfully cohort patients using unsupervised classification methods. Additionally, to demonstrate increased translational value of machine learning models through the integration of nursing knowledge. METHODS: A primary care practice dataset (N = 3,438) of high-need patients defined by practice criteria was parsed to a subset population of patients with diabetes (n = 1233). Three expert nurses selected variables for k-means cluster analysis using knowledge of critical factors for care coordination. Nursing knowledge was again applied to describe the psychosocial phenotypes in four prominent clusters, aligned with social and medical care plans. RESULTS: Four distinct clusters interpreted and mapped to psychosocial need profiles, allowing for immediate translation to clinical practice through the creation of actionable social and medical care plans. (1) A large cluster of racially diverse female, non-English speakers with low medical complexity, and history of childhood illness; (2) a large cluster of English speakers with significant comorbidities (obesity and respiratory disease); (3) a small cluster of males with substance use disorder and significant comorbidities (mental health, liver and cardiovascular disease) who frequently visit the hospital; and (4) a moderate cluster of older, racially diverse patients with renal failure. CONCLUSION: This manuscript provides a practical method for analysis of primary care practice data using machine learning in tandem with expert clinical knowledge.

Improving Dementia Caregiver Activation With a Brief Communication Module.

Objective: Palliative care often plays a pivotal role in supporting informal caregivers of persons living with dementia who experience a lack of continuity in care. Dementia caregiver activation, the caregiver's willingness and ability to navigate care needs, requires communication skills for developing relationships with healthcare providers. Communication activation is important because caregivers facilitate physician and patient information exchange. This study aimed to explore changes in communication outcomes (attitude, knowledge, and skills) and impact on caregiver communication activation (confidence, self-report) following completion of a brief communication module. Methods: A 15-minute asynchronous online module was developed to provide caregivers with communication skills for working with doctors and nurses. Caregivers completed pre/post module measures of communication outcomes, a vignette for applying communication strategies and were interviewed within a week of module completion to assess self-reported communication activation. Module acceptability was also evaluated. Results: Communication knowledge (P < .01) significantly increased and nearly all participants (99%) demonstrated use of module-specific communication skills after completing the module. While not statistically significant, caregiver attitudes were in the expected direction. Caregiver self-reported communication confidence (P < .001) significantly increased and 84% of caregivers described communication activation at post-module. Caregivers (83%) were likely to recommend the module. Conclusions: The brief communication module for dementia caregivers in this project offers an online resource with low time-burden that results in caregiver communication activation. Future testing in the clinical setting will increase understanding of its efficacy and integration and could be a viable resource for palliative care providers.

Exploring Differences in Caregiver Communication in Serious Illness.

Background: Demographic factors, such as disease context and family relationships, are communication mediators and moderators; however, little is known about how understanding these factors can improve caregiver communication with providers. Recognition of communication differences among caregivers may aid the development of approaches to improve serious illness communication. Objective: To explore whether caregiver communication differs by disease context (cancer vs. dementia) and caregiver communication type (Manager, Carrier, Partner, and Lone). Caregiver communication type is based on communication patterns between the care recipient and caregiver. Design and Measurements: Caregivers of persons with cancer and/or dementia were surveyed from a U.S. national research registry website. Measures of caregiver communication included information needs, communication confidence, perception of provider understanding of the caregiver, perceived frequency of caregiver assessment, and caregiver stress. Analysis of variance (ANOVA) determined significant differences between caregiver communication (p < 0.05) based on disease context and caregiver communication type. Results: Cancer caregivers reported higher unrecognized-demanded information states (i.e., not recognizing information was needed), more communication confidence, and more frequent caregiver assessment compared to dementia caregivers. Among caregiver communication types, Manager caregiver types were more confident communicating than other caregiver types and perceived greater understanding by providers than the Lone caregiver type. Manager caregivers reported significantly less stress than other caregiver communication types. Conclusions: Understanding disease context and caregiver communication type may help improve caregiver communication with health care providers.

Don't Throw the Baby Out With the Bathwater: Meta-Analysis of Advance Care Planning and End-of-life Cancer Care.

CONTEXT: There is ongoing discourse about the impact of advance care planning (ACP) on end-of-life (EOL) care. No meta-analysis exists to clarify ACP's impact on patients with cancer. OBJECTIVE: To investigate the association between, and moderators of, ACP and aggressive vs. comfort-focused EOL care outcomes among patients with cancer. METHODS: Five databases were searched for peer-reviewed observational/experimental ACP-specific studies that were published between 1990-2022 that focused on samples of patients with cancer. Odds ratios were pooled to estimate overall effects using inverse variance weighting. RESULTS: Of 8,673 articles, 21 met criteria, representing 33,541 participants and 68 effect sizes (54 aggressive, 14 comfort-focused). ACP was associated with significantly lower odds of chemotherapy, intensive care, hospital admissions, hospice use fewer than seven days, hospital death, and aggressive care composite measures. ACP was associated with 1.51 times greater odds of do-not-resuscitate orders. Other outcomes-cardiopulmonary resuscitation, emergency department admissions, mechanical ventilation, and hospice use-were not impacted. Tests of moderation revealed that the communication components of ACP produced greater reductions in the odds of hospital admissions compared to other components of ACP (e.g., documents); and, observational studies, not experimental, produced greater odds of hospice use. CONCLUSION: This meta-analysis demonstrated mixed evidence of the association between ACP and EOL cancer care, where tests of moderation suggested that the communication components of ACP carry more weight in influencing outcomes. Further disease-specific efforts to clarify models and components of ACP that work and matter to patients and caregivers will advance the field.

The 2023-2026 Hospice and Palliative Nurses Association Research Agenda.

The Hospice and Palliative Nursing Association established the triannual research agenda to ( a ) provide focus for researchers to conduct meaningful scientific and quality improvement initiatives and inform evidence-based practice, ( b ) guide organizational funding, and ( c ) illustrate to other stakeholders the importance of nursing research foci. HPNA Research Agendas are developed to give direction for future research to continue advancing expert care in serious illness and ensure equitable delivery of hospice and palliative care.

Exploring Web-Based Twitter Conversations Surrounding National Healthcare Decisions Day and Advance Care Planning From a Sociocultural Perspective: Computational Mixed Methods Analysis.

BACKGROUND: Within the cultures and societies of the United States, topics related to death and dying continue to be taboo, and as a result, opportunities for presence and engagement during the end of life, which could lead to a good death, are avoided. Several efforts have been made to help people engage in advance care planning (ACP) conversations, including completing advance care directives so that they may express their goals of care if they become too sick to communicate their wishes. A major effort in the United States toward encouraging such challenging discussions is the annual celebration of the National Healthcare Decisions Day. OBJECTIVE: This study aimed to explore ACP from a sociocultural perspective by using Twitter as a communication tool. METHODS: All publicly available tweets published between August 1, 2020, and July 30, 2021 (N=9713) were collected and analyzed using the computational mixed methods Analysis of Topic Model Network approach. RESULTS: The results revealed that conversations driven primarily by laypersons (7107/7410, 95.91% of tweets originated from unverified accounts) surrounded the following three major themes: importance and promotion, surrounding language, and systemic issues. CONCLUSIONS: On the basis of the results, we argue that there is a need for awareness of the barriers that people may face when engaging in ACP conversations, including systemic barriers, literacy levels, misinformation, policies (including Medicare reimbursements), and trust among health care professionals, in the United States. This is incredibly important for clinicians and scholars worldwide to be aware of as we strive to re-envision ACP, so that people are more comfortable engaging in ACP conversations. In terms of the content of tweets, we argue that there is a chasm between the biomedical and biopsychosocial elements of ACP, including patient narratives. If used properly, Twitter conversations and National Health Care Decision Day hashtags could be harnessed to serve as a connecting point among organizations, physicians, patients, and family members to lay the groundwork for the trajectory toward a good death.