Characterizing end-of-life communication in families.

Background: The chronic disease course can be uncertain, contributing to delayed end-of-life discussion within families resulting in missed opportunity to articulate wishes, increased decisional uncertainty, and delayed hospice care. Consistent with the Family Communication Patterns Theory (FCPT), family communication patterns may affect the quality and timing of end-of-life discussion, hospice utilization, and the experience of 'a good death.' Objective: To assess how families' conversation and conformity orientation (spontaneity of conversation and hierarchical rigidity) form four family communication patterns (consensual, pluralistic, protective, and laissez-faire) and may be associated with the number and timing of end-of-life discussions. Design: A cross-sectional study. Methods: Family members of loved ones who died from chronic illnesses while in hospice (n = 56) completed online surveys including a modified Revised Family Communication Pattern instrument (RFCP) and the Chronic Illness Rating Scale (CIRS). Additional survey questions assessed the number and timing of end-of-life discussions and timing of hospice enrollment. IBM SPSS version 26 was used for descriptive analysis. Results: Most families (42.9%) were pluralistic, reporting communication styles with high conversation and low conformity orientation; (39.29%) were protective, reporting low conversation and high conformity orientation. Pluralistic families had more end-of-life conversations than did protective families. Conclusion: Study findings suggest that there may be a relationship between family communication pattern type and inclination toward end-of-life discussion. This first step supports future research regarding whether the FCPT can be used to predict which families may be at increased risk for ineffective or delayed end-of-life discussion. Additional variables to consider include the timing of hospice enrollment and the quality of the dying experience. Clinicians may ultimately use findings to facilitate earlier identification of and intervention for families who are at risk for poor end-of-life communication and outcomes.

Study protocol: Type III hybrid effectiveness-implementation study implementing Age-Friendly evidence-based practices in the VA to improve outcomes in older adults.

BACKGROUND: Unmet care needs among older adults accelerate cognitive and functional decline and increase medical harms, leading to poorer quality of life, more frequent hospitalizations, and premature nursing home admission. The Department of Veterans Affairs (VA) is invested in becoming an "Age-Friendly Health System" to better address four tenets associated with reduced harm and improved outcomes among the 4 million Veterans aged 65 and over receiving VA care. These four tenets focus on "4Ms" that are fundamental to the care of older adults, including (1) what Matters (ensuring that care is consistent with each person's goals and preferences); (2) Medications (only using necessary medications and ensuring that they do not interfere with what matters, mobility, or mentation); (3) Mentation (preventing, identifying, treating, and managing dementia, depression, and delirium); and (4) Mobility (promoting safe movement to maintain function and independence). The Safer Aging through Geriatrics-Informed Evidence-Based Practices (SAGE) Quality Enhancement Research Initiative (QUERI) seeks to implement four evidence-based practices (EBPs) that have shown efficacy in addressing these core tenets of an "Age-Friendly Health System," leading to reduced harm and improved outcomes in older adults. METHODS: We will implement four EBPs in 9 VA medical centers and associated outpatient clinics using a type III hybrid effectiveness-implementation stepped-wedge trial design. We selected four EBPs that align with Age-Friendly Health System principles: Surgical Pause, EMPOWER (Eliminating Medications Through Patient Ownership of End Results), TAP (Tailored Activities Program), and CAPABLE (Community Aging in Place - Advancing Better Living for Elders). Guided by the Pragmatic Robust Implementation and Sustainability Model (PRISM), we are comparing implementation as usual vs. active facilitation. Reach is our primary implementation outcome, while "facility-free days" is our primary effectiveness outcome across evidence-based practice interventions. DISCUSSION: To our knowledge, this is the first large-scale randomized effort to implement "Age-Friendly" aligned evidence-based practices. Understanding the barriers and facilitators to implementing these evidence-based practices is essential to successfully help shift current healthcare systems to become Age-Friendly. Effective implementation of this project will improve the care and outcomes of older Veterans and help them age safely within their communities. TRIAL REGISTRATION: Registered 05 May 2021, at ISRCTN #60,657,985. REPORTING GUIDELINES: Standards for Reporting Implementation Studies (see attached).

Noticing Acute Changes in Health in Long-Term Care Residents.

PURPOSE: Early signs of acute conditions and increased fall risk often go unrecognized in patients in long-term care facilities. The aim of this study was to examine how healthcare staff identify and act on changes in health status in this patient population. DESIGN: A qualitative study design was used for this study. METHODS: Six focus groups across two Department of Veterans Affairs long-term care facilities were conducted with 26 interdisciplinary healthcare staff members. Using thematic content analysis, the team preliminarily coded based on interview questions, reviewed and discussed emerging themes, and agreed on the resultant coding scheme for each category with additional independent scientist review. RESULTS: Themes included describing and explaining how "normal" or expected behavior is identified by staff, noticing changes in a resident, determining the significance of the change, hypothesizing reasons for an observed change, response to an observed change, and resolution of the clinical change. CONCLUSIONS: Despite limited training in formal assessment methods, long-term care staff have developed methods to conduct ongoing assessments of the residents. This technique, individual phenotyping, often identifies acute changes; however, the lack of formal methods, language, or tools to communicate the changes means that these assessments are not often formalized in a manner that informs the residents' changing care needs. CLINICAL RELEVANCE TO THE PRACTICE OF REHABILITATION NURSING: More formal objective measures of health change are needed to assist long-term care staff in expressing and interpreting the subjective phenotype changes into objective, easily communicated health status changes. This is particularly important for acute health changes and impending falls, both of which are associated with acute hospitalization.

Reviewing the past to inform the future: an 8-year review of severe maternal morbidity.

BACKGROUND: Maternal morbidity is becoming a key indicator used to compare health systems in the developed world and also to inform clinical practice. OBJECTIVE: This study aimed to evaluate a single center experience of severe maternal morbidity over an 8-year period. STUDY DESIGN: We conducted a retrospective review of all cases of severe maternal morbidity from 2012 to 2019 at a tertiary level maternity hospital in the Republic of Ireland with approximately 9000 births per year. We examined maternal demographics, pregnancy characteristics, and care requirements. Descriptive statistics were used throughout. RESULTS: There were 81,504 maternity cases and 67,894 births during the study period. A total of 504 women had a severe maternal morbidity, giving a rate of 6.1 per 1000 maternity cases overall, peaking in 2017 at 8.8 per 1000. When individual severe maternal morbidity events were evaluated, the rate increased from 6 per 1000 to 9 per 1000 over the 8-year period. There were no differences in maternal age, nationality, or body mass index during the years analyzed. Interestingly, 8.9% (n=45) were multiple gestations, and nearly one-fifth (19.4%; n=98) required escalation of care to a general hospital; of these, 14.0% (n=74) required cardiac or intensive care management. The majority of morbidities manifested in the third trimester (58.7%; n=296) or postnatally (42.8%, n=216). The most common severe maternal morbidities were hypertensive disorders of pregnancy, followed by postpartum hemorrhage and sepsis (45.0%, 44.2%, and 12.7%, respectively). CONCLUSION: We provide a longitudinal overview of severe maternal morbidity in a large maternity hospital that replicates other international findings. This information can be used for healthcare comparisons and for resource planning and allocation.

What matters when it comes to measuring Age-Friendly Health System transformation.

Thousands of health systems are now recognized as "Age-Friendly Health Systems," making this model one of the most widely disseminated - and most promising- models to redesign care delivery for older adults. Sustaining these gains will require demonstrating the impact on care delivery and outcomes of older adults. We propose a new measurement model to more tightly link Age-Friendly Health System transformation to outcomes within each "M" (What Matters, Medications, Mobility, and Mentation). We evaluated measures based on the following characteristics: (1) conceptual responsiveness to changes brought about by practicing "4Ms" care; (2) degree to which they represent outcomes that matter to older adults; and (3) how they can be feasibly, reliably, and validly measured. We offer specific examples of how novel measures are currently being used where available. Finally, we present measures that could capture system-level effects across "M"s. We tie these suggestions together into a conceptual measurement model for AFHS transformation, with the intent to spur discussion, debate, and iterative improvement in measures over time.

Developing Acute Event Risk Profiles for Older Adults with Dementia in Long-Term Care Using Motor Behavior Clusters Derived from Deep Learning.

OBJECTIVES: This paper uses deep (machine) learning techniques to develop and test how motor behaviors, derived from location and movement sensor tracking data, may be associated with falls, delirium, and urinary tract infections (UTIs) in long-term care (LTC) residents. DESIGN: Longitudinal observational study. SETTING AND PARTICIPANTS: A total of 23 LTC residents (81,323 observations) with cognitive impairment or dementia in 2 northeast Department of Veterans Affairs LTC facilities. METHODS: More than 18 months of continuous (24/7) monitoring of motor behavior and activity levels used objective radiofrequency identification sensor data to track and record movement data. Occurrence of acute events was recorded each week. Unsupervised deep learning models were used to classify motor behaviors into 5 clusters; supervised decision tree algorithms used these clusters to predict acute health events (falls, delirium, and UTIs) the week before the week of the event. RESULTS: Motor behaviors were classified into 5 categories (Silhouette score = 0.67), and these were significantly different from each other. Motor behavior classifications were sensitive and specific to falls, delirium, and UTI predictions 1 week before the week of the event (sensitivity range = 0.88-0.91; specificity range = 0.71-0.88). CONCLUSION AND IMPLICATIONS: Intraindividual changes in motor behaviors predict some of the most common and detrimental acute events in LTC populations. Study findings suggest real-time locating system sensor data and machine learning techniques may be used in clinical applications to effectively prevent falls and lead to the earlier recognition of risk for delirium and UTIs in this vulnerable population.

Changes in Motor Behavior Predict Falls and Identify Acute Events.

This study aimed to examine how changes in motor behavior are associated with falls, delirium, and urinary tract infections (UTIs). Twenty-three (128 observations) skilled nursing residents were examined for up to 18 months. In multilevel models, motor behaviors (e.g., time and distance traveled, gait speed), measured by a real-time locating system, were used to predict falls, UTIs, and delirium. Falls were associated with decreased gait speed (OR = 0.01; p ≤ 0.001) and path distance (OR = 0.99; p ≤ 0.05); delirium was associated with increased distance traveled (OR = 1.01; p ≤ 0.001), path distance (OR = 1.02; p ≤ 0.001), and decreased time traveled (OR = 0.99; p ≤ 0.001) and path time (OR = 0.99; p ≤ 0.001); UTIs were associated with increased distance traveled (OR = 1.01; p ≤ 0.001), decreased time traveled (OR = 0.99; p ≤ 0.001), and the number of paths (OR = 0.91; p ≤ 0.01). Subtle changes in motor behavior may be an early warning sign of falls and acute events. Continuous monitoring may enable clinical staff to prevent, identify early, and/or delay these poor health outcomes.

Changes in Physical and Cognitive Function Predict Sedentary Behavior in Older Adults With Mild Cognitive Impairment.

The current longitudinal study examined the influence of cognitive and lower extremity function on sedentary behavior continuously over 6 months in community-dwelling older adults with mild cognitive impairment (MCI). Multilevel models examined Montreal Cognitive Assessment (MoCA) change scores and the Short Physical Performance Battery (SPPB) on percent time in sedentary behavior among 17 older adults with MCI (50 to 74 observations for analysis). Sedentary behavior was measured daily and averaged monthly using wrist-worn actigraphy. Each 1-unit decrease in MoCA score was associated with an increase of 2 percentage points in sedentary behavior (p ≤ 0.01). In addition, each 1-unit decrease in chair stand score (lower extremity strength) was associated with an increase of 5 percentage points in sedentary behavior (p ≤ 0.01). Older adults experiencing cognitive decline and concurrent changes in lower extremity strength had the sharpest increase in sedentary behavior. Findings suggest lower body strengthening interventions may reduce sedentary behavior time and subsequently preserve physical functioning in this vulnerable population. [Research in Gerontological Nursing, 14(6), 285-291.].

Prior Night Sleep Affects Next-Day Pain Interference Among Community-Dwelling Older Adults With Lower Extremity Chronic Pain.

Emergent work suggests that sleep is a robust biobehavioral predictor of pain; however, it remains unclear how sleep is prospectively linked to pain on a day-to-day basis among older adults. The current prospective study examined how sleep duration (total sleep time), quality (sleep efficiency, wake after sleep onset), and late and irregular sleep timing influenced next-day pain perception among community-dwelling older adults (N = 10; 65 matched observations) with lower extremity chronic pain over 1 week. Multilevel modeling estimated the association between sleep (Actigraph GT9X Link) and pain perception (Brief Pain Inventory Short Form). Increased wake after sleep onset (B = 0.19, p = 0.04), sleep variability (B = 0.02, p = 0.01), and later midsleep time (B = 0.40, p < 0.05) were associated with increased pain interference the following day. Findings support the idea that timely sleep interventions may reduce the effect of poor sleep on next-day pain in older adults. [Research in Gerontological Nursing, 14(4), 173-179.].

Poor Sleep Predicts Increased Pain Perception Among Adults With Mild Cognitive Impairment.

BACKGROUND: Older adults with mild cognitive impairment are at an increased risk for dementia of the Alzheimer's type. These older adults also report poorer sleep and more pain than their cognitively intact adult counterparts. Poor sleep and pain are both symptoms associated with an increased risk for dementia in later life. Symptom science research in the direction of how poor sleep affects pain among older adults, especially those with mild cognitive impairment, is needed for the development of targeted sleep interventions to reduce pain and potentially delay/reduce the risk for Alzheimer's disease in this population. OBJECTIVE: The aim of the study was to examine a predictive model of the relationship between poor sleep and pain perception among community-dwelling older adults with mild cognitive impairment. METHODS: A longitudinal prospective design with 58 continuous matched sleep-pain observations of 15 older adults with mild cognitive impairment for up to 6 months was used. Multilevel, mixed-modeling, statistical techniques were used to examine the effects of prior-week sleep on subsequent pain perception. Pain perception (pain intensity, pain interference, and pain behavior) is measured by the Patient-Reported Outcomes Measurement Information System during monthly in-person visits. The ActiGraph GT3X+ was used to measure sleep (total sleep time, sleep efficiency, awakenings after sleep onset) objectively and continuously for up to 6 months, along with other covariates (e.g., physical activity). RESULTS: Increased awakenings after sleep onset in the prior week is associated with increased pain intensity, pain interference, and pain behavior. There was a trend toward sleep efficiency, and increased pain intensity and sleep efficiency predicted increased pain interference and pain behavior. There was no relationship between prior-week total sleep time and subsequent pain perception. DISCUSSION: In this study, poor sleep in the prior week increased pain intensity, pain interference, and pain behavior. Interventions designed to decrease awakening after sleep onset and increase sleep efficiency specifically may effectively reduce pain in this population. Given that these symptoms are prevalent among older adults with mild cognitive impairment, sleep and pain interventions may also ameliorate some of the risk for Alzheimer's disease in this population.

Monitoring functional status using a wearable real-time locating technology.

Sensor technologies enable real-time, continuous, and objective monitoring of activity and functioning in later life. In long-term care, timely assessment of functional status is needed to prevent falls and other acute events. However, the electronic forms and paper and pencil tools currently used are time-consuming and conducted too infrequently (e.g., every 6 months) to provide the sensitivity and specificity required. Staff are also unable to detect subtle changes in functioning through observation alone. The purpose of this paper is to discuss the use of a wearable real-time locating system that utilizes ultra wideband radio technology to continuously and objectively measure activity and aspects of functional status. This paper discusses the associated conceptualization and development of the scoring algorithms, raw data transformation, use of traditional paper and pencil tools and electronic health record data to validate sensor data, and other tips for those interested in this type of wearable sensor technology.

Factors Associated With Health Service Use Among Older Adults in a Mobile Veterans Program.

The current retrospective, longitudinal study applied Andersen's Behavioral Model of Health Services Use to examine how demographic characteristics (age), available resources (e.g., a caregiver, the Mobile Veterans Program [MVP]) and health needs (e.g., cognitive and physical functioning, depressive symptoms) affect hospitalization and institutionalization outcomes among older adults using the MVP. Fifty-four Veterans (age 55 to 95) participating in the MVP for up to 2 years were examined using hierarchical linear modeling (HLM) and growth curve model. In the final HLM model, each 1-point increase in depressive symptoms was associated with 76% (p ≤ 0.05) greater risk of institutionalization and 40% (p ≤ 0.01) greater risk of hospitalization. Each 1-point increase in cognitive functioning was associated with 24% (p ≤ 0.05) lower risk of institutionalization. The relationship between caregiver burden and hospitalization was attenuated by frequency of MVP visits. Services focused on reducing depressive symptoms may influence health service use and reduce caregiver burden in this population. [Journal of Gerontological Nursing, 46(5), 15-22.].

A research proposal testing a new model of ambulation activity among long-term care residents with dementia/cognitive impairment: the study protocol of a prospective longitudinal natural history study.

BACKGROUND: Excessive and patterned ambulation is associated with falls, urinary tract infections, co-occurring delirium and other acute events among long-term care residents with cognitive impairment/dementia. This study will test a predictive longitudinal data model that may lead to the preservation of function of this vulnerable population. METHODS/DESIGN: This is a single group, longitudinal study with natural observations. Data from a real-time locating system (RTLS) will be used to objectively and continuously measure ambulation activity for up to 2 years. These data will be combined with longitudinal acute event and functional status data to capture patterns of change in health status over time. Theory-driven multilevel models will be used to test the trajectories of falls and other acute conditions as a function of the ambulation activity and demographic, functional status, gait quality and balance ability including potential mediation and/or moderation effects. Data-driven machine learning algorithms will be applied to run screening of the high dimensional RTLS data together with other variables to discover new and robust predictors of acute events. DISCUSSION: The findings from this study will lead to the early identification of older adults at risk for falls and the onset of acute medical conditions and interventions for individualized care.

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults.

A real-time locating system (RTLS) can be used to track the walking activity of institutionalized older adults in long-term care who are at risk for wandering behaviors. The benefits of a RTLS are objective and continuous measurements of activity. Self-report methods of activity, especially wandering, by health care staff are vulnerable to floor effects and recall bias, and continuous clinical or research observation over the long-term can be time-consuming and expensive. Health care staff also fail to recognize the onset and/or duration of wandering behaviors, which are associated with a variety of adverse health outcomes in this population but amenable to intervention. RTLS technologies can measure the walking activity of institutionalized residents with cognitive impairment over time with a high degree of accuracy. This is particularly useful for the study of wandering, defined as walking for at least 60 seconds with few (if any) breaks in activity. Wandering is associated with disease progression, hospitalizations, falls and death. Previous work suggests older adults with poor balance ability and high sustained walking activity may be particularly susceptible to poor health outcomes. RTLS's are used to assess cognitive impairment and factors associated with gait and balance; however, supplemental paper and pencil gait/balance tools may be used to further refine risk profiles. This project discusses the use of a RTLS to measure walking activity and also gait quality and balance ability measures on this population.

A Stroke Reduction Health Plan for Older Adults in Rural Sussex County, Delaware.

Stroke is a leading cause of death and disability among adults age 65 and over in the United States. Modifiable risk factors for stroke include: obesity, poor nutrition, and lack of exercise. Sussex County, Delaware has the highest stroke rate among older adults in the state. Twenty-five percent of the population in Sussex County are 65 and over and about 70% of adults are overweight or obese. Consistent with the social ecological framework, the Stroke Population Risk Tool may be used at the individual level to identify those at an increased risk for stroke and to create individualized stroke specific education. At the community level, local nutrition, fitness, and senior services may be utilized - with older adults at the highest risk profile participating in a 12 week stroke education program focused on risk reduction behaviors, nutrition and exercise classes. At the policy level, the Walkability Assessment Tool may be utilized to encourage local municipalities to identify areas of the county which lack safe spaces to be physically active and to develop a plan to create a more exercise conducive environment. Taken together, the proposal discusses an implementable plan that may, in the long-term, effectively reduce the stroke rates of older adults in Sussex County and allow for the early identification of those at the greatest risk for stroke.

Wandering Behaviors and Activities of Daily Living Among Older Adults With Cognitive Impairment.

PURPOSE: The aim of the study was to examine the characteristics of wandering associated with preserved versus worsened activities of daily living (ADL) function. DESIGN: Longitudinal prospective design. Twenty-two cognitively impaired residents of an assisted living facility with over 450 observations were followed up to 8 months. METHODS: Hierarchical linear modeling techniques examine how wandering activity (episodes, distance traveled, gait speed), measured by a real-time locating system, may affect ADL (the Barthel index, the Functional Independence Measure [FIM]). FINDINGS: Wandering episodes were associated with increased ADL (B = 0.11, p ≤ .05, FIM); wandering distance (B = -4.52, p ≤ .05, the Barthel index; B = -2.14, p ≤ .05, FIM) was associated with decreased ADL. CONCLUSION: Walking an average of 0.81 miles per week with 18 or fewer wandering episodes is associated with decreased ability to perform ADL. CLINICAL RELEVANCE: Tailored protocols that allow productive wandering with ongoing assessment for fatigue/other physiological needs to appropriately limit distance walked within wandering episodes are needed for this population.

Development and internal validation of the multivariable CIPHER (Collaborative Integrated Pregnancy High-dependency Estimate of Risk) clinical risk prediction model.

BACKGROUND: Intensive care unit (ICU) outcome prediction models, such as Acute Physiology And Chronic Health Evaluation (APACHE), were designed in general critical care populations and their use in obstetric populations is contentious. The aim of the CIPHER (Collaborative Integrated Pregnancy High-dependency Estimate of Risk) study was to develop and internally validate a multivariable prognostic model calibrated specifically for pregnant or recently delivered women admitted for critical care. METHODS: A retrospective observational cohort was created for this study from 13 tertiary facilities across five high-income and six low- or middle-income countries. Women admitted to an ICU for more than 24 h during pregnancy or less than 6 weeks post-partum from 2000 to 2012 were included in the cohort. A composite primary outcome was defined as maternal death or need for organ support for more than 7 days or acute life-saving intervention. Model development involved selection of candidate predictor variables based on prior evidence of effect, availability across study sites, and use of LASSO (Least Absolute Shrinkage and Selection Operator) model building after multiple imputation using chained equations to address missing data for variable selection. The final model was estimated using multivariable logistic regression. Internal validation was completed using bootstrapping to correct for optimism in model performance measures of discrimination and calibration. RESULTS: Overall, 127 out of 769 (16.5%) women experienced an adverse outcome. Predictors included in the final CIPHER model were maternal age, surgery in the preceding 24 h, systolic blood pressure, Glasgow Coma Scale score, serum sodium, serum potassium, activated partial thromboplastin time, arterial blood gas (ABG) pH, serum creatinine, and serum bilirubin. After internal validation, the model maintained excellent discrimination (area under the curve of the receiver operating characteristic (AUROC) 0.82, 95% confidence interval (CI) 0.81 to 0.84) and good calibration (slope of 0.92, 95% CI 0.91 to 0.92 and intercept of -0.11, 95% CI -0.13 to -0.08). CONCLUSIONS: The CIPHER model has the potential to be a pragmatic risk prediction tool. CIPHER can identify critically ill pregnant women at highest risk for adverse outcomes, inform counseling of patients about risk, and facilitate bench-marking of outcomes between centers by adjusting for baseline risk.

Balance ability and cognitive impairment influence sustained walking in an assisted living facility.

PURPOSE OF STUDY: The purpose of this study was to determine the influence of cognitive impairment (CI),1 gait quality, and balance ability on walking distance and speed in an assisted living facility. MATERIALS AND METHODS: This was a longitudinal cohort study of institutionalized older adults (N = 26; 555 observations) followed for up to 8 months. Hierarchical linear modeling statistical techniques were used to examine the effects of gait quality and balance ability (using the Tinetti Gait and Balance Test) and cognitive status (using the Montreal Cognitive Assessment) on walking activity (distance, sustained distance, sustained speed). The latter were measured objectively and continuously by a real-time locating system (RTLS). RESULTS: A one-point increase in balance ability was associated with an 8% increase in sustained walking distance (p = 0.03) and a 4% increase in sustained gait speed (p = 0.00). Gait quality was associated with decreased sustained gait speed (p = 0.03). Residents with moderate (ERR = 2.34;p = 0.01) or severe CI (trend with an ERR = 1.62; p = 0.06) had longer sustained walking distances at slower speeds when compared to residents with no CI. CONCLUSIONS: After accounting for cognitive status, it was balance ability, not gait quality, that was a determinant of sustained walking distances and speeds. Therefore, balance interventions for older adults in assisted living may enable sustained walking activity. Given that CI was associated with more sustained walking, limiting sustained walking in the form of wandering behavior, especially for those with balance impairments, may prevent adverse events, including fall-related injury.