Age-Friendly Health Systems and Meeting the Principles of High Reliability Organizations in the VHA.

Background: The Veterans Health Administration (VHA) is the largest integrated health care system in the US, providing care to more than 9 million enrolled veterans. In February 2019, the VHA identified key actionable steps to become a high reliability organization (HRO), transforming how employees think about patient safety and care quality. The VHA is also working toward becoming the largest age-friendly health system in the US to be recognized by the Institute for Healthcare Improvement for its commitment to providing care guided by the 4Ms (what matters, medication, mentation, and mobility), causing no harm, and aligning care with what matters to older veterans. Observations: In this article, we describe how the Age-Friendly Health Systems (AFHS) movement supports the culture shift observed in HROs. AFHS use the 4Ms as a framework to be implemented in every care setting. The 4Ms are used in conjunction with the 3 pillars (leadership commitment, culture of safety, and continuous process improvement) and 5 principles (sensitivity to operations, reluctance to simplify, preoccupation with failure, deference to clinical expertise, and commitment to resilience) that guide an HRO. We also share an HRO case study that is representative of many Community Living Centers involved in AFHS. Conclusions: AFHS empower VHA teams to honor veterans' care preferences and values, supporting their independence, dignity, and quality of life across care settings. The adoption of AFHS brings evidence-based practices to the point of care by addressing common pitfalls in the care of older adults, drawing attention to, and calling for action on inappropriate medication use, physical inactivity, and assessment of the vulnerable brain. The 4Ms also serve as a framework to continuously improve care and cause zero harm, reinforcing HRO pillars and principles across the VHA and ensuring that older adults reliably receive the evidence-based, high-quality care they deserve.

Pain intensity, physical function, and depressive symptoms associated with discontinuing long-term opioid therapy in older adults with Alzheimer's disease and related dementias.

INTRODUCTION: Limited evidence exists on the associations of discontinuing versus continuing long-term opioid therapy (LTOT) with pain intensity, physical function, and depression among patients with Alzheimer's disease and related dementias (ADRD). METHODS: A cohort study among 138,059 older residents with mild-to-moderate ADRD and receipt of LTOT was conducted using a 100% Medicare nursing home sample. Discontinuation of LTOT was defined as no opioid refills for ≥ 60 days. Outcomes were worsening pain, physical function, and depression from baseline to quarterly assessments during 1- and 2-year follow-ups. RESULTS: The adjusted odds of worsening pain and depressive symptoms were 29% and 5% lower at the 1-year follow-up and 35% and 9% lower at the 2-year follow-up for residents who discontinued versus continued LTOT, with no difference in physical function. DISCUSSION: Discontinuing LTOT was associated with lower short- and long-term worsening pain and depressive symptoms than continuing LTOT among older residents with ADRD. HIGHLIGHTS: Discontinuing long-term opioid therapy (LTOT) was associated with lower short- and long-term worsening pain. Discontinuing LTOT was related to lower short- and long-term worsening depression. Discontinuing LTOT was not associated with short- and long-term physical function.

Use of a Data Repository to Identify Delirium as a Presenting Symptom of COVID-19 Infection in Hospitalized Adults: Cross-Sectional Cohort Pilot Study.

BACKGROUND: Delirium, an acute confusional state highlighted by inattention, has been reported to occur in 10% to 50% of patients with COVID-19. People hospitalized with COVID-19 have been noted to present with or develop delirium and neurocognitive disorders. Caring for patients with delirium is associated with more burden for nurses, clinicians, and caregivers. Using information in electronic health record data to recognize delirium and possibly COVID-19 could lead to earlier treatment of the underlying viral infection and improve outcomes in clinical and health care systems cost per patient. Clinical data repositories can further support rapid discovery through cohort identification tools, such as the Informatics for Integrating Biology and the Bedside tool. OBJECTIVE: The specific aim of this research was to investigate delirium in hospitalized older adults as a possible presenting symptom in COVID-19 using a data repository to identify neurocognitive disorders with a novel group of International Classification of Diseases, Tenth Revision (ICD-10) codes. METHODS: We analyzed data from 2 catchment areas with different demographics. The first catchment area (7 counties in the North-Central Florida) is predominantly rural while the second (1 county in North Florida) is predominantly urban. The Integrating Biology and the Bedside data repository was queried for patients with COVID-19 admitted to inpatient units via the emergency department (ED) within the health center from April 1, 2020, and April 1, 2022. Patients with COVID-19 were identified by having a positive COVID-19 laboratory test or a diagnosis code of U07.1. We identified neurocognitive disorders as delirium or encephalopathy, using ICD-10 codes. RESULTS: Less than one-third (1437/4828, 29.8%) of patients with COVID-19 were diagnosed with a co-occurring neurocognitive disorder. A neurocognitive disorder was present on admission for 15.8% (762/4828) of all patients with COVID-19 admitted through the ED. Among patients with both COVID-19 and a neurocognitive disorder, 56.9% (817/1437) were aged ≥65 years, a significantly higher proportion than those with no neurocognitive disorder (P<.001). The proportion of patients aged <65 years was significantly higher among patients diagnosed with encephalopathy only than patients diagnosed with delirium only and both delirium and encephalopathy (P<.001). Most (1272/4828, 26.3%) patients with COVID-19 admitted through the ED during our study period were admitted during the Delta variant peak. CONCLUSIONS: The data collected demonstrated that an increased number of older patients with neurocognitive disorder present on admission were infected with COVID-19. Knowing that delirium increases the staffing, nursing care needs, hospital resources used, and the length of stay as previously noted, identifying delirium early may benefit hospital administration when planning for newly anticipated COVID-19 surges. A robust and accessible data repository, such as the one used in this study, can provide invaluable support to clinicians and clinical administrators in such resource reallocation and clinical decision-making.

Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium.

BACKGROUND: Prognostic models of hospital-induced delirium, that include potential predisposing and precipitating factors, may be used to identify vulnerable patients and inform the implementation of tailored preventive interventions. It is recommended that, in prediction model development studies, candidate predictors are selected on the basis of existing knowledge, including knowledge from clinical practice. The purpose of this article is to describe the process of identifying and operationalizing candidate predictors of hospital-induced delirium for application in a prediction model development study using a practice-based approach. METHODS: This study is part of a larger, retrospective cohort study that is developing prognostic models of hospital-induced delirium for medical-surgical older adult patients using structured data from administrative and electronic health records. First, we conducted a review of the literature to identify clinical concepts that had been used as candidate predictors in prognostic model development-and-validation studies of hospital-induced delirium. Then, we consulted a multidisciplinary task force of nine members who independently judged whether each clinical concept was associated with hospital-induced delirium. Finally, we mapped the clinical concepts to the administrative and electronic health records and operationalized our candidate predictors. RESULTS: In the review of 34 studies, we identified 504 unique clinical concepts. Two-thirds of the clinical concepts (337/504) were used as candidate predictors only once. The most common clinical concepts included age (31/34), sex (29/34), and alcohol use (22/34). 96% of the clinical concepts (484/504) were judged to be associated with the development of hospital-induced delirium by at least two members of the task force. All of the task force members agreed that 47 or 9% of the 504 clinical concepts were associated with hospital-induced delirium. CONCLUSIONS: Heterogeneity among candidate predictors of hospital-induced delirium in the literature suggests a still evolving list of factors that contribute to the development of this complex phenomenon. We demonstrated a practice-based approach to variable selection for our model development study of hospital-induced delirium. Expert judgement of variables enabled us to categorize the variables based on the amount of agreement among the experts and plan for the development of different models, including an expert-model and data-driven model.

Guiding Post-Hospital Recovery by 'What Matters:' Implementation of Patient Priorities Identification in a VA Community Living Center.

BACKGROUND: Patient priorities care (PPC) is an effective age-friendly health systems (AFHS) approach to aligning care with goals derived from 'what matters'. The purpose of this quality improvement program was to evaluate the fidelity and feasibility of the health priorities identification (HPI) process in VA Community Living Centers (CLC). METHODS: PPC experts worked with local CLC staff to guide the integration of HPI into the CLC and utilized a Plan-Do-Study-Act (PDSA) model for this quality improvement project. PPC experts reviewed health priorities identification (HPI) encounters and interdisciplinary team (IDT) meetings for fidelity to the HPI process of PPC. Qualitative interviews with local CLC staff determined the appropriateness of the health priorities identification process in the CLC. RESULTS: Over 8 months, nine facilitators completed twenty HPI encounters. Development of a Patient Health Priorities note template, staff education and PPC facilitator training improved fidelity and documentation of HPI encounters in the electronic health record. Facilitator interviews suggested that PPC is appropriate in this setting, not burdensome to staff and fostered a person-centered approach to AFHS. CONCLUSIONS: The HPI process is an acceptable and feasible approach to ask the 'what matters' component of AFHS in a CLC setting.

Updating the landmark literature for the practice of geriatrics: Notable articles from 2012-2019.

BACKGROUND: Remaining current on the latest advances in the peer-reviewed literature is a basic tenant of medical education and evidence-based practice. We updated an important prior publication (Vaughan, et al.) identifying landmark articles in geriatric medicine by considering the influence of altmetrics and updating the list with notable articles published between 2012 and 2019. METHODS: Articles were identified by searching Web of Science and Scopus for highly cited articles clinically relevant to geriatrics or gerontology and by searching the Altmetric Explorer database for relevant articles with high altmetric scores. The results of the literature search were screened and evaluated using a bibliometric score consisting of an adjusted journal impact factor, citation count, and altmetric score. RESULTS: The top 12 notable articles in geriatrics were selected by a consensus panel and ranked using an expert opinion survey. This process reinforces the concept of combining subjective and objective measures to identify notable articles to be used for the education of healthcare professionals in geriatrics principles of care for older adults. CONCLUSIONS: While our update was performed approximately 9 years after the initial identification of landmark articles, we propose that future updates are conducted at an interval of every 5 years by the governance of a national professional society.

Uncontrolled Pain and Risk for Depression and Behavioral Symptoms in Residents With Dementia.

OBJECTIVES: Limited cohort studies have assessed the association between uncontrolled pain and risk for behavioral and psychological symptoms of dementia (BPSDs). We conducted a longitudinal cohort study to examine whether associations exist between uncontrolled pain and risk for 2 common BPSDs-depression and behavioral symptoms-among long-term care (LTC) residents with Alzheimer disease and related dementia (ADRD). DESIGN: This retrospective cohort study analyzed quarterly data from the 5% Medicare sample linked to Minimum Data Set (MDS) 3.0 between January 1, 2011, and December 31, 2015. SETTING AND PARTICIPANTS: LTC residents aged 50 years or older with ADRD who had chronic pain and at least 2 quarterly MDS 3.0 assessments. METHODS: LTC residents were followed up quarterly from first observed quarterly MDS 3.0 until first outcome event or last observed quarterly MDS 3.0. Uncontrolled pain was defined as numerical rating scale >4, verbal descriptor scale of moderate or severe pain, or ≥1 pain indicators on the Checklist of Nonverbal Pain Indicators. Depression was defined as ≥10 on the Patient Health Questionnaire 9; behavioral symptoms were defined as the presence of psychotic (delusions or hallucinations) or disruptive behaviors (rejection of care, or physical, verbal, or other aggressive behaviors). Generalized linear models (GLMs) with marginal structural modeling (MSM) stabilized weights were used to examine uncontrolled pain and outcome risk. RESULTS: The incidence rate of depression and behavioral symptoms during follow-up was 9.4 and 23.1 per 100 resident-years, respectively. Results from the MSM-GLMs showed that LTC residents with uncontrolled pain had a higher risk than those with controlled pain for developing depression [hazard ratio 1.67, 95% confidence interval (CI) 1.54-1.81] and behavioral symptoms (hazard ratio 1.28, 95% CI 1.19-1.37). CONCLUSIONS AND IMPLICATIONS: Uncontrolled pain was associated with elevated risk for depressive and behavioral symptoms in dementia, underscoring the importance of pain assessment and control among LTC residents with ADRD.

Quality of opioid prescribing in older adults with or without Alzheimer disease and related dementia.

BACKGROUND: Pain is common among individuals with Alzheimer's disease and related dementias (ADRD), and use of opioids has been increasing over the last decade. Yet, it is unclear to what extent opioids are appropriately prescribed for patients with ADRD and whether the appropriateness of opioid prescribing differs by ADRD status. The objective of this study is to compare the quality of opioid prescribing among patients with or without ADRD who have chronic noncancer pain. METHODS: A nationally representative cohort study of Medicare beneficiaries aged 50 years or older who had chronic pain but who had no cancer, hospice, or palliative care from 2011 to 2015. Four indicators of potentially inappropriate opioid prescribing were measured in patients residing in communities (75,258 patients with and 435,870 patients without ADRD); five indicators were assessed in patients in nursing homes (NHs) (37,117 patients with and 5128 patients without ADRD). Each indicator was calculated as the proportion of eligible patients with inappropriate opioid prescribing in the year after a chronic pain diagnosis. Differences in proportions between ADRD and non-ADRD groups were estimated using a generalized linear model adjusting for covariates through inverse probability weighting. RESULTS: Patients with ADRD versus those without had higher concurrent use of opioids and central nervous system-active drugs (community 44.1% vs 33.3%; NH 58.8% vs 54.1%, both P < 0.001) and no opioids or scheduled pain medications for moderate or severe pain (NH 60.1% vs 52.5%, P < 0.001). The ADRD versus non-ADRD group had higher use of long-term opioids for treating neuropathic pain in communities (21.7% vs 19.5%, P = 0.003) but lower use in NHs (26.9% vs 36.0%, P < 0.001). Use of strong or high-dose opioids when naive to opioids (community 1.5% vs 2.8%; NH 2.5% vs 3.5%) and use of contraindicated opioids (community 0.08% vs 0.12%; NH 0.05% vs 0.21%) were rare for either group. CONCLUSION: Potential inappropriate opioid prescribing in 2 areas of pain care was more common among patients with ADRD than among patients without ADRD in community or NH settings. Further studies aimed at understanding the factors and effects associated with opioid prescribing patterns that deviate from guidelines are warranted.

Agreement of Minimum Data Set 3.0 depression and behavioral symptoms with clinical diagnosis in a nursing home.

OBJECTIVES: While the Minimum Data Set (MDS) 3.0 has adopted Patient Health Questionnaire (PHQ)-9 to screen for depression and rephrased language for behavioral symptoms among nursing home residents, it remains unclear how well the assessment data agree with medical records. DESIGN: Using a retrospective review of MDS 3.0 linked to medical records between October 2010 and November 2017, we included residents with at least one quarterly or short-term (day 30 or day 60) MDS 3.0 assessment of depression PHQ-9 (n = 446) or behavioral symptoms (n = 460). For each resident of each cohort, we randomly selected an eligible MDS 3.0 depression and behavioral symptom assessment and compared against the respective medical diagnoses recorded within 30 days before the MDS 3.0 assessment. RESULTS: Percent agreement was high for depression (90.1%) and behavioral symptoms (89.3%). Negative agreement was high for depression (94.8%) and behavioral symptoms (94.3%), while positive agreement was low for both conditions (4.3% and 10.9%). CONCLUSION: MDS 3.0 depression and behavioral symptoms had high overall and negative agreement, but low positive agreement with clinician diagnoses. MDS 3.0 data may be useful in ruling out depression and behavioral symptoms. Confirmation of the findings in a representative sample of nursing homes is warranted.

Training hospital inpatient nursing to know (THINK) delirium: A nursing educational program.

BACKGROUND/OBJECTIVES: Recognition and documentation of delirium is a challenge in the hospital. Education programs lack standardized screening tools. The presence of dementia or depression contribute to poor recognition of delirium. Many front-line healthcare workers attribute delirium to dementia, often misidentifying or delaying a correct diagnosis and in turn, treatment. Unrecognized and untreated delirium is costly. Non-pharmacologic interventions improve patient outcomes and decrease costs. Without delirium education, nurses are vulnerable to injury and low job satisfaction when caring for delirious patients. We describe an education program improving recognition and attitudes towards patients experiencing delirium. DESIGN: An education program about screening, documenting, and treating delirium. SETTING: A large Veterans Health System Hospital. PARTICIPANTS: Healthcare professionals(n = 389) participated in the education program. 355 Nurses and patient-care assistants took the pre and post-test, and 43 returned the post program follow-up survey. A delirium education program with three steps; 1) self-directed online module; 2) dementia simulation experience; and 3) a multi-station delirium skills fair. Pre and post-tests were conducted after step 2, as well as a four-month follow-up survey. MEASUREMENTS: Changes in attitude toward patients with cognitive impairment and their abilities. Self-assessment of attitudes toward patients with delirium. RESULTS: Statistically significant differences in pre and post-testing suggested increased understanding of the experience and abilities of people experiencing cognitive impairment . The four-month follow-up survey showed a continued understanding of the importance of recognizing, documenting, and treating delirium. CONCLUSION: Nursing Education about delirium that includes instruction on a standardized screening tool, documentation, and non-pharmacologic interventions improved knowledge and recognition of delirium and may have changed attitudes surrounding delirium in the hospital.

A Simulated Graphical Interface for Integrating Patient-Generated Health Data From Smartwatches With Electronic Health Records: Usability Study.

BACKGROUND: Wearable technology, such as smartwatches, can capture valuable patient-generated data and help inform patient care. Electronic health records provide logical and practical platforms for including such data, but it is necessary to evaluate the way the data are presented and visualized. OBJECTIVE: The aim of this study is to evaluate a graphical interface that displays patients' health data from smartwatches, mimicking the integration within the environment of electronic health records. METHODS: A total of 12 health care professionals evaluated a simulated interface using a usability scale questionnaire, testing the clarity of the interface, colors, usefulness of information, navigation, and readability of text. RESULTS: The interface was positively received, with 14 out of the 16 questions generating a score of 5 or greater among at least 75% of participants (9/12). On an 8-point Likert scale, the highest rated features of the interface were quick turnaround times (mean score 7.1), readability of the text (mean score 6.8), and use of terminology/abbreviations (mean score 6.75). CONCLUSIONS: Collaborating with health care professionals to develop and refine a graphical interface for visualizing patients' health data from smartwatches revealed that the key elements of the interface were acceptable. The implementation of such data from smartwatches and other mobile devices within electronic health records should consider the opinions of key stakeholders as the development of this platform progresses.

Identification of important factors in an inpatient fall risk prediction model to improve the quality of care using EHR and electronic administrative data: A machine-learning approach.

BACKGROUND: Inpatient falls, many resulting in injury or death, are a serious problem in hospital settings. Existing falls risk assessment tools, such as the Morse Fall Scale, give a risk score based on a set of factors, but don't necessarily signal which factors are most important for predicting falls. Artificial intelligence (AI) methods provide an opportunity to improve predictive performance while also identifying the most important risk factors associated with hospital-acquired falls. We can glean insight into these risk factors by applying classification tree, bagging, random forest, and adaptive boosting methods applied to Electronic Health Record (EHR) data. OBJECTIVE: The purpose of this study was to use tree-based machine learning methods to determine the most important predictors of inpatient falls, while also validating each via cross-validation. MATERIALS AND METHODS: A case-control study was designed using EHR and electronic administrative data collected between January 1, 2013 to October 31, 2013 in 14 medical surgical units. The data contained 38 predictor variables which comprised of patient characteristics, admission information, assessment information, clinical data, and organizational characteristics. Classification tree, bagging, random forest, and adaptive boosting methods were used to identify the most important factors of inpatient fall-risk through variable importance measures. Sensitivity, specificity, and area under the ROC curve were computed via ten-fold cross validation and compared via pairwise t-tests. These methods were also compared to a univariate logistic regression of the Morse Fall Scale total score. RESULTS: In terms of AUROC, bagging (0.89), random forest (0.90), and boosting (0.89) all outperformed the Morse Fall Scale (0.86) and the classification tree (0.85), but no differences were measured between bagging, random forest, and adaptive boosting, at a p-value of 0.05. History of Falls, Age, Morse Fall Scale total score, quality of gait, unit type, mental status, and number of high fall risk increasing drugs (FRIDs) were considered the most important features for predicting inpatient fall risk. CONCLUSIONS: Machine learning methods have the potential to identify the most relevant and novel factors for the detection of hospitalized patients at risk of falling, which would improve the quality of patient care, and to more fully support healthcare provider and organizational leadership decision-making. Nurses would be able to enhance their judgement to caring for patients at risk for falls. Our study may also serve as a reference for the development of AI-based prediction models of other iatrogenic conditions. To our knowledge, this is the first study to report the importance of patient, clinical, and organizational features based on the use of AI approaches.

Intensive Care Unit Delirium in Surgical Patients Is Associated with Upregulation in Tryptophan Metabolism.

INTRODUCTION: In intensive care unit (ICU) patients, delirium is frequent, occurs early in ICU admission, and is associated with poor outcomes. Risk models based on clinical factors have shown variable performance in terms of predictive ability. Identification of a candidate biomarker that associates with delirium may lead to a better understanding of disease mechanism, validation biomarker studies, and the ability to develop targeted interventions for prevention and treatment of delirium. This study analyzed metabolite concentrations early in the course of ICU admission to assess the association with delirium onset. METHODS: Within 24 hours of ICU admission, blood samples for global and targeted metabolomics analyses in adult surgical ICU patients were collected prospectively. Metabolites were determined using mass spectrometry/ultra-high-pressure liquid chromatography and analyzed in patients with delirium and a group of controls matched on age, sex, and admission Sequential Organ Function Assessment (SOFA) score. RESULTS: Patients in the study (65 per group) were a mean age of 59 years, had a median SOFA score of 6, and were most commonly admitted to the ICU following major trauma. In the delirium group, median onset of delirium was 3 (interquartile range 1-6) days, and the most common delirium subtype was mixed (56%). Kynurenic acid was significantly increased, and tryptophan concentration was significantly decreased in the delirium group (p=0.04). The ratio of kynurenine-to-tryptophan concentration was significantly higher in the delirium group (p=0.005). CONCLUSIONS: Evidence of upregulation was found in the tryptophan metabolic pathway in delirious patients because tryptophan concentrations were lower, tryptophan metabolites were higher, and the kynurenine-to-tryptophan ratio was increased. These findings suggest a role of increased inflammation and accumulation of neurotoxic metabolites in the pathogenesis of ICU delirium. Future studies should target this pathway to validate metabolites in the tryptophan pathway as risk biomarkers in patients with ICU delirium.

Secondary care provider attitudes towards patient generated health data from smartwatches.

Wearable devices, like smartwatches, are increasingly used for tracking physical activity, community mobility, and monitoring symptoms. Data generated from smartwatches (PGHD_SW) is a form of patient-generated health data, which can benefit providers by supplying frequent temporal information about patients. The goal of this study was to understand providers' perceptions towards PGHD_SW adoption and its integration with electronic medical records. In-depth, semi-structured qualitative interviews were conducted with 12 providers from internal medicine, family medicine, geriatric medicine, nursing, surgery, rehabilitation, and anesthesiology. Diffusion of Innovations was used as a framework to develop questions and guide data analysis. The constant comparative method was utilized to formulate salient themes from the interviews. Four main themes emerged: (1) PGHD_SW is perceived as a relative advantage; (2) data are viewed as compatible with current practices; (3) barriers to overcome to effectively use PGHD_SW; (4) assessments from viewing sample data. Overall, PGHD_SW was valued because it enabled access to information about patients that were traditionally unattainable. It also can initiate discussions between patients and providers. Providers consider PGHD_SW important, but data preferences varied by specialty. The successful adoption of PGHD_SW will depend on tailoring data, frequencies of reports, and visualization preferences to correspond with the demands of providers.

Magnitude of and Characteristics Associated With the Treatment of Calcium Channel Blocker-Induced Lower-Extremity Edema With Loop Diuretics.

Importance: Calcium channel blockers, specifically dihydropyridine calcium channel blockers (DH CCBs, eg, amlodipine), may cause lower-extremity edema. Anecdotal reports suggest this may result in a prescribing cascade, where DH CCB-induced edema is treated with loop diuretics. Objective: To assess the magnitude and characteristics of the DH CCB prescribing cascade. Design, Setting, and Participants: This cohort study used a prescription sequence symmetry analysis to assess loop diuretic initiation before and after the initiation of DH CCBs among patients aged 20 years or older without heart failure. Data from a private insurance claims database from 2005 to 2017 was analyzed. Use of loop diuretics associated with initiation of angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and other commonly used medications was used as negative controls. Data were analyzed from March 2019 through October 2019. Exposures: Initiation of DH CCB or negative control medications. Main Outcomes and Measures: The temporality of loop diuretic initiation relative to DH CCB or negative control initiation. Secular trend-adjusted sequence ratios (aSRs) with 95% CIs were calculated using data from 360 days before and after initiation of DH CCBs. Results: Among 1 206 093 DH CCB initiators, 55 818 patients (4.6%) (33 100 [59.3%] aged <65 years; 32 916 [59.0%] women) had a new loop diuretic prescription 360 days before or after DH CCB initiation, resulting in an aSR of 1.87 (95% CI, 1.84-1.90). An estimated 1.44% of DH CCB initiators experienced the prescribing cascade. The aSR was disproportionately higher among DH CCB initiators who were prescribed high doses (aSR, 2.20; 95% CI, 2.13-2.27), initiated amlodipine (aSR, 1.89; 95% CI, 1.86-1.93), were men (aSR, 1.96; 95% CI, 1.91-2.01), and used fewer antihypertensive classes (aSR, 2.55; 95% CI, 2.47-2.64). The evaluation of ACE inhibitors or ARBs as negative controls suggested hypertension progression may have tempered the incidence of the prescribing cascade (aSR for ACE inhibitors and ARBs, 1.27; 95% CI, 1.24-1.29). Conclusions and Relevance: This study found an excessive use of loop diuretics following initiation of DH CCBs that cannot be completely explained by secular trends or hypertension progression. The prescribing cascade was more pronounced among those initially prescribed a high dose of DH CCBs.

Geriatric Care Boot Camp Series: Interprofessional education for a new training paradigm.

Interprofessional education of health care professionals caring for older adults is critical to address the unique needs of geriatric patients. An interprofessional education program - the Geriatric Care Boot Camp Series ("Series") - was designed for health care professionals to fill this education gap. The program consisted of three half-day, intensive boot camps conducted over a one-year period. A total of 112 learners participated; more than half were nurses. Data analysis revealed statistically significant increases following each boot camp in attendees' reported knowledge about caring for older adults; statistically significant increases in comfort caring for older adults were also seen among participants in two boot camps. Attendees found the interprofessional nature of the program beneficial and said they would attend a similar program again. The Series is easily replicable, appealing to the target audience, and fulfills the need to better educate health care professionals on caring for older adults.

Nutrition and Exercise in Sarcopenia.

Sarcopenia is a debilitating condition that involves loss of muscle mass and function, which affects virtually everyone as they age, and can lead to frailty and ultimately disability. In growing recognition of the importance of both muscle strength and muscle mass relative to body size in contributing to functional decline, recent definitions have now incorporated grip strength and a correction for body mass as part of the key criteria that define sarcopenia. With this new definition, a much larger population of older adults are now at risk of sarcopenia. In the present article, we reviewed the literature for studies which tested the effects of diet or exercise interventions on changes in lean mass and/or functional outcomes in individuals with either sarcopenia and/or frailty and identified 19 clinical trials. There were a few key findings. First, dietary interventions involving protein supplementation improved functional and/or strength outcomes in a few trials; however, other dietary approaches were less effective. Exercise interventions and combined diet and exercise interventions produced consistent improvements in lower body muscle strength but had less consistent effects on walking speed and grip strength. Lifestyle interventions not involving calorie restriction generally did not induce significant changes in body composition. There were a limited number of trials in which participants with sarcopenia were specifically targeted, and thus there is an important need for more research to determine the appropriate types of intervention approaches for the high risk population of sarcopenic older adults.

Delirium.

Delirium is a common, often underdiagnosed, geriatric syndrome characterized by an acute change in attention and consciousness. As a neuropsychiatric disorder with an underlying organic cause, delirium has been considered a diagnosis reserved for the hospital setting. However, delirium is known to occur as both an acute and subacute condition that carries significant morbidity and mortality. Combined with its association with dementia and aging, this makes delirium an important topic for primary care providers to become more familiar with as they are tasked with caring for an aging population.