Accounting for the Hierarchical Structure in Veterans Health Administration Data: Differences in Healthcare Utilization between Men and Women Veterans

Women currently constitute 15% of active United States of America military service personnel, and this proportion is expected to double in the next 5 years. Previous research has shown that healthcare utilization and costs differ in women US Veterans Health Administration (VA) patients compared to men. However, none have accounted for the potential effects of clustering on their estimates of healthcare utilization. US Women Veterans are more likely to serve in specific military branches (e.g. Army), components (e.g. National Guard), and ranks (e.g. officer) than men. These factors may confer different risk and protection that can affect subsequent healthcare needs. Our study investigates the effects of accounting for the hierarchical structure of data on estimates of the association between gender and VA healthcare utilization. The sample consisted of data on 406,406 Veterans obtained from VA's Operation Enduring Freedom/ Operation Iraqi Freedom roster provided by Defense Manpower Data Center - Contingency Tracking System Deployment File. We compared three statistical models, ordinary, fixed and random effects hierarchical logistic regression, in order to assess the association of gender with healthcare utilization, controlling for branch of service, component, rank, age, race, and marital status. Gender was associated with utilization in ordinary logistic and, but not in fixed effects hierarchical logistic or random effects hierarchical logistic regression models. This points out that incomplete inference could be drawn by ignoring the military structure that may influence combat exposure and subsequent healthcare needs. Researchers should consider modeling VA data using methods that account for the potential clustering effect of hierarchy

The Method of Randomization for Cluster-Randomized Trials: Challenges of Including Patients with Multiple Chronic Conditions

Cluster-randomized clinical trials (CRT) are trials in which the unit of randomization is not a participant but a group (e.g. healthcare systems or community centers). They are suitable when the intervention applies naturally to the cluster (e.g. healthcare policy); when lack of independence among participants may occur (e.g. nursing home hygiene); or when it is most ethical to apply an intervention to all within a group (e.g. school-level immunization). Because participants in the same cluster receive the same intervention, CRT may approximate clinical practice, and may produce generalizable findings. However, when not properly designed or interpreted, CRT may induce biased results. CRT designs have features that add complexity to statistical estimation and inference. Chief among these is the cluster-level correlation in response measurements induced by the randomization. A critical consideration is the experimental unit of inference; often it is desirable to consider intervention effects at the level of the individual rather than the cluster. Finally, given that the number of clusters available may be limited, simple forms of randomization may not achieve balance between intervention and control arms at either the cluster- or participant-level. In non-clustered clinical trials, balance of key factors may be easier to achieve because the sample can be homogenous by exclusion of participants with multiple chronic conditions (MCC). CRTs, which are often pragmatic, may eschew such restrictions. Failure to account for imbalance may induce bias and reducing validity. This article focuses on the complexities of randomization in the design of CRTs, such as the inclusion of patients with MCC, and imbalances in covariate factors across clusters

Associations between home deaths and end-of-life nursing care trajectories for community-dwelling people: a population-based registry study

Background: Few studies have estimated planned home deaths compared to actual place of death in a general population or the longitudinal course of home nursing services and associations with place of death. We aimed to investigate trajectories of nursing services, potentially planned home deaths regardless of place of death; and associations of place of death with potentially planned home deaths and nursing service trajectories, by analyzing data from the last 90 days of life. Methods: A retrospective longitudinal study with data from the Norwegian Cause of Death Registry and National registry for statistics on municipal healthcare services included all community-dwelling people who died in Norway 2012–2013 (n = 53,396). We used a group-based trajectory model to identify joint trajectories of home nursing (hours per week) and probability of a skilled nursing facility (SNF) stay, each of the 13 weeks leading up to death. An algorithm estimated potentially planned home deaths. We used a multinomial logistic regression model to estimate associations of place of death with potentially planned home deaths, trajectories of home nursing and short-term SNF. Results: We identified four home nursing service trajectories: no (46.5%), accelerating (7.6%), decreasing (22.1%), and high (23.5%) home nursing; and four trajectories of the probability of a SNF stay: low (69.0%), intermediate (6.7%), escalating (15.9%), and increasing (8.4%) SNF. An estimated 24.0% of all deaths were potentially planned home deaths, of which a third occurred at home. Only high home nursing was associated with increased likelihood of a home death (adjusted relative risk ratio (aRRR) 1.29; CI 1.21–1.38). Following any trajectory with elevated probability of a SNF stay reduced the likelihood of a home death. Conclusions: We estimated few potentially planned home deaths. Trajectories of home nursing hours and probability of SNF stays indicated possible effective palliative home nursing for some, but also missed opportunities of staying at home longer at the end-of-life. Continuity of care seems to be an important factor in palliative home care and home death.publishedVersio

Multimorbidity and Associated Informal Care Receiving Characteristics for US Older Adults: a Latent Class Analysis

Older adults with varying patterns of multimorbidity may require distinct types of care and rely on informal caregiving to meet their care needs. This study aims to identify groups of older adults with distinct, empirically-determined multimorbidity patterns and compare characteristics of informal care received among estimated classes. Methods Data are from the 2011 National Health and Aging Trends Study (NHATS). Ten chronic conditions were included to estimate multimorbidity patterns among 7532 individuals using latent class analysis. Multinomial logistic regression model was estimated to examine the association between sociodemographic characteristics, health status and lifestyle variables, care-receiving characteristics and latent class membership. Results A four-class solution identified the following multimorbidity groups: some somatic conditions with moderate cognitive impairment (30%), cardiometabolic (25%), musculoskeletal (24%), and multisystem (21%). Compared with those who reported receiving no help, care recipients who received help with household activities only (OR = 1.44, 95% CI 1.05–1.98), mobility but not self-care (OR = 1.63, 95% CI 1.05–2.53), or self-care but not mobility (OR = 2.07, 95% CI 1.29–3.31) had greater likelihood of being in the multisystem group versus the some-somatic group. Having more caregivers was associated with higher odds of being in the multisystem group compared with the some-somatic group (OR = 1.09, 95% CI 1.00-1.18), whereas receiving help from paid helpers was associated with lower odds of being in the multisystem group (OR = 0.36, 95% CI 0.19–0.77). Conclusions Results highlighted different care needs among persons with distinct combinations of multimorbidity, in particular the wide range of informal needs among older adults with multisystem multimorbidity. Policies and interventions should recognize the differential care needs associated with multimorbidity patterns to better provide person-centered care

Pain, Complex Chronic Conditions and Potential Inappropriate Medication in People with Dementia. Lessons Learnt for Pain Treatment Plans Utilizing Data from the Veteran Health Administration

Alzheimer’s disease and related dementias (ADRD), pain and chronic complex conditions (CCC) often co-occur leading to polypharmacy and with potential inappropriate medications (PIMs) use, are important risk factors for adverse drug reactions and hospitalizations in older adults. Many US veterans are at high risk for persistent pain due to age, injury or medical illness. Concerns about inadequate treatment of pain—accompanied by evidence about the analgesic efficacy of opioids—has led to an increase in the use of opioid medications to treat chronic pain in the Veterans Health Administration (VHA) and other healthcare systems. This study aims to investigate the relationship between receipt of pain medications and centrally (CNS) acting PIMs among veterans diagnosed with dementia, pain intensity, and CCC 90-days prior to hospitalization. The final analytic sample included 96,224 (81.7%) eligible older veterans from outpatient visits between October 2012–30 September 2013. We hypothesized that veterans with ADRD, and severe pain intensity may receive inappropriate pain management and CNS-acting PIMs. Seventy percent of the veterans, and especially people with ADRD, reported severe pain intensity. One in three veterans with ADRD and severe pain intensity have an increased likelihood for CNS-acting PIMs, and/or opioids. Regular assessment and re-assessment of pain among older persons with CCC, patient-centered tapering or discontinuation of opioids, alternatives to CNS-acting PIMs, and use of non-pharmacological approaches should be considered.publishedVersio

Mental-Somatic Multimorbidity in Trajectories of Cognitive Function for Middle-Aged and Older Adults

Multimorbidity may confer higher risk for cognitive decline than any single constituent disease. This study aims to identify distinct trajectories of cognitive impairment probability among middle-aged and older adults, and to assess the effect of changes in mental-somatic multimorbidity on these distinct trajectories

Digital phenotyping by wearable-driven artificial intelligence in older adults and people with Parkinson's disease: Protocol of the mixed method, cyclic ActiveAgeing study

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Active ageing is described as the process of optimizing health, empowerment, and security to enhance the quality of life in the rapidly growing population of older adults. Meanwhile, multimorbidity and neurological disorders, such as Parkinson’s disease (PD), lead to global public health and resource limitations. We introduce a novel user-centered paradigm of ageing based on wearable-driven artificial intelligence (AI) that may harness the autonomy and independence that accompany functional limitation or disability, and possibly elevate life expectancy in older adults and people with PD. Methods: ActiveAgeing is a 4-year, multicentre, mixed method, cyclic study that combines digital phenotyping via commercial devices (Empatica E4, Fitbit Sense, and Oura Ring) with traditional evaluation (clinical assessment scales, in-depth interviews, and clinical consultations) and includes four types of participants: (1) people with PD and (2) their informal caregiver; (3) healthy older adults from the Helgetun living environment in Norway, and (4) people on the Helgetun waiting list. For the first study, each group will be represented by N = 15 participants to test the data acquisition and to determine the sample size for the second study. To suggest lifestyle changes, modules for human expert-based advice, machine-generated advice, and self-generated advice from accessible data visualization will be designed. Quantitative analysis of physiological data will rely on digital signal processing (DSP) and AI techniques. The clinical assessment scales are the Unified Parkinson’s Disease Rating Scale (UPDRS), Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory (GAI), Apathy Evaluation Scale (AES), and the REM Sleep Behaviour Disorder Screening Questionnaire (RBDSQ). A qualitative inquiry will be carried out with individual and focus group interviews and analysed using a hermeneutic approach including narrative and thematic analysis techniques. Discussion: We hypothesise that digital phenotyping is feasible to explore the ageing process from clinical and lifestyle perspectives including older adults and people with PD. Data is used for clinical decision-making by symptom tracking, predicting symptom evolution, and discovering new outcome measures for clinical trials.publishedVersio

Geriatric assessment with management in cancer care: Current evidence and potential mechanisms for future research

Older adults with cancer represent a complex patient population. Geriatric assessment (GA) is recommended to evaluate the medical and supportive care needs of this group. “GA with management” is a term encompassing the resultant medical decisions and interventions implemented in response to vulnerabilities identified on GA. In older, non-cancer patients, GA with management has been shown to improve a variety of outcomes, such as reducing functional decline and health care utilization. However, the role of GA with management in the older adult with cancer is less well established. Rigorous clinical trials of GA with management are necessary to develop an evidence base and support its use in the routine oncology care of older adults. At the recent U-13 conference, “Design and Implementation of Intervention Studies to Improve or Maintain Quality of Survivorship in Older and/or Frail Adults with Cancer,” a session was dedicated to developing research priorities in GA with management. Here we summarize identified knowledge gaps in GA with management studies for older patients with cancer and propose areas for future research

Perceptions of generic medicines and medication adherence after percutaneous coronary intervention: a prospective multicentre cohort study

Objective: To determine patient perceptions of generic medicines 2 and 6 months after percutaneous coronary intervention (PCI), and to determine whether these perceptions moderate medication adherence. Design: Prospective multicentre cohort study with repeated measures of perceptions of generic medicines and medication adherence. Setting: The CONCARDPCI study conducted at seven large referral PCI centres in Norway and Denmark between June 2017 and May 2020. Participants: A total of 3417 adults (78% men), using both generic and brand name medicines, with a mean age of 66 years (SD 11) who underwent PCI were followed up 2 and 6 months after discharge from hospital. Main outcome measures: Perceptions of generic medicines were the main outcome. The secondary outcome was medication adherence. Results: Perceptions of generic medicines were significantly more negative at 2 than at 6 months (1.10, 95% CI 0.41 to 1.79, p=0.002). Female sex (−4.21, 95% CI −6.75 to −1.71, p=0.001), older age (−0.12, 95% CI −0.23 to −0.02, p=0.020), lower education level (overall p<0.001), ethnicity (overall p=0.002), Norwegian nationality (10.27, 95% CI 8.19 to 12.40, p<0.001) and reduced self-reported health status (0.19, 95% CI 0.09 to 0.41, p=0.003) were significantly associated with negative perceptions of generic medicines. There was no evidence to suggest that perceptions of generic medicines moderate the association between sociodemographic and clinical variables and medication adherence (p≥0.077 for all covariates). Moreover, self-reported medication adherence was high, with 99% scoring at or above the Medication Adherence Report Scale midpoint at both time points. There were no substantial correlations between negative perceptions of generic medicines and medication non-adherence at 2 months (r=0.041, 95% CI 0.002 to 0.081, p=0.037) or 6 months (r=0.038, 95% CI −0.005 to 0.081, p=0.057). Conclusions: Mistrust and uncertainty about the safety and efficacy of generic medicines remains in a sizeable proportion of patients after PCI. This applies especially to those of lower socioeconomic status, older age, female sex, immigrants and those with poorer mental health. However, this study demonstrated a shift towards more positive perceptions of generic medicines in the longer term.publishedVersio

Increased TLR4 Expression and Downstream Cytokine Production in Immunosuppressed Adults Compared to Non-Immunosuppressed Adults

An increasing number of patients have medical conditions with altered host immunity or that require immunosuppressive medications. While immunosuppression is associated with increased risk of infection, the precise effect of immunosuppression on innate immunity is not well understood. We studied monocyte Toll-like receptor (TLR) expression and cytokine production in 137 patients with autoimmune diseases who were maintained on immunosuppressive medications and 419 non-immunosuppressed individuals.Human peripheral blood monocytes were assessed for surface expression of TLRs 1, 2, and 4. After incubation with TLR agonists, in vitro production of the cytokines IL-8, TNFalpha, and MIF were measured by ELISA as a measure of TLR signaling efficiency and downstream effector responsiveness. Immunosuppressed patients had significantly higher TLR4 surface expression when compared to non-immunosuppressed adults (TLR4 %-positive 70.12+/-2.28 vs. 61.72+/-2.05, p = 0.0008). IL-8 and TNF-alpha baseline levels did not differ, but were significantly higher in the autoimmune disease group following TLR stimulation. By contrast, baseline MIF levels were elevated in monocytes from immunosuppressed individuals. By multivariable analyses, IL-8 and TNFalpha, but not MIF levels, were associated with the diagnosis of an underlying autoimmune disease. However, only MIF levels were significantly associated with the use of immunosuppressive medications.Our results reveal that an enhanced innate immune response is a feature of patients with autoimmune diseases treated with immunosuppressive agents. The increased risk for infection evident in this patient group may reflect a dysregulation rather than a simple suppression of innate immunity