Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients.

In December 2017, the National Academy of Neuropsychology convened an interorganizational Summit on Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients in Denver, Colorado. The Summit brought together representatives of a broad range of stakeholders invested in the care of older adults to focus on the topic of cognitive health and aging. Summit participants specifically examined questions of who should be screened for cognitive impairment and how they should be screened in medical settings. This is important in the context of an acute illness given that the presence of cognitive impairment can have significant implications for care and for the management of concomitant diseases as well as pose a major risk factor for dementia. Participants arrived at general principles to guide future screening approaches in medical populations and identified knowledge gaps to direct future research. Key learning points of the summit included: recognizing the importance of educating patients and healthcare providers about the value of assessing current and baseline cognition;emphasizing that any screening tool must be appropriately normalized and validated in the population in which it is used to obtain accurate information, including considerations of language, cultural factors, and education; andrecognizing the great potential, with appropriate caveats, of electronic health records to augment cognitive screening and tracking of changes in cognitive health over time

Surgical assessment of the geriatric oncology patient

BACKGROUND: The aging population in the United States will correlate with an increased number of cancer diagnoses as cancer is primarily a disease of the elderly. Providing this ever-growing group of individuals with quality surgical management, while taking into account the unique needs and desires of this cohort, is a great challenge facing both geriatricians and surgeons going forward. The best approach to ensure that oncogeriatric patients receive the best tailored treatment is through the completion of a pre-surgical geriatric assessment. However, only a minority of oncogeriatric patients is undergoing a comprehensive pre-surgical geriatric assessment despite the majority of geriatricians and surgeons acknowledging its importance in order to properly risk stratify their patients. LITERATURE REVIEW FINDINGS: Multiple theories exist as to why geriatric assessments are not being utilized more frequently, but the most probable answer is that these assessments are very time-consuming, making it virtually impossible for incorporation into a healthcare provider’s busy schedule. Comprehensive literature review regarding geriatric assessments amongst the oncogeriatric population found that the most sensitive and specific domains of the geriatric assessments predicting morbidity and mortality include Frailty Index, Social Support Survey, Mini-Nutritional Assessment, and Geriatric Depression Screening. PROPOSED METHODS: A novel educational intervention will be proposed to teach Physician Assistant and Medical Students about the domains of the geriatric assessment most predictive of post-surgical risk during their surgical clerkship. The curriculum will utilize both simulation- and competency-based education training under the guidance of geriatricians and surgeons. Students will first learn the necessary skills in a controlled classroom environment and then proceed to incorporate these skills during their clerkship with patients on their service. CONCLUSIONS: The goal of the proposed method is to instill the confidence and skills necessary to provide an accurate geriatric assessment for oncogeriatric patients in future clinicians. The field of geriatric oncology is going to grow exponentially in the up-coming years and familiarizing future clinicians with the most predictive domains regarding surgical outcome will improve treatment outcomes for oncogeriatric patients in the immediate and foreseeable future

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

Display Enhanced Testing For Concussions And Mild Traumatic Brain Injury

Cognitive assessment systems and methods that provide an integrated solution for evaluating the presence or absence of cognitive impairment. The present invention is used to test cognitive functions of an individual including information processing speed, working memory, work list learning and recall, along with variations of these tasks. Immersive and non-immersive systems and methods are disclosed. Testing and results feedback using the present invention may be completed in real time, typically in less than 15 minutes.Emory UniversityGeorgia Tech Research Corporatio

Developing and implementing an integrated delirium prevention system of care:a theory driven, participatory research study

Background: Delirium is a common complication for older people in hospital. Evidence suggests that delirium incidence in hospital may be reduced by about a third through a multi-component intervention targeted at known modifiable risk factors. We describe the research design and conceptual framework underpinning it that informed the development of a novel delirium prevention system of care for acute hospital wards. Particular focus of the study was on developing an implementation process aimed at embedding practice change within routine care delivery. Methods: We adopted a participatory action research approach involving staff, volunteers, and patient and carer representatives in three northern NHS Trusts in England. We employed Normalization Process Theory to explore knowledge and ward practices on delirium and delirium prevention. We established a Development Team in each Trust comprising senior and frontline staff from selected wards, and others with a potential role or interest in delirium prevention. Data collection included facilitated workshops, relevant documents/records, qualitative one-to-one interviews and focus groups with multiple stakeholders and observation of ward practices. We used grounded theory strategies in analysing and synthesising data. Results: Awareness of delirium was variable among staff with no attention on delirium prevention at any level; delirium prevention was typically neither understood nor perceived as meaningful. The busy, chaotic and challenging ward life rhythm focused primarily on diagnostics, clinical observations and treatment. Ward practices pertinent to delirium prevention were undertaken inconsistently. Staff welcomed the possibility of volunteers being engaged in delirium prevention work, but existing systems for volunteer support were viewed as a barrier. Our evolving conception of an integrated model of delirium prevention presented major implementation challenges flowing from minimal understanding of delirium prevention and securing engagement of volunteers alongside practice change. The resulting Prevention of Delirium (POD) Programme combines a multi-component delirium prevention and implementation process, incorporating systems and mechanisms to introduce and embed delirium prevention into routine ward practices. Conclusions: Although our substantive interest was in delirium prevention, the conceptual and methodological strategies pursued have implications for implementing and sustaining practice and service improvements more broadly

Pain assessment for people with dementia: a systematic review of systematic reviews of pain assessment tools.

BACKGROUND: There is evidence of under-detection and poor management of pain in patients with dementia, in both long-term and acute care. Accurate assessment of pain in people with dementia is challenging and pain assessment tools have received considerable attention over the years, with an increasing number of tools made available. Systematic reviews on the evidence of their validity and utility mostly compare different sets of tools. This review of systematic reviews analyses and summarises evidence concerning the psychometric properties and clinical utility of pain assessment tools in adults with dementia or cognitive impairment. METHODS: We searched for systematic reviews of pain assessment tools providing evidence of reliability, validity and clinical utility. Two reviewers independently assessed each review and extracted data from them, with a third reviewer mediating when consensus was not reached. Analysis of the data was carried out collaboratively. The reviews were synthesised using a narrative synthesis approach. RESULTS: We retrieved 441 potentially eligible reviews, 23 met the criteria for inclusion and 8 provided data for extraction. Each review evaluated between 8 and 13 tools, in aggregate providing evidence on a total of 28 tools. The quality of the reviews varied and the reporting often lacked sufficient methodological detail for quality assessment. The 28 tools appear to have been studied in a variety of settings and with varied types of patients. The reviews identified several methodological limitations across the original studies. The lack of a 'gold standard' significantly hinders the evaluation of tools' validity. Most importantly, the samples were small providing limited evidence for use of any of the tools across settings or populations. CONCLUSIONS: There are a considerable number of pain assessment tools available for use with the elderly cognitive impaired population. However there is limited evidence about their reliability, validity and clinical utility. On the basis of this review no one tool can be recommended given the existing evidence

A new tool for the evaluation of the rehabilitation outcomes in older persons. a machine learning model to predict functional status 1 year ahead

Purpose To date, the assessment of disability in older people is obtained utilizing a Comprehensive Geriatric Assessment (CGA). However, it is often difficult to understand which areas of CGA are most predictive of the disability. The aim of this study is to evaluate the possibility to early predict—1year ahead—the disability level of a patient using machine leaning models. Methods Community-dwelling older people were enrolled in this study. CGA was made at baseline and at 1year follow-up. After collecting input/independent variables (i.e., age, gender, schooling followed, body mass index, information on smoking, polypharmacy, functional status, cognitive performance, depression, nutritional status), we performed two distinct Support Vector Machine models (SVMs) able to predict functional status 1year ahead. To validate the choice of the model, the results achieved with the SVMs were compared with the output produced by simple linear regression models. Results 218 patients (mean age = 78.01; SD = 7.85; male = 39%) were recruited. The combination of the two SVMs is able to achieve a higher prediction accuracy (exceeding 80% instances correctly classified vs 67% instances correctly classified by the combination of the two linear regression models). Furthermore, SVMs are able to classify both the three categories, self sufficiently, disability risk and disability, while linear regression model separates the population only in two groups (self-sufficiency and disability) without identifying the intermediate category (disability risk) which turns out to be the most critical one. Conclusions The development of such a model can contribute to the early detection of patients at risk of self-sufficiency loss