Ambient activity monitoring systems produce large amounts of data, which can be used for health monitoring. The problem is that patterns in this data reflecting health status are not identified yet. In this paper the possibility is explored of predicting the functional health status (the motor score of AMPS = Assessment of Motor and Process Skills) of a person from data of binary ambient sensors. Data is collected of five independently living elderly people. Based on expert knowledge, features are extracted from the sensor data and several subsets are selected. We use standard linear regression and Gaussian processes for mapping the features to the functional status and predict the status of a test person using a leave-oneperson-out cross validation. The results show that Gaussian processes perform better than the linear regression model, and that both models perform better with the basic feature set than with location or transition based features. Some suggestions are provided for better feature extraction and selection for the purpose of health monitoring. These results indicate that automated functional health assessment is possible, but some challenges lie ahead. The most important challenge is eliciting expert knowledge and translating that into quantifiable features.
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Aims: In-hospital prescribing errors may result in patient harm, such as prolonged hospitalisation and hospital (re)admission, and may be an emotional burden for the prescribers and healthcare professionals involved. Despite efforts, in-hospital prescribing errors and related harm still occur, necessitating an innovative approach. We therefore propose a novel approach, in-hospital pharmacotherapeutic stewardship (IPS). The aim of this study was to reach consensus on a set of quality indicators (QIs) as a basis for IPS. Methods: A three-round modified Delphi procedure was performed. Potential QIs were retrieved from two systematic searches of the literature, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. In two written questionnaires and a focus meeting (held between the written questionnaire rounds), potential QIs were appraised by an international, multidisciplinary expert panel composed of members of the European Association for Clinical Pharmacology and Therapeutics (EACPT). Results: The expert panel rated 59 QIs and four general statements, of which 35 QIs were accepted with consensus rates ranging between 79% and 97%. These QIs describe the activities of an IPS programme, the team delivering IPS, the patients eligible for the programme and the outcome measures that should be used to evaluate the care delivered. Conclusions: A framework of 35 QIs for an IPS programme was systematically developed. These QIs can guide hospitals in setting up a pharmacotherapeutic stewardship programme to reduce in-hospital prescribing errors and improve in-hospital medication safety.
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Background: Geriatric rehabilitation positively influences health outcomes in older adults after acute events. Integrating mobile health (mHealth) technologies with geriatric rehabilitation may further improve outcomes by increasing therapy time and independence, potentially enhancing functional recovery. Previous reviews have highlighted positive outcomes but also the need for further investigation of populations receiving geriatric rehabilitation. Objective: Our main objective was to assess the effects of mHealth applications on the health status of older adults after acute events. A secondary objective was to examine the structure and process elements reported in these studies. Methods: Systematic review, including studies from 2010 to January 2024. Studies were eligible if they involved older adults’ post-acute care and used mHealth interventions, measured health outcomes and compared intervention and control groups. The adjusted Donabedian Structure-Process-Outcome (SPO) framework was used to present reported intervention processes and structures. Results: After initial and secondary screenings of the literature, a total of nine studies reporting 26 health outcomes were included. mHealth interventions ranged from mobile apps to wearables to web platforms. While most outcomes showed improvement in both the intervention and control groups, a majority favored the intervention groups. Reporting of integration into daily practice was minimal. Conclusion: While mHealth shows positive effects on health status in geriatric rehabilitation, the variability in outcomes and methodologies among studies, along with a generally high risk of bias, suggest cautious interpretation. Standardized measurement approaches and co-created interventions are needed to enhance successful uptake into blended care and keep geriatric rehabilitation accessible and affordable.
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The aim of this systematic review was to examine the association between malnutrition and oral health in older people (≥ 60 years of age). A comprehensive systematic literature search was performed in four databases (PubMed, CINAHL, Dentistry and Oral Sciences Source, and Embase) for literature from January 2000 to May 2020. Both observational and intervention studies were screened for eligibility. Two reviewers independently screened the search results to identify potential eligible studies, and assessed the methodological quality of the full-text studies. A total of 3240 potential studies were identified. After judgement for relevance, 10 studies (cross-sectional (n = 9), prospective cohort (n = 1)) met the inclusion criteria. Three studies described malnourished participants as having fewer teeth, or functional (tooth) units (FTUs), compared to well-nourished participants. Four studies reported soft tissue problems in malnourished participants, including red tongue with blisters, and dry or cracked lips. Subjective oral health was the topic in six studies, with poorer oral health and negative self-perception of oral health in malnourished elderly participants. There are associations between (at risk of) malnutrition and oral health in older people, categorized in hard and soft tissue conditions of the mouth, and subjective oral health. Future research should be focused on longitudinal cohort studies with proper determination of malnutrition and oral health assessments, in order to evaluate the actual association between malnutrition and oral health in older people.
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Objective: The aim of this study was to assess the relationship between frailty syndrome and the nutritional status of older patients. Material and methods: This cross-sectional study was conducted in a sample of 120 patients hospitalized at the Geriatric Clinic between January 2017 and May 2017. The research tools were the Frailty Instrument of the Survey of Health, Ageing and Retirement in Europe (SHARE-FI), including relevant anthropometric measurements and muscle strength measurement, and the Mini Nutritional Assessment (MNA). All the calculations were performed using the Statistica 10.0 program. The p-values lower than 0.05 were considered as statistically significant. Results: The mean age of the participants was 71 years (SD=9.03). Most participants were from urban areas. More than half of the participants (53.3%) were women. Based on the SHARE-FI, the frailty syndrome was found in 33.3% of the participants. The mean value in the MNA scale was 24.4 points (SD=3.4). The frailty syndrome was significantly correlated to gender (p<0.025), financial status (p=0.036) and MNA (p<0.01) score. A statistically significant difference was observed between gender (p=0.026), financial status (p=0.016), place of living (p=0.046) and MNA score. Conclusion: This study confirmed significant correlations between the frailty syndrome and the nutritional status of older adults. In terms of prevention and clinical application, it seems important to control the nutritional status of older people and the frailty syndrome. The above-mentioned scales should be used to evaluate patients, analyze the risk and plan the intervention for that group of patients.
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Preoperative functional status is a risk factor for developing postoperative complications (POC) in major abdominal and thoracic surgery, but this has hardly been evaluated in esophageal cancer patients undergoing esophagectomy. The aim of this prospective cohort study was to determine if preoperative functional status in esophageal cancer patients is associated with POC. From March 2012 to October 2014, esophageal cancer patients scheduled for esophagectomy at the outpatient clinic of a large tertiary referral center were eligible for the study. We measured inspiratory muscle strength, hand grip strength, physical activities, and health related quality of life as indicators of functional status one day before surgery. POC were scored according to the Clavien-Dindo Classification. We used univariate and multivariate backward regression analysis to determine the association between functional status and POC. We included 94 patients in the study and esophagectomy was performed in 90 patients from which 55 developed POC (61.1%). After multivariate analysis, none of the indicators of preoperative functional status were independently associated with POC (inspiratory muscle strength [OR 1.00; P = 0.779], hand grip strength [OR 0.99; P = 0.250], physical activities [OR 1.00; P = 0.174], and health related quality of life [OR 1.02; P = 0.222]). We concluded that preoperative functional status in our study cohort is not associated with POC after esophagectomy.
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Background: In frail older people with natural teeth factors like polypharmacy, reduced salivary flow, a decrease of oral self-care, general healthcare issues, and a decrease in dental care utilization contribute to an increased risk for oral complications. On the other hand, oral morbidity may have a negative impact on frailty. Objective: This study explored associations between oral health and two frailty measures in community-dwelling older people. Design: A cross-sectional study. Setting: The study was carried out in a Primary Healthcare Center (PHC) in The Netherlands. Participants: Of the 5,816 persons registered in the PHC, 1,814 persons were eligible for participation at the start of the study. Measurements: Two frailty measures were used: 1. Being at risk for frailty, using Electronical Medical Record (EMR) data, and: 2. Survey-based frailty using ‘The Groningen Frailty Indicator’ (GFI). For oral health measures, dental-record data (dental care utilization, dental status, and oral health information) and self-reported oral problems were recorded. Univariate regression analyses were applied to determine the association between oral health and frailty, followed by age- and sex-adjusted multivariate logistic regressions. Results: In total 1,202 community-dwelling older people were included in the study, 45% were male and the mean age was 73 years (SD=8). Of all participants, 53% was at risk for frailty (638/1,202), and 19% was frail based on the GFI (222/1,202). A dental emergency visit (Odds Ratio (OR)= 2.0, 95% Confidence Interval (CI)=1.33;3.02 and OR=1.58, 95% CI=1.00;2.49), experiencing oral problems (OR=2.07, 95% CI=1.52;2.81 and OR=2.87, 95% CI= 2.07;3.99), and making dietary adaptations (OR=2.66, 95% CI=1.31;5.41 and OR=5.49, 95% CI= 3.01;10.01) were associated with being at risk for frailty and surveybased frailty respectively. Conclusions: A dental emergency visit and self-reported oral health problems are associated with frailty irrespective of the approach to its measurement. Healthcare professionals should be aware of the associations of oral health and frailty in daily practice.
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Background: Over the years, a plethora of frailty assessment tools has been developed. These instruments can be basically grouped into two types of conceptualizations – unidimensional, based on the physical–biological dimension – and multidimensional, based on the connections among the physical, psychological, and social domains. At present, studies on the comparison between uni- and multidimensional frailty measures are limited. Objective: The aims of this paper were: 1) to compare the prevalence of frailty obtained using a uni- and a multidimensional measure; 2) to analyze differences in the functional status among individuals captured as frail or robust by the two measures; and 3) to investigate relations between the two frailty measures and disability.
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Background: Nurse-sensitive indicators and nurses’ satisfaction with the quality of care are two commonly used ways to measure quality of nursing care. However, little is known about the relationship between these kinds of measures. This study aimed to examine concordance between nurse-sensitive screening indicators and nurse-perceived quality of care. Methods: To calculate a composite performance score for each of six Dutch non-university teaching hospitals, the percentage scores of the publicly reported nurse-sensitive indicators: screening of delirium, screening of malnutrition, and pain assessments, were averaged (2011). Nurse-perceived quality ratings were obtained from staff nurses working in the same hospitals by the Dutch Essentials of Magnetism II survey (2010). Concordance between the quality measures was analyzed using Spearman’s rank correlation. Results: The mean screening performances ranged from 63 % to 93 % across the six hospitals. Nurse-perceived quality of care differed significantly between the hospitals, also after adjusting for nursing experience, educational level, and regularity of shifts. The hospitals with high-levels of nurse-perceived quality were also high-performing hospitals according to nurse-sensitive indicators. The relationship was true for high-performing as well as lower-performing hospitals, with strong correlations between the two quality measures (r S = 0.943, p = 0.005). Conclusions: Our findings showed that there is a significant positive association between objectively measured nurse sensitive screening indicators and subjectively measured perception of quality. Moreover, the two indicators of quality of nursing care provide corresponding quality rankings. This implies that improving factors that are associated with nurses’ perception of what they believe to be quality of care may also lead to better screening processes. Although convergent validity seems to be established, we emphasize that different kinds of quality measures could be used to complement each other, because various stakeholders may assign different values to the quality of nursing care.
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Introduction: This study evaluates the course of physical fitness and nutritional status during curative therapy for esophageal cancer, after implementation of a prehabilitation program. Additionally, the impact of baseline physical fitness level and severe postoperative complications on the course of individual patients were explored. Materials and methods: This multicenter, observational cohort study included patients with esophageal cancer following curative treatment. Prehabilitation, consisting of supervised exercise training and nutritional counseling was offered as standard care to patients after neoadjuvant therapy, prior to surgery. Primary outcome measures included change of exercise capacity, hand grip strength, self-reported physical functioning, Body Mass Index, and malnutrition risk from diagnosis to 2–6 months postoperatively. Analyses over time were performed using linear mixed models, and linear mixed regression models to investigate the impact of baseline level and severe postoperative complications. Results: Hundred sixty-eight patients were included (mean age 65.9 ± 8.6 years; 78.0 % male). All parameters (except for malnutrition risk) showed a decline during neoadjuvant therapy (p < .05), an improvement during prehabilitation (p < .005) and a decline postoperatively (p < .001), with a high heterogeneity between patients. Change in the outcomes from baseline to postoperatively was not different for patients with or without a severe complication. Better baseline physical fitness and nutritional status were significantly associated with a greater decline postoperatively (p < .001). Conclusion: This study demonstrates a notable decline during neoadjuvant therapy, that fully recovers during prehabilitation, and a subsequent long lasting decline postoperatively. The heterogeneity in the course of physical fitness and nutritional status underlines the importance of individualized monitoring.
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