BackgroundVitamin D deficiency is known to be highly prevalent in older persons. However, the prevalence in the subgroup of frail older hospitalized patients is not clear. We sought to investigate the prevalence and predictors of vitamin D deficiency in frail older hospitalized patients.Methods217 consecutively geriatric hospitalized patients with routine measurements of 25-hydroxyvitamin D [25 (OH)D] at hospital admission were analyzed retrospectively, including information of previous vitamin D supplementation and the geriatric assessment. Serum 25 (OH)D concentrations < 20 ng/ml and between 20 and 29.99 ng/ml were classified as deficient and insufficient, respectively, whereas concentrations ≥30 ng/ml were considered as desirable. A stepwise binary logistic regression model was performed to assess the simultaneous effects of age, gender and geriatric assessments on the prevalence of low vitamin D concentration.ResultsMean age of the cohort was 81.6 ± 8.0 years (70.0% females). Mean serum 25(OH)D was 12.7 ± 12.9 ng/ml. Of 167 (77%) subjects without known previous vitamin D supplementation, only 21 (12.6%) had serum concentrations ≥20 ng/ml and only 8 (4.2%) had desirable serum concentrations ≥30 ng/ml. In total population, 146 (87.4%) participants were vitamin D deficient. Despite vitamin D supplementation, 22 of 50 participants (44.0%) were vitamin D deficient and only 19 (38.0%) had desirable concentrations of ≥30 ng/ml. In a stepwise logistic regression analysis, only previous intake of vitamin D supplementation and high Geriatric Depression Scale score (GDS-15) were significantly associated with vitamin D deficiency.ConclusionsIn the group of frail older hospitalized patients without previous vitamin D supplementation, the prevalence of inadequate vitamin D concentrations is extremely high. Therefore, usefulness of the routine measurement of vitamin D status before initiating of supplementation appears to be questionable in this patient group.
Background The ability to walk is an important indicator of general health and mobility deficits have wide-ranging economic implications. We undertook a systematic review to elucidate the impact of walking parameters on health care costs. Methods Publications reporting on associations between health care costs and walking parameters were identified by a systematic literature search in MEDLINE, Embase, and manual reference screening, following the PRISMA reporting guidelines. First, titles and abstracts were screened by two independent reviewers followed by a review of the full articles if they met the inclusion criteria. Costs were converted to US-Dollars with inflation adjustment for 2021. A narrative synthesis was performed. Results Ten studies conducted between 2001 and 2021 fulfilled the inclusion criteria. Assessment of walking ability was carried out via patient reported outcomes, performance tests, or using wearable digital devices. Walking more than one hour per day, a faster walking speed and the ability to walk without impairments are associated with significant lower health care costs. A higher number of steps per day is associated with significant lower costs in two simulation studies, while in the study using a digital device, taking more than 10,000 steps per day is not significantly associated with lower direct costs. The heterogeneity of mobility assessments and of economic analyses both precluded a quantitative synthesis. Conclusion Cross-sectional and observational studies from this systematic review suggest a significant association of better walking performance with lower health care costs. Future health economic research and health technology assessments should use quantifiable mobility outcomes when evaluating new drugs or non-pharmacological interventions.
Background/Aims Medical documentation is an important and unavoidable part of a health professional's working day. However, the time required for medical documentation is often viewed negatively, particularly by clinicians with heavy workloads. Digital speech recognition has become more prevalent and is being used to optimise working time. This study evaluated the time and cost savings associated with speech recognition technology, and its potential for improving healthcare processes. Methods Clinicians were directly observed while completing medical documentation. A total of 313 samples were collected, of which 163 used speech recognition and 150 used typing methods. The time taken to complete the medical form, the error rate and error correction time were recorded. A survey was also completed by 31 clinicians to gauge their level of acceptance of speech recognition software for medical documentation. Two-sample t-tests and Mann–Whitney U tests were performed to determine statistical trends and significance. Results On average, medical documentation using speech recognition software took just 5.11 minutes to complete the form, compared to 8.9 minutes typing, representing significant time savings. The error rate was also found to be lower for speech recognition software. However, 55% of clinicians surveyed stated that they would prefer to type their notes rather than use speech recognition software and perceived the error rate of this software to be higher than typing. Conclusions The results showed that there are both temporal and financial advantages of speech recognition technology over text input for medical documentation. However, this technology had low levels of acceptance among staff, which could have implications for the uptake of this method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.