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2022 ◽  
Vol 44 ◽  
pp. 101245
Author(s):  
Paul D. Sonenthal ◽  
Mulinda Nyirenda ◽  
Noel Kasomekera ◽  
Regan H. Marsh ◽  
Emily B. Wroe ◽  
...  

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Thomas Knight ◽  
Catherine Atkin ◽  
Finbarr C Martin ◽  
Chris Subbe ◽  
Mark Holland ◽  
...  

Abstract Background The incorporation of acute frailty services into the acute care pathway is increasingly common. The prevalence and impact of acute frailty services in the UK are currently unclear. Methods The Society for Acute Medicine Benchmarking Audit (SAMBA) is a day of care survey undertaken annually within the UK. SAMBA 2019 (SAMBA19) took place on Thursday 27th June 2019. A questionnaire was used to collect hospital and patient-level data on the structure and organisation of acute care delivery. SAMBA19 sought to establish the frequency of frailty assessment tool use and describe acute frailty services nationally. Hospitals were classified based on the presence of acute frailty services and metrics of performance compared. Results A total of 3218 patients aged ≥70 admitted to 129 hospitals were recorded in SAMBA19. The use of frailty assessment tools was reported in 80 (62.0%) hospitals. The proportion of patients assessed for the presence of frailty in individual hospitals ranged from 2.2 to 100%. Bedded Acute Frailty Units were reported in 65 (50.3%) hospitals. There was significant variation in admission rates between hospitals. This was not explained by the presence of a frailty screening policy or presence of a dedicated frailty unit. Conclusion Two fifths of participating UK hospitals did not have a routine frailty screening policy: where this existed, rates of assessment for frailty were variable and most at-risk patients were not assessed. Responses to positive results were poorly defined. The provision of acute frailty services is variable throughout the UK. Improvement is needed for the aspirations of national policy to be fully realised.


2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Emily Rayens ◽  
Karen A Norris

Abstract Background Fungal infections are responsible for >1.5 million deaths globally per year, primarily in those with compromised immune function. This is concerning as the number of immunocompromised patients, especially in those without human immunodeficiency virus (HIV), has risen in the past decade. The purpose of this analysis was to provide the current prevalence and impact of fungal disease in the United States. Methods We analyzed hospital discharge data from the most recent (2018) Healthcare Cost and Utilization Project National Inpatient Sample, and outpatient visit data from the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey. Costs are presented in 2018 United States (US) dollars. Results In the 35.5 million inpatient visits documented in 2018 in the US, approximately 666 235 fungal infections were diagnosed, with an estimated attributable cost of $6.7 billion. Aspergillus, Pneumocystis, and Candida infections accounted for 76.3% of fungal infections diagnosed, and 81.1% of associated costs. Most fungal disease occurred in patients with elevated risk of infection. The visit costs, lengths of stay, and risks of mortality in this population were more than twice that of those without fungal diagnoses. A further 6.6 million fungal infections were diagnosed during outpatient visits. Conclusions Fungal disease is a serious clinical concern with substantial healthcare costs and significant increases in morbidity and mortality, particularly among predisposed patients. Increased surveillance, standardized treatment guidelines, and improvement in diagnostics and therapeutics are needed to support the rising numbers of at-risk patients.


10.2196/27008 ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. e27008
Author(s):  
Li-Hung Yao ◽  
Ka-Chun Leung ◽  
Chu-Lin Tsai ◽  
Chien-Hua Huang ◽  
Li-Chen Fu

Background Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a triage system, such as the 5-level emergency severity index, somewhat improves the process of ED treatment, it still heavily relies on the nurse’s subjective judgment and triages too many patients to emergency severity index level 3 in current practice. Hence, a system that can help clinicians accurately triage a patient’s condition is imperative. Objective This study aims to develop a deep learning–based triage system using patients’ ED electronic medical records to predict clinical outcomes after ED treatments. Methods We conducted a retrospective study using data from an open data set from the National Hospital Ambulatory Medical Care Survey from 2012 to 2016 and data from a local data set from the National Taiwan University Hospital from 2009 to 2015. In this study, we transformed structured data into text form and used convolutional neural networks combined with recurrent neural networks and attention mechanisms to accomplish the classification task. We evaluated our performance using area under the receiver operating characteristic curve (AUROC). Results A total of 118,602 patients from the National Hospital Ambulatory Medical Care Survey were included in this study for predicting hospitalization, and the accuracy and AUROC were 0.83 and 0.87, respectively. On the other hand, an external experiment was to use our own data set from the National Taiwan University Hospital that included 745,441 patients, where the accuracy and AUROC were similar, that is, 0.83 and 0.88, respectively. Moreover, to effectively evaluate the prediction quality of our proposed system, we also applied the model to other clinical outcomes, including mortality and admission to the intensive care unit, and the results showed that our proposed method was approximately 3% to 5% higher in accuracy than other conventional methods. Conclusions Our proposed method achieved better performance than the traditional method, and its implementation is relatively easy, it includes commonly used variables, and it is better suited for real-world clinical settings. It is our future work to validate our novel deep learning–based triage algorithm with prospective clinical trials, and we hope to use it to guide resource allocation in a busy ED once the validation succeeds.


2021 ◽  
Vol 11 (1) ◽  
pp. 71
Author(s):  
Ikenna Unigwe ◽  
Seonkyeong Yang ◽  
Hyun Jin Song ◽  
Wei-Hsuan Lo-Ciganic ◽  
Juan Hincapie-Castillo ◽  
...  

We examined the prevalence trends of non-human immunodeficiency virus (HIV) sexually transmitted infections (STI) and associated patient characteristics in U.S. ambulatory-care settings from 2005–2016. We conducted a retrospective repeated cross-sectional analysis using data from the National Ambulatory Medical Care Survey (NAMCS) for individuals aged 15–64 with a non-HIV STI-related visit. Data were combined into three periods (2005–2008, 2009–2012, and 2013–2016) to obtain reliable estimates. Logistic regression was used for analysis. A total of 19.5 million weighted, non-HIV STI-related ambulatory visits from 2005–2016 were identified. STI-related visits per 100,000 ambulatory care visits increased significantly over the study period: 206 (95% CI = 153–259), 343 (95% CI = 279–407), and 361 (95% CI = 277–446) in 2005–2008, 2009–2012, and 2013–2016, respectively (Ptrend = 0.003). These increases were mainly driven by increases in HPV-related visits (56 to 163 per 100,000 visits) from 2005–2008 to 2009–2012, followed by syphilis- or gonorrhea-related visits (30 to 67 per 100,000 visits) from 2009–2012 to 2013–2016. Higher odds of having STI-related visit were associated with younger age (aged 15–24: aOR = 4.45; 95% CI = 3.19–6.20 and aged 25–44: aOR = 3.59; 95% CI = 2.71–4.77) vs. 45–64-year-olds, Black race (aOR = 2.41; 95% CI = 1.78–3.25) vs. White, and HIV diagnosis (aOR = 10.60; 95% CI = 5.50–20.27) vs. no HIV diagnosis. STI-related office visits increased by over 75% from 2005–2016, and were largely driven by HPV-related STIs and syphilis- or gonorrhea-related STIs.


2021 ◽  
Vol 11 (1) ◽  
pp. 38
Author(s):  
Michael T. Phan ◽  
Daniel M. Tomaszewski ◽  
Cody Arbuckle ◽  
Sun Yang ◽  
Brooke Jenkins ◽  
...  

Objective: To evaluate trends in national emergency department (ED) adolescent opioid use in relation to reported pain scores. Methods: A retrospective, cross-sectional analysis on National Hospital Ambulatory Medical Care Survey (NHAMCS) data was conducted on ED visits involving patients aged 11–21 from 2008–2017. Crude observational counts were extrapolated to weighted estimates matching total population counts. Multivariate models were used to evaluate the role of a pain score in the reported use of opioids. Anchors for pain scores were 0 (no pain) and 10 (worst pain imaginable). Results: 31,355 observations were captured, which were extrapolated by the NHAMCS to represent 162,515,943 visits nationwide. Overall, patients with a score of 10 were 1.35 times more likely to receive an opioid than patients scoring a 9, 41.7% (CI95 39.7–43.8%) and 31.0% (CI95 28.8–33.3%), respectively. Opioid use was significantly different between traditional pain score cutoffs of mild (1–3) and moderate pain (4–6), where scores of 4 were 1.76 times more likely to receive an opioid than scores of 3, 15.5% (CI95 13.7–17.3%) and 8.8% (CI95 7.1–10.6%), respectively. Scores of 7 were 1.33 times more likely to receive opioids than scores of 6, 24.7% (CI95 23.0–26.3%) and 18.5% (CI95 16.9–20.0%), respectively. Fractures had the highest likelihood of receiving an opioid, as 49.2% of adolescents with a fracture received an opioid (CI95 46.4–51.9%). Within this subgroup, only adolescents reporting a fracture pain score of 10 had significantly higher opioid use than adjacent pain scores, where fracture patients scoring a 10 were 1.4 times more likely to use opioids than those scoring 9, 82.2% (CI95 76.1–88.4%) and 59.8% (CI95 49.0–70.5%), respectively. Conclusions: While some guidelines in the adult population have revised cut-offs and groupings of the traditional tiers on a 0–10 point pain scale, the adolescent population may also require further examination to potentially warrant a similar adjustment.


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