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71.
目的:总结典型国家基层卫生服务提供中实现医防整合的经验,为我国基层医疗卫生服务整合提供借鉴。方法:本研究方法为文献研究。结果:在个人层面,英国、泰国、古巴培养全科医生作为"守门人"并将其作为提供医防整合服务的主体;在机构层面,各国基层机构组成服务网络,内部强调跨学科合作;在体系层面,通过横向合作和有序的首诊与转诊协调服务;国家立法保障和健康保险筹资等引导支持基层医疗卫生服务整合。结论:培养和配置高质量的医防一体的全科医生、促进机构跨学科融合、通过立法和筹资体系予以保障是各国提供基层整合型服务的核心,值得我国基层医防服务整合借鉴。  相似文献   
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Objective

Low psoas muscle area is shown to be an indicator for worse postoperative outcome in patients undergoing vascular surgical. Additionally, it has been associated with longer durations of hospital stay in patients with cancer who undergo surgery and subsequently greater health care costs in Europe and the United States. We sought to evaluate this effect on hospital expenditure for patients undergoing vascular repair in a health care system with universal access.

Methods

Skeletal muscle mass was assessed on preoperative abdominal computed tomography scans of patients undergoing open aortic aneurysm repair in a retrospective fashion. The skeletal muscle index (SMI) was used to define low muscle mass. Health care costs were obtained for all patients and the relationship between a low SMI and higher costs was explored using linear regression and cross-sectional analysis.

Results

We included 156 patients (81.5% male) with a median age of 72 years undergoing elective surgery for infrarenal abdominal aortic aneurysm in this analysis. The median SMI for patients with low skeletal muscle mass was 53.21 cm2/kg and for patients without, 70.07 cm2/kg. Hospital duration of stay was 2 days longer in patients with low skeletal muscle mass as compared with patients with normal (14 days vs 11 days; P = .001), as was duration of intensive care stay (3 days vs 1 day; P = .01). The median overall hospital costs were €10,460 higher for patients with a low SMI as compared with patients with a normal physical constitution (€53,739 [interquartile range, €45,007-€62,471] vs €43,279 [interquartile range, €39,509-€47,049]; P = .001). After confounder adjustment, a low SMI was associated with a 14.68% cost increase in overall hospital costs, for a cost increase of €6521.

Conclusions

Low skeletal muscle mass is independently associated with higher hospital as well as intensive care costs in patients undergoing elective aortic aneurysm repair. Strategies to reduce this risk factor are warranted for these patients.  相似文献   
73.
《Vaccine》2019,37(43):6255-6261
Health workers represent an important target group for seasonal influenza vaccination because of their increased risk of infection as well as the risk of transmitting infection to vulnerable patients in the health care setting. Moreover, seasonal vaccination of health workers contributes to pandemic preparedness. However, many countries, especially in Africa and Asia, do not have policies for health worker influenza vaccination. In countries where such policies exist, vaccination coverage is often low. The World Health Organization (WHO) is developing a manual to guide the introduction of seasonal influenza vaccination of health workers. An Independent External Advisory Group (IEAG) that is advising WHO on the content of the manual met to discuss issues that are relevant and often unique to health worker vaccination. This meeting report summarizes the main issues that were discussed and the outcomes of the discussion. The issues include policy considerations, including the evidence in support of health worker vaccination; categorization and prioritization of health workers; the choice of vaccination strategy; its integration into broader health worker vaccination and occupational health policies; planning and management of vaccination, particularly the approaches for communication and demand generation; and the challenges with monitoring and evaluation of health worker vaccination, especially in low and middle-income countries.  相似文献   
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Conducting high-quality clinical research is dependent on merging scientific rigor with the clinical environment. This is often a complex endeavor that may include numerous barriers and competing interests. Overcoming these challenges and successfully integrating clinical research programs into clinical practice settings serving rehabilitation outpatients is beneficial from both a logistical perspective (eg, supports efficient and successful research procedures) and the establishment of a truly patient-centered research approach. Leveraging our experience with navigating this research-clinical care relationship, this article (1) proposes the Patient-Centered Framework for Rehabilitation Research, a model for integrating patient-centered research in an outpatient clinical setting that incorporates a collaborative, team-based model encompassing patient-centered values, as well as strategies for recruitment and retention, with a focus on populations living with disabilities or chronic diseases; (2) describes application of this framework in a comprehensive specialty multiple sclerosis center with both general strategies and specific examples to guide adaptation and implementation in other settings; and (3) discusses the effect of the framework as a model in 1 center, as well as the need for additional investigation and adaptation for other populations. The 5 interconnected principles incorporated in the Framework and which prioritize patient-centeredness include identifying shared values, partnering with the clinical setting, engaging with the population, building relationships with individuals, and designing accessible procedures. The Patient-Centered Framework for Rehabilitation Research is a model presented as an adaptable roadmap to guide researchers in hopes of not only improving individual patients’ experiences but also the quality and relevance of rehabilitation research as a whole. Future investigation is needed to test the Framework in other settings.  相似文献   
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《Pancreatology》2022,22(5):665-670
Background and objectivesHyperlipasemia is highly prevalent among coronavirus disease 2019 (COVID-19) patients. The aim of this study was to assess the effect of lipase activity, measured at the time of admission, on the clinical course and mortality in COVID-19 patients.MethodsThe population of this study comprised 12,139 patients who were hospitalized due to COVID-19 between June 2020 and June 2021 in a pandemic hospital. Of these, 8819 patients were excluded from the study due to missing data, four patients were excluded due to a diagnosis of acute pancreatitis (according to the revised Atlanta criteria), and 72 patients were excluded due to alcohol use or having a history of chronic pancreatitis. The final study sample consisted of the remaining 3244 COVID-19 patients. Laboratory results, intensive care unit (ICU) follow-up periods, the need for mechanical ventilation, and mortality rates were compared between the normal lipase activity and high lipase activity groups.ResultsThere were 968 (29.8%) patients with high lipase activity at the time of admission. The rate of ICU admission was 36.1% vs. 9.9% (p < 0.001), mechanical ventilation requirement rates were 33.7% vs. 8.3% (p < 0.001), and mortality rates were as 24.6% vs. 6.4% (p < 0.001) in the high lipase activity group compared to the normal lipase activity group. Multivariate regression analysis revealed that high lipase activity was an independent factor in predicting mortality in hospitalized COVID-19 patients (odds ratio [OR]: 3.191, p < 0.001).ConclusionElevated lipase activity without acute pancreatitis at the time of admission in COVID-19 patients was determined as an independent predictor of poor prognosis.  相似文献   
80.
The coronavirus disease 2019 (COVID-19) has currently caused the mortality of millions of people around the world. Aside from the direct mortality from the COVID-19, the indirect effects of the pandemic have also led to an increase in the mortality rate of other non-COVID patients. Evidence indicates that novel COVID-19 pandemic has caused an inflation in acute cardiovascular mortality, which did not relate to COVID-19 infection. It has in fact increased the risk of death in cardiovascular disease (CVD) patients. For this purpose, it is dramatically inevitable to monitor CVD patients’ vital signs and to detect abnormal events before the occurrence of any critical conditions resulted in death. Internet of things (IoT) and health monitoring sensors have improved the medical care systems by enabling latency-sensitive surveillance and computing of large amounts of patients’ data. The major challenge being faced currently in this problem is its limited scalability and late detection of cardiovascular events in IoT-based computing environments. To this end, this paper proposes a novel framework to early detection of cardiovascular events based on a deep learning architecture in IoT environments. Experimental results showed that the proposed method was able to detect cardiovascular events with better performance (95.30% average sensitivity and 95.94% mean prediction values).  相似文献   
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