786 resultados para Standard of Care


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Technological advances during the past 30 years have dramatically improved survival rates for children with life-threatening conditions (preterm births, congenital anomalies, disease, or injury) resulting in children with special health care needs (CSHCN), children who have or are at increased risk for a chronic physical, developmental, behavioral, or emotional condition and who require health and related services beyond that required by children generally. There are approximately 10.2 million of these children in the United States or one in five households with a child with special health care needs. Care for these children is limited to home care, medical day care (Prescribed Pediatric Extended Care; P-PEC) or a long term care (LTC) facility. There is very limited research examining health outcomes of CSHCN and their families. The purpose of this research was to compare the effects of home care settings, P-PEC settings, and LTC settings on child health and functioning, family health and function, and health care service use of families with CSHCN. Eighty four CSHCN ages 2 to 21 years having a medically fragile or complex medical condition that required continual monitoring were enrolled with their parents/guardians. Interviews were conducted monthly for five months using the PedsQL TM Generic Core Module for child health and functioning, PedsQL TM Family Impact Module for family health and functioning, and Access to Care from the NS-CSHCN survey for health care services. Descriptive statistics, chi square, and ANCOVA were conducted to determine differences across care settings. Children in the P-PEC settings had a highest health care quality of life (HRQL) overall including physical and psychosocial functioning. Parents/guardians with CSHCN in LTC had the highest HRQL including having time and energy for a social life and employment. Parents/guardians with CSHCN in home care settings had the poorest HRQL including physical and psychosocial functioning with cognitive difficulties, difficulties with worry, communication, and daily activities. They had the fewest hours of employment and the most hours providing direct care for their children. Overall health care service use was the same across the care settings.

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This study aims to characterize the National Long-Term Care Network (NL-TCN) users. The Portuguese National Health Service, was restructured in 2006 with the creation of the National Long-Term Care Network to respond to new health and social needs concerning the continuity of care. Objectives- Analyse the sociodemographic profile of the network users and the review of hospital, local and regional management procedures. Methods-we used various methods of observational or experimental nature (data processing and presentation of results with the program Statistical Package for Social Sciences, version 20, descriptive statistics (frequencies, crosstabs and test chi-square)). The Pearson correlation test showed a positive correlation between time procedures at the local and regional management and hospital’s length of stay. Results- from a sample of 805 cases, 595 (74%) were admitted in the NL-TCN, a rate lower than the national average (86%). Almost half of the sample was admitted in Rehabilitation Units (46%), while nationally the highest number of admissions was in Home Care Teams (30%). The average time from hospital referral to network admission was 9.73 days with a positive correlation between referred network management procedures and hospital length of stay. Conclusions- For specialized units, the maximum waiting times were for the Long-Term and Support Units (mean 30.27 days) and the minimum waiting times were for Home Care Teams (mean 5.57 days). The average time between the local and regional management was 3.59 days. Almost 90% of referrals were orthopaedics, internal medicine and neurology and Network users were mostly elderly (average 75 years old), female and married. Most users were admitted to inpatient units (78%) and only 15% remained in their home town.

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The home support services are a social response in order to improve the quality of life directed predominantly for the elderly and for people with varying degrees of disability and dependence. Examples of those services are hygiene and personal comfort, medication, housekeeping and cleaning, preparation and monitoring of the meals; the dressing, etc. It is necessary to make society aware of the importance of these services to all those who need them. The general objective was to understand the most important relationships among informal caregivers, those who are care and home support services providers. Material and Methods. Data were collected through a questionnaire, using the various dimensions of the construct Quality SERVPERF model of service that matches the 22 items of SERVQUAL model. The various items used to assess the perception of care individuals and informal caregivers about the quality of home care services. 82 individuals participated providers of informal care, to receive home support services, and exclusion criteria, the fact of having a diagnosed psychiatric illness or psychological factors that prevent them from responding. The analysis was performed with SPSS and SEM-PLS for the estimation of the proposed structural model. Written consent was obtained, free and clear of each subject. Results and Conclusions. The results showed that the relationships with healthcare professionals are the most important positive effects on satisfaction. This research emphasizes the need to work closely with health professionals to improve the relationship between technicians and patients. Although current constructs appear to explain much of the satisfaction, it is recommended that the future researches exploit new variables, to get a better understanding of the effects of public health policies on the quality of life of these patients.

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This article considers the issue of poor care and how nurses should respond when they encounter it. Several reports and inquiries into failings in care have called into question the standards of care provided by nurses. Of equal concern is the observation that in some instances, poor care is unreported. While there may be underlying structural and organisational reasons for this, it is contended that nurses have a legal, moral and professional obligation to report poor care when they become aware of it.

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Older people have been identified as being at risk of social exclusion. However, despite the fact that care is commonly required in later life and the majority of that care provided by informal carers, a connection between social exclusion and informal care-receipt has rarely been considered. The aim of this study was to examine how informal care-receipt is related to social exclusion. A face-to-face questionnaire survey on social exclusion and informal care-receipt was carried out among older people (n=1255) living in Barnsley, United Kingdom. Multivariable analyses examined the association between social exclusion and categories of informal care-receipt: care receiver; assurance receiver; non-receiver with no need; non-receiver with need. Compared to being a non-receiver with no need participants were more likely to be a care receiver or assurance receiver if they had higher levels of social exclusion. The highest level of social exclusion, however, was found in non-receivers with need. Despite a lack of informal care and support, formal practical support and personal care was also low in this latter group. Findings are discussed in relation to the conceptualisation of care-receipt and how contact with medical services could be an opportunity for identification and appropriate referral of non-receivers with need.

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As a matter of fact, an Intensive Care Unit (ICU) stands for a hospital facility where patients require close observation and monitoring. Indeed, predicting Length-of-Stay (LoS) at ICUs is essential not only to provide them with improved Quality-of-Care, but also to help the hospital management to cope with hospital resources. Therefore, in this work one`s aim is to present an Artificial Intelligence based Decision Support System to assist on the prediction of LoS at ICUs, which will be centered on a formal framework based on a Logic Programming acquaintance for knowledge representation and reasoning, complemented with a Case Based approach to computing, and able to handle unknown, incomplete, or even contradictory data, information or knowledge.