202 resultados para Economics, Hospital


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Objectives: This study aimed to gather data on the nutritional status of older patients attending Cork University Dental School and Hospital for treatment in the Restorative Department. Information was also collected about the medical status of the patients including the prevalence of self-reported xerostomia.
Methods: Data was collected by a self-completion questionnaire followed by a brief clinical examination. Nutritional Status was measured using the short version of the Mini Nutritional Assessment (MNA) which recorded patients’ Body Mass Index (BMI). The MNA consists of 6 parameters (including questions relating to patients’ history and anthropometric data) with a maximum total of 14 points. Scores of 12-14 indicate “normal nutritional status” whilst those between 8 and 11 indicate a patient “at risk of malnutrition”. Scores lower than 8 are an indication a patient who is “malnourished”. All patients attending Cork University Dental School and Hospital aged 65 years and older were invited to participate in the study.

Results: A total of 22 subjects participated in this study. Twelve patients were partially dentate with 10 edentulous. The results from the MNA indicate that 11 patients were of “normal nutritional status” with 11 patients identified as being “at risk of malnutrition”. None of the subjects were “malnourished”. Edentate patients generally recorded lower MNA scores than partially dentate patients. In total, 9 patients reported experiencing xerostomia with 8 indicating that they needed to sip liquids to aid swallowing but only 3 had difficulty swallowing food.

Conclusion: This small study indicates that a number of the older patients attending Cork University Dental School and Hospital for dental care may be “at risk of malnutrition”. These findings suggest that nutritional advice and dental care should both be included in an overall package of care for older patients.

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Walking is the most common form of moderate‐intensity physical activity among adults, is widely accessible and especially appealing to obese people. Most often policy makers are interested in valuing the effect on walking of changes in some characteristics of a neighbourhood, the demand response for walking, of infrastructure changes. A positive demand response to improvements in the walking environment could help meet the public health target of 150 minutes of at least moderate‐intensity physical activity per week. We model walking in an individual’s local neighbourhood as a ‘weak complement’ to the characteristics of the neighbourhood itself. Walking is affected by neighbourhood
characteristics, substitutes, and individual’s characteristics, including their opportunity cost of time.  Using compensating variation, we assess the economic benefits of walking and how walking behaviour is affected by improvements to the neighbourhood.  Using a sample of 1,209 respondents surveyed over a 12 month period (Feb 2010‐Jan 2011) in East Belfast, United Kingdom, we find that a policy that increased walkability and people’s perception of access to shops and facilities  would lead to an increase in walking of about 36 minutes/person/week, valued at £13.65/person/week. When focusing on inactive residents, a policy that improved the walkability of the area would lead to guidelines for physical activity being reached by only 12.8% of the population who are currently inactive. Additional interventions would therefore be needed to encourage inactive residents to
achieve the recommended levels of physical activity, as it appears that interventions that improve the walkability of an area are particularly effective in increasing walking among already active citizens, and, among the inactive ones, the best response is found among healthier, younger and wealthier citizens.

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Objectives: To audit the quality of treatment of lower respiratory tract infections (LRTIs) and urinary tract infections (UTIs) and to identify targets for antibiotic stewardship. Methods: The audit involved collecting data on admitted patients, who were diagnosed with LRTIs or UTIs and subsequently received antibiotic treatment (January 2009-April 2009). Key findings: The percentage adherence rate for hospital antibiotic policy was 68.6% (24/35). Documentation of the CURB-65 score was found in 80% (16/20) of the patients' clinical notes, for which 46.2% (6/13) of patients were treated according to their CURB- 65 score. The percentages of delayed and missed doses for all antibiotics were 21.7% (254/1171) and 8.6% (101/1171), respectively. The percentage of patients switched from intravenous to oral antibiotics in accordance with the policy was 58.5% (31/53). The mean length of stay for patients switched in line with the guidelines was 6.9 days (range: 2-18 days) compared with 13.2 days (range: 4-28 days) for patients treated with intravenous antibiotics >24 h after the intravenous to oral switch criteria were fulfilled; this equates to on average an extra 6.3 days of hospitalisation (p=0.01). Conclusions: The study identified a number of targets for quality improvement including adherence to antibiotic policy, documentation of the CURB-65 score in patients' notes and treating patients accordingly, addressing the issue of missed and delayed doses, and maintaining adherence to the hospital intravenous-to-oral antibiotic switch policy. The findings suggest that the quality of antibiotic prescribing could be improved by measuring and addressing such performance indicators.

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This paper presents multilevel models that utilize the Coxian phase-type distribution in order to be able to include a survival component in the model. The approach is demonstrated by modeling patient length of stay and in-hospital mortality in geriatric wards in Italy. The multilevel model is used to provide a means of controlling for the existence of possible intra-ward correlations, which may make patients within a hospital more alike in terms of experienced outcome than patients coming from different hospitals, everything else being equal. Within this multilevel model we introduce the use of the Coxian phase-type distribution to create a covariate that represents patient length of stay or stage (of hospital care). Results demonstrate that the use of the multilevel model for representing the in-patient mortality is successful and further enhanced by the inclusion of the Coxian phase-type distribution variable (stage covariate).

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The number of elderly patients requiring hospitalisation in Europe is rising. With a greater proportion of elderly people in the population comes a greater demand for health services and, in particular, hospital care. Thus, with a growing number of elderly patients requiring hospitalisation competing with non-elderly patients for a fixed (and in some cases, decreasing) number of hospital beds, this results in much longer waiting times for patients, often with a less satisfactory hospital experience. However, if a better understanding of the recurring nature of elderly patient movements between the community and hospital can be developed, then it may be possible for alternative provisions of care in the community to be put in place and thus prevent readmission to hospital. The research in this paper aims to model the multiple patient transitions between hospital and community by utilising a mixture of conditional Coxian phase-type distributions that incorporates Bayes' theorem. For the purpose of demonstration, the results of a simulation study are presented and the model is applied to hospital readmission data from the Lombardy region of Italy.

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Within a defined law framework, the Italian central health system dictates the standards for hospitalization to local care units, which are in turn allowed to establish their own effectiveness criteria. The appropriateness of the hospitalization decision is therefore predetermined at patients admission, whereas its effectiveness relies on the ex post patient well-being as a result of the complex system of reciprocal relations between patients and healthcare agents at the ward level. We consider the outcomes in geriatric wards referring to the national health system, with respect both to patients traits at the individual level and wards/hospital settings. The risk that models the healthcare outcome is accordingly adjusted for covariates at the different levels of analysis (Goldstein & Spiegelhalter, 1996), thus allowing to differentiate among outcomes in terms of the hospitalization structure and, when appropriate, of territorial aggregation.

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Medicines reconciliation is a way to identify and act on discrepancies in patients’ medical histories and it is found to play a key role in patient safety. This review focuses on discrepancies and medical errors that occurred at point of discharge from hospital. Studies were identified through the following electronic databases: PubMed, Sciences Direct, EMBASE, Google Scholar, Cochrane Reviews and CINAHL. Each of the six databases was screened from inception to end of January 2014. To determine eligibility of the studies; the title, abstract and full manuscript were screened to find 15 articles that meet the inclusion criteria. The median number of discrepancies across the articles was found to be 60%. In average patient had between 1.2–5.3 discrepancies when leaving the hospital. More studies also found a relation between the numbers of drugs a patient was on and the number of discrepancies. The variation in the number of discrepancies found in the 15 studies could be due to the fact that some studies excluded patient taking more than 5 drugs at admission. Medication reconciliation would be a way to avoid the high number of discrepancies that was found in this literature review and thereby increase patient safety.