870 resultados para Hospital furniture


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A large percentage of the industrial SMEs has an organizational structure for product development too far from the adequate practices and models, elaborated by renowned authors with expertise in the theme of product development. On the other hand, the authors state that SMEs obtain considerable advantages by adopting a model of product development process (PDP) management. Healt is one of the most innovative sectors in the world, and countries like Brazil and Colombia are transitioning from a system that cares for contagious infecttions diseases where the drug product is the main form of treatment - to a system that cares for chronic degenerative conditions - where the equipment, including hospital furniture, has more relevance to the treatment. This change is offering better opportunities of specialized markets to hospital furniture SMEs that adopt an adquate PDF model. The present study proposes a first outline of a model of PDP management for industrial metal-mechanical SMEs that develop and manufacture hospital furniture, from a review of models proposed for great mechanical area.

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Nas Pequenas e Médias Empresas (PMEs) industriais em que o seu produto é essencialmente metal mecânico e o desenvolvimento de produtos é estratégico, surgem questões sobre quais são as metodologias mais adequadas para as diferentes fases de projeto de produto e como implantá-las em um modelo de Processo de Desenvolvimento de Produto (PDP) adequado às necessidades dessas empresas, de modo a aumentar a probabilidade de sucesso do produto. O presente trabalho propõe um modelo de referência do PDP aplicado a PMEs industriais do setor metal mecânico que desenvolvem móveis hospitalares. O modelo é baseado em propostas de PDP da grande área mecânica, especificidades do produto, a saber, móveis hospitalares e dispositivos médicos e em fatores da realidade das PMEs. O trabalho divide-se nas seguintes fases principais: revisão bibliográfica sobre propostas de modelos de gestão do PDP da grande área mecânica e do setor específico de móveis e dispositivos médicos, revisão de normas e regulamentações que tenham influência no PDP, realização de estudos de casos múltiplos de PMEs industriais metal mecânicas que desenvolvem móveis hospitalares, no Brasil e na Colômbia e, por último, síntese de uma proposta final do modelo de referência de PDP, específico para as PMEs industriais do setor metal mecânico que desenvolvem móveis hospitalares, aplicado à realidade do Brasil e da Colômbia.

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In hospitals, one of the ways to control microbial contamination is by disinfecting the furniture used by patients. This study's main objective was to evaluate the microbiological condition of hospital mattresses before and after such disinfection, in order to identify bacteria that are epidemiologically important in nosocomial infection, such as Staphylococcus aureus and Pseudomonas aeruginosa. RODAC plates with two different culture media were used to collect specimens. Patient beds were selected according to previously established criteria, and surface areas on the mattresses were chosen at random. From the total of 1 040 plate cultures from 52 mattresses, positive results were obtained from 500 of them (48.1%), 263 before disinfection and 237 after disinfection. Considering the selectivity of the culture media, the positivity rate was high. There were high prevalences of S. aureus both before and after mattress disinfection. The study results suggest that the usual disinfection procedures, instead of diminishing the number of microbes, merely displace them from one part of the mattress to another, and the number of microorganisms remains the same.

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Second Edition. Pp.5-61 General Surgical Necessities, Gauze, Antiseptic Sundries, Surgical Sundries, Rubber Bandages, Catheters, Bougies, Splints, Tents, Emergency Bags, Surgeon's Needles, Operating Instruments, Amputating, Forceps, Aspiration, Cases, Catheters and Directors, Pocket Case Instruments, Dissecting and Post-Mortem Pp.62-118 General Operating - Osteotomy, Mastoid, Trephining, Eye Instruments, Aural, Nasal, Mouth and Throat, Tooth Forceps, Laryngoscopic Sets, Hydraulic Air Compressor, Variocele, Genito Urinary Pp. 119-167 Genito Urinary-Lithotrity, Alimentary, Anal and Rectal, Gynaecological, Pessaries, Microscopes, Syringes Pp.168-205 Chemical Apparatus and Glassware, Physician's Cabinets, Office Furniture, Operating Chairs and Tables, Hospital Beds, Cautery, Electrolytic, Batteries Pp.206-246 Cases, Varicose, Braces, Abdominal Supporters, Trusses, Invalid Chairs and Supplies, Sterilizers, Saddle-Bags, Deformity Apparatus Advertisements: Bandages, Abdominal Supporters, Rubber Supplies, Bags, Batteries, Cotton, Microscopes, Hypodermic Tablets, Atomizers, Furniture, Sterilizers, Syringes

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Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

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Objective: To compare the effectiveness of the STRATIFY falls tool with nurses’ clinical judgments in predicting patient falls. Study Design and Setting: A prospective cohort study was conducted among the inpatients of an acute tertiary hospital. Participants were patients over 65 years of age admitted to any hospital unit. Sensitivity, specificity, and positive predictive value (PPV) and negative predictive values (NPV) of the instrument and nurses’ clinical judgments in predicting falls were calculated. Results: Seven hundred and eighty-eight patients were screened and followed up during the study period. The fall prevalence was 9.2%. Of the 335 patients classified as being ‘‘at risk’’ for falling using the STRATIFY tool, 59 (17.6%) did sustain a fall (sensitivity50.82, specificity50.61, PPV50.18, NPV50.97). Nurses judged that 501 patients were at risk of falling and, of these, 60 (12.0%) fell (sensitivity50.84, specificity50.38, PPV50.12, NPV50.96). The STRATIFY tool correctly identified significantly more patients as either fallers or nonfallers than the nurses (P50.027). Conclusion: Considering the poor specificity and high rates of false-positive results for both the STRATIFY tool and nurses’ clinical judgments, we conclude that neither of these approaches are useful for screening of falls in acute hospital settings.

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Objective-To establish the demographic, health status and insurance determinants of pre-hospital ambulance non-usage for patients with emergency medical needs. Methods-Triage category, date of birth, sex, marital status, country of origin, method and time of arrival, ambulance insurance status, diagnosis, and disposal were collected for all patients who presented over a four month period (n=10 229) to the emergency department of a major provincial hospital. Data for patients with urgent (n=678) or critical care needs (n=332) who did not use pre-hospital care were analysed using Poisson regression. Results-Only a small percentage (6.6%) of the total sample were triaged as having urgent medical needs or critical care needs (3.2%). Predictors of usage for those with urgent care needs included age greater than 65 years (prevalence ratio (PR)=0.54; 95% confidence interval (CI)= 0.35 to 0.83), being admitted to intensive care or transferred to another hospital (PR=0.62; 95% CI=0.44 to 0.89) or ward (PR=0.72; 95% CI=0.56 to 0.93) and ambulance insurance status (PR=0.67; 95% CI=052 to 0.86). Sex, marital status, time of day and country of origin were not predictive of usage and non-usage. Predictors of usage for those with critical care needs included age 65 years or greater (PR=0.45; 95% CI=0.25 to 0.81) and a diagnosis of trauma (PR=0.49; 95% CI=0.26 to 0.92). A non-English speaking background was predictive of non-usage (PR=1.98; 95% CI=1.06 to 3.70). Sex, marital status, time of day, triage and ambulance insurance status were not predictive of non-usage. Conclusions-Socioeconomic and medical factors variously influence ambulance usage depending on the severity or urgency of the medical condition. Ambulance insurance status was less of an influence as severity of condition increased suggesting that, at a critical level of urgency, patients without insurance are willing to pay for a pre-hospital ambulance service.

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Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.

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This study aimed to identify: i) the prevalence of malnutrition according to the scored Patient Generated-Subjective Global Assessment (PG-SGA); ii) utilization of available nutrition resources; iii) patient nutrition information needs; and iv) external sources of nutrition information. An observational, cross-sectional study was undertaken at an Australian public hospital on 191 patients receiving oncology services. According to PG-SGA, 49% of patients were malnourished and 46% required improved symptom management and/or nutrition intervention. Commonly reported nutrition-impact symptoms included: peculiar tastes (31%), no appetite (24%) and nausea (24%). External sources of nutrition information were accessed by 37%, with popular choices being media/internet (n=19) and family/friends (n=13). In a sub-sample (n=65), 32 patients were aware of the available nutrition resources, 23 thought the information sufficient and 19 patients had actually read them. Additional information on supplements and modifying side effects was requested by 26 patients. Malnutrition is common in oncology patients receiving treatment at an Australian public hospital and almost half require improved symptom management and/or nutrition intervention. Patients who read the available nutrition information found it useful, however awareness of these nutrition resources and the provision of information on supplementation and managing symptoms requires attention.