912 resultados para Health public policies. Home care services. Hospital and home care


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This issue of the FAL Bulletin analyses institutional alternatives and international best practices for the development of transportation services that explicitly include and integrate users with some type of disability.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This study identifies the key challenges facing the region in the domain of care provision. To that end it describes, analyses and discusses the concept of care, the rights approach and the public policies implemented in Latin America and the Caribbean on the social organization of care. The document describes care policies in the region generally, and it specifically analyses experiences of the social organization of care provision in four countries. In Chile, it studies the Chile Crece Contigo national child-care programme; in Costa Rica it reviews the National Care Network; in Ecuador, it analyses the recognition of unpaid reproductive work in the 2008 Constitution and the National Plan for Good Living; and in Uruguay it considers the National Care System.

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Do you know what choices you would make if faced with an ethical dilemma? This fact-based case includes situations and issues that a real citizen considered when faced with the knowledge that his employer may have been overbilling the state of North Carolina for health care. Professionals, especially those in accounting and finance positions, are likely to face serious dilemmas in the course of their careers. These situations may require them to choose between honoring a confidentiality clause in an employment contract and acting according to ethical and professional values. This case provides facts gathered from an actual case in which an individual faced this particular challenge. By working through the case, students should develop an appreciation of the pressures and personal ethical challenges they are likely to face in the workplace. By engaging in discussion and role play, students will be more likely to recognize these issues when they occur, and will have already developed critical thinking skills to help them develop a plan of action.

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BACKGROUND Recently, two simple clinical scores were published to predict survival in trauma patients. Both scores may successfully guide major trauma triage, but neither has been independently validated in a hospital setting. METHODS This is a cohort study with 30-day mortality as the primary outcome to validate two new trauma scores-Mechanism, Glasgow Coma Scale (GCS), Age, and Pressure (MGAP) score and GCS, Age and Pressure (GAP) score-using data from the UK Trauma Audit and Research Network. First, an assessment of discrimination, using the area under the receiver operating characteristic (ROC) curve, and calibration, comparing mortality rates with those originally published, were performed. Second, we calculated sensitivity, specificity, predictive values, and likelihood ratios for prognostic score performance. Third, we propose new cutoffs for the risk categories. RESULTS A total of 79,807 adult (≥16 years) major trauma patients (2000-2010) were included; 5,474 (6.9%) died. Mean (SD) age was 51.5 (22.4) years, median GCS score was 15 (interquartile range, 15-15), and median Injury Severity Score (ISS) was 9 (interquartile range, 9-16). More than 50% of the patients had a low-risk GAP or MGAP score (1% mortality). With regard to discrimination, areas under the ROC curve were 87.2% for GAP score (95% confidence interval, 86.7-87.7) and 86.8% for MGAP score (95% confidence interval, 86.2-87.3). With regard to calibration, 2,390 (3.3%), 1,900 (28.5%), and 1,184 (72.2%) patients died in the low, medium, and high GAP risk categories, respectively. In the low- and medium-risk groups, these were almost double the previously published rates. For MGAP, 1,861 (2.8%), 1,455 (15.2%), and 2,158 (58.6%) patients died in the low-, medium-, and high-risk categories, consonant with results originally published. Reclassifying score point cutoffs improved likelihood ratios, sensitivity and specificity, as well as areas under the ROC curve. CONCLUSION We found both scores to be valid triage tools to stratify emergency department patients, according to their risk of death. MGAP calibrated better, but GAP slightly improved discrimination. The newly proposed cutoffs better differentiate risk classification and may therefore facilitate hospital resource allocation. LEVEL OF EVIDENCE Prognostic study, level II.

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BACKGROUND Caring for patients with multimorbidity is common for generalists, although such patients are often excluded from clinical trials, and thus such trials lack of generalizability. Data on the association between multimorbidity and preventive care are limited. We aimed to assess whether comorbidity number, severity and type were associated with preventive care among patients receiving care in Swiss University primary care settings. METHODS We examined a retrospective cohort composed of a random sample of 1,002 patients aged 50-80 years attending four Swiss university primary care settings. Multimorbidity was defined according to the literature and the Charlson index. We assessed the quality of preventive care and cardiovascular preventive care with RAND's Quality Assessment Tool indicators. Aggregate scores of quality of provided care were calculated by taking into account the number of eligible patients for each indicator. RESULTS Participants (mean age 63.5 years, 44% women) had a mean of 2.6 (SD 1.9) comorbidities and 67.5% had 2 or more comorbidities. The mean Charlson index was 1.8 (SD 1.9). Overall, participants received 69% of recommended preventive care and 84% of cardiovascular preventive care. Quality of care was not associated with higher numbers of comorbidities, both for preventive care and for cardiovascular preventive care. Results were similar in analyses using the Charlson index and after adjusting for age, gender, occupation, center and number of visits. Some patients may receive less preventive care including those with dementia (47%) and those with schizophrenia (35%). CONCLUSIONS In Swiss university primary care settings, two thirds of patients had 2 or more comorbidities. The receipt of preventive and cardiovascular preventive care was not affected by comorbidity count or severity, although patients with certain comorbidities may receive lower levels of preventive care.

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This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^

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"January 1983."

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Item 507-B-5

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Mode of access: Internet.

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Shipping list no.: 2011-0418-P (pt. 1), 2011-0423-P (pt. 2A), 2011-0426-P (pt. 2B), 2011-0439-P (pt. 3), 2011-0432-P (pt. 4), 2012-0085-P (pt. 5), 2012-0221-P (pt. 6), 2012-0256-P (pt. 7).

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Shipping list no. 2012-0243-P (pt. 1, 4), 2012-0266-P (pt. 2A), 2012-0267-P (pt. 2B), 2012-0250-P (pt. 3), 2013-0038 (pt. 5), 2013-0040-P (pt. 6), 2012-0298-P (pt. 7).