874 resultados para Primary care (Medicine)


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The primary health care has been recognized as one of the key components of an effective health system. In its most developed form, the primary health care is the first contact with the health system and the site responsible for the organization of health care over time: individuals, their families and the general population; seeks to provide balance between the two goals of a national health system, which are improving the health of the population and provide equitable distribution of resources. Hospitalizations for primary care sensitive conditions (HPCSC) may be associated with deficiencies of service coverage primary health care or its effectiveness. Hospitalization rates can and should represent a warning sign, triggering mechanisms for analysis and search for explanations for these problems. The use of hospitalization data for HPCSC can serve as indicators of inequality in the health system, contributing to the evaluation of the deployment and implementation of health policies.

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Family Health Support Centers (NASF) were created in Brazil to increase the case-resolution capacity of primary healthcare. Prior to their implementation in the West Side of the city of Sao Paulo, Brazil, a series of workshops were held for primary healthcare professionals to prepare a proposal for such centers. Hermeneutic analysis was used to study the transcribed material. The thematic categories were: role, constitution, and functioning of the NASF, relationship with family health teams, and interdisciplinarity. The participants' expected the NASF to be an empowering device for comprehensiveness of care, intervening in an existing culture of unnecessary referrals while fostering linkage with other levels of care. The participants also expected the NASF to contribute to the discussion on health professionals' training and stimulating reflection with policy-makers on health indicators based exclusively on the number of consultations. These indicators fail to reflect the impact on the services' activities and the quality of care offered to the population in the coverage area.

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Objective: to characterize the profiles of families in the area covered by a Primary Health Center and to identify those in a vulnerable situation. Method: this is an epidemiological, observational, cross-sectional and quantitative study. 320 home visits were made, defined by a random sample of the areas covered by the Urban Center 1 in the city of Sao Sebastiao, in Brazil's Federal District. A structured questionnaire was used for data collection, elaborated based on the Family Development Index (FDI). Results: there was a predominance of young families, women, and low levels of schooling. The FDI permitted the identification of families in situations of "high" and "very high" vulnerability. The most critical dimensions were: "access to knowledge" and "access to work". Conclusion: the study indicated the importance of greater investments in the areas of education, work and income, and highlighted the need for the use of a wider concept of vulnerability by the health services.

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Background: Few cross-sectional studies involving adults and elderly patients with major DDIs have been conducted in the primary care setting. The study aimed to investigate the prevalence of potential drug-drug interactions (DDIs) in patients treated in primary care. Methodology/Principal Findings: A cross-sectional study involving patients aged 45 years or older was conducted at 25 Basic Health Units in the city of Maringa (southern Brazil) from May to December 2010. The data were collected from prescriptions at the pharmacy of the health unit at the time of the delivery of medication to the patient. After delivery, the researcher checked the electronic medical records of the patient. A total of 827 patients were investigated (mean age: 64.1; mean number of medications: 4.4). DDIs were identified in the Micromedex (R) database. The prevalence of potential DDIs and major DDIs was 63.0% and 12.1%, respectively. In both the univariate and multivariate analyses, the number of drugs prescribed was significantly associated with potential DDIs, with an increasing risk from three to five drugs (OR = 4.74; 95% CI: 2.90-7.73) to six or more drugs (OR = 23.03; 95% CI: 10.42-50.91). Forty drugs accounted for 122 pairs of major DDIs, the most frequent of which involved simvastatin (23.8%), captopril/enalapril (16.4%) and fluoxetine (16.4%). Conclusions/Significance: This is the first large-scale study on primary care carried out in Latin America. Based on the findings, the estimated prevalence of potential DDIs was high, whereas clinically significant DDIs occurred in a smaller proportion. Exposing patients to a greater number of prescription drugs, especially three or more, proved to be a significant predictor of DDIs. Prescribers should be more aware of potential DDIs. Future studies should assess potential DDIs in primary care over a longer period of time.

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The Primary Care Information System (SIAB) concentrates basic healthcare information from all different regions of Brazil. The information is collected by primary care teams on a paper-based procedure that degrades the quality of information provided to the healthcare authorities and slows down the process of decision making. To overcome these problems we propose a new data gathering application that uses a mobile device connected to a 3G network and a GPS to be used by the primary care teams for collecting the families' data. A prototype was developed in which a digital version of one SIAB form is made available at the mobile device. The prototype was tested in a basic healthcare unit located in a suburb of Sao Paulo. The results obtained so far have shown that the proposed process is a better alternative for data collecting at primary care, both in terms of data quality and lower deployment time to health care authorities.

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This study examines predictors of sickness absence in patients presenting to a health practitioner with acute/ subacute low back pain (LBP). Aims of this study were to identify baseline-variables that detect patients with a new LBP episode at risk of sickness absence and to identify prognostic models for sickness absence at different time points after initial presentation. Prospective cohort study investigating 310 patients presenting to a health practitioner with a new episode of LBP at baseline, three-, six-, twelve-week and six-month follow-up, addressing work-related, psychological and biomedical factors. Multivariate logistic regression analysis was performed to identify baseline-predictors of sickness absence at different time points. Prognostic models comprised 'job control', 'depression' and 'functional limitation' as predictive baseline-factors of sickness absence at three and six-week follow-up with 'job control' being the best single predictor (OR 0.47; 95%CI 0.26-0.87). The six-week model explained 47% of variance of sickness absence at six-week follow-up (p<0.001). The prediction of sickness absence beyond six-weeks is limited, and health practitioners should re-assess patients at six weeks, especially if they have previously been identified as at risk of sickness absence. This would allow timely intervention with measures designed to reduce the likelihood of prolonged sickness absence.

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To reduce the socio-economic burden of persistent low back pain (LBP), factors influencing the progression of acute/subacute LBP to the persistent state must be identified at an early stage.

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BACKGROUND: Physiological data obtained with the pulmonary artery catheter (PAC) are susceptible to errors in measurement and interpretation. Little attention has been paid to the relevance of errors in hemodynamic measurements performed in the intensive care unit (ICU). The aim of this study was to assess the errors related to the technical aspects (zeroing and reference level) and actual measurement (curve interpretation) of the pulmonary artery occlusion pressure (PAOP). METHODS: Forty-seven participants in a special ICU training program and 22 ICU nurses were tested without pre-announcement. All participants had previously been exposed to the clinical use of the method. The first task was to set up a pressure measurement system for PAC (zeroing and reference level) and the second to measure the PAOP. RESULTS: The median difference from the reference mid-axillary zero level was - 3 cm (-8 to + 9 cm) for physicians and -1 cm (-5 to + 1 cm) for nurses. The median difference from the reference PAOP was 0 mmHg (-3 to 5 mmHg) for physicians and 1 mmHg (-1 to 15 mmHg) for nurses. When PAOP values were adjusted for the differences from the reference transducer level, the median differences from the reference PAOP values were 2 mmHg (-6 to 9 mmHg) for physicians and 2 mmHg (-6 to 16 mmHg) for nurses. CONCLUSIONS: Measurement of the PAOP is susceptible to substantial error as a result of practical mistakes. Comparison of results between ICUs or practitioners is therefore not possible.

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