970 resultados para Hospital information


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Os modelos de maturidade são instrumentos facilitadores da gestão das organizações, incluindo a gestão da sua função sistemas de informação, não sendo exceção as organizações hospitalares. Neste artigo apresenta-se uma investigação inicial que visa o desenvolvimento de um abrangente modelo de maturidade para a gestão dos sistemas de informação hospitalares. O desenvolvimento deste modelo justifica-se porque os modelos de maturidade atuais no domínio da gestão dos sistemas informação hospitalares ainda se encontram numa fase embrionária de desenvolvimento, sobretudo porque são pouco detalhados, não disponibilizam ferramentas para determinação da maturidade e não apresentam as características dos estágios de maturidade estruturadas por diferentes fatores de influência.

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Issued in numerous parts identified by no. and geographic area (e.g.: v. 46, Texas. Part 1) and including as its final no. a technical suppl. not additionally identified.

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OBJETIVO: Conhecer a qualidade dos dados de internação por causas externas em São José dos Campos, São Paulo. MÉTODO: Foram estudadas as internações pelo Sistema Único de Saúde por lesões decorrentes de causas externas no primeiro semestre de 2003, no Hospital Municipal, referência para o atendimento ao trauma no Município, por meio da comparação dos dados registrados no Sistema de Informações Hospitalares com os prontuários de 990 internações. A concordância das variáveis relativas à vítima, à internação e ao agravo foi avaliada pela taxa bruta de concordância e pelo coeficiente Kappa. As lesões e as causas externas foram codificadas segundo a 10ª revisão da Classificação Internacional de Doenças, respectivamente, capítulos XIX e XX. RESULTADOS: A taxa de concordância bruta foi de boa qualidade para as variáveis relativas à vítima e à internação, variando de 89,0% a 99,2%. As lesões tiveram concordância ótima, exceto os traumatismos do pescoço (k=0,73), traumatismos múltiplos (k=0,67) e fraturas do tórax (k=0,49). As causas externas tiveram concordância ótima para acidentes de transporte (k=0,90) e quedas (k=0,83). A confiabilidade foi menor para agressões (k=0,50), causas indeterminadas (k=0,37), e complicações da assistência médica (k=0,03). Houve concordância ótima nos acidentes de transporte em pedestres, ciclistas e motociclistas. CONCLUSÃO: A maioria das variáveis de estudo teve boa qualidade no nível de agregação analisado. Algumas variáveis relativas à vítima e alguns tipos de causas externas necessitam de aperfeiçoamento da qualidade dos dados. O perfil da morbidade hospitalar encontrado confirmou os acidentes de transporte como importante causa externa de internação hospitalar no Município.

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OBJECTIVE Develop an index to evaluate the maternal and neonatal hospital care of the Brazilian Unified Health System.METHODS This descriptive cross-sectional study of national scope was based on the structure-process-outcome framework proposed by Donabedian and on comprehensive health care. Data from the Hospital Information System and the National Registry of Health Establishments were used. The maternal and neonatal network of Brazilian Unified Health System consisted of 3,400 hospitals that performed at least 12 deliveries in 2009 or whose number of deliveries represented 10.0% or more of the total admissions in 2009. Relevance and reliability were defined as criteria for the selection of variables. Simple and composite indicators and the index of completeness were constructed and evaluated, and the distribution of maternal and neonatal hospital care was assessed in different regions of the country.RESULTS A total of 40 variables were selected, from which 27 single indicators, five composite indicators, and the index of completeness of care were built. Composite indicators were constructed by grouping simple indicators and included the following variables: hospital size, level of complexity, delivery care practice, recommended hospital practice, and epidemiological practice. The index of completeness of care grouped the five variables and classified them in ascending order, thereby yielding five levels of completeness of maternal and neonatal hospital care: very low, low, intermediate, high, and very high. The hospital network was predominantly of small size and low complexity, with inadequate child delivery care and poor development of recommended and epidemiological practices. The index showed that more than 80.0% hospitals had a low index of completeness of care and that most qualified heath care services were concentrated in the more developed regions of the country.CONCLUSIONS The index of completeness proved to be of great value for monitoring the maternal and neonatal hospital care of Brazilian Unified Health System and indicated that the quality of health care was unsatisfactory. However, its application does not replace specific evaluations.

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ABSTRACT OBJECTIVE To identify individual and hospital characteristics associated with the risk of readmission in older inpatients for proximal femoral fracture in the period of 90 days after discharge. METHODS Deaths and readmissions were obtained by a linkage of databases of the Hospital Information System of the Unified Health System and the System of Information on Mortality of the city of Rio de Janeiro from 2008 to 2011. The population of 3,405 individuals aged 60 or older, with non-elective hospitalization for proximal femoral fracture was followed for 90 days after discharge. Cox multilevel model was used for discharge time until readmission, and the characteristics of the patients were used on the first level and the characteristics of the hospitals on the second level. RESULTS The risk of readmission was higher for men (hazard ratio [HR] = 1.37; 95%CI 1.08–1.73), individuals more than 79 years old (HR = 1.45; 95%CI 1.06–1.98), patients who were hospitalized for more than two weeks (HR = 1.33; 95%CI 1.06-1.67), and for those who underwent arthroplasty when compared with the ones who underwent osteosynthesis (HR = 0.57; 95%CI 0.41–0.79). Besides, patients admitted to state hospitals had lower risk for readmission when compared with inpatients in municipal (HR = 1.71; 95%CI 1.09–2.68) and federal hospitals (HR = 1.81; 95%CI 1.00–3.27). The random effect of the hospitals in the adjusted model remained statistically significant (p < 0.05). CONCLUSIONS Hospitals have complex structures that reflect in the quality of care. Thus, we propose that future studies may include these complexities and the severity of the patients in the analysis of the data, also considering the correlation between readmission and mortality to reduce biases.

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The clinical content of administrative databases includes, among others, patient demographic characteristics, and codes for diagnoses and procedures. The data in these databases is standardized, clearly defined, readily available, less expensive than collected by other means, and normally covers hospitalizations in entire geographic areas. Although with some limitations, this data is often used to evaluate the quality of healthcare. Under these circumstances, the quality of the data, for instance, errors, or it completeness, is of central importance and should never be ignored. Both the minimization of data quality problems and a deep knowledge about this data (e.g., how to select a patient group) are important for users in order to trust and to correctly interpret results. In this paper we present, discuss and give some recommendations for some problems found in these administrative databases. We also present a simple tool that can be used to screen the quality of data through the use of domain specific data quality indicators. These indicators can significantly contribute to better data, to give steps towards a continuous increase of data quality and, certainly, to better informed decision-making.

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Information technologies changed the way of how the health organizations work, contributing to their effectiveness, efficiency and sustainability. Hospital Information Systems (HIS) are emerging on all of health institutions, helping health professionals and patients. However, HIS are not always implemented and used in the best way, leading to low levels of benefits and acceptance by users of these systems. In order to mitigate this problem, it is essential to take measures able to ensure if the HIS and their interfaces are designed in a simple and interactive way. With this in mind, a study to measure the user satisfaction and their opinion was made. It was applied the Technology Acceptance Model (TAM) on a HIS implemented on various hospital centers (AIDA), being used the Pathologic Anatomy Service. The study identified weakness and strengths features of AIDA and it pointed some solutions to improve the medical record.

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OBJECTIVE: To study the factors associated with the risk of in-hospital death in acute myocardial infarction in the Brazilian public health system in Rio de Janeiro, Brazil. METHODS: Sectional study of a sample with 391 randomly drawn medical records of the hospitalizations due to acute myocardial infarction recorded in the hospital information system in 1997. RESULTS: The diagnosis was confirmed in 91.7% of the cases; 61.5% males; age = 60.2 ± 2.4 years; delta time until hospitalization of 11 hours; 25.3% were diabetic; 58.1% were hypertensive; 82.6% were in Killip I class. In-hospital mortality was 20.6%. Thrombolysis was used in 19.5%; acetylsalicylic acid (ASA) 86.5%; beta-blockers 49%; angiotensin-converting enzyme (ACE) inhibitors 63.3%; calcium channel blockers 30.5%. Factors associated with increased death: age (61-80 years: OR=2.5; > 80 years: OR=9.6); Killip class (II: OR=1.9; III: OR=6; IV: OR=26.5); diabetes (OR=2.4); ventricular tachycardia (OR=8.5); ventricular fibrillation (OR=34); recurrent ischemia (OR=2.7). The use of ASA (OR=0.3), beta-blockers (OR=0.3), and ACE inhibitors (OR=0.4) was associated with a reduction in the chance of death. CONCLUSION: General lethality was high and some interventions of confirmed efficacy were underutilizated. The logistic model showed the beneficial effect of beta-blockers, and ACE inhibitors on the risk of in-hospital death.

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[Table des matières] 1. Introduction. 2. Structure (introduction, hiérarchie). 3. Processus (généralités, flux de clientèle, flux d'activité, flux de ressources, aspects temporels, aspects comptables). 4. Descripteurs (qualification, quantification). 5. Indicateurs (définitions, productivité, pertinence, adéquation, efficacité, effectivité, efficience, standards). 6. Bibliographie.

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OBJECTIVE to describe hospital admissions for ambulatory care sensitive conditions in children under five years of age in the State of Paraná, Brazil by condition type, age group and health region. METHOD a temporal ecological study was conducted using data from the Unified Health System Hospital Information System for the period 2000 to 2011. Conditions were grouped in accordance with the list of ambulatory care sensitive conditions in Brazil. RESULTS there was an increase in the rate of admissions for ambulatory care sensitive conditions in all age groups in 50% of the health regions, with a marked increase in children under the age of one. Pneumonia, gastroenteritis and asthma were the main causes of admissions. There was an increase in the proportion of overall admissions accounted for by pneumonia and gastroenteritis. CONCLUSION the increase in admissions reveals the need for actions to improve access to primary healthcare and provide effective treatment of the main ambulatory care sensitive conditions in order to prevent hospital admissions among children.

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The objectives of this study were to develop a computerized method to screen for potentially avoidable hospital readmissions using routinely collected data and a prediction model to adjust rates for case mix. We studied hospital information system data of a random sample of 3,474 inpatients discharged alive in 1997 from a university hospital and medical records of those (1,115) readmitted within 1 year. The gold standard was set on the basis of the hospital data and medical records: all readmissions were classified as foreseen readmissions, unforeseen readmissions for a new affection, or unforeseen readmissions for a previously known affection. The latter category was submitted to a systematic medical record review to identify the main cause of readmission. Potentially avoidable readmissions were defined as a subgroup of unforeseen readmissions for a previously known affection occurring within an appropriate interval, set to maximize the chance of detecting avoidable readmissions. The computerized screening algorithm was strictly based on routine statistics: diagnosis and procedures coding and admission mode. The prediction was based on a Poisson regression model. There were 454 (13.1%) unforeseen readmissions for a previously known affection within 1 year. Fifty-nine readmissions (1.7%) were judged avoidable, most of them occurring within 1 month, which was the interval used to define potentially avoidable readmissions (n = 174, 5.0%). The intra-sample sensitivity and specificity of the screening algorithm both reached approximately 96%. Higher risk for potentially avoidable readmission was associated with previous hospitalizations, high comorbidity index, and long length of stay; lower risk was associated with surgery and delivery. The model offers satisfactory predictive performance and a good medical plausibility. The proposed measure could be used as an indicator of inpatient care outcome. However, the instrument should be validated using other sets of data from various hospitals.

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Objective: To investigate the lag structure effects from exposure to atmospheric pollution in acute outbursts in hospital admissions of paediatric rheumatic diseases (PRDs). Methods: Morbidity data were obtained from the Brazilian Hospital Information System in seven consecutive years, including admissions due to seven PRDs (juvenile idiopathic arthritis, systemic lupus erythematosus, dermatomyositis, Henoch-Schonlein purpura, polyarteritis nodosa, systemic sclerosis and ankylosing spondylitis). Cases with secondary diagnosis of respiratory diseases were excluded. Daily concentrations of inhaled particulate matter (PM10), sulphur dioxide (SO2) nitrogen dioxide (NO2), ozone (O-3) and carbon monoxide (CO) were evaluated. Generalized linear Poisson regression models controlling for short-term trend, seasonality, holidays, temperature and humidity were used. Lag structures and magnitude of air pollutants' effects were adopted to estimate restricted polynomial distributed lag models. Results: The total number of admissions due to acute outbursts PRD was 1,821. The SO2 interquartile range (7.79 mu g/m(3)) was associated with an increase of 1.98% (confidence interval 0.25-3.69) in the number of hospital admissions due to outcome studied after 14 days of exposure. This effect was maintained until day 17. Of note, the other pollutants, with the exception of O-3, showed an increase in the number of hospital admissions from the second week. Conclusion: This study is the first to demonstrate a delayed association between SO2 and PRD outburst, suggesting that oxidative stress reaction could trigger the inflammation of these diseases. Lupus (2012) 21, 526-533.