In-hospital mortality after traumatic brain injury surgery: a nationwide population-based comparison of mortality predictors used in artificial neural network and logistic regression models

Shi, Hon-Yi; Hwang, Shiuh-Lin; Lee, King‐Teh; Lin, Chih-Lung

doi:10.3171/2013.1.jns121130

Cited by 83 publications

(73 citation statements)

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“…4,20,21 Advanced age reportedly has a strong positive association with a high DCCI score. A study by Chen et al also showed that mortality rates tend to be higher in patients with several comorbidities.…”

Section: Discussionmentioning

confidence: 99%

Trends and outcome predictors after traumatic brain injury surgery: a nationwide population-based study in Taiwan

Shi¹,

Hwang

Lee³

et al. 2014

JNS

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Object.The authors sought to analyze trends in hospital resource utilization and mortality rates in a population of patients who had received traumatic brain injury (TBI) surgery.Methods. This nationwide population-based cohort study retrospectively analyzed 18,286 patients who had received surgical treatment for TBI between 1998 and 2010. The multiple linear regression model and Cox proportional hazards model were used for multivariate assessment of outcome predictors.Results. The prevalence rate of surgical treatment for patients with TBI gradually but significantly (p < 0.001) increased by 47.6% from 5.0 per 100,000 persons in 1998 to 7.4 per 100,000 persons in 2010. Age, sex, DeyoCharlson comorbidity index score, hospital volume, and surgeon volume were significantly associated with TBI surgery outcomes (p < 0.05). Over the 12-year period analyzed, the estimated mean hospital treatment cost increased 19.06%, whereas the in-hospital mortality rate decreased 10.9%. The estimated mean time of overall survival after TBI surgery (± SD) was 83.0 ± 4.2 months, and the overall in-hospital and 1-, 3-, and 5-year survival rates were 74.5%, 67.3%, 61.1%, and 57.8%, respectively.Conclusions. These data reveal an increased prevalence of TBI, especially in older patients, and an increased hospital treatment cost but a decreased in-hospital mortality rate. Health care providers and patients should recognize that attributes of the patient and of the hospital may affect hospital resource utilization and the mortality rate. These results are relevant not only to other countries with similar population sizes but also to countries with larger populations. (http://thejns.org/doi/abs/10.3171/2014.8.JNS131526) KeY worDS • traumatic brain injury • trends • predictors • hospital resource utilization • mortality rateAbbreviations used in this paper: BNHI = Bureau of National Health Insurance; DCCI = Deyo-Charlson comorbidity index; ICD-9-CM = International Classification of Diseases, Ninth Revision, Clinical Modification; IQR = interquartile range; LOS = length of stay; TBI = traumatic brain injury.* Drs. K. T. Lee and Lin contributed equally to this study.

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Section: Discussionmentioning

confidence: 99%

Trends and outcome predictors after traumatic brain injury surgery: a nationwide population-based study in Taiwan

Shi¹,

Hwang

Lee³

et al. 2014

JNS

Self Cite

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“…Many researchers have constructed predictive models for outcome prediction after traumatic brain injury. Most of these attempts focused on outcomes with two possibilities such as survival versus death or good outcomes versus poor outcomes 26 42–46 48 49. However, one study focused on ANN prediction of outcomes in five possible categories based on the Glasgow Outcome Scale (death, persistent vegetative state, severe disability, moderate disability and good recovery) after moderate-to-severe head injury 48.…”

Section: Discussionmentioning

confidence: 99%

Artificial neural networks in neurosurgery

Azimi

Mohammadi

Benzel

et al. 2014

Journal of Neurology, Neurosurgery & Psychiatry

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Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review of the relevant published articles that focused on the application of ANNs as a tool for assisting clinical decision-making in neurosurgery. A literature review of all full publications in English biomedical journals (1993-2013) was undertaken. The strategy included a combination of key words 'artificial neural networks', 'prognostic', 'brain', 'tumor tracking', 'head', 'tumor', 'spine', 'classification' and 'back pain' in the title and abstract of the manuscripts using the PubMed search engine. The major findings are summarized, with a focus on the application of ANNs for diagnostic and prognostic purposes. Finally, the future of ANNs in neurosurgery is explored. A total of 1093 citations were identified and screened. In all, 57 citations were found to be relevant. Of these, 50 articles were eligible for inclusion in this review. The synthesis of the data showed several applications of ANN in neurosurgery, including: (1) diagnosis and assessment of disease progression in low back pain, brain tumours and primary epilepsy; (2) enhancing clinically relevant information extraction from radiographic images, intracranial pressure processing, low back pain and real-time tumour tracking; (3) outcome prediction in epilepsy, brain metastases, lumbar spinal stenosis, lumbar disc herniation, childhood hydrocephalus, trauma mortality, and the occurrence of symptomatic cerebral vasospasm in patients with aneurysmal subarachnoid haemorrhage; (4) the use in the biomechanical assessments of spinal disease. ANNs can be effectively employed for diagnosis, prognosis and outcome prediction in neurosurgery.

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“…Ainda sobre a regressão logística, Shi et al (2013) O TOC é implementado com sucesso em organizações, principalmente em empresas e indústrias. Embora escasso, é no setor da saúde que as aplicações têm sido mais desenvolvidas, principalmente para a gestão do fluxo de pacientes.…”

Section: Análise De Conteúdounclassified

Logística Hospitalar: Uma Síntese Do Estado Da Arte

Reis

Oliveira

Castro

2018

RGD

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Os sistemas de saúde visam a prevenção de doenças, promoção, assistência e recuperação da saúde da população. As preocupações gerais de saúde em um país são usualmente relevantes por se tratar de um direito do cidadão e pela necessidade de eficiência e qualidade na prestação do atendimento. Diante das dificuldades enfrentadas com as restrições de verbas e má administração, ocasionado principalmente por crise política econômica de um país, aumento da taxa de envelhecimento e complexidade do setor, torna-se importante diminuir os desperdícios e melhorar os processos nesta área. Este trabalho tem como objetivo realizar uma revisão sistemática da literatura sobre operações em logística hospitalar. Para tanto, pretende-se discutir a metodologia da revisão bibliográfica e analisar os resultados obtidos por meio de quatro bases de dados on-line, Web of Science, Science Direct, Emerald Insight e Scopus. Como resultado, os pesquisadores e gestores que trabalham no segmento da saúde terão uma síntese do estado da arte da logística hospitalar, com abordagens do uso da gestão lean, modelos computacionais, teoria das restrições, contratação de serviços de terceiros, armazenamento de materiais em redes, fluxo de pacientes, utilização de rôbos móveis, armários eletrônicos, RFID e tecnologia da informação, dentre outros.Palavras-chave: Operações. Saúde. Logística.ABSTRACTHealth systems aim at disease prevention, health promotion, care and recovery of the population. General health concerns in a country are usually relevant because it is a citizen's right and the need for efficiency and quality in care delivery. Faced with the difficulties faced by budget constraints and maladministration, caused mainly by a country's economic crisis, increasing the aging rate and complexity of the sector, it is becoming increasingly important to reduce waste and improve processes in this area. This paper aims to conduct a systematic review of the literature on hospital logistics in operations. To do so, we intend to discuss the methodology of the bibliographic review and analyze the results obtained through four online data base, Web of Science, Science Direct, Emerald Insight and Scopus. As a result, researchers and managers working in the health sector will have a art state synthesis of hospital logistics, with lean management approaches, computational models, constraint theory, contracting outsourced services, materials storage in networks, patients flow, use of mobile robotics, electronic cabinets, RFID and information technology, among others.Keywords: Operations. Healthcare. Logistics.

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In-hospital mortality after traumatic brain injury surgery: a nationwide population-based comparison of mortality predictors used in artificial neural network and logistic regression models

Abstract: This work supports the continued use of ANNs for predictive modeling of neurosurgery outcomes. However, further studies are needed to confirm the clinical efficacy of the proposed model.

Cited by 83 publications

References 31 publications

Trends and outcome predictors after traumatic brain injury surgery: a nationwide population-based study in Taiwan

Trends and outcome predictors after traumatic brain injury surgery: a nationwide population-based study in Taiwan

Artificial neural networks in neurosurgery

Logística Hospitalar: Uma Síntese Do Estado Da Arte

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