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RESUMEN Introducción: el enfrentamiento a la COVID-19 impone importantes retos a los profesionales de la salud relacionados con los cuidados de la salud de la población y con la prevención y control de infecciones en la comunidad y en las instituciones de salud. Uno de los mayores retos a los que se enfrentan los hospitales es gestionar los riesgos sin que ello suponga un deterioro de la calidad percibida por el paciente y personal sanitario. Objetivo: diseñar un modelo para la gestión de riesgos epidemiológicos relacionado con la COVID-19 en consejos y unidades de salud. Métodos: se utilizó la Lógica Difusa Compensatoria como método pertinente de la modelación matemática en procesos complejos. Resultados: se tiene un modelo de decisión para la valoración de la gestión de riesgos relacionado con la COVID-19, integrado al sistema de control interno hospitalario. Conclusiones: se demostró la pertinencia de la gestión de riesgos como alternativa para exterminar la pandemia causada por el nuevo Coronavirus SARS CoV-2. Se confirma la pertinencia de la lógica difusa compensatoria para la toma de decisiones en proceso complejos. Se integró la gestión de riesgos de la COVID-19 al sistema de control interno hospitalario, permitiendo tomar estrategias para la mejora de las entidades de la salud.
ABSTRACT Introduction: the confrontation with COVID-19 imposes important challenges on health professionals related to the health care of the population and to the prevention and control of infections in the community and in health institutions. One of the biggest challenges that hospitals face is managing their risk more efficiently without this deteriorating the quality perceived by the patient and healthcare personnel. Objective: assessing the management of epidemiological risk related to COVID-19 in healt councils and units. Methods: compensatory fuzzy logic was used as a pertinent method of mathematical modeling in complex processes Results: there is a decision model for the assessment of risk management related to COVID-19, integrated into the hospital internal control system Conclusions: the relevance of risk management as an alternative to exterminate the pandemic caused by the new coronavirus SARS CoV-2was demonstrated. The pertinence of diffuse compensatory logic for decision making in complex processes is confirmed. The risk management of de covid was integrated into the hospital internal control system, allowing the desing of strategies for the improvement of health entities.
RESUMO Introdução: o enfrentamento da COVID-19 impõe desafios importantes para os profissionais de saúde relacionados à atenção à saúde da população e à prevenção e controle de infecções na comunidade e nas instituições de saúde. Um dos maiores desafios que os hospitais enfrentam é gerenciar os riscos sem causar uma deterioração na qualidade percebida pelo paciente e profissionais de saúde. Objetivo: traçarum modelo de gestão dos riscos epidemiológicos relacionados ao COVID-19 em conselhos e unidades de saúde. Métodos: A Lógica Fuzzy Compensatória foi utilizada como um método pertinente de modelagem matemática em processos complexos. Resultados: existe um modelo de decisão para avaliação do gerenciamento de riscos relacionado ao COVID-19, integrado ao sistema de controle interno do hospital. Conclusões: ficou demonstrada a relevância do gerenciamento de risco como alternativa para exterminar a pandemia causada pelo novo Coronavírus SARS CoV-2. A relevância da lógica fuzzy compensatória para a tomada de decisão em processos complexos é confirmada. A gestão de riscos do COVID-19 foi integrada ao sistema de controle interno do hospital, permitindo a adoção de estratégias de melhoria das entidades de saúde.
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In view of the inherent drawbacks of traditional medical equipment procurement mode, a decision-making model of medical equipment procurement based on Improved Markov model is proposed and the engineering evaluation practice is carried out. The data pool of medical equipment procurement of big data level is constructed, the core constraint factors of medical equipment procurement are perceived by deep learning, the decision model of medical equipment procurement under multi-dimensional constraints is constructed, and the Improved Markov model is introduced, and the observable decision-making scheme of medical equipment procurement is given. The results show that the model can give the decision-making scheme of medical equipment procurement with global optimal attribute under multi-dimensional constraints. It has obvious advantages in the balance of long-term demand and immediate demand, the optimization of procurement decision-making scheme, and the accuracy of patient demand prediction in a long period.
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Objective:To evaluate the association between the use of emergency medical services (EMS) and the severity of disease among patients admitted to the emergency room, to analyze the characteristics of the patients, and to build prediction model providing evidence-based use of EMS resources.Methods:The data of patients admitted to the Emergency Room of the First Affiliated Hospital of University of Science and Technology of China from January 2020 to July 2021 were extracted from the Chinese Emergency Triage Assessment and Treatment (CETAT) database. Patients were divided into the EMS use group (AB+ group) and self-seeing group (AB-group) according to whether they used EMS. The patients’ general condition, vital signs and laboratory tests results were recorded. The severity of patients’ condition was judged based on whether the patient was admitted to the department of critical medicine, specialized care unit, emergency operation and/or emergency percutaneous intervention. A 9-variable model that did not require laboratory inspection and 22-variable model that required laboratory inspection were established to correct the propensity score to analyze the correlation between the severity of disease and the EMS use. In the subgroup analysis, the correlation between the EMS use and severity of the patients was analyzed according to the reason of the patient’s visit.Results:During the study period, 16 489 patients were admitted to the emergency room, and 6975 patients were finally enrolled in this study. There were 2768 patients (39.7%) in the AB+ group and 4207 patients (60.3%) in the AB-group. In the AB+ group 522 patients (18.9%) were in high risk, and in the AB-group 563 patients (13.4%) were in high risk. Compared with the AB-group, patients in the AB+ group were older and had a higher proportion of coma, a faster autonomic heart rate, and a lower diastolic blood pressure and peripheral oxygen saturation (SpO 2). In the 9-variable model, sex, consciousness, temperature, heart rate and diastolic blood pressure were associated with the EMS use. In the 22-variable model, consciousness, SpO 2, neutrophils, and albumin were the relevant factors for patients using EMS. Before the correction of propensity score, the EMS use was an independent risk factor for critically ill patients ( OR=1.5, 95% CI 1.32-1.72, P<0.001). After adjusted using 9-variable propensity score, the EMS use ratio decreased significantly compared with that without correction ( OR=1.24,95% CI 1.08-1.42, P<0.001). Interestingly, after adjusted with propensity score match with 22-variable model, there was no association between the severity of disease and t the EMS use ( OR=1.10,95% CI 0.95-1.28, P=0.195). In subgroup analysis, patients’ chief complaint of central nervous system, cardiovascular system, and trauma were the top three reasons at admission. Before the propensity score correction, the EMS calling patients with chief complaint of central nervous system, digestive system, and trauma were related to the severity of the patients. After adjusted with 9-variable model the EMS use was associated with the severity of the disease only in trauma patients, and after adjusted with 22-variable model there was no statistical difference considering the severity of the disease in all subgroups. Conclusions:The EMS use is common. However, the association of the EMS use with the severity of disease is decreased with variable models using propensity score. These findings indicate that the EMS use should be based on multivariable models, which may be important in detecting critically ill patients, optimizing the EMS use, and avoiding unnecessary call in the future.
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OBJECTIVE:To discuss the pros and cons of Markov decision model, an optimized Markov model and to facilitate its application in pharmacoeconomics. METHODS: The basic characteristics of Markov model were introduced and the advantage of the Markov decision model in pharmacoeconomics was analyzed by comparing it with Markov model. RESULTS & CONCLUSION: Markov decision model can evaluate the economics of drugs and treatment methods more effectively than Markov model; moreover, it can alter medication or treatment methods according to patients' specific health status.
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OBJECTIVES: To investigate the therapeutic compliance and its related factors in lung cancer patients. METHODS: The subjects of this study comprised 277 patients first diagnosed with lung cancer at Kyungpook National University Hospital between Jan 1999 and Sept 1999. Of these, 141 (50.9%) participated in the study by properly replying to structured questionnaires. The data was analyzed using a simplified Health Decision Model. This model includes categories of variables covering therapeutic compliance, health beliefs, patient preferences, knowledge and experience, social interaction, sociodemographic and clinical characteristics. RESULTS: The therapeutic compliance rate of the 141 study subjects was 78.0%. An analysis of health beliefs and patient preferences revealed health concern (p<0.05), dependency on medicine (p<0.05), perceived susceptibility and severity (p<0.05) as well as preferred treatment (p<0.01) as factors related to therapeutic compliance. Factors from the sociodemographic characteristics and clinical factors that were related to therapeutic compliance were age (p<0.01), monthly income (p<0.05), histological type (p<0.05) and clinical stage (p<0.05) of cancer. CONCLUSIONS: In order to improve therapeutic compliance in lung cancer patients it is necessary to educate the aged, low-income patients, or patients who have small cell lung cancer or lung cancer of an advanced stage for which surgery is not indicated. Additionally, it is essential for medical personnel to have a deep concern about patients who have poor lifestyles, a low dependency on medicine, or a high perceived susceptibility and severity. Practically, early diagnosis of lung cancer and thoughtful considerations of low-income patients are important. By means of population-based education in a community, we may promote attention to health and enhance the early diagnosis of lung cancer.