Estimation of physician demand based on an unequal weight combination forecasting model / 中华医院管理杂志

Objective:To measure the demand of physicians in 2020-2035 period by constructing an unequal weight combination forecasting model, and to provide scientific reference for health manpower planning.Methods:This study called into play the trend extrapolation method, human/population ratio method and health service demand method to preliminarily predict the demand of physicians in 2020-2035, followed by Delphi method to carry out unequal weight combination of the results of these three methods. Hence the physicians demand in 2020-2035 in China was calculated.Results:Based on the unequal weight combination forecasting model, the physicians demand of the period in China was estimated to increase from 2.64 people / 1 000 population to 3.67 people / 1 000 population, and the physicians demand to gradually increase at a growth rate in gradual slowdown.Conclusions:This research used the unequal weight combination forecast model, based on the service demand and the historical situation. It is suggested that relevant policies of medical education and specialists division be made based on both the demand and the factors affecting the supply and demand balance of physicians.

Development of a nomogram for predicting survival of patients with ovarian serous cystadenocarcinoma after based on SEER database / 浙江大学学报·医学版

To develop a survival time prediction model for patients with ovarian serous cystadenocarcinoma after surgery. A retrospective analysis of 5906 postoperative patients with ovarian serous cystadenocarcinoma in the surveillance, epidemiology, and end results (SEER) database from 2010 to 2015 was performed. The independent risk factors for long-term survival were analyzed with multivariate Cox proportional hazard regression model. The nomogram of 3-year and 5-year survival was developed by using R language. The receiver operator characteristic (ROC) curve and were used to test the discrimination of the model and the calibration diagram was used to evaluate the degree of calibration of the prediction model. The survival curves was conducted by the risk factors. Cox proportional hazard regression model showed that age, race, histological grade (poorly differentiated and undifferentiated), stage T (T2a, T2b, T2c, T3a, T3b and T3c), and stage M (M1) were independent factors for the prognosis of patients with ovarian serous cystadenocarcinoma after surgery. A nomogram was developed by the R language tool for predicting the 3-year and survival of patients through age, race, histological classification, stage T and stage M. The C-index was 0.688 and the areas under ROC curve of the nomogram for predicting 3-year and 5-year survival were 0.708 and 0.716, respectively. The results of the calibration indicated that the predicted values were consistent with the actual values in the prediction models. The survival time of patients with high-risk factors was shorter than that of patients with low-risk factors (<0.05). The developed nomogram in this study can be used to predict 3-year and 5-year survival of postoperative patients with ovarian serous cystadenocarcinoma, and it may be beneficial to guide clinical treatment.

Malaria in India: A Predictive Study

@#Introduction: Malaria is devastating infectious disease not only India but also throughout the globe due to its high morbidity and mortality factor for last few centuries. From 19th and early 20th centuries, almost a quarter of the Indian populations were severely suffering from malaria. The economic loss due to increased mortality in malaria was estimated 10 million rupees per year in 1935. According to the World Malaria Report of 2017, malaria incidence accounted for 58% of cases in India. The objective of this study is to prediction of “annual” malaria incidences in India, depending on the basis of last 22 years national malaria epidemiology data. Methods: This study uses data from the official website of the National Program for the Control of Vector borne Diseases (NVBDCP) (http://nvbdcp. gov.in/) from 1995 to 2016. For creating a forecasting tool on Malaria surveillance in India, Econometric forecasting model (ARIMA Model ((0,1,1) (1,0,0) 12)) was used. Results: ARIMA statistical model ((0,1,1) (1,0,0) 12) found to be highly effective and significant (P < 0.05) in prediction of future epidemiological surveillance of malaria in India. ARIMA statistical model could be successfully use in prediction of annual malaria incidences in India after adjusting different highly contributing environmental and geographical factors, such as climate change, temperature, rainfall, and relative humidity. Conclusion: The historical forecast of the occurrence of malaria in India will allow the government to improve planning, control and prevention through public health interventions. In addition, the pharmaceutical industry will assist medical members in pre-treatment and drug interventions to respond to the increased or decreased occurrence of malaria.

Forecasting model of operational casualty in surface warship formation against several groups of missile attacks / 第二军医大学学报

Combat casualty prediction on the sea is always challenging. Considering various factors involved in the attack and defense of warship formation and missile attack effect, we calculated the combat casualty based on the damage assessment result of combat simulation with reasonable simplification, which provided a forecasting model of combat casualty for surface warship after multiple missile attacks, improving the accuracy of casualty prediction in naval warfare.

Descripción de la Cronología del Dolor de las Contracciones Uterinas para Analgesia del Trabajo de Parto, una tarea pendiente / Description of the chronology of the pain of uterine contractions for analgesia of labor, a pending task

Propósito: Describir la periodicidad del momento de máxima intensidad del dolor de las contracciones uterinas (CUs) durante el trabajo de parto (TDP) para eventualmente permitir el desarrollo de nuevos modelos de administración de analgesia endovenosa. Material y método: Embarazadas de término en TDP, reclutadas desde marzo 2014 por 18 meses, de manera no probabilística consecutiva. Se obtuvo el momento de máximo dolor por autoreporte de las pacientes con cronómetros, previa capacitación. Análisis: Regresión para medidas repetidas de efectos mixtos a los 3-5, 6-7 y 8-10cm de dilatación. La variable respuesta es el intervalo de tiempo desde el momento de máximo dolor de la CU basal al de la contracción siguiente. Resultados: En 64 pacientes, se obtuvo 5 intervalos de tiempo. Para la dilatación de 3-5cm una mediana=140.92 segundos y los coeficientes de regresión (CR) en 4 intervalos de tiempo con respecto al basal de 4.2, 15.9, -2.7 y -5.8 segundos. Para 67cm una mediana=131.16 seg y CR 13.4, 11.3, 2 y -10 seg. Para 8-10cm una mediana=129.3 seg y CR -6.7, 0.49, -2.5 y -7.7 seg. No hubo diferencias significativas entre los coeficientes de regresión. Conclusiones: Con los datos obtenidos podemos señalar que no hubo diferencias estadísticas significativas entre los intervalos de tiempo de los momentos de máximo dolor durante el TDP en fase activa. Esta información es relevante para apoyar el desarrollo de un modelo predictivo del dolor.

Aim: To describe the timing of the moment of maximum intensity of uterine contraction (UC) pain in labor to possibly enable the development of new models for administering endovenous analgesia. Materials and Methods: Full-term pregnant women in labor, recruited from March 2014 for 18 months, using consecutive nonprobability sampling. The moment of maximum pain was ascertained as self-reported by patients previously trained with chronometers. Analysis: Regression for repeated measurements from mixed results at 3-5, 6-7 and 8-10cm of dilation. The response variable was the time interval from the moment of maximum pain of the baseline UC to the following contraction. Results: In 64 patients, 5 time intervals were obtained. For the dilation of 3-5cm, a median=140.92 seconds and regression coefficients (RC) in 4 time intervals relative to the baseline of 4.2, 15.9, -2.7 and -5.8 seconds. For 6-7cm, a median =131.16 sec and RC 13.4, 11.3, 2 and -10 sec. For 8-10cm, a median =129.3 sec and RC -6.7, 0.49, -2.5 and -7.7 sec. There were no significant differences among the regression coefficients. Conclusions: With the data collected we can report that there were no statistically significant differences between the time intervals of the moments of maximum pain during active labor. This information is relevant to support the development of a predictive model for this pain.

The application of weighted combination forecasting model for health resource allocation / 中华医学科研管理杂志

Scientificly forecasting the health resources is the premise and foundation for making health resource planning.This paper summarized the application scope and characteristics of commonly used statistical models for health resources forecasting,introduced many S type curve prediction models commonly used in natural and social economic fields,hackled and concluded the weight calculation methods of combination forecasting models,and on this basis put forward that multivariable time series model or combination forecasting model based on single time series model and multi-linear regression equation of the predictive value should be set up for forecasting health resources,so as to provide methodological references for related forecasting research.

Investigation on the Performance of the Forecasting Model in University Foodservice

The purpose of this study was to investigate the utilization level of forecasting methods in contract foodservice management companies. Questionnaires were distributed and collected from 30 foodservice management companies contracted with universities and 49 university foodservices in Seoul and Kyungki area. Statistical data analysis was performed using SPSS/WIN 10.0 based on the production records of Yonsei University foodservices and the weather reports from a meteorological observatory. The results of this study were as follows: 1) The objectives of the fore-casting systems were identified as saving costs through eliminating the leftover, meeting the customer demands, and improving efficiency in food preparation.2) All of the university foodservices were already performing the forecasting methods but in foodservice management companies as a whole,89.7 percents were applying the method and only 55.2 percents had the separate forecasting department. 3) A large number of foodservice staffs in the head office (65.5%) answered that they often utilized intuitive estimates based on the past experiences and records for forecasting while 65.3% managing staffs in the university foodservices answered the same.4) Both in the head office and university foodservices, actual number of meals served were recorded. In the head office, mostly estimated numbers and actual numbers of meals were recorded while estimated, prepared, and actual numbers of meals served were recorded for most of the cases in university foodservices. 5) The primary factors considered for forecasting were the actual production records for the last month, the customer preference for the selected menu items, and the specific day of the week.