This document analyzes the longitudinal medical costs of hypertensive diseases in Mexico from 2012 to 2050. It calculates probabilities of disease detection, treatment, and death by age and sex using historical Mexican health data. Medical costs are projected under base, optimal, and worse economic growth scenarios. Costs are higher for women and increase significantly after age 50. The maximum number of patients in treatment is between ages 20-29, decreasing until ages 65-69 for men and 60-64 for women before rising again with other age-related illnesses. Hypertensive disease costs are more expensive than diabetes and projected to increase as the population ages.
Aim: Suicide is the leading cause of non-accidental death in Spain across both sexes and all age groups; however, data on suicide attempts by region are heterogeneous and little reported. This study aimed to examine the socio-demographic and epidemiological variables most
strongly related to suicide attempts in Jaén province.
Method: Data on people who had attempted suicide over a 26-month period (2009–2011) were collected from the emergency departments of two hospitals via their electronic medical record systems specific to the Autonomous Community of Andalusia (Spain). Descriptive and frequency statistics were obtained and the relationship among variables was examined.
Results: Suicide attempters were aged 24 to 53 years, being primarily women (65.25%). The most frequent suicide method was medication ingestion (85.55%); thus, ingestion of toxic substances has become the preferred method among women (LR(3) = 14.731; p = .02). The
hospitals discharged the patients (46.44%) or referred them to mental health services in the area (20.08%) following a suicide attempt. There were more hospital discharges when the attempt involved ingestion of toxic substances or self-harm (LR(12) = 20.603; p = .05), and in winter
and spring (LR(12) = 69.772; p < .001).
Conclusion: The need for emergency departments to have prevention and intervention procedures in place, specifically designed for suicide attempts and at-risk individuals, is discussed
CAMA: The global macroeconomic impacts of COVID-19: Seven scenarios (results)TatianaApostolovich
The research of Warwick McKibbin (Australian National University, The Brookings Institution, Centre of Excellence in Population Ageing Research) and Roshen Fernando (Australian National University, Centre of Excellence in Population Ageing Research (CEPAR))
A Retrospective Study of Malaria Cases Reported in a Decade at Tertiary Level...IOSR Journals
Background: Malaria, a non-fatal disease if detected promptly and treated properly, still causes many deaths in malaria-endemic countries. The present study is intended to find out changing pattern of malarial morbidity and mortality in western India Methods: A retrospective record base study was conducted on malarial cases reported at medical out-patient door (OPD) of SMS Hospital Jaipur (Rajasthan) during last decade i.e. from 1st Jan 2003 to 31st Dec 2012. Available data regarding socio-demographic and mortality profile was collected and analyzed. Case fatality Rates and Proportional Death rates were found out along with cause of death in malaria cases. Chi-squire test was used to find out the significance of difference between proportions. Results: Out of total 3748 malaria cases, maximum cases were reported in Aug to Oct i.e. 2614 (69.74%). Mean age of diseases was 37.4 years with 3.2 M:F Ratio. Maximum Case Fatality Rate was reported in 2003 which decreases with time with sum ups and downs and in 2012 it remains only 1.8%. Most frequent (33%) cause of death was cerebral malaria. Conclusions: Malaria has seasonal variation with maximum cases in post monsoon season affecting mainly middle aged persons. Although there is no certain trend on malarial morbidity but malarial mortality has significantly declined trend.
Aim: Suicide is the leading cause of non-accidental death in Spain across both sexes and all age groups; however, data on suicide attempts by region are heterogeneous and little reported. This study aimed to examine the socio-demographic and epidemiological variables most
strongly related to suicide attempts in Jaén province.
Method: Data on people who had attempted suicide over a 26-month period (2009–2011) were collected from the emergency departments of two hospitals via their electronic medical record systems specific to the Autonomous Community of Andalusia (Spain). Descriptive and frequency statistics were obtained and the relationship among variables was examined.
Results: Suicide attempters were aged 24 to 53 years, being primarily women (65.25%). The most frequent suicide method was medication ingestion (85.55%); thus, ingestion of toxic substances has become the preferred method among women (LR(3) = 14.731; p = .02). The
hospitals discharged the patients (46.44%) or referred them to mental health services in the area (20.08%) following a suicide attempt. There were more hospital discharges when the attempt involved ingestion of toxic substances or self-harm (LR(12) = 20.603; p = .05), and in winter
and spring (LR(12) = 69.772; p < .001).
Conclusion: The need for emergency departments to have prevention and intervention procedures in place, specifically designed for suicide attempts and at-risk individuals, is discussed
CAMA: The global macroeconomic impacts of COVID-19: Seven scenarios (results)TatianaApostolovich
The research of Warwick McKibbin (Australian National University, The Brookings Institution, Centre of Excellence in Population Ageing Research) and Roshen Fernando (Australian National University, Centre of Excellence in Population Ageing Research (CEPAR))
A Retrospective Study of Malaria Cases Reported in a Decade at Tertiary Level...IOSR Journals
Background: Malaria, a non-fatal disease if detected promptly and treated properly, still causes many deaths in malaria-endemic countries. The present study is intended to find out changing pattern of malarial morbidity and mortality in western India Methods: A retrospective record base study was conducted on malarial cases reported at medical out-patient door (OPD) of SMS Hospital Jaipur (Rajasthan) during last decade i.e. from 1st Jan 2003 to 31st Dec 2012. Available data regarding socio-demographic and mortality profile was collected and analyzed. Case fatality Rates and Proportional Death rates were found out along with cause of death in malaria cases. Chi-squire test was used to find out the significance of difference between proportions. Results: Out of total 3748 malaria cases, maximum cases were reported in Aug to Oct i.e. 2614 (69.74%). Mean age of diseases was 37.4 years with 3.2 M:F Ratio. Maximum Case Fatality Rate was reported in 2003 which decreases with time with sum ups and downs and in 2012 it remains only 1.8%. Most frequent (33%) cause of death was cerebral malaria. Conclusions: Malaria has seasonal variation with maximum cases in post monsoon season affecting mainly middle aged persons. Although there is no certain trend on malarial morbidity but malarial mortality has significantly declined trend.
Abstract—Epidemiological study of Rivers State University of Science and Technology Port Harcourt, Nigeria was carried out to identify the morbidity pattern in the University community in order to establish the current health status and trends. This study utilized secondary morbidity data sourced from Health Services Department. Data on staff mortality were obtained from the Personnel/Establishment Division. Methods employed for data collection were health records survey and data collection sheets. Morbidity information required were date, sex, age, department, card number and diagnosis of each case. Information required for each mortality case was date, sex, age, department, salary level and the cause of death. Of all cases of morbidity, communicable diseases comprised 17.5%; non-communicable diseases 24.1%, generalized disease symptoms 55.2% and others 3.2%. The study revealed that the leading causes of morbidity in the University were fever/headache/cold (36.9%), hypertension (13.6%), generalized body pain (7.5%), abdominal pain/vomiting (6.7%) and diabetes (4.9%). Hypertension emerged the second major cause of morbidity among the staff and males had higher rate of morbidity compared to females. It was also concluded that although mortality was increasing with time but there was no sex wise significant difference in mortality trend. It was recommended among others that Diabetes Mellitus and Hypertension being silent killers should be monitored regularly within the University community. Also the current practice of manual data entry should be replaced with computerized data system for better health records management.
International Journal of Business and Management Invention (IJBMI)inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
The predictive modeling approach on continuous statisticsSergey Soshnikov
Using several Modeling technics as Multiple regression, Decision Trees, Neural Networks and Partial Least Square we found and measured several causal factors that influence the level of alcohol in the Russian society.
Cost profiles of colorectal cancer patients in Italy based on individual patt...Enrique Moreno Gonzalez
Due to changes in cancer-related risk factors, improvements in diagnostic procedures and treatments, and the aging of the population, in most developed countries cancer accounts for an increasing proportion of health care expenditures. The analysis of cancer-related costs is a topic of several economic and epidemiological studies and represents a research area of great interest to public health planners and policy makers. In Italy studies are limited either to some specific types of expenditures or to specific groups of cancer patients. Aim of the paper is to estimate the distribution of cancer survivors and associated health care expenditures according to a disease pathway which identifies three clinically relevant phases: initial (one year following diagnosis), continuing (between initial and final) and final (one year before death).
This article is a departure from many prior studies in the literature on Medicare spending in the United
States. Previous works have focused on time-invariant or hereditary demographic characteristics and
congenital health status. In contrast, this study examined state-level variations in Medicare costs per
enrollee with special emphasis on prominent acquired health-related lifestyle attributes that are more
reversible over a short time period. Our main findings are (1) reversible acquired health-related lifestyle
attributes such as smoking and obesity are statistically significant determinants of state-level variations in
Medicare costs; and (2) state-level variations in Medicare spending is elastic with respect to changes in the
prevalence of the two acquired health-related lifestyle attributes.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
z/OS Small Enhancements - Episode 2014AMarna Walle
This presentation covers small enhancements from older z/OS releases. You might have missed little functions that are helpful, but you never knew existed! The content of each of these z/OS Small Enhancements changes every half year (Episode A and Episode B each year).
Predictive analysis WHO's life expectancy dataset using Tableau data visualis...Tarun Swarup
Performed predictive analysis on global Life expectancy dataset (WHO) to analyze the vital factors affecting human health and other societal risks demographically.
Designed a visual dashboard to identify intrinsic patterns in different factors and extract valuable insights to predict life expectancy accordingly.
▪ Infant Death Rate almost reduced by 40% in the last two decades.
▪ Overall adult mortality rate turned down by almost 17% in the previous years.
The Link Between Health Care Expenditure and Life Expectancy: Turkey (1975-2015)inventionjournals
This paper aims to investigate the link between health care expenditure and life expectancy in Turkey, causality and co-integration relationship between health care expenditure (HCE) and life expectancy (LE) in Turkey for the period 1975-2015. In this paper we also used real GDP per capita and some demographic variables such as dependency ratio of the old-aged populations, the number of practicing physicians per hundred thousand persons that may explain the variations in HCE. According to the results of analyze, drperpop, gdp, hce, le65, le70, le75 variables are stable at 1% significance in the first I(1) difference value. The AGE valuable is stable 1% at the level value. There are two long-term cointegration relationships between health spending and life expectant variables. AGE → DGDP, AGE → DLE40, AGE → DLE60, DHCE → DDRPERPOP, DLE80 →DDRPERPOP, DHCE → DGDP and DLE60 → DLE80 shows the direction of granger causality
Deaths from fall-related traumatic brain injuries are on the rise in U.S.Δρ. Γιώργος K. Κασάπης
Deaths due to traumatic brain injuries from falls have risen in recent years, according to new CDC data. Here's more:
•Overall trends: From 2008-2017, the number of TBI-related deaths from falls increased 17%, leading to more than 17,400 such deaths in 2017.
•Demographics: In 2017, the rate of such deaths was highest in males and in people aged 75 and older. In fact, the death rate in this age group was eight times more than for those 55-74.
•Implications: Given the study's findings, and the aging population in the U.S., health care providers ought to educate the elderly and their families about the risk of falls, the report authors conclude.
Background; Social Class has shown relation with admissions at Emergency Departments. To assess whether there is a relationship between the level of triage and the social class of patients who attend the emergency department and whether there are other variables that can modulate this association. Methods Observational study with 1000 patients was carried out between May and July 2018 in the Emergency Department of the University Hospital Arnau de Vilanova in Lleida. Sociodemographic variables such as age, gender, country of origin and marital status were analyzed. The triage level and the main explanatory variable was social class. Social class was calculated based on the CSO-SEE 2012 scale. Results 49.4% were male and the average age was 51.7 years. Most of the patients (66.6%) attended the emergency department under their own volition and the most common triage levels were level III or Emergency (45%). There is a significant relationship between age and triage level. The younger patients had a lower triage level (p <0.001). The percentage of patients with lower social class who attended the emergency department for minor reasons was 42% higher compared to the rest of the patients (RR = 1.42; 1.21-1.67 95% CI, p <0.001). Conclusions; Patients with a lower socioeconomic class go to the Emergency Department for less serious pathologies.
Abstract—Epidemiological study of Rivers State University of Science and Technology Port Harcourt, Nigeria was carried out to identify the morbidity pattern in the University community in order to establish the current health status and trends. This study utilized secondary morbidity data sourced from Health Services Department. Data on staff mortality were obtained from the Personnel/Establishment Division. Methods employed for data collection were health records survey and data collection sheets. Morbidity information required were date, sex, age, department, card number and diagnosis of each case. Information required for each mortality case was date, sex, age, department, salary level and the cause of death. Of all cases of morbidity, communicable diseases comprised 17.5%; non-communicable diseases 24.1%, generalized disease symptoms 55.2% and others 3.2%. The study revealed that the leading causes of morbidity in the University were fever/headache/cold (36.9%), hypertension (13.6%), generalized body pain (7.5%), abdominal pain/vomiting (6.7%) and diabetes (4.9%). Hypertension emerged the second major cause of morbidity among the staff and males had higher rate of morbidity compared to females. It was also concluded that although mortality was increasing with time but there was no sex wise significant difference in mortality trend. It was recommended among others that Diabetes Mellitus and Hypertension being silent killers should be monitored regularly within the University community. Also the current practice of manual data entry should be replaced with computerized data system for better health records management.
International Journal of Business and Management Invention (IJBMI)inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
The predictive modeling approach on continuous statisticsSergey Soshnikov
Using several Modeling technics as Multiple regression, Decision Trees, Neural Networks and Partial Least Square we found and measured several causal factors that influence the level of alcohol in the Russian society.
Cost profiles of colorectal cancer patients in Italy based on individual patt...Enrique Moreno Gonzalez
Due to changes in cancer-related risk factors, improvements in diagnostic procedures and treatments, and the aging of the population, in most developed countries cancer accounts for an increasing proportion of health care expenditures. The analysis of cancer-related costs is a topic of several economic and epidemiological studies and represents a research area of great interest to public health planners and policy makers. In Italy studies are limited either to some specific types of expenditures or to specific groups of cancer patients. Aim of the paper is to estimate the distribution of cancer survivors and associated health care expenditures according to a disease pathway which identifies three clinically relevant phases: initial (one year following diagnosis), continuing (between initial and final) and final (one year before death).
This article is a departure from many prior studies in the literature on Medicare spending in the United
States. Previous works have focused on time-invariant or hereditary demographic characteristics and
congenital health status. In contrast, this study examined state-level variations in Medicare costs per
enrollee with special emphasis on prominent acquired health-related lifestyle attributes that are more
reversible over a short time period. Our main findings are (1) reversible acquired health-related lifestyle
attributes such as smoking and obesity are statistically significant determinants of state-level variations in
Medicare costs; and (2) state-level variations in Medicare spending is elastic with respect to changes in the
prevalence of the two acquired health-related lifestyle attributes.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
z/OS Small Enhancements - Episode 2014AMarna Walle
This presentation covers small enhancements from older z/OS releases. You might have missed little functions that are helpful, but you never knew existed! The content of each of these z/OS Small Enhancements changes every half year (Episode A and Episode B each year).
Predictive analysis WHO's life expectancy dataset using Tableau data visualis...Tarun Swarup
Performed predictive analysis on global Life expectancy dataset (WHO) to analyze the vital factors affecting human health and other societal risks demographically.
Designed a visual dashboard to identify intrinsic patterns in different factors and extract valuable insights to predict life expectancy accordingly.
▪ Infant Death Rate almost reduced by 40% in the last two decades.
▪ Overall adult mortality rate turned down by almost 17% in the previous years.
The Link Between Health Care Expenditure and Life Expectancy: Turkey (1975-2015)inventionjournals
This paper aims to investigate the link between health care expenditure and life expectancy in Turkey, causality and co-integration relationship between health care expenditure (HCE) and life expectancy (LE) in Turkey for the period 1975-2015. In this paper we also used real GDP per capita and some demographic variables such as dependency ratio of the old-aged populations, the number of practicing physicians per hundred thousand persons that may explain the variations in HCE. According to the results of analyze, drperpop, gdp, hce, le65, le70, le75 variables are stable at 1% significance in the first I(1) difference value. The AGE valuable is stable 1% at the level value. There are two long-term cointegration relationships between health spending and life expectant variables. AGE → DGDP, AGE → DLE40, AGE → DLE60, DHCE → DDRPERPOP, DLE80 →DDRPERPOP, DHCE → DGDP and DLE60 → DLE80 shows the direction of granger causality
Deaths from fall-related traumatic brain injuries are on the rise in U.S.Δρ. Γιώργος K. Κασάπης
Deaths due to traumatic brain injuries from falls have risen in recent years, according to new CDC data. Here's more:
•Overall trends: From 2008-2017, the number of TBI-related deaths from falls increased 17%, leading to more than 17,400 such deaths in 2017.
•Demographics: In 2017, the rate of such deaths was highest in males and in people aged 75 and older. In fact, the death rate in this age group was eight times more than for those 55-74.
•Implications: Given the study's findings, and the aging population in the U.S., health care providers ought to educate the elderly and their families about the risk of falls, the report authors conclude.
Background; Social Class has shown relation with admissions at Emergency Departments. To assess whether there is a relationship between the level of triage and the social class of patients who attend the emergency department and whether there are other variables that can modulate this association. Methods Observational study with 1000 patients was carried out between May and July 2018 in the Emergency Department of the University Hospital Arnau de Vilanova in Lleida. Sociodemographic variables such as age, gender, country of origin and marital status were analyzed. The triage level and the main explanatory variable was social class. Social class was calculated based on the CSO-SEE 2012 scale. Results 49.4% were male and the average age was 51.7 years. Most of the patients (66.6%) attended the emergency department under their own volition and the most common triage levels were level III or Emergency (45%). There is a significant relationship between age and triage level. The younger patients had a lower triage level (p <0.001). The percentage of patients with lower social class who attended the emergency department for minor reasons was 42% higher compared to the rest of the patients (RR = 1.42; 1.21-1.67 95% CI, p <0.001). Conclusions; Patients with a lower socioeconomic class go to the Emergency Department for less serious pathologies.
Dr Yousef Elshrek is One co-authors in this study >>>> Global, regional, and...Univ. of Tripoli
Global, regional, and national age–sex specifi c all-cause and cause-specifi c mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013
GBD 2013 Mortality and Causes of Death Collaborators*
Dr. Yousef Elshrek is Coauthors in this study
PRIVATE AGE ADJUSTMENTWhen analyzing epidemiologic dat.docxsleeperharwell
PRIVATE
AGE ADJUSTMENT
When analyzing epidemiologic data, researchers often wish to adjust for the influence of some variable so that the "true" effect of other variables can be seen more clearly. Consider the example of a study to determine if gray hair is related to mortality risk. Two statements stand out in this study:
1. People with gray hair have a higher death rate when compared to other people.
2. People with gray hair are older than others people.
Because of this second statement the meaning of statement one is obscure. The possible link between gray hair and mortality risk is confused by the effect of age on mortality risk. Age is considered a confounding factor that needs to be accounted for to accurately assess the impact of gray hair on mortality rates. Epidemiologists use many tools to sort through information and overcome this confusion of information by adjusting data. The purpose of data adjustment is to disentangle the relationship so that we can evaluate a variables effect free from confusion and distortion. For the gray hair investigation, adjustment would permit us to determine whether persons of the same age who have gray hair have different mortality risks. (Sempos 1989)
Confounding Variables
Confounding variables are variables whose effects confuse the true relationships between factors and diseases. This is why there is a need for data adjustment. In order for a variable to be considered a confounding variable, it must be related to the disease or condition of interest and to the risk factor being investigated (Miettinen 1970). But if the possible confounding variable is truly related only to the disease of interest, it may still be desirable to adjust for it (Mantel 1986). One reason is the adjustment could possibly reduce the sampling variance of the comparison that is being investigated.
Adjustments
A common example of data adjustment is the age adjustment of mortality rates. While the age adjustment technique is most often applied to mortality (death) rates, it could also be applied to incidence of disease, prevalence, or any other kind of proportional rates. Age adjustment allows comparison of mortality risk for various groups free from the distortion of one group having a different age distribution than another. There are two types of age adjustments in relation to mortality rates -- direct and indirect age adjustments.
Direct Adjustment
Direct adjustment, or direct standardization, is to superimpose the age distribution of a standard population on the two study groups to be compared. Standardized rates are then calculated for each population, making use of the standard age distribution. These adjusted rates are then compared, and any difference between them can no longer be due to difference in age distribution because age has been taken into account. The direct method uses two inputs called age-specific rates and standard population.
Age-Specific Rates
A set of age-specif.
Examination of the incidence of heart disease in the US. A multivariate logis...AJHSSR Journal
ABSTRACT:Heart disease is a condition that affects the human heart and blood vessels. Heart disease affects
about half of American adults, and it also played a role in the high death rate in the rest of the world. The data
extracted from National Center for Health Statistics (NCHS) span from December 2019 to December 2021. The
only goal of this study is to look at the risk factors that affect the incidence of heart disease. After that, it will
estimate a Youden index to find the best cut-off point and measure how well the multivariate logistic regression
model's diagnostic test performed, adding to the body of knowledge. The application of logistic regression
yielded the finding that socioeconomic and health risk variables strongly influence the incidence of heart
disease. According to the Youden index, the ideal cutoff value is around 52%. Consequently, it is crucial for
American adults to monitor their lifestyle, have their BMI, blood pressure, diabetes, and other risk factors for
heart disease diagnosed, and then make sure they are receiving adequate treatment to prevent the tendency to
develop heart disease, which in turn will lower the death rate brought on by heart disease.
KEYWORDS: Heart disease, Multivariate logistic regression, Youden index, Health risk factors,
socioeconomic factors.
Used for Medical Grand Rounds at several hospitals, this is data based comprehensive review of the shortcomings of the American Medical System and dysfunctional political attempts at reform. Single payer, Medicare for all, with elimination of for profit insurance companies is the best answer.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Epistemic Interaction - tuning interfaces to provide information for AI support
C05841121
1. IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org
ISSN (e): 2250-3021, ISSN (p): 2278-8719
Vol. 05, Issue 08 (August. 2015), ||V4|| PP 11-21
International organization of Scientific Research 11 | P a g e
Longitudinal Analysis and Prospective of Medical Cost for
Hypertensive Diseases: Case of Mexico
Dora Elena Ledesma-Carrión1
, Lidia Hernández-Hernández2
and
María Teresa Leonor Muciño-Porras3
1
Instituto Nacional de Estadística y Geografía (INEGI)
Av. Patriotismo 711, Col. San Juan Mixcoac, C.P. 03730, Del. Benito Juárez, México D.F.,
Tel.: 52781000, ext.1624
2
Instituto Nacional de Estadística y Geografía (INEGI)
Av. Patriotismo 711, Col. San Juan Mixcoac, C.P. 03730, Del. Benito Juárez, México D.F.,
3
Instituto Nacional de Estadística y Geografía (INEGI)
Av. Patriotismo 711, Col. San Juan Mixcoac, C.P. 03730, Del. Benito Juárez, México D.F.,
Abstract: - The treatment unit costs are similarly between men and women, but there are more men than women
with hypertension and increasing the medical costs. Medical costs are calculated for hypertensive diseases for
all age groups of Mexican people and sex into range of 2012-2050. Probabilities of entrance or disease
detection, permanence or in treatment and departure or death are calculated for each age group and sex. The
maximum probabilities for each case are 1.92% (60-64), 53.31% (85+) and 3.13% (85+) for male. Analogously,
for female are 2.45% (60-64), 72.46% (85+) and 2.27% (85+), respectively. The maximum number of people in
treatment is between 20 and 29 years old, decreasing up to 65-69 (male) and 60-64 (female) years of age and,
70+ (male) and 65+ (female) increases again because of other sickness appear linking with hypertension.
Keywords: - aging, health, hypertension, medical costs, prospective.
I. INTRODUCTION
Mexican food is varied but rich in carbohydrates and fats, recent advances in medicine have shown that
the change of cane sugar by fructose as a sweetener in the Mexican diet is largely responsible along with
hereditary factors of physical deterioration of the Mexican population: obesity, diabetes mellitus, hypertensive
diseases (HD) and chronic-disease degenerative[1], [5].
This work shows the economic impact over a horizon of 2012-2050 of HD in terms of percentages of gross
domestic product (GDP), for the three scenarios: base, optimal and worse. The base scenario is calculated by
adjusting a model AR(2)MA(2)[2] with weighting, the other two are given by experts and both depend on the
effect of energy and labor reforms.
The available information is from public institutions: Ministry of Health (Secretaría de Salud, SS[3],
[8], [9], [11]), National Population Council (Consejo Nacional de Población, CONAPO[12]), Mexican Institute
of Social Security (Instituto Mexicano del Seguro Social, IMSS[4], [6], [7]), National Institute of Statistics and
Geography (Instituto Nacional de Estadística y Geografía, INEGI[10]) and private: Mexican Association of
Insurance Institutions (AMIS) and hospitals.
Population projections by CONAPO whose methodology appears on the official website[12] and decadal cohort
of number of patients and unit costs for some diseases IMSS beneficiaries were used[6], [7]. IMSS information
is not showed by age group neither sex (patients in treatment). New cases information appears since 1980 up to
1990 by big age group and sex and 1991-2011 by age group. Deceased people by HD is presented by age and
sex.
The cost of this disease is high for its treatment and its duration. As insured persons by IMSS represent
40% of the population, IMSS data are taken as sampling. The Mexican health system (SS) covers the following
institutions: IMSS, Institute for Social Security and Services for State Workers (Instituto de Seguridad y
Servicios Sociales de los Trabajadores del Estado, ISSSTE), Popular Insurance (Seguro Popular, SP-IMSS), Oil
Company (Petróleos Mexicanos, PEMEX), Ministry of Defense (Secretaría de la Defensa Nacional, SEDENA),
Ministry of Navy (Secretaría de Marina, SEMAR), private institutions and other public institutions, so the
numbers of deaths and new cases are representative of the population.
II. METHODOLOGY
The proposed model is stochastic[2] with entrance, in treatment and death probabilities by HD, population,
number of patients and unitary cost at time t by age group and sex (stock).
The probabilities are calculated for each year, t, as
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Pr(death; age; sex; t)= (# death by the disease(age; sex; t))/(# death by the disease(age; sex; t)) (1)
Pr(new cases; age; sex; t)= (# new cases or #detected disease(age; sex; t))/(# death by the disease(age; sex; t))
(2)
Pr(+1; age; sex; t)= (# death by the disease(age; sex; t)# permanence or #people who have survived the disease
one more year(age; sex; t))/(# death by the disease(age; sex; t)) (3)
The model diagram is showed in Figure 1. Several considerations must be taken by each patient’s condition.
Deaths. It works with the records of the SS with respect to age, sex and cause key, excluding unspecified. It has
the historical 1990 to 2011. Curve fitting are applied to these data by ordinary least-squares (OLS) after the
transformation of equation (4). In most cases it is the exponential. The growth rates are denoted as λ´s.
Prospective is constructed following behavior given these rates, for 2012-2050 taken as input data 2011.
The correlation coefficient of curve fitting are showed in Table 1.
deatht= death0eλt
⇒ Ln(deatht )=Ln(death0eλt
)=Ln(death0 )+ λt (4)
The equation (1) is calculated using both prospective, the population and the exponential behavior of
deaths by HD. This latter based on the high correlation coefficients by age group and sex shown in Table 1.
Behavior of deaths was analyzed. The age groups 40+ showed an exceptional exponential behavior with
correlation coefficients greater than 92% for female and 94% for male.
New cases. From the database of the SS tables of major diseases are obtained by age group (<1, 1-4, 5-9, 10-14,
15-19, 20-24, 25-44, 45-49, 50-59, 60-65 & 65+). Information was obtained from 1990-2011 data which its
trend behavior and basic statistics (mean and standard deviation) was analyzed. In case non-trend was chosen to
simulate an exponential growth between the extreme values for the entire period. As a base scenario was chosen
the trend values as first option and minimum among all the options as second choice.
The equation (2) is calculated using both prospective, the population and the exponential behavior of new cases
by HD.
For new cases exhibit this behavior with correlations of 25% for women and 83.39% for men in
general. The probabilities of entrance, in treatment and death to HD are dynamics and they are different in each
stage. Their dynamic changes are gotten by LSO. Table of these dynamic changes by age group are shown in the
appendix.
In treatment. IMSS data were used to rebuild the intermediate years. The method Runge-Kuta was applied to
the exponential growth rates per period. Then data were redistributed according to death rates of SS for age
groups. Subsequently normalized with respect to the prospective of the IMSS. The initial value is the amount of
the average proportion of deaths[1] by age group by sex (2003-2011) multiplied by the number of patients
treated according to IMSS prospective.
Data from 2011 patients in treatment are obtained by extrapolating the values of 2012 compared to
exponential growth rates (2012-2020) of its prospective. The cases of initial values are the maximum, minimum
and average in the period. After these are distributed by age and sex as mentioned in the previous paragraph.
The equation (3) is calculated using both prospective, the population and the exponential behavior of in
treatment patients by HD. As the number of in treatment patients are IMSS data (sample), these were analyzed
and calculated their behavior and prospective of both beneficiaries of the IMSS and beneficiaries who have
survived the disease one more year. Latter, the probabilities by age group by sex by each year were gotten
applying equation (3). After, these probabilities were input to make inference to population.
Redistribution by age group (2012-2050) can be calculated using standard growth rates (about the death)
following the general prospective IMSS or initial value using any of the three values obtained from the ratios of
deaths by group age by sex by disease (1990-2012): average, maximum or minimum. And from the initial value
to apply the before mentioned growth rates. The scenarios I, II and III use the average, maximum and minimal
values as initial value (2011), respectively.
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Figure 1: Schematic model. Started CONAPO population projections estimated population with hypertensive
diseases, new cases and dying from this disease from 2012 to 2050.
Table 1: Correlation coefficients for exponential behavior (Death)
2.1 Gross Domestic Product scenarios: Basis, optimal and worse.
Base Scenario. Quarterly gross domestic product (GDP) data since 1996-I up to 2012-IV current prices are
applied to AR(2)MA(2) model (Eq. (5)). Adjusted data are deflated to base year 2012.
GDPt = 1.037568GDPt-2 + [AR(2) = 0.730942, MA(2) = -0.937709], 1996 ≤ t ≤ 2012 (5)
From Table 2, AR process is stationary and ARMA model is invertible. The model presents positive serial
correlation because of Durbin-Watson statistical is between 1 and 2. Covariance matrix values appear in Table
3.
Table 2: Statistical parameter of model AR(2)MA(2)
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Table 3: Covariance matrix of model AR(2)MA(2)
The increasing GDP was 2.5% (January 2013) fall dawn 1.7% (December 2013). Average rate in June
2014 was 3.1% (fall dawn up to 2.5%) and last semester is expected 1.7%. The government expects an
increasing rates during 2015 between (2.5% - 3.5%). In 2016, rates could be of (3.0% - 3.1%) and in 2017-2050
of 3%. If energy and labor reforms are successful, the GDP growth rates could be of up to 7% from 2020. The
GDP prospective is showed in the Figure 2.
Optimum scenario. Upper limits of the ranges of the above paragraph.
Worse scenario. Lower limits of the ranges of the above paragraph.
Figure 2: Curves fitted for each scenarios of gross domestic product are showed.
2.2 Probabilities of entrance, in treatment and death for hypertensive diseases.
Dynamics probabilities prospective by patient condition by age group by sex by year are gotten from
IMSS prospective for in treatment patients (Table 4) and applied to Runge-Kutta approximation to
reconstruction year by year. Late, death data historic distribution by age groups and its prospective and applied
to Table 5 data. Maximal increasing rate for male is 12.832% at 2010 and 28.623% for female at 2012. These
rates are larger for women as men throughout the period. NOTE: In the IMSS prospective of in treatment
patients, their rates are decreasing from 2040 to differences obtained from the analysis of historical data from
1990 to 2011.
Table 4: IMSS prospective for in treatment patients of hypertensive diseases
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Table 5: Probabilities by patient condition by sex by year (2012-2050)
In the cases of death and new cases condition, dynamics probabilities prospective are fitted by LSO. SS data are
age groups.
III. RESULTS
From Figures 3 and 4, comparing two arbitrary years, 2019 and 2040, HD medical costs are higher for
women than men about 0.44% and 0.77% of GDP, respectively, for base scenario. To worse scenario the
differences are 0.63% and 1.42% for each reference year. To optimum scenario are 0.55% and 0.65%. All in
absolute terms.
If the initial value of patients in 2011 is the historical minimum, the differences in medical costs versus
maximum are 0.11% (2019) and 0.12% (2040) for male. For female, the costs differences are 0.1871% and
0.1856%, respectively. All in absolute terms.
For historical minimum initial value versus average initial value, the differences in medical costs for male are
0.0926% (2019) and 0.1037% (2040) and for female are 0.1147% and 0.1151%, respectively. All in absolute
terms.
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Figure 3: Medical cost as a percentage of GDP for male and female since 2012 up to 2050 for three scenarios:
base, optimum and worse.
Figure 4: Medical cost as a percentage of GDP for male and female for base scenario.
From Figures 5, 6 and 7, he medical costs represent 11.609% (2019) and 11.38% (2040) for 50 and more years
old male respect all disease population. For female, the costs are 3.71% and 3.62%, respectively.
The maximum number of people in treatment is between 20 and 29 years old. The sick HD cases are going to
shoot up after 85+ years old for female.
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Figure 5: Comparative number of patients for male and female by age group for base scenario and minimum
initial value.
Figure 6: Comparative unit cost for male and female all age group vs. 50 and more years old.
Figure 7: Comparative number of patients of HD for male and female all age group vs. 50 and more years old.
IV. CONCLUSIONS
The hypertensive diseases are more expensive than diabetes mellitus[13]. After of 50 years old HD
increasing costs conceivably owing to others illness linking like neuronal diseases and renal failure. HD appears
at early age (20-29) for both sex and increase from 70 years old.
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It is necessary to construct consistent data bases for new cases and in treatment condition patient for age by sex
by year to better models.
V. ACKNOWLEDGEMENTS
The authors would like to thank Jorge Rodolfo Daudé Balmer, María Rebeca Ruíz Velasco, Gabriela Pérez
García, María de Lourdes Vázquez Díaz, María Guadalupe Aguilar Frías.
I. APPENDIX
Table 6: Probabilities of enter or disease detection – Male
Table7: Probabilities of enter or disease detection – Female
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Table 8: Probabilities of stock or in treatment – Male
Table 9: Probabilities of stock or in treatment – Female
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Table 10: Probabilities of death – Male
Table 11: Probabilities of death – Female
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