Markov model
•
13 likes•5,313 views
A Markov model is a mathematical modeling technique derived from matrix algebra that describes the transitions a cohort of patients make among a finite number of mutually exclusive and exhaustive health states over a series of short intervals or cycles. In a Markov model, patients are always in one of the defined health states and events are modeled as transitions between states. The contribution of utility to overall prognosis depends on the length of time spent in each health state. Transition probabilities are used to represent the likelihood of moving between states in each cycle. An example Markov model was provided to demonstrate these concepts.
Report
Share
Report
Share
Recommended
Pharmacoepidemiology
Pharmacoepidemiology is the study of drug use in populations and the application of epidemiological methods to examine drug effects. It bridges clinical pharmacology and epidemiology. Pharmacoepidemiological research includes evaluating specific drug use, patterns of drug use, and drug-taking behaviors. Studies focus on prescribing trends, medication adherence, drug interactions, and adverse drug reactions. Data sources include medical records, health insurance claims, and national databases. Observational studies measure drug exposure and outcomes without intervention, while interventional studies actively change exposures. Descriptive studies describe disease occurrence, and case reports/series provide initial signals of drug effects. Cross-sectional studies examine drug use at a point in time, while cohort studies follow exposed and
Bayesian theory
Bayesian theory in population pharmacokinetics--
1) INTRODUCTION TO BAYESIAN THEORY
2)BAYESIAN PROBABILITY TO DOSING OF DRUGS
3)APPLICATIONS AND USES OF BAYESIAN THEORY IN APPLIED PHARMACOKINETICS:
therapeutic drug monitoring and clinical pharmacokinetics-fifth pharm d notes
Pharmacoeconomics
Pharmacoeconomics is the description and analysis of the costs of drug therapy to health systems and society. It identifies, measures, and compares the costs and outcomes of drug therapies and healthcare programs. Key methods include cost-of-illness, cost-benefit analysis, cost-effectiveness analysis, and cost-utility analysis. These evaluate the economic, clinical, and humanistic impacts of healthcare interventions from various perspectives including patients, providers, payers, and society.
Pharmacoeconomics
The partial pharmacoeconomic evaluations are cost analysis, cost-effectiveness analysis and cost-utility analysis. A comparison of costs and consequences of two alternatives is an example of a full pharmacoeconomic evaluation known as cost-benefit analysis. Therefore, the answer is not a.
b) A cost analysis of a single intervention
c) A comparison of costs per life-year gained for two interventions
d) An estimation of the total costs of a disease to the society
12/10/2018
DEPARTMENT OF PHARMACOLOGY
KMCH COLLEGE OF PHARMACY
42
Which one of the following is an example of a partial
pharmaco-economic evaluation
Pharmacoeconomics 22 feb 2018
This document provides an overview of pharmacoeconomics. It defines key terms like health economics and pharmacoeconomics. It discusses the history and components of pharmacoeconomics. The document outlines different types of costs, perspectives, and methodologies used in pharmacoeconomics like cost-minimization analysis, cost-effectiveness analysis, cost-utility analysis, and cost-benefit analysis. It also discusses the need, applications, and challenges of pharmacoeconomics evaluations.
Hospital Pharmaco-epidemiology
This document discusses hospital pharmacoepidemiology, which involves tracking drugs administered to patients during their hospital stay and systematically recording adverse drug reactions (ADRs). It notes challenges like patients receiving care in multiple departments and from various providers, making complete drug exposure data difficult to obtain. Other challenges include uncertain validity of drug and diagnosis information in medical records. Solutions discussed include intensive hospital surveillance programs and use of integrated inpatient databases. The document also describes a new adverse drug monitoring program aimed at improving patient care and safety through activities like maintaining ADR reports, preventing drug interactions, and educating staff.
introduction to Pharmacoepidemiology
breif notes on what is pharmacoepidemiology, why do we need pharmacoepidemiology, whats is its aim and its main applications, advantages and disadvantages
Pharmacoeconomics
This document discusses the field of pharmacoeconomics. It begins by defining pharmacoeconomics as the scientific discipline concerned with comparing the costs and benefits of drug therapies. It describes how pharmacoeconomics helps optimize health care resource allocation by comparing drug costs and outcomes. The document then outlines several key aspects of pharmacoeconomics including its need, challenges, evaluation methods, and applications. In conclusion, it states that pharmacoeconomics provides a means to quantify pharmaceutical value by balancing costs and outcomes to help inform better healthcare decisions.
Recommended
Pharmacoepidemiology
Pharmacoepidemiology is the study of drug use in populations and the application of epidemiological methods to examine drug effects. It bridges clinical pharmacology and epidemiology. Pharmacoepidemiological research includes evaluating specific drug use, patterns of drug use, and drug-taking behaviors. Studies focus on prescribing trends, medication adherence, drug interactions, and adverse drug reactions. Data sources include medical records, health insurance claims, and national databases. Observational studies measure drug exposure and outcomes without intervention, while interventional studies actively change exposures. Descriptive studies describe disease occurrence, and case reports/series provide initial signals of drug effects. Cross-sectional studies examine drug use at a point in time, while cohort studies follow exposed and
Bayesian theory
Bayesian theory in population pharmacokinetics--
1) INTRODUCTION TO BAYESIAN THEORY
2)BAYESIAN PROBABILITY TO DOSING OF DRUGS
3)APPLICATIONS AND USES OF BAYESIAN THEORY IN APPLIED PHARMACOKINETICS:
therapeutic drug monitoring and clinical pharmacokinetics-fifth pharm d notes
Pharmacoeconomics
Pharmacoeconomics is the description and analysis of the costs of drug therapy to health systems and society. It identifies, measures, and compares the costs and outcomes of drug therapies and healthcare programs. Key methods include cost-of-illness, cost-benefit analysis, cost-effectiveness analysis, and cost-utility analysis. These evaluate the economic, clinical, and humanistic impacts of healthcare interventions from various perspectives including patients, providers, payers, and society.
Pharmacoeconomics
The partial pharmacoeconomic evaluations are cost analysis, cost-effectiveness analysis and cost-utility analysis. A comparison of costs and consequences of two alternatives is an example of a full pharmacoeconomic evaluation known as cost-benefit analysis. Therefore, the answer is not a.
b) A cost analysis of a single intervention
c) A comparison of costs per life-year gained for two interventions
d) An estimation of the total costs of a disease to the society
12/10/2018
DEPARTMENT OF PHARMACOLOGY
KMCH COLLEGE OF PHARMACY
42
Which one of the following is an example of a partial
pharmaco-economic evaluation
Pharmacoeconomics 22 feb 2018
This document provides an overview of pharmacoeconomics. It defines key terms like health economics and pharmacoeconomics. It discusses the history and components of pharmacoeconomics. The document outlines different types of costs, perspectives, and methodologies used in pharmacoeconomics like cost-minimization analysis, cost-effectiveness analysis, cost-utility analysis, and cost-benefit analysis. It also discusses the need, applications, and challenges of pharmacoeconomics evaluations.
Hospital Pharmaco-epidemiology
This document discusses hospital pharmacoepidemiology, which involves tracking drugs administered to patients during their hospital stay and systematically recording adverse drug reactions (ADRs). It notes challenges like patients receiving care in multiple departments and from various providers, making complete drug exposure data difficult to obtain. Other challenges include uncertain validity of drug and diagnosis information in medical records. Solutions discussed include intensive hospital surveillance programs and use of integrated inpatient databases. The document also describes a new adverse drug monitoring program aimed at improving patient care and safety through activities like maintaining ADR reports, preventing drug interactions, and educating staff.
introduction to Pharmacoepidemiology
breif notes on what is pharmacoepidemiology, why do we need pharmacoepidemiology, whats is its aim and its main applications, advantages and disadvantages
Pharmacoeconomics
This document discusses the field of pharmacoeconomics. It begins by defining pharmacoeconomics as the scientific discipline concerned with comparing the costs and benefits of drug therapies. It describes how pharmacoeconomics helps optimize health care resource allocation by comparing drug costs and outcomes. The document then outlines several key aspects of pharmacoeconomics including its need, challenges, evaluation methods, and applications. In conclusion, it states that pharmacoeconomics provides a means to quantify pharmaceutical value by balancing costs and outcomes to help inform better healthcare decisions.
Prescription event monitoring and record linkage system
This document discusses record linkage and its use in pharmacovigilance. Record linkage involves combining records from different data sources that relate to the same individual to create a single longitudinal record. It allows rapid access to a patient's complete medical history across different data sources. This reduces the time needed to study relationships between drug exposure and health outcomes. Challenges include ensuring data quality and completeness when integrating records from various sources.
Studies of vaccine safety (Pharmacoepidemiology) V PharmD
This document discusses selected special applications of pharmacoepidemiology, focusing on studies of vaccine safety. It describes various methods used to monitor vaccine safety, including pre-licensure clinical trials, post-licensure surveillance systems like VAERS, and epidemiological studies. It addresses some methodological challenges in vaccine safety studies like assessing causality, accounting for confounding factors, and identifying rare adverse events. Large automated databases like the Vaccine Safety Datalink are highlighted as a valuable tool for monitoring vaccine safety on a population-level.
Pharmacoeconomics
Pharmacoeconomics evaluates the costs and outcomes of pharmaceutical products and services. It involves choosing a perspective such as patient or payer, identifying costs which can be direct, indirect, or intangible, and identifying outcomes which can be clinical, economic, or humanistic. Common pharmacoeconomic methodologies include cost-consequence analysis, cost-of-illness evaluation, cost-minimization analysis, cost-benefit analysis, cost-effectiveness analysis, and cost-utility analysis. Pharmacoeconomics is important for achieving maximum benefits with limited costs and aids decision making for formularies, policies, and resource allocation.
Clinical trials its types and designs
clinical trials- definition
types of clinical trials
various designs of clinical trials such as observational design and intervention design.
Population pharmacokinetics
This document discusses population pharmacokinetics and analyzing population pharmacokinetic data. It notes that while all humans are alike as a species, there are differences between populations in drug metabolism and responses. These differences are due to genetic variations between racial/ethnic groups. It describes several methods for analyzing population pharmacokinetic data, including NONMEM, which fits concentration data from all subjects simultaneously to estimate population parameters and variances, and standard two-stage methods.
Prescription event monitoring
The document describes Prescription Event Monitoring (PEM), a method of pharmacovigilance that involves collecting information on patient outcomes after being prescribed new medications. PEM was developed in the 1980s in the UK to address limitations of spontaneous adverse event reporting. It involves sending questionnaires to prescribers to obtain follow-up data on patients. Analysis of the data provides incidence rates of adverse events and allows detection of potential safety issues with new drugs. Modified PEM (M-PEM) expands the method to collect additional targeted safety information.
Adaptive method OR dosing with feedback
adaptive methods are doing with feedback in population pharmacokinetics---- clinical pharmacokinetics and therapeutic drug monitoring-- fifth pharm D notes
conversion from INTRAVENOUS TO ORAL DOSING----- design of dosage regimen
conversion from INTRAVENOUS TO ORAL DOSING----- TYPES OF IV TO PO THERAPY CONVERSIONS: MEDICATIONS INCLUDED IN AN IV TO PO CONVERSION PROGRAM: SELECTION OF PATIENTS FOR IV TO PO THERAPY CONVERSION: design of dosage regimen--clinical pharmacokinetics and therapeutic drug monitoring-- fifth pharm D notes
Spontaneous reporting
The spontaneous reporting system is a passive surveillance system where health professionals voluntarily report adverse drug reactions directly to regulatory authorities or pharmaceutical companies. It involves 3 main processes: 1) data acquisition from reported cases, 2) assessment of individual reports and pooled data, and 3) interpretation of signals based on the available data. Initiatives have been taken to widen reporting bases to include pharmacists and nurses. Special focus has been given to reporting reactions related to HIV drugs, pediatric drugs, and herbal products to improve surveillance in underreported areas.
Pharmacoepidemiology
This document discusses pharmacoepidemiology and provides an overview of key concepts:
- Pharmacoepidemiology is defined as the study of the use and effects of drugs in large populations. It combines principles from clinical pharmacology and epidemiology.
- Several study designs can be used including cohort studies, case-control studies, and case reports. Spontaneous adverse event reporting systems are an important source of pharmacoepidemiology data and can generate hypotheses for further investigation.
- Factors that may prompt a pharmacoepidemiological study include regulatory requirements, assessing drug safety in real-world use, and investigating potential issues identified from pre-marketing studies or spontaneous reports.
Study of Vaccine safety
A vaccine is a biological preparation that improves immunity to a particular Disease.
No vaccine is completely safe or completely effective, while all known vaccine adverse events are minor and self limited, some vaccine have been associated with rare but serious health effects.
AUTOMATED DATABASES INTRO.docx
Post marketing studies of drug effects must then generally include at least 10,000 exposed persons in a cohort study, or enroll diseased patients from a population of equivalent size for a case–control study. A study of this size would be 95% certain of observing at least one case of any adverse effect that occurs with an incidence of 3 per 10 000 or greater (see Chapter 3). However, studies this large are expensive and difficult to perform. Yet, these studies often need to be conducted quickly, to address acute and serious regulatory, commercial, and/or public health crises. For all of these reasons, the past two decades have seen a growing use of computerized databases containing medical care data, so called “automated databases,” as potential data sources for pharmacoepidemiology studies.
Genetic polymorphism in drug transport and drug targets.
This document discusses genetic polymorphisms in drug transporters and drug targets. It defines genetic polymorphisms as variations in gene sequences that occur in at least 1% of the general population. The most common type is a single nucleotide polymorphism (SNP) resulting from a change in a single nucleotide base pair. SNPs can be synonymous or non-synonymous, with non-synonymous SNPs potentially altering the protein's structure and function. The document outlines various drug transporters including P-glycoprotein and discusses genetic polymorphisms that can affect their expression and activity levels. It also discusses how genetic polymorphisms in drug metabolizing enzymes and drug receptors can influence drug response and side effects.
Measurement of outcome v5
various measures for the measurement of outcome such as incidence prevalence and other drug us measures are briefly discussed here with suitable examples and equations
INTRODUCTION TO PHARMACOECONOMICS.pptx
Pharmacoeconomics is the one of the evolving area in Clinical pharmacy. Let's go through the history of PE and need of PE in India.
DRUG USE MEASURES.pptx
Different outcome measures in Pharmacoepidemiology includes monetary units, no. of prescriptions, DDDs, PDD, etc.
Pharmacokinetic and pharmacodynamic correlation
Pharmacodynamic models along with relationship between dose, pharmacological effect, duration of activity and elimination half life.
Pharmacovigilance methods
Active Surveillance, Passive Surveillance, Comparative observational methods, stimulated reporting, targeted clinical investigations
Meta analysis and spontaneous reporting
This document discusses meta-analysis, which is a statistical technique for combining the results of multiple independent studies on a topic to obtain an overall estimate of treatment effect. It defines meta-analysis and outlines its key functions and steps, including performing a literature search, establishing inclusion/exclusion criteria, collecting and analyzing data, and formulating conclusions. The document also compares fixed and random effect models of meta-analysis and discusses guidelines and software used in conducting meta-analyses.
Prescription Event Monitoring & Record Linkage Systems
- Prescription-Event Monitoring (PEM) is a non-interventional observational cohort technique used to study the safety of new medications prescribed by general practitioners. It involves collecting data on all clinical events reported by patients after being prescribed a new drug.
- PEM provides clinically useful safety information as it establishes incidence densities for all reported events during treatment with the monitored drug based on data collected from the first 5,000-18,000 prescriptions. This allows for comparisons of event rates before and after drug use.
- While PEM provides nationally representative data on new drugs in real-world settings, it also has disadvantages like an inability to measure compliance or determine use of non-prescription medications.
Deterministic vs stochastic
This document discusses deterministic and stochastic models. Deterministic models have unique outputs for given inputs, while stochastic models incorporate random elements, so the same inputs can produce different outputs. The document provides examples of how each model type is used, including for steady state vs. dynamic processes. It notes that while deterministic models are simpler, stochastic models better account for real-world uncertainties. In nature, deterministic models describe behavior based on known physical laws, while stochastic models are needed to represent random factors and heterogeneity.
Pharmacokinetic study of epileptic patients
epilepsy , pharmacokinetics , study , design , bipharmaceutics , health , medicine , pharmacy , clinical pharmacy , pakistan , lahore , dose dependent clearance , population pk
More Related Content
What's hot
Prescription event monitoring and record linkage system
This document discusses record linkage and its use in pharmacovigilance. Record linkage involves combining records from different data sources that relate to the same individual to create a single longitudinal record. It allows rapid access to a patient's complete medical history across different data sources. This reduces the time needed to study relationships between drug exposure and health outcomes. Challenges include ensuring data quality and completeness when integrating records from various sources.
Studies of vaccine safety (Pharmacoepidemiology) V PharmD
This document discusses selected special applications of pharmacoepidemiology, focusing on studies of vaccine safety. It describes various methods used to monitor vaccine safety, including pre-licensure clinical trials, post-licensure surveillance systems like VAERS, and epidemiological studies. It addresses some methodological challenges in vaccine safety studies like assessing causality, accounting for confounding factors, and identifying rare adverse events. Large automated databases like the Vaccine Safety Datalink are highlighted as a valuable tool for monitoring vaccine safety on a population-level.
Pharmacoeconomics
Pharmacoeconomics evaluates the costs and outcomes of pharmaceutical products and services. It involves choosing a perspective such as patient or payer, identifying costs which can be direct, indirect, or intangible, and identifying outcomes which can be clinical, economic, or humanistic. Common pharmacoeconomic methodologies include cost-consequence analysis, cost-of-illness evaluation, cost-minimization analysis, cost-benefit analysis, cost-effectiveness analysis, and cost-utility analysis. Pharmacoeconomics is important for achieving maximum benefits with limited costs and aids decision making for formularies, policies, and resource allocation.
Clinical trials its types and designs
clinical trials- definition
types of clinical trials
various designs of clinical trials such as observational design and intervention design.
Population pharmacokinetics
This document discusses population pharmacokinetics and analyzing population pharmacokinetic data. It notes that while all humans are alike as a species, there are differences between populations in drug metabolism and responses. These differences are due to genetic variations between racial/ethnic groups. It describes several methods for analyzing population pharmacokinetic data, including NONMEM, which fits concentration data from all subjects simultaneously to estimate population parameters and variances, and standard two-stage methods.
Prescription event monitoring
The document describes Prescription Event Monitoring (PEM), a method of pharmacovigilance that involves collecting information on patient outcomes after being prescribed new medications. PEM was developed in the 1980s in the UK to address limitations of spontaneous adverse event reporting. It involves sending questionnaires to prescribers to obtain follow-up data on patients. Analysis of the data provides incidence rates of adverse events and allows detection of potential safety issues with new drugs. Modified PEM (M-PEM) expands the method to collect additional targeted safety information.
Adaptive method OR dosing with feedback
adaptive methods are doing with feedback in population pharmacokinetics---- clinical pharmacokinetics and therapeutic drug monitoring-- fifth pharm D notes
conversion from INTRAVENOUS TO ORAL DOSING----- design of dosage regimen
conversion from INTRAVENOUS TO ORAL DOSING----- TYPES OF IV TO PO THERAPY CONVERSIONS: MEDICATIONS INCLUDED IN AN IV TO PO CONVERSION PROGRAM: SELECTION OF PATIENTS FOR IV TO PO THERAPY CONVERSION: design of dosage regimen--clinical pharmacokinetics and therapeutic drug monitoring-- fifth pharm D notes
Spontaneous reporting
The spontaneous reporting system is a passive surveillance system where health professionals voluntarily report adverse drug reactions directly to regulatory authorities or pharmaceutical companies. It involves 3 main processes: 1) data acquisition from reported cases, 2) assessment of individual reports and pooled data, and 3) interpretation of signals based on the available data. Initiatives have been taken to widen reporting bases to include pharmacists and nurses. Special focus has been given to reporting reactions related to HIV drugs, pediatric drugs, and herbal products to improve surveillance in underreported areas.
Pharmacoepidemiology
This document discusses pharmacoepidemiology and provides an overview of key concepts:
- Pharmacoepidemiology is defined as the study of the use and effects of drugs in large populations. It combines principles from clinical pharmacology and epidemiology.
- Several study designs can be used including cohort studies, case-control studies, and case reports. Spontaneous adverse event reporting systems are an important source of pharmacoepidemiology data and can generate hypotheses for further investigation.
- Factors that may prompt a pharmacoepidemiological study include regulatory requirements, assessing drug safety in real-world use, and investigating potential issues identified from pre-marketing studies or spontaneous reports.
Study of Vaccine safety
A vaccine is a biological preparation that improves immunity to a particular Disease.
No vaccine is completely safe or completely effective, while all known vaccine adverse events are minor and self limited, some vaccine have been associated with rare but serious health effects.
AUTOMATED DATABASES INTRO.docx
Post marketing studies of drug effects must then generally include at least 10,000 exposed persons in a cohort study, or enroll diseased patients from a population of equivalent size for a case–control study. A study of this size would be 95% certain of observing at least one case of any adverse effect that occurs with an incidence of 3 per 10 000 or greater (see Chapter 3). However, studies this large are expensive and difficult to perform. Yet, these studies often need to be conducted quickly, to address acute and serious regulatory, commercial, and/or public health crises. For all of these reasons, the past two decades have seen a growing use of computerized databases containing medical care data, so called “automated databases,” as potential data sources for pharmacoepidemiology studies.
Genetic polymorphism in drug transport and drug targets.
This document discusses genetic polymorphisms in drug transporters and drug targets. It defines genetic polymorphisms as variations in gene sequences that occur in at least 1% of the general population. The most common type is a single nucleotide polymorphism (SNP) resulting from a change in a single nucleotide base pair. SNPs can be synonymous or non-synonymous, with non-synonymous SNPs potentially altering the protein's structure and function. The document outlines various drug transporters including P-glycoprotein and discusses genetic polymorphisms that can affect their expression and activity levels. It also discusses how genetic polymorphisms in drug metabolizing enzymes and drug receptors can influence drug response and side effects.
Measurement of outcome v5
various measures for the measurement of outcome such as incidence prevalence and other drug us measures are briefly discussed here with suitable examples and equations
INTRODUCTION TO PHARMACOECONOMICS.pptx
Pharmacoeconomics is the one of the evolving area in Clinical pharmacy. Let's go through the history of PE and need of PE in India.
DRUG USE MEASURES.pptx
Different outcome measures in Pharmacoepidemiology includes monetary units, no. of prescriptions, DDDs, PDD, etc.
Pharmacokinetic and pharmacodynamic correlation
Pharmacodynamic models along with relationship between dose, pharmacological effect, duration of activity and elimination half life.
Pharmacovigilance methods
Active Surveillance, Passive Surveillance, Comparative observational methods, stimulated reporting, targeted clinical investigations
Meta analysis and spontaneous reporting
This document discusses meta-analysis, which is a statistical technique for combining the results of multiple independent studies on a topic to obtain an overall estimate of treatment effect. It defines meta-analysis and outlines its key functions and steps, including performing a literature search, establishing inclusion/exclusion criteria, collecting and analyzing data, and formulating conclusions. The document also compares fixed and random effect models of meta-analysis and discusses guidelines and software used in conducting meta-analyses.
Prescription Event Monitoring & Record Linkage Systems
- Prescription-Event Monitoring (PEM) is a non-interventional observational cohort technique used to study the safety of new medications prescribed by general practitioners. It involves collecting data on all clinical events reported by patients after being prescribed a new drug.
- PEM provides clinically useful safety information as it establishes incidence densities for all reported events during treatment with the monitored drug based on data collected from the first 5,000-18,000 prescriptions. This allows for comparisons of event rates before and after drug use.
- While PEM provides nationally representative data on new drugs in real-world settings, it also has disadvantages like an inability to measure compliance or determine use of non-prescription medications.
What's hot (20)
Prescription event monitoring and record linkage system
Prescription event monitoring and record linkage system
Studies of vaccine safety (Pharmacoepidemiology) V PharmD
Studies of vaccine safety (Pharmacoepidemiology) V PharmD
conversion from INTRAVENOUS TO ORAL DOSING----- design of dosage regimen
conversion from INTRAVENOUS TO ORAL DOSING----- design of dosage regimen
Genetic polymorphism in drug transport and drug targets.
Genetic polymorphism in drug transport and drug targets.
Prescription Event Monitoring & Record Linkage Systems
Prescription Event Monitoring & Record Linkage Systems
Similar to Markov model
Deterministic vs stochastic
This document discusses deterministic and stochastic models. Deterministic models have unique outputs for given inputs, while stochastic models incorporate random elements, so the same inputs can produce different outputs. The document provides examples of how each model type is used, including for steady state vs. dynamic processes. It notes that while deterministic models are simpler, stochastic models better account for real-world uncertainties. In nature, deterministic models describe behavior based on known physical laws, while stochastic models are needed to represent random factors and heterogeneity.
Pharmacokinetic study of epileptic patients
epilepsy , pharmacokinetics , study , design , bipharmaceutics , health , medicine , pharmacy , clinical pharmacy , pakistan , lahore , dose dependent clearance , population pk
Bayesian Phylogenetics - Systematics.pptx
This document provides an introduction to Bayesian phylogenetic analysis for empirical biologists. It explains that Bayesian phylogenetic models were introduced in the 1990s and have revolutionized data analysis by using powerful models and user-friendly computer programs. The purpose of the paper is to explain basic Bayesian statistical concepts like priors, likelihoods, Markov chain Monte Carlo algorithms, and assessing convergence and mixing to help biologists use Bayesian phylogenetic programs. It covers topics like choosing appropriate priors, types of data that can be used, how MCMC sampling works, and diagnosing convergence, burn-in and mixing. Bayesian phylogenetics has grown due to available models and programs and is commonly used for tasks like divergence time estimation, species tree estimation, and species delimitation.
MM - KBAC: Using mixed models to adjust for population structure in a rare-va...
Confounding from population structure, extended families and inbreeding can be a significant issue for burden and kernel association tests on rare variants from next generation DNA sequencing. An obvious solution is to combine the power of a mixed model regression analysis with the ability to assess the rare variant burden using methods such as KBAC or CMC. Recent approaches have adjusted burden and kernel tests using linear regression models; this method adjusts for the relatedness of samples and includes that directly into a logistic regression model.
This webcast will focus on the details of bringing Mixed Model Regression and KBAC together, including: deriving an optimal logistic mixed model algorithm for calculating the reduced model score, how the kinship or random effects matrix should be specified, and how it all comes together into one algorithm. Results from applying the method to variants from the 1000 Genomes project will also be presented and compared to famSKAT.
Data Science Project: Advancements in Fetal Health Classification
Explore the latest techniques and technologies used in classifying fetal health, from traditional methods to cutting-edge AI approaches. Understand the importance of accurate classification for prenatal care and fetal well-being. Join us to delve into this critical aspect of healthcare. visit https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/ for more data science insights
Ddp(disease drug prediction using ml)
This document describes a disease and drug prediction system using machine learning. It introduces using medical decision support systems to help doctors make accurate diagnoses by considering various patient factors. It then discusses using k-means clustering and logistic regression algorithms to analyze symptom data and predict diseases. The system is able to predict diseases like diabetes and hypertension based on entered symptoms and recommend drugs for the predicted conditions. It provides examples of predicting hypertension using logistic regression and SVM for a patient with chest pain and dizziness.
Or ppt,new
This document discusses methods of simulation and Monte Carlo simulation. It is authored by a group including Roy Thomas, Sam Scaria, Sonu Sebastian, and others. The document defines simulation as using a model of a real system to conduct experiments on a computer in order to describe, explain, and predict the behavior of the real system. Monte Carlo simulation is described as using probability and sampling to solve complicated equations. Key steps of Monte Carlo simulation include drawing a flow diagram, determining variable distributions, selecting random numbers, and applying mathematical functions to obtain solutions. Examples of applications include queuing problems, inventory problems, and risk analysis.
Correcting bias and variation in small RNA sequencing for optimal (microRNA) ...
Correcting bias and variation in small RNA sequencing for optimal (microRNA) ...Christos Argyropoulos
Presentation given about the Generalized Additive Model Location, Scale and Shape (GAMLSS) methodology for the analysis of small RNA sequencing data and the potential of microRNAs as biomarkers for kidney and cardiometabolic diseasesTesis_Eugenia_Koblents
This document summarizes Eugenia Koblents Lapteva's doctoral thesis on nonlinear population Monte Carlo methods for Bayesian inference. The thesis addresses the problem of approximating posterior probability distributions and associated integrals using Monte Carlo methods like population Monte Carlo. It proposes new nonlinear population Monte Carlo algorithms to address the weight degeneracy problem in high dimensions. These include a basic nonlinear PMC with a Gaussian proposal, an adaptive nonlinear mixture PMC for multimodal targets, and a particle nonlinear PMC for state space models. The thesis analyzes the convergence of the nonlinear importance sampling technique and provides numerical tests demonstrating the performance of the proposed algorithms on simulation examples and applications like stochastic kinetic models and alpha-stable distributions.
Multicollinearity1
This document discusses multicollinearity in regression analysis. It defines multicollinearity as a near linear relationship between predictor variables, which violates an assumption of classical linear regression. It provides an example of multicollinearity between product price and competitor prices. The effects of multicollinearity include indeterminate regression coefficients and infinite variance and covariance of coefficients when multicollinearity is perfect. Sources of multicollinearity include the data collection method, constraints in the population, model specification, and having more predictors than observations.
Application of stochastic modelling in bioinformatics
This document discusses stochastic modeling and its applications in bioinformatics. It defines stochastic models and processes, and explains how they differ from deterministic models in accounting for uncertainty. Some examples of stochastic modeling approaches described include stochastic process algebra using tools like π-calculus and Petri nets, Markov models including Markov chains and hidden Markov models, and BioAmbients for modeling biological systems with mobile boundaries. The document argues that stochastic methods are better suited than deterministic ones for describing complex and dynamically evolving biological systems.
Probability Models for Estimating Haplotype Frequencies and Bayesian Survival...
Probability Models for Estimating Haplotype Frequencies and Bayesian Survival...Université de Dschang
M. Kum Cletus Kwa a soutenu une thèse de Doctorat/Phd en mathématiques ce 14 juin 2016 à l'Université de Dschang. Le jury lui a décerné à l'issue des échanges la mention très honorable. Similar to Markov model (12)
MM - KBAC: Using mixed models to adjust for population structure in a rare-va...
MM - KBAC: Using mixed models to adjust for population structure in a rare-va...
Data Science Project: Advancements in Fetal Health Classification
Data Science Project: Advancements in Fetal Health Classification
Correcting bias and variation in small RNA sequencing for optimal (microRNA) ...
Correcting bias and variation in small RNA sequencing for optimal (microRNA) ...
Application of stochastic modelling in bioinformatics
Application of stochastic modelling in bioinformatics
Probability Models for Estimating Haplotype Frequencies and Bayesian Survival...
Probability Models for Estimating Haplotype Frequencies and Bayesian Survival...
More from Nouran Hamza, MSc, PgDPH
Cluster dendrogram for rapd pcr gram negative bacteria
This document contains R output from a dendrogram analysis conducted by Dr. Kawthar and published on LinkedIn by Nouran Hamza on April 8, 2019. The output is from analyzing a file related to Dr. Kawthar's dendrogram work.
Anova , ANCOVA, MANOVA and MANCOVA for the very beginners
1) The document describes four scenarios analyzing data from clinical trials using ANOVA, ANCOVA, MANOVA, and MANCOVA. The primary endpoints were achieving normal fasting blood sugar and HbA1c levels.
2) In the first scenario, ANOVA was used to assess efficacy of single and double dosing of an oral hypoglycemic drug. Treatment had a significant effect on fasting blood sugar.
3) In the second scenario, a two-factor ANOVA assessed dosing and vitamin B supplementation, finding a significant effect of treatment but not vitamin B on fasting blood sugar.
Disaster Epidemiology - breif overview
Despite that disasters are usually named after the causing phenomenon or event; a disaster by itself is not the phenomenon or event. Unless an earthquake strikes a populated area of weak physical constructions, it is not described as a disaster. Also, the definition of a ‘disaster’ depends to a great extent on who is defining. (1) On another hand, man-made disasters can be divided into four categories: armed conflict and civil strife, technological disasters, disasters that occur in human settlements and severe accidents. (2)
Here, with the fact that deaths following disasters are preventable, and also, most subjects affected by them do not die. A standardized and feasible incident management system along with Standard Operating Procedures are essential for linking site operations to health-facility based care during an occurring disaster. (3)Not to mention the important rule of multi-disciplinary efforts in the planning, organization, coordination and implementation of all measures to mitigate/prevent, prepare for, respond to and recover from disaster events.(4)
Disaster epidemiology nouran
Despite that disasters are usually named after the causing phenomenon or event; a disaster by itself is not the phenomenon or event. Unless an earthquake strikes a populated area of weak physical constructions, it is not described as a disaster. Also, the definition of a ‘disaster’ depends to a great extent on who is defining. (1) On another hand, man-made disasters can be divided into four categories: armed conflict and civil strife, technological disasters, disasters that occur in human settlements and severe accidents. (2)
Here, with the fact that deaths following disasters are preventable, and also, most subjects affected by them do not die. A standardized and feasible incident management system along with Standard Operating Procedures are essential for linking site operations to health-facility based care during an occurring disaster. (3)Not to mention the important rule of multi-disciplinary efforts in the planning, organization, coordination and implementation of all measures to mitigate/prevent, prepare for, respond to and recover from disaster events.(4)
Overview on crossover trials Statistical illustration “SPSS” Continues outcome
Overview on crossover trials Statistical illustration “SPSS” Continues outcomeNouran Hamza, MSc, PgDPH
crossover design
is a repeated/longitudinal measurements design.
|
Patients (experimental units) cross over from one treatment to another during the trial course.
|
In contrast to a parallel design where patients are randomized to a treatment and remain on that treatment throughout the trial durationA Brief Overview on the Pharmacoeconomics Course
This document provides an overview of value-based healthcare and pharmacoeconomics. It defines value-based healthcare as putting patient values at the center of care by focusing on outcomes that are important to patients. It also describes types of economic evaluation used in pharmacoeconomics like cost-minimization analysis, cost-utility analysis, cost-effectiveness analysis, and cost-benefit analysis. Examples of using decision trees and Markov models for financial evaluations of programs are also briefly mentioned.
Overview on randomized control trial
Randomized controlled trials (RCTs) aim to reduce bias when testing new treatments by randomly allocating participants to either a treatment group or a control group. Random allocation means each participant has an equal probability of being assigned to either group. RCTs can be classified based on their design, such as parallel-group trials where each participant receives either the treatment or control. Blinding of participants and researchers is important to reduce biases. Allocation concealment, such as using opaque sealed envelopes, also helps reduce biases in RCT outcomes.
Critical appraisal example systematic review and meta-analysis
This document provides guidance on appraising a systematic review using a checklist. It addresses key questions like whether the systematic review had a clear research question, performed a comprehensive literature search, explicitly stated inclusion/exclusion criteria, assessed study quality, stated how results were combined statistically, reported absolute numbers and summary statistics, and discussed clinical relevance. The document notes that important details on these aspects can typically be found in sections like the Methods, Results, and Conclusion sections of a systematic review. It aims to help reviewers appraise important methodological aspects of a systematic review.
Brief overview on meta analysis
Definition
Steps
Appreciate the benefits and limitations
Some basic concepts and plots ( forest, funnel, bubble plots)
Useful resources.
Anova post hoc
ANOVA tests determine if there are differences in group means but do not specify which pairs differ. Post hoc tests identify the pairs of means that are significantly different. Tukey's HSD test and Fisher's LSD test can be used when variances are equal between groups. The Games Howell test is recommended when variances are not equal.
Introduction to Research Methodology
This document provides an overview of key aspects of the research process, including identifying a research problem, reviewing relevant literature, specifying a research purpose, collecting and analyzing data, and reporting results. It discusses different types of epidemiological study designs like cross-sectional studies, case-control studies, cohort studies, and their strengths and limitations. Literature reviews are described as assessing previous research on a topic to identify knowledge gaps and questions. The importance of a clear and specific research purpose is highlighted. Methods of data collection and presentation like tables, bar charts, histograms and graphs are also covered.
More from Nouran Hamza, MSc, PgDPH (11)
Cluster dendrogram for rapd pcr gram negative bacteria
Cluster dendrogram for rapd pcr gram negative bacteria
Anova , ANCOVA, MANOVA and MANCOVA for the very beginners
Anova , ANCOVA, MANOVA and MANCOVA for the very beginners
Overview on crossover trials Statistical illustration “SPSS” Continues outcome
Overview on crossover trials Statistical illustration “SPSS” Continues outcome
Critical appraisal example systematic review and meta-analysis
Critical appraisal example systematic review and meta-analysis
Recently uploaded
NVBDCP.pptx Nation vector borne disease control program
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
Top Effective Soaps for Fungal Skin Infections in India
Swisschem Dermacare has mentioned the List of The Best Antifungal Soap In India 2022. All of these soaps are trusted by various Dermatology Experts.
Top-Vitamin-Supplement-Brands-in-India List
Swisschem Dermacare provides the Top 10 Vitamin Supplement Brands in India. To know more about us give us call at our official number
#cALL# #gIRLS# In Dehradun ꧁❤8107221448❤꧂#cALL# #gIRLS# Service In Dehradun W...
#cALL# #gIRLS# In Dehradun ꧁❤8107221448❤꧂#cALL# #gIRLS# Service In Dehradun W...chandankumarsmartiso
#cALL# #gIRLS# In Dehradun ꧁❤8107221448❤꧂#cALL# #gIRLS# Service In Dehradun Women Seeking Service
TEST BANK For Community Health Nursing A Canadian Perspective, 5th Edition by...
TEST BANK For Community Health Nursing A Canadian Perspective, 5th Edition by Stamler, Verified Chapters 1 - 33, Complete Newest Version Community Health Nursing A Canadian Perspective, 5th Edition by Stamler, Verified Chapters 1 - 33, Complete Newest Version Community Health Nursing A Canadian Perspective, 5th Edition by Stamler Community Health Nursing A Canadian Perspective, 5th Edition TEST BANK by Stamler Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Pdf Chapters Download Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Pdf Download Stuvia Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Study Guide Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Ebook Download Stuvia Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Questions and Answers Quizlet Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Studocu Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Quizlet Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Stuvia Community Health Nursing A Canadian Perspective, 5th Edition Pdf Chapters Download Community Health Nursing A Canadian Perspective, 5th Edition Pdf Download Course Hero Community Health Nursing A Canadian Perspective, 5th Edition Answers Quizlet Community Health Nursing A Canadian Perspective, 5th Edition Ebook Download Course hero Community Health Nursing A Canadian Perspective, 5th Edition Questions and Answers Community Health Nursing A Canadian Perspective, 5th Edition Studocu Community Health Nursing A Canadian Perspective, 5th Edition Quizlet Community Health Nursing A Canadian Perspective, 5th Edition Stuvia Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Pdf Chapters Download Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Pdf Download Stuvia Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Study Guide Questions and Answers Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Ebook Download Stuvia Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Questions Quizlet Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Studocu Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Quizlet Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Stuvia
Dehradun #ℂall #gIRLS Oyo Hotel 8107221448 #ℂall #gIRL in Dehradun
Dehradun #ℂall #gIRLS Oyo Hotel 8107221448 #ℂall #gIRL in Dehradun
micro teaching on communication m.sc nursing.pdf
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
REGULATION FOR COMBINATION PRODUCTS AND MEDICAL DEVICES.pptx
It includes regulation of combination products and medical devices. FDA and industry liaisons.
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
Efficacy of Avartana Sneha in Ayurveda
Avartana Sneha is a unique method of Preparation of Sneha Kalpana in Ayurveda, mainly it is indicated for the Vataja rogas.
How STIs Influence the Development of Pelvic Inflammatory Disease.pptx
STIs may cause PID. For the both disease, herbal medicine Fuyan Pill can be a solution.
Physiology of Chemical Sensation of smell.pdf
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Novas diretrizes da OMS para os cuidados perinatais de mais qualidadeProf. Marcus Renato de Carvalho
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Recently uploaded (20)
NVBDCP.pptx Nation vector borne disease control program
NVBDCP.pptx Nation vector borne disease control program
Top Effective Soaps for Fungal Skin Infections in India
Top Effective Soaps for Fungal Skin Infections in India
#cALL# #gIRLS# In Dehradun ꧁❤8107221448❤꧂#cALL# #gIRLS# Service In Dehradun W...
#cALL# #gIRLS# In Dehradun ꧁❤8107221448❤꧂#cALL# #gIRLS# Service In Dehradun W...
TEST BANK For Community Health Nursing A Canadian Perspective, 5th Edition by...
TEST BANK For Community Health Nursing A Canadian Perspective, 5th Edition by...
Dehradun #ℂall #gIRLS Oyo Hotel 8107221448 #ℂall #gIRL in Dehradun
Dehradun #ℂall #gIRLS Oyo Hotel 8107221448 #ℂall #gIRL in Dehradun
REGULATION FOR COMBINATION PRODUCTS AND MEDICAL DEVICES.pptx
REGULATION FOR COMBINATION PRODUCTS AND MEDICAL DEVICES.pptx
CHEMOTHERAPY_RDP_CHAPTER 6_Anti Malarial Drugs.pdf
CHEMOTHERAPY_RDP_CHAPTER 6_Anti Malarial Drugs.pdf
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...
How STIs Influence the Development of Pelvic Inflammatory Disease.pptx
How STIs Influence the Development of Pelvic Inflammatory Disease.pptx
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Markov model
- 1. Markov model Pharmacoeconomics Nouran Hamza, B Pharm, MSc Freelance biostatistician
- 2. What is a Markov Model? Mathematicalmodelingtechnique,derivedfrommatrixalgebra,thatdescribesthetransitionsacohortofpatientsmakeamonganumberof mutuallyexclusiveandexhaustivehealthstate duringaseriesofshortintervalsorcycles
- 3. Properties of a Markov Model • Patientisalwaysinoneofafinitenumberofhealthstates • Eventsaremodeledastransitionsfromonestatetoanother • Contributionofutilitytooverallprognosisdependsonlengthoftimespentinhealthstates • Duringeachcycle,thepatientmaymakeatransitionfromonestatetoanother
- 4. Example Please note that in Markov model we use the probability ( convert rates or percent to probability
- 11. Please note that all the previous numbers are in probability terms if the problem state a number of population , or a specific cost, do all the pervious steps + multiplying by the stated population or cost
- 12. Construct a Markov model for a cohort of 5000 subject using the following