Sharing data without sharing data

Last modified by Grace Scorrar on 2018/02/12 17:08

In this webinar we will discuss the benefits of creating a Common Data Model (CDM) across a network of healthcare organisations. By arranging data into a standard structure and by using privacy preserving methods, each member of the network can benefit from augmented sample sizes and depth of data to increase the possibilities for data driven decision making. The presentation will draw from our experience working with the PCORNET research network which includes a CDM built using Electronic Health Record data. 

In this webinar we will discuss the benefits of creating a Common Data Model (CDM) across a network of healthcare organisations. By arranging data into a standard structure and by using privacy preserving methods, each member of the network can benefit from augmented sample sizes and depth of data to increase the possibilities for data driven decision making. The presentation will draw from our experience working with the PCORNET research network which includes a CDM built using Electronic Health Record data. 

Click here to view the presentation. 

ErickMoyneur.jpgErick Moyneur
Erick supports many major firms and pharmaceutical companies in developing their products’ market characterization, buying process and value propositions. Recognizing his skill, organizations look to him to meet their immediate needs for data analytics. He also helps them with their cost-benefit, stress testing, event study and market share analysis needs. Erick has also been involved in signal detection analyses (hypothesis-generating and hypothesis-testing frameworks) using public, private and commercially available data sources and in distributed research networks (DRNs). He has used economic modeling, forecast models and discrete choice analyses to help resolve economic disputes. He has created, benchmarked, implemented and provided training on optimization algorithms. These have included user-friendly applications for high-tech and pharmaceutical firms and electric utility companies as strategy decision support tools for supply chain management issues. Erick holds a BSc in Mathematics and a M.A. in Economics with a specialization in econometrics and quantitative modeling.

EricGravel.jpgEric Gravel
An econometrics, economics and finance expert, Eric puts his analytical and econometric skills to good use in retail, credit risk management, litigation damage assessment, pharmacovigilance and pharmacoeconomics. Eric and his team also made the most of his analytical and SAS programming skills developing several tools used by the Food and Drug Administration’s Mini-Sentinel distributed data network. In the last 10 years, Eric developed several credit risk assessment models for the credit portfolios of companies and individuals. He is the co-author of scientific articles on evaluating investments using real options analysis, pharmacovigilance, the evaluation of public projects and the discount rate. With a strong quantitative background, Eric holds a MSc in Finance and M.A. in Economics from Université Laval.

Erick Moyneur: Erick supports many major firms and pharmaceutical companies in developing their products’ market characterization, buying process and value propositions. Recognizing his skill, organizations look to him to meet their immediate needs for data analytics. He also helps them with their cost-benefit, stress testing, event study and market share analysis needs. Erick has also been involved in signal detection analyses (hypothesis-generating and hypothesis-testing frameworks) using public, private and commercially available data sources and in distributed research networks (DRNs). He has used economic modeling, forecast models and discrete choice analyses to help resolve economic disputes. He has created, benchmarked, implemented and provided training on optimization algorithms. These have included user-friendly applications for high-tech and pharmaceutical firms and electric utility companies as strategy decision support tools for supply chain management issues. Erick holds a BSc in Mathematics and a M.A. in Economics with a specialization in econometrics and quantitative modeling.

 

Eric Gravel: An econometrics, economics and finance expert, Eric puts his analytical and econometric skills to good use in retail, credit risk management, litigation damage assessment, pharmacovigilance and pharmacoeconomics. Eric and his team also made the most of his analytical and SAS programming skills developing several tools used by the Food and Drug Administration’s Mini-Sentinel distributed data network. In the last 10 years, Eric developed several credit risk assessment models for the credit portfolios of companies and individuals. He is the co-author of scientific articles on evaluating investments using real options analysis, pharmacovigilance, the evaluation of public projects and the discount rate. With a strong quantitative background, Eric holds a MSc in Finance and M.A. in Economics from Université Laval.

Erick Moyneur: Erick supports many major firms and pharmaceutical companies in developing their products’ market characterization, buying process and value propositions. Recognizing his skill, organizations look to him to meet their immediate needs for data analytics. He also helps them with their cost-benefit, stress testing, event study and market share analysis needs. Erick has also been involved in signal detection analyses (hypothesis-generating and hypothesis-testing frameworks) using public, private and commercially available data sources and in distributed research networks (DRNs). He has used economic modeling, forecast models and discrete choice analyses to help resolve economic disputes. He has created, benchmarked, implemented and provided training on optimization algorithms. These have included user-friendly applications for high-tech and pharmaceutical firms and electric utility companies as strategy decision support tools for supply chain management issues. Erick holds a BSc in Mathematics and a M.A. in Economics with a specialization in econometrics and quantitative modeling.

 

Eric Gravel: An econometrics, economics and finance expert, Eric puts his analytical and econometric skills to good use in retail, credit risk management, litigation damage assessment, pharmacovigilance and pharmacoeconomics. Eric and his team also made the most of his analytical and SAS programming skills developing several tools used by the Food and Drug Administration’s Mini-Sentinel distributed data network. In the last 10 years, Eric developed several credit risk assessment models for the credit portfolios of companies and individuals. He is the co-author of scientific articles on evaluating investments using real options analysis, pharmacovigilance, the evaluation of public projects and the discount rate. With a strong quantitative background, Eric holds a MSc in Finance and M.A. in Economics from Université Laval.

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Created by Grace Scorrar on 2017/12/19 21:47