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license: cc-by-nc-4.0 |
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tags: |
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- emrbots |
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- healthcare |
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- emr |
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- ehr |
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- rwe |
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- rwd |
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- observational |
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- virtual |
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- simulation |
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--- |
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### A 10,000-patient database that contains in total 10,000 patients, 36,143 admissions, and 10,726,505 lab observations. ### |
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### Created by: Uri Kartoun, PhD, Copyright 2014 (https://urikartoun.com/). ### |
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############################################################################################################################# |
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**The Problem:** It is difficult and expensive to access Electronic Medical Records (EMRs) due to privacy concerns and technical problems. I am a student or a researcher working at a university that does not have yet an access to EMR system and I am interested in evaluating machine learning algorithms. Tedious bureaucracy. I am teaching a computer science course and I wish to let my 150 students to experiment with electronic medical records. Not possible due to privacy issues. I am in a process of founding a company focused on developing a new EMR management platform and I want to demonstrate to a venture capital company and to potential customers the ability of my product to handle big data. Current simulated medical databases are limited and are hard to configure. |
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**The Solution:** A database of artificial patients. The data is generated according to pre-defined criteria and is not based on any human data. The database contains the same characteristics that exist in a real medical database such as patients admission details, demographics, socioeconomic details, labs, medications, etc. The database is customizable. For example, it is possible to generate a population of 100,000 patients of which 60% are male, 40% are African American, 15% are diabetic, specific lab range distributions can be set, etc. The number of records can range from several thousands to millions, depending on the desired configuration. |
