Welcome to
Leumit Start introduces Pay & Research, the game-changer in EMR preliminary data access. Get started with your POC in just two working days with our revolutionary platform.
Obtaining access to medical data is a time-consuming and expensive process. Pay & Research changes everything about gaining access to EMR data!
Changing the Rules
of Engagement
Reduced Costs
Accessing medical data for research and development can be expensive.
Our innovative engagement model enables us to provide you with a significantly more affordable access to our comprehensive synthetic medical records for €2,500 + VAT.
Reduced Time
The process of signing a data sharing agreement might take months.
However, in Pay & Research, our uniform and simple agreement, streamlines the typically long legal procedures for such collaborations, accomplishing it within just two working days.
Reduced Bureaucracy
Signing collaboration agreement and obtaining IRB approval (Helsinki) consist of a lot of paper-work.
By signing a generic agreement digitally and using synthetic data, we reduced the bureaucracy to a minimum.
01
Register
Explore and review the Data Description section to ensure it contains the data you’re looking for. Then, click the Register button.
02
Sign & Pay
We will call you to schedule a video meeting to verify your identity. After that, you will need to sign the Terms of Use Agreement and complete the payment.
03
Get Access
You will receive guidance on connecting to the Virtual Lab Room, where you can proceed to install your analysis tools. Once the installation is complete, we will upload the synthetic dataset to your Lab Room, enabling you to begin your work.
About the
Data set
The data intended for sharing is a “one size fits all” synthetic data, based on real-world, raw data from Leumit’s EMR.
The synthetic data represents patients’ information from 2003 until June 2018 but due to the synthesis process the data will be spread beyond this range (for computational reasons only).
The data contains information on approximately 130,000 synthetic patients in a distribution close to reality in Leumit. The data however, does not claim to be a full representation of the population. For a more in-depth explanation, please refer to the attached file below.
This cohort is randomly selected and is a representative sample of the population in terms of demographic, medical condition and other aspects. The synthetic data is structured in such a way that it simulates the statistical behavior of the real population and enables a reliable analysis and a very close approximation to the real-world data.
The data will be accessible in CSV format files and contains the following types of information:
- Customer Details: Gender, demographics, customer status, etc.
- Provider’s Treatments: Data regarding hospitalizations, ERs, and other treatments (treatment code, date, etc.) as reported by external providers.
- Physician’s/Nurse’s Procedures: Procedures performed by the Physicians/ nurses in the HMO clinics (Procedure code, date, etc.).
- Medication Consumption: Data regarding medication consumption (Date, Drug ATC7 code, Quantity, etc.).
- Medication Prescriptions: Data regarding prescriptions for medications given by the Physician (Date, Drug ATC7 code, Dose, etc.).
- Physicians’ Details: License number (deidentified token), specialty.
- HMO Clinic Visits: Physician license (deidentified token), Customer token, date & time.
- Diagnosis – HMO: Diagnosis given by the HMO’s physicians encoded by ICD9 code (Physician license deidentified token), Customer token, date & time, ICD9, status, etc.).
- Diagnosis – Hospitals: Diagnosis given by the hospital’s physicians encoded by ICD9 code (Hospital, Date, ICD9) (data from 2007, gradually added).
- Medical Measures: Height, weight, heartbeat, blood pressure, etc.
- Sensitivities: Medications, allergies, food, etc. (Date, type, description, status, etc.).
- Laboratory Tests: Demands, Orders, Results (Date, type, name, Physician license (deidentified token), results, etc.).
- Medical Assessments: Data regarding estimations/ Assessments performed mainly by nurses (Date, assessment code, Nurse details, result, question & answer code, etc.
- Risk Factors: Such as smoking, drinking, drugs, etc. (risk code, date, value, etc.).
- Insurance Details: Insurance type, date start/end
In the table below, we have gathered data on the prevalence of a few common clinical conditions in the dataset that are often subjects of research (based on documented diagnoses). For detailed information on these conditions and the diagnoses that were included.
Diagnosis | Cohort size |
|---|---|
Colorectal cancer | 561 |
Lung cancer | 909 |
Breast cancer | 1075 |
Skin cancer | 2636 |
Diabetes | 10236 |
CKD | 2052 |
COPD | 3488 |
Asthma | 29258 |
Stroke | 1817 |
Dementia syndromes | 2146
|
NAFLD | 2784 |
Cardiovascular | 10092 |
Limitation in the dataset:
- The data does not contain any prices and costs.
- The data does not contain the names of locations (towns, cities etc.), providers and hospitals.
- Very rare occurrences are not fully reflected in the synthetic data.
- The synthetic data is not suitable for research related to seasonality.
- Medication names are based on the generic name and not the commercial name.
For more information about the synthetic data, please read carefully these two files:
MDClone – Leumit Synthetic Data solution
Leumit – The complete Data Catalog
Frequently Asked Questions
Unlock Instant Access to the Data You Need
Start your medical research journey today! Leave your name and email below to begin the process digitally. We’ll get back to you within two working days, answer your questions, proceed to signing the agreement, and complete the payment.
Pay & Research
Leumit Start is Leumit Health Services innovation and digital health unit. We aim to encourage Innovation in the HealthTech industry by supplying responsible and reasonable access to de-identified high quality clinical data, clinical consultancy, clinical trials and more. Leumit Start operates under Leumit La’atid Ltd.
Visit: www.innovation.leumit.co.il