Common Data Models to Improve Canadian Healthcare

By Andrew Tomayer, CPDSN Data Analyst, CAPHC

Data, in every shape and form, is a constant in our daily lives. We have come to know that if we want to show where we want to go, we must measure our progress so far. This measure of progress must be clear, consistent and as accurate as possible or else it becomes directionless numbers.

Data can help us understand our everyday lives, and in the healthcare system it can be used to improve processes and determine better care. To collect health data that is consistent and comparable within and between datasets, a common standardized language is required.

In our ever-advancing, computer-literate world, many data elements are collected across the continuum of healthcare. Similar data elements between multiple sites can be collected through numerous different methods. The Common Data Model (CDM) is then helpful so all the data elements are collected in the same format.

Join Erick Moyneur and Eric Gravel in this enticing webinar session about the impact of a Common Data Model and how it leads to more efficient analysis among the various players in the healthcare system, including high-level stakeholders, decision support units and data analysts, researchers or other healthcare professionals that are interested in understanding more about their healthcare facility or patient population. A demonstration will be provided on how the CDM leads to less work for the clinicians and administrators on data cleaning and data transformation processes. A CDM embraces the data revolution and makes a difference in health information management by assuring constant and comparable information is available at one’s fingertips.

To learn more about a Common Data Model that is used in healthcare research, how it is created, how it can securely mask data for healthcare professionals and the benefits it can provide to improving healthcare knowledge, register for the CAPHC Presents! Webinar:

Sharing Data without Sharing Data
Wednesday January 31, 2018, 11:00-12:00 EST.
Presentation by Erick Moyneur and Eric Gravel of StatLog.