We will make our Agile Authoring development platform available to researchers need to collect data through a sophisticated algorithmic decision tree. The license will be free for researchers. Commercial uses will require license fees. The data collected will be yours. Let me know if you want to learn more. [email protected]
Agile Author
Starting with existing protocols, best practices and checklists, the Agile Author create electronic versions, called templates. Behavioral logic for decision support, data validation, error checking, and inclusion of dynamic reference material is added through visual commands.
Task: Protocol and data requirement standards development
User: Knowledge Engineer. This is the person who sets the standards for a defined group of users.
To collect data for mTuitive synoptic reporting, you should first identify the specific variables and data elements that you want to collect. Synoptic reporting is designed to capture structured data in a standardized format, so it is important to define a set of data elements that are relevant to the clinical scenario or research question that you are studying.
Once you have identified the data elements that you want to collect, you can design a data collection form or template that includes these elements in a standardized format. The mTuitive synoptic reporting system provides a set of standard templates that can be used for a variety of clinical scenarios, but you may need to customize these templates to meet your specific needs.
When designing your data collection form, you should consider the following best practices for synoptic reporting:
- Use standardized language: Use consistent and unambiguous terminology to describe each data element. This will ensure that the data is easy to understand and analyze.
- Define clear inclusion and exclusion criteria: Define clear criteria for including or excluding patients or cases from the study. This will help ensure that the data is representative of the population of interest.
- Use clear data fields: Use clear and concise data fields to capture each data element. This will make it easier to collect and analyze the data.
- Provide clear instructions: Provide clear instructions for completing the data collection form, including any required fields or data elements.
- Pilot test the form: Pilot test the data collection form with a small sample of patients or cases to ensure that it is effective and easy to use.
- Train data collectors: Provide training to data collectors to ensure that they understand how to use the data collection form and collect data consistently.
Once the data collection form is designed and tested, you can begin collecting data by administering the form to patients or collecting data from medical records. You should ensure that the data is collected consistently and accurately, and that it meets the inclusion and exclusion criteria defined for the study. It may also be helpful to monitor the quality of the data collection process and to provide feedback to data collectors as needed.
Credit: mainly AI tools
Thank you Imam, you are entirely correct. Whenever possible we utilize and license existing standards for our products. Take a look at our web site to see the standards we use. However, in some situations actual standards or multiple standards are not available. Additionally, protocols, best practices and standard procedures might not have risen to the level of a formal standard. Quality enhancement starts with being able to accurately measure performance.
John www.mtuitive.com
Yes, you can use the mTuitive synoptic reporting opportunity for research data collection. Each response in an mTuitive synoptic report is a piece of structured data—this means it can be sent to local, state, national, and other registries automatically and be used for downstream research without the vast monetary and time costs of abstraction.