Benefiting from Health Data Exchange Requires an Effective Decision Automation Solution That can Use Healthcare Data Standards.
Health data exchange is referred to the exchange of patient and medical records among health organisations like hospitals, healthcare providers, government agencies and health insurance companies. These data will be passed from one system to the other and then be used for various purposes like diagnosis, medical researches, and insurance claims. That is why the systems should be able to communicate with each other more efficiently.
This need of interoperability has raised the importance of a quality standard that can be used by different healthcare systems. Especially, in an industry like health, privacy, accuracy, security, and quality are major issues of data exchange and an international standard is a must. That is the reason behind HL7 standard which was introduced in 1987 by Health Level Seven International as a comprehensive framework to standardise data “exchange, integration, sharing, and retrieval of electronic health information that supports clinical practice and the management, delivery and evaluation of health services.” Therefore, this standard is being used widely by healthcare systems across the globe.
The following image is a snippet from a HL7 message:
Once these messages are received in HL7 standard, initially, it requires to be decoded and then can be used to make effective healthcare decisions.
If we consider a sample situation, when a person meet a fatal accident in a foreign country, passing this patient’s data to his family and the country of his citizenship, informing his health insurance provider, and using his treatment data for a medical research are some of the challenges we face although there is a standard for data exchange. These challenges urge an improvement to the current solutions, innovating more automated systems that effectively communicate with each other.
Decision Automation Using Decoded HL7 Messages
Moving forward to another step, the decoded messages can be useful to take important decisions in healthcare systems.
After decoding the above message in FlexRule® Advanced Decision Management Suite:
You will see that the decoded message is available in JSON format and different segments of the message provide certain important details about the patients and their conditions. Using that, we have built the following decision table to validate the message. For example, if the patient identification is not presented in the message, it will display an error notification.
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Furthermore, being able to decode and encode the HL7 messages opens more opportunities in healthcare systems. One of the major breakthroughs is the ability to use the decoded messages as a data source for machine learning.
These are a few use cases of end-to-end decision automation based on decoded HL7 messages:
- Diagnose illnesses
- Innovate medical treatments
- Claim healthcare insurance
- Send emergency alerts doctors and caretakers
- Develop safety measures and policies
For instance, if a particular data is missing from the message, a solution with end-to-end decision automation can directly inform the patient/ healthcare provider about the missing data reducing an unnecessary human interaction in between.
Conclusion: End-to-end Decision Automation can Help Healthcare Providers Make Decisions Using Health Data
There are several aspects that should be considered when we exchange health data among systems. Accuracy, privacy, and quality are some of those critical factors. That is why it requires a standard like HL7 which ticks most of these factors of health data exchange. Having the quality data coming from various sources, a robust system that enables end-to-end decision automation can help to validate data, take important decisions using machine learning or pre-defined set of business rules and communicate with the right parties. Therefore, this will be a huge support for the healthcare providers to focus more on making healthcare policies and deliver the care that needs to improve the health as a society.
Last updated January 10th, 2023 at 11:00 am, Published September 10th, 2020 at 11:00 am