While working with Healthcare clients who want us to work with Data such as ICD Codes and HL7 / CCD here is a small example of how we process information.
Converting HL7 (Health Level 7) messages to SQL Server (or any relational database) involves multiple steps, as the structure of HL7 messages is considerably different from the tabular format of relational databases. Here's a high-level overview of how you might achieve this:
Importing HL7 messages into SQL Server involves parsing the HL7 data and then inserting the parsed data into appropriate tables. Below are the general steps and methods to achieve this:
Understanding HL7:
HL7 messages are hierarchical and segment-based. Each segment represents a specific type of data. For instance:
MSH|^~\&|SENDING_APP|SENDING_FACILITY|RECEIVING_APP|RECEIVING_FACILITY|20110614075841||ADT^A01|934576120110614075841|P|2.3|
PID|||123456||DOE^JOHN^||...
Design Your Database Schema:
Create tables that represent different segments and fields of HL7 messages.
For instance, you may have tables for MSH, PID, OBR, etc., depending on which segments you're interested in.
Parse HL7 Messages:
Use a library or toolkit that can parse HL7.
For .NET, NHapi is a popular choice.
For Java, you can use HAPI.
These tools can parse the HL7 message and provide you with structured objects or data that you can then insert into SQL Server.
Insert Data into SQL Server:
Use your favorite SQL Server SDK or library to insert the parsed data into the database.
If you're using .NET, you might use ADO.NET or Entity Framework.
If you're using Java, you might use JDBC.
Map the parsed HL7 data to your database schema and insert it into the respective tables.
Use Middleware Tools:
Tools like Mirth Connect or Rhapsody can be configured to receive HL7 messages, parse them, and then insert them into SQL Server or any other database.
These tools provide connectors for various databases and can simplify the transformation and insertion of HL7 into databases.
Considerations:
Error Handling: Ensure you handle and log any errors that arise during the import process.
Batching: Instead of inserting one message at a time, consider batching multiple messages for more efficient data insertion.
Security: Given the sensitive nature of healthcare data, ensure that your connection to SQL Server is secure (using SSL) and that sensitive data is encrypted as required.
Data Validation: Ensure that the data being imported adheres to the HL7 standards and any additional standards that your application requires.
Sample Code Using NHapi (.NET): Below is a very basic example using NHapi to parse an HL7 message and then insert the patient's first name from the PID segment into SQL Server using ADO.NET:
using NHapi.Base.Parser;
using NHapi.Model.V24.Message;
using System.Data.SqlClient;
// ...
string hl7MessageText = "..."; // Your HL7 message here
// Parse the HL7 message using NHapi
PipeParser parser = new PipeParser();
IMessage message = parser.Parse(hl7MessageText);
ADT_A01 adtMessage = message as ADT_A01;
if (adtMessage != null)
{
string patientFirstName = adtMessage.PID.PatientName.GivenName.Value;
// Insert into SQL Server
string connectionString = "..."; // Your connection string here
using (SqlConnection connection = new SqlConnection(connectionString))
{
connection.Open();
using (SqlCommand command = new SqlCommand("INSERT INTO Patients (FirstName) VALUES (@FirstName)", connection))
{
command.Parameters.AddWithValue("@FirstName", patientFirstName);
command.ExecuteNonQuery();
}
}
}
Remember that real-world scenarios are often more complex than this sample. Ensure you handle different message types, versions, error scenarios, etc