#HealthShare

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InterSystems HealthShare is a healthcare informatics platform for hospitals, integrated delivery networks (IDNs) and regional and national health information exchanges (HIE). HealthShare includes health information exchange, data aggregation, workflow, text analysis, and analytics technology.

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I am looking for a way to capture Data Quality issues with the Source data that is populating HealthShare Provider Directory. 1 way is to use Managed Alerts, but since it could be multiple Providers and different messages it seems silly to alert on every message that has the error. Instead, I was thinking of using the Workflow Engine so it could populate a Worklist for someone to review and work.

Looking over the Demo.Workflow Engine example, I am not comprehending on how to send a task to the Workflow manager to populate the worklist from a DTL.

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Article
· Oct 22 2m read
Tips on handling Large data

Hello community,

I wanted to share my experience about working on Large Data projects. Over the years, I have had the opportunity to handle massive patient data, payor data and transactional logs while working in an hospital industry. I have had the chance to build huge reports which had to be written using advanced logics fetching data across multiple tables whose indexing was not helping me write efficient code.

Here is what I have learned about managing large data efficiently.

Choosing the right data access method.

As we all here in the community are aware of, IRIS provides multiple ways to access data. Choosing the right method, depends on the requirement.

  • Direct Global Access: Fastest for bulk read/write operations. For example, if i have to traverse through indexes and fetch patient data, I can loop through the globals to process millions of records. This will save a lot of time.
Set ToDate=+H
Set FromDate=+$H-1 For  Set FromDate=$O(^PatientD("Date",FromDate)) Quit:FromDate>ToDate  Do
. Set PatId="" For  Set PatId=$Order(^PatientD("Date",FromDate,PatID)) Quit:PatId=""  Do
. . Write $Get(^PatientD("Date",FromDate,PatID)),!
  • Using SQL: Useful for reporting or analytical requirements, though slower for huge data sets.

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Hello!!!

Data migration often sounds like a simple "move data from A to B task" until you actually do it. In reality, it is a complex process that blends planning, validation, testing, and technical precision.

Over several projects where I handled data migration into a HIS which runs on IRIS (TrakCare), I realized that success comes from a mix of discipline and automation.

Here are a few points which I want to highlight.

1. Start with a Defined Data Format.

Before you even open your first file, make sure everyone, especially data providers, clearly understands the exact data format you expect. Defining templates early avoids unnecessary bank-and-forth and rework later.

While Excel or CSV formats are common, I personally feel using a tab-delimited text file (.txt) for data upload is best. It's lightweight, consistent, and avoids issues with commas inside text fields. 

PatID   DOB Gender  AdmDate
10001   2000-01-02  M   2025-10-01
10002   1998-01-05  F   2025-10-05
10005   1980-08-23  M   2025-10-15

Make sure that the date formats given in the file is correct and constant throughout the file because all these files are usually converted from an Excel file and an Basic excel user might make mistakes while giving you the date formats wrong. Wrong date formats can irritate you while converting into horolog.

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Overview

This web interface is designed to facilitate the management of Data Lookup Tables via a user-friendly web page. It is particularly useful when your lookup table values are large, dynamic, and frequently changing. By granting end-users controlled access to this web interface (read, write, and delete permissions limited to this page), they can efficiently manage lookup table data according to their needs.

The data managed through this interface can be seamlessly utilized in HealthConnect rules or data transformations, eliminating the need for constant manual monitoring and management of the lookup tables and thereby saving significant time.

Note:
If the standard Data Lookup Table does not meet your mapping requirements, you can create a custom table and adapt this web interface along with its supporting class with minimal modifications. Sample class code is available upon request.

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