case study

Legacy System Integration with EMR Case Study

Seamless Integration of Cloud-Based Eligibility Verification Platform with EMR

What should healthcare facilities do to ensure the critical medical data is received in a fast and secure way?

Approved Admissions was thinking over APIs enterprise system integration but encountered bottlenecks on its way. The management looked for industry experts that has proven expertise with successful legacy system integration case studies and chose our team.

About the Client

Approved Admissions is a cloud-based eligibility verification platform that helps healthcare facilities determine the patient’s coverage and avoid billing errors in patients' care.

Data Bridge is an integration platform designed to automatically export medical records from PCC, SigmaCare, and Visual EMR to the AA platform.

By facing an increasing flow of customers, AA decided to optimize a patient verification process.

To reduce the time and resources they spent on data retrieving and processing, there was a need for the solution to facilitate data exchange.

Notes

The system monitors and reports changes in Medicare, Medicaid, and HMO payers.

Why Does the Client
Choose to Integrate Legacy Systems via APIs?

Legacy system integration with APIs ensure solutions interoperability and provide access to multiple data sources.

In healthcare, it’s a vital tool for
Such reasons:

It’s a secure way
to deliver sensitive data

The industry went ahead in using specific API protocols and certifications (The Health IT Standards Committee (HITSC)). So, it much safer to use APIs instead of proprietary technology

It’s possible to operate
data siloed in EMRs

Most of the medical records are stored in monolithic legacy applications. The API-led approach allows extracting them in an efficient and cost-effective way.

USER DEVICE

API

EMR

The Challenges We Faced in
This Project

The APIs integration in
healthcare solutions may have
difficulties like various data
standards, exacerbated in old
frameworks using outdated technology.

WE HAD TWO
TECHNICAL ISSUES

Data standardization in legacy software

The client wanted the solution to support HL7, X12 EDI, XML, FHIR, and other communication standards and non-standardized interfaces (web, etc.). So our team should transform arbitrary data into a single standardized model. It would allow Approved Admissions to connect with other healthcare facilities and integrate legacy database.

APIs connectivity to ASP.NET MVC

The older technology, the harder it is to integrate legacy software with newer solutions. AA was a bright representative of such a legacy system before we upgraded it from ASP.NET MVC to .NET Core 3.1. So, to provide seamless integration for ASP.NET MVC, we had to build a module that transfers data from medical databases to AA, and vice versa.

Planning as an Important Groundwork

The first goal was creating a microservices-based architecture with message queues to organize and modernize the data transfer from multiple services. It also enabled achieving a stable load balance of the system.

The rest of the work on the project, we divided into 2 tasks:

build a wrapper for AA to accept files

build a web scraper to extract data from EMR platforms

In carrying out the tasks, we were guided by SOLID, KISS, and DRY principles that stand for lean programming.

Perfect Code

As an outcome, the solution has a clear architecture with logically connected parts. Further, it would be easy to extend functionality or get rid of some code pieces.

WRAPPER

BRIDGE

Scheme

The simplest explanation tends to be the right one

We, at ModLogix, are sure there's a strong coding philosophy behind every effective
solution.

That’s why our team adheres to basic principles such:

SOLID

KISS

DRY

Just do not go deep into theory, they make code simple, structured, and reduce duplications.

How to Effectively Conduct a Legacy System Integration

What's the best way to integrate your legacy systems? Check 4 basic approaches to revamp your software.

Learn more

All articles

Blog Posts

Designing a Web Scraper to
Retrieve Data

While the different EMR platforms contain large amounts of data, our team decided to develop a web scraper.

It should collect data in a single point to analyze it and deliver the required results to AA upon request.

TransformATION non-uniform formats of data into a structured format

This model automatically exports medical records allowing omitting the time-consuming manual process.

document load

Pull in
the webpage

parsing

Parse the HTML
metadata

extraction

Use the results of parsing to extract the data

transformation

Convert the data into desired format

Creating of a Custom Wrapper
to Accept Import Files

The next big step

Provide an environment for easily and securely accepting the EMR data by the verification platform.

So, we agreed to craft a wrapper with the required interface to support API requests.

By these developments, the Approved Admissions system could receive import files, process the data, and generate reports in a single click.

How Do We Establish the Data Exchange Process

But hold on, how did we implement the data transfer between these 2 touchpoints? And how did we make it a HIPAA compliant? So first things first.

The main cornerstone

The main cornerstone was to choose a relevant tool that would be compatible with ASP.NET MVC and could work with sensitive information, as in our case.

The choice fell on RabbitMQ - a message broker that receives and sends requests via secure TLS protocols.

On top of it, we applied .NET-friendly MassTransit framework that puts various message types on queue. The framework organizes messages from the queue to distribute the load over the system.

It helps us to build a universal model for smooth data transition and design an effective strategy to integrate legacy systems.

message flow in an microservice architechture
using a messagebroker

Producer

Message

MESSAGE
BROKER

C0NSUMER 1

CONSUMER 2

CONSUMER 3

Technologies
and Tools We Use

000

001

010

SCOPE OF WORK :

1 Project Manager

1 Tech Lead

2 Developers

1 Business Analyst

6 Months

Results

12.3 times faster
reports generated

43% increase in
customer base

15,000 proceeded
requests per day

The reports of vital patients’ info are generated 12.3 times faster without manual intervention. Based on these data, the AA clients sped up patients’ eligibility verification process.

AA management also won new market niches by offering seamless integration into the platform with just one click for healthcare organizations. Only for a year, they have increased the client base about 43%.

The automatic and easy export of medical records was the ultimate goal we strived for. For now, Bridge provides Approved Admissions direct access to disparate EMR data sets and ensures interoperability among healthcare facilities.

Results

Key Takeaways

Look for an experienced vendor of software modernization services who is digging deep into standards and regulations in healthcare (HIPAA, etc.).

Consider microservice architecture in dealing with large amounts of API request queues.

Effective communication among team members is a vital part within a problem-solving approach.

Client Review

We are delighted to be working with customers in a variety of industries and verticals.

Being subject matter experts in Healthcare, they really understood our challenges and we didn't have to spend hours explaining what we needed.

Alan Dworetsky

DIRECTOR OF BUSINESS DEVELOPMENT, APPROVED ADMISSIONS

Our Team
on This Project

Alex

business Analyst

extensive deepening
the industry expertise

We have had projects in the sphere of digital healthcare solutions since our beginning. Yet, Bridge has extensively deepened the industry expertise, as we had to deal with various EHR platforms and data formats. Now we can freely operate with them and apply this knowledge in other enterprise projects.