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Building an Integration Plan for Health Data Exchange

by davinci
Health Data Exchange - intely

The healthcare system in the United States is changing at a breakneck pace, so it’s critical to make integration planning a core component of IT operations.

When new software and systems are added to an existing environment, integration challenges can become complicated. Unfortunately, technology businesses frequently overlook integration project management in their deployment strategy.

The consequences of increased operational expenses, inadequate data exchange, project delays, and safety hazards. Building a framework to enable effective integration planning and administration is critical to supporting new or current initiatives.

It aids in preparing electronic health records (EHR) projects and achieving general IT goals for better data management.

What is health data exchange?

With bidirectional data exchange to serve operational and quality process demands, Health Data Exchange bridges the data gap between EMS and the hospital. All of this is safe, auditable, and real-time.

Its goal is to make global medical and wellness research and treatment development more accessible. We cut the time and expense of creating study cohorts in half, from years to millions of dollars.

How to build an integration plan for health data exchange?

Data integration aims to provide a single stream of condensed information. However, extensive preparation is necessary, and various analyses before any data integration can occur to guarantee that this data stream is correct.

The steps below show our consultants’ tried-and-true method for effectively delivering integrated data to our clients.

  • Define the project:

The success of a project may be assessed and tracked if it has defined objectives. Consider what format the consolidated data should be most valuable to the organization.

Daily transportation of 100% of sales data from a company’s retail locations to the Customer Relationship Management system at head office with a 98 ‘uptime, for example, may be an example goal.

Include the project’s parameters in your objectives. Make a list of all relevant databases, datasets, and software. Determine whether or not real-time data access is required. If not, how often should the information be transferred?

Reduce risk by making a list of all potential concerns, both before and after the project’s execution, and measures to address them. For example, unresponsive system custodians to faulty data streams are all potential risks.

  • Recognize the systems:

Make sure you go through all of the systems involved with the data, from the extraction to the final, aggregated output. Ascertain that the systems are connected properly, and determine any settings required for the data to be exchanged.

Depending on the systems involved, our data integration specialists may plan to implement data connections, SFTP ports, or APIs to facilitate data interchange. But, first, determine whether any manual procedures are currently in use and whether or not they can scale them. intelyConnect offers a no-code and low-code approach to healthcare data integration and interoperability.

Consider whether outdated systems are still contributing data and whether they can replace them with a more current solution. It must consider data security at every level of the data integration process.

Consider how the transmission of data from one system to another may influence the security of the other. Datahub, our data integration technology, offers top-notch security by encrypting data with 2048-bit encryption and sending data over SFTP.

  • Design the data integration framework:

Learn about the data you’ll integrate. Is it organized or unstructured? What sources of this information sources? How excellent is quality?

Determine the needs for the combined data in its final form. For example, what data sets are needed? How often will the data be delivered? Our DataHub system can offer data in various forms, including dashboards and Excel files.

DataHub is adaptable enough to allow our experts to develop custom solutions to match the needs of each customer. In addition, it can use scripts or off-the-shelf data integration technologies to develop a comparable system.

Budget, in-house experience, and your organization’s preparedness to adopt new technologies will all be factors to consider when evaluating various data integration options.

Read also: 4 Top apps for super-fast scanning

  • Define how the information will use:

If a third party provides data, make sure the file content definition is specified and signed off on as soon as possible. If your company already has the data, make sure that sample data is available for testing early on in the project.

The data will be mapped to new structures or translated into a new format based on the reporting needs indicated in Stage 1.

Consider how the end-user is informed about the status of the integration system. For example, you could need notifications for system-level problems like connection or data-specific problems like invalid entries. Next, decide who will be notified for each sort of alert.

  • Carry out the project:

Select a project champion to ensure that the integration is given the attention it deserves within the company. In addition, they can guarantee that sufficient resources are available and that other initiatives do not divert them.

Determine who the stakeholders are. For example, which internal departments utilize the data or systems and should be included in the project? Who from those departments will be engaged in the project’s design and implementation? 

Using sample data, extensively test the systems before installation. It guarantees that data quality criteria and data mappings have been successfully applied. In addition, to prevent relying on the knowledge of one or two persons, the system must be future-proofed.

It’s also critical that the data may be quickly changed or expanded. Long and short-term maintenance will be necessary, which is handled by our support team in the case of Datahub. You’ll also require a recovery strategy.

Some benefits of an integration plan for health data exchange: –

More and more health care providers are engaged in health data exchange to manage better and securely share individuals’ comprehensive medical histories.

Health data interchange aids inpatient care coordination, reducing redundant therapies, and avoiding costly errors because the necessity for health data exchange is evident. 

The advantages of health data exchange are great; this practice is becoming more popular among health professionals.

  • Increase patient safety by cutting down on medication and medical blunders.
  • Increase efficiency by reducing the amount of paperwork and processing required.
  • Provide clinical decision support tools to caregivers for more effective care and treatment.
  • Remove any testing that is redundant or unnecessary.
  • Enhance public health monitoring and reporting.
  • Involve healthcare consumers in discussions about their health data.
  • Improve the quality and results of healthcare.
  • Lower health-care expenses.

Conclusion:

Not only is the expense of the system, but also the integration a difficulty when developing an integration strategy for health data interchange with other systems. 

Maintaining various interfaces is expensive, and system compatibility issues may make it difficult to expand the firm. Therefore, before embarking on the development path, it’s critical to construct an integration road map that outlines the practical purposes of a software product. Let intely handle the complexities of workflows, data integration & healthcare interoperability.

Choosing intelyConnect to assist with creating an app allows the developer to focus on the app while the specialists do the hard work of integration.

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