Step-By-Step Guide to Healthcare Warehousing

When it comes to carrying out advanced analytics, few tools are more valuable to healthcare organizations than an enterprise data warehouse

Healthcare Data Warehouses: Why They Are So Important

For those in the health field, a data warehouse is a place to compile a large volume of clinical data, financial records, and more. Healthcare facility practitioners and administrators compile data to identify trends, create forecasting models, make appropriate decisions, and ensure data quality management

Additionally, an enterprise data warehouse can help organizations in the healthcare industry prepare for regulatory compliance audits. 

 A healthcare data warehouse can be invaluable, but the process of creating and managing one can be incredibly complex. 

In this post, we’ll cover what exactly healthcare warehousing is, why it’s useful, and—most importantly—how to create a data warehouse of your own.


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What Is the Function of Data Warehousing in Healthcare?

A data warehouse—or enterprise data warehouse (EDW)—is a system in which a large volume of historical data is compiled. In healthcare, warehousing can include electronic health records (EHRs), as well as many other useful data sources within the healthcare system, including:

  • Supply chain data
  • Data from claims management systems 
  • Prescriptions
  • Cause of mortality and disease registries 
  • Social determinants of health (SDOH) 

Essentially, a data warehouse makes it possible to gather all data—every scanned image, the information received from every medical device, the cost of every medical supply and so on—in one place. 

Healthcare providers can use this data to make clinical decisions or for business intelligence purposes, such as financial forecasting. Healthcare analytics have innumerable uses, which fit into three categories: descriptive, predictive, and prescriptive analytics. 

Descriptive analytics tells you what has happened in the past. 

You might, for example, conduct descriptive analytics to look at the spread of a virus in a certain population, determine how much your clinic spent on staffing within a certain period, or understand how many patients visit your clinic at different times of the year. 

You can use this information to discover patterns, which is a necessary foundation for predictive and prescriptive analytics. You can also use it to determine whether you’re meeting your financial or service goals. 

Predictive analytics, meanwhile, rely on both past and present healthcare data to predict what will happen. 

As the name suggests, predictive analytics will tell your healthcare organization what you can expect in the future and is invaluable for managing healthcare logistics

Predictive analytics might tell you the best course of action for patient care, determine the likelihood that certain treatments will be effective, or allow you to anticipate how severely a virus might present in certain patients.

Healthcare Data Warehouse

Prescriptive analytics goes beyond providing insights into what has already happened or what might happen next. It goes further to prescribe solutions to predictions at both individual and organizational levels. 

For example, prescriptive analytics might take into account the likelihood of patients with a certain illness or background developing certain other illnesses and prescribe appropriate adjustments to insurance reimbursement rates for those illnesses. Prescriptive analytics can also prescribe measures or treatments for preventing said illnesses from developing.

Step-By-Step Guide to Healthcare Warehousing

1. Plan and Gather Requirements

The planning stage is your chance to get all departments and team members on board with your intention to create an enterprise data warehouse for your healthcare organization.

At this stage, you should establish your data warehouse goals and how your team can help achieve those objectives. That involves determining your specific requirements and singling out those that are most important to ensure that your data warehouse meets all of these needs.

For a healthcare organization, this will include requirements related to regulatory compliance, as well as patient care, business performance, and general security.


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2. Design Your Data Warehouse Architecture

At this stage, you should:

  • Determine your data integration strategy and your ETL (Extract, Transform and Load) or ELT (Extract, Load and Transform) solution—i.e., the data integration process that will get your data from its source to your warehouse.ETL is the standard approach. Though ELT is faster, it can result in data that is less “clean”, due to the fact that it involves extracting and loading data and then transforming it after it’s been moved.
  • Defining your data model. This involves choosing between:
    • A data mart model. Data marts are ideal for organizations that wish to work with data that are specific to a certain department or domain.
    • An enterprise-wide data model. This model encompasses data from various departments/domains and is ideal for organizations that wish to analyze a larger volume of data or data from multiple sources.

 If these decisions appear to be beyond the scope of your own team, you’re not alone. Most organizations—especially those without a substantial in-house IT team—find this stage is best carried out with help from a trusted software vendor

3. Design the Front-End of Your Data Warehouse

A vendor can also connect you to resources that will help you create the front-end of your healthcare data warehouse. 

Healthcare Warehousing

Your warehouse should be easy for users to navigate and interpret. Designing a personalized solution from scratch is more trouble than it’s worth. As such, most organizations opt for a pre-built tool or kit for front-end data warehouse design.  

4. Develop Your Warehouse

Once you’ve designed a back-end and front-end that support your goals and requirements, it’s time to deploy the appropriate IT infrastructure and launch your data warehouse. Assuming you’ve worked with a reputable vendor, this stage should be a breeze.

5. Manage and Test Your Warehouse

The work isn’t over as soon as your data warehouse is up and running. It’s important to continue testing the warehouse to ensure that the data contained within it is accurate and reliable.

If you’re ready to begin the process of developing an enterprise data warehouse for your healthcare organization, True North can help you choose the best solutions and software for your unique needs.

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