The Limitations and Inefficiencies of a Clinical Data Repository

Healthcare organizations that implement a clinical data repository may think they are on the cutting-edge of data management and understanding that data, but these repositories are actually quite limiting.

Merely having a database of data does not provide the quality information needed to improve the costs and quality of services provided. To fully understand why this is the case, it is important to define the term clinical data repository to fully explore the limitations and inefficiencies caused by relying on a data repository.

What Is a Clinical Data Repository?

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In order to fully understand the limitations of a clinical data repository, it is imperative to define clinical data repository. In simplest terms, a clinical data repository consolidates data from a wide range of clinical sources. In broader terms, an EHR, lab or similar clinical source will utilize a clinical data repository to receive a quick snapshot of the totality of a patient’s care.

Typical data that might be included in a clinical data repository include the following:

  • Lab results
  • Radiology images
  • Diagnoses
  • Transfers
  • Demographics
  • And more

While it may seem that such a system provides clear and obvious benefits that make implementing a repository a no-brainer decision, it is actually a poor solution as a healthcare provider’s data system.

The Clinical Data Repository Is Simply a Glorified Database

While it is certainly true that having a snapshot of a patient’s clinical data is important, a clinical data repository lacks meaningful analytics that are flexible and scale with the healthcare provider’s needs.

The data repository merely holds clinical data, which means it cannot integrate with other source systems which are non-clinical. This prevents medical providers from understanding the patient’s healthcare data and history across the totality of the patient care spectrum. In short, the clinical data repository is at best a glorified database.

In effect, data repositories will not provide critical information such as the patient’s satisfaction after their visit, the complete cost of treating each patient, and more. While these limitations are the major downsides of a clinical data repository, there are other key inefficiencies stemming from the use of a clinical data repository.

Other Inefficiencies and Limitations

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Healthcare professionals must be able to receive quick access to quality data in order to produce effective reports. Given the demands of quick data requests, an IT team will often be inundated with the need to produce many reports all at the same time.

This team was hired to be an essential part of the analytics arm of the healthcare organization, but under a repository system, they simply find data, plug it into the repository, generate a report and continue ad nauseam. Contrast this approach with an approach that lets IT pros work with clinical teams to pore over reports and refine them to produce better data that is actionable and will improve the organization.

Not only will this alternative approach save time, but it will also produce markedly improved results. Another hindrance of the data repository system is that there is no standardization for reports and tools. Since different visualization tools are used to build reports based off of the data generated from the repository, every report can vary by department.

“If you don’t make mistakes,
you’re doing it wrong.
If you don’t correct your mistakes,
you’re doing it really wrong.” Chris Bojrab, MD

If you can’t accept that you’re mistaken, you’re not doing it at all.
As a result, reading reports will become a time-consuming task that detracts from organizational efficiency. Given these additional drawbacks as well as the main concerns already mentioned, the question becomes whether there is a suitable alternative to a clinical data repository.

Fortunately, the answer to that question is yes, thanks to a late-binding data warehouse.

The Benefits of a Late-Binding Data Warehouse

Unlike a data repository, a late-binding data warehouse brings all data from the health network into a single system. Naturally, this produces reliable and repeatable reporting results that will save time and provide faster access to meaningful reports.

Analysts can then provide value by analyzing this data instead of spending the bulk of their hours merely tracking data down under a repository setup. Standardized reports will ensure that all of the organization is on the same page, reducing response times, errors and increasing patient satisfaction.

In short, a late-binding data warehouse provides the meaningful insights needed for a healthcare organization to excel in a way that a clinical data repository cannot match.

Data Warehousing Solutions for Healthcare