Data management is essential for efficient service delivery in the healthcare system. Clinical data repositories help healthcare facilities manage patient data by making it easily accessible.A clinical data repository  (CDR) is a database that unifies data from various sources for a single patient. These repositories are like data storage facilities that accept and display data in real time. These repositories have been shown to increase data access of patient health records due to their ease of use.The repositories contain data such as lab results, prescription information, admissions, and patient demographics. The CDRs collect and pool information from many health centers in a given radius.

Uses of Clinical Data Repositories

CDRs have helped ease access to information on patients and health trends. This has led to the following advantages.

Reducing antibiotic resistance

The micro bacteria that cause diseases are slowly evolving and becoming resistant to antibiotics. This is a big problem since it means that conventional antibiotics are becoming useless in treating various types of diseases. One method used to curb the increase of the resistant bacteria is to reduce the prescription of the affected antibiotics.  Such a method was implemented by Harvard researchers to lower the growth of the drug resistant enterococci bacteria. The researchers used CDRs to monitor lab results and recommend alternative prescriptions instead of prescribing the affected vancomycin

Medical Research

Clinical data repositories are accessed by medical researchers to gain information on their research. Since the repositories contain the entire health records of patients, it becomes easier for medical researchers to deduce various trends and associations by querying data about a particular subject. Therefore, doctors can associate certain conditions with different diseases after analyzing the information on CDRs.

Clinical trials

CDRs are very useful in clinical trials as they help pharmaceutical companies to track the progress of their patients. The data repositories also assist other researchers that aim to improve on the drugs by having access to the clinical trials information.

The Clinical Data Warehouse

With the amount of data that is created each day, having all of a company’s information on just one computer is not only inefficient, but also impossible. Any of the Fortune 500 businesses out there have conglomerated data stored in vast data warehouses. These warehouses are specially designed for different types of industries in order to perform needed tasks with greater effectiveness. But one industry was lagging behind and was forced to utilize data warehouses qualified for much different purposes. This industry was the healthcare industry. And the sheer volume of data that is created in the different doctors’ offices, hospitals and other health professionals’ care requires special attention to detail.

The first generation of clinical data warehouses had a lot of promise, yet weren't able to live up to the agility that the warehouses for other industries provided. The demand for a sweeping overhaul was made and in today’s market, there are solutions that provide the customized adaptability and flexibility specific to the needs within healthcare.

Challenges

 Although clinical data repositories help the healthcare community to access data, they do not provide analytics and hence a lot of time is wasted when generating reports. The repositories are usually just data storages. Therefore, in scenarios where one needs to compile and analyze data from the CDRs, it becomes a tedious task. Much of the time is spent gathering data from various records in the repository, which leaves very little time for improving the data so that it is accurate and presentable.

Clinical data repositories are also used to handle clinical data exclusively. They cannot be integrated with disparate systems that handle other forms of data such as the patient’s financial records.

The CDRs also contain normalized tables which help in database maintenance and integrity. However, this becomes a challenge for people trying to compile reports using various data tables. Organizing clear and understandable data often requires one query the database and link multiple related tables.

Report presentation is also a challenge for the CDRs. Since a clinical data repository does not have the capability of analyzing data and generating reports, its users are forced to use other tools to perform this task. As such, similar reports or reports generated from the same data by different individuals might appear totally different. This makes the task of comparing different reports less efficient.

It is due to these challenges that more health analysts are opting for enterprise data warehouses.

Enterprise Data Warehouse

Enterprise data warehouses (EDW) help to deal with most of the challenges faced by CDRs. The data warehouses are like intelligent CDRs that can be assigned different tasks, such as generating reports and aggregating certain types of data. The data warehouses are well suited for reporting and data analysis.

The EDWs help to reduce the inefficiencies experienced on CDRs such as time wastage. Their ability to generate reports ensures that you get standardized reports that are easy to compare. 

Healthcare Analytics Depend on Data Warehouses

Clinical data warehouses or clinical data repositories are structured to be more exact or at least close to exact to the plethora of incoming and outgoing information and data. Unlike most business industries, healthcare has a wide variety of information that is related to each patient such as the typical information of name, address and phone number, but also health insurance plan, coverage, billing, medical history, family history, medical data from office visits and so much more. What also may not be realized by many in the public is that medical professionals also have reporting that has to be regularly supplied to government and other organizations. All this consist the type of data that is stored and processed through clinical data repositories.