Clinical Data Repository (CDR)

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A Clinical Data Repository (CDR) is a data store with clinical data record.

References

2021

  • (Wikipedia, 2021) ⇒ https://en.wikipedia.org/wiki/Clinical_data_repository Retrieved:2021-12-11.
    • A Clinical Data Repository (CDR) or Clinical Data Warehouse (CDW) is a real time database that consolidates data from a variety of clinical sources to present a unified view of a single patient. It is optimized to allow clinicians to retrieve data for a single patient rather than to identify a population of patients with common characteristics or to facilitate the management of a specific clinical department. Typical data types which are often found within a CDR include: clinical laboratory test results, patient demographics, pharmacy information, radiology reports and images, pathology reports, hospital admission, discharge and transfer dates, ICD-9 codes, discharge summaries, and progress notes.

      A Clinical Data Repository could be used in the hospital setting to track prescribing trends as well as for the monitoring of infectious diseases. One area CDR's could potentially be used is monitoring the prescribing of antibiotics in hospitals especially as the number of antiobiotic-resistant bacteria is ever increasing. In 1995, a study at the Beth Israel Deaconess Medical Center conducted by the Harvard Medical School used a CDR to monitor vancomycin use and prescribing trends since vancomycin-resistant enterococci is a growing problem. They used the CDR to track the prescribing by linking the individual patient, medication, and the microbiology lab results which were all contained within the CDR. If the microbiology lab result did not support the use of vancomycin, it was suggested to change the medication to something appropriate as under the Center for Disease Control CDC guidelines. The use of CDR's could help monitor infectious diseases in the hospital and the appropriate prescribing based on lab results. The use of Clinical Data Repositories could provide a wealth of knowledge about patients, their medical conditions, and their outcome. The database could serve as a way to study the relationship and potential patterns between disease progression and management. The term "Medical Data Mining" has been coined for this method of research. Past epidemiological studies may not have had as complete of information as that which is contained in a CDR, which could lead to inconclusive data/results. The use of medical data mining and correlative studies using the CDR could serve as a valuable resource helping the future of healthcare in all facets of medicine. The idea of data mining a CDW was used for screening variables that were associated with diabetes and poor glycemic control. It allowed for novel correlations that may have not been discovered without this method. One potential use of a clinical data repository would be for clinical trials. This would allow for researchers to have all the information from a study in one place as well as let other researchers benefit from the data to further innovation. They would also be advantageous since they are digital and real-time. This would be easier to log data and keep it accurate since it would be digital rather than in paper form. The clinical data repository is not without its weaknesses, however. Since they usually don't integrate with other non-clinical sources, following patient treatment across the care continuum becomes very difficult. In turn, tracking the true cost per case for each patient isn't feasible. IT teams spend most of their time gathering and compiling data instead of interpreting information and finding opportunities for cutting costs and improving patient care.


2020

  • https://www.sciencedirect.com/topics/nursing-and-health-professions/clinical-data-repository
    • QUOTE: ... CDRs suffer from a variety of problems when used as a research data source, in part because of the confusion surrounding the nature of CDRs themselves. For example, a common misconception about CDRs is that they are interchangeable as a clinical data warehouse (CDW), but this is generally not the case. Data warehouses, as discussed in detail in an upcoming section of this chapter, have distinguishing characteristics such as support for data query or analysis “in place,” and the straightforward transformation of data into smaller “data marts.” The creation of a true CDW requires that the clinical data be reorganized at a minimum, and often be deconstructed into more granular forms. A true clinical repository, on the other hand, collects information as it exists in its primary form, albeit usually with additional indexing. In theory, a CDR can be an excellent data source for a CDW. In reality, CDR designs exist along the spectrum from a true repository to a true data warehouse. ...

2017

2016

  • (Nadkarni, 2016) > Prakash Nadkarni. (2016). “Clinical Data Repositories: Warehouses, Registries, and the Use of Standards." In: Clinical Research Computing.
    • ABSTRACT: This chapter describes different kinds of data repositories: operational data stores (ODSs), clinical data warehouses, clinical data marts, and clinical registries. The purpose of the ODS is to serve as a location for the processes of extraction, transfer, and load prior to creating a warehouse or data marts, both of which are physically integrated databases optimized for rapid query. Virtual data integration or federation is not recommended unless political realities make physical integration infeasible. Registries are repositories that limit their contents to patients with specific disease conditions: their formats are often archaic, reflecting their long existence. The act of creating warehouses or marts may paradoxically make reporting and data extraction needs increase. It is important to set end-users’ expectations by identifying limitations in the quality of the data sources. It is important to map data elements during warehousing if only to increase the usability of the resulting system.
    • QUOTE: Clinical data repositories are databases intended to facilitate arbitrary querying of the data and analyses for reporting and research. They are secondary databases, that is, they receive data that has been originally input into other sources. Repositories can be subclassified by function into the following categories: ODSs, data warehouses/data marts, and clinical registries. I discuss each category later.

       Repositories are populated either electronically by a process called extraction–transformation–load (ETL), which is explained shortly, or with a significant manual component (ie, abstraction of the electronic record). Manual abstraction continues to be employed for registries, as discussed shortly. ...

2011

  • (Cho et al., 2011) ⇒ InSook Cho, Hyeoun-Ae Park, and Eunja Chung. (2011). “Exploring Practice Variation in Preventive Pressure-ulcer Care Using Data from a Clinical Data Repository.” International journal of medical informatics 80, no. 1
    • ABSTRACT: ... The narrative nursing notes of 427 intensive-care patients who were discharged in 2007 that were documented at the point-of-care using standardized nursing statements were extracted from a clinical data repository at a teaching hospital in Korea and analyzed. The frequencies of five nursing interventions for pressure-ulcer prevention were compared between pressure-ulcer and pressure-ulcer risk groups, as were the characteristics of the nurses who were treating the patients in these two groups. Nursing interventions for pressure-ulcer prevention were also assessed relative to the patients’ medical problems. ...
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