Clinical data repository: Difference between revisions

Revision as of 12:29, 15 January 2021

Latest revision as of 20:18, 29 May 2024

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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 antiobioticantibiotic-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 [[Centers for Disease Control and Prevention|CDC]] guidelines. The use of CDR's could help monitor infectious diseases in the hospital and the appropriate prescribing based on lab results.<ref>{{cite journal |author1=Samore M Lichtenberg D |author2=Saubermann L |author3=Kawachi C |author4=Carmeli Y | year = 1997| title = A Clinical Data Repository Enhances Hospital Infection Control | journal = Harvard Medical School | volume = 1997 | pages = 56–60 | pmc=2233433 | pmid=9357588}}</ref>

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.<ref>{{cite journal |vauthors=Prather JC, Lobach DF, Goodwin LK, Hales JW, Hage ML, Hammond WE | year = 1997| title = Medical Data Mining: Knowledge Discovery in a Clinical Data Warehouse | journal = Duke University Medical Center | volume = 1997 | pages = 101–105 | pmc=2233405 | pmid=9357597}}</ref> 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.<ref>{{cite journal | doi=10.1016/S0933-3657(02)00051-9 | pmid=12234716 | volume=26 | issue=1–2 | title=Data mining a diabetic data warehouse | journal=Artificial Intelligence in Medicine | pages=37–54| date=September 2002 | last1=Breault | first1=Joseph L. | last2=Goodall | first2=Colin R. | last3=Fos | first3=Peter J. }}</ref>