Title |
Codifying healthcare – big data and the issue of misclassification
|
---|---|
Published in |
BMC Anesthesiology, December 2015
|
DOI | 10.1186/s12871-015-0165-y |
Pubmed ID | |
Authors |
Karim S. Ladha, Matthias Eikermann |
Abstract |
The rise of electronic medical records has led to a proliferation of large observational studies that examine the perioperative period. In contrast to randomized controlled trials, these studies have the ability to provide quick, cheap and easily obtainable information on a variety of patients and are reflective of everyday clinical practice. However, it is important to note that the data used in these studies are often generated for billing or documentation purposes such as insurance claims or the electronic anesthetic record. The reliance on codes to define diagnoses in these studies may lead to false inferences or conclusions. Researchers should specify the code assignment process and be aware of potential error sources when undertaking studies using secondary data sources. While misclassification may be a short-coming of using large databases, it does not prevent their use in conducting meaningful effectiveness research that has direct consequences on medical decision making. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Spain | 2 | 22% |
Germany | 1 | 11% |
France | 1 | 11% |
United Kingdom | 1 | 11% |
Unknown | 4 | 44% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 7 | 78% |
Practitioners (doctors, other healthcare professionals) | 2 | 22% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 52 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 11 | 21% |
Researcher | 10 | 19% |
Student > Master | 6 | 12% |
Other | 4 | 8% |
Student > Doctoral Student | 4 | 8% |
Other | 7 | 13% |
Unknown | 10 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 12 | 23% |
Computer Science | 6 | 12% |
Nursing and Health Professions | 5 | 10% |
Engineering | 3 | 6% |
Business, Management and Accounting | 2 | 4% |
Other | 11 | 21% |
Unknown | 13 | 25% |