A framework for capturing clinical data sets from computerized sources.
The pressure to improve health care and provide better care at a lower cost has generated the need for efficient capture of clinical data. Many data sets are now being defined to analyze health care. Historically, review and research organizations have simply determined what data they wanted to collect, developed forms, and then gathered the information through chart review without regard to what is already available institutionally in computerized databases. Today, much electronic patient information is available in operational data systems (for example, laboratory systems, pharmacy systems, and surgical scheduling systems) and is accessible by agencies and organizations through standards for messages, codes, and encrypted electronic mail. Such agencies and organizations should define the elements of their data sets in terms of standardized operational data, and data producers should fully adopt these code and message standards. The Health Plan Employer Data and Information Set and the Council of State and Territorial Epidemiologists in collaboration with the Centers for Disease Control and Prevention and the Association of State and Territorial Public Health Laboratory Directors provide examples of how this can be done.
McDonald
C J
CJ
Regenstrief Institute for Health Care, Indianapolis, IN, USA.
Overhage
J M
JM
Dexter
P
P
Takesue
B Y
BY
Dwyer
D M
DM
D000043:Abstracting and Indexing; D015510:Clinical Medicine / Q000592:standards; D003625:Data Collection / Q000379:methods* / Q000592:standards; D016208:Databases, Factual / Q000592:standards*; D006751:Hospital Information Systems; D006801:Humans; D016347:Medical Records Systems, Computerized / Q000145:classification; D011785:Quality Assurance, Health Care / Q000458:organization & administration*; D014481:United States