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Computerized history-taking as a tool to manage dyslipidemia

BACKGROUND: Validated guidelines to manage low-density lipoprotein (LDL)-cholesterol are utilized inconsistently or not at all even though their application lowers the incidence of coronary events. New approaches are needed, therefore, to implement these guidelines in everyday practice. METHODS AND...

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Detalles Bibliográficos
Autores principales: Zakim, David, Fritz, Christine, Braun, Niko, Fritz, Peter, Alscher, M Dominik
Formato: Texto
Lenguaje:English
Publicado: Dove Medical Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2988621/
https://www.ncbi.nlm.nih.gov/pubmed/21127700
http://dx.doi.org/10.2147/VHRM.S14302
Descripción
Sumario:BACKGROUND: Validated guidelines to manage low-density lipoprotein (LDL)-cholesterol are utilized inconsistently or not at all even though their application lowers the incidence of coronary events. New approaches are needed, therefore, to implement these guidelines in everyday practice. METHODS AND RESULTS: We compared an automated method for applying The National Cholesterol Education Panel (NCEP) guidelines with results from routine care for managing LDL-cholesterol. The automated method comprised computerized history-taking and analysis of historical data without physician input. Results from routine care were determined for 213 unselected patients and compared with results from interviews of the same 213 patients by a computerized history-taking program. Data extracted from hospital charts showed that routine care typically did not collect sufficient information to stratify risk and assign treatment targets for LDL-cholesterol and that there were inconsistencies in identifying patients with normal or elevated levels of LDL-cholesterol in relation to risk. The computerized interview program outperformed routine care in collecting historical data relevant to stratifying risk, assigning treatment targets, and clarifying the presence of hypercholesterolemia relative to risk. CONCLUSIONS: Computerized history-taking coupled with automated analysis of the clinical data can outperform routine medical care in applying NCEP guidelines for stratifying risk and identifying patients with hypercholesterolemia in relation to risk.