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Fernando Lopes

Researcher at University of Porto

Publications -  33
Citations -  344

Fernando Lopes is an academic researcher from University of Porto. The author has contributed to research in topics: Data quality & Health care. The author has an hindex of 9, co-authored 28 publications receiving 253 citations.

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Factors influencing hospital high length of stay outliers

TL;DR: Age, type of admission, and hospital type were significantly associated with high LOS outliers, and the proportion of high outliers does not seem to be related to their financial coverage; they should be studied in order to highlight areas for further investigation.
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Health records as the basis of clinical coding: Is the quality adequate? A qualitative study of medical coders' perceptions.

TL;DR: The use of standards in health records, audits and physician awareness could increase the quality ofhealth records, contributing to improvements in the qualityof coded data, and in the fulfilment of its purposes (e.g. more accurate payments and more reliable research).
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Methodologies for the detection of adverse drug reactions: comparison of hospital databases, chart review and spontaneous reporting

TL;DR: To evaluate a methodology for adverse drug reactions (ADRs) detection through hospital databases, a large number of hospital databases are searched through.
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Detection of adverse drug reactions using hospital databases—a nationwide study in Portugal

TL;DR: This study aimed to detect and characterize adverse drug reactions that occurred during hospitalization and associated with admission in Portugal from 2000 to 2009 and to compare the results of this methodology with spontaneous reporting.
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Problems and Barriers during the Process of Clinical Coding: a Focus Group Study of Coders' Perceptions.

TL;DR: Some problems were identified and solutions such as the standardization of the documents used for coding an episode, the adoption of the electronic coding, the development of tools to help coding and audits, and the recognition of the importance of coding by the management were described as relevant factors for the improvement of the quality of data.