Kwok, CS, Muntean, E-A, Mallen, CD and Borovac, JA (2022) Data Collection Theory in Healthcare Research: The Minimum Dataset in Quantitative Studies. Clinics and Practice, 12 (6). 832 - 844. ISSN 2039-7283

[thumbnail of clinpract-12-00088.pdf]
Preview
Text
clinpract-12-00088.pdf - Published Version

Download (854kB) | Preview

Abstract

There is considerable interest in data analytics because of its value in informing decisions in healthcare. Data variables can be derived from routinely collected records or from primary studies. The level of detail for individual variables in quantitative studies is often disregarded. In this work, we aim to present the concept of a minimum dataset for any variable. The most basic level of data collection is the value of a variable. In addition, there may be an indicator of severity and a measure of duration or how long the value has been present. The time course defines how the values for a variable fluctuated over time. The validity or accuracy of the values for a variable is also important to avoid spurious findings. Finally, there may be additional modifiers which drastically change the impact of a variable. In conclusion, the minimum dataset is a framework which can be used for the purposes of study design and appraisal of studies. Not all data requires full consideration of the minimum dataset framework for each variable, but the framework may be important if more detailed results are desired.

Item Type: Article
Additional Information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Subjects: R Medicine > R Medicine (General) > R735 Medical education. Medical schools. Research
R Medicine > RA Public aspects of medicine
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Divisions: Faculty of Medicine and Health Sciences > School of Medicine
Related URLs:
Depositing User: Symplectic
Date Deposited: 30 Nov 2022 14:34
Last Modified: 30 Nov 2022 14:34
URI: https://eprints.keele.ac.uk/id/eprint/11744

Actions (login required)

View Item
View Item