Development of a national core dataset for the Iranian ICU patients outcome prediction: A comprehensive approach

Atashi, A. and Ahmadian, L. and Rahmatinezhad, Z. and Miri, M. and Nazeri, N. and Eslami, S. (2018) Development of a national core dataset for the Iranian ICU patients outcome prediction: A comprehensive approach. Journal of Innovation in Health Informatics, 25 (2). pp. 71-76.

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Abstract

Objective To define a core dataset for intensive care unit (ICU) patients outcome prediction in Iran. This core data set will lead us to design ICU outcome prediction models with the most effective parameters. Methods A combination of literature review, national survey and expert consensus meetings were used. First, a literature review was performed by a general search in PubMed to find the most appropriate models for intensive care mortality prediction and their parameters. Second, in a national survey, experts from a couple of medical centres in all parts of Iran were asked to comment on a list of items retrieved from the earlier literature review study. In the next step, a multi-disciplinary committee of experts was installed. In four meetings, each data item was examined separately and included/excluded by committee consensus. Results The combination of the literature review findings and experts' consensus resulted in a draft dataset including 26 data items. Ninety-two percent of data items in the draft dataset were retrieved from the literature study and the others were suggested by the experts. The final dataset of 24 data items covers patient history and physical examination, chemistry, vital signs, oxygenations and some more specific parameters. Conclusions This dataset was designed to develop a nationwide prognostic model for predicting ICU mortality and length of stay. This dataset opens the door for creating standardised approaches in data collection in the Iranian intensive care unit estimation of resource utility. Copyright © 2018 The Author(s).

Item Type: Article
Additional Information: Export Date: 16 February 2020 Correspondence Address: Ahmadian, L.; Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical SciencesIran; email: ahmadianle@yahoo.com
Uncontrolled Keywords: Data sets Intensive care units Iran Prognosis Risk assessment adult article chemistry consensus female human intensive care unit length of stay male medical history Medline mortality oxygenation physical examination prediction systematic review vital sign aged factual database hospital mortality medical informatics outcome assessment questionnaire Databases, Factual Humans Outcome Assessment (Health Care) Surveys and Questionnaires
Subjects: WX Hospital and other health Facilities
W General medicine- Health professions
Divisions: Mashhad University of Medical Sciences
Depositing User: lib2 lib2 lib2
Date Deposited: 06 Jun 2020 09:34
Last Modified: 06 Jun 2020 09:34
URI: http://eprints.mums.ac.ir/id/eprint/17212

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