An optimisation approach for determining the efficiency of vital medical devices in intensive care units with COVID-19 patients using Apriori algorithm. (8th June 2023)

• Record Type: Journal Article
• Authors: Mirzaei, Abasat; Hoseini, Fatemeh; Lalinia, Mehrshad
• Is Part Of: International journal of data mining, modelling and management. Volume 15:Number 2(2023)
• Page Start: 154
• Page End: 168
• Publication Date: 2023-06-08
• Subjects: medical equipment -- COVID-19 -- hospital -- Apriori algorithm -- technology management -- healthcare equipment -- medical devices -- data mining -- medical data -- association rule -- ECLAT algorithm; Data mining -- Periodicals; Information science -- Periodicals; Databases -- Periodicals; 005.7
• Languages: English
• ISSNs: 1759-1163

Abstract

Improving the process of strategic management in hospitals preparation and equipping the intensive care units (ICUs) and the availability of medical devices plays an important role for knowing consumer behaviour and need. This cross-sectional study was performed in the ICU of Farhikhtegan Hospital, Tehran, Iran for a period of six months. During these months, ten medical devices have been used 5, 497 times. These devices include: ventilator, oxygen cylinder, infusion pump, electrocardiography machine, vital signs monitor, oxygen flowmeter, wavy mattress, ultrasound sonography machine, ultrasound echocardiography machine, and dialysis machine. The Apriori algorithm showed that four devices: ventilator, oxygen cylinder, vital signs monitoring device, oxygen flowmeter are the most used ones by patients. These devices are positively correlated with each other and their confidence is over 80% and their support is 73%. For validating the results, we have used equivalence class clustering and bottom-up lattice traversal (ECLAT) algorithm in our dataset.