A method for predicting the utilization of medical technology in neonatal care

João D. Scalon; Marcos F. Vidai Melo; Ronney B. Panerai

doi:10.3233/thc-1996-3408

A method for predicting the utilization of medical technology in neonatal care

João D. Scalon, Marcos F. Vidai Melo, Ronney B. Panerai

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

The utilization of 12 neonatal intensive care technologies was recorded in 193 patients. An index of utilization (P(u)) was adopted to classify these technologies into three sub-groups corresponding to low (P(u) < 15%), medium (15% ≤ P(u) ≤ 85%), and high (P(u) > 85%) intensity of use. No models were developed for technologies with high intensity of use (intravenous hydration, warming, micro-haematocrit, heart rate monitoring). Multiple linear regression was used to predict the utilization of technologies with medium intensity of use (gasometry, oxygen hood, CPAP, mechanical ventilation), and multiple logistic regression was used with the same purpose for technologies with low intensity of use (exchange transfusion, bicarbonate, adrenaline, echocardiography). Both methods yielded significant models (P < 0.05) which can be used to improve planning and management of technology in neonatal intensive care units.

Original language	English (US)
Pages (from-to)	273-278
Number of pages	6
Journal	Technology and Health Care
Volume	3
Issue number	4
DOIs	https://doi.org/10.3233/thc-1996-3408
State	Published - Mar 1996
Externally published	Yes

Keywords

Clinical engineering
Forecasting
Health planning
NICU
Resource allocation
Technology management
Utilization review

ASJC Scopus subject areas

Biophysics
Bioengineering
Biomaterials
Information Systems
Biomedical Engineering
Health Informatics

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10.3233/thc-1996-3408

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title = "A method for predicting the utilization of medical technology in neonatal care",

abstract = "The utilization of 12 neonatal intensive care technologies was recorded in 193 patients. An index of utilization (P(u)) was adopted to classify these technologies into three sub-groups corresponding to low (P(u) < 15%), medium (15% ≤ P(u) ≤ 85%), and high (P(u) > 85%) intensity of use. No models were developed for technologies with high intensity of use (intravenous hydration, warming, micro-haematocrit, heart rate monitoring). Multiple linear regression was used to predict the utilization of technologies with medium intensity of use (gasometry, oxygen hood, CPAP, mechanical ventilation), and multiple logistic regression was used with the same purpose for technologies with low intensity of use (exchange transfusion, bicarbonate, adrenaline, echocardiography). Both methods yielded significant models (P < 0.05) which can be used to improve planning and management of technology in neonatal intensive care units.",

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year = "1996",

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AU - Vidai Melo, Marcos F.

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N2 - The utilization of 12 neonatal intensive care technologies was recorded in 193 patients. An index of utilization (P(u)) was adopted to classify these technologies into three sub-groups corresponding to low (P(u) < 15%), medium (15% ≤ P(u) ≤ 85%), and high (P(u) > 85%) intensity of use. No models were developed for technologies with high intensity of use (intravenous hydration, warming, micro-haematocrit, heart rate monitoring). Multiple linear regression was used to predict the utilization of technologies with medium intensity of use (gasometry, oxygen hood, CPAP, mechanical ventilation), and multiple logistic regression was used with the same purpose for technologies with low intensity of use (exchange transfusion, bicarbonate, adrenaline, echocardiography). Both methods yielded significant models (P < 0.05) which can be used to improve planning and management of technology in neonatal intensive care units.

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KW - Resource allocation

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A method for predicting the utilization of medical technology in neonatal care

Abstract

Keywords

ASJC Scopus subject areas

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