Limits...
Monitoring and Prognosis System Based on the ICF for People with Traumatic Brain Injury.

Subirats L, Lopez-Blazquez R, Ceccaroni L, Gifre M, Miralles F, García-Rudolph A, Tormos JM - Int J Environ Res Public Health (2015)

Bottom Line: The prognosis system achieves 41% of accuracy and sensitivity in the prediction of emotional functions, and 48% of accuracy and sensitivity in the prediction of executive functions.This monitoring and prognosis system has the potential to: (1) save costs and time, (2) provide more information to make decisions, (3) promote interoperability, (4) facilitate joint decision-making, and (5) improve policies of socioeconomic evaluation of the burden of disease.Professionals found the monitoring system useful because it generates a more comprehensive understanding of health oriented to the profile of the patients, instead of their diseases and injuries.

View Article: PubMed Central - PubMed

Affiliation: Health Department, Eurecat, Roc Boronat, 08018 Barcelona, Spain. laia.subirats@eurecat.org.

ABSTRACT
The objective of this research is to provide a standardized platform to monitor and predict indicators of people with traumatic brain injury using the International Classification of Functioning, Disability and Health, and analyze its potential benefits for people with disabilities, health centers and administrations. We developed a platform that allows automatic standardization and automatic graphical representations of indicators of the status of individuals and populations. We used data from 730 people with acquired brain injury performing periodic comprehensive evaluations in the years 2006-2013. Health professionals noted that the use of color-coded graphical representation is useful for quickly diagnose failures, limitations or restrictions in rehabilitation. The prognosis system achieves 41% of accuracy and sensitivity in the prediction of emotional functions, and 48% of accuracy and sensitivity in the prediction of executive functions. This monitoring and prognosis system has the potential to: (1) save costs and time, (2) provide more information to make decisions, (3) promote interoperability, (4) facilitate joint decision-making, and (5) improve policies of socioeconomic evaluation of the burden of disease. Professionals found the monitoring system useful because it generates a more comprehensive understanding of health oriented to the profile of the patients, instead of their diseases and injuries.

No MeSH data available.


Related in: MedlinePlus

Flowchart of the automatic generation of multidimensional indicators.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4555314&req=5

ijerph-12-09832-f001: Flowchart of the automatic generation of multidimensional indicators.

Mentions: We analyzed the experience of the monitoring system with five health professionals (a neuropsychologist, a doctor, a social worker and two psychologists). Quantitative and qualitative information was collected by verbal reports protocol. This monitoring system has been implemented in Liferay Portal CE, which is available under the GNU Public License (LGPL) v2.1. However, the results of this system are not available to the public and there is a published patent [30] of the standardization method. MATLAB was used for the different plots [31]. Figure 1 shows the flowchart of the standardization of the ICF and its integration in the monitoring system, which is comprised of an extractor, a transformer, an inference engine, a selector, a filter and a presentation system. The extractor access databases and selectively fetches information. The transformer performs the standardization of attributes and values (performed by the attribute normalizer and value normalizer respectively) and aggregates the information. Then, the inference engine performs when necessary the inference of values from other attributes. The selector selects the relevant information depending on the particular profile being analyzed. The filter enables the personalization of data visualization enabling filtering by a plurality of parameters. Finally, the presentation system enables the graphical representation of all normalized data.


Monitoring and Prognosis System Based on the ICF for People with Traumatic Brain Injury.

Subirats L, Lopez-Blazquez R, Ceccaroni L, Gifre M, Miralles F, García-Rudolph A, Tormos JM - Int J Environ Res Public Health (2015)

Flowchart of the automatic generation of multidimensional indicators.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4555314&req=5

ijerph-12-09832-f001: Flowchart of the automatic generation of multidimensional indicators.
Mentions: We analyzed the experience of the monitoring system with five health professionals (a neuropsychologist, a doctor, a social worker and two psychologists). Quantitative and qualitative information was collected by verbal reports protocol. This monitoring system has been implemented in Liferay Portal CE, which is available under the GNU Public License (LGPL) v2.1. However, the results of this system are not available to the public and there is a published patent [30] of the standardization method. MATLAB was used for the different plots [31]. Figure 1 shows the flowchart of the standardization of the ICF and its integration in the monitoring system, which is comprised of an extractor, a transformer, an inference engine, a selector, a filter and a presentation system. The extractor access databases and selectively fetches information. The transformer performs the standardization of attributes and values (performed by the attribute normalizer and value normalizer respectively) and aggregates the information. Then, the inference engine performs when necessary the inference of values from other attributes. The selector selects the relevant information depending on the particular profile being analyzed. The filter enables the personalization of data visualization enabling filtering by a plurality of parameters. Finally, the presentation system enables the graphical representation of all normalized data.

Bottom Line: The prognosis system achieves 41% of accuracy and sensitivity in the prediction of emotional functions, and 48% of accuracy and sensitivity in the prediction of executive functions.This monitoring and prognosis system has the potential to: (1) save costs and time, (2) provide more information to make decisions, (3) promote interoperability, (4) facilitate joint decision-making, and (5) improve policies of socioeconomic evaluation of the burden of disease.Professionals found the monitoring system useful because it generates a more comprehensive understanding of health oriented to the profile of the patients, instead of their diseases and injuries.

View Article: PubMed Central - PubMed

Affiliation: Health Department, Eurecat, Roc Boronat, 08018 Barcelona, Spain. laia.subirats@eurecat.org.

ABSTRACT
The objective of this research is to provide a standardized platform to monitor and predict indicators of people with traumatic brain injury using the International Classification of Functioning, Disability and Health, and analyze its potential benefits for people with disabilities, health centers and administrations. We developed a platform that allows automatic standardization and automatic graphical representations of indicators of the status of individuals and populations. We used data from 730 people with acquired brain injury performing periodic comprehensive evaluations in the years 2006-2013. Health professionals noted that the use of color-coded graphical representation is useful for quickly diagnose failures, limitations or restrictions in rehabilitation. The prognosis system achieves 41% of accuracy and sensitivity in the prediction of emotional functions, and 48% of accuracy and sensitivity in the prediction of executive functions. This monitoring and prognosis system has the potential to: (1) save costs and time, (2) provide more information to make decisions, (3) promote interoperability, (4) facilitate joint decision-making, and (5) improve policies of socioeconomic evaluation of the burden of disease. Professionals found the monitoring system useful because it generates a more comprehensive understanding of health oriented to the profile of the patients, instead of their diseases and injuries.

No MeSH data available.


Related in: MedlinePlus