Back-UP: Personalised Prognostic Models To Imporve Well-Being And return To Work After Neck and Low Back Pain

Research output: Contribution to conferencePaperAcademicpeer-review

Abstract

Patients with Neck and/or Low Back Pain (NLBP) constitute a heterogeneous group with the prognosis and precise mix of factors involved varying substantially between individuals. This means that a one-size-fits-all approach is not recommended, but methods to tailor treatment to the individual needs are still relatively under-developed. Moreover, the fragmentation of disciplines involved in its study hampers achieving sound answers to clinical questions. Data mining techniques open new horizons by combining data from existing datasets, in order to select the best treatment at each moment in time to a patient based on the individual characteristics.
Within the Back-UP project (H2020 #777090) a multidisciplinary consortium is creating a prognostic model to support more effective and efficient management of NLBP, based on the digital representation of multidimensional clinical information. Patient-specific models provide a personalized evaluation of the patient case, using multidimensional health data from the following sources: (1) psychological, behavioral, and socioeconomic factors, (2) biological patient characteristics, including musculoskeletal structures and function, and molecular data, (3) workplace and lifestyle risk factors.
The Back-UP system leverages shared-decision making, not only by enabling interoperability between all professionals involved in the care trajectory, but also empowering the patient in the decisions related to his/her care path. Furthermore, dynamic intervention models ensure that the patient receives the most beneficial treatment at each moment in time, having into account the current position of the patient in the care path (i.e. within clinical rehabilitation, in return-to-work process or through motivational strategies that support self-management in daily life).

Original languageEnglish
Pages26
Number of pages1
Publication statusPublished - 15 Nov 2018
EventSBPR 2018: Understanding the mechanisms of back pain: work, rest and play - University Medical Centre , Groningen, Netherlands
Duration: 15 Nov 201816 Nov 2018

Conference

ConferenceSBPR 2018
Abbreviated titleSBPR
CountryNetherlands
CityGroningen
Period15/11/1816/11/18

Fingerprint

Return to Work
Low Back Pain
Neck
Data Mining
Information Storage and Retrieval
Self Care
Molecular Structure
Workplace
Life Style
Decision Making
Patient Care
Therapeutics
Rehabilitation
Psychology
Health

Cite this

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title = "Back-UP: Personalised Prognostic Models To Imporve Well-Being And return To Work After Neck and Low Back Pain",
abstract = "Patients with Neck and/or Low Back Pain (NLBP) constitute a heterogeneous group with the prognosis and precise mix of factors involved varying substantially between individuals. This means that a one-size-fits-all approach is not recommended, but methods to tailor treatment to the individual needs are still relatively under-developed. Moreover, the fragmentation of disciplines involved in its study hampers achieving sound answers to clinical questions. Data mining techniques open new horizons by combining data from existing datasets, in order to select the best treatment at each moment in time to a patient based on the individual characteristics. Within the Back-UP project (H2020 #777090) a multidisciplinary consortium is creating a prognostic model to support more effective and efficient management of NLBP, based on the digital representation of multidimensional clinical information. Patient-specific models provide a personalized evaluation of the patient case, using multidimensional health data from the following sources: (1) psychological, behavioral, and socioeconomic factors, (2) biological patient characteristics, including musculoskeletal structures and function, and molecular data, (3) workplace and lifestyle risk factors. The Back-UP system leverages shared-decision making, not only by enabling interoperability between all professionals involved in the care trajectory, but also empowering the patient in the decisions related to his/her care path. Furthermore, dynamic intervention models ensure that the patient receives the most beneficial treatment at each moment in time, having into account the current position of the patient in the care path (i.e. within clinical rehabilitation, in return-to-work process or through motivational strategies that support self-management in daily life).",
author = "Cabrita, {Ana Miriam} and {Oude Nijeweme - d'Hollosy}, Wendy and S. Jansen-Kosterink",
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language = "English",
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note = "SBPR 2018 : Understanding the mechanisms of back pain: work, rest and play, SBPR ; Conference date: 15-11-2018 Through 16-11-2018",

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Cabrita, AM, Oude Nijeweme - d'Hollosy, W & Jansen-Kosterink, S 2018, 'Back-UP: Personalised Prognostic Models To Imporve Well-Being And return To Work After Neck and Low Back Pain' Paper presented at SBPR 2018, Groningen, Netherlands, 15/11/18 - 16/11/18, pp. 26.

Back-UP: Personalised Prognostic Models To Imporve Well-Being And return To Work After Neck and Low Back Pain. / Cabrita, Ana Miriam; Oude Nijeweme - d'Hollosy, Wendy; Jansen-Kosterink, S.

2018. 26 Paper presented at SBPR 2018, Groningen, Netherlands.

Research output: Contribution to conferencePaperAcademicpeer-review

TY - CONF

T1 - Back-UP: Personalised Prognostic Models To Imporve Well-Being And return To Work After Neck and Low Back Pain

AU - Cabrita, Ana Miriam

AU - Oude Nijeweme - d'Hollosy, Wendy

AU - Jansen-Kosterink, S.

PY - 2018/11/15

Y1 - 2018/11/15

N2 - Patients with Neck and/or Low Back Pain (NLBP) constitute a heterogeneous group with the prognosis and precise mix of factors involved varying substantially between individuals. This means that a one-size-fits-all approach is not recommended, but methods to tailor treatment to the individual needs are still relatively under-developed. Moreover, the fragmentation of disciplines involved in its study hampers achieving sound answers to clinical questions. Data mining techniques open new horizons by combining data from existing datasets, in order to select the best treatment at each moment in time to a patient based on the individual characteristics. Within the Back-UP project (H2020 #777090) a multidisciplinary consortium is creating a prognostic model to support more effective and efficient management of NLBP, based on the digital representation of multidimensional clinical information. Patient-specific models provide a personalized evaluation of the patient case, using multidimensional health data from the following sources: (1) psychological, behavioral, and socioeconomic factors, (2) biological patient characteristics, including musculoskeletal structures and function, and molecular data, (3) workplace and lifestyle risk factors. The Back-UP system leverages shared-decision making, not only by enabling interoperability between all professionals involved in the care trajectory, but also empowering the patient in the decisions related to his/her care path. Furthermore, dynamic intervention models ensure that the patient receives the most beneficial treatment at each moment in time, having into account the current position of the patient in the care path (i.e. within clinical rehabilitation, in return-to-work process or through motivational strategies that support self-management in daily life).

AB - Patients with Neck and/or Low Back Pain (NLBP) constitute a heterogeneous group with the prognosis and precise mix of factors involved varying substantially between individuals. This means that a one-size-fits-all approach is not recommended, but methods to tailor treatment to the individual needs are still relatively under-developed. Moreover, the fragmentation of disciplines involved in its study hampers achieving sound answers to clinical questions. Data mining techniques open new horizons by combining data from existing datasets, in order to select the best treatment at each moment in time to a patient based on the individual characteristics. Within the Back-UP project (H2020 #777090) a multidisciplinary consortium is creating a prognostic model to support more effective and efficient management of NLBP, based on the digital representation of multidimensional clinical information. Patient-specific models provide a personalized evaluation of the patient case, using multidimensional health data from the following sources: (1) psychological, behavioral, and socioeconomic factors, (2) biological patient characteristics, including musculoskeletal structures and function, and molecular data, (3) workplace and lifestyle risk factors. The Back-UP system leverages shared-decision making, not only by enabling interoperability between all professionals involved in the care trajectory, but also empowering the patient in the decisions related to his/her care path. Furthermore, dynamic intervention models ensure that the patient receives the most beneficial treatment at each moment in time, having into account the current position of the patient in the care path (i.e. within clinical rehabilitation, in return-to-work process or through motivational strategies that support self-management in daily life).

UR - https://wencke4.housing.rug.nl/Cursuswinkel/public/Brochure/SBPR_program%20with%20abstracts.pdf

M3 - Paper

SP - 26

ER -