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Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs)

One of the next frontiers in medical research, particularly in orthopaedic surgery, is personalized treatment outcome prediction. In personalized medicine, treatment choices are adjusted for the patient based on the individual’s and their disease’s distinct features. A high-value and patient-centere...

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Autores principales: Milella, Frida, Seveso, Andrea, Famiglini, Lorenzo, Banfi, Giuseppe, Cabitza, Federico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9699394/
https://www.ncbi.nlm.nih.gov/pubmed/36579522
http://dx.doi.org/10.3390/jpm12111811
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author Milella, Frida
Seveso, Andrea
Famiglini, Lorenzo
Banfi, Giuseppe
Cabitza, Federico
author_facet Milella, Frida
Seveso, Andrea
Famiglini, Lorenzo
Banfi, Giuseppe
Cabitza, Federico
author_sort Milella, Frida
collection PubMed
description One of the next frontiers in medical research, particularly in orthopaedic surgery, is personalized treatment outcome prediction. In personalized medicine, treatment choices are adjusted for the patient based on the individual’s and their disease’s distinct features. A high-value and patient-centered health care system requires evaluating results that integrate the patient’s viewpoint. Patient-reported outcome measures (PROMs) are widely used to shed light on patients’ perceptions of their health status after an intervention by using validated questionnaires. The aim of this study is to examine whether meteorological or light (night vs. day) conditions affect PROM scores and hence indirectly affect health-related outcomes. We collected scores for PROMs from questionnaires completed by patients (N = 2326) who had undergone hip and knee interventions between June 2017 and May 2020 at the IRCCS Orthopaedic Institute Galeazzi (IOG), Milan, Italy. Nearest neighbour propensity score (PS) matching was applied to ensure the similarity of the groups tested under the different weather-related conditions. The exposure PS was derived through logistic regression. The data were analysed using statistical tests (Student’s t-test and Mann−Whitney U test). According to Cohen’s effect size, weather conditions may affect the scores for PROMs and, indirectly, health-related outcomes via influencing the relative humidity and weather-related conditions. The findings suggest avoiding PROMs’ collection in certain conditions if the odds of outcome-based underperformance are to be minimized. This would ensure a balance between costs for PROMs’ collection and data availability.
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spelling pubmed-96993942022-11-26 Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs) Milella, Frida Seveso, Andrea Famiglini, Lorenzo Banfi, Giuseppe Cabitza, Federico J Pers Med Article One of the next frontiers in medical research, particularly in orthopaedic surgery, is personalized treatment outcome prediction. In personalized medicine, treatment choices are adjusted for the patient based on the individual’s and their disease’s distinct features. A high-value and patient-centered health care system requires evaluating results that integrate the patient’s viewpoint. Patient-reported outcome measures (PROMs) are widely used to shed light on patients’ perceptions of their health status after an intervention by using validated questionnaires. The aim of this study is to examine whether meteorological or light (night vs. day) conditions affect PROM scores and hence indirectly affect health-related outcomes. We collected scores for PROMs from questionnaires completed by patients (N = 2326) who had undergone hip and knee interventions between June 2017 and May 2020 at the IRCCS Orthopaedic Institute Galeazzi (IOG), Milan, Italy. Nearest neighbour propensity score (PS) matching was applied to ensure the similarity of the groups tested under the different weather-related conditions. The exposure PS was derived through logistic regression. The data were analysed using statistical tests (Student’s t-test and Mann−Whitney U test). According to Cohen’s effect size, weather conditions may affect the scores for PROMs and, indirectly, health-related outcomes via influencing the relative humidity and weather-related conditions. The findings suggest avoiding PROMs’ collection in certain conditions if the odds of outcome-based underperformance are to be minimized. This would ensure a balance between costs for PROMs’ collection and data availability. MDPI 2022-11-01 /pmc/articles/PMC9699394/ /pubmed/36579522 http://dx.doi.org/10.3390/jpm12111811 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Milella, Frida
Seveso, Andrea
Famiglini, Lorenzo
Banfi, Giuseppe
Cabitza, Federico
Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs)
title Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs)
title_full Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs)
title_fullStr Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs)
title_full_unstemmed Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs)
title_short Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs)
title_sort detecting the effect size of weather conditions on patient-reported outcome measures (proms)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9699394/
https://www.ncbi.nlm.nih.gov/pubmed/36579522
http://dx.doi.org/10.3390/jpm12111811
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