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.

Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs) / Milella, F; Seveso, A; Famiglini, L; Banfi, G; Cabitza, F. - In: JOURNAL OF PERSONALIZED MEDICINE. - ISSN 2075-4426. - 12:11(2022). [10.3390/jpm12111811]

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

Banfi, G;
2022-01-01

Abstract

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.
2022
patient-reported outcome measures
weather effect
propensity score matching
personalized medicine
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/134732
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