A theoretical model of health management using data-driven decision-making: the future of precision medicine and health

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15110%2F21%3A73607319" target="_blank" >RIV/61989592:15110/21:73607319 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00098892:_____/21:N0000156 RIV/61989100:27240/21:10254685

Výsledek na webu

<a href="https://translational-medicine.biomedcentral.com/track/pdf/10.1186/s12967-021-02714-8.pdf" target="_blank" >https://translational-medicine.biomedcentral.com/track/pdf/10.1186/s12967-021-02714-8.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s12967-021-02714-8" target="_blank" >10.1186/s12967-021-02714-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A theoretical model of health management using data-driven decision-making: the future of precision medicine and health

Popis výsledku v původním jazyce

Background: The burden of chronic and societal diseases is afected by many risk factors that can change over time. The minimalisation of disease-associated risk factors may contribute to long-term health. Therefore, new data-driven health management should be used in clinical decision making in order to minimise future individual risks of disease and adverse health efects. Methods: We aimed to develop a health trajectories (HT) management methodology based on electronic healthrecords (EHR) and analysing overlapping groups of patients who share a similar risk of developing a particular disease or experiencing specifc adverse health efects. Formal concept analysis (FCA) was applied to identify and visualise overlapping patient groups, as well as for decision-making. To demonstrate its capabilities, the theoretical model presented uses genuine data from a local total knee arthroplasty (TKA) register (a total of 1885 patients) and shows the infuence of step by step changes in fve lifestyle factors (BMI, smoking, activity, sports and long-distance walking) on the risk of early reoperation after TKA. Results: The theoretical model of HT management demonstrates the potential of using EHR data to make datadriven recommendations to support both patients’ and physicians’ decision-making. The model example developed from the TKA register acts as a clinical decision-making tool, built to show surgeons and patients the likelihood of early reoperation after TKA and how the likelihood changes when factors are modifed. The presented data-driven tool suits an individualised approach to health management because it quantifes the impact of various combinations of factors on the early reoperation rate after TKA and shows alternative combinations of factors that may change the reoperation risk. Conclusion: This theoretical model introduces future HT management as an understandable way of conceiving patients’ futures with a view to positively (or negatively) changing their behaviour. The model’s ability to infuence benefcial health care decision-making to improve patient outcomes should be proved using various real-world data from EHR datasets

Název v anglickém jazyce

A theoretical model of health management using data-driven decision-making: the future of precision medicine and health

Popis výsledku anglicky

Background: The burden of chronic and societal diseases is afected by many risk factors that can change over time. The minimalisation of disease-associated risk factors may contribute to long-term health. Therefore, new data-driven health management should be used in clinical decision making in order to minimise future individual risks of disease and adverse health efects. Methods: We aimed to develop a health trajectories (HT) management methodology based on electronic healthrecords (EHR) and analysing overlapping groups of patients who share a similar risk of developing a particular disease or experiencing specifc adverse health efects. Formal concept analysis (FCA) was applied to identify and visualise overlapping patient groups, as well as for decision-making. To demonstrate its capabilities, the theoretical model presented uses genuine data from a local total knee arthroplasty (TKA) register (a total of 1885 patients) and shows the infuence of step by step changes in fve lifestyle factors (BMI, smoking, activity, sports and long-distance walking) on the risk of early reoperation after TKA. Results: The theoretical model of HT management demonstrates the potential of using EHR data to make datadriven recommendations to support both patients’ and physicians’ decision-making. The model example developed from the TKA register acts as a clinical decision-making tool, built to show surgeons and patients the likelihood of early reoperation after TKA and how the likelihood changes when factors are modifed. The presented data-driven tool suits an individualised approach to health management because it quantifes the impact of various combinations of factors on the early reoperation rate after TKA and shows alternative combinations of factors that may change the reoperation risk. Conclusion: This theoretical model introduces future HT management as an understandable way of conceiving patients’ futures with a view to positively (or negatively) changing their behaviour. The model’s ability to infuence benefcial health care decision-making to improve patient outcomes should be proved using various real-world data from EHR datasets

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30211 - Orthopaedics

Projekt

<a href="/cs/project/NU20-06-00269" target="_blank" >NU20-06-00269: Využití buněčných profilů a proteomiky synoviální tekutiny, případně tkání pro podporu klinického rozhodování u osteoartrózy kolena</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Translational Medicine

ISSN

1479-5876

e-ISSN

—

Svazek periodika

19

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

"nestránkováno"

Kód UT WoS článku

000620257500002

EID výsledku v databázi Scopus

2-s2.0-85101468457