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

Result code in 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>

Alternative codes found

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

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30211 - Orthopaedics

Project

<a href="/en/project/NU20-06-00269" target="_blank" >NU20-06-00269: Utility of cellular profiles and proteomics of synovial fluid and periprosthetic tissues for clinical decision making in knee osteoarthritis</a><br>

Continuities

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

Publication year

2021

Confidentiality

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

Name of the periodical

Journal of Translational Medicine

ISSN

1479-5876

e-ISSN

—

Volume of the periodical

19

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

12

Pages from-to

"nestránkováno"

UT code for WoS article

000620257500002

EID of the result in the Scopus database

2-s2.0-85101468457