The Evolution of Personalized Healthcare and the Pivotal Role of European Regions in its Implementation

Nardini, Christine; Osmani, Venet; Cormio, Paola Giulia; Frosini, Andrea; Turrini, Mauro; Lionis, Christos; Neumuth, Thomas; Ballensiefen, Wolfgang; Borgonovi, Elio

doi:10.2217/pme-2020-0115

Cited by 37 publications

(36 citation statements)

References 40 publications

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“…The understanding of the underlying mechanisms and causes of chronic diseases is transforming medicine from a reactive discipline to a proactive and preventive one. Therefore, a Predictive, Preventive, Personalized and Participatory Medicine (medicine P4) [ 40 ] which also applies to nutrition, with the objectives of quantifying well-being, will predict and prevent disease. Consumers are different in each country and the form of salt consumption is also different.…”

Section: Discussionmentioning

confidence: 99%

Interventions That Successfully Reduced Adults Salt Intake—A Systematic Review

et al. 2021

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Background: Adequate sodium intake is important for lowering blood pressure and thus reducing cardiovascular disease risk and other complications. The aim of this review is to identify recent interventions around the world that have been successful in reducing salt intake. Methods: A search in the PubMed, Web of Science and Scopus databases was performed. We include studies published in the last 10 years; randomized trials, pilot intervention without a control arm or experimental study; adult participants; and interventions that successfully reduced salt intake. Study quality was assessed. Results: We included 21 studies, 16 randomized intervention trials and five nonrandomized intervention studies. Eleven interventions described health and nutritional education, seven interventions described nutritional education plus other interventions, and three studies used salt meters to reduce sodium intake. Conclusion: Health and nutritional education, nutritional education plus other interventions and estimates of salt intake showed success in the reduction of salt consumption. There is no evidence that one type of intervention analyzed is more effective than other in reducing salt consumption, so we must analyze each in which individuals or subpopulations will have the intervention performed and use the most suitable approaches to lead to better results.

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Section: Discussionmentioning

confidence: 99%

Interventions That Successfully Reduced Adults Salt Intake—A Systematic Review

et al. 2021

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“…Predictive models play a key role in bolstering decision systems, and ML techniques have outstanding potential to create models with an excellent level of accuracy [ 70 ]. They have been used to identify useful correlations between biometric, genetic and environmental data with the potential risks and benefits of certain therapeutic choices [ 71 ]. They also have great potential to exceed the performance of physicians’ heuristics, reducing lags in diagnosis and treatment costs when their application is extended from the genomic and biometric data to the clinical and demographic data in the patient’s records.…”

Section: Conclusion and Recommendations In The Framework Of 3p Medicinementioning

confidence: 99%

Diagnosing hospital bacteraemia in the framework of predictive, preventive and personalised medicine using electronic health records and machine learning classifiers

et al. 2021

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Background The bacteraemia prediction is relevant because sepsis is one of the most important causes of morbidity and mortality. Bacteraemia prognosis primarily depends on a rapid diagnosis. The bacteraemia prediction would shorten up to 6 days the diagnosis, and, in conjunction with individual patient variables, should be considered to start the early administration of personalised antibiotic treatment and medical services, the election of specific diagnostic techniques and the determination of additional treatments, such as surgery, that would prevent subsequent complications. Machine learning techniques could help physicians make these informed decisions by predicting bacteraemia using the data already available in electronic hospital records. Objective This study presents the application of machine learning techniques to these records to predict the blood culture’s outcome, which would reduce the lag in starting a personalised antibiotic treatment and the medical costs associated with erroneous treatments due to conservative assumptions about blood culture outcomes. Methods Six supervised classifiers were created using three machine learning techniques, Support Vector Machine, Random Forest and K-Nearest Neighbours, on the electronic health records of hospital patients. The best approach to handle missing data was chosen and, for each machine learning technique, two classification models were created: the first uses the features known at the time of blood extraction, whereas the second uses four extra features revealed during the blood culture. Results The six classifiers were trained and tested using a dataset of 4357 patients with 117 features per patient. The models obtain predictions that, for the best case, are up to a state-of-the-art accuracy of 85.9%, a sensitivity of 87.4% and an AUC of 0.93. Conclusions Our results provide cutting-edge metrics of interest in predictive medical models with values that exceed the medical practice threshold and previous results in the literature using classical modelling techniques in specific types of bacteraemia. Additionally, the consistency of results is reasserted because the three classifiers’ importance ranking shows similar features that coincide with those that physicians use in their manual heuristics. Therefore, the efficacy of these machine learning techniques confirms their viability to assist in the aims of predictive and personalised medicine once the disease presents bacteraemia-compatible symptoms and to assist in improving the healthcare economy.

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“…It is here that the role played by Patient Centered Care ensures the active engagement of the patient by bringing his personal needs and preferences into the decision-making process. Nardini et al 2021 [ 50 ] describe a new healthcare configuration that includes personalized, predictive, preventive, participatory and person-centered care approaches, to be applied to all areas of medicine. Agreeing with such findings, this review recognizes how both models together are needed to ensure a positive and effective change in the path of patient care and attempts to tailor such a transition to the context of breast cancer care.…”

Section: Discussionmentioning

confidence: 99%

Success Factors and Barriers in Combining Personalized Medicine and Patient Centered Care in Breast Cancer. Results from a Systematic Review and Proposal of Conceptual Framework

Belvis

Pellegrino

Castagna

et al. 2021

JPM

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Breast Cancer (BC) is the leading cause of death due to cancer in women. Ensuring equitable, quality-assured and effective care has increased the complexity of BC management. This systematic review reports on the state-of-the art of available literature investigating the enactment of personalized treatment and patient-centered care models in BC clinical practice, building a framework for the delivery of personalized BC care within a Patient-Centered model. Databases were searched for articles (from the inception to December 2020) reporting on Patient-Centered or Personalized Medicine BC management models, assessing success factors or limits. Out of 1885 records, 25 studies were included in our analysis. The main success factors include clearly defined roles and responsibilities within a multi-professional collaboration, appropriate training programs and adequate communication strategies and adopting a universal genomic language to improve patients’ involvement in the decision-making process. Among detected barriers, delays in the use of genetic testing were linked to the lack of public reimbursement schemes and of clear indications in timing and appropriateness. Overall, both care approaches are complementary and necessary to effectively improve BC patient management. Our framework attempts to bridge the gap in assigning a central role played by shared decision-making, still scarcely investigated in literature.

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The Evolution of Personalized Healthcare and the Pivotal Role of European Regions in its Implementation

Cited by 37 publications

References 40 publications

Interventions That Successfully Reduced Adults Salt Intake—A Systematic Review

Interventions That Successfully Reduced Adults Salt Intake—A Systematic Review

Diagnosing hospital bacteraemia in the framework of predictive, preventive and personalised medicine using electronic health records and machine learning classifiers

Success Factors and Barriers in Combining Personalized Medicine and Patient Centered Care in Breast Cancer. Results from a Systematic Review and Proposal of Conceptual Framework

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