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Journal articles on the topic 'Personalised healthcare'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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1

Gray, Muir, Jonathon Gray, and Jeremy Howick. "Personalised healthcare and population healthcare." Journal of the Royal Society of Medicine 111, no. 2 (September 18, 2017): 51–56. http://dx.doi.org/10.1177/0141076817732523.

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Sahal, Radhya, Saeed H. Alsamhi, and Kenneth N. Brown. "Personal Digital Twin: A Close Look into the Present and a Step towards the Future of Personalised Healthcare Industry." Sensors 22, no. 15 (August 8, 2022): 5918. http://dx.doi.org/10.3390/s22155918.

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Digital twins (DTs) play a vital role in revolutionising the healthcare industry, leading to more personalised, intelligent, and proactive healthcare. With the evolution of personalised healthcare, there is a significant need to represent a virtual replica for individuals to provide the right type of care in the right way and at the right time. Therefore, in this paper, we surveyed the concept of a personal digital twin (PDT) as an enhanced version of the DT with actionable insight capabilities. In particular, PDT can bring value to patients by enabling more accurate decision making and proper treatment selection and optimisation. Then, we explored the progression of PDT as a revolutionary technology in healthcare research and industry. However, although several research works have been performed for smart healthcare using DT, PDT is still at an early stage. Consequently, we believe that this work can be a step towards smart personalised healthcare industry by guiding the design of industrial personalised healthcare systems. Accordingly, we introduced a reference framework that empowers smart personalised healthcare using PDTs by bringing together existing advanced technologies (i.e., DT, blockchain, and AI). Then, we described some selected use cases, including the mitigation of COVID-19 contagion, COVID-19 survivor follow-up care, personalised COVID-19 medicine, personalised osteoporosis prevention, personalised cancer survivor follow-up care, and personalised nutrition. Finally, we identified further challenges to pave the PDT paradigm toward the smart personalised healthcare industry.

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Borro, Marina, Giovanna Gentile, Luigi Cipolloni, Zeno Foldes-Papp, Paola Frati, Alessandro Santurro, Luana Lionetto, and Maurizio Simmaco. "Personalised Healthcare: The DiMA Clinical Model." Current Pharmaceutical Biotechnology 18, no. 3 (April 16, 2017): 242–52. http://dx.doi.org/10.2174/1389201018666170208125131.

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Horgan, Denis. "Keeping the Person in Personalised Healthcare." Biomedicine Hub 2, Suppl. 1 (November 21, 2017): 1–9. http://dx.doi.org/10.1159/000481683.

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Proponents of personalised medicine believe that the involvement of the patients, including in “risk-sharing agreements,” will result in cost savings, the use of the genetic makeup of an individual patient as the starting point will save resources and, indirectly, there will be great potential for startups and new business in many areas. But how can Europe ensure that the “person” is central stage and allow us to focus on the development of personalised medicine for his or her ultimate benefit? The EU has a clear role to play, argues the author. One way for this to happen is for the EU to focus investment in guidelines for governance. This will go a long way to ensuring that the citizen is the principal factor when it comes to utilising the new wealth of innovation in health. The citizen must always come first when innovation is harnessed.

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Gray, Muir, Harpreet Sood, Mahiben Maruthappu, and Fiona Moss. "Training for population and personalised healthcare." Journal of the Royal Society of Medicine 110, no. 12 (November 24, 2017): 476–82. http://dx.doi.org/10.1177/0141076817741245.

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Nicholson, J. "Systems medicine, microbiomes and personalised healthcare." Toxicology Letters 238, no. 2 (October 2015): S12. http://dx.doi.org/10.1016/j.toxlet.2015.08.074.

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Posfay-Barbe, Klara M., Julia Bielicki, and Pascale Wenger. "Considerations on General Consent in paediatrics." Regulatory Affairs Watch 2, no. 3 (March 2020): 15–18. http://dx.doi.org/10.54920/scto.2020.rawatch.3.15.

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The general goal of the initiative launched by the Swiss Personalized Health Network (SPHN) is to establish the infrastructure needed to collect and provide data and samples from Swiss residents, to ultimately support personalised approaches to healthcare.

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Nardini, Christine, Venet Osmani, Paola G. Cormio, Andrea Frosini, Mauro Turrini, Christos Lionis, Thomas Neumuth, Wolfgang Ballensiefen, Elio Borgonovi, and Gianni D’Errico. "The evolution of personalized healthcare and the pivotal role of European regions in its implementation." Personalized Medicine 18, no. 3 (May 2021): 283–94. http://dx.doi.org/10.2217/pme-2020-0115.

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Personalized medicine (PM) moves at the same pace of data and technology and calls for important changes in healthcare. New players are participating, providing impulse to PM. We review the conceptual foundations for PM and personalized healthcare and their evolution through scientific publications where a clear definition and the features of the different formulations are identifiable. We then examined PM policy documents of the International Consortium for Personalised Medicine and related initiatives to understand how PM stakeholders have been changing. Regional authorities and stakeholders have joined the race to deliver personalized care and are driving toward what could be termed as the next personalized healthcare. Their role as a key stakeholder in PM is expected to be pivotal.

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Coyle, Shirley, King-Tong Lau, Niall Moyna, Donal O'Gorman, Dermot Diamond, Fabio Di Francesco, Daniele Costanzo, et al. "BIOTEX—Biosensing Textiles for Personalised Healthcare Management." IEEE Transactions on Information Technology in Biomedicine 14, no. 2 (March 2010): 364–70. http://dx.doi.org/10.1109/titb.2009.2038484.

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Bauer, Denis C., Clara Gaff, Marcel E. Dinger, Melody Caramins, Fabian A. Buske, Michael Fenech, David Hansen, and Lynne Cobiac. "Genomics and personalised whole-of-life healthcare." Trends in Molecular Medicine 20, no. 9 (September 2014): 479–86. http://dx.doi.org/10.1016/j.molmed.2014.04.001.

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11

Jones, Sam, David Barlow, David Smith, Anant Jani, and Muir Gray. "Personalised and population healthcare for higher value." Journal of the Royal Society of Medicine 111, no. 3 (February 12, 2018): 84–87. http://dx.doi.org/10.1177/0141076818758845.

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12

Campean, Felician, Daniel Neagu, Aleksandr Doikin, Morteza Soleimani, Thomas Byrne, and Andrew Sherratt. "Automotive IVHM: Towards Intelligent Personalised Systems Healthcare." Proceedings of the Design Society: International Conference on Engineering Design 1, no. 1 (July 2019): 857–66. http://dx.doi.org/10.1017/dsi.2019.90.

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AbstractUnderpinned by a contemporary view of automotive systems as cyber-physical systems, characterised by progressively open architectures increasingly defined by their interaction with the users and the smart environment, this paper provides a critical and up-to-date review of automotive Integrated Vehicle Health Management (IVHM) systems. The paper discusses the challenges with prognostics and intelligent health management of automotive systems, and proposes a high-level framework, referred to as the Automotive Healthcare Analytic Factory, to systematically collect and process heterogeneous data from across the product lifecycle, towards actionable insight for personalised healthcare of systems.

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FERNANDEZDELAVEGA, C. "Involving patients in their personalised healthcare plan." American Journal of Hypertension 18, no. 5 (May 2005): A227. http://dx.doi.org/10.1016/j.amjhyper.2005.03.620.

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Winfield, Sarah, and Maria Booker. "Personalised care in maternity." British Journal of Midwifery 29, no. 8 (August 2, 2021): 472–74. http://dx.doi.org/10.12968/bjom.2021.29.8.472.

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McDonald, Suzanne, and Jane Nikles. "N-of-1 Trials in Healthcare." Healthcare 9, no. 3 (March 15, 2021): 330. http://dx.doi.org/10.3390/healthcare9030330.

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Holland, JasonP. "The Role of Molecular Imaging in Personalised Healthcare." CHIMIA International Journal for Chemistry 70, no. 11 (November 30, 2016): 787–95. http://dx.doi.org/10.2533/chimia.2016.787.

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Bantel, Carsten, Helen Laycock, Stephen Ward, Charlotte Halmshaw, and Istvan Nagy. "Pain in Intensive Care: A Personalised Healthcare Approach." Journal of the Intensive Care Society 14, no. 4 (October 2013): 312–18. http://dx.doi.org/10.1177/175114371301400408.

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Horgan, Denis, Mary Baker, Peter Riegman, and Chiara Bernini. "Personalised Medicine - Bringing Innovation to the Healthcare System." Biomedicine Hub 2, Suppl. 1 (November 21, 2017): 1–6. http://dx.doi.org/10.1159/000479674.

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Healthcare innovation has never been more prevalent than it is today. But these innovations are only very slowly being embedded into Europe's healthcare systems. There is a huge capacity here in the EU to improve the health and quality of life of all citizens, but the extent to which it is happening is far from optimal. What is ringing out like a bell is that there is a clear need for better focus from policy makers, as this article explains. A policy bridge is required and a conscious decision among the powers-that-be in Europe needs to find a way to harmonise multiple strands of activity and responsibility in the health arena. The end goal will be for the EU to more effectively integrate the incredible advances in science into healthcare systems, for the benefit of all patients.

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Conteduca, Donato. "Photonic Biosensors: Detection, Analysis and Medical Diagnostics." Biosensors 12, no. 4 (April 13, 2022): 238. http://dx.doi.org/10.3390/bios12040238.

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The necessity of personalised diagnoses and ad hoc treatments for individual patients is driving the outbreak of personalised nanomedicine in research and in clinical studies in the healthcare field [...]

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20

Garg, Harita. "Digital twin technology: Revolutionaryto improve personalized healthcare." Science Progress and Research 1, no. 1 (January 1, 2021): 32–34. http://dx.doi.org/10.52152/spr/2021.105.

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Personalized medicine uses fine grained information on individual persons, to pinpoint deviations from the normal. ‘Digital Twins’ in engineering provide a conceptual framework to analyze these emerging data-driven health care practices, as well as their conceptual and ethical implications for therapy, preventative care and human enhancement. Digital Twins stand for a specific engineering paradigm, where individual physical artifacts are paired withdigital models that dynamically reflects the status of those artifacts. Moral distinctions namely may be based on patterns found in these data and the meanings that are grafted on these patterns. Ethical and societal implications of Digital Twins are explored. Digital Twins imply a data-driven approachto health care. This approach has the potential to deliver significant societal benefits, and can function as a social equalizer, by allowing for effective equalizing enhancement interventions. Digital twins will be key to delivering highly personalised treatments and interventions and we will have more explainable AI to rely upon.

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March, Ruth, and Cecilia Schott. "Personalized/Precision Medicine/Personalised Healthcare: the art of giving different names to the same thing?" Personalized Medicine 14, no. 6 (November 2017): 463–66. http://dx.doi.org/10.2217/pme-2017-0073.

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Fergus, Paul, Shamaila Iram, Dhiya Al-Jumeily, Martin Randles, and Andrew Attwood. "Home-Based Health Monitoring and Measurement for Personalised Healthcare." Journal of Medical Imaging and Health Informatics 2, no. 1 (March 1, 2012): 35–43. http://dx.doi.org/10.1166/jmihi.2012.1059.

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23

Yang, Jack Y., and Mary Qu Yang. "Transforming medicine: functional informatics, drug design, and personalised healthcare." International Journal of Functional Informatics and Personalised Medicine 1, no. 1 (2008): 1. http://dx.doi.org/10.1504/ijfipm.2008.018289.

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Chen, Su Shing. "An integrated service for Personalised Healthcare and Wellness (PHW)." International Journal of Functional Informatics and Personalised Medicine 3, no. 2 (2010): 144. http://dx.doi.org/10.1504/ijfipm.2010.037151.

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25

Fraser, Clementine S., and Ricardo J. José. "Insights into Personalised Medicine in Bronchiectasis." Journal of Personalized Medicine 13, no. 1 (January 10, 2023): 133. http://dx.doi.org/10.3390/jpm13010133.

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Bronchiectasis is a heterogenous disease with multiple aetiologies resulting in inflammation and dilatation of the airways with associated mucus production and chronic respiratory infection. The condition is being recognised ever more frequently as the availability of computed tomography increases. It is associated with significant morbidity and healthcare-related costs. With new understanding of the disease process, varying endotypes, identification of underlying causes and treatable traits, the management of bronchiectasis can be increasingly personalised.

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26

Kim, Gun-Woo, and Dong-Ho Lee. "Personalised health document summarisation exploiting Unified Medical Language System and topic-based clustering for mobile healthcare." Journal of Information Science 44, no. 5 (August 9, 2017): 619–43. http://dx.doi.org/10.1177/0165551517722983.

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According to the growing interest in mobile healthcare, multi-document summarisation techniques are increasingly required to cope with health information overload and effectively deliver personalised online healthcare information. However, because of the peculiarities of medical terminology and the diversity of subtopics in health documents, multi-document summarisation must consider technical aspects that are different from those of the general domain. In this article, we propose a personalised health document summarisation system that provides a reliable personal health-related summary to general healthcare consumers via mobile devices. Our system generates a personalised summary from multiple online health documents by exploiting biomedical concepts, semantic types and semantic relations extracted from the Unified Medical Language System (UMLS) and analysing individual health records derived from mobile personal health record (PHR) applications. Furthermore, to increase the diversity and coverage of summarised results and to display them in a user-friendly manner on mobile devices, we create a summary that is categorised into subtopics by grouping semantically related sentences through topic-based clustering. The experimental evaluations demonstrate the effectiveness of our proposed system.

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Emamipour, Sajad, Amber A. W. A. van der Heijden, Giel Nijpels, Petra Elders, Joline W. J. Beulens, Maarten J. Postma, Job F. M. van Boven, and Talitha L. Feenstra. "A personalised screening strategy for diabetic retinopathy: a cost-effectiveness perspective." Diabetologia 63, no. 11 (July 31, 2020): 2452–61. http://dx.doi.org/10.1007/s00125-020-05239-9.

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Abstract Aims/hypothesis In this study we examined the cost-effectiveness of three different screening strategies for diabetic retinopathy: using a personalised adaptive model, annual screening (fixed intervals), and the current Dutch guideline (stratified based on previous retinopathy grade). Methods For each individual, optimal diabetic retinopathy screening intervals were determined, using a validated risk prediction model. Observational data (1998–2017) from the Hoorn Diabetes Care System cohort of people with type 2 diabetes were used (n = 5514). The missing values of retinopathy grades were imputed using two scenarios of slow and fast sight-threatening retinopathy (STR) progression. By comparing the model-based screening intervals to observed time to develop STR, the number of delayed STR diagnoses was determined. Costs were calculated using the healthcare perspective and the societal perspective. Finally, outcomes and costs were compared for the different screening strategies. Results For the fast STR progression scenario, personalised screening resulted in 11.6% more delayed STR diagnoses and €11.4 less costs per patient compared to annual screening from a healthcare perspective. The personalised screening model performed better in terms of timely diagnosis of STR (8.8% less delayed STR diagnosis) but it was slightly more expensive (€1.8 per patient from a healthcare perspective) than the Dutch guideline strategy. Conclusions/interpretation The personalised diabetic retinopathy screening model is more cost-effective than the Dutch guideline screening strategy. Although the personalised screening strategy was less effective, in terms of timely diagnosis of STR patients, than annual screening, the number of delayed STR diagnoses is low and the cost saving is considerable. With around one million people with type 2 diabetes in the Netherlands, implementing this personalised model could save €11.4 million per year compared with annual screening, at the cost of 658 delayed STR diagnoses with a maximum delayed time to diagnosis of 48 months. Graphical abstract

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Stefanicka-Wojtas, Dorota, and Donata Kurpas. "Barriers and Facilitators to the Implementation of Personalised Medicine across Europe." Journal of Personalized Medicine 13, no. 2 (January 23, 2023): 203. http://dx.doi.org/10.3390/jpm13020203.

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(1) Background: Personalised medicine (PM) is an innovative way to produce better patient outcomes by using an individualised or stratified approach to disease and treatment rather than a collective approach to treating patients. PM is a major challenge for all European healthcare systems. This article aims to identify the needs of citizens in terms of PM adaptation, as well as to provide insights into the barriers and facilitators categorised in relation to key stakeholders of their implementation. (2) Methods: This article presents data obtained from the survey “Barriers and facilitators of Personalised Medicine implementation—qualitative study under Regions4PerMed (H2020) project”. Semi-structured questions were included in the above-mentioned survey. The questions included both structured and unstructured segments in an online questionnaire (Google Forms). Data were compiled into a data base. The results of the research were presented in the study. The number of people who participated in the survey can be considered an insufficient sample size for statistical measurement. In order to avoid collecting unreliable data, the questionnaires were sent to various stakeholders of the Regions4PerMed project, which includes members of the Advisory Board of the Regions4PerMed Project, but also speakers of conferences and workshops, and participants in these events. The professional profiles of the respondents are also diverse. (3) Results: The insights on what would help in the adaptation of Personal Medicine to citizen needs have been categorised into 7 areas of need: education; finances; dissemination; data protection/IT/data sharing; system changes/governmental level; cooperation/collaboration; public/citizens. Barriers and facilitators have been categorised into ten key stakeholders of the implementation barriers: government and government agencies; medical doctors/practitioners; healthcare system; healthcare providers; patients and patient organisations; medical sector, scientific community, researchers, stakeholders; industry; technology developers; financial institutions; media. (4) Conclusions: Barriers to the implementation of Personalised Medicine are observed across Europe. The barriers and facilitators mentioned in the article need to be effectively managed in healthcare systems across Europe. There is an urgent need to remove as many barriers as possible and create as many facilitators as possible to implement personalized medicine in the European system.

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Ahamed, Farhad, Farnaz Farid, Basem Suleiman, Zohaib Jan, Luay A. Wahsheh, and Seyed Shahrestani. "An Intelligent Multimodal Biometric Authentication Model for Personalised Healthcare Services." Future Internet 14, no. 8 (July 26, 2022): 222. http://dx.doi.org/10.3390/fi14080222.

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With the advent of modern technologies, the healthcare industry is moving towards a more personalised smart care model. The enablers of such care models are the Internet of Things (IoT) and Artificial Intelligence (AI). These technologies collect and analyse data from persons in care to alert relevant parties if any anomaly is detected in a patient’s regular pattern. However, such reliance on IoT devices to capture continuous data extends the attack surfaces and demands high-security measures. Both patients and devices need to be authenticated to mitigate a large number of attack vectors. The biometric authentication method has been seen as a promising technique in these scenarios. To this end, this paper proposes an AI-based multimodal biometric authentication model for single and group-based users’ device-level authentication that increases protection against the traditional single modal approach. To test the efficacy of the proposed model, a series of AI models are trained and tested using physiological biometric features such as ECG (Electrocardiogram) and PPG (Photoplethysmography) signals from five public datasets available in Physionet and Mendeley data repositories. The multimodal fusion authentication model shows promising results with 99.8% accuracy and an Equal Error Rate (EER) of 0.16.

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Horgan, Denis, and Mario Pazzagli. "Prevention, Early Dialogue and Education in the Personalised Healthcare Era." Biomedicine Hub 2, Suppl. 1 (November 21, 2017): 1–11. http://dx.doi.org/10.1159/000479492.

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In the EU, the “portrait” of healthcare has undergone many changes down the years, with many adaptations as the EU has evolved. The role of patients has become much more significant as they have gained greater knowledge; there have been giant leaps in innovation, while societal changes and issues (such as the ageing population) have led to different priorities. Today's portrait of healthcare features many perspectives, schools of thought and approaches coming from different stakeholders, different Member States and even different regions within those Member States. One thing that has become very clear is that a one-size-fits-all approach to treatment is outmoded, wasteful and often counterproductive to the health of patients. This includes, in these days of increasing co-morbidities, treating one disease separately, rather than looking at the patient's health issues as a whole. Meanwhile, citizens are being bombarded with often contradictory messages regarding what is “good” or “bad” for them, often in a patronising manner, while the realities of extremely effective preventative measures are often obscured, with a lack of emphasis on screening and early diagnosis. The authors argue that, among other matters, better communication and education are key to improving healthcare in Europe.

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Qi, Jun, Po Yang, Geyong Min, Oliver Amft, Feng Dong, and Lida Xu. "Advanced internet of things for personalised healthcare systems: A survey." Pervasive and Mobile Computing 41 (October 2017): 132–49. http://dx.doi.org/10.1016/j.pmcj.2017.06.018.

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Alivia, Mauro, Paola Guadagni, and Paolo Roberti di Sarsina. "Towards salutogenesis in the development of personalised and preventive healthcare." EPMA Journal 2, no. 4 (November 8, 2011): 381–84. http://dx.doi.org/10.1007/s13167-011-0131-9.

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Finnikin, Sam. "Supporting shared decision making in general practice." Practice Management 30, no. 3 (March 2, 2020): 14–16. http://dx.doi.org/10.12968/prma.2020.30.3.14.

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Steele, Rachel, and Paul A. Tiffin. "‘Personalised evidence’ for personalised healthcare: integration of a clinical librarian into mental health services – a feasibility study." Psychiatric Bulletin 38, no. 1 (February 2014): 29–35. http://dx.doi.org/10.1192/pb.bp.112.042382.

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Aims and methodTo evaluate the feasibility of integrating a clinical librarian (CL) within four mental health teams. A CL was attached to three clinical teams and the Trustwide Psychology Research and Clinical Governance Structure for 12 months. Requests for evidence syntheses were recorded. The perceived impact of individual evidence summaries on staff activities was evaluated using a brief online questionnaire.ResultsOverall, 82 requests for evidence summaries were received: 50% related to evidence for individual patient care, 23% to generic clinical issues and 27% were on management/corporate topics. In the questionnaires 105 participants indicated that the most common impact on their practice was advice given to colleagues (51 respondents), closely followed by the evidence summaries stimulating new ideas for patient care or treatment (50 respondents).Clinical implicationsThe integration of a CL into clinical and corporate teams is feasible and perceived as having an impact on staff activities. A CL may be able to collate ‘personalised evidence’ which may enhance individualised healthcare. In some cases the usual concept of a hierarchy of evidence may not easily apply, with case reports providing guidance which may be more applicable than population-based studies.

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McDonald, Annabel, Jessica A. Eccles, Sanaz Fallahkhair, and Hugo D. Critchley. "Online psychotherapy: trailblazing digital healthcare." BJPsych Bulletin 44, no. 2 (October 7, 2019): 60–66. http://dx.doi.org/10.1192/bjb.2019.66.

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Advances in digital technology have a profound impact on conventional healthcare systems. We examine the trailblazing use of online interventions to enable autonomous psychological care which can greatly enhance individual- and population-level access to services. There is strong evidence supporting online cognitive–behavioural therapy and more engaging programmes are now appearing so as to reduce user ‘attrition’. The next generation of autonomous psychotherapy programmes will implement adaptive and personalised responses, moving beyond impersonalised advice on cognitive and behavioural techniques. This will be a more authentic form of psychotherapy that integrates therapy with the actual relationship experiences of the individual user.

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Cazap, Eduardo. "Personalised Cancer Care – A Global Perspective." European Oncology & Haematology 10, no. 02 (2014): 104. http://dx.doi.org/10.17925/eoh.2014.10.2.104.

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Much debate surrounds the matter of personalised medicine. The problem of new treatments at high costs is usually mentioned in relation with inequalities and problems of access to care. But there is also an urgent need to discuss the impossibility for many healthcare systems in the world to provide myriad new diagnostic procedures and treatments to all populations. In this editorial, the current situation from a global perspective will be analysed and the position of some of the leading cancer organisations will be presented. We also discuss some possible actions to be developed to overcome this urgent and contradictory situation.

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Cesuroglu, Tomris, Elena Syurina, Frans Feron, and Anja Krumeich. "Other side of the coin for personalised medicine and healthcare: content analysis of ‘personalised’ practices in the literature." BMJ Open 6, no. 7 (July 2016): e010243. http://dx.doi.org/10.1136/bmjopen-2015-010243.

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Pryazhnikova, Olga. "INNOVATIVE APPROACHES TO DEVELOPMENT OF HEALTHCARE IN THE ASIAN REGION." Vostokovedenie i Afrikanistika, no. 3 (2021): 113–22. http://dx.doi.org/10.31249/rva/2021.03.10.

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The spread of mobile communication and use of advanced methods of prevention and treatment stimulate the development of mobile healthcare and personalised medicine in Asian countries. New methods in health care, first of all, preserving the health of the population in the face of increasing life expectancy.

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Majellano, Eleanor C., Vanessa L. Clark, Rebecca F. McLoughlin, Peter G. Gibson, and Vanessa M. McDonald. "Using a knowledge translation framework to identify health care professionals’ perceived barriers and enablers for personalised severe asthma care." PLOS ONE 17, no. 6 (June 7, 2022): e0269038. http://dx.doi.org/10.1371/journal.pone.0269038.

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Background Whilst multidimensional assessment enables the detection of treatable traits in severe asthma and has the potential to improve patient outcomes, healthcare disparities exist, and little is known about the factors influencing optimal management in severe asthma. This study aimed to explore perceived barriers, and enablers to implementing personalised care in severe asthma, from the healthcare professionals’ perspective. Methods A descriptive, qualitative study involving a single focus group (n = 7) and semi-structured interviews (n = 33) with multidisciplinary healthcare professionals involved in severe asthma care was conducted. A hybrid thematic and content analysis was undertaken to identify themes, which were then deductively mapped to the Theoretical Domains Framework (TDF). Results Overall, three emergent themes were identified: (1) Barriers- (2) Enablers- to optimal management; (3) Desired model of care. Across all TDF domains, 6 constructs influenced development and implementation of optimal care: (1) belief about consequences, (2) environmental context and resources, (3) belief about capabilities, (4) social/professional role and identity, (5) goals and (6) knowledge. Conclusion Implementation of personalised care in severe asthma is complex and non-linear. The use of a theory-based approach effectively demonstrated how a variety of behaviours could be targeted to optimise and promote personalised care in different clinical setting.

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Dimopoulos-Bick, Tara, Kim E. Clowes, Katie Conciatore, Maggie Haertsch, Raj Verma, and Jean-Frederic Levesque. "Barriers and facilitators to implementing playlists as a novel personalised music intervention in public healthcare settings in New South Wales, Australia." Australian Journal of Primary Health 25, no. 1 (2019): 31. http://dx.doi.org/10.1071/py18084.

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Listening to personalised music is a simple and low-cost intervention with expected therapeutic benefits, including reduced agitation, stress responses and anxiety. While there is growing evidence for the use of personalised music as a therapeutic intervention, there has been little investigation into processes and strategies that would support the implementation of playlists. The aim of this study was to identify the perceived barriers and facilitators to implementing personalised playlists on a large scale in public healthcare settings. A mixed-methods approach was used to evaluate the feasibility of the intervention in 21 different acute, sub-acute and primary healthcare settings in New South Wales (NSW), Australia, between June 2016 and June 2017. Data collection included 153 survey responses (staff n=35, patients n=49 and family members n=69), six focus groups (staff n=21) and an analysis of 37 documents. Data sources were systematically categorised using a Policy Analysis Framework. Facilitators included the use of implementation leads and volunteers, a high level of staff engagement and the integration of music selection and playlist development into routine clinical practice. Barriers included ongoing and unexpected funding, time to prepare playlists and staff turnover. The results from this study support the feasibility and acceptability of implementing playlists in different healthcare settings.

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Wang, Ye Diana, Gloria Phillips-Wren, and Guisseppi Forgionne. "E-delivery of personalised healthcare information to intermediaries for suicide prevention." International Journal of Electronic Healthcare 1, no. 4 (2005): 396. http://dx.doi.org/10.1504/ijeh.2005.006687.

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Velikova, Marina, Josien Terwisscha van Scheltinga, Peter J. F. Lucas, and Marc Spaanderman. "Exploiting causal functional relationships in Bayesian network modelling for personalised healthcare." International Journal of Approximate Reasoning 55, no. 1 (January 2014): 59–73. http://dx.doi.org/10.1016/j.ijar.2013.03.016.

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Miles, Andrew, Michael Loughlin, and Andreas Polychronis. "Evidence-based healthcare, clinical knowledge and the rise of personalised medicine." Journal of Evaluation in Clinical Practice 14, no. 5 (October 2008): 621–49. http://dx.doi.org/10.1111/j.1365-2753.2008.01094.x.

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Van Dyck, Walter, Daniel Gassull, Gergely Vértes, Prateek Jain, Muhilan Palaniappan, Duane Schulthess, Erik Tambuyzer, Richard Hudson, and Nuala Moran. "Unlocking the value of personalised healthcare in Europe—breast cancer stratification." Health Policy and Technology 1, no. 2 (June 2012): 63–68. http://dx.doi.org/10.1016/j.hlpt.2012.04.006.

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Rafi, Imran, Judith Hayward, and Corinna Alberg. "General practice and genomics." InnovAiT: Education and inspiration for general practice 10, no. 2 (November 10, 2016): 69–72. http://dx.doi.org/10.1177/1755738016666571.

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Clinicians have always personalised patient management. There is a growing momentum to improve this further through the integration of genomic information into clinical care. This will incorporate powerful new tools, through which clinicians can further tailor healthcare, improving disease prevention, prediction, diagnosis and treatment. This article aims to suggest ways in which this revolution in healthcare will affect GPs.

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Western, Max J., Dylan Thompson, Oliver J. Peacock, and Afroditi Stathi. "The impact of multidimensional physical activity feedback on healthcare practitioners and patients." BJGP Open 3, no. 1 (February 5, 2019): bjgpopen18X101628. http://dx.doi.org/10.3399/bjgpopen18x101628.

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BackgroundPromotion of physical activity in primary care has had limited success. Wearable technology presents an opportunity to support healthcare practitioners (HCPs) in providing personalised feedback to their patients.AimTo explore the differing thoughts and feelings of both HCPs and at-risk patients provided with personalised multidimensional physical activity feedback.Design & settingQualitative study with HCPs (n = 15) and patients at risk of cardiovascular disease or type 2 diabetes (n = 29), recruited from primary care.MethodHCPs and patients wore a physical activity monitor for 7 days and were subsequently shown their personalised multidimensional feedback, including sedentary time, calorie burn, short (1-minute) or long (>10-minute) bouts of moderate-to-vigorous activity during semi-structured interviews. Transcripts were analysed thematically with comparisons made between individuals of high (n = 21) and low (n = 23) physical activity levels as to their cognitive–affective responses to their data.ResultsPersonalised feedback elicited positive emotional responses for highly active participants and negative emotional responses for those with low activity. However, individuals with low activity demonstrated largely positive coping mechanisms. Some low active participants were in denial over feedback, but the majority valued it as an opportunity to think of ways to improve physical activity (cognitive reappraisal) and started forming action plans (problem-focused coping). Around half of all participants also sought to validate their feedback against peers.ConclusionPersonalised, visual feedback elicits immediate emotional and coping responses in participants of high and low physical activity levels. Further studies should explore whether multidimensional feedback could help practitioners explore diverse ways for lifestyle change with patients.

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Hood, Christopher C., and Sarah Bougourd. "Research Essay." International Journal of E-Health and Medical Communications 2, no. 2 (April 2011): 82–85. http://dx.doi.org/10.4018/ijehmc.201104012011040106.

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Some online health information and services have the potential to mislead, confuse or create unnecessary anxiety and more should be done to help people find trustworthy health websites and use online health services safely and effectively, says a new report on the ethics of ‘personalised healthcare’ (Nuffield Council on Bioethics, 2010). In September 2008, the UK Nuffield Council on Bioethics established a Working Party to consider the ethical issues raised by developments in medical profiling and online medicine that promise more ‘personalised healthcare’. The resulting report, published in October 2010, makes a number of policy and practice recommendations for providers and users of e-health services. This article highlights the recommendations made in three of the report’s e-health case studies: online health information, online personal health records, and telemedicine.

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Horgan, Denis, and Walter Ricciardi. "Leviathan, or the Rudder of Public Health." Biomedicine Hub 2, Suppl. 1 (November 21, 2017): 1–8. http://dx.doi.org/10.1159/000479490.

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In the world of modern health, despite the fact that we've been blessed with amazing advances of late - the advent of personalised medicine is just one example - “change” for most citizens seems slow. There are clear discrepancies in availability of the best care for all, the divisions in access from country to country, wealthy to poor, are large. There are even discrepancies between regions of the larger countries, where access often varies alarmingly. Too many Member States (with their competence for healthcare) appear to be clinging stubbornly to the concept of “one-size-fits-all” in healthcare and often stifle advances possible through personalised medicine. Meanwhile, the legislative arena encompassing health has grown big and unwieldy in many respects. And bigger is not always better. The health advances spoken of above, an increased knowledge on the part of patients, the emergence of Big Data and more, are quickly changing the face of healthcare in Europe. But healthcare thinking across the EU isn't changing fast enough. The new technologies will certainly speak for themselves, but only if allowed to do so. Acknowledging that, this article highlights a positive reform agenda, while explaining that new avenues need to be explored.

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Chung, Kian Fan. "Personalised medicine in asthma: time for action." European Respiratory Review 26, no. 145 (September 27, 2017): 170064. http://dx.doi.org/10.1183/16000617.0064-2017.

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Asthma is a heterogeneous disease comprising several phenotypes driven by different pathways. To define these phenotypes or endotypes (phenotypes defined by mechanisms), an unbiased approach to clustering of various omics platforms will yield molecular phenotypes from which composite biomarkers can be obtained. Biomarkers can help differentiate between these phenotypes and pinpoint patients suitable for specific targeted therapies – the basis for personalised medicine. Biomarkers need to be linked to point-of-care biomarkers that may be measured readily in exhaled breath, blood or urine. The potential for using mobile healthcare approaches will help patient enpowerment, an essential tool for personalised medicine. Personalised medicine in asthma is not far off – it is already here, but we need more tools and implements to carry it out for the benefit of our patients.

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Stefanicka-Wojtas, Dorota, and Donata Kurpas. "Personalised Medicine—Implementation to the Healthcare System in Europe (Focus Group Discussions)." Journal of Personalized Medicine 13, no. 3 (February 21, 2023): 380. http://dx.doi.org/10.3390/jpm13030380.

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Background: Personalized medicine (PM) is an approach based on understanding the differences between patients with the same disease and represents a change from the “one size fits all” concept. According to this concept, appropriate therapies should be selected for specific groups of patients. PM makes it possible to predict whether a particular therapy will be effective for a particular patient. PM will still have to overcome many challenges and barriers before it can be successfully implemented in healthcare systems. However, it is essential to remember that PM is not a medical revolution but an evolution. Methods: Three focus groups were conducted, to achieve the purpose of this study, which was to identify the barriers and facilitators existing to the implementation of PM and to highlight existing practices in European countries. Focus group discussions covered the areas of barriers and facilitators to the implementation of personalized medicine. Results: This section describes the results of the focus groups that covered the areas of barriers and facilitators of personalized medicine implementation. Conclusions: Personalized medicine faces many challenges and barriers before it can be successfully implemented in health systems. The translation of PM to European countries, differences in regulations, high costs of new technologies, and reimbursement are the reasons for the delay in PM implementation.

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