One application of personalized medicine is the tailoring of medication to the individual, so that the medication will have the highest chance of success. In order to individualize medication, one must have a complete inventory of all current pharmaceutical compounds (a detailed formulary) combined with pharmacogenetic datasets, the genetic makeup of the patient, their (medical) family history and other health-related data. For healthcare professionals to make the best use of this information, it must be visualized in a way that makes the most medically relevant data accessible for their decision-making. Similarly, to enable bioinformatics analysis of these data, it must be prepared and provided through an interface for controlled computational analysis. Due to the high degree of personal information gathered for such initiatives, privacy-sensitive implementation choices and ethical standards are paramount. The Personal Genetic Locker project provides an approach to enable the use of personal genomic data in primary care. In this paper, we provide a description of the Personal Genetic Locker project and show its utility through a use case based on open standards, which is illustrated by the 4MedBox system.
Many patients with lifestyle-related chronic diseases find it difficult to adhere to a healthy and active lifestyle, often due to psychosocial difficulties. The aim of the current study was to develop an eHealth care pathway aimed at detecting and treating psychosocial and lifestyle-related difficulties that fits the needs and preferences of individual patients across various lifestyle-related chronic diseases. Each intervention component was developed by (1) developing initial versions based on scientific evidence and/or the Behavior Change Wheel; (2) co-creation: acquiring feedback from patients and health professionals; and (3) refining to address users’ needs. In the final eHealth care pathway, patients complete brief online screening questionnaires to detect psychosocial and lifestyle-related difficulties, i.e., increased-risk profiles. Scores are visualized in personal profile charts. Patients with increased-risk profiles receive complementary questionnaires to tailor a 3-month guided web-based cognitive behavioral therapy intervention to their priorities and goals. Progress is assessed with the screening tool. This systematic development process with a theory-based framework and co-creation methods resulted in a personalized eHealth care pathway that aids patients to overcome psychosocial barriers and adopt a healthy lifestyle. Prior to implementation in healthcare, randomized controlled trials will be conducted to evaluate its cost-effectiveness and effectiveness on psychosocial, lifestyle, and health-related outcomes.
Background Kidney failure and dialysis treatment have a large impact on a patient’s life. Patients experience numerous, complex symptoms and usually have multiple comorbid conditions. Despite the multitude of problems, patients often have priorities for improvement of specific aspects of their functioning, which would be helpful for clinicians to become informed of. This highlights a clear need for patient-centered care in this particular patient group, with routine screening as a vital element to timely recognize symptoms and tailored treatment to match individual patients’ needs and priorities. By also providing feedback on patient’s screening results to the patient itself, the patient is empowered to actively take control in one’s mostly uncontrollable disease process. The current paper describes the study design of a multicenter randomized controlled trial evaluating the effectiveness of the “E-HEealth treatment in Long-term Dialysis” (E-HELD) intervention. This therapist-guided Internet-based cognitive-behavioral therapy (ICBT) intervention is focused on and personalized to the myriad of problems that dialysis patients experience and prioritize. Methods After a screening procedure on adjustment problems, 130 eligible dialysis patients will be randomized to care as usual or the E-HELD intervention. Patients will complete questionnaires on distress (primary outcome measure), several domains of functioning (e.g., physical, psychological, social), potential predictors and mediators of treatment success, and the cost-effectiveness of the intervention, at baseline, 6-month follow-up, and 12-month follow-up. In addition, to take account of the personalized character of the intervention, the Personalized Priority and Progress Questionnaire (PPPQ) will be administered which is a personalized instrument to identify, prioritize, and monitor individual problems over time. Discussion The present study design will provide insight in the effectiveness of tailored ICBT in patients with kidney failure who are treated with dialysis. When proven effective, the screening procedure and the subsequent ICBT intervention could be implemented in routine care to detect, support, and treat patients struggling with adjustment problems. Trial registration NL63422.058.17 [Registry ID: METC-LDD] NL7160 [Netherlands Trial Register; registered on 16 July 2018]
Ongoing health challenges, such as the increased global burden of chronic disease, are increasingly answered by calls for personalized approaches to healthcare. Genomic medicine, a vital component of these personalization strategies, is applied in risk assessment, prevention, prognostication, and therapeutic targeting. However, several practical, ethical, and technological challenges remain. Across Europe, Personal Health Data Space (PHDS) projects are under development aiming to establish patient-centered, interoperable data ecosystems balancing data access, control, and use for individual citizens to complement the research and commercial focus of the European Health Data Space provisions. The current study explores healthcare users’ and health care professionals’ perspectives on personalized genomic medicine and PHDS solutions, in casu the Personal Genetic Locker (PGL). A mixed-methods design was used, including surveys, interviews, and focus groups. Several meta-themes were generated from the data: (i) participants were interested in genomic information; (ii) participants valued data control, robust infrastructure, and sharing data with non-commercial stakeholders; (iii) autonomy was a central concern for all participants; (iv) institutional and interpersonal trust were highly significant for genomic medicine; and (v) participants encouraged the implementation of PHDSs since PHDSs were thought to promote the use of genomic data and enhance patients’ control over their data. To conclude, we formulated several facilitators to implement genomic medicine in healthcare based on the perspectives of a diverse set of stakeholders.
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