Towards a systems approach for chronic diseases, based on health state modeling

A new paradigm of hearing loss and preservation with cochlear implants: Learnings from fundamental studies and clinical research

In 2010 Cochlear initiated a coordinated preclinical research program to identify the factors and underlying mechanisms of acoustic hearing loss following cochlear implantation and device use. At its inception the program was structured around several major hypotheses implicated in the loss of acoustic hearing. The understanding of causes evolved over the course of the program, leading to an increased appreciation of the role of the biological response in post-implant hearing loss. A systematic approach was developed which mapped the cochlear implant journey along a timeline that considers all events in an individual's hearing history. By evaluating the available data in this context, rather than by discrete hypothesis testing, causative and associated factors may be more readily detected. This approach presents opportunities for more effective research management and may aid in identifying new prospects for intervention. Many of the outcomes of the research program apply beyond preservation of acoustic hearing to factors important to overall cochlear health and considerations for future therapies.

Redefining and Validating Digital Biomarkers as Fluid, Dynamic Multi-Dimensional Digital Signal Patterns

"Digital biomarker" is a term broadly and indiscriminately applied and often limited in its conceptualization to mimic well-established biomarkers as defined and approved by regulatory agencies such as the United States Food and Drug Administration (FDA). There is a practical urgency to revisit the definition of a digital biomarker and expand it beyond current methods of identification and validation. Restricting the promise of digital technologies within the realm of currently defined biomarkers creates a missed opportunity. A whole new field of prognostic and early diagnostic digital biomarkers driven by data science and artificial intelligence can break the current cycle of high healthcare costs and low health quality that is being driven by today's chronic disease detection and treatment approaches. This new class of digital biomarkers will be dynamic and require developing new FDA approval pathways and next-generation gold standards.

Factors affecting the quality and reliability of online health information

Background

Internet represents a relevant source of information, but reliability of data that can be obtained by the web is still an unsolved issue. Non-reliable online information may have a relevance, especially in taking decisions related to health problems. Uncertainties on the quality of online health data may have a negative impact on health-related choices of citizens.

Objective

This work consisted in a cross-sectional literature review of published papers on online health information. The two main research objectives consisted in the analysis of trends in the use of health web sites and in the quality assessment and reliability levels of web medical sites.

Methods

Literature research was made using four digital reference databases, namely PubMed, British Medical Journal, Biomed, and CINAHL. Entries used were “trustworthy of medical information online,” “survey to evaluate medical information online,” “medical information online,” and “habits of web-based health information users”. Analysis included only papers published in English. The Newcastle Ottawa Scale was used to conduct quality checks of selected works.

Results

Literature analysis using the above entries resulted in 212 studies. Twenty-four articles in line with study objectives, and user characteristics were selected. People more prone to use the internet for obtaining health information were females, younger people, scholars, and employees. Reliability of different online health sites is an issue taken into account by the majority of people using the internet for obtaining health information and physician assistance could help people to surf more safe health web sites.

Conclusions

Limited health information and/or web literacy can cause misunderstandings in evaluating medical data found in the web. An appropriate education plan and evaluation tools could enhance user skills and bring to a more cautious analysis of health information found in the web.