We are driven by a culture of continuous improvement and innovative thinking. The EBSCO Health Innovation Lab is made up of people who are passionate about developing cutting-edge technology solutions that help patients, clinicians, policymakers, and supporting parties to improve patient care and provide the most useful support for healthcare decision making.
Do you want to be part of the innovation wave? If yes, email us.
Patients want to be able to compare options when they have important decisions to make about treatments and tests. There are limited resources available that make this easy to do and even fewer that can be tailored to individual needs and kept continually current and accurate. EBSCO Health Option Grid decision aids are brief, easy-to-read tools that help patients and healthcare professionals compare healthcare options. Take a look at some sample EBSCO Health Option Grid decision aids.
Physicians and patients want to understand the evidence behind quality measures and the benefits of quality measures. Historically, the scrutiny applied to clinical quality measures has been less than the scrutiny applied to clinical research results and clinical practice guidelines. We are working on a systematic approach to appraising the appropriateness of quality measures. Take a look at a sample appraisal of clinical quality measures in this DynaMed Plus topic.
Evidence-based medicine crosses clinical practice guidelines, clinical decision support, and shared decision making but these three major domains do not necessarily work together seamlessly. We are working with established leaders around the world to collaborate on sharing ideas for how to improve communication and share information. To learn more visit Healthcare Guidance for Patients Society.
Reporting the net effect of an intervention has not been easy to do without complicated statistical solutions. We have developed a calculator that enables clinical researchers and guideline developers to enter the effect estimates and relative importance values for health outcomes and obtain a net effect estimate with 95% confidence interval.
Creating high-quality clinical practice guidelines is labor-intensive. We are working with guideline developers to create protocols to support high-quality guideline development with limited resources. Strategies include taking advantage of databases that systematically identify, appraise and synthesize evidence for clinical application. The goal is to accelerate the time for new guidelines to be developed.
Basic summaries of information that are averaged for a population may not be relevant for an individual patient. Clinical practice guidelines and patient decision aids fall short. Technology can help physicians select multiple options for an individual patient and compare results to select the best approach.