Our goal is to have a positive impact on the lives of millions of people worldwide. When we started CovidGraph we always knew that it had enormous potential as a platform.
At HealthECCO we start from User Stories. We want to know that what we are doing is useful and not just scratching a technically interesting itch. Our initial focus was very much on making the lives of Covid-19 Researchers easier, but it quickly became apparent that CovidGraph is a solid foundation for many different applications.
We have come a long way in the last year and on our journey we have spoken to many people from around the world and from different parts of the healthcare system. The discussions we have had, not just with our community but particularly with Trinity Challenge members have helped us to form a strategy for how HealthECCO will develop as an organisation and, perhaps more importantly, how we will develop CovidGraph as a platform. We are much more clear about how we see HealthECCO, CovidGraph (and a suite of supporting applications/utilities) having a positive impact for a variety of stakeholders.
As we stand at present, we will be concentrating our efforts on the following three user groups:
Around the world there are a number of government and non-governmental organisations responsible for the timely generation of guidelines that need to be accurate and appropriate for a given audience and possibly locality. Such organisations, particularly in the developing world, are often stretched for resources and do not always have the capacity or skills to properly interpret or develop robust, harmonised guidelines.
A tool like CovidGraph is well placed to serve as the basis for an application that will help such organisations to conduct basic literature research and to understand the wider scope providing information access where it may previously have been limited.
In addition, by exploring the ongoing integration of relevant data sources combined with effective Natural Language Processing, CovidGraph can present a consolidated view of peer reviewed literature alongside emerging grey literature like donor reports and government policies which can be critical in responding to rapidly evolving situations like the Pandemic.
For Health Workers, particularly those on the front line, decision making is a vital element of their role and better decisions can equate directly to improved outcomes for their patients. Treatment guidelines may refer to underlying studies but rarely provide enough data for a Health Worker to assess whether the evidence applies to their specific patient or situation.
We aim to streamline access to this evidence making it easier for Health Workers to quickly understand the underlying bases of treatment guidelines. We will work with Health Workers to build an application that can fit into their workflows without slowing them down.
This use case naturally complements the Policy Maker use case and there is significant overlap. A tool that can help Health Workers assess the evidence can also help Policy Makers explore the existing landscape.
Data in the healthcare sector is complex and in reality highly connected, but this does not translate into the literature where health information becomes isolated in data silos: undiscovered, unconnected and underused. Combine this with the ever growing mountain of research data and the task of trying to find useful information about any given topic becomes seemingly insurmountable.
CovidGraph was built to solve these problems by systematically connecting information points not only within the literature, but also to related data sets like biomedical concepts, clinical trials and patents. This process allows CovidGraph to present a more realistic data model to Researchers. Connections that are inherent and obvious in the real world are created in the knowledge graph. Adding a layer of Natural Language Processing enhances the quality and number of connections we are able to make between all the elements contained in the knowledge graph regardless of their source.
This means that Researchers are able to quickly find information that relates to, say a gene of interest even if it originates from a completely different speciality or from a database that they would not previously have considered exploring. New avenues to explore are much easier for Researchers to uncover and in the process they can discover other published scientists or institutions working on similar areas.
In addition the time it takes to uncover such information is orders of magnitude faster using CovidGraph than it is using traditional methods. See our Graphs in Action post for more detail.
Bonus Use Case
Even though our efforts will revolve around the three use cases listed above there are spillover benefits for the media, journalists, and by extension, the general public.
The Wider Impact
While the use cases above detail the direct positive impact the HealthECCO ecosystem has on those three groups of stakeholders, the transitive impact should not be forgotten. There is a butterfly effect that magnifies the benefits that HealthECCO has on the wider population. This is especially true in the case of Researchers and Policy Makers whose work can affect the lives of millions.
- Fast, effective research can speed up the time-to-market of new, life-changing treatments.
- The rapid dissemination of clear, evidence based guidelines can help save lives in the face of emerging threats.
- Making the evidence more transparent to individual Health Workers can improve healthcare outcomes for large numbers of patients.
There is a lot of work to be done but we are dedicated and passionate about making a positive impact on the world and will continue to grow our community, build our platform and maximise the potential of HealthECCO.