The 70/30 Dilemma
After a lengthy hiatus, I wanted to make a concerted effort to come back to this blog with a posting that was both timely and of potential use to our readers. After thinking about this for a while, I was struck by a number of meetings I have had of late, both internally at OSU, and at the national level, concerned with informatics research and service in the context of large-scale program, project, and center grants (e.g., CCSG, CTSA, P01’s, etc.). As many of you are most likely and acutely aware, informatics research and development occurs with great frequency in the context of such settings, due to the need to provide systematic information management and analysis support to program-specific scientific projects or cores – needs that do not always come associated with a known best practice or solution, thus necessitating both research AND development in order to satisfy end user requirements. This situation presents both significant benefits and significant challenges. First the good news – by performing such research and development in the context of motivating, scientific use cases, the opportunity exists to demonstrate the efficacy, utility, and impact of such informatics solutions in real world settings with results of interest to the broad biomedical community – an outcome that is not always seen in theoretical informatics research (which is often a factor contributing to the limited uptake of such theoretical constructs or methods). Now, the bad news – most funding agencies make it explicit that such research and development within the confines of a largely service-oriented core or program is not necessarily a positive feature, and often if it is emphasized too heavily when applying for such funding, can be a detriment to the overall proposal. Perhaps even more worrisome is that in many cases, the scientific or clinical PI’s of such program/projects share this perspective. This is clearly a sub-optimal situation, and given the current funding environment, it seems we should re-examine our approach to such research programs in order to ensure we can make the most of our limited resources. Therefore, I would propose the following call to action for the biomedical, informatics, and funding communities:
However, if we are to realize the preceding goals, we must also work to understand what the optimal balance for research and development versus service in such programs is. In my experience, study sections and other funding review processes outside of the immediate informatics community tend to appreciate a roughly 70%/30% split between service and research efforts respectively. However, such an anecdotal finding is limited at best, and more understanding of this balance is needed to establish prevailing best practices that can be accepted by the entire biomedical community. Creating this understanding will require our community to invest in the meta-analytical process of “Research on Research.” If we can achieve such an understanding of this critical split in efforts, we will be much better positions to make the optimal use of resources in our highest yield and most impactful basic science, clinical, and translational research efforts.