Sometime in the mid 1990s, DRIP (data rich, information poor) syndrome was coined to describe the plight of healthcare organizations that were failing to improve their performance despite all the effort and dollars poured into monitoring a never-ending list of success indicators. Sadly, as technological advancements have enabled inexpensive large-scale data generation and digitization, this issue has slowly turned into a bit of a chronic illness. And it’s not just healthcare organizations that are grappling with it, other complex entities including governments and large private companies are impacted too. So why have we not been able to harness advancements in data technology to optimize performance and maximize results? Below we point out three important building blocks for a more solid path forward.

1. Recruit with an eye for uncompromising research excellence

This is the foundation of all successful research endeavours. All the other principles are important – but recruiting and retaining the best researchers is paramount. Although the salary level is important for recruitment, it is not the only factor, and maybe not even the most important factor. Scientists want to be where the action is, where there is opportunity for maximum scientific impact, where there is a stimulating intellectual milieu. This is where the other principles come into play.

2. Focus and foster your strengths

You have to be good at something, not everything. Depth, not breadth. This principle exists at the individual, small group and, depending on size, research institute levels. One could consider focus as the research mission statement. Having a clear focus sets off a cascade of self perpetuating positive outcomes: Scientists are recruited who have complementary skills and a corpus of excellent scientists with a focus is attractive to other scientists. Multi-modality training of students is also maximized and trans-disciplinary interactions are facilitated. And finally, the reputations of the individual scientists and the group are reciprocally enhanced. Lack of focus is a major reason some institutes fail, or perhaps more correctly, never reach their potential.

3. Don’t put the cart (commercialization) before the horse (basic science)

In today’s world, everyone understands the importance of showing the value of research. Product development and commercialization form today’s research zeitgeist. And they should play a prominent role – these are important methods to move science to application. Taxpayers and funding agencies are right to ask what the usefulness of the research is. But there are two enormous pitfalls that often impede doing this right. First, the push toward commercialization of science is often driven not by principle but by money. There is less money for research infrastructure in budgets, and less money for funding research through agencies. In hospitals, there is push and pull between funds for care and for research. Commercialization of science is seen as a money-maker, a way for research to be self-sufficient. This pushes the cart before the horse. The more significant danger is that commercialization becomes the vision of research. There is a push toward more rapidly applied research, with the ease of implementation becoming the research criterion, not the inherent validity of the knowledge being implemented. The truth is that, in any discipline, gathering valid and reliable knowledge before it reaches the stage of value for commercialization takes multiple steps and time. Magnetic resonance imaging is today a very active commercialization activity. However, research into the electromagnetic properties of blood was necessary long before a useful imaging machine could be developed. The horse must pull the cart. 

What we need to think of is how to change the management of research to facilitate a more rapid uptake of basic science, breaking down the barriers between basic and clinical science, between the researchers and product developers, while maintaining the principles of knowledge creation. I talk more about this below.

4. Plan with care and implement with patience

A mission requires a plan. Starting de novo is in some ways easier, since steps to fulfill the mission can be planned and implemented properly. But the major concern in a research start-up is lack of patience. Recruitment can be difficult without a history, and there is a temptation to recruit just to recruit. Recruitment must be judicial. In addition to excellence, new scientists should add value beyond what is already present while at the same time deepening the focus by the addition of new technologies and new knowledge. Research plans often require more than can be afforded by a single research group. The simple answer is partnerships. As in all partnerships, benefits must accrue for all parties.

5. Facilitate the scientific milieu

The scientific environment must be fostered. Scientists, to be creative, must have time to think – I like to call this the “Monastery of the mind”, a time to be creative. Ideas generate hypotheses and analyses of data promote maximum value. At the same time, the research lab should seed the potential of interactions and collaboration to answer questions that an individual scientist might not be able to address. The importance of collegiality in an integrated program has multiple benefits, including an open sharing of knowledge which expedites progress.

6. Invest in systems and practices to couple research and care

In the medical field, there is increasing awareness of inter-individual variability; stated otherwise, there is a push for precision, or personalized medicine. To address this quite overwhelming heterogeneity in patient populations, a different approach to science is required. One needs large samples of patients so that there is adequate representation of the possible multiple factors related to disease development and expression. This requires embedding research into care, and understanding and facilitating the role of clinicians. Improved phenotyping naturally demands a more comprehensive evaluation including clinical and bio- medical biomarkers. Assessments at all levels (history, clinical, imaging, etc.) must be standardized to research quality. Informatics platforms have to be developed to allow sharing of data, with principles for privacy and security. Hospitals and institutions that normally compete must work together for the common good (and somewhat “magically”, sharing data means an increase in research productivity because of so much data gathered). To achieve this level of order and productivity requires an unprecedented level of consensus building and goodwill from all.

Dr. Donald Stuss is the Founding Director of Baycrest’s Rotman Research Institute (RRI) and founding President and Scientific Director of the Ontario Brain Institute. He is an internationally respected neuropsychologist who has expanded scientific understanding of brain function, injury and rehabilitation. Dr. Stuss is also a trailblazer in the field of cognitive neuroscience via his pioneering research into the brain’s frontal lobes. His evolved theory of frontal lobe function and interventions to optimize brain functionality in older adults has been adopted internationally by researchers and clinicians to treat and enhance the well-being of patients with brain injuries. Dr. Stuss led the growth of the Rotman Research Institute and the Ontario Brain Institute into world-class scientific organizations that are founded on a multi-disciplinary and collaborative approach to scientific inquiry and knowledge integration. Dr. Stuss is a member of Spindle’s Senior Advisory Group.