Complex collaboration in data-intensive health science
Data-intensive biotechnologies such as genomics and proteomics in biomedical sciences have immensely increased our ability to generate data on an unprecedented scale. Twenty-first century healthcare and life sciences are experiencing a “data deluge” from these high-throughput “Omics” biotechnologies. We are facing the challenges of exponential growth in data volume and variety, generated daily through massively parallel studies of biological pathways. These developments have garnered international attention as seen in the recent release of policy reports about “Science as Open Enterprise” (2012) by the Royal Society, London, UK, and a “National Bioeconomy Blueprint” (2012) by the United States White House. An important focus of these reports is a new form of scientific inquiry, data-intensive massively collaborative science, understood as a rapidly emerging research paradigm that firmly depends on a data commons or “infrastructure science”, and inseparable from the classic “discovery science”.
Healthcare research in 21st century is increasingly data-intensive in nature. A key example is the field of genomics that has transformed towards collective innovation due to the increasing ability of researchers to share and pool their genomic databases. The reduced cost of IT databases and data mining software has further reduced the cost and threshold of collaboration in genomics-driven health research. As we move from a science where data collection was a major challenge and an essential locus of the scientific endeavor to one where data collection is automated or at least made easier and is available in digital form, there is a need to understand the new collaborative possibilities that emerge.
In collaboration with colleagues at the Department of Human Genetics at McGill, we have initiated an innovative program of research to understand how data-intensive science is helping spark global health innovation and evaluating how these new ways of conducting data-intensive health science are creating knowledge ecologies and collective innovation via large consortia and international health collaborations. Among the key issues we are studying:
· As we move from classical Edisonian model of science to a more collective one, how do we develop complex collaboration schemes that support and sustain personalized medicine and the new field of theranostics (convergence of therapeutics and diagnostics research), and postgenomics life sciences more broadly?
· Vaccinomics represents the current entry of data-intensive ‘Omics’ health technologies such as genomics to the practice of classical vaccinology. What forms of complex collaboration, organizing, reward structures and collaborative norms will enable collective action to translate vaccinomics to 21st century vaccines?
· Collective innovation in post-genomic science offers the promise of novel diagnostics as well as customized drug therapies. How do we support collective innovation in the data-enabled sciences? Are consortia and new open science initiatives the best way to proceed?
· Biomedical science in the 21st century is embedded in, and draws from, a digital commons created by data-intensive Omics technologies such as genomics and proteomics. We are currently initiating fieldwork to explore whether the new data-intensive science is adapting basic organizing principles, norms, and rewards from collective action. We will further explore the impact of consortia, data repositories, and new collaborative tools on scientific output and research coordination.
Complex collaboration in knowledge and high reliability teams
The issues of how teams integrate and coordinate their resident expertise, manage knowledge across their team boundaries, generate novel solutions, and are lead to ensure high team performance is an increasingly important issue. While much is known about how to create teams and ensure their performance, much of the literature is based on team design and social psychological processes.
Because our research focuses on teams where expertise is distributed or that need to operate in high reliability settings, we take a knowledge perspective and focus on expertise sharing and knowledge processes and their link to team outcomes. We use a range of methods in our studies ranging from survey methods, network analysis, and in depth qualitative analysis of team practices.
Our research on complex collaboration in knowledge teams has focused on answering some of the following questions:
· What practices do medical teams at a leading trauma center engage in to ensure the timely availability of expertise and to effectively manage unexpected events while maintaining patient safety?
· In the age of teamwork, how do knowledge teams members manage their boundaries? Using data from 64 teams, we have shown how effective knowledge teams engage in boundary work in the form of boundary spanning, buffering, and reinforcement to generate team performance and ensure psychological safety.
· What leadership style works best for knowledge teams? Looking at software development teams, we have found that an empowering leadership style works best compared to a more directive one for team performance.
· How do knowledge differences and lack of familiarity impede the work of cross-functional teams that need to integrate expertise and generate creative solutions rapidly? We identify how such teams were able to co-generate a solution without needing to identify, elaborate, and confront differences and dependencies between the specialty areas.
· Given the varied demands on medical specialists, how do trauma centers ensure the coordination and availability of specialists when trauma teams are activated?
· What is the impact of expertise distribution in a team on performance? Building on innovative team network analysis, we have found that for different kinds of expertise the link with team performance is more complex than generally accepted.
· How do team members and leaders assess the expertise of others and integrate knowledge when collaborating in complex multidisciplinary projects? Our qualitative study of the phenomena identifies some emergent strategies
Complex collaboration and innovation in online communities
Computer networks have enabled the development of new organizational forms of working, coordinating, and sharing knowledge both within and outside organizational boundaries. Much attention has recently been generated by the phenomena of “Web 2.0” or “social media” as a new form of organizing that spans between hierarchy and markets and that relies on computer networks for coordination and collaboration. Thus, this new form of organizing allows novel forms of collaboration to emerge and to be sustained. For us, this new connectivity strengthens complex collaboration within teams and organizations, but also allows the emergence of online communities where individuals, with little familiarity with each other, come together to discuss a shared practice.
Why people go out of their way to help others whom they do not know, or may not even share a common organizational identity with, is a major open question for organizational research. Are generalized reciprocity and preferential attachment the mechanisms that avoid the tragedy of the commons in line with the perspective advanced by Nobel prize winner’s Eleanor Ostrom on how to avoid the tragedy of the commons in public good settings? Our work has specifically engaged the following questions:
· How do we conceptualize collaborations in online communities and what are the tensions that need to be managed in order for knowledge sharing to be fostered?
· Using sophisticated statistical analysis as well as simulation, we have demonstrated that social exchange mechanisms (reciprocity and generalized exchange) explain the structure of online community participation better than the currently dominant preferential attachment mechanism.
· Using data from a North American legal association, we have measured the role of social capital in promoting knowledge exchange in electronic networks of practice.
· What are the affordances and disaffordances of social media for knowledge sharing? A forthcoming CMC paper presents some surprising challenges.
· We know little about leadership in online communities. What are the predictors of leadership in online settings focused on knowledge exchange? Do the emergent leaders occupy certain kinds of network positions? Do they behave differently? Do they use semantic strategies at odds with the general discourse in the community?
· How do we improve knowledge sharing in teams? Is it from making available knowledge sources or is it by having access to trusted experts? Building on an in-depth field study, we open up the black box of the knowledge transformation processes used by individuals in knowledge work and suggest that they depend not only on the type of knowledge source but also task novelty.
Complex collaboration around technology’s materiality, evolution, and appropriation
How does technology emerge, evolve, gets appropriated, and intertwines with the actions of organizational actors? These broad and stubborn questions have been of interest to many organizational scholars. Here is how we approach these questions:
· How do core web technologies evolve and dominant designs win? Using historical data regarding the birth and evolution of the web browser and online search, we examine technology frames, complex collaborations and alliances, and features inscribed in artifacts to offer an evolutionary model of technology development.
· What strategies are most effective for firms to utilize when competing on the web? What kind of partnering portfolio should be used to sustain growth? Using historic data to compare Yahoo and Google, we identify the essential mechanisms and value-creation logics linking partnering portfolios to differences in firm growth.
· If we free ourselves from the features lens imposed by vendors and the technology as external object perspective, can we offer new insight on technology? We offer a relational theory of technology affordances that emphasizes the how materiality becomes intertwined with human agency.
· How do we make sense of changes in Internet technology leadership when economic theories emphasize the importance of lock-in and network externalities as providing an imposing advantage to first movers? Using historic data from the evolution of the browser and search engines, we have developed alternative explanations as to why technology leadership changes.
· The appropriation of complex information technologies in large organizations often takes place over years. The line between design and implementation is seldom clear and institutional constraints are at play. We have developed multiple papers exploring the contest over computerization’s meaning during technology implementation.
Complex collaboration surrounding Health IT
Health IT is often presented as a necessary and important component for reforming health care. Yet, much evidence has emerged as to the challenges present in the appropriation of such technologies. The implementation of HIT is often challenged by complex interfacing issues with other medical systems and patient data inconsistencies, disruptions to work flows, or even failure due to the HIT system’s inability to accommodate the variety of physician practices.
The GCC carefully studies the process of implementation and change as it unfolds using a combination of research methods. We are currently working on the following studies:
· An implementation of an open source (free) Electronic Medical Record (EMR) in Montreal where we are following the work of multiple clinics including an urgent care center. Our emergent findings are focused on workarounds, the impact on patient care, and coordination across specialties.
· We are finishing a study of 3 ambulatory-care clinics implementing a large commercial HIT solution. The clinics differ in terms of population served and local practices. We explore how and why some healthcare service practices became globalized while some remained localized.