Transforming healthcare

The healthcare system has always faced complex organizational challenges, some of which have been exacerbated with the onset of the COVID-19 crisis. The challenge of coordination is especially acute in healthcare organizations because they must ensure that critically ill patients receive the appropriate treatment at the right time, by the right specialists, in the most cost-effective manner possible. Since health services are organized along different professional specializations, the complexity of decisions, control, and coordination around treatment and care delivery is high. Further, the system of healthcare is strictly regulated and faces a growing pressure to offer more patient-centric care, while at the same time requires incorporating timely innovation in treatment and care delivery.

We are drawn to research that can generate a richer understanding of how healthcare organizations can innovate and drive system-wide change while continuing to deliver essential services. This is an ongoing challenge that the public sector faces in Canada and elsewhere. The coordination of expertise is at the heart of how a hospital operates and delivers care. Thus, ensuring that the relevant diagnosis is made, that care is effectively coordinated, and that relevant caregivers are constantly up to date about patient conditions remain an important challenge. Further, healthcare is rapidly moving towards precision medicine, which offers the potential of better treatment through the integration of genetic information and an increasing array of knowledge objects and digital representations.

In healthcare, attempts to introduce technologies such as EHR, tele-health, robotics, artificial intelligence (AI) and data analytics, have been welcomed and the promised digital transformation implicit in slogans such as “the hospital of the future” is well under way. Further, healthcare is rapidly moving towards precision medicine, which offers the potential of better treatment through the integration of genetic information and an increasing array of knowledge objects and digital representations. This rapid digitalization now allows for all forms of data to be more easily collected, shared, transformed, and analyzed. However, technological change often does not unfold as planned. As a result, the adoption and implementation of these technologies is likely to raise thorny questions about power relations, role structures, professional boundaries and call into question knowing practices and organizing principles.

Our current focus in medicine and healthcare explores how diagnoses and treatments serve as coordination devices, and how specific technologies (medical and otherwise) affect the coordination of work and offer different collaboration possibilities.

Some of our active research projects:

  • AI is said to offer great advantages for helping solve complex decision making, coordination, and operational decisions in hospitals. In this current study, we intend to trace how AI is integrated into the process of coordinating resources, schedules, and people in the operating rooms (OR suite) at two leading university-affiliated, tertiary care hospitals. For both hospitals the AI is being developed by the same developer but it is likely that the design and operation of the system will diverge given the different local conditions, needs, and cultures. Understanding these similarities and differences may shed light on how emerging technologies like AI can be effectively incorporated into complex coordination processes in healthcare settings. This is an ongoing collaboration with Samer Faraj and Anand Bhardwaj.

  • The move to a new, state-of-the-art medical campus offers the rare opportunity to establish novel ways of working and organizing. However, when long established coordination practices can no longer be carried out in the new space, costly breakdowns may occur, necessitating effortful repair work to reestablish coordination. Through a two-year ethnographic study, we examined how coordination was disrupted and restored following the relocation of a leading Canadian hospital into a newly built and equipped state-of-the-art building. Early findings indicate that established care coordination practices could no longer be sustained in the new setting and have to be reconstituted to address breakdown situations. Our findings highlight the importance of the situation in guiding shared action and the importance of organizing scripts in reassembling a novel coordination ordering. This is an ongoing collaboration between Karla Sayegh and Samer Faraj.

  • Trauma care offers a difficult organizing challenge to a hospital. Specialized trauma bays must be available and a team of highly specialized experts must be on call to respond to the cases arriving at the ED, yet, it is a challenge to know ahead of time the kind of injury and the number of trauma victims that have to be attended to. The challenge is acute for hospital in a resource-constrained system. Today, innovative AI prediction algorithms are being developed to allow for ahead of time prediction of the trauma load that a hospital will face using a model that analyzes environmental and historic data. We are currently studying efforts in a level-1 trauma center to build and use such a system. This study (collaboration involving Xian Zhu and Samer Faraj) focuses on how trauma care coordination is affected by the participation of a forecasting tool.

  • How publicly-administered hospitals can respond rapidly in crises, maintaining their operations while being part of an interconnected complex healthcare network, is a topic of increasing importance. We have collected over two years' worth of direct observations and strategic decision-making data of a frontline hospital as it responded to the COVID-19 pandemic. We are in the process of theorizing, using manuscripts. This is an ongoing collaboration with Samer Faraj, Fabrice Brunet (former CEO of the CHUM), Kathy Malas and Anand Bhardwaj.

  • Based on field work related to cancer genomics as well as neuroscience consortia We have initiated an innovative program of research to understand how data-intensive science built on the principles of open science is helping spark global health innovation and creating novel knowledge and innovation ecologies. This is an ongoing collaboration with Alberto Cambrosio, Ellen Abrams and Paolo Leone.

  • Precision medicine, also known as personalized medicine, transforms disease diagnosis and offers more appropriate treatment and health prevention. It does so by considering the unique variant of the disease, the individual’s specific genetic makeup, their health history, and their situated environmental and lifestyle markers. This approach allows healthcare providers to make a more accurate diagnosis and create specialist treatment plans. We are studying how a leading hospital in Canada is undertaking the journey toward personalized medicine and health. The fieldwork will follow how the clinicians and designers will address how to render compatible various data repositories that contain mostly clinical (E.g. demographics, diagnoses, and test results) and administrative data (E.g. patient visit, admission, and transfer data) and integrate them with the collecting and storing a variety of “omic” data, such as radiomic (radiological image data), genomic (gene data), proteomic (protein data), metabolomic (metabolism data), exposomic (environmental exposure data). This is an ongoing collaboration with Kathy Malas, Head of Innovation and Artificial Intelligence, CHUM.

  • In critical and intensive care units, the diagnosis of a patient and the ensuing treatment process are best understood from an expertise and knowledge integration perspective. As the patient situation changes, knowledge puzzles are often encountered and require assembling an array of clinical expertise as well as various knowledge objects such as tests and diagnoses. This long-term field work is taking place in the NICU of a Montreal hospital and attempts to uncover regularities and successful strategies in resolving expertise differences. This is an ongoing collaboration between Wadih Renno and Samer Faraj.

  • When hospital units are merged, one assumes that communities of experts in a single occupation settle their practice differences and converge on common practices. We conducted a two-year ethnographic study of how two neonatal intensive care units belonging to Canada's largest hospital network synchronized their care practices in a merger. While scientific knowledge provides a foundation for settling differences, experts often push back against rules because working to them diverges from the established and tacit ways by which experts perform their work (i.e., through intuition and judgement based on experiential knowledge). Thus, the navigation of practices seem to require a complex repertoire of interventions to facilitate practice convergence. This ongoing collaboration of Karla Sayegh, Ann Langley, and Samer Faraj.

  • In Neuroscience, just like in other medical science fields, collaboration dilemmas hinder clinical and scientific advancement. Sharing is challenging in this context, especially for data related to rare diseases, as researchers have a hard time collecting relevant medical cases. Our current research is on the development of a Canadian Open Source Neuroscience platform where novel model collaboration is made possible via the development of sharing work, paper, and even authorship. This is an ongoing collaboration between Paolo Leone and Samer Faraj.

Some representative papers: