Clinical and Organizational Innovation In Healthcare Organizations June 2001 Jean-Louis Denis, PhD Marie-Dominique Beaulieu, MD, MSc Yann Hébert, PhD (cand.) Ann Langley, PhD Daniel Lozeau, PhD Raynald Pineault, MD, PhD Louise-Hélène Trottier, PhD (cand.) Decision-maker partners: L agence d évaluation des technologies et des modes d intervention en santé (AÉTMIS) Le Collège des médecins du Québec Funded by: Canadian Health Services Research Foundation Fonds de recherche en santé du Québec (FRSQ) HEALNet Agence d'évaluation des technologies et des modes d'intervention en santé (AÉTMIS)
Contact principal investigator at: Jean-Louis Denis Full Professor CHSRF/CIHR Chair Université de Montréal Montreal, Quebec Canada H3T 1A8 Telephone: (514) 343-6031 Fax: (514) 343-2448 E-mail: jean-louis.denis@umontreal.ca This document is available on the Canadian Health Services Research Foundation web site (www.chrsf.ca). For more information on the Canadian Health Services Research Foundation, contact the foundation at: 11 Holland Avenue, Suite 301 Ottawa, Ontario K1Y 4S1 E-mail: communications@chsrf.ca Telephone: (613) 728-2238 Fax: (613) 728-3527 Ce document est disponible sur le site Web de la Fondation canadienne de la recherche sur les services de santé (www.fcrss.ca). Pour de plus amples renseignements sur la Fondation canadienne de la recherche sur les services de santé, communiquez avec la Fondation à l adresse suivante : 11, avenue Holland, bureau 301 Ottawa (Ontario) K1Y 4S1 Courriel : communications@fcrss.ca Téléphone : (613) 728-2238 Télécopier : (613) 728-3527
Clinical and Organizational Innovation In Healthcare Organizations Jean-Louis Denis, PhD 1 Marie-Dominique Beaulieu, MD, MSc 2 Yann Hébert, PhD (cand.) 3 Ann Langley, PhD 4 Daniel Lozeau, PhD 5 Raynald Pineault, MD, PhD 6 Louise-Hélène Trottier, PhD (cand.) 7 1 Full Professor, CHSRF/CIHR Chair, Université de Montréal 2 Full Professor, Chair Dr Sadok Besrour en médecine familiale, Université de Montréal 3 Doctoral student, Université du Québec à Montréal 4 Full Professor, École des Hautes Études Commerciales 5 Assistant Professor, École nationale d administration publique 6 Full Professor, Université de Montréal 7 Doctoral candidate, Université de Montréal Acknowledgements: We thank the Canadian Health Services Research Foundation (CHSRF), Bill 1997-160, the Fonds de recherche en santé du Québec (FRSQ), HEALNet, the Agence d'évaluation des technologies et des modes d'intervention en santé (AÉTMIS) and the Quebec College of Physicians for supporting this study. We also thank the members of the Advisory Committee for their support to start this study. Finally, we also acknowledge all persons who agreed to meet with us throughout this research.
Key Implications for Decision Makers The healthcare sector is characterized by very strong dynamics of innovation. What factors advance or limit the adoption of innovations and what is the role of evidence in this process? Why can innovations with little evidence-based support be widely adopted while others strongly supported by evidence are largely overlooked? The study reveals the following. The dissemination and adoption of clinical and organizational innovations are influenced by players (clinicians, administrators, patients, etc.) who do not see the associated benefits and risks in the same way. The scientific evidence generally covers the hard core of an innovation (for example, effectiveness of a drug) whereas there often is little or no evidence on the strategies that must be developed to promote implementation of innovations (for example, the learning process for a complex new surgical technique). To intervene effectively and influence clinical practices, decision makers and managers must factor in the perceptions of players. They also must consider the status these players give to evidence, their interests, and the values brought into play by the innovations. Organizations would be wise to develop strategies to encourage clinical settings to discuss in detail the benefits and drawbacks of an innovation for patients, clinicians and organizations. Organizations and professionals must exercise some vigilance to promote controlled learning processes designed to limit the risks for patients and maximize the benefits of a clinical innovation. i
Executive Summary To provide better support for disseminating clinical innovations, many suggest using a model of evidence-based medicine. This approach emphasizes the importance of better understanding what helps or limits the adoption of innovations, as well as the role of evidence in these processes. We therefore conducted research guided by four questions: 1) Why can innovations with little evidence-based support be widely adopted while others strongly supported by evidence are largely overlooked? 2) What is the nature of evidence considered in processes for adopting innovations? 3) In what way do relationships between players and organizations in the healthcare system foster or inhibit the adoption of certain innovations? 4) What is the potential role of strategies developed to promote evidence-based medicine in the process of adopting innovations? Implications for managing innovations Decision makers and managers who wish to influence practices must consider the perceptions of players. They must also factor in the status these players give to evidence, their interests, and the values brought into play by innovations. The distribution of benefits and risks among players might explain in part adoption phenomena that appear to be irrational. This distribution also provides a potential mechanism for intervention to ensure the adoption of practices likely to enhance the healthcare system. By acting on this distribution of risks and benefits, they might be able to stimulate the adoption of certain innovations and better control the dissemination of others. The varying ability of clinicians and managers to conduct a critical assessment of the scientific evidence available must also be considered. This is partly why various people will identify a range of legitimate sources for evidence they consider relevant (for example, a clinical setting with a solid reputation, a clinician considered leader, scientific journals, conventions, etc.). Analysis revealed five dilemmas in the regulation of new technologies and healthcare practices: Dilemma # 1: The dissemination and adoption of clinical innovations must be rationally based on solid, clearly defined scientific evidence. Evidence also forms part of a complex social dynamic, which means that players and organizations will not reach the same conclusions on the nature and scope of evidence. Dilemma # 2: Evidence-based medicine gives predominant weight to scientific evidence in the dissemination and adoption of clinical innovations. The scientific evidence associated with a clinical innovation is always partial, which means that dissemination and adoption of clinical innovations are inevitably accompanied by negotiations over the true nature of an innovation and the adaptations required for implementation. ii
Dilemma # 3: The dissemination and adoption of clinical innovations are generally addressed as a rational problem of bringing practices into compliance with standards. Retention of clinical innovations is also dependent on ideological factors and the interests of the players and organizations involved. Dilemma # 4: The dissemination and adoption of clinical innovations require varying periods of experimentation. Experimentation can generate risks and limit the benefits of a clinical innovation. Dilemma # 5: The dissemination and adoption of clinical innovations are often accompanied by pressure for standardization. This means that everyone (players and organizations) agrees, which is not necessarily consistent with innovative dynamics. In general, these dilemmas suggest that the process for disseminating and adopting clinical innovations is related to a rational process in very special circumstances. Thus, the probability of adoption of clinical innovations will be high where: The interests and values of players, groups and organizations may be specifically recognized and, to some extent, are met; and The players, groups and organizations are able to state their preference and develop compromises. It appears that players, groups and organizations place growing importance on scientific evidence where it supports the validity of an innovation. However, where a series of other social and organizational factors favour a clinical innovation, there is little likelihood of widespread adoption with a tight timeline given the evidence available. In this case, there may be fad effects of the type, everyone is doing it, so we must too, in which the presence of serious coercive pressure such as the risk of losing a market may be enough to promote an innovation. This dynamic can be accompanied by a different positioning of the evidence. The evidence could arise during the process to alert players of the risks their new practices may pose. Approach The analysis focused on the process of disseminating four clinical innovations with organizational consequences. The first case involves the use of low molecular weight heparins (LMWH) to treat deep thrombophlebitis. This is a new practice with well established evidence that appears to be gaining wide adoption (a success story). The second case involves a surgical procedure, laparoscopic cholecystectomy. This is a case of over-adoption in which the dissemination curve has far outpaced the emergence of evidence. iii
The third case involves reusable hemodialyzer. This is an ambiguous case for which the dissemination process can be described as cautious. The fourth case, initially described as under-adopt, is intensive monitoring in the community for patients with serious psychiatric problems. The four cases were selected in conjunction with a committee of experts to cover the various options in terms of adoption speed (fast and slow) and the availability of evidence (early, late or ambiguous). For each case, the state of the evidence available and the process of adoption throughout the Montreal area were studied in light of statistical data and 63 in-depth interviews. The analysis was conducted in two phases: first, by identifying the specific issues raised by each case, and then by making comparisons between cases. iv