Diffusion of innovation theory for clinical change
Author: Robert W Sanson-Fisher
Published online: 15 March 2004
Abstract
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Maximising the adoption of evidence-based practice has been argued to be a major factor in determining healthcare outcomes. However, there are gaps between evidence-based recommendations and current care.
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Bridging the evidence gap will not be achieved simply by informing clinicians about the evidence.
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One theoretical approach to understanding how change may be achieved is Rogers’ diffusion model. He argues that certain characteristics of the innovation itself may facilitate its adoption. Other factors infuencing acceptance include promotion by influential role models, the degree of complexity of the change, compatibility with existing values and needs, and the ability to test and modify the new procedure before adopting it.
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The diffusion model may provide valuable insights into why some practices change and others do not, as well as guiding those who try to effect adoption of best-evidence practice.
The adoption of a new clinical behaviour by a clinician and healthcare system is a consequence of multiple factors, with research evidence being only one. Research on the diffusion or adoption of innovations suggests that a number of themes come into play. For example, the willingness to use new drugs is influenced by the physician’s sex, specialty, medical school, years since graduation, practice location and practice volume, and the relative proportion of elderly patients in the physician’s practice.1
Rogers2 has developed one of the better-known theoretical approaches to diffusion of innovation. This theoretical framework is helpful when determining the adoption of specific clinical behaviours and when deciding which components will require additional effort if diffusion is to occur. It includes a consideration of aspects of the innovation (or new technology), style of communication, steps in decision making, and the social context.
According to Rogers2 there are five elements of a new or substitute clinical behaviour that will each partly determine whether adoption or diffusion of a new activity will occur: relative advantage, compatibility, complexity, trialability and observability.
To increase the probability of adoption, the innovation must address an issue that clinicians or others perceive to be a problem. For example, a new procedure that enables early detection of a life-threatening illness is likely to be adopted. Early screening tests are compatible with medical beliefs that early detection of disease is beneficial. Consequently, tests and procedures that appear to offer this capacity are more likely to be adopted. Real-life examples include the rapid adoption of mammography screening3,4 and testing for prostate cancer,5 despite some debate about their effectiveness.
“Complexity” is a measure of the degree to which an innovation is perceived as difficult to understand and use. A clinical procedure is more likely to be adopted if it is simple and well defined. For example, altering a patient’s drug regimen is relatively simple, and thus changes in drug therapy can occur rapidly. In contrast, preventive activities such as detecting and treating patients with hazardous alcohol consumption6 and smoking7 have not been adopted quickly, in spite of the potential health gain. This may, at least in part, be a result of the complexity of these activities. Attempts to intervene at the level of primary prevention may be hampered by patients’ resistance and their lack of accuracy in self-reporting risk behaviours. Moreover, some clinicians may have insufficient expertise in the consulting skills necessary to achieve change.
“Observability” is the degree to which the results of the innovation are visible to others. “Visibility” of an innovation stimulates peer discussion, as colleagues of a clinician adopting a new procedure often request information about it. If respected and influential clinicians argue for and demonstrate the application of a new procedure or treatment approach, it is likely to have a positive impact upon adoption rates.8 The more charismatic the person providing the role model, the greater the chance that a greater number of other professionals will adopt the advocated change in clinical behaviour. In surgery, new techniques are often adopted very quickly, as there is a common perception that there are disadvantages in being “left behind” by not adopting new technology.9
Current research suggests that the most effective communication strategy is face-to-face exchange.8 It provides an opportunity to tailor information to recipients and allows the advocate of the change to explore and, if necessary, modify the reasons why a shift in clinical behaviour should occur. Interpersonal communication is usually more effective when there is a high degree of professional resemblance between the individual attempting to introduce the innovation and the recipient. This may partly explain why clinical audits undertaken by medical practitioners are more likely to lead to adoption of a new practice than those performed by allied health staff.8
The diffusion model2 postulates five steps in the decision-making process:
Competing interests
The author is a Senior Advisor to the National Institute of Clinical Studies.
References
- Tamblyn R, McLeod P, Hanley JA, et al. Physician and practice characteristics associated with the early utilization of new prescription drugs. Med Care 2003; 41: 895-908. i1082950
- Rogers E. Diffusion of innovations. New York: Free Press, 1983. i1082952
- Goodman SN. The mammography dilemma: a crisis for evidence-based medicine? Ann Intern Med 2002; 13: 363-365. i1082954
- Stanley DE. The mammography dilemma. Ann Intern Med 2003; 138: 771. i1082956
- McDougall GJ Jr, Weber BA, Dziuk TW, Heneghan R. The controversy of prostate screening. Geriatr Nurs 2000; 21: 245-248. i1082958
- Schorling JB, Klas PT, Willems JP, Everett AS. Addressing alcohol use among primary care patients: differences between family medicine and internal medicine residents. J Gen Intern Med 1994; 9: 248-254. i1082960
- Franzgrote M, Ellen JM, Millstein SG, Irwin CE Jr. Screening for adolescent smoking among primary care physicians in California. Am J Public Health 1997; 87: 1341-1345. i1082962
- Bero LA, Grilli R, Grimshaw JM, et al. Closing the gap between research and practice: an overview of systematic reviews of interventions to promote the implementation of research findings. BMJ 1998; 317: 465-468. i1082964
- Denis J-L, Hebert Y, Langley A, et al. Explaining diffusion patterns for complex health care innovations. Health Care Manage Rev 2002; 27: 60-73. i1082966
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