Achieving Clinician Buy-in to Technology

Bryan Bergeron, MD

In This Article

Individual Behavior

Predicting individual clinician behavior when presented with a new technology is no trivial task, given the dozens of variables involved. A clinician's individual perception of the benefits and risks associated with adopting the new technology is a major factor. The clinician may see no clear benefit in using a technology, it may seem too expensive, too difficult to use, take too much time and effort to learn, and may not provide an obvious advantage over alternative approaches. A clinician may simply be resistant to change and may fear the unknown.

In today's computerized economy, it's possible for marketers to predict, with a fair degree of accuracy, how a clinician is likely to respond, for example, to an offer for a new computer or software. However, getting at that much information on an individual clinicians is still very difficult, even with the large electronic databases that companies compile on every clinician. An alternative approach is to model individual behavior based on accepted psychological models of generic human behavior.

One way for a decision maker to gain some degree of control over the demand and subsequent purchase of a particular product is to model individual clinician behavior change. A popular model of behavior change that is used successfully in everything from dieting to smoking cessation is the Transtheoretical Model of Change, also referred to as the Stages of Change Model, developed by 2 clinical psychologists, James Prochaska and Carlo DiClemente.[4] It assumes that every person goes through 5 discrete, predictable of stages when making a major behavior change, such as a purchase and then adoption of a new product. The stages, labeled 1-5 in Figure 3, are described below.

Stages of Change Model. 1-Precontemplation, 2-Contemplation, 3-Preparation, 4-Action, and 5-Maintenance.

1. Precontemplation. In the Precontemplation phase ("1" in Figure 3), a clinician typically has no knowledge of the alternative technologies available, and no plans for changing his or her behavior. At this stage, clinicians may selectively filter information that justifies their decisions to stay with their current behavior. The goal of many marketing campaigns is to move a clinician out of their comfort zone of Precontemplation and to create an awareness and desire for the new technology. Only when the clinician becomes aware of a technology -- in the form of a journal advertisement, for example -- that promises time or money savings is a clinician motivated to leave the steady-state condition of Precontemplation.

2. Contemplation. During the Contemplation phase, a clinician assesses the investment in time, energy, and money associated with purchasing a technology. As depicted in "2" in Figure 3, the Contemplation phase of behavior change includes a modest, increasing investment of time and energy. The ramp-up in energy expenditure may be instantaneous, as in an impulse buy a PDA, or occur slowly over weeks and months, depending on the nature of the behavior change. This stage is often characterized by ambivalence about changing, and clinicians may waver between staying in their comfort zone and venturing out into the unknown because of the risks they associate with changing behavior. A clinician can contemplate technology adoption indefinitely. These first 2 states of change, with their risk of slowness, can determine the rate of behavior change or the pace of technology adoption.

3. Preparation. During the third phase of the Stages of Change model, Preparation ("3" in Figure 3), a clinician makes the decision to change and takes steps to prepare for the change. Preparation typically requires only a modest expenditure of time and energy over that already invested.

4. Action. In the Action phase of behavior change ("4" in Figure 3), a clinician is actually making a change. That is, a clinician is expending energy and time, throwing aside previous behaviors in favor of the new technology. It's during the Action phase of behavior change that impediments to change become most apparent and decrease the odds that the behavior change will be long-lasting. Impediments to change include:

  • Social pressures to maintain the old behaviors;

  • Uncertainty in the payback of the energy and time invested in the new behavior;

  • Difficulty in practicing the new behavior;

  • Extended training requirements;

  • Significant and unexpected monetary requirements;

  • The frequency with which the former behavior was practiced; and

  • Disbelief in the efficacy and worth of the new behavior.

The challenges of succeeding during the Action phase are represented by the recidivism arrow in Figure 3. If the challenges associated with taking action are too great, as depicted by the enormous time and energy requirements in the "disaster" curve, then a clinician is likely to travel backward through the behavior change model -- that is, revert to old habits.

Similarly, the likelihood of recidivism is greater if the time and energy required to maintain the new steady state or baseline behavior isn't significantly lower than that associated with the initial behavior, as in the "failure" curve in Figure 3. In this respect, the probability of recidivism is a function of the relative time and energy required to maintain phase 1 or Precontemplation vs the end of phase 4 or Action.

5. Maintenance. The final phase of behavior change, Maintenance, represents sustained behavior change, where the energy and time associated with the behavior is constant. Ideally, energy and time expenditures are along the lines of curve "Ideal" in Figure 3; but the less-than-ideal expenditures described by curves "failure" and "disaster" are also possible. The Maintenance phase of one behavior change sequence becomes the Precontemplation phase of the next. That is, even if a clinician is happy with a technology, a newer, more efficient, and easier-to-use model may eventually appear on the market. However, the company that's "first to market" with a new technology product has the opportunity to establish brand recognition, consumer loyalty, and market share, creating a market dominance that may be difficult for a competitor to overcome with only a marginal improvement in features. A sixth stage that is often considered part of the model, Termination (of the original behavior), is not included here to simplify the discussion.

Another tool for modeling individual clinician behavior is to use the Technology Co-Evolution Model. This model suggests that an important factor affecting clinician buy-in is the co-evolution of clinicians and the technology. That is, as illustrated in Figure 4, clinicians co-evolve with technology. Clinicians are transformed as old technologies are replaced by new technologies.

The continuous cycle of co-evolution of technology and clinicians. New technologies change clinicians, resulting in rising expectations and eventual disappropriation of the now-old technology with the latest new technology.

In the co-evolution model, old technologies, such as an antiquated information system or paper-based medical record, are replaced by new technologies through the processes of substitution and diffusion. Substitution occurs when a new technology is substituted for an older technology. Diffusion describes the adoption or appropriation of the newly introduced technology into the clinician's work. Diffusion is a function of the rate of appropriation, which is in turn a function of the positive reinforcement that the clinician receives from working with the technology. The main point of this model is the interaction between the clinician and the technology.

As an example that most readers will be able to relate to, consider a clinician who is offered a new clinical information system running on a modern PC to replace (substituting for) an aging medical record system that runs on old, terminal-based hardware. Although it takes the clinician a few weeks to get comfortable with the new hardware and operating system (diffusion), the increased productivity (positive reinforcement) she realizes with the new system motivates her to increase her time investment in learning the system. When she returns to her old system to retrieve some old medical records, the system seems unbearably slow; even its performance was satisfactory before she experienced the new clinical system.

The appropriation of the new technology is facilitated by positive personal, peer, and functional reinforcement. Not only does the clinician get her work done faster, but fellow clinicians are also likely to watch her progress closely during the first few weeks that it's on her desk. The new, high-speed system becomes part of the clinician's identity, to the same extent that a sports car defines its driver. She also likely invests time and energy into learning the new operating system and defining the desktop to suit her preferences and needs. That is, she appropriates the technology. The system hasn't changed in only a few weeks -- the clinician has. Her expectations of what a clinical information system can deliver in terms of performance and ease of use have been permanently altered by her definition of what constitutes a clinical system.

Of course, as many readers may have experienced first hand, the "new" system eventually becomes "old" in a matter of months or years, when a faster, easier-to-use, more feature-laden system becomes available. In this way, the cycle continues, with the technology modifying clinicians as they interact with the latest technology. What's more, not only is this cycle continually progressing, but the pace of technologic innovation is accelerating. As such, the process of appropriation and then disappropriation of "new" technology is accelerating.


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