The Challenge Of Integrating Genomic Innovation

It is commonly believed that innovations succeed on their own merit. Those without real merit fail in the market place; those with superior merit succeed simply on the basis of their superiority over existing alternatives. However, experience shows otherwise. Technological capability and superior engineering do not, in fact, guarantee acceptance (Table 1). Great innovations themselves are often insufficient to ensure usability, effectiveness, or user satisfaction. In other words, good technology does not equal adoption. Why? (Fig. 1) Because factors integral to users' experiences, such as intuitive approaches to problem solving, environmental factors or underlying beliefs, values or attitudes, play an integral role in adoption. More specifically, these factors can facilitate or thwart integration of new knowledge and thus bar acceptance. For example, the problem-solving logic inherent in IT tools may well serve a developer's needs, but prove incoherent with end users' intuitive problemsolving processes, thereby failing to be a useful solution for the employee.[1]

Similarly, physician lag in adopting innovation is well known. The history of medical practice, in particular, is replete with examples of un- and underutilized innovations, whether new IT solutions, devices, diagnostics, clinical guidelines, or therapeutics.[2-5] This history suggests the very real possibility that genetics innovations will not be readily or accurately integrated into daily practice without an identification of and remedy to barriers (Table 2).

A central goal of genetics educational initiatives, indeed, has been to promote adoption and accomplish the primary aim of effecting a change in medical practice. The desired behavioral change is to improve physician decision making about potential genetic involvement in the face of uncertainty. Existing educational programs have increased clinician awareness of advances in molecular medicine.[6] Clinical competency in problem solving about potential involvement depends on more than mere awareness[7] (Table 3). Despite the high quality of many current genetics education curriculum, education assessments confirm that practitioners remain unconvinced about the relevance of genetics advances to their practices as well as uneasy about how to integrate this new information into point-of-care service.[8-10] Education alone, then, has been less than fully successful and changing clinician behavior so that practice reflects the appropriate incorporation of innovation. The shortcomings are due far less to the quality and delivery of educational programs than they are to a lack of understanding of practitioner diagnostic problem-solving strategies, and both the environmental and internal factors (i.e., cognitive, attitudinal, and normative factors) that influence those strategies. Researchers in continuing medical

Table 1 Predicting innovation

1943 IBM, Chairman (Thomas Watson) ''I think there is a world market for about 5 computers''

1977 Digital Equipment Co., President (Ken Olson) ''There is no reason for any individual to have a computer in their home''

1981 Microsoft, CEO (Bill Gates) ''640K [of memory] ought to be enough for anybody''

education show that such factors, hidden within the day to day of medical practice, nonetheless can pose significant obstacles to acceptance.[11-14]

Cognitive barriers represent a particularly difficult hurdle, primarily because they are embedded in clinical problem-solving strategies that become deeply engrained over time in one's practice.[15] For example, clinicians rarely use formal probabilistic modes as they engage in diagnostic reasoning. Instead, they use induction and heuristics as problem-solving tactics because heuristics[16] (i.e., rules of thumb or shortcuts), in particular, drastically reduce the number of steps needed in a search for solutions to a problem, or a diagnosis. Heuristics, reasoning shortcuts, and other thinking habits aid physicians in accurately and efficiently solving clinical conundrums, making diagnoses, or determining medical decisions. Although these tactics are neither precise indicators of prevalence nor other probability associations, heuristics are convenient and frequently correct. As such they serve a practitioner well, given time, and other practice, constraints. Furthermore, their accuracy reinforces their continued use. In fact, they are typically learned in medical school, refined to one's idiosyncratic ways of framing and solving diagnostic puzzles and continually reinforced in daily practice. As such, they become more ingrained in a clinician's intuitive diagnostic approaches.[17]

BARRIERS ^ Despite great engineering. 75% of all new products fail in the marketplace in the marketplace

^ invention is fiat Enough

Fig. 1 Innovativeness doesn't ensure adoption. (View this art in color at

^ invention is fiat Enough

Fig. 1 Innovativeness doesn't ensure adoption. (View this art in color at

The ''availability'' heuristic is used to judge frequency and probability but relies on the cases brought to mind as a basis for judgment. As such, it can impede focus on case specifics. The ''representative'' heuristic assumes that a present case so closely resembles a well-defined case that the probability of the disease occurring in this case is that of the well-defined case. Resemblances between a patient's features and a classic disease pattern can produce exaggerated estimates of the likelihood that present disease as in fact the classic one. In other words, the class of things retrieved most easily leads subjects to believe that that class is more frequent than those classes less easily retrievable. As such this tactic can result in failure to consider either prior probability or factors that limit predictive accuracy of thought generated.

Applied to genetic issues, however, these techniques are less useful and may even contribute to failure to detect genetic involvement or appropriately consider genetic influences, thereby resulting in misdiagnosis or mistreatment. Specific characteristics of genetics thwart the clinical utility of these clinical reasoning strategies that are designed to identify observable pathology (phenotype), determine a proximate cause (diagnosis), and prescribe appropriate treatment and management. In particular, scientists determined that one gene can affect more than one trait (pleiotropy), that any single trait can be affected by more than one gene, and that the majority of traits are affected by environmental factors as well as by other genes. Identifying the cause of a clinical symptom (or trait) is then far more complicated than identifying a symptom or determining that a number of symptoms indicate the presence of disease. Furthermore, determining the clinical significance of any genetic findings (that is, what do the genetic findings mean in the context of the patient's biochemical, hormonal and other biological processes) is more complicated than many general medical diagnoses, such as detecting the presence or absence of an otitis media or strep throat. The utility of heuristics and clinical reasoning shortcuts in the context of complicated genetic involvement is thus compromised.1-18-20-1

Constructing, understanding and problem solving are cognitively similar activities. Expertise in clinical problem solving has been shown to consist of highly automated, yet highly accurate perceptual and cognitive processes. For example, expert behavior is characterized by rapid recognition of key aspects of problems. Experts

Table 2 Indicators of physician receptivity to genomics innovations

''I've taken CME in the new genetics, but I shy away from it.

It takes lots of time, is changing so fast and is so complicated.

But, I have the working consciousness of a geneticist. I look for things.''

''Several doctors (at a bioethics conference) admitted they had never heard the pharmacogenomics until the conference and weren't quite sure what they would do with a genetic test if they had one.'

''Teachers open the door, but you must enter by yourself.''

(Primary Care Physician recently trained in genetics advances)

(Chinese Proverb)

in any domain, for example in primary-care delivery, are known to use more elaborate but more flexible schemas for conceptualizing, understanding, and reasoning through problems, as well as domain-specific conceptual and procedural knowledge. These skills enable clinicians to identify critical cues within data presented and reason using data-based hypothesis generation, both of which are considered marks of expertise.[21]

Research into classical genetics problem solving shows that domain-specific and procedural knowledge is crucial to successful problem solving.[22] Knowledge-based and procedural errors in reasoning typically include knowledge deficits, factual errors, recall failure, fallacies of inference, fallacies of availability, metajudgments about the importance of pieces of information, and misapplied knowledge. Research into the effectiveness of genetics education programs indicates that clinicians have displayed a proclivity for confirming genotype solely on the basis of phenotypes ascertained through physical exam. Family history characteristics, which could trigger suspicion of possible heritable involvement, were not spontaneously considered by clinicians.[23] This tactic, which is a very narrow approach to genetics thinking, represents problematic genetic reasoning competency. Clinicians are trained to diagnose on the basis of observed phenomenon, (phenotype) and biochemical tests indicated what has most likely caused the physical finding. This approach, however, motivates practitioners to consider genetic involvement from the physical (phenotype) to the internal (genotype) and therein lies a major potential for error in clinical judgment. Research further indicates that clinicians with recent training in advances in genetics did not perform as well as clinicians lacking specific genetics training but known to be outstanding clinical problem solvers.[24]

Assimilation of new genetic knowledge occurs when the possibility of genetics involvement is continually brought to mind, entertained, pursued, and rigorously tested for validation or falsification. Deriving genetic suspicions solely from phenotypic characteristics does not achieve the desired clinical competency in identifying or making medical decisions about potential genetic involvement because pleiotropy, phenotypic variability, and other aforementioned characteristics of genetics introduce considerable room for error in clinical judgment. Physicians will become clinically competent genetic thinkers when their clinical thinking attends to the particular characteristics of genetics.

In particular, clinicians will display competence in genomic medicine when they apply more substantive genomic knowledge, a higher level of inquisitiveness, a broader range of diagnostic hypotheses and interpretations of clinical findings, as well as a more methodical manner of testing candidate hypotheses. A lower threshold for considering possible genetic involvement and consulting a geneticist to validate a suspicion will also serve clinicians well. In addition, family history gathering focused on identifying possible inheritance patterns and recurrence risk will serve clinicians well in refining possible genetic involvement. Reliance on textbook definitions and diagnostic criteria may contribute to a failure to appreciate phenotypic variability. Furthermore, as research suggests that clinicians view a ''genetic'' diagnosis as unfortunate and associated with dire medical and social consequences, they will continue to be reluctant to confer a genetic diagnosis. As knowledge increases and positive actions are proven to mitigate genetic risks, and the ill effects of a genetic diagnosis, clinicians are likely to shed this reluctance.

Table 3 Genetics' barriers to adoption

Complicates typical strategies to ensure innovation adoption Challenges the efficiency and efficacy of the usual clinical reasoning strategies involved in medical problem solving Ethical concerns increase the stakes in using genetics in practice

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