Chapter 23 Clinical reasoning in dentistry
Although clinical reasoning is a core competency for the healthcare professions, it is not always clear how the reasoning of one profession differs from that of another. This lack of clarity reflects our limited understanding of the clinical problems tackled by most professions and of the reasoning processes required to cope with such problems. Or perhaps, more precisely, it reflects lack of knowledge of the many factors used by clinicians as they unravel the myriad of clues and leads associated with most clinical problems.
Stemming from the historical relationship of dentistry with medicine, especially surgery, dental education and practice are based largely on a biomedical model of health care. In guiding clinicians, teachers and researchers through the process of diagnosing oral diseases, and in establishing clinical practice guidelines based on reliable evidence, dentistry has adopted in large part the analytical approaches of medicine, which are based on decision theory and information processing theory. However, the classical biomedical perceptions invoked by these theories are being challenged by more broadly based psychosocial models of health care (Evans et al 1994). Consequently, recent explorations of the psychosocial basis of diagnosis and treatment planning have been conducted through inductive or interpretive perspectives, unlike the deductive or hypothesis-based studies that dominate medical research in health care and clinical practice (Bryant et al 1995, Fleming 1991).
During the 18th century in Europe, and about a century later in North America, dentistry embraced the responsibilities of a clinical profession somewhat differently than medicine, although it followed closely the educational and regulatory paths established by medicine (Adams 1999, Lafkin 1948). Dental educators in general adopted the classical medical model of professional education, with formal curricula based as much as possible on scientific enquiry and supplemented by a clinical apprenticeship under the guidance of experienced clinicians (Formicola 1991, Gies 1926). Indeed, this close affiliation with medicine was seen as the key to the survival and growth of dentistry as a ‘respectable’ clinical profession (Schön 1983).
The strength of the relationship between dentistry and medicine has served, and continues to serve, as the standard by which dental education, research and services are judged. However, it is not at all clear that this standard is a reasonable basis for exploring and explaining clinical reasoning in dentistry. The contact that most people have with surgeons is a ‘one-off’ relationship in which patient and surgeon may never see each other again. For example, patients may have their wisdom teeth removed by an oral surgeon whom they never see again. However, most dentists encourage patients to establish an ongoing relationship for routine dental care that will ideally last for many years. Healthy patients may see a general dentist more frequently and regularly than they see a physician, which is likely to influence the dynamics of the relationship and the clinical reasoning required. An ongoing relationship promotes an approach to care that is more problem-preventing than problem-solving, and is focused more on health than on disease.
The emergence of science during the enlightenment period coincided with the development of hospitals and promoted a reductionist concept of disease and health (Foucault 1973). Disease was portrayed as a malfunction of biological systems, in which the mind had very little influence. Surgeons and physicians claimed the professional knowledge and authority to identify and diagnose malfunction and prescribe therapy. It followed, therefore, that health was simply the absence of disease (Davis & George 1988).
Parsons’s theory of the ‘sick role’ challenged the medical model by introducing the social aspects of health and disease in relation to the patient’s role in society. Accordingly, doctors were deemed by society as professionally responsible for recognizing disease and legitimizing patients’ exemptions from their functional role in society due to sickness (Parsons 1951). Parsons’ theory launched a move to explore the psychosocial aspects of medicine, from which emerged the biopsychosocial model of health care promoted by Engel (1977). Recent developments with interpretive methods have explored further the complexities of the interactions between clinicians, patients and society, and helped to redefine health and disease. Consequently, definitions of health have evolved from a simple perception of health as the absence of physical disease to the current view that health occurs when there is a general feeling of physical, psychological and social well-being. A good example of this is the research of Svenaeus (2000), who adopted an interpretive approach to studying the lived experience of health and disease based on hermeneutic phenomenology. He concluded that health is a sense of ‘homelike being-in-the-world’ (p. 173). He made the point, relevant to dentistry, that clinicians ‘do not meet with agents [patients] who evaluate their pain and take a rational stand upon what they want to have done with their biological processes, but with worried, help-seeking persons, who need care and understanding in order to be brought back to a homelike being-in-the-world again’ (p. 173–174).
How such care and understanding manifests itself depends on the interaction of all the biopsychosocial factors involved. At one extreme are casual patients, seeking immediate relief from toothache, who have little interest in ongoing dental care. These people appreciate an instrumental approach, with its emphasis on the technical expertise that will ease their suffering as quickly and painlessly as possible. At the other extreme are patients suffering from chronic orofacial pain, such as the so-called ‘burning mouth syndrome’. These patients need a clinician who can listen to their stories of suffering and who can empathize with what they have been going through. Kleinman (1988) called this latter approach ‘empathic witnessing’. Dentists need clinical judgement to recognize when a more instrumental approach is needed and when to be more empathic (Loftus 2006). This is not always easy for dentists because dental education has, in general, emphasized the more instrumental approach for the majority of oral problems.
Dental education has traditionally placed great emphasis on developing instrumental skills that are demanding and require a high level of manual dexterity and attention to detail. Such skills are developed only with time and under close supervision. However, this education tends to produce dentists who feel that they are truly practising dentistry only when they perform instrumental procedures such as surgery and fillings. Many dentists may feel that they are not doing real work if they are ‘just’ conversing with patients.
Dentists who work in an environment such as a multidisciplinary pain clinic have to make profound changes to their attitudes and approaches to care when their assessments and management must focus on a patient’s history and psychosocial state rather than surgical or restorative needs (Loftus 2006). There may be none of the usual accoutrements of a dental clinic: no dental chair, light or instruments. Such management will normally entail an integrated approach, typically combining medication with psychological support.
Schön (1987) wrote that being a professional is ontological; it is a way of being in the world. For many dentists their sense of being a dentist is closely associated with the performance of instrumental tasks. This is reinforced in many countries by the remuneration systems for dentists, who are rewarded only for performing instrumental tasks. All this has the tendency to focus attention on the treatment of dental disease and away from the promotion of oral health.
The relationship between oral health and general health has been emphasized repeatedly in numerous reports (Field 1995, Gies 1926). The impact of change in theories of health surfaced in dental curricula during the latter part of the 20th century under the banner of the ‘socially sensitive’ movement (Formicola 1991). Consequently, dental curricula in most countries developed teaching of ethics and communication, to broaden the clinical competency of dentists beyond the more traditional instrumental psychomotor and technical skills that were the hallmark of previous curricula. Dentistry is now beginning to explore the psychosocial impact of oral health by adopting interpretive methods of research from sociology, psychology and other disciplines which have an explicit focus on human behaviour and belief. However, this shift in research methods has not yet had a major impact on studies of clinical reasoning in dentistry.
Psychometric measurement of how dentists diagnose clinical problems and decide on the appropriate treatment has shown how inconsistently dentists approach diagnosis and treatment (Kay et al 1992, Reit & Kvist 1998). Apparently, many diagnostic tests are both insensitive and non-specific, which might explain why dentists use specific tests inconsistently, and why there have been repeated calls for improved decision-support systems and practice guidelines. Since the 1970s there has been growing interest in how dentists could or should solve problems, and numerous conceptual explanations have been suggested, such as decision analysis, preference-based measurement, rating scales, standard gamble techniques, time trade-offs, quality-adjusted life (tooth) years, game theory, and Bayesian-based utility measures, all of which are known collectively as medical decision theory (Fyffe & Nuttall 1995, Matthews et al 1999).
Decision analysis considers diagnosis and treatment planning as a sequential process whereby dentists revise their decisions as they construct and proceed along the trunk and branches of decision trees. All decisions are weighted under the influence of Bayesian rules to: (1) identify expected outcomes; (2) estimate the probability of each outcome; (3) evaluate risks and benefits; and (4) assign a utility value for every possible outcome. Eventually, each branch offers a probability and utility value that together offer a value for the utility of each decision. This approach carries the authority of scientific and mathematical rationality for optimizing and justifying clinical decisions. It has been recommended as a means of evaluating clinical competency within a perceived range of normal or optimal decisions, as established by mathematical probability. However, a rational treatment decision based on the rules of decision analysis occasionally conflicts with a clinician’s ethical principles or with a patient’s preferences for treatment (Patel et al 2002). Moreover, the analyses based on Bayesian rules require comprehensive knowledge of all the available alternatives and their consequences, and these are not readily, if at all, accessible. Bradley (1993) noted that designing decision trees requires a certain degree of artistry and expertise. This is not a mechanical or automatic process. In other words, some interpretive creativity is required when constructing decision trees. It can be argued that decision theory implicitly relies upon such interpretive creativity, even though the conceptual framework and vocabulary of decision theory have no place for artistry. Consequently, there is little support for further development of decision support systems based on Bayesian rules.
Expert systems appeared in dentistry in the 1980s with a range of computer-based decision support systems for diagnosis and treatment planning in several dental specialties, such as orthodontics (Sims-Williams et al 1987), prosthodontics (Kawahata & MacEntee 2002) and oral medicine (Hubar et al 1990). Initially the systems were simplistic in scope and application, but recently there have been suggestions of applying more sophisticated systems based on the theory of fuzzy logic (Akcam & Takada 2002). There is now an awareness of the significance of language, symbols and semantics within the context of clinical situations where uncertainty is a dominant feature (Sadegh-Zadeh 2001). The relatively simple computation of numbers in Bayesian theory is being replaced by symbolic computations designed to address uncertainty, and by applications of heuristics or trial-and-error and the structure of knowledge and perception (Zadeh 2001). However, we are not aware of a practical application of these new ideas to analysing the clinical reasoning of dentists. Computerized decision-support systems are seen by some as overly reductionist, mechanistic, acontextual and value-free (Dreyfus 1992). Computerized systems cannot take account of the rich, complex and multilayered meanings that patients can bring to any encounter with a doctor or a dentist. Humans, both clinicians and patients, live out complex narratives that can affect any clinical interaction (Charon 2006). However, it can be argued that clinical decision support systems may have a useful role in education (Gozum 1994). They can give students a degree of practice in solving simulated but realistic cases in a safe environment where patients will not be harmed.
The 1990s saw the beginning of exploration into the process by which dental clinical decisions are made, largely under the influence of the theory of information processing. The hypothetico-deductive (H-D) model (Elstein et al 1978) serves as the basis for problem-based learning in dentistry and in medicine. It identifies four stages in solving problems: cue acquisition, generation of hypothesis, cue interpretation and evaluation of hypothesis. A more elaborate model of H-D reasoning addresses the actual thinking process used when biomedical knowledge is applied to diagnose diseases (Gale & Marsden 1982). However, H-D models cannot adequately explain the diagnostic reasoning of dental students when confronted by a typically routine dental problem, such as managing a patient with caries. Apparently, students combine various strategies of H-D reasoning with aspects of pattern recognition to make diagnostic and therapeutic decisions (Maupome & Sheiham 2000).
Pattern recognition theory entails the assumption that the fast and efficient retrieval and processing of clinical information is related to the structure of knowledge in a person’s memory. This is particularly evident among expert clinicians such as dermatologists and radiologists, who use visual cues from previous clinical experiences (Elstein & Schwartz 2000). Students, in contrast, store their knowledge in a more disorganized and disjointed pattern, and retrieve it in a process of trial and error to locate and connect isolated bits of information (Hendricson & Cohen 2001). From the perspective of cognitive psychology, it seems that experienced clinicians function unconsciously within the context of an ‘illness script’ that offers various cues or action ‘triggers’ based on previous experiences with similar patterns (Charlin et al 2000). From this viewpoint, caries, for example, is a visible disease that triggers the clinician to action based on a script describing the colour and size of the lesion and a hypothesis about whether or not the disease is present or absent (Bader & Shugars 1997).