This classification assumes that appropriate training, preparation, and care are devoted to the planning and implementation of treatment plans. No classification can adequately address cases or outcomes that deviate significantly from the norm. In addition, it is assumed that clinicians will be practicing within the bounds of their clinical competence and abilities. Thus, within each classification, the following general and specific assumptions are implied:
• Treatment will be provided in an appropriately equipped dental office with an appropriate aseptic technique.
• Adequate clinical and laboratory support is available.
• Patients’ medical conditions are appropriately addressed.
• The surgical procedures are planned and provided following recognized protocols.
• The prosthesis is designed, manufactured, and managed correctly.
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ITI Learning Module Surgical Setup for Office-Based Implant Surgery by Waldemar Daudt Polido. |
With the increasing popularity of dental implant treatments with both patients and dental practitioners, the risks associated with the clinician are often overlooked. Derks and coworkers (Derks et al, 2016) described a situation where implant complications from peri-implantitis were significantly correlated with the level of experience of the dentist who was completing the restorative part of the treatment. In this study of real-world treatments, general dentists were 4.3 times more likely to be associated with a peri-implantitis problem than were restorative specialists. While this result may relate to confounding biases in the data set used in this study, which could not be controlled due to the nature of the data, it is still a somewhat disconcerting statistic.
It is also a concern in connection with the incidence of complaints and medicolegal claims relating to implant treatments that are increasing in many jurisdictions. In some regions, professional indemnity insurers are charging additional premiums for particular groups of practitioners who are participating in implant dentistry. These insurance companies do so on the basis of their own actuarial research, which indicates additional risk associated with these treatments in the hands of specific cohorts of practitioners.
It is a widely held truism in the surgical disciplines in medicine that a surgeon needs to complete between 50 and 100 procedures to be considered competent. The real evidence for this is somewhat less clear. Jerjes and Hopper (2018) described a number of investigations into the relationship between experience and postoperative outcomes in both medical and dental surgical disciplines. Their review found no consistent relationship between these factors. However, it did find evidence that there was often a threshold level of experience below which surgeons could be expected to have greater incidence of problems, indicating that there was a “learning curve” related to most surgical procedures. This threshold value varied between disciplines and studies.
In a systematic review of the relationship between surgeon experience and implant failure rates, Sendyk and others (Sendyk et al, 2017) noted that this relationship did not correlate with the surgeon’s specialty but was significantly related to the number of implants that the surgeon had placed. In an earlier study, Lambert and coworkers (Lambert et al, 1997) found similar outcomes, noting that implant failure rates were two times higher for inexperienced surgeons (ie, who had placed less than 50 implants) compared to those of surgeons who had placed 50 or more implants. They also noted that the first nine implants placed by a surgeon under training where at the greatest risk of failure. These findings could be reasonably accepted as showing a relationship between experience and outcomes in implant treatments.
Training is another area of consideration. The Conscious Competence Learning Model (Curtiss & Warren, 1973) is an accepted description of how people learn new skills. In this model (Figure 1), four stages of learning are described:
1. Unconsciously incompetent: Here
2. Unconsciously incompetent: Here the person knows little about what they are doing. They cannot comprehend the potential difficulties involved in a process, and they often feel that they are performing the task to a high standard. They do not know what they do not know, and this is a major impediment to learning.
3. Consciously incompetent The learner comprehends that they fall short of ideal performance and understands their knowledge deficit. Making mistakes at this stage is often a key part of learning.
4. Consciously competent: The person at this level of learning can perform the task to an acceptable standard, but this requires concentration and attention to detail.
5. Unconsciously competent The individual at this level has had so much practice that they can perform this task without conscious effort. These people can be good teachers in the technique but can also make the task appear “too easy” to casual observers.
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Congress lecture Surgical Treatment of Esthetic Disasters by Waldemar Daudt Polido. |
Fig 1. The Conscious Competence Learning Model.
Training in implant dentistry needs to address each of these learner levels. For the unconsciously incompetent, clinical training must address their knowledge deficit and stress best-practice approaches to treatment provision. Simulations of treatment provision, and mentoring by more experienced clinicians, can assist the consciously incompetent practitioner to pass through this level without endangering patients under their care. Mentoring will also benefit the consciously competent clinician by supporting their incremental development of skills. Finally, for the unconsciously competent clinician, training must support their focus on practicing in a reflective and consistent manner. The unconsciously competent clinician is at some risk of complacency and overconfidence and must make a conscious effort to remain focused on current best practices and the evolution of techniques in implant dentistry. They are also something of a risk to less knowledgeable and less skillful colleagues who might observe them providing patient care and conclude that these treatments are more straightforward than they really are.
Another way of considering this journey of skill development is the so-called “Dunning-Kruger Effect” (Kruger & Dunning, 1999). This describes a form of cognitive bias that leads to individuals overestimating their own ability because they lack sufficient knowledge and understanding of what they are doing to realistically measure their level of skill. It is only through painful discovery of the limitations of their ability that they can begin to learn. This correlates well with the unconsciously incompetent level described above. It is also a potentially dangerous issue with a novice clinician involved in providing a potentially complex treatment to a patient.
Training in implant dentistry is provided at a number of levels. At its simplest, clinicians learn from each other as they progress along the learning curve. This is the process by which most of today’s acknowledged “experts” learned these skills in the period during which implant treatments were evolving.
With implant dentistry now an established discipline, learning from shared experience is valuable for clinicians who have a sound understanding of implant treatments. Here, the consciously and unconsciously competent clinicians can benchmark their understanding against that of others.
However, this approach is unlikely to be effective if the individuals (eg, those in the unconsciously incompetent group) sharing their experiences do not fully understand the significance of what these experiences represent. This model is often popular today with younger practitioners who learn from colleagues via online forums, but this represents a real risk of being “the blind leading the blind.”
Similar observations might be made about the short, companyled programs. Often the aim of this training is to make practitioners aware of the processes needed to handle that company’s componentry, and thus these programs often focus on the “how” rather than the “why” or “why not.” Also, due to the brevity of these courses, the biologic and biomechanical principles involved in implant treatments must be greatly abbreviated or are simply not covered at all. Unfortunately, this method can be fraught with danger to patients and cannot allow for a focus on best-practice protocols, as these concepts may be unknown to those learning.
The most effective training comes from structured programs that provide a sound basis for patient selection and treatment. These courses address the basic sciences that underpin successful treatment, introduce protocols for patient assessment and selection and treatment planning, and then provide candidates with the opportunity to perform actual treatment and patient maintenance with assistance and guidance from more experienced mentors. Given the breadth of the topics to be covered, these programs must extend over longer periods compared with other approaches. Thus, these programs can be expensive in terms of time and money and difficult to fit in alongside daily practice, leading to under-utilization of this type of education and training.
Intuitively, one might expect that better-quality training would result in fewer complications or failure. While this is generally accepted in health care, little evidence is available to support these conclusions. Certainly, patients and regulators see this connection as true, and this forms that basic assumption that underpins mandated continuing professional development requirements.
What have been described as “human factors” are becoming recognized as sources of error in health care provision. Much of the research in this area comes from the commercial aviation industry, but these findings are beginning to permeate into health care safety considerations.
A second edition of Renouard and Rangert’s book about risk factors was published in 2008 (Renouard & Rangert, 2008) and brought the topic of experience and human factors to the discussion.
In a recent review of these factors and their influence in dental implantology, Renouard and coworkers (Renouard et al, 2017) described five hazardous attitudes or behaviors that are potentially detrimental to safe practice. Originally identified in aviation, these types are:
1. Impulsiveness The urge to get things done quickly, without necessarily considering potential dangers.
2. Anti-authority The attitude held by some practitioners that rules, regulations, and protocols are for others, and do not pertain to them.
3. Invulnerability Practitioners who believe that adverse outcomes only happen to others, and not to them.
4. Macho The belief that a practitioner must be constantly demonstrating their superiority over others. While this is mostly a male trait, it can affect women as well.
5. Resignation The belief that no matter what a practitioner does, it will not have any effect on the outcome.
Renouard and coworkers also discuss stress as a potential problem. While the stress response is adaptive (ie, it is protective against external threats), it can have negative effects in a health care setting where the stress is mostly self-induced. Stress factors such as time pressures, staff problems, and interpersonal frictions between the dentist and the patient can all have a negative effect on performance. Stress tends to reduce the practitioner’s ability to rationally think through a problem and rather promotes the use of automatic responses, which may be incorrect or unhelpful. These factors are well studied in the medical literature as well, as it relates to many daily issues, like less sleep, financial problems, and health or family issues (West et al, 2006).
To counter these “human factor” issues, Renouard recommends using techniques that have been developed for the airline industry to address safety problems: so-called “crew resource management.” The concept of the “sterile cockpit” where all extraneous activity is banned during high-risk periods, such as take-off and landing, can be transferred to the dental implantology setting for use during critical periods of treatment provision. Strict division of responsibilities between team members also reduces stress and “information overload.” Additionally, checklists can be very useful in concentrating attention on critical steps, especially in highly procedural tasks such as those seen in medicine and dentistry. This approach has also been promoted by other authors (Gawande, 2009; Pinsky et al, 2010). Here the SAC classification can be used as a checklist to ensure that all factors relevant to the patient’s presentation are assessed and incorporated into treatment plans.
The clinician is central to most decisions and their practical application in implant treatment. Risks in implant dentistry can be attributed to four main sources: the patient, the treatment approach, the biomaterials, and the clinician. This relationship between the clinician, the materials, and the patient factors was first described by Chen and Schärer in 1993 (Chen & Schärer, 1993). Further, Buser and Chen (Buser & Chen, 2008), published on a model that also illustrates the potential interactions between these factors, as shown in Figure 2.
Fig 2. Potential sources of risk (Source: ITI Treatment Guide Vol. 3 “Implant Placement in Post-Extraction Sites”)
In this model, the clinician has a potentially disproportionate influence: they select the patient, the treatment approach, and the biomaterials, and they subsequently carry out the treatment on the patient. Thus, a flaw or shortcoming in their knowledge or skills will put their patient at greater risk of adverse outcomes. Therefore, in answer to the question posed earlier, we must conclude that the clinician has the potential to be a significant risk factor.
Can the SAC classification assist in reducing risk? By focusing the attention of the clinician on potential risk factors, it should ensure that the clinician-related risk is mitigated. However, the review group did not believe that the clinician could be considered as a factor in determining the SAC classification for a case, as they were not confident that all clinicians could accurately self-assess their ability. Nonetheless, discussions such as this may assist individuals in progressing along their own learning journey and improve their ability to control this potential risk.
In the 2009 version of the SAC classification (Dawson & Chen, 2009) the main determinants of the classification were:
• The esthetic risk
• The complexity of the process
• The risks of complications
These factors were considered for each of the treatments considered in this publication, and a normative SAC classification was derived for each of these case types. Further modifiers were considered that might increase or decrease the level of complexity or risk, but these did not change the normative classification for the case type.
In this update, the normative classifications have been reviewed, but they have not altered greatly. These are still based on the factors above, with an increased emphasis on the SAC classification as a risk management instrument.
The updated SAC Assessment Tool now allows users to derive a SAC classification for their specific case based on the pattern of risk factors that they report. Risks are considered in four broad areas:
• General risks These are the issues normally identified during anamnesis and the initial clinical assessment and are mostly patient related.
• Esthetic risk Esthetic issues are often the patient’s only way of measuring the treatment outcome. This is more than a consideration of “is the treatment site visible during function and/or smiling, and are the peri-implant mucosal tissues visible?” but also includes other factors described by Martin and coworkers (Martin et al, 2017) in their discussion of the esthetic risk assessment for single-tooth implant prostheses. Esthetic risk assessment for more extensive tooth replacement situations have also been considered.
• Edentulous esthetic risk When patients undergo complete loss of teeth, several unique clinical factors specific to this patient subset can have a significant influence on esthetic outcomes. The edentulous esthetic risk assessment will highlight these factors as they influence particular case types.
• Surgical risk Factors influencing the complexity and risk of the surgical phase of treatment.
• Prosthetic risks Factors relating the implant-supported prosthesis; for example, the clinical processes involved, the mode of manufacture, the materials used, and the design employed.
Each of these areas will be considered in more detail later in this book.
A. DAWSON, W. MARTIN, W. D. POLIDO
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All interventions in health care carry some risk of failure, complications, or other suboptimal outcomes. Implant treatments are no different.
The risk management cycle is a term used to define a process aimed at limiting the incidence of adverse outcomes, and their impact.
Fig 1. The risk management cycle.
In general, this cycle aims to:
• Identify potential problems
• Measure the incidence of these adverse outcomes and the impact that they have
• Educate users about these potential problems
• Develop strategies to mitigate the incidence or effect of these problems
• Review the effectiveness of these mitigation strategies
As indicated in Figure 1, this is a continuous process where outcomes are monitored, and refinements are made to mitigation strategies to incrementally improve process outcomes.
In implant dentistry, the users refer to patients and clinicians. However, the process remains the same. Although it is not usually referenced in such terms, effective practice in most areas of health care, including implant dentistry, follow the basic principles of risk management. A common dental practice example of this might be the management of dental caries. Here, our modern preventive approach to caries management centers on identifying risk factors (eg, patient behavior/diet, salivary function, oral microflora, plaque retentive restorations, etc) and measuring their impact. We then can focus on reducing risk by attempting to mitigate these risks through patient education and risk-reduction focused treatments. We then continue to monitor our patient’s progress and the success of our interventions.
The importance or severity of a risk can be considered in terms of the likelihood of that risk being realized and the impact or significance associated with the outcome that follows. These situations are often tabulated in a risk matrix, an example of which can be seen in Table 1.
While we often concentrate our efforts on mitigating the risks of high-impact outcomes, like implant failure, it must also be noted that less dire outcomes that are more common, such as peri-implant disease, may be more important.
Table 1 An example of a risk matrix.