IMPORTANT CONSIDERATIONS IN THE DIAGNOSTIC PROCESS
The committee elaborated on several aspects of the diagnostic process, which are discussed below.
diagnostic uncertainty \stime \population trends \diverse populations and health disparities
mental health \diagnostic Uncertainty
One of the complexities in the diagnostic process is the inherent uncertainty in diagnosis. As noted in the committee’s conceptual model of the diagnostic process, an overarching question is whether sufficient information has been collected to make a diagnosis. This does not mean that a diagnosis needs to be sure to initiate treatment. Kassirer concluded that:
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Absolute certainty in diagnosis is unattainable, no matter how much information we gather, how many observations we make, or how many tests we perform. A diagnosis is a hypothesis about the nature of a patient’s illness derived from statements by inference. As the inferential process unfolds, our confidence as [clinicians] in a given diagnosis is enhanced by gathering data that either favor it or argue against competing hypotheses. Our task is not to attain certainty but to reduce diagnostic uncertainty enough to make optimal therapeutic decisions. (Kassirer, 1989, p. 1489)
Thus, the probability of disease does not have to be equal to one (diagnostic certainty) for treatment to be justified (Pauker & Kassirer, 1980). (Pauker and Kassirer, 1980). The decision to begin treatment based on a working diagnosis is informed by the following:
The degree of certainty about the diagnosis.
The harms and benefits of treatment.
The harms and benefits of further information-gathering activities, including the impact of delaying treatment.
The risks associated with diagnostic testing are essential considerations when conducting information-gathering activities in the diagnostic process. While the underuse of diagnostic testing has been a long-standing concern, overly aggressive diagnostic strategies have recently been recognized for their risks (Zhi et al., 2013) (see Chapter 3). (see Chapter 3). Overuse of diagnostic testing has been partially attributed to clinicians’ fear of missing something essential and intolerance of diagnostic uncertainty: “I am far more concerned about doing too little than doing too much. It is the scan, the test, the operation that I should have done that sticks with me—sometimes for years. . . . By contrast, I cannot remember anyone I sent for an unnecessary CT scan or operated on for questionable reasons a decade ago” (Gawande, 2015). (Gawande, 2015). However, there is growing recognition that overly aggressive diagnostic pursuits are putting patients at greater risk for harm and not improving diagnostic certainty (Kassirer, 1989; Welch, 2015). (Kassirer, 1989; Welch, 2015).
When considering diagnostic testing options, the procedure’s harm must be weighed against the potential information that could be gained. For some patients, the risk of invasive diagnostic testing may be inappropriate due to the risk of mortality or morbidity from the test itself (such as cardiac catheterization or invasive biopsies) (such as cardiac catheterization or invasive biopsies). In addition, the risk for harm must consider the cascade of diagnostic testing and treatment decisions that could stem from a diagnostic test result. These assessments include the potential for false positives and ambiguous or slightly abnormal test results that lead to further diagnostic testing or unnecessary treatment.
There are some cases in which treatment is initiated even though there is little certainty in a working diagnosis. For example, an individual who has been exposed to a tick bite or HIV may be treated with prophylactic antibiotics or antivirals because the risk of treatment may be felt to be smaller than the risk of harm from tick-borne diseases or HIV infection. Clinicians sometimes employ empiric treatment strategies—or the provision of treatment with a very uncertain diagnosis—and use a patient’s response to treatment as an information-gathering activity to help arrive at a working diagnosis. However, it is essential to note that response rates to treatment can be highly variable, and the failure to respond to treatment does not necessarily reflect that a diagnosis is incorrect. Nor does improvement in the patient’s condition necessarily validate that the treatment conferred this benefit and that the empirically tested diagnosis was correct. A treatment that is beneficial for some patients might not be beneficial for others with the same condition (Kent & Hayward, 2007), hence the interest in precision medicine, which is hoped to tailor therapy better to maximize efficacy and minimize toxicity (Jameson & Longo, 2015). (Jameson and Longo, 2015). In addition, there are isolated cases where a diagnostic procedure’s morbidity and mortality and the likelihood of disease are sufficiently high that effective therapy has been given empirically. Moroff and Pauker (1983) described a decision analysis in which a 90-year-old practicing lawyer with a new 1.5-centimeter lung nodule was deemed to have a sufficiently high risk for mortality from lung biopsy and high likelihood of malignancy that the radiation oncologists felt comfortable treating the patient empirically for suspected lung cancer.
Of significant importance in the diagnostic process is the element of time. Most diseases evolve, and there can be a delay between the onset of the disease and the onset of a patient’s symptoms; time can also elapse before a patient’s symptoms are recognized as a specific diagnosis (Zwaan & Singh, 2015). (Zwaan and Singh, 2015). Some diagnoses can be determined concisely, while months may elapse before other diagnoses can be made. This is partially due to the growing recognition of the variability and complexity of disease presentation. Similar symptoms may be related to several different diagnoses, and symptoms may evolve in different ways as a disease progresses; for example, a disease affecting multiple organs may initially involve symptoms or signs from a single organ. The thousands of different diseases and health conditions do not present in thousands of unique ways; there are only a finite number of symptoms with which a patient may present. At the outset, it can be complicated to determine which diagnosis is indicated by a particular combination of symptoms, especially if symptoms are nonspecific, such as fatigue. Diseases may also present atypically, with an unusual and unexpected constellation of symptoms (Emmett, 1998). (Emmett, 1998).
Adding to the complexity of the time-dependent nature of the diagnostic process are the numerous settings of care in which diagnosis occurs and the potential involvement of multiple settings of care within a single diagnostic process. Henriksen and Brady noted that this process—for patients, their families, and clinicians alike—can often feel like “a disjointed journey across confusing terrain, aided or impeded by different agents, with no destination in sight and few landmarks along the way” (Henriksen and Brady, 2013, p. ii2) (Henriksen and Brady, 2013, p. ii2).
Some diagnoses may be more important to establish immediately than others. These include diagnoses that can lead to significant patient harm if not recognized, diagnosed, and treated early, such as anthrax, aortic dissection, and pulmonary embolism. Sometimes making a timely diagnosis relies on the fast recognition of symptoms outside of the health care setting (e.g., public awareness of stroke symptoms can help improve the speed of receiving medical help and increase the chances of a better recovery) (National Stroke Association, 2015). (National Stroke Association, 2015). In these cases, the benefit of treating the disease promptly can significantly exceed the potential harm from unnecessary treatment. Consequently, the threshold for ordering diagnostic testing or initiating treatment becomes relatively low for such health problems (Pauker and Kassirer, 1975, 1980). (Pauker and Kassirer, 1975, 1980). In other cases, the potential harm from rapidly and unnecessarily treating a diagnosed condition can lead to a more conservative (or higher-threshold) approach in the diagnostic process.
Population trends, such as the aging of the population, are adding significant complexity to the diagnostic process and require clinicians to consider such complicating factors in diagnosis as comorbidity, polypharmacy, and attendant medication side effects, as well as disease and medication interactions (IOM, 2008, 2013b) (IOM, 2008, 2013b). Diagnosis can be incredibly challenging in older patients because classic disease presentations are less common in older adults (Jarrett et al., 1995). (Jarrett et al., 1995). For example, infections such as pneumonia or urinary tract infections often do not present in older patients with fever, cough, and pain but instead with symptoms such as lethargy, incontinence, loss of appetite, or disruption of cognitive function (Mouton et al., 2001). (Mouton et al., 2001). Acute myocardial infarction (MI) may present with fatigue and confusion rather than with typical symptoms such as chest pain or radiating arm pain (Bayer et al., 1986; Qureshi et al., 2000; Rich, 2006). (Bayer et al., 1986; Qureshi et al., 2000; Rich, 2006). Sensory limitations in older adults, such as hearing and vision impairments, can also contribute to challenges in making diagnoses (Campbell et al., 1999). (Campbell et al., 1999). Physical illnesses often present with a change in cognitive status in older individuals without dementia (Mouton et al., 2001). (Mouton et al., 2001). In older adults with mild to moderate dementia, such illnesses can manifest with worsening cognition. Older patients with multiple comorbidities, medications, or cognitive and functional impairments are more likely to have atypical disease presentations, which may increase the risk of experiencing diagnostic errors (Gray-Miceli, 2008). (Gray-Miceli, 2008).
Diverse Populations and Health Disparities
Communicating with diverse populations can also contribute to the complexity of the diagnostic process. Language, health literacy, and cultural barriers can affect clinician–patient encounters and increase the potential for challenges in the diagnostic process (Flores, 2006; IOM, 2003; The Joint Commission, 2007). (Flores, 2006; IOM, 2003; The Joint Commission, 2007). There are indications that biases influence diagnosis; one well-known example is the differential referral of patients for cardiac catheterization by race and gender (Schulman et al., 1999). (Schulman et al., 1999). In addition, women are more likely than men to experience a missed diagnosis of heart attack, a situation that has been partly attributed to real and perceived gender biases but which may also be the result of physiologic differences, as women have a higher likelihood of presenting with atypical symptoms, including abdominal pain, shortness of breath, and congestive heart failure (Pope et al., 2000). (Pope et al., 2000).
Mental health diagnoses can be particularly challenging. Mental health diagnoses rely on the Diagnostic and Statistical Manual of Mental Disorders (DSM); each diagnosis in the DSM includes a set of diagnostic criteria that indicate the type and length of symptoms that need to be present, as well as the symptoms, disorders, and conditions that cannot be present, in order to be considered for a particular diagnosis (APA, 2015). (APA, 2015). Compared to physical diagnoses, many mental health diagnoses rely on patient reports and observation; few biological tests are used in such diagnoses (Pincus, 2014). (Pincus, 2014). A key challenge can be distinguishing physical diagnoses from mental health diagnoses; sometimes, physical conditions manifest as psychiatric ones, and vice versa (Croskerry, 2003a; Hope et al., 2014; Pincus, 2014; Reeves et al., 2010). (Croskerry, 2003a; Hope et al., 2014; Pincus, 2014; Reeves et al., 2010). In addition, there are concerns about missing psychiatric diagnoses and overtreatment concerns (Bor, 2015; Meyer & Meyer, 2009; Pincus, 2014). (Bor, 2015; Meyer and Meyer, 2009; Pincus, 2014). For example, clinician biases toward older adults can contribute to missed diagnoses of depression because it may be perceived that older adults are likely to be depressed, lethargic, or have little interest in interactions. Patients with mental health–related symptoms may also be more vulnerable to diagnostic errors, a situation that is attributed partly to clinician biases; for example, clinicians may disregard symptoms in patients with previous diagnoses of mental illness or substance abuse and attribute new physical symptoms to a psychological cause (Croskerry, 2003a) (Croskerry, 2003a). Individuals with health problems that are difficult to diagnose or those who have chronic pain may also be more likely to receive psychiatric diagnoses erroneously.
Go to: \sCLINICAL REASONING AND DIAGNOSIS.
Accurate, timely, and patient-centered diagnosis relies on proficiency in clinical reasoning, which is often regarded as the clinician’s quintessential competency. Clinical reasoning is “the cognitive process that is necessary to evaluate and manage a patient’s medical problems” (Barrows, 1980, p. 19). (Barrows, 1980, p. 19). They understand that the clinical reasoning process and the factors that can impact it are essential to improving diagnosis, given that clinical reasoning processes contribute to diagnostic errors (Croskerry, 2003a; Graber, 2005). (Croskerry, 2003a; Graber, 2005). Healthcare professionals involved in the diagnostic process have an obligation and ethical responsibility to employ clinical reasoning skills: “As an expanding body of scholarship further elucidates the causes of medical error, including the considerable extent to which medical errors, particularly in diagnostics, may be attributable to cognitive sources, insufficient progress in systematically evaluating and implementing suggested strategies for improving critical thinking skills and medical judgment is of mounting concern” (Stark & Fins, 2014, p. 386). (Stark and Fins, 2014, p. 386). Clinical reasoning occurs within clinicians’ minds (facilitated or impeded by the work system) and involves judgment under uncertainty, with a consideration of possible diagnoses that might explain symptoms and signs, the harms and benefits of diagnostic testing and treatment for each of those diagnoses, and patient preferences and values.
The current understanding of clinical reasoning is based on the dual process theory, a widely accepted decision-making paradigm. The dual process theory integrates analytical and nonanalytical decision-making models (see Box 2-4). (see Box 2-4). Analytical models (slow system 2) involve a conscious, deliberate process guided by critical thinking (Kahneman, 2011). (Kahneman, 2011). Nonanalytical models (fast system 1) involve unconscious, intuitive, and automatic pattern
Subacute polyarticular arthralgias • swelling of the ankles and right knee • recent travel to the Dominican Republic • Dx?
A 78-year-old woman with a history of anxiety and hypertension presented to our family medicine residency practice in Massachusetts with subacute polyarticular arthralgias that had been present for 2 months. She complained of pain and swelling of both ankles and the right knee. She noted that her symptoms had started on a recent trip to the Dominican Republic, where she developed generalized joint pain and a fever that lasted 1 to 2 weeks and subsequently resolved with the lingering polyarthralgia. She denied any rash,
constitutional symptoms, photosensitivity, headaches, photophobia, or history of tick bite. Physical examination revealed normal vital signs, notable warmth and swelling of the bilateral ankles that was worse on the right side, and swelling of the right knee with effusion—but no tenderness—to palpation.
2- Possible Diagnosis with rationale explanation.
3-At least 3 differentials must be mentioned with rationales explanation.
at least 3 references with no less then 5 years