Looking for online definition of potential diagnosis in the Medical Dictionary? potential diagnosis explanation free. What is potential diagnosis? Meaning of. An actual nursing diagnosis is for an active problem. For example, if someone has heart failure, the nursing diagnosis could be 'Inadequate perfusion r/t. A nursing diagnosis may be part of the nursing process and is a clinical judgment about individual, family, or community experiences/responses to actual or potential health problems/life processes.
To help in reduction of pain. Discuss with client and SO the nature of sexuality and reactions when it is altered or threatened. Provide information about normality of these problems and that many people find it helpful to seek assistance with adaptation process. Acknowledges legitimacy of the problem.
Sexuality encompasses the way men and women view themselves as individuals and how they relate between and among themselves in every area of life.
Advise client of side effects of prescribed cancer treatment that are known to affect sexuality. Anticipatory guidance can help client and SO begin the process of adaptation to new state.
Provide private time for hospitalized client. Knock on door and receive permission from client and SO before entering. Sexual needs do not end because the client is hospitalized. Intimacy needs continue and an open and accepting attiude for the expression of those needs is essential.
Refer to sex therapist, as indicated. May require additional assistance in dealing with situation. This creates a supportive climate and sends message of caring. Do this by involving the patient in decision making, by giving information, and by enabling the patient to control the environment as appropriate. Patients become very dependent in the high-tech, medical environment and may relegate decision making to the health care providers.
This may be especially evident in patients of cultures or ethnic heritages different from the dominant health care providers. Review of past coping experiences and prior decision- making skills may assist the patient to recognize inner strengths. Self-confidence and security come with a sense of control. Determine what the doctor has told client and what conclusion client has reached.
Encourage client to share thoughts and feelings. Provides opportunity to examine realistic fears and misconceptions about diagnosis. Provide open environment in which client feels safe to discuss feelings or to refrain from talking. Helps client feel accepted in present condition without feeling judged and promotes sense of dignity and control. Maintain frequent contact with client. Talk with and touch client, as appropriate.
Provides assurance that the client is not alone or rejected; conveys respect for and acceptance of the person, fostering trust. Be aware of effects of isolation on client when required by immunosuppressionor radiation implant.
Limit use of isolation clothing, as possible. Sensory deprivation may result when sufficient stimulation is notavailable and may intensify feelings of anxiety, fear, and alienation. Assist client and SO in recognizing and clarifying fears to begin developingcoping strategies for dealing with these fears. Coping skills are often stressed after diagnosis and during differentphases of treatment. Support and counseling are often necessary to enableindividual to recognize and deal with fear and to realize that control and copingstrategies are available.
Explain the recommended treatment, its purpose, and potential side effects. Help client prepare for treatments. The goal of cancer treatment is to destroy malignant cells whileminimizing damage to normal ones. Treatment may includecurative, preventive, or palliative surgery as well as chemotherapy, internal orexternal radiation, or newer, organ-specific treatments such as whole-bodyhyperthermia or biotherapy.
Bone marrow or peripheral progenitor cell transplantmay be recommended for some types of cancer. The development pathway is often timeconsuming, expensive, and uncertain.
In addition, there are underdeveloped and inconsistent standards of evidence for evaluating the scientific validity of tests and a lack of appropriate study designs and analytical methods for these analyses IOM, , , Ensuring that diagnostic tests have adequate analytical and clinical validity is critical to preventing diagnostic errors. For example, in the Centers for Disease Control and Prevention and the Food and Drug Administration issued a warning about potential diagnostic errors related to false positives caused by contamination in a Lyme disease test Nelson et al.
As molecular diagnostic testing becomes increasingly complex such as the movement from single biomarker tests to omicsbased tests that rely on high-dimensional data and complex algorithms , there is considerable interest in ensuring their appropriate development and use IOM, Molecular diagnostic testing presents many regulatory, clinical practice, and reimbursement challenges; an Institute of Medicine study is looking into these issues and is expected to release a report in IOM, b.
For example, one regulatory issue is the oversight of laboratorydeveloped tests, an area that has been met with considerable controversy see Table Evans and Watson, ; Sharfstein, A clinical practice issue is next generation sequencing, which may frequently identify new genetic variants with unknown implications for health outcomes ACMG Board of Directors, Medical imaging plays a critical role in establishing the diagnoses for innumerable conditions and it is used routinely in nearly every branch of medicine.
The advancement of imaging technologies has improved the ability of clinicians to detect, diagnose, and treat conditions while also allowing patients to avoid more invasive procedures European Society of Radiology, ; Gunderman, For many conditions e. The appropriate choice of imaging modality depends on the disease, organ, and specific clinical questions to be addressed. CT procedures are frequently used to assess and diagnose cancer, circulatory system diseases and conditions, inflammatory diseases, and head and internal organ injuries.
A majority of MRI procedures are performed on the spine, brain, and musculoskeletal system, although usage for the breast, prostate, abdominal, and pelvic regions is rising IMV, Medical imaging is characterized not just by the increasingly precise anatomic detail it offers but also by an increasing capacity to illuminate biology.
For example, magnetic resonance spectroscopic imaging has allowed the assessment of metabolism, and a growing number of other MRI sequences are offering information about functional characteristics, such as blood perfusion or water diffusion. In addition, several new tracers for. Functional and molecular imaging data may be assessed qualitatively, quantitatively, or both.
Although other forms of diagnostic testing can identify a wide array of molecular markers, molecular imaging is unique in its capacity to noninvasively show the locations of molecular processes in patients, and it is expected to play a critical role in advancing precision medicine, particularly for cancers, which often demonstrate both intra- and intertumoral biological heterogeneity Hricak, The growing body of medical knowledge, the variety of imaging options available, and the regular increases in the amounts and kinds of data that can be captured with imaging present tremendous challenges for radiologists, as no individual can be expected to achieve competency in all of the imaging modalities.
General radiologists continue to be essential in certain clinical settings, but extended training and sub-specialization are often necessary for optimal, clinically relevant image interpretation, as is involvement in multidisciplinary disease management teams.
Furthermore, the use of structured reporting templates tailored to specific examinations can help to increase the clarity, thoroughness, and clinical relevance of image interpretation Schwartz et al.
Like other forms of diagnostic testing, medical imaging has limitations. Some studies have found that between 20 and 50 percent of all advanced imaging results fail to provide information that improves patient outcome, although these studies do not account for the value of negative imaging results in influencing decisions about patient management Hendee et al.
Imaging may fail to provide useful information because of modality sensitivity and specificity parameters; for example, the spatial resolution of an MRI may not be high enough to detect very small abnormalities. Inadequate patient education and preparation for an imaging test can also lead to suboptimal imaging quality that results in diagnostic error. Perceptual or cognitive errors made by radiologists are a source of diagnostic error Berlin, ; Krupinski et al.
In addition, incomplete or incorrect patient information, as well as insufficient sharing of patient information, may lead to the use of an inadequate imaging protocol, an incorrect interpretation of imaging results, or the selection of an inappropriate imaging test by a referring clinician.
Referring clinicians often struggle with selecting the appropriate imaging test, in part because of the large number of available imaging options and gaps in the teaching of radiology in medical schools. Although consensus-based guidelines e.
The use of clinical decision support systems at the point of care as well as direct consultations with radiologists have been proposed by the ACR as methods for improving imaging test selection Allen and Thorwarth, There are several mechanisms for ensuring the quality of medical imaging.
The Mammography Quality Standards Act MQSA —overseen by the Food and Drug Administration—was the first government-mandated accreditation program for any type of medical facility; it was focused on X-ray imaging for breast cancer. MQSA provides a general framework for ensuring national quality standards in facilities that perform screening mammography IOM, MQSA requires all personnel at facilities to meet initial qualifications, to demonstrate continued experience, and to complete continuing education.
MQSA addresses protocol selection, image acquisition, interpretation and report generation, and the communication of results and recommendations. In addition, it provides facilities with data on diagnostic performance that can be used for benchmarking, self-monitoring, and improvement.
MQSA has decreased the variability in mammography performed across the United States and improved the quality of care Allen and Thorwarth, However, the ACR noted that MQSA is complex and specified in great detail, which makes it inflexible, leading to administrative burdens and the need for extensive training of staff for implementation Allen and Thorwarth, It also focuses on only one medical imaging modality in one disease area; thus, it does not address newer screening technologies IOM, The requirements include personnel qualifications, image quality, equipment performance, safety standards, and quality assurance and quality control ACR, a.
There are four CMS-designated accreditation organizations for medical imaging: MIPPA also mandated that, beginning in , ordering clinicians will be required to consult appropriateness criteria to order advanced medical imaging procedures, and the act called for a demonstration project evaluating clinician compliance with appropriateness criteria Timbie et al. The consult may help to confirm or reject the working diagnosis or may provide information on potential treatment options.
Clinicians can also recommend that the patient seek a second opinion from another clinician to verify their impressions of an uncertain diagnosis or if they believe that this would be helpful to the patient. Diagnostic consultations can also be arranged through the use of integrated practice units or diagnostic management teams Govern, ; Porter, ; see Chapter 4. The committee elaborated on several aspects of the diagnostic process which are discussed below, including.
One of the complexities in the diagnostic process is the inherent uncertainty in diagnosis. This does not mean that a diagnosis needs to be absolutely certain in order to initiate treatment.
Absolute certainty in diagnosis is unattainable, no matter how much information we gather, how many observations we make, or how many tests we perform.
As the inferential process unfolds, our confidence as [clinicians] in a given diagnosis is enhanced by the gathering of data that either favor it or argue against competing hypotheses.
Our task is not to attain cer-. Thus, the probability of disease does not have to be equal to one diagnostic certainty in order for treatment to be justified Pauker and Kassirer, The decision to begin treatment based on a working diagnosis is informed by: The risks associated with diagnostic testing are important considerations when conducting information-gathering activities in the diagnostic process.
While underuse of diagnostic testing has been a long-standing concern, overly aggressive diagnostic strategies have recently been recognized for their risks Zhi et al. However, there is growing recognition that overly aggressive diagnostic pursuits are putting patients at greater risk for harm, and they are not improving diagnostic certainty Kassirer, ; Welch, When considering diagnostic testing options, the harm from the procedure itself needs to 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. In addition, the risk for harm needs to take into account the cascade of diagnostic testing and treatment decisions that could stem from a diagnostic test result. Included in these assessments are 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 limited 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.
However, it is important to note. A treatment that is beneficial for some patients might not be beneficial for others with the same condition Kent and Hayward, , hence the interest in precision medicine, which is hoped to better tailor therapy to maximize efficacy and minimize toxicity Jameson and Longo, In addition, there are isolated cases where the morbidity and the mortality of a diagnostic procedure and the likelihood of disease is sufficiently high that significant therapy has been given empirically.
Moroff and Pauker described a decision analysis in which a year-old practicing lawyer with a new 1. Of major importance in the diagnostic process is the element of time.
Some diagnoses can be determined in a very short time frame, 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 a number of 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 very difficult to determine which particular 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, 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. 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. In these cases, the benefit of treating the disease promptly can greatly exceed the potential harm from unnecessary treatment.
Consequently, the threshold for ordering diagnostic testing or for initiating treatment becomes quite low for such health problems Pauker and Kassirer, , 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, , b.
Diagnosis can be especially challenging in older patients because classic presentations of disease are less common in older adults Jarrett et al. For example, infections such as pneumonia or urinary tract infections often do not present in older patients with fever, cough, and pain but rather with symptoms such as lethargy, incontinence, loss of appetite, or disruption of cognitive function Mouton et al.
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. Sensory limitations in older adults, such as hearing and vision impairments, can also contribute to challenges in making diagnoses Campbell et al. Physical illnesses often present with a change in cognitive status in older individuals without dementia Mouton et al. In older adults with mild to moderate dementia, such illnesses can manifest with worsening cognition.
Older patients who have 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, 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, ; IOM, ; The Joint Commission, 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.
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.
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, Compared to physical diagnoses, many mental health diagnoses rely on patient reports and observation; there are few biological tests that are used in such diagnoses Pincus, A key challenge can be distinguishing physical diagnoses from mental health diagnoses; sometimes physical conditions manifest as psychiatric ones, and vice versa Croskerry, a; Hope et al.
In addition, there are concerns about missing psychiatric diagnoses, as well as overtreatment concerns Bor, ; Meyer and Meyer, ; Pincus, 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, a.
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. Understanding the clinical reasoning process and the factors that can impact it are important to improving diagnosis, given that clinical reasoning processes contribute to diagnostic errors Croskerry, a; Graber, Health care professionals involved in the diagnostic process have an obligation and ethical responsibility to employ clinical reasoning skills: The current understanding of clinical reasoning is based on the dual process theory, a widely accepted paradigm of decision making.
The dual process theory integrates analytical and non-analytical models of decision making see Box Analytical models slow system 2 involve a conscious, deliberate process guided by critical thinking Kahneman, Nonanalytical models fast system 1 involve unconscious, intuitive, and automatic pattern recognition Kahneman, Fast system 1 nonanalytical, intuitive automatic processes require very little working memory capacity.
They are often triggered by stimuli or result from overlearned associations or implicitly learned activities. In contrast, slow system 2 reflective, analytical processing places a heavy load on working memory and involves hypothetical and counterfactual reasoning Evans and Stanovich, ; Stanovich and Toplak, System 2 processing requires individuals to generate mental models.
Analytical models slow system 2. Hypotheticodeductivism is an analytical reasoning model that describes clinical reasoning as hypothesis testing Elstein et al. The steps involved in hypothesis testing include. Analytical reasoning models have several additional characteristics. First, the generation of a set of hypotheses that occurs after cue acquisition facilitates the construction of a differential diagnosis, with evidence suggesting that the consideration of potential hypotheses prior to gathering information can improve diagnostic accuracy Kostopoulou et al.
Second, in order to supplement hypotheses retrieved from memory, some clinicians may employ clinical decision support tools. Third, the evolving list of diagnostic hypotheses determines subsequent information-gathering activities Kassirer et al. Fourth, the entire process involves, either explicitly or implicitly, clinicians assigning and updating the probability of each potential diagnosis, given the available data Kassirer et al.
These models hold that clinical problem-solving tasks, such as diagnosis, require deliberate, logically sound reasoning by clinicians. Thus, clinical reasoning can be improved by developing the critical thinking skills Papp et al. They also imply that clinical reasoning uses the presence or absence of specific signs or symptoms to be evidence that either confirms or disproves a diagnosis.
Hypothetical thinking occurs when one reasons about what should occur if some condition held: Counterfactual reasoning occurs when one thinks about what should occur if the situation differed from how it actually is.
However, studies also suggest that experience is crucial to the development of expertise and that general problemsolving skills, such as hypothesis testing, cannot account for differences in clinical reasoning skills between experts and novices Elstein and Schwarz, ; Groen and Patel, ; Neufeld et al. These findings support a role for nonanalytical models of clinical reasoning and the importance of content knowledge and clinical experience. Nonanalytical models fast system 1.
Broadly construed through a pattern-recognition framework, nonanalytical models attempt to understand clinical reasoning through human categorization and classification practices. These models suggest that clinicians make diagnoses and choose treatments by matching presenting patients to their mental models of diseases or information about diseases that is stored in memory.
Although the nature of these mental models remain under debate, most assume that they are either exemplars specific patients seen previously and stored in memory as concrete examples or prototypes an abstract disease conceptualization that weighs disease features according to their frequency Bordage and Zacks, ; Norman, ; Rosch and Mervis, ; Schmidt et al.
Expert pattern matching by experienced clinicians may involve illness scripts, in which elaborated disease knowledge includes enabling conditions or risk factors e. After encountering a patient, a clinician may activate a single illness script or multiple scripts.
Illness scripts differ from exemplars and prototypes by having more extensive knowledge stored for each disease. As the diagnostic process evolves, the clinician matches the activated scripts against the presenting signs and symptoms, with the best matching script offered as the most likely diagnosis. While exemplars, prototypes, and illness scripts are assumed to encode different types of information about disease conditions—that is, actual instances versus typical presentation versus multidimensional information—pattern recognition models assume them to play the same role in diagnosis.
Heuristics—mental shortcuts or cognitive strategies that are automatically and unconsciously employed—are particularly important for decision making Gigerenzer and Goldstein, Heuristics can facilitate decision making but can also lead to errors, especially when patients present with atypical symptoms Cosmides and Tooby, ; Gigerenzer, ; Kahneman, ; Klein, ; Lipshitz et al. When a heuristic fails, it is referred to as a cognitive bias.
Cognitive biases, or predispositions to think in a way that leads to failures in judgment, can also be caused by affect and motivation Kahneman, Prolonged learning in a regular and predictable environment increases the success-fulness of heuristics, whereas uncertain and unpredictable environments are a chief cause of heuristic failure Kahneman, ; Kahneman and Klein, There are many heuristics and biases that affect clinical reasoning and decision making see Table for medical and nonmedical examples.
Additional examples of heuristics and biases that affect decision making and the potential for diagnostic errors are described below Croskerry, b:. In addition to cognitive biases, research suggests that fallacies in reasoning, ethical violations, and financial and nonfinancial conflicts of interest can influence medical decision making Seshia et al.
The interaction between fast system 1 and slow system 2 remains controversial. Some hold that these processes are constantly occurring in parallel and that any conflicts are resolved as they arise. When system 2 overrides system 1, this can lead to improved decision making, because engaging in analytical reasoning may correct for inaccuracies. It is important to note that slow system 2 processing does not guarantee correct decision making. For instance, clinicians with an inadequate knowledge base may not have the information necessary to make a correct decision.
There are some instances when system 1 processing is correct, and the override from system 2 can contribute to incorrect decision making. However, when system 1 overrides system 2 processing, this can also result in irrational decision making. Intervention by system 2 is likely to occur in novel situations when the task at hand is difficult; when an individual has minimal knowledge or experience Evans and Stanovich, ; Kahneman, ; or when an individual deliberately employs strategies to overcome known biases Croskerry et al.
Monitoring and intervention by system 2 on system 1 is unlikely to catch every failure because it is inefficient and would require sustained vigilance, given that system 1 processing often leads to correct solutions Kahneman, Factors that affect working memory can impede the ability of system 2 to monitor and, when necessary, intervene on system 1 processes Croskerry, b. For example, if clinicians are tired or distracted by elements in the work system, they may fail to recognize when a decison provided by system 1 processing needs to be reconsidered Croskerry, b.
System 1 and system 2 perform optimally in different types of clinical practice settings. System 1 performs best in highly reliable and predictable environments but falls short in uncertain and irregular settings Kahneman and Klein, ; Stanovich, System 2 performs best in relaxed and unhurried environments.
This section applies the dual process theory of clinical reasoning to the diagnostic process Croskerry, a,b; Norman and Eva, ; Pelaccia et al. Croskerry and colleagues provide a framework for understanding the cognitive activities that occur in clinicians as they iterate through information gathering, information integration and interpretation, and determining a working diagnosis Croskerry et al.
When patients present, clinicians gather information and compare that information with their knowledge about various diseases. When a patient presents to a clinician, the initial data include symptoms and signs of disease, which can range from single characteristics of disease to illness scripts.
If the symptoms and signs of illness are recognized, system 1 processes are used. If they are not recognized, system 2 processes are used. Repetition of data to system 2 processes may eventually be recognized as a new pattern and subsequently processed through system 1.
Multiple arrows stem from system 1 processes to depict intuitive, fast, parallel decision making. Because system 2 processes are slow and serial, only one arrow stems from system 2 processes, depicting analytical decision making.
The executive override pathway shows that system 2 surveillance has the potential to overrule system 1 decision making. The irrational override pathway shows the capability for system 1 processes to overrule system 2 analytical decision making.
The toggle arrow T illustrates how the decision maker may employ both fast system 1 and slow system 2 processes throughout the decision-making process. Origins of bias and theory of debiasing.
This initial pattern matching is an instance of fast system 1 processing. If a sufficiently unique match occurs, then a diagnosis may be made without involvement of slow system 2. However, some symptoms or signs may not be recognized or they may trigger mental models for several diseases at once. When this happens, slow system 2 processing may be engaged, and the clinician will continue to gather, integrate, and interpret potentially relevant information until a working diagnosis is generated and communicated to the patient.
When this process triggers pattern matches for several mental models of disease, a differential diagnosis is developed. At this point, the diagnostic process shifts to slow system 2 analytical reasoning. Based on their knowledge base, clinicians then use deductive reasoning: If this patient has disease A, what clinical history and physical examination findings might be expected, and does the patient have them? This process is repeated for each condition in the differential diagnosis and may be augmented by additional sources of information, such as diagnostic testing, further history gathering or physical examination, or referral or consultation.
The cognitive process of reassessing the probability assigned to each potential diagnosis involves inductive reasoning, 5 or going from observed signs and symptoms to the likelihood of each disease to determine which hypothesis is most likely Goodman, This can help refine and narrow the differential diagnosis. Further information gathering activities or treatment could provide greater certainty regarding a working diagnosis or suggest that alternative diagnoses be considered.
Throughout this process, clinicians need to communicate with patients about the working diagnosis and the degree of certainty involved. Task complexity and expertise affect which cognitive system is dominantly employed in the diagnostic process. System 1 processing is more likely to be used when patients present with typical signs and symptoms of disease.
However, system 2 processing is likely to intervene in situations marked by novelty and difficulty, when patients present with atypical signs and symptoms, or when clinicians lack expertise Croskerry, b; Evans and Stanovich, Novice clinicians and medical students are more likely to rely on analytical reasoning throughout the diagnostic process compared to experienced clinicians Croskerry, b; Elstein and Schwartz, ; Kassirer, ; Norman, Expert clinicians possess better developed mental models of diseases, which support more reliable pattern matching system 1 processes Croskerry, b.
The ability to create and develop mental models through repetition explains why expert clinicians are more likely to rely on pattern recognition when making diagnoses than are novices—continuous engagement with disease conditions allows the expert to develop more reliable mental models of disease—by retaining more exemplars, creating more nuanced prototypes, or developing more detailed illness scripts.
Figure illustrates the concept of calibration, or the process of a clinician becoming aware of his or her diagnostic abilities and limitations through feedback. Feedback mechanisms—both in educational settings see Chapter 4 and in learning health care systems see Chapter 6 —allow. Adapted with permission from The feedback sanction. Academic Emergency Medicine 7 Calibration enables clinicians to assess their diagnostic accuracy and improve their future performance.
Work system factors influence diagnostic reasoning, including diagnostic team members and tasks, technologies and tools, organizational characteristics, the physical environment, and the external environment.
For example, Chapter 6 describes how the physical environment, including lighting, noise, and layout, can influence clinical reasoning. Chapter 5 discusses how health IT can improve or degrade clinical reasoning, depending on the usability of health IT including clinical decision support , its integration into clinical workflow, and other factors.
Box describes how certain individual characteristics of diagnostic team members can affect clinical reasoning. As described above, the diagnostic process involves initial information gathering that leads to a working diagnosis. The process of ruling in or ruling out a diagnosis involves probabilistic reasoning as findings are integrated and interpreted.
Probabilistic or Bayesian reasoning provides a formal method to avoid some cognitive biases when integrating and interpreting information.
For instance, when patients present with typical symptoms but the disease is rare e. Using Bayesian reasoning and formally revising probabilities of the various diseases under consideration helps clinicians avoid these errors.
Clinicians can then decide whether to pursue additional information gathering or treatment based on an accurate estimate of the likelihood of disease, the harms and benefits of treatment, and patient preferences Kassirer et al. Probabilistic reasoning is most often considered in the context of diagnostic testing, but the presence or absence of specific signs and symptoms can also help to rule in or rule out diseases. The likelihood of a positive finding the presence of signs or symptoms or a positive test when disease is present is referred to as sensitivity.
The likelihood of a negative finding the absence of symptoms, signs, or a negative test when a disease is absent is referred to as specificity. If a sign, symptom, or test is always positive in the presence of a particular disease percent sensitivity , then the absence of that symptom, sign, or test rules out disease e.
There are a number of individual characteristics that can affect clinical reasoning, including intelligence and knowledge, age, affect, experience, personality, physical state, and gender. High scores on intelligence tests indicate that an individual is adept at these cognitive tasks and is more likely to engage system 2 processes to monitor and, when necessary, override system 1 processing Croskerry and Musson, ; Eva, ; Evans and Stanovich, Although intelligence that allows one to monitor and override system 1 processing is important, it rarely suffices by itself for good clinical reasoning.
A sufficiently large knowledge base of both biological science and disease conditions is also important. It is likely that clinician age has an impact on clinical reasoning abilities Croskerry and Musson, ; Eva, ; Singer et al. For example, older and more experienced clinicians may be better able to employ system 1 processes in diagnosis, due to well-developed mental models of disease. However, as clinicians age, they tend to have more trouble considering alternatives and switching tasks during the diagnostic process Croskerry and Musson, ; Eva, Not all individuals experience cognitive or memory decline at the same rate or time though many people start to experience moderate declines in analytical reasoning capacity at some point in their 70s Croskerry and Musson, Affective factors such as mood and emotional state often play a role both positive and negative in clinical reasoning and decision making Blanchette and Richards, ; Croskerry, b; Croskerry et al.
When an obvious solution to a problem is not present, emotions may help direct people toward an outcome that is better than one that would be produced by random choice Johnson-Laird and Oatley, ; Stanovich, In cases where precision is important or when an emotional response is unlikely to be a reliable indicator, the affect heuristic can lead to negative consequences.
In these cases, the. Affective states such as irritation and stress due to environmental conditions can also affect reasoning, primarily through decreasing the ability of system 2 processes to monitor and override system 1 processes Croskerry et al. Novices and experts employ different decision-making practices Kahneman, Expert nurses, for instance, have been found to collect a wider range of cues than their novice counterparts during clinical decision making Hoffman et al.
Expert clinicians are more likley to rely on system 1 processing during the diagnostic process, while novice practioners and medical students rely more on conscious, explicit, linear analytical reasoning. Furthermore, expert clinicians are likely to be more accurate than novices when they employ system 1 processes because they have larger stores of developed mental models of disease conditions.
While some have argued that experts are more susceptible to premature closure i. Individual personality influences clinical reasoning and decision making Croskerry and Musson, Arrogance, for instance, may lead to clinician overconfidence, a personality trait identified as a source of diagnostic error Berner and Graber, ; Croskerry and Norman, Other personality traits, such as openness to experiences and agreeableness, could improve decision making in some individuals if it increases their openness to divergent views and feedback.
Fatigue and sleep deprivation have been found to impede system 2 processing interventions on system 1 processes Croskerry and Musson, ; Zwaan et al. Additionally, some research suggests that there are gender-specific effects associated with reasoning, including a male tendency toward risk-taking Byrnes et al. Other studies have failed to replicate this proposed gender effect Croskerry and Musson, If a sign, symptom, or test is always negative in the absence of a particular disease percent specificity , then the presence of that symptom, sign, or test rules in disease e.
However, nearly all signs, symptoms, or test results are neither percent sensitive or specific. For example, studies suggest exceptions for findings such as Kayser—Fleischer rings with other causes of liver disease Frommer et al. Bayesian calculators are available to facilitate these probability revision analyses Simel and Rennie, Box works through two examples of probabilistic reasoning. While most clinicians will not formally calculate probabilities, the logical principles behind Bayesian reasoning can help clinicians consider the trade-offs involved in further information gathering, decisions about treatment, or evaluating clinically ambiguous cases Kassirer et al.
Bayesian reasoning then calculates the likelihood of GABHS among those without nasal congestion to be The presence of three additional distinguishing symptoms tonsillar exudates, no cough, and swollen, tender anterior cervical nodes would raise the likelihood of GABHS to 70 percent, and if those three additional distinguishing symptoms were absent, the likelihood of GABHS would fall to 3 percent Centor et al.
To provide a second example, suppose a woman has a 0. Among women with breast cancer, a mammogram will be positive in 90 percent sensitivity. Among women without breast cancer, a mammogram will be positive in 7 percent false positive rate or 1 minus a specificity of 93 percent. If the mammogram is positive, what is the likelihood of this woman having breast cancer?
Among 1, women, 8 0. Among the without breast cancer, 69 7 percent of will have a false positive mammogram. Thus, among the 76 women with a positive mammogram, 7—or 9 percent—will have breast cancer.
When a very similar question was presented to practicing physicians with an average of 14 years of experience, their answers ranged from 1 percent to 90 percent, and very few answered correctly Gigerenzer and Edwards, Thus, a better understanding of probabilistic reasoning can help clinicians apply signs, symptoms, and test results to subsequent decision making such as refining or expanding a differential diagnosis, determining the likelihood that a patient has a specific diagnosis on the basis of a positive or negative test result, deciding whether retesting or ordering new tests is appropriate, or beginning treatment see Chapter 4.
Advances in biology and medicine have led to improvements in prevention, diagnosis, and treatment, with a deluge of innovations in diagnostic testing IOM, , a; Korf and Rehm, ; Lee and Levy, The rising complexity and volume of these advances, coupled with clinician time constraints and cognitive limitations, have outstripped human capacity to apply this new knowledge IOM, a, a; Marois and Ivanoff, ; Miller, ; Ostbye et al. The sheer number of potential diagnoses illustrates this complexity: With the rapidly increasing number of published scientific articles on health see Figure , health care professionals have difficulty keeping up with the breadth and depth of knowledge in their specialties.
For example, to remain up to date, primary care clinicians would need to read for an estimated McGlynn and colleagues found that Americans receive only about half of recommended care, including recommended diagnostic processes. Thus, clinicians need approaches to ensure they know the evidence base and are well-equipped to deliver care that reflects the most up-to-date information.
One of the ways that this is accomplished is through team-based. Publications have increased steadily over 40 years. In addition, systematic reviews and clinical practice guidelines CPGs help synthesize available information in order to inform clinical practice decision making IOM, a,b.
CPGs came into prominence partly in response to studies that found excessive variation in diagnostic and treatment-related care practices, indicating that inappropriate care was occurring Chassin et al. CPGs can include diagnostic criteria for specific conditions as well as approaches to information gathering, such as conducting a clinical history and interview, the physical exam, diagnostic testing, and consultations.
CPGs translate knowledge into clinical care decisions, and adherence to evidence-based guideline recommendations can improve health care quality and patient outcomes Bhatt et al.
However, there have been a number of challenges to the development and use of CPGs in clinical practice IOM, a, a,b; Kahn et al. Two of the primary challenges are the inadequacy of the evidence base supporting CPGs and determining the applicability of guidelines for individual patients IOM, a, b. For example, individual patient preferences for possible health outcomes may vary, and with the growing prevalence of chronic disease, patients often have comorbidities or competing causes of mortality that need to be considered.
CPGs may not factor in these patient-specific variables Boyd et al. In addition, the majority of scientific evidence about any diagnostic test typically is focused on test accuracy and not on the impact of the test on patient outcomes Brozek et al. This makes it difficult to develop guidelines that inform clinicians about the role of diagnostic tests within the diagnostic process and about how these tests can influence the path of care and health outcomes for a patient Gopalakrishna et al.
Furthermore, diagnosis is generally not a primary focus of CPGs; diagnostic testing guidelines typically account for a minority of recommendations and often have lower levels of evidence supporting them than treatment-related CPGs Tricoci et al. The adoption of available clinical practice guideline recommendations into practice remains suboptimal due to concerns about the trustworthiness of the guidelines as well as the existence of varying and conflicting guide-.
Health care professional societies have also begun to develop appropriate use or appropriateness criteria as a way of synthesizing the available scientific literature and expert opinion to inform patient-specific decision making Fitch et al. With the growth of diagnostic testing and substantial geographic variation in the utilization of these tools due in part to the limitations in the evidence base supporting their use , health care professional societies have developed appropriate use criteria aimed at better matching patients to specific health care interventions Allen and Thorwarth, ; Patel et al.
Checklists are another approach that has been implemented to improve the safety of care by, for example, preventing health care—acquired infections or errors in surgical care. Checklists have also been proposed to improve the diagnostic process Ely et al. Developing checklists for the diagnostic process may be a significant undertaking; thus far, checklists have been developed for discrete, observable tasks, but the complexity of the diagnostic process, including the associated cognitive tasks, may represent a fundamentally different type of challenge Henriksen and Brady, About the AAFP proficiency testing program.
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A nursing diagnosis is a statement indicating several different potential problems a patient may face. A nurse will diagnose and treat the. Therefore we identify the risk factors that predispose the individual to a potential problem. The correct statement for a NANDA-I nursing diagnosis would be: Risk. POTENTIAL NURSING DIAGNOSISSittie Norjannah P. Santos.