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Official Journal of the Society to Improve Diagnosis in Medicine (SIDM)

Editor-in-Chief: Graber, Mark L. / Plebani, Mario

Ed. by Argy, Nicolas / Epner, Paul L. / Lippi, Giuseppe / Singhal, Geeta / McDonald, Kathryn / Singh, Hardeep / Newman-Toker, David

Editorial Board: Basso , Daniela / Crock, Carmel / Croskerry, Pat / Dhaliwal, Gurpreet / Ely, John / Giannitsis, Evangelos / Katus, Hugo A. / Laposata, Michael / Lyratzopoulos, Yoryos / Maude, Jason / Sittig, Dean F. / Sonntag, Oswald / Zwaan, Laura

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The diagnostic field’s players and interactions: from the inside out

Kathryn M. McDonald
  • Corresponding author
  • Stanford University School of Medicine and University of California, Berkeley, School of Public Health, Center Health Policy/Center for Primary Care and Outcomes Research, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019, USA
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Published Online: 2014-01-08 | DOI: https://doi.org/10.1515/dx-2013-0023


For diagnoses that require inputs from multiple players – patients, informal caregivers, health care professionals – a team approach to coordinating diagnostic care has the potential to improve outcomes. Taking a patient-system perspective helps elucidate important factors relevant to team-based diagnostic performance. These factors are conceptualized as a metaphoric playing field that has goals, players interacting, unavoidable uncertainties and influential social conditions specifically tied to the diagnosis phase of care. In terms of rules of the game, the patient-system interaction might be guided by application of Gittell and colleague’s relational coordination concepts, and understood within a broader social network framework of diagnosis, adapted from work by Berkman and colleagues. Patient-centered metrics are also needed to monitor the success of diagnosis.

Keywords: diagnostic error; patient-centeredness; relational coordination; sociological Influences; teamwork

Is diagnosis an individual sport or a team sport? The answer depends, as is the case for most questions that delve below the surface of complex issues. In some cases, achieving an accurate and timely diagnosis is straightforward and made by one physician in a quick encounter with a patient, such as “you just have a common cold”. At the other end of the extreme, diagnosis relies on a series of contacts the patient must make while navigating through the health care system from a physician’s office to the place where her blood is drawn, followed by an abdominal ultrasound, then the pharmacy to fill a prescription ordered by doctor number one, and then off to a couple of specialists knowledgeable in the two body systems that have lit up suspicion. But that may not be all, again depending upon what happens in each office visit and outside the office. Further patient-system interactions to put a whole picture together and come up with a normal pressure hydrocephalus (NPH) diagnosis, for example, may or may not result depending upon how the team plays together, if at all. Did referrals to neurologist, urologist and orthopedic specialists result in anyone looking at three findings together – dementia, urinary incontinence, and gait disturbance? If observation of the classic triad for NPH is missed, the patient may experience consequential and potentially reversible cognitive declines that influence quality of life for both patient and family. Who on the team is responsible for this miss? Paradoxically, from a team perspective, the answer is no one and everyone.

A particular challenge in diagnosis is uncertainty, and how the various players understand its presence and influence. There may be uncertainties that are clinical in nature (i.e., different explanations for what is causing a patient’s symptoms), as well as those that emanate from the people side of diagnosis. Which specialists need to be called in? What will each contribute to the diagnostic work-up? How will they coordinate their activities? Will they coordinate their activities? When, how and why will they seek patient involvement in the diagnostic process? What will be the best plan for making a diagnosis (or diagnoses)? How will it depend on the clinical presentation? Answers to these questions may result in a great deal of variation based on levels of uncertainty about the best way to proceed for each decision. Fully appreciating the multiple sources of uncertainty in diagnostic workups is the first challenge of diagnostic teamwork.

While evidence is mounting about the advantages of teamwork for improving patient outcomes, most if not all has focused on the treatment side of the health care enterprise [1]. Once a diagnosis is established, then a health care system can organize around it (e.g., chronic care model [2], disease management, and even newer financing approaches like bundled payment). In the treatment phase of care, diagnosis is simply a means to an end, the method by which a treatment team can be formed with specific goals. Fundamental to definitions of care coordination is a goal [3]. But what is the goal during the diagnostic phase of care? The goal of achieving the true diagnosis while maintaining a reasonable level of doubt (i.e., a working diagnosis concept) may not be squarely on everyone’s radar as a patient is sent to different specialists and care settings across a potentially fragmented system. Being unsure about who is a member of a patient’s diagnostic team and what specific role each person plays are uncertainties in diagnosis, not yet fully appreciated in terms of consequences for goal-directed teamwork.

In addition, the patient represents a team member oft overlooked by a health care system organized around those delivering care. This is not to say that anyone forgets that the patient exists or is central to the existence of a health care system. What is debated is the patient’s role – do we consider the patient as a metaphoric ball thrown towards the goal post, handled with care preferably, or as a part of the team to the extent desired and feasible by a given patient? Patient involvement in the diagnostic journey may take different forms, many of which are only recently being articulated [4].

Patients and their caregivers – both professional and informal – still need to work out the diagnostic game’s rules more clearly for effective diagnostic teamwork. Shared decision making about treatment options and patient activation mechanisms in chronic care may offer foundations for efforts focused on diagnosis, as long as unique aspects of diagnosis are considered. What models of shared diagnosis between patient and physician might be developed? What teamwork models might be most useful to the diagnostic process? Under what circumstances will these models work?

It is likely easier to develop models for situations that recur frequently and present rather homogeneously. On the treatment side, many people may have traveled the same pathway with known crossroads and signposts. But the path to diagnosis may be harder to predict given the possibility for different potential pathways to the diagnostic label, idiosyncratic ways the body presents an as yet unidentified ailment, and the inexperience of the patient (by definition, when the patient has never experienced the path to the particular diagnosis before). How can the diagnostic system become more robust and reliable under these circumstances? Like other patient safety concerns, understanding causes of mishaps is one strategy for developing options for improvement. Some studies have split the underlying causes for diagnostic error into cognitive and systems problems [5, 6]. Others have developed classification schemes with more categories for potential remediation [7, 8].

In addition to targeted improvement strategies, cross-cutting approaches could include better diagnostic care coordination. Diagnosis is often complex with time-constraints, interdependencies in accomplishing the diagnostic task between people exchanging information, and unavoidable uncertainties. These three complexity factors (i.e., time urgency, interdependence and uncertainty) are known in management sciences to require high-powered, flexible, coordinating interventions. Specifically, attention to relational aspects of coordination between those in different roles is critical to achieve better performance. Some health care researchers apply novel metrics and strategies for these greater complexity situations from a framework by Gittell et al. called relational coordination to understand the dynamics present in performance-oriented collaboration (teamwork) [9]. A validated relational coordination measure assesses seven key dimensions – quality of communication (timely, frequent, accurate, problem-solving) and role relationships (shared goals, shared knowledge, mutual respect) among participants in a health care activity such as diagnosis [9, 10]. The patient and family can be included as participants in both the measure and the general characterization of those involved in performing tasks that need to be achieved to get to a desired outcome, in this case a timely and correct diagnosis.

The argument for including the patient (and/or family) in the team of participants is that the common denominator of all diagnoses is the patient. This person experiences the events internally and externally that are both determinants and consequences of a correct, missed, wrong or pending diagnosis. Diagnostic performance often affects the patient′s (and family’s) life in significant ways.

Further work to understand improvement opportunities for diagnosis from a patient-system perspective might benefit by going beyond just the health care system, to consideration of broader psycho-social frameworks. In response to mounting evidence supporting that social associations have a strong effect on health, Berkman and colleagues developed a conceptual model of important linkages from societal to psychological and biologic processes [11]. The framework integrates across theories and empirical evidence related to social networks, social integration and social support, all of which could have influences on the diagnostic journey that patients and their caregivers take, as shown in Figure 1. As a broad theory of cascading causal processes contributing to the observed positive effect of social integration (versus isolation) on health outcomes, the model is dichotomized into upstream and downstream linkages. The upstream operations shape the development and structure of social networks, the nexus of the model. On the other end are the processes downstream of the social networks that influence patient outcomes, including getting a correct diagnosis.

Social network framework of diagnosis, adapted from Berkman et al. [11].
Figure 1

Social network framework of diagnosis, adapted from Berkman et al. [11].

Influences of social networks on social and interpersonal behavior (e.g., degree of patient involvement in diagnostic journey) which may act on diagnosis and health include: 1) social support provision, and 2) social influence [11, 12]. These factors may influence a patient’s diagnosis via: 1) health behaviors (including help-seeking, and adherence to medical recommendations), and 2) individual psychology (including self-efficacy, distress, sense of well-being, and coping effectiveness).

The type and extent of social support provided depends on the patient’s social network [11, 13]. Moreover, social support may be helpful or detrimental as a function of characteristics of the network structure (e.g., a person’s position relative to others within a network of social ties). On the positive side, social support can be emotional, instrumental, appraisal or informational. In the diagnostic context, emotional support may include a spouse sympathizing about a distressing symptom and the worry that is aroused. Having such support may allow the patient to be less absorbed in worry, and more able to follow-up and make a medical appointment to be checked. The spouse may even offer to call the doctor, take the loved one in for an invasive test, and so forth, as instrumental support. Appraisal support may be particularly relevant to diagnostic odyssey situations. Does the patient have a network of ties that help her discern any trouble with the path taken, offer feedback about new courses of action to revisit ruled out diagnosis, for example? Informational support may also be relevant, especially as more patients turn to the Internet to assess their symptoms. Those with more social ties to medical professionals may find help in interpreting information found from these sources. In addition, communities of people are forming around particular illnesses, such as on the website “Patients Like Me”, where patients report symptoms in detail. These virtual ties can play a supportive role in assisting patients, and even advancing research relevant to those looking for a diagnosis [14].

Berkman et al. emphasize that social support is not the only influence on behaviors (e.g., help-seeking) or psychological disposition (e.g., self-efficacy) [11]. They posit that people compare their attitudes to others in similar circumstances. The influence of social comparisons may be a fruitful area for understanding sense of personal control. Social comparison could affect how people perceive their symptoms prior to a diagnosis, and therefore may influence their actions. This part of Berkman et al’s model points to the potential utility of considering social influence on behavior and disposition during the uncertain phase of diagnosis.

When things get a bit more complicated, diagnosis is indeed a team sport, with the patient as the star player. Sometimes family members and other informal caregivers pinch hit for the patient. Including these members on the team, and helping support their involvement (to the extent they want) is part of the health care system’s responsibility. Setting up teamwork for success requires attention to all people with information pertinent to the end goal – a working diagnosis when there is one worth making. Developing metrics to monitor the success in diagnosis in a patient-centered way may be the next frontier for supporting effective teamwork and broad systems thinking in this domain.


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About the article

Corresponding author: Kathryn M. McDonald, Stanford University School of Medicine and University of California, Berkeley, School of Public Health, Center Health Policy/Center for Primary Care and Outcomes Research, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019, USA, Phone: +650-723-0559, Fax: +650-723-1919, E-mail:

Received: 2013-09-14

Accepted: 2013-11-11

Published Online: 2014-01-08

Published in Print: 2014-01-01

Conflict of interest statement The author declares no conflict of interest.

Citation Information: Diagnosis, Volume 1, Issue 1, Pages 55–58, ISSN (Online) 2194-802X, ISSN (Print) 2194-8011, DOI: https://doi.org/10.1515/dx-2013-0023.

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©2014 by Walter de Gruyter Berlin/Boston. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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