Katarina Jacobsson Categories by Heart : Shortcut Reasoning in a Cardiology Clinic

This article examines the practice of doctors and nurses to invoke the categories of age, sex, class, ethnicity, and/or lifestyle factors when discussing individual patients and patient groups. In what situations are such references explicitly made, and what does this practice accomplish? The material consists of field notes from a cardiology clinic in Sweden, and a theory of descriptive practice guided the analysis. When professionals describe patients, discuss decisions, or explain why a patient is ill, age, sex, class, ethnicity, and/or lifestyle serve as contextualization cues, often including widespread results from epidemiological research about groups of patients at higher or lower risk for cardiac disease. These categories work as shortcut reasoning to nudge interpretations in a certain direction, legitimize decisions, and strengthen arguments. In general, studying the descriptions of patients/clients/students provides an entrance to professional methods of reasoning, including their implicit moral assumptions.

regarding health and inequality in general, and inequality with regard to health care in particular, have been reported and debated in the Swedish mass media (for the equivalent in the UK see Davidson, Hunt, & Kitzinger, 2003). "Surviving breast cancer is now class-bound" 1 and "Unequal health care when the man is the norm" 2 are examples of headlines in our newspapers. In addition to the common use of demographic indicators when health issues are discussed, the idea that some diseases are caused by "lifestyle factors" (e.g., diet, smoking, lack of exercise) is extensively accepted in wider society (e.g., Nettleton, 2006;Bunton & MacDonald 2002). Risk factors are emphasized and various health recommendations presented repeatedly in newspapers, on television, in national health campaigns, and through preventive care in schools and workplaces. The epidemiological framework sits well with the risk society portrayed by Ulrich Beck (1992)-a society preoccupied with risk assessments and prognoses. The framework is widespread and tends to become an obvious point of reference with regard to not only health patterns in populations, but also descriptions of individuals. In this sense, a doctor, nurse, journalist, teacher, or practically anyone can discuss, evaluate, and scrutinize their fellow human beings according to well-known epidemiological results.
In other words, there are several actors involved in shaping societal ideas of health and illness, which are greatly inspired and influenced by statistical sociological health research and risk-factor epidemiology (Shim, 2002). This article deals with the specific manifestations of such ideas by medical professionals. During fieldwork at a cardiology clinic, it became clear that staff engaged in not only constructing and (re)producing the categories age, sex, class, and ethnicity in their talk about the patients, but they did so with a glance at popular "common" beliefs and knowledge of the distribution of health, health-related behavior, and debates on health-care inequalities. The aim of this article is to examine the practices of invoking the categories age, sex, class, ethnicity, or "lifestyle factors" when doctors and nurses describe and discuss individual patients and patient categories. In what situations are such references explicitly made and what does this practice accomplish?

Description, discretion, and morality
The qualitative study of the categories age, sex/gender, class, and ethnicity is vast and multifaceted. From an interactionist approach, scholars are interested in how people create and negotiate their age, gender, ethnic, racial, sexual, and class identities, whereas social constructionist scholars are concerned with "the doing of" age, sex, class, and ethnicity-a perspective greatly inspired by West and Zimmerman's (1987) article Doing Gender-and particularly with how these processes (re)produce dominant discourses (e.g., Mik-Meyer, 2011). In the present analysis, inquiries concerned how these central categories are invoked in specific situations and contexts and what this accomplishes (cf. Maynard, 1982;Holstein, 2013).
This study is based on underpinnings from two research fields: the sociology of medicine and the study of professions. With the former I share the position that everyday medical decisions or problem solving emerge situationally in a blend of medical and moral reasoning (e.g., Måseide, 2011;Silverman, 2004;Griffiths & Hughes, 1994). With the latter I share the standpoint that professional discretion is "...a way of reasoning about particular cases under conditions of indeterminacy," where standards and rules must be interpreted and actions that are taken must be justifiable (Molander & Grimen, 2010, p. 171; see also Hawkins, 1994). I will argue that the practice of staff to invoke categories such as age, sex, class, ethnicity, and lifestyle factors when discussing patients is one ingredient in such practical reasoning. In particular, I will focus on data where the medical staff refer to popularized epidemiological knowledge associated with these categories.
Theoretically, the analysis rests on the ethnomethodological stance that every description is a vital part of the reality it describes (Heritage, 1984), or more precisely, it draws on a theory of "descriptive practice" (Holstein, 2013). According to Holstein, instead of "seeking and finding" a client's problems, human service workers select and weave together descriptions that produce a client for the organization to treat, teach, or control. Though patient and client descriptions often seem objective and detached from a given situation, they are tailored for the actual purpose at hand (Maynard, 1982). Situationally relevant person-descriptions can be incorporated into professional arguments for or against certain courses of action; thus, professionals' descriptive practices form the basis for making decisions and taking action (Holstein, 2013). The choice of this perspective also means that I will refrain from disentangling the multiple definitions and conceptual meanings of the categories age, sex, class, ethnicity, and lifestyle. The analysis pays close attention to members' own use of these categories (or variations thereof) rather than preconceptualized ideas about their meanings (e.g., Garfinkel, 1988;Maynard & Manzo, 1993).
My ambition is restricted to identifying situations when these categories seem to be useful to the staff and in what way they are useful within that situation. What particular categories they invoke emerge situationally in interactions and cannot be predicted. Similarly, the subsequent strategy regarding the patient cannot be foreseen or taken for granted. Nevertheless, the way in which a patient is described harbors both medical and moral assumptions about that patient. Therefore, patient descriptions should not be considered "merely talk" given their constituent character (Holstein, 2013). Patient descriptions are mostly framed as medical facts, background details, or clinical judgments (e.g., Måseide, 2011;Jacobsson, 2013a). Yet, the moral dimension of professional work is embedded in the language of professionalism, which is currently marked by the ideals of evidence-based practice with its claims of objectivity, standardization, and best-practice routines. In the medical context studied here, the categories age, sex, class, and ethnicity in combination with "lifestyle factors" open up a range of (categorical) assumptions about individual patients and large patient groups. Thus, patient descriptions (or client/student/customer descriptions) provide an entrance to professional methods of reasoning, arguing, and explaining, and how these methods-in an ethnomethodological sense-touch on ordinary "common sense" methods (Lynch, 2008).

Methods and material
The body of material consists of field notes, interviews, and documents collected for a project on medical decision-making 3 Data was mainly gathered by "shadowing" doctors and nurses (Davies, 2003;Czarniawska, 2007) at a cardiology clinic in a Swedish public university hospital situated in a big city. The clinic had a capacity of approximately 50 in-patients divided into two units: coronary and heart failure. I spent time in both units, but more in the coronary unit, shadowing the staff to take part in their day-to-day work experience, routines, and practices. In a year I spent two month-long periods at the clinic, half of the time with nurses and half of the time with doctors (resulting in approximately 230 pages of typed field notes). Access was negotiated with the head of the cardiology clinic (a doctor) and the manager of the clinic (a nurse). Each day I was assigned a willing member of the staff, and I followed some of these staff members for more than one day. Because I went along with the staff to patients, meetings, and surgery, I met with a large proportion of the entire staff at the cardiology clinic as well as doctors and nurses from other departments at the hospital. I was often treated as a medical student or student nurse, even though I informed patients and staff about my research project whenever possible. At university hospitals staff are used to having students or researchers observing their activities, and this hospital was no exception. The nurses and doctors I followed were helpful and allowed me to observe or take part in as many activities as possible. In return, I tried to help out whenever I could when the day was busy, basically simple errands such as fetching a bedpan, staying with a worried patient, or taking a patient to the ultrasound room.
The material also consists of eight recorded interviews with six doctors and two nurses who I shadowed or met during this time. The interviews lasted approximately an hour and provided opportunities for more elaborate conversations with the staff than was possible during the observation period when they were working. For the present analysis I relied on field notes rather than interviews in order to capture the hasty and mundane character of the staff's references to age, sex, class, ethnicity, and/or lifestyle factors. Though the interviews are transcribed verbatim, the observations obviously are not. To a great extent my field notes contain quoted talk because I paid much attention to conversation. Being able to write field notes continuously throughout the day (at rounds, meetings, etc.) gave me the opportunity to take careful notes of specific wordings and conversational turns, though not as detailed as a recording. Thus, quoted speech in the field notes are not claims of exact utterances. The field notes were written in Swedish, and I have translated the excerpts presented here.
Both ethically and practically, there is obvious difficulty recording speech during the kind of observations I conducted at the clinic. As we were almost always on the go (at the ward or to another ward) we constantly met 'new' people who would have had to approve of the recording. Access to recorded material is highly valued by researchers interested in talk-in-interaction, numerous studies in the medical field rely on recordings of specific medical settings, such as a medical conference (e.g., Hughes & Griffiths, 2004) or doctor-patient meetings (e.g., Silverman, 2004). Keeping a varied ethnographic approach to the medical field is important given the risk of restricting it to recorded settings only (Atkinson, 1995, p. 93). Without a recorder I gained access to staff conversations about patients not only during the conferences, but also during coffee breaks, when they dictated to the medical record, or when they bumped into someone on their way to another task. I have addressed the lack of exactness in the quoted speech by restricting analytical claims accordingly.
Taking accusations of gender biased medical work as a starting point, the original idea was to study how and in what sense medical staff refer to and demonstrate "objectivity" in their accounts of professional practice and decision-making. As is often the case with ethnographic studies, the original idea was pushed aside in favor of related but more conspicuous or persistent themes. Two such themes were the organization of everyday work at the clinic in terms of memory work (Jacobsson, 2013b) and the staff's constructions of (un)deserving patients (Jacobsson, 2013a). A third theme was the topic of this article: professionals' use of categories when discussing patients.

Analysis
The analysis deals with three analytically separate situations or contexts in which medical professionals explicitly referred to one or more of the categories age, sex, class, ethnicity, and/or lifestyle factors: (1) patient descriptions (the characteristics of the patient), (2) decision-making (discussions about diagnostic methods and treatment), and (3) finding explanations (what caused the medical trouble?). Obviously, these contexts do not present themselves as isolated events, but merge and mix to the point that distinguishing them analytically is difficult. Therefore, a final part of the analysis concerns a "case" -"Paula is overweight" -in which the three contexts blend together.

Patient descriptions
Describing someone is a matter of selection; there are a myriad of characteristics, aspects, or episodes for a single person, yet a given situation restricts what characteristics, aspects, or episodes are appropriate. Person-descriptions are tailored for the actual purposes at hand (Maynard, 1982). For "patient descriptions," the most obvious descriptive element concerns the patient's diagnostic category. In addition, almost everyone who talks about patients at the clinic establishes the categories age, sex, class, and ethnicity at an early stage. For example, a doctor I shadowed was called to the emergency room to examine a patient. The doctor wanted to admit the patient to the clinic for more thorough tests and on our way back to the ward we ran into the senior physician. The doctor told the senior physician that she needs a bed for a new patient. The following brief exchange occurred: Doctor: It's a woman with chest pain. Senior physician: How old is she? Doctor: Not that old. She is from Somalia.
Sex, symptom, age, ethnicity are efficiently established in a matter of seconds. It is not immediately clear for what purpose the two doctors collaboratively categorize the patient in this way as neither the patient's sex nor age, let alone ethnicity, is legitimate grounds for admission to the clinic. It may be fair to suggest that the staff simply want to "get a picture" of who they are dealing with, and for that purpose the most basic and prominent social categories that are applied are age, sex, class, and ethnicity (Baker, 2004).
In the hospital, patients' "class affiliation" is certainly indistinct and less conspicuous than the other categories; determining class or social status is trickier than the other categories. However, "class" seems to merge with "lifestyle" as a token of the impact of the epidemiological framework; bad lifestyle choices are linked to the lower classes, and vice versa. Thus, indications of class or social status and expected lifestyle behavior may be expressed by mentioning a patient's occupation: "he's a taxi driver," "sport teacher," or "the hockey pro." I cannot recall ever hearing the staff mention a female patient's occupation. More common than mentioning occupations was the explicit elements of "lifestyle" descriptions. These were included, for example, when patients were discussed during rounds: "And then we have Anders Svensson, a healthy person who exercises a lot." Pointing out a patient's healthy and active lifestyle is a way of signaling an otherwise healthy status, but can also be used by the staff to stress the importance of helping the patient. A doctor argued for a more thorough examination of a patient as follows: "A woman who is very physically active: takes care of grandchildren and does aqua aerobics. I think we have to help her. She shouldn't have to put up with this!" The description of the patient (physically active, grandchildren, aqua aerobics) was repeated on several occasions during the day: in the medical report, in face-to-face conversations with colleagues, and in a telephone conversation with a senior physician. The doctor paved the way for her colleagues to agree with her suggestion of a more comprehensive battery of tests and samples. In this and similar ways, age, sex, class, ethnicity, and lifestyle serve as contextualizing cues that direct the interpretation of the situation (Gumpertz, 1982). Such cues can be blunt and direct, but they can also be "a nudge to the inferential process" (Levinson, 2002, p. 27).
Patient descriptions that draw on the categories age, sex, class, or ethnicity often appear in the context of linking an individual patient to known generalized categories in order to establish how this particular patient may be expected to behave. Such descriptions can be swift and stereotypical, and they are sometimes explicitly framed as gross generalizations. For example, a doctor tells me about a patient of "immigrant origin" who had his second infarct. She continues: "If I were to generalize, they feel good for 10 years and then they stop taking the medicine" (with the unfortunate consequence that they become ill again). By stating that this claim is generalized, the doctor demonstrates an awareness that the "typical behavior" does not have to be valid for all immigrant patients. Yet, by mentioning the generalized knowledge of "immigrant patients," she establishes an easy link between this patient category and any individual patient associated with the category. In establishing (or sometimes guessing at) an individual patient's social background, the staff constructs an idea of what kind of patient they are dealing with and what to expect regarding patient compliance or typical behavior in general.
In addition to heredity, today's coronary risk factors are widely thought to relate to lifestyle. Lifestyle factors concern what we eat and drink, whether we smoke, and how we use (or do not use) our bodies, which means that practically everyone is potentially at risk for coronary disease and should be constantly cautious (cf. Hunt & Emslie, 2001). "Risk factor epidemiologists" link these risks to various categories defined by sex, class, and ethnicity (Shim, 2002) using the categories as proxy indicators of harmful lifestyle habits (Heyman et al., 1998). This practice seems to have trickled down to the individual level. Simplified links between category and behavior may be used as "facts" or "evidence" when specific patients at the clinic are described. For example, one of the senior physicians seemed to have the habit of checking the internet for the patient's residence using their postcode. During a conference he exclaimed district names-"Berga!" or "Stensby!"-when the patients were discussed. The tone was light and playful, and by way of explanation he stated: "The postcode is important for the prognosis." The places he mentioned (false names) are primarily represented by council estates and considered "working-class areas" and/or areas with large proportions of immigrants, and by referring to them he implicitly invokes the epidemiological idea that people from lower classes generally do not lead healthy lifestyles. The readiness of staff at the cardiology clinic to accept and use such epidemiological links is most likely due to the constant demand for risk assessments of individual patients, and the emphasis on behavioral risk factors (Hunt & Emslie, 2001). Notably, the doctor's playful tone of voice when searching for a patient's postcode suggests a distanced approach to the link he establishes between a single patient and aggregated epidemiological results, leaving a line of retreat if someone accuses him of an overly dogmatic stance.
From a distance, all categorization work may seem blunt and stereotypical, and it is often pointed out as such by the categorizer ("One shouldn't generalize..."). However, it would be depreciating to see stereotyping only when people make use of categories in order to describe and explain reality. In any setting age, sex, class, and ethnicity are basic social categories applied by people to determine with whom they are dealing (Baker, 2004). In addition, each local setting attaches specific meanings, assumptions, and knowledge to these categories, which become visible when people invoke them in certain situations. In a judicial context, for example, age, sex, class, and ethnicity can carry connotations that differ from the connotations found in an educational context. At the cardiology clinic, the categories are "epidemiologically colored," so to speak; they are linked to ideas about lifestyle habits, patient compliance, and discourses on health inequality, among others, and as such they work as contextualizing cues that guide the interpretation of the situation (Gumpertz, 1982).

Discussions about decision making
Patient and client descriptions in human service organizations are often incorporated into arguments for or against various decisions (Holstein, 2013), so how are the categories age, sex, class, ethnicity, and lifestyle made situationally relevant when emphasized in discussions for or against treatment decisions? As Holstein (2013) argues, professionals' descriptive practices form the basis for making decisions and taking actions. The power of descriptions may be exemplified by the fact that, for a long time, the dominating picture of a typical cardiac patient in both professional and lay beliefs was that of a middle-aged man with chest pain. This picture was taught in a textbook widely used in U.S. medical training, consequently directing doctors' perceptions, actions, and decisions (Lutfey & McKinlay, 2009). Throughout the Western world, researchers have pointed to the neglect of symptoms other than chest pain and the underdiagnosis of female cardiac patients (e.g., Lockyer & Bury, 2002;Perers, 2006).
The gender bias within cardiology has been debated widely in Swedish tabloids and newspaper articles with headlines such as "Anneli 60: The doctors missed my cardiac infarct-didn't bother to take important blood tests." 4 The medical staff in my study discussed and related to this critique of gender bias by (mostly) opposing it. They disagree with the idea that women are discriminated against and are more likely to put forward "age" as being influential for decision making. Age, it seems, is less controversial than gender, probably because the notion of age as a biological category is not yet contested to the same degree as that of gender (but see Jönson & Siverskog, 2012;Bytheway, 1995). The last few decades bore witness to a displacement of the criterion "old age," and highly advanced technology may now be offered to patients over the age of 90. Shim, Russ, and Kaufman (2006) analyzed how routine practices for life extension within cardiology change ideas about how old is "old" and link this development to risk. What was formerly seen as a risky population has now become a new class of medical subjects, as new technology means that risks are manageable. This view was expressed by a senior physician during a conference when the discussion concerned a patient named Mary who is in her 80s. Three medical candidates were present during the conference: David (senior physician) proposes angioplasty (a surgery to widen blocked or narrowed coronary arteries) for Mary on Friday or Monday. "Candidates!" he exclaims. "Diverging opinions?" None of the candidates speak but deny disagreement by shaking their heads and mumbling a bit. David raises the question of whether it is reasonable to do "angioplasty on an old lady." He continues: "One might think, 'Why'? It's important to look at objective facts here: she has good blood counts, she's managed all on her own in the past, and she has good chances. One should be careful not to rule her out for more advanced medical care." (field notes) When no doubt or questioning of the decision is uttered, the senior physician raises the question himself: is it reasonable to do surgery on an "old lady"? The doctor invokes the categories age and sex and their adjoining discourses on risk and discrimination; old age is a risk factor for infarcts and higher risk exists for older patients undergoing invasive procedures (sometimes argued to be even riskier for women due to narrow vessels). Furthermore, the possible suspicion that age or sex would be discriminatory grounds for a negative treatment decision rather than legitimate medical grounds is effectively discarded by the demand to "look at the objective facts" and the listing of reasons for a positive treatment decision. Notably, his considerations may have been directed to me as an observer rather than to the candidates; prior to the round, the nurse I was shadowing had introduced me to David (it was the first time I met him) and I told him briefly about my project on medical decision making. Still, his rhetorical performance shows the staff's readiness to discuss medical practice in the context of prevailing societal debates.
"Ethnicity" as a category can be acknowledged in the form of "cultural knowledge." One example is the male doctor who announces his appearance outside the door in order to let the female patient put on her veil before he enters. In another example, ethnicity and gender are invoked in a case in which the doctors have to decide what kind of medical examination is the most appropriate for Fatima, a patient with chest pain. There are various methods with which to examine a patient's coronary artery, such as a cardiac stress test (exercise bike), cardiac scintigraphy (a kind of x-ray), and the more precise surgical angiography. The two doctors discuss which method to use for Fatima, who suffers from kidney disease in addition to her cardiac symptoms, which means that it is too risky for her to go through angiography: In a medical context, this vast and odd generalization can be framed as "cultural competence"-a specific kind of knowledge that is celebrated within health care. 5 "Cultural" in this context means "ethnicity" and fits well with the epidemiological framework and its routine inclusion of demographic differences. The statement offers a logic that meets the request from medical staff to provide "culturally competent" medical care (Shim, 2002, p. 141).
In the context of risk assessment, another example of a rather crude application of "cultural competence" is found in Hughes and Griffiths' (2004) analysis of case presentations by cardiac surgeons in a British study. The doctors discuss a candidate patient of South Asian origin and a surgeon says; "But he's a grim prospect isn't he? Is he still smoking? These Asians smoke like chimneys" (Hughes & Griffiths, 2004, p. 82). By implicitly referring to aggregated epidemiological knowledge of coronary artery disease in an ethnic minority group, the surgeon instructs the listener to be vigilant about all patients from that group with respect to risk assessment. Ethnicity ("these Asians") is used as a short-cut to invoke an assemblage of (epidemiological) assumptions.

Finding explanations
Why do people end up in the cardiology clinic? Medical staff point out family history as one vital cause, but they commonly speak about lifestyle as the cause of cardiac disease (e.g., obesity, inactivity, smoking). The position that a healthy lifestyle is imperative to good health is often demonstrated at the clinic, not only in conversations with patients, but also between colleagues. For example, just before rounds the doctors chatted informally: Doctor: The remarkable thing is that the disease is caused by lifestyle and yet you have a candy machine placed outside the cardiology clinic! Specialist: It has been proposed to get rid of it. Doctor: It's been removed from the schools but the cardiology clinic still keeps it! Not surprisingly, patients at the clinic are often concerned about what caused their illness, and they are prone to identify possible errors in their lifestyles: "Should I exercise even more?" asks one patient, and another suggests giving up the daily dessert. Dietary and exercise advice, as well as programs to help smokers quit, are offered to patients on a routine basis. When the staff face unlikely cases, they are preoccupied by finding explanations as to why a certain individual suffers from an infarct despite no apparent risk factors, such as heredity. Old age is an uncontested risk factor for cardiac disease and seems to work as a self-evident explanation in such a way that staff do not comment on age as a cause at all. 6 Yet, relatively young people may also suffer from cardiac infarct. These unlikely cases tend to be talked about and commented on by the staff in addition to the regular discussions over lab results, anamneses, and treatments. Discussions about unlikely cases often link to lifestyle factors (e.g., weight, smoking, exercise, etc. Nina is initially perplexed by having such a young person as an inpatient at the clinic. When she notices the patient's weight, she utters "Ah, well" [in Swedish: "Jahaaa"] in a tone of voice that suggests that the weight in and of itself explains the patient's misfortune. Her astonishment over the young patient was reduced by the knowledge of his heavy weight, and my effort to explain heavy weight with height is brushed aside ("But still"). A remarkable occurrence (a young person having heart problems) is turned into something not-so-remarkable when signs of a hazardous lifestyle is observed (heavy weight).
Lifestyle factors are not always found. During a report from the night shift to the morning shift, the nurses go through each patient. In one such report, the night nurse says about Paul, who has been treated for his second cardiac infarct: And then we have Paul. Born [19]48. Strange. Such a fit man, sports teacher and all. He lives a healthy life and yet it happened quite early. (field notes) The fact that patients who are compliant with the staff's directions (take medicine, quit smoking, eat less fatty food, etc.) may still have another infarct is described as unfair. "There is no fairness in this", says a senior physician in placing the patient in the "bad luck category," which Davison and colleagues (1991) found in the lay epidemiology used by British interviewees discussing what kind of person gets heart trouble. In their study, chance, fate, and destiny accounted for the unexpected cases of coronary disease and death in young, healthy, non-smoking people. When plausible explanations are absent, such as lifestyle and heredity, or simply old age, professionals at the cardiology clinic refer to the unpredictable cases as unfair randomness.

"Paula is overweight"
I will end the analysis with a final example, which is not a clear-cut case of the previously separated analytical contexts of patient descriptions, decision making, or finding explanations. Instead, it is a fuzzy mixture of all these contexts. I think the following excerpts from the field notes show how person-descriptions guide the decision-making process, as well as the search (or non-search) for an explanation. This time the explanation concerns a symptom, not the disease itself, and it has vital implications for what course of action the doctors choose.
Paula is a patient who has stayed at the ward for almost a week with no signs of improvement. She has complained about breathlessness and she worries it may be something more in addition to her "regular" heart disease (which is why she is an in-patient at the clinic). The senior physician, Dan, has reassured Paula that it is not fibrillation, a heart rhythm disorder. During the week, Dan has repeatedly referred to her breathlessness as being caused by her being overweight, stating to his colleagues, "I guess she weighs 90 kilos, so. . ." Another example was observed during the rounds when we visit Paula's bedside: Paula complains about shortness of breath in daily chores like cleaning and gardening. Dan tells her that it is not due to fibrillation. When we walk out of the room I hear Dan comment on Paula's breathlessness in a low voice to the other doctor: "It's not fibrillation, it is overweight!" (field notes) Dan actually used the English word "overweight" here; the rest of the excerpt is translated from Swedish. It is reminiscent of the way Swedish parents often switch to English or another language when they do not want their children to understand what they are talking about. This verbal procedure suggests moral sensitivity to the matter; a perceived blameworthiness that is withheld from Paula. Nonetheless, to the medical staff she is described as a person who is overweight, and this "lifestyle factor" explains Paula's extra symptoms (i.e., the breathlessness). This description of Paula, among other things, guides Dan and the staff when they discuss her medical troubles. Towards the end of the week, during a conference, the doctors want to discharge Paula but a nurse's objections alter the course of events: Dan: She doesn't have to stay ad absurdum. Specialist: It's strange to keep her over the weekend. Dan: It's possible she'll have to go home today.
Nurse: She's not well, you know. I know you say that her breathlessness is because of her being overweight, but she is very affected. She's trying to move about.
The nurse shows images of the ECG and other lab results. Dan asks for more pictures, oxygen numbers, and the like. The two doctors check the digital medical record and read in silence.
Dan: (reads out loud) Atrial tachycardiaperhaps that's what she's got? Is she always out of breath, then? Nurse: Today is really bad. She can barely walk.
The doctors agree to order some new tests and they continue reading the digital record, clearly puzzled. The nurse excuses herself for raising the question. Dan answers, "Nah, but it's perfectly fine. Now we have shifted our focus: cardiac ultrasound, spirometry, and then look at the tachycardia and see if there is any connection with breathlessness." (field notes) When we walk the rounds later and leave Paula's room, Dan says to his colleague, "I guess we shouldn't ignore it." Paula's symptom was initially ignored because it was obviously caused by her being overweight, but by the end of the week her symptom had turned into a legitimate medical puzzle to solve. The continuous references to Paula as a patient with heavy weight worked as a morally loaded patient description. At other times "overweight" was put forward as an explicit and certain explanation of the symptom. "Overweight" as an explanatory lifestyle category rules out alternative explanations, leading the doctors to conclude that they cannot do more for Paula but send her home. When the nurse raises subtle objections to their decision, another description of Paula is presented. She is willing to be active ("she's trying to move about"), but she simply can't because she is too affected by her medical condition. The nurse backs up her statement with ECG images and lab results, convincing the doctors to look for other explanations than her merely being overweight. Eventually the doctors find a possible (and treatable) explanation in the diagnosis atrial tachycardia, initiating a range of tests to establish if their suspicion is correct. The initial decision to discharge the patient the same day is dropped and not mentioned again.
The case of Paula shows the close association between patient descriptions and the search for explanations, and ultimately their consequences on medical decisionmaking. This case also shows that the explanatory value of patient descriptions is not necessarily uncontested, but can be subject to objections during the course of medical reasoning between staff members.

Conclusion
Though patient descriptions are vital for decision-making (Holstein, 2013), they are not fixed; they are collaboratively carved out via talk about the patients at rounds, meetings, in the corridors, and so on (cf. Atkinson, 1995). The use of categories, such as age, sex, class, ethnicity, and lifestyle factors, is one of many ingredients in such medical talk, and this study shows how categories serve as shortcut reasoning in at least three situations: when staff describe patients, when they discuss what to do, and when they discuss what may have caused the medical trouble.
"Ordinary" people's interest in "what kind of person" gets, for example, heart trouble, brittle bones, or diabetes, is evident in studies on lay beliefs of various illnesses (e.g., Skolbekken, Østerlie, & Forsmo, 2008). Quite often such ideas are rather well-informed. Davison and colleagues (1991) point to the closeness between common people's beliefs regarding coronary risk factors and those of expert epidemiologists, leading them to suggest the study of lay epidemiology rather than lay beliefs. Hunt and Emslie (2001) agree with the similarities between lay epidemiologists and professional epidemiologists in explaining causes of illness, but they also point to differences. For example, the lay epidemiologist is more concerned with individual occurrences of disease, whereas the professional epidemiologist focuses on the common denominator in the majority.
If we mean by "lay epidemiology" people's interpretation of individual cases of disease aided by reasoning about the common categories age, sex, class, and ethnicity paired with widespread knowledge of lifestyle risk factors, then lay epidemiology is commonplace not only among "ordinary" people, but among medical staff as well. When the medical staff describe patients, they rely on lab results, diagnoses, and nurses' reports, among others. In addition, they use epidemiologically colored categories when discussing individual patients with colleagues-categories that serve as stepping stones for shortcut reasoning. Though categorization happens quickly, and at times stereotypically, it is not predictive for subsequent treatment of patients in a simple manner (if a, then b). The main findings of my analysis call attention to when and how this kind of categorization work occurs and what medical staff accomplish by categorizing within the particular situation. Persondescriptions are always consequential in the context of human service work, but how they affect decision-making, problem-solving, and other responses must be studied situationally.
The phenomenon discussed in this article extends beyond the medical field, drawing attention to the study of whether and how popular research results and well-established categories such as age, sex, class, and ethnicity are used in everyday reasoning in various professional fields, such as education, social services, and the judicial system. For example, Atkinson (1985, p. 16) points out that Basil Bernstein's theories of language codes, published and widely discussed during the 1970s, became condensed into taken-for-granted stereotypical explanations of inequality in education and were reproduced in the form of simplified truths by both teachers and students. It is reasonable to believe that this "condensation phenomenon" is even more widespread and visible today given the call for evidence-based practice in almost all human service organizations and the interest in social science research in all sorts of channels (e.g., talk shows, specialized popular magazines, news reports on radio and television).
The far and ever-more-reaching call for evidence-based practice in various fields is accompanied by the idea that by "fertilizing" the professional field with the latest research results, particularly outcome studies, the "best practice" will be harvested. This fertilizer may come in the form of standardized manuals from authorities and in-service training (e.g., Martinell Barfoed & Jacobsson, 2012), as well as through debates and articles in professional magazines and the mass media. However, social-scientific knowledge seldom manifests as a simple one-to-one application in everyday professional practice. Concepts, theories, and research results are locally discerned, constructed, and reproduced; they are made relevant to the local setting and its members. This knowledge may assume simplistic notions in the course of daily work and serve as shortcuts for legitimizing decisions, strengthening arguments, and making everyday work accountable. Investigations of when and how such shortcuts are used and what moral assumptions may be embedded in them are rewarding for the study of professional reasoning.