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Section of Biostatistics, Division of Health Sciences Research, Mayo Clinic, Scottsdale, Arizona
Given name(s)
Helene R.
Family name
Labonte
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DO

Teaching Cases Perception vs Reality

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Resident and hospitalist perspectives on the “great teaching case”: Correlation with actual patient assignment decisions

The advent of work‐hour restrictions and admission limits for teaching services has led many academic hospitals to implement hospitalist‐run staff (ie, nonteaching) services.[1] Although this practice is not new,[2] it is growing in popularity[3] and has been endorsed as a way to protect resident teaching and prevent excessive workload.[4] One potential benefit is the assignment of more educational cases to teaching services, whereas the nonteaching services receive more patients whose care is presumably relatively mundane or routine.[5]

Despite the rapid growth of this system of educational triage,[6] little is known about the factors considered when teaching versus nonteaching decisions are made. Studies of clinical outcomes for patients assigned to teaching versus nonteaching services have understandably used random assignment,[7, 8] whereas a study finding that patients with unhealthy substance use were more likely to be on teaching services than nonteaching services relied on patient assignment based on the identity of the patient's primary care provider or insurer.[9] In 2009, O'Connor et al. reported that implementation of nonteaching services at 2 hospitals had led to unequal distribution of patients in terms of demographics, diagnosis, and illness severity.[10] Triage decisions were made by either a nurse coordinator or a medical chief resident, and sicker patients (and occasionally good teaching cases) were preferentially placed on the teaching services, reportedly out of respect for the comfort level of the midlevel providers who staffed the nonteaching services.

Our institution has used a system of hospitalist educational triage since 1998. Over that time, residents have often expressed concerns about the assignment of patients to the teaching services, reporting in particular that they receive a disproportionate number of complex cases and outside transfers. In 2006, the hospitalist group attempted to address these concerns by collecting real‐time admission data, but the application of the data was limited by suspicion on both sides of a Hawthorne effect (data not published).

If trainee and hospitalist expectations for what constitutes a great teaching case differ substantially, that difference can have significant implications for resident and medical student teaching, self‐perceived roles, and satisfaction. More significantly, an understanding of what faculty perceive as ideal teaching cases would provide valuable information about the strengths and weaknesses of the teachingnonteaching model, which may prove useful to other academic institutions considering such a system. In this study, we endeavored to understand what residents and hospitalists consider an educational admission and to compare these expectations to the actual triage decisions of hospitalists.

METHODS

Mayo Clinic Hospital (Phoenix, Arizona) has used separate teaching and nonteaching services since opening in 1998. At our institution, like many others,[11] a hospitalist is assigned to take all calls for emergency department (ED) admissions, admissions from outpatient clinics, and transfer requests; this physician directs patients to the teaching or nonteaching service. At the time of our study, the 2 teaching services alternated days in which they admitted up to 7 patients, and the 5 nonteaching services admitted all other patients and provided medicine consultative services for the hospital. Teaching services consisted of 1 hospitalist, 2 senior residents, 2 or 3 first‐year residents, and sometimes 1 third‐ or fourth‐year medical student. Nonteaching services consisted of a hospitalist with intermittent assistance from a physician assistant or nurse practitioner.

Although there are no formal guidelines for the hospitalist triage role, hospitalists are encouraged to assign more educational cases to the teaching services and to allow the residents enough time to address the acute needs of the prior admission before receiving the next admission. Residents are not assigned any patients between 4:00 am and 7:00 am. The goals and objectives for the resident rotation on the medicine teaching service include a list of diagnoses with which residents are expected to become familiar during their residency; triage hospitalists have on‐line access to these goals and objectives.

To assess resident and hospitalist opinions about what types of patients should or should not be admitted to teaching services and to compare those characteristics with those of the patients actually admitted to teaching services, we began by administering a simple, open‐ended survey and asked both groups: (1) In an ideal world, what kinds of patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital? (2) In the real world, what kinds of patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?

Ample space was provided for free‐text entries. Residents were additionally asked their postgraduate year level. The survey was administered in April 2011, at which time all residents would have rotated on the medicine teaching services several times. Survey responses were anonymous and were compiled and retyped by someone unfamiliar with the subjects' handwriting.

Two authors (D.L.R. and H.R.L.) reviewed the results of the first survey and used conventional content analysis to group responses into categories and tally them.[12] Responses from hospitalists and residents were used to determine the content for a second, quantitative survey that asked respondents to rate specific possible factors that affected triage decisions on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission). The second survey, administered to the same residents and hospitalists in May 2011, asked: (1) In an ideal world, how do these factors contribute to the decision about which patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital? (2) In the real world, how do these factors contribute to the decision about which patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?

Assuming a 3:1 ratio of nonteaching to teaching admissions, we calculated that we would need to analyze 1028 admissions to detect a 10% difference in the proportion of a specific trait present in 50% of patients admitted to the nonteaching service, with the use of a 2‐sided test with 80% statistical power and a significance level of 0.05.

We collected data on patient assignment via retrospective chart review to avoid the possibility of a Hawthorne effect. We studied all admissions to the internal medicine services for a 3‐month period before the administration of the first survey (January 1, 2011 through March 31, 2011). The following patient data were collected: service assignment (teaching vs nonteaching), age, sex, source of admission (ED, direct from clinic, outside transfer, internal transfer from another hospital service), first visit to our institution, prior hematology or oncology visit at our institution (as a surrogate for cancer), prior psychiatry visit at our institution (as a surrogate for psychiatric disease), transplantation history, human immunodeficiency virus (HIV) or acquired immune deficiency syndrome (AIDS) history, chronic or functional pain mentioned in ED or admission note, need for translator, and benefactor status. Additionally, an online calculator was used to determine the Charlson Comorbidity Index score for each patient.[13] We collected actual patient data corresponding to factors reported by survey respondents whenever possible and practical, but not every factor reported by survey respondents was amenable to rigorous analysis; for example, no unbiased method could be devised to rigorously categorize patients whose admissions are likely to take more time or difficult patients and families.

Responses to the second (quantitative) survey and patient data were compared using the Pearson [2] and Fisher exact test for categorical variables and the Student t test or Wilcoxon rank sum test for continuous variables. Categorical variables that achieved statistical significance for overall difference were analyzed on a post hoc basis using the Bonferroni method to control for the overall type I error rate. We also examined the differences between actual and ideal triage decisions using the Wilcoxon signed rank test. Data were analyzed using SAS 9.3 (SAS Institute, Inc., Cary, NC). Statistical significance was defined as P<0.05.

The project was deemed exempt by the Mayo Clinic institutional review board.

RESULTS

We surveyed all categorical internal medicine residents (n=30, 10 each from postgraduate year [PGY]‐1, PGY‐2, and PGY‐3) and hospitalists except the authors (n=21; average years since completing training=13.3; range, 129 years). For both surveys, responses were collected from 29 (96.7%) residents. The nonresponding resident was a PGY‐2. The response rate for hospitalists was 20/21 (95.2%) for the first survey and 16/21 (76.2%) for the second survey.

First Survey

Table 1 compares the most frequent resident and faculty responses to the initial, open‐ended survey about what types of patients should or should not be admitted to teaching services. Residents most commonly indicated that ideal patients were traditional medicine cases (ie, bread‐and‐butter admissions, with 13 residents using that exact phrase), and others supplied specific examples of such cases, including chronic obstructive pulmonary disease, pneumonia, diabetic ketoacidosis, congestive heart failure, chest pain, and gastrointestinal tract bleeding. Only 1 faculty member mentioned bread‐and‐butter admissions, although several listed examples like chest pain and pneumonia. A smaller number of residents pointed to the importance of rare cases, whereas faculty considered rare cases to be ideal for teaching services, followed by variety of pathology and complexity.

Most Frequent Resident and Faculty Responses to an Open‐Ended Survey About Types of Patients Admitted (Ideal vs Actual)
 Residents (n=29)Faculty (n=20)
QuestionCharacteristicNo. (%)CharacteristicNo. (%)
  • NOTE: Abbreviations: AIDS, acquired immunodeficiency syndrome; HIV, human immunodeficiency virus.

  • Similar responses were grouped via content analysis.

  • Specific examples cited include chronic obstructive pulmonary disease, pneumonia, diabetic ketoacidosis, congestive heart failure, chest pain, and gastrointestinal tract bleeding.

In an ideal world, what kinds of patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital?Bread‐and butter admissionsb14 (44.8)Rare cases9 (45.0)
Rare cases9 (31.0)Variety of pathology7 (35.0)
No social admissions7 (24.1)Complex cases5 (25.0)
New diagnoses instead of chronic management4 (13.8)Variety of complexity5 (25.0)
Variety of complexity4 (13.8)Patients with HIV/AIDS3 (15.0)
Diagnostic dilemmas3 (15.0)
New diagnoses instead of chronic management3 (15.0)
In the real world, what kinds of patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?Patients with cancer11 (37.9)Complex patients6 (30.0)
Complex patients10 (34.5)Difficult patients5 (25.0)
Social admissions9 (31.0)Patients whose admissions are expected to be time consuming5 (25.0)
Acutely ill patients6 (20.7)Rare cases3 (15.0)
Variety of pathology6 (20.7)Cases determined by the time of day3 (15.0)

With regard to actual admissions, residents and faculty agreed that they often were complex, but residents were more likely to suggest high rates of patients with cancer (11 residents vs 2 hospitalists) and social admissions (9 residents vs 2 hospitalists). Four residents each believed that they preferentially received elderly patients, outside transfers, and patients with functional pain, and 2 perceived a disproportionate number of patients making their first visit to Mayo Clinic. One hospitalist believed that residents were more likely to receive non‐English speakers.

Second Survey

Table 2 compares the resident and faculty responses to the second, numerical survey regarding ideal admissions to the teaching services. In contrast to the first survey, residents prioritized rare cases as the feature they most associated with ideal teaching admissions. They also placed a premium on variety of pathology, patients with unique findings, and patients likely to be written up or presented. The patients they believed were least appropriate for a teaching service were social admissions or those with placement issues, patients with functional or chronic pain, and benefactors or public figures.

Resident and Faculty Survey Responses Regarding Ideal Admissions to Teaching Services
FactorResident, n=29Faculty, n=16P Value
  • NOTE: Participants rated each factor on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission), with 3 representing No impact on admission decision. Abbreviations: AIDS, acquired immune deficiency syndrome; HIV, human immunodeficiency virus; SD, standard deviation.

Rare diseases  0.22
Mean (SD)4.8 (0.5)4.9 (0.3) 
Median55 
Variety of pathology  0.22
Mean (SD)4.7 (0.5)4.5 (0.5) 
Median55 
Cases that might be written up or presented  0.35
Mean (SD)4.7 (0.5)4.8 (0.6) 
Median55 
Bread‐and‐butter cases  0.001
Mean (SD)4.6 (0.7)3.7 (0.9) 
Median54 
Unique physical findings  0.67
Mean (SD)4.6 (0.6)4.7 (0.5) 
Median55 
Variety of complexity  0.21
Mean (SD)4.3 (0.7)4.1 (0.6) 
Median44 
Variety of acuity  0.40
Mean (SD)4.2 (0.7)4.1 (0.7) 
Median44 
Spectrum of ages  0.046
Mean (SD)4.1 (0.8)3.6 (0.8) 
Median43 
HIV or AIDS  0.39
Mean (SD)4.1 (0.9)4.4 (0.5) 
Median44 
Acutely ill or unstable  0.54
Mean (SD)4.0 (0.9)3.9 (0.6) 
Median44 
Complex patients  0.94
Mean (SD)4.0 (0.8)3.9 (0.6) 
Median44 
Patients at end of life  0.16
Mean (SD)3.5 (0.8)3.1 (0.6) 
Median33 
First‐time Mayo patients  0.45
Mean (SD)3.5 (0.7)3.3 (0.5) 
Median33 
Younger patients  0.50
Mean (SD)3.5 (0.9)3.3 (0.6) 
Median33 
Stable patients  0.21
Mean (SD)3.3 (0.8)3.1 (0.3) 
Median33 
Patients with cancer  0.67
Mean (SD)3.3 (0.8)3.1 (0.4) 
Median33 
Straightforward patients  0.64
Mean (SD)3.2 (0.8)3.1 (0.8) 
Median33 
Older patients  0.73
Mean (SD)3.2 (0.7)3.1 (0.3) 
Median33 
Patients with a history of transplantation  0.67
Mean (SD)3.1 (1.1)3.3 (0.6) 
Median33 
Time of day of admission  0.71
Mean (SD)3.1 (1.0)3.1 (0.5) 
Median33 
Patients with a history of psychiatric illness  0.59
Mean (SD)3.1 (1.0)3.1 (0.6) 
Median33 
Patients who require a translator  0.49
Mean (SD)3.0 (0.9)3.1 (0.5) 
Median33 
Patients whose admissions are expected to take more time  0.13
Mean (SD)2.9 (0.8)3.2 (0.6) 
Median33 
Difficult patients and families  0.55
Mean (SD)2.8 (1.0)2.6 (0.8) 
Median33 
Transfers from other hospitals  0.11
Mean (SD)2.7 (1.1)3.1 (0.3) 
Median33 
Benefactors and public figures  0.49
Mean (SD)2.7 (1.0)2.5 (0.7) 
Median33 
Patients with functional or chronic pain  0.87
Mean (SD)2.4 (1.1)2.4 (1.0)
Median23 
Social admissions or placement issues  0.99
Mean (SD)2.1 (1.1)2.0 (1.0) 
Median22 

Faculty prioritized many of the same features for ideal teaching cases as residents; 4 of their 5 highest‐scoring factors were the same (rare diseases, patients whose cases might be written up or presented, patients with unique physical findings, and variety of pathology). They also agreed on the least ideal features (social admissions or placement issues, patients with functional or chronic pain, and benefactors or public figures). The only significant differences between resident and faculty ratings for ideal teaching cases were for bread‐and‐butter cases and a spectrum of ages.

Discordance between resident and faculty survey responses on actual admission decisions (Table 3) was starker; residents rated several features significantly higher than faculty as features contributing to triage decisions including older patients; patients with functional or chronic pain, social admissions, or placement issues; patients with cancer; transfers from other hospitals; and difficult patients and families. Relative to residents, faculty reported that patients with HIV or AIDS, and patients whose cases were likely to be written up or presented, were more likely to be admitted to teaching services.

Resident and Faculty Survey Responses Regarding Actual Admissions to Teaching Services
FactorResident, n=29Faculty, n=16P Value
  • NOTE: Participants rated each factor on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission), with 3 representing No impact on admission decision. Abbreviations: AIDS, acquired immune deficiency syndrome; HIV, human immunodeficiency virus; SD, standard deviation.

Rare diseases  0.14
Mean (SD)4.4 (0.6)4.7 (0.6) 
Median45 
Complex patients  0.83
Mean (SD)4.3 (0.6)4.3 (0.6) 
Median44 
Acutely ill or unstable  0.18
Mean (SD)4.3 (0.7)3.9 (0.9) 
Median44 
Unique physical findings  0.18
Mean (SD)4.1 (0.8)4.5 (0.6) 
Median45 
Transfers from other hospitals  0.003
Mean (SD)4.1 (1.0)3.5 (0.5) 
Median43 
Cases that might be written up or presented  0.03
Mean (SD)4.1 (0.7)4.6 (0.6) 
Median45 
Older patients  <0.001
Mean (SD)3.9 (0.8)3.0 (0.7) 
Median43 
Time of day of admission  0.50
Mean (SD)3.9 (1.1)3.7 (0.9) 
Median44 
Patients with cancer  0.01
Mean (SD)3.9 (0.9)3.3 (0.5) 
Median43 
Variety of pathology  0.21
Mean (SD)3.9 (0.8)4.2 (0.7) 
Median44 
Patients whose admissions are expected to take more time  0.13
Mean (SD)3.9 (1.0)3.4 (0.9) 
Median43 
HIV or AIDS  0.008
Mean (SD)3.8 (0.9)4.5 (0.5) 
Median44.5 
Variety of complexity  0.31
Mean (SD)3.7 (0.9)3.9 (0.6) 
Median3.54 
Bread‐and‐butter cases  0.07
Mean (SD)3.6 (1.0)2.9 (1.2) 
Median33 
First‐time Mayo patients  0.82
Mean (SD)3.6 (0.9)3.5 (0.7) 
Median33 
Patients with functional or chronic pain  0.004
Mean (SD)3.6 (1.0)2.8 (0.7) 
Median43 
Social admissions or placement issues  0.03
Mean (SD)3.5 (1.2)2.7 (0.9) 
Median43 
Variety of acuity  0.25
Mean (SD)3.5 (0.8)3.7 (0.6) 
Median34 
Difficult patients and families  0.03
Mean (SD)3.4 (0.9)2.8 (0.7) 
Median33 
Patients at end of life  0.10
Mean (SD)3.4 (0.8)3.0 (0.5) 
Median33 
Spectrum of ages  0.80
Mean (SD)3.3 (0.7)3.3 (0.6) 
Median33 
Patients with a history of psychiatric illness  0.81
Mean (SD)3.3 (0.9)3.1 (0.6) 
Median33 
Patients with a history of transplantation  0.25
Mean (SD)3.2 (0.9)3.5 (0.5) 
Median33 
Patients who require a translator  0.60
Mean (SD)3.2 (0.7)3.2 (0.6) 
Median33 
Younger patients  0.42
Mean (SD)3.0 (0.9)3.1 (0.4) 
Median33 
Benefactors and public figures  0.09
Mean (SD)2.9 (1.0)2.3 (0.7) 
Median32 
Straightforward patients  0.18
Mean (SD)2.8 (1.0)2.4 (1.0) 
Median2.52 
Stable patients  0.53
Mean (SD)2.7 (1.0)2.8 (0.7) 
Median33 

Comparing resident survey ratings for ideal versus actual triage decisions gave some insight into the features that they thought were inappropriately emphasized or ignored when triage decisions were made. Differences in resident scores for ideal versus actual admissions were significantly different for 16 of 28 items (data available upon request), suggesting a degree of perceived discordance. The largest positive differences (ie, features they valued in teaching admissions but thought were less represented in actual admissions) were for bread‐and‐butter admissions, variety of pathology, a spectrum of ages, and variety of acuity. The largest negative differences (ie, features they thought were well represented in actual admissions but were less valuable) were for social admissions or placement issues, transfers from other hospitals, patients with functional or chronic pain, and patients whose admissions were expected to take more time.

In terms of ideal versus actual triage decisions, faculty reported less discordance than residents; ideal and actual triage behavior differed significantly only for 4 of 28 items (data available upon request). They did agree with residents about the relative lack of bread‐and‐butter admissions and the over‐representation of social admissions or placement issues and transfers from other hospitals. They additionally noted a lack of straightforward cases.

We reviewed records of the 1426 patients admitted to the internal medicine services during the study period. Of these, 359 (25.2%) were assigned to the teaching services. Patient characteristics are summarized in Table 4.

Characteristics of Patients Admitted to the Internal Medicine Services (N=1,426)
CharacteristicTeaching Service, n=359Nonteaching Service, n=1,067P Value
  • NOTE: Abbreviations: SD, standard deviation.

Age, y, mean (SD)66.7 (16.5)69.3 (15.7)0.008
Admission type, No. (%)  0.049
Admission from the emergency department315 (87.7)915 (85.8)0.34
Direct admission from Mayo outpatient clinic27 (7.5)114 (10.7)0.08
Transfer from another institution16 (4.5)27 (2.5)0.06
Internal transfer from a different hospital service1 (0.3)11 (1.0)0.31
First‐time Mayo patient, No. (%)61 (17.0)175 (16.4)0.79
Prior hematology or oncology visit, No. (%)86 (24.0)235 (22.0)0.45
History of transplantation, No. (%)20 (5.6)52 (4.9)0.60
Prior psychiatry visit, No. (%)53 (14.8)122 (11.4)0.10
History of chronic or functional pain, No. (%)122 (34.0)330 (30.9)0.28
Required translator, No. (%)5 (1.4)14 (1.3)0.91
Benefactor, No. (%)5 (1.4)24 (2.2)0.32
Charlson comorbidity score, mean (SD)2.7 (2.5)2.6 (2.5)0.49

DISCUSSION

The results of our qualitative and quantitative surveys showed significant differences between resident and staff perceptions of the faculty triage role. Although both groups similarly valued many features, residents expressed a clear preference for more bread‐and‐butter admissions, whereas the staff prioritized selecting the most complex, challenging, and rare cases from among the day's admissions to give to the residents. (Residents were also very interested in rare cases, suggesting that they saw benefit to admitting patients with a variety of degrees of rarity and complexity.) Residents and faculty seemed to agree that the number of social admissions and outside transfers admitted to teaching services was not ideal.

These perceptions have substantial implications. If the current triage process is to continue, there may be benefit to designing a faculty development project focused on the triage process, which previously has been largely unexamined. Efforts to remove or limit time barriers that prevent perceived educational cases from being admitted to teaching services is also a worthy endeavor (eg, structuring the 2 teams to admit simultaneously so that teaching teams can admit patients back to back without exceeding capacity). In addition, residents may benefit from teaching hospitalists who concentrate educational efforts on the learning that can be extracted from the care of any patient, including admissions that initially seem mundane or purely social.[14] A concerted effort to divert more traditional medicine admissions and fewer unusual cases to the teaching service might improve resident perceptions of the triage process. Further, although the care of any patient can have education benefit, the fact that both groups perceived excessive social admissions in the teaching service suggests that a potential benefit of a nonteaching service (ie, absorbing the most mundane admissions) may not yet be fully realized.

Despite the perceived differences noted on the surveys, we found remarkably few differences between patients admitted to the teaching and nonteaching services. Although both groups rated complexity; outside transfers; being seen at the institution for the first time; and histories of transplantation, cancer, chronic or functional pain, and psychiatric disease as increasing the likelihood of admission to a teaching service, no differences were observed for these factors or their quantifiable surrogates. (Although the overall test for admission type achieved marginal statistical significance, none of the individual admission types were significantly different in post hoc analysis.) Residents, but not faculty, thought that older patients were over‐represented on the teaching service, but their assigned patients were significantly younger than those on the nonteaching service.

These findings have several possible explanations. First, although most hospitalists spend time on teaching and nonteaching services (and therefore are familiar with the patient composition of each), residents get very little exposure to the nonteaching services (until they are senior residents with a rotation on a consulting service). Their impression of inequity may be due to misunderstanding the patient composition of the nonteaching services. Second, the mere existence of a triage role may create false expectations about patient composition; that is, simply by knowing that every admission was chosen for its educational merit, residents may have disproportionate perceptions about those cases judged to have less educational value, even ifas our data suggestassignments to teaching versus nonteaching services are occurring fairly equitably.

Study Limitations

We acknowledge several limitations of our study. First, many factors that were reported as important in the qualitative survey did not lend themselves to objective abstraction from patient records. For example, providers did not specifically document when an admission is purely social, nor was there an objective way to identify difficult patients or families or admissions that were expected to take more time. We attempted to limit the analysis to objective patient metrics that were (1) not influenced by the teaching or nonteaching assignment itself (eg, we avoided discharge diagnoses, which might be entered differently by residents and staff hospitalists) and (2) easily available to triage hospitalists. For the latter reason, we used a prior appointment in the hematology or oncology clinic as a surrogate for cancer patients and a prior psychiatry visit as a surrogate for patients with a history of psychiatric disease. These are naturally inexact surrogates, but they reflect the information a busy hospitalist is likely to access when making patient assignment decisions.

Second, it may well be that assigning patients equitably according to a certain trait is not the same as assigning patients ideally for the educational needs of residents. The patients admitted to our medicine services (teaching and nonteaching) were generally older than 60 years, had complex diagnoses, and had substantial pain. Residents on the teaching services potentially would benefit from an intentionally unbalanced admission policy that shunted patients to the teaching services on the basis of features other than individual perceived educational merit. It must also be borne in mind that resident, and for that matter faculty, perceptions of ideal teaching cases are likely inexact correlates of educational best practices; the ideal role of the triage hospitalist is to admit to the teaching services those patients that will best advance the education of the learners, including a consideration of the goals and objectives of the rotation. Future studies correlating different triage practices to actual educational outcomes would be very helpful.

Third, the analysis could not reliably eliminate patients whose admissions did not represent genuine triage decisions (eg, those assigned to the hospitalist service after the teaching service had reached its capacity or immediately after they had received a complex case). Studying admission decisions prospectively could eliminate this variability, but it could introduce a Hawthorne effect, the negative effects of which likely would outweigh this benefit.

CONCLUSION

Triage hospitalists distributed patients fairly evenly between teaching and nonteaching services, but residents and faculty alike perceived that residents would benefit from more bread‐and‐butter cases. Hospitals considering the addition of a nonteaching service may want to incorporate a faculty development project focused on the triage process to ensure that these traditional medicine cases are assigned to resident services and to ensure that the great teaching case is not considered such because of complexity and acuity alone.

Acknowledgements

The authors thank Elizabeth Jones and Lois Bell for their assistance with survey collection and collation.

Disclosures: This study (institutional review board application #11‐3;002635) was deemed exempt by the Mayo Clinic institutional review board on May 16, 2011. The authors report no conflicts of interest.

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The advent of work‐hour restrictions and admission limits for teaching services has led many academic hospitals to implement hospitalist‐run staff (ie, nonteaching) services.[1] Although this practice is not new,[2] it is growing in popularity[3] and has been endorsed as a way to protect resident teaching and prevent excessive workload.[4] One potential benefit is the assignment of more educational cases to teaching services, whereas the nonteaching services receive more patients whose care is presumably relatively mundane or routine.[5]

Despite the rapid growth of this system of educational triage,[6] little is known about the factors considered when teaching versus nonteaching decisions are made. Studies of clinical outcomes for patients assigned to teaching versus nonteaching services have understandably used random assignment,[7, 8] whereas a study finding that patients with unhealthy substance use were more likely to be on teaching services than nonteaching services relied on patient assignment based on the identity of the patient's primary care provider or insurer.[9] In 2009, O'Connor et al. reported that implementation of nonteaching services at 2 hospitals had led to unequal distribution of patients in terms of demographics, diagnosis, and illness severity.[10] Triage decisions were made by either a nurse coordinator or a medical chief resident, and sicker patients (and occasionally good teaching cases) were preferentially placed on the teaching services, reportedly out of respect for the comfort level of the midlevel providers who staffed the nonteaching services.

Our institution has used a system of hospitalist educational triage since 1998. Over that time, residents have often expressed concerns about the assignment of patients to the teaching services, reporting in particular that they receive a disproportionate number of complex cases and outside transfers. In 2006, the hospitalist group attempted to address these concerns by collecting real‐time admission data, but the application of the data was limited by suspicion on both sides of a Hawthorne effect (data not published).

If trainee and hospitalist expectations for what constitutes a great teaching case differ substantially, that difference can have significant implications for resident and medical student teaching, self‐perceived roles, and satisfaction. More significantly, an understanding of what faculty perceive as ideal teaching cases would provide valuable information about the strengths and weaknesses of the teachingnonteaching model, which may prove useful to other academic institutions considering such a system. In this study, we endeavored to understand what residents and hospitalists consider an educational admission and to compare these expectations to the actual triage decisions of hospitalists.

METHODS

Mayo Clinic Hospital (Phoenix, Arizona) has used separate teaching and nonteaching services since opening in 1998. At our institution, like many others,[11] a hospitalist is assigned to take all calls for emergency department (ED) admissions, admissions from outpatient clinics, and transfer requests; this physician directs patients to the teaching or nonteaching service. At the time of our study, the 2 teaching services alternated days in which they admitted up to 7 patients, and the 5 nonteaching services admitted all other patients and provided medicine consultative services for the hospital. Teaching services consisted of 1 hospitalist, 2 senior residents, 2 or 3 first‐year residents, and sometimes 1 third‐ or fourth‐year medical student. Nonteaching services consisted of a hospitalist with intermittent assistance from a physician assistant or nurse practitioner.

Although there are no formal guidelines for the hospitalist triage role, hospitalists are encouraged to assign more educational cases to the teaching services and to allow the residents enough time to address the acute needs of the prior admission before receiving the next admission. Residents are not assigned any patients between 4:00 am and 7:00 am. The goals and objectives for the resident rotation on the medicine teaching service include a list of diagnoses with which residents are expected to become familiar during their residency; triage hospitalists have on‐line access to these goals and objectives.

To assess resident and hospitalist opinions about what types of patients should or should not be admitted to teaching services and to compare those characteristics with those of the patients actually admitted to teaching services, we began by administering a simple, open‐ended survey and asked both groups: (1) In an ideal world, what kinds of patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital? (2) In the real world, what kinds of patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?

Ample space was provided for free‐text entries. Residents were additionally asked their postgraduate year level. The survey was administered in April 2011, at which time all residents would have rotated on the medicine teaching services several times. Survey responses were anonymous and were compiled and retyped by someone unfamiliar with the subjects' handwriting.

Two authors (D.L.R. and H.R.L.) reviewed the results of the first survey and used conventional content analysis to group responses into categories and tally them.[12] Responses from hospitalists and residents were used to determine the content for a second, quantitative survey that asked respondents to rate specific possible factors that affected triage decisions on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission). The second survey, administered to the same residents and hospitalists in May 2011, asked: (1) In an ideal world, how do these factors contribute to the decision about which patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital? (2) In the real world, how do these factors contribute to the decision about which patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?

Assuming a 3:1 ratio of nonteaching to teaching admissions, we calculated that we would need to analyze 1028 admissions to detect a 10% difference in the proportion of a specific trait present in 50% of patients admitted to the nonteaching service, with the use of a 2‐sided test with 80% statistical power and a significance level of 0.05.

We collected data on patient assignment via retrospective chart review to avoid the possibility of a Hawthorne effect. We studied all admissions to the internal medicine services for a 3‐month period before the administration of the first survey (January 1, 2011 through March 31, 2011). The following patient data were collected: service assignment (teaching vs nonteaching), age, sex, source of admission (ED, direct from clinic, outside transfer, internal transfer from another hospital service), first visit to our institution, prior hematology or oncology visit at our institution (as a surrogate for cancer), prior psychiatry visit at our institution (as a surrogate for psychiatric disease), transplantation history, human immunodeficiency virus (HIV) or acquired immune deficiency syndrome (AIDS) history, chronic or functional pain mentioned in ED or admission note, need for translator, and benefactor status. Additionally, an online calculator was used to determine the Charlson Comorbidity Index score for each patient.[13] We collected actual patient data corresponding to factors reported by survey respondents whenever possible and practical, but not every factor reported by survey respondents was amenable to rigorous analysis; for example, no unbiased method could be devised to rigorously categorize patients whose admissions are likely to take more time or difficult patients and families.

Responses to the second (quantitative) survey and patient data were compared using the Pearson [2] and Fisher exact test for categorical variables and the Student t test or Wilcoxon rank sum test for continuous variables. Categorical variables that achieved statistical significance for overall difference were analyzed on a post hoc basis using the Bonferroni method to control for the overall type I error rate. We also examined the differences between actual and ideal triage decisions using the Wilcoxon signed rank test. Data were analyzed using SAS 9.3 (SAS Institute, Inc., Cary, NC). Statistical significance was defined as P<0.05.

The project was deemed exempt by the Mayo Clinic institutional review board.

RESULTS

We surveyed all categorical internal medicine residents (n=30, 10 each from postgraduate year [PGY]‐1, PGY‐2, and PGY‐3) and hospitalists except the authors (n=21; average years since completing training=13.3; range, 129 years). For both surveys, responses were collected from 29 (96.7%) residents. The nonresponding resident was a PGY‐2. The response rate for hospitalists was 20/21 (95.2%) for the first survey and 16/21 (76.2%) for the second survey.

First Survey

Table 1 compares the most frequent resident and faculty responses to the initial, open‐ended survey about what types of patients should or should not be admitted to teaching services. Residents most commonly indicated that ideal patients were traditional medicine cases (ie, bread‐and‐butter admissions, with 13 residents using that exact phrase), and others supplied specific examples of such cases, including chronic obstructive pulmonary disease, pneumonia, diabetic ketoacidosis, congestive heart failure, chest pain, and gastrointestinal tract bleeding. Only 1 faculty member mentioned bread‐and‐butter admissions, although several listed examples like chest pain and pneumonia. A smaller number of residents pointed to the importance of rare cases, whereas faculty considered rare cases to be ideal for teaching services, followed by variety of pathology and complexity.

Most Frequent Resident and Faculty Responses to an Open‐Ended Survey About Types of Patients Admitted (Ideal vs Actual)
 Residents (n=29)Faculty (n=20)
QuestionCharacteristicNo. (%)CharacteristicNo. (%)
  • NOTE: Abbreviations: AIDS, acquired immunodeficiency syndrome; HIV, human immunodeficiency virus.

  • Similar responses were grouped via content analysis.

  • Specific examples cited include chronic obstructive pulmonary disease, pneumonia, diabetic ketoacidosis, congestive heart failure, chest pain, and gastrointestinal tract bleeding.

In an ideal world, what kinds of patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital?Bread‐and butter admissionsb14 (44.8)Rare cases9 (45.0)
Rare cases9 (31.0)Variety of pathology7 (35.0)
No social admissions7 (24.1)Complex cases5 (25.0)
New diagnoses instead of chronic management4 (13.8)Variety of complexity5 (25.0)
Variety of complexity4 (13.8)Patients with HIV/AIDS3 (15.0)
Diagnostic dilemmas3 (15.0)
New diagnoses instead of chronic management3 (15.0)
In the real world, what kinds of patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?Patients with cancer11 (37.9)Complex patients6 (30.0)
Complex patients10 (34.5)Difficult patients5 (25.0)
Social admissions9 (31.0)Patients whose admissions are expected to be time consuming5 (25.0)
Acutely ill patients6 (20.7)Rare cases3 (15.0)
Variety of pathology6 (20.7)Cases determined by the time of day3 (15.0)

With regard to actual admissions, residents and faculty agreed that they often were complex, but residents were more likely to suggest high rates of patients with cancer (11 residents vs 2 hospitalists) and social admissions (9 residents vs 2 hospitalists). Four residents each believed that they preferentially received elderly patients, outside transfers, and patients with functional pain, and 2 perceived a disproportionate number of patients making their first visit to Mayo Clinic. One hospitalist believed that residents were more likely to receive non‐English speakers.

Second Survey

Table 2 compares the resident and faculty responses to the second, numerical survey regarding ideal admissions to the teaching services. In contrast to the first survey, residents prioritized rare cases as the feature they most associated with ideal teaching admissions. They also placed a premium on variety of pathology, patients with unique findings, and patients likely to be written up or presented. The patients they believed were least appropriate for a teaching service were social admissions or those with placement issues, patients with functional or chronic pain, and benefactors or public figures.

Resident and Faculty Survey Responses Regarding Ideal Admissions to Teaching Services
FactorResident, n=29Faculty, n=16P Value
  • NOTE: Participants rated each factor on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission), with 3 representing No impact on admission decision. Abbreviations: AIDS, acquired immune deficiency syndrome; HIV, human immunodeficiency virus; SD, standard deviation.

Rare diseases  0.22
Mean (SD)4.8 (0.5)4.9 (0.3) 
Median55 
Variety of pathology  0.22
Mean (SD)4.7 (0.5)4.5 (0.5) 
Median55 
Cases that might be written up or presented  0.35
Mean (SD)4.7 (0.5)4.8 (0.6) 
Median55 
Bread‐and‐butter cases  0.001
Mean (SD)4.6 (0.7)3.7 (0.9) 
Median54 
Unique physical findings  0.67
Mean (SD)4.6 (0.6)4.7 (0.5) 
Median55 
Variety of complexity  0.21
Mean (SD)4.3 (0.7)4.1 (0.6) 
Median44 
Variety of acuity  0.40
Mean (SD)4.2 (0.7)4.1 (0.7) 
Median44 
Spectrum of ages  0.046
Mean (SD)4.1 (0.8)3.6 (0.8) 
Median43 
HIV or AIDS  0.39
Mean (SD)4.1 (0.9)4.4 (0.5) 
Median44 
Acutely ill or unstable  0.54
Mean (SD)4.0 (0.9)3.9 (0.6) 
Median44 
Complex patients  0.94
Mean (SD)4.0 (0.8)3.9 (0.6) 
Median44 
Patients at end of life  0.16
Mean (SD)3.5 (0.8)3.1 (0.6) 
Median33 
First‐time Mayo patients  0.45
Mean (SD)3.5 (0.7)3.3 (0.5) 
Median33 
Younger patients  0.50
Mean (SD)3.5 (0.9)3.3 (0.6) 
Median33 
Stable patients  0.21
Mean (SD)3.3 (0.8)3.1 (0.3) 
Median33 
Patients with cancer  0.67
Mean (SD)3.3 (0.8)3.1 (0.4) 
Median33 
Straightforward patients  0.64
Mean (SD)3.2 (0.8)3.1 (0.8) 
Median33 
Older patients  0.73
Mean (SD)3.2 (0.7)3.1 (0.3) 
Median33 
Patients with a history of transplantation  0.67
Mean (SD)3.1 (1.1)3.3 (0.6) 
Median33 
Time of day of admission  0.71
Mean (SD)3.1 (1.0)3.1 (0.5) 
Median33 
Patients with a history of psychiatric illness  0.59
Mean (SD)3.1 (1.0)3.1 (0.6) 
Median33 
Patients who require a translator  0.49
Mean (SD)3.0 (0.9)3.1 (0.5) 
Median33 
Patients whose admissions are expected to take more time  0.13
Mean (SD)2.9 (0.8)3.2 (0.6) 
Median33 
Difficult patients and families  0.55
Mean (SD)2.8 (1.0)2.6 (0.8) 
Median33 
Transfers from other hospitals  0.11
Mean (SD)2.7 (1.1)3.1 (0.3) 
Median33 
Benefactors and public figures  0.49
Mean (SD)2.7 (1.0)2.5 (0.7) 
Median33 
Patients with functional or chronic pain  0.87
Mean (SD)2.4 (1.1)2.4 (1.0)
Median23 
Social admissions or placement issues  0.99
Mean (SD)2.1 (1.1)2.0 (1.0) 
Median22 

Faculty prioritized many of the same features for ideal teaching cases as residents; 4 of their 5 highest‐scoring factors were the same (rare diseases, patients whose cases might be written up or presented, patients with unique physical findings, and variety of pathology). They also agreed on the least ideal features (social admissions or placement issues, patients with functional or chronic pain, and benefactors or public figures). The only significant differences between resident and faculty ratings for ideal teaching cases were for bread‐and‐butter cases and a spectrum of ages.

Discordance between resident and faculty survey responses on actual admission decisions (Table 3) was starker; residents rated several features significantly higher than faculty as features contributing to triage decisions including older patients; patients with functional or chronic pain, social admissions, or placement issues; patients with cancer; transfers from other hospitals; and difficult patients and families. Relative to residents, faculty reported that patients with HIV or AIDS, and patients whose cases were likely to be written up or presented, were more likely to be admitted to teaching services.

Resident and Faculty Survey Responses Regarding Actual Admissions to Teaching Services
FactorResident, n=29Faculty, n=16P Value
  • NOTE: Participants rated each factor on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission), with 3 representing No impact on admission decision. Abbreviations: AIDS, acquired immune deficiency syndrome; HIV, human immunodeficiency virus; SD, standard deviation.

Rare diseases  0.14
Mean (SD)4.4 (0.6)4.7 (0.6) 
Median45 
Complex patients  0.83
Mean (SD)4.3 (0.6)4.3 (0.6) 
Median44 
Acutely ill or unstable  0.18
Mean (SD)4.3 (0.7)3.9 (0.9) 
Median44 
Unique physical findings  0.18
Mean (SD)4.1 (0.8)4.5 (0.6) 
Median45 
Transfers from other hospitals  0.003
Mean (SD)4.1 (1.0)3.5 (0.5) 
Median43 
Cases that might be written up or presented  0.03
Mean (SD)4.1 (0.7)4.6 (0.6) 
Median45 
Older patients  <0.001
Mean (SD)3.9 (0.8)3.0 (0.7) 
Median43 
Time of day of admission  0.50
Mean (SD)3.9 (1.1)3.7 (0.9) 
Median44 
Patients with cancer  0.01
Mean (SD)3.9 (0.9)3.3 (0.5) 
Median43 
Variety of pathology  0.21
Mean (SD)3.9 (0.8)4.2 (0.7) 
Median44 
Patients whose admissions are expected to take more time  0.13
Mean (SD)3.9 (1.0)3.4 (0.9) 
Median43 
HIV or AIDS  0.008
Mean (SD)3.8 (0.9)4.5 (0.5) 
Median44.5 
Variety of complexity  0.31
Mean (SD)3.7 (0.9)3.9 (0.6) 
Median3.54 
Bread‐and‐butter cases  0.07
Mean (SD)3.6 (1.0)2.9 (1.2) 
Median33 
First‐time Mayo patients  0.82
Mean (SD)3.6 (0.9)3.5 (0.7) 
Median33 
Patients with functional or chronic pain  0.004
Mean (SD)3.6 (1.0)2.8 (0.7) 
Median43 
Social admissions or placement issues  0.03
Mean (SD)3.5 (1.2)2.7 (0.9) 
Median43 
Variety of acuity  0.25
Mean (SD)3.5 (0.8)3.7 (0.6) 
Median34 
Difficult patients and families  0.03
Mean (SD)3.4 (0.9)2.8 (0.7) 
Median33 
Patients at end of life  0.10
Mean (SD)3.4 (0.8)3.0 (0.5) 
Median33 
Spectrum of ages  0.80
Mean (SD)3.3 (0.7)3.3 (0.6) 
Median33 
Patients with a history of psychiatric illness  0.81
Mean (SD)3.3 (0.9)3.1 (0.6) 
Median33 
Patients with a history of transplantation  0.25
Mean (SD)3.2 (0.9)3.5 (0.5) 
Median33 
Patients who require a translator  0.60
Mean (SD)3.2 (0.7)3.2 (0.6) 
Median33 
Younger patients  0.42
Mean (SD)3.0 (0.9)3.1 (0.4) 
Median33 
Benefactors and public figures  0.09
Mean (SD)2.9 (1.0)2.3 (0.7) 
Median32 
Straightforward patients  0.18
Mean (SD)2.8 (1.0)2.4 (1.0) 
Median2.52 
Stable patients  0.53
Mean (SD)2.7 (1.0)2.8 (0.7) 
Median33 

Comparing resident survey ratings for ideal versus actual triage decisions gave some insight into the features that they thought were inappropriately emphasized or ignored when triage decisions were made. Differences in resident scores for ideal versus actual admissions were significantly different for 16 of 28 items (data available upon request), suggesting a degree of perceived discordance. The largest positive differences (ie, features they valued in teaching admissions but thought were less represented in actual admissions) were for bread‐and‐butter admissions, variety of pathology, a spectrum of ages, and variety of acuity. The largest negative differences (ie, features they thought were well represented in actual admissions but were less valuable) were for social admissions or placement issues, transfers from other hospitals, patients with functional or chronic pain, and patients whose admissions were expected to take more time.

In terms of ideal versus actual triage decisions, faculty reported less discordance than residents; ideal and actual triage behavior differed significantly only for 4 of 28 items (data available upon request). They did agree with residents about the relative lack of bread‐and‐butter admissions and the over‐representation of social admissions or placement issues and transfers from other hospitals. They additionally noted a lack of straightforward cases.

We reviewed records of the 1426 patients admitted to the internal medicine services during the study period. Of these, 359 (25.2%) were assigned to the teaching services. Patient characteristics are summarized in Table 4.

Characteristics of Patients Admitted to the Internal Medicine Services (N=1,426)
CharacteristicTeaching Service, n=359Nonteaching Service, n=1,067P Value
  • NOTE: Abbreviations: SD, standard deviation.

Age, y, mean (SD)66.7 (16.5)69.3 (15.7)0.008
Admission type, No. (%)  0.049
Admission from the emergency department315 (87.7)915 (85.8)0.34
Direct admission from Mayo outpatient clinic27 (7.5)114 (10.7)0.08
Transfer from another institution16 (4.5)27 (2.5)0.06
Internal transfer from a different hospital service1 (0.3)11 (1.0)0.31
First‐time Mayo patient, No. (%)61 (17.0)175 (16.4)0.79
Prior hematology or oncology visit, No. (%)86 (24.0)235 (22.0)0.45
History of transplantation, No. (%)20 (5.6)52 (4.9)0.60
Prior psychiatry visit, No. (%)53 (14.8)122 (11.4)0.10
History of chronic or functional pain, No. (%)122 (34.0)330 (30.9)0.28
Required translator, No. (%)5 (1.4)14 (1.3)0.91
Benefactor, No. (%)5 (1.4)24 (2.2)0.32
Charlson comorbidity score, mean (SD)2.7 (2.5)2.6 (2.5)0.49

DISCUSSION

The results of our qualitative and quantitative surveys showed significant differences between resident and staff perceptions of the faculty triage role. Although both groups similarly valued many features, residents expressed a clear preference for more bread‐and‐butter admissions, whereas the staff prioritized selecting the most complex, challenging, and rare cases from among the day's admissions to give to the residents. (Residents were also very interested in rare cases, suggesting that they saw benefit to admitting patients with a variety of degrees of rarity and complexity.) Residents and faculty seemed to agree that the number of social admissions and outside transfers admitted to teaching services was not ideal.

These perceptions have substantial implications. If the current triage process is to continue, there may be benefit to designing a faculty development project focused on the triage process, which previously has been largely unexamined. Efforts to remove or limit time barriers that prevent perceived educational cases from being admitted to teaching services is also a worthy endeavor (eg, structuring the 2 teams to admit simultaneously so that teaching teams can admit patients back to back without exceeding capacity). In addition, residents may benefit from teaching hospitalists who concentrate educational efforts on the learning that can be extracted from the care of any patient, including admissions that initially seem mundane or purely social.[14] A concerted effort to divert more traditional medicine admissions and fewer unusual cases to the teaching service might improve resident perceptions of the triage process. Further, although the care of any patient can have education benefit, the fact that both groups perceived excessive social admissions in the teaching service suggests that a potential benefit of a nonteaching service (ie, absorbing the most mundane admissions) may not yet be fully realized.

Despite the perceived differences noted on the surveys, we found remarkably few differences between patients admitted to the teaching and nonteaching services. Although both groups rated complexity; outside transfers; being seen at the institution for the first time; and histories of transplantation, cancer, chronic or functional pain, and psychiatric disease as increasing the likelihood of admission to a teaching service, no differences were observed for these factors or their quantifiable surrogates. (Although the overall test for admission type achieved marginal statistical significance, none of the individual admission types were significantly different in post hoc analysis.) Residents, but not faculty, thought that older patients were over‐represented on the teaching service, but their assigned patients were significantly younger than those on the nonteaching service.

These findings have several possible explanations. First, although most hospitalists spend time on teaching and nonteaching services (and therefore are familiar with the patient composition of each), residents get very little exposure to the nonteaching services (until they are senior residents with a rotation on a consulting service). Their impression of inequity may be due to misunderstanding the patient composition of the nonteaching services. Second, the mere existence of a triage role may create false expectations about patient composition; that is, simply by knowing that every admission was chosen for its educational merit, residents may have disproportionate perceptions about those cases judged to have less educational value, even ifas our data suggestassignments to teaching versus nonteaching services are occurring fairly equitably.

Study Limitations

We acknowledge several limitations of our study. First, many factors that were reported as important in the qualitative survey did not lend themselves to objective abstraction from patient records. For example, providers did not specifically document when an admission is purely social, nor was there an objective way to identify difficult patients or families or admissions that were expected to take more time. We attempted to limit the analysis to objective patient metrics that were (1) not influenced by the teaching or nonteaching assignment itself (eg, we avoided discharge diagnoses, which might be entered differently by residents and staff hospitalists) and (2) easily available to triage hospitalists. For the latter reason, we used a prior appointment in the hematology or oncology clinic as a surrogate for cancer patients and a prior psychiatry visit as a surrogate for patients with a history of psychiatric disease. These are naturally inexact surrogates, but they reflect the information a busy hospitalist is likely to access when making patient assignment decisions.

Second, it may well be that assigning patients equitably according to a certain trait is not the same as assigning patients ideally for the educational needs of residents. The patients admitted to our medicine services (teaching and nonteaching) were generally older than 60 years, had complex diagnoses, and had substantial pain. Residents on the teaching services potentially would benefit from an intentionally unbalanced admission policy that shunted patients to the teaching services on the basis of features other than individual perceived educational merit. It must also be borne in mind that resident, and for that matter faculty, perceptions of ideal teaching cases are likely inexact correlates of educational best practices; the ideal role of the triage hospitalist is to admit to the teaching services those patients that will best advance the education of the learners, including a consideration of the goals and objectives of the rotation. Future studies correlating different triage practices to actual educational outcomes would be very helpful.

Third, the analysis could not reliably eliminate patients whose admissions did not represent genuine triage decisions (eg, those assigned to the hospitalist service after the teaching service had reached its capacity or immediately after they had received a complex case). Studying admission decisions prospectively could eliminate this variability, but it could introduce a Hawthorne effect, the negative effects of which likely would outweigh this benefit.

CONCLUSION

Triage hospitalists distributed patients fairly evenly between teaching and nonteaching services, but residents and faculty alike perceived that residents would benefit from more bread‐and‐butter cases. Hospitals considering the addition of a nonteaching service may want to incorporate a faculty development project focused on the triage process to ensure that these traditional medicine cases are assigned to resident services and to ensure that the great teaching case is not considered such because of complexity and acuity alone.

Acknowledgements

The authors thank Elizabeth Jones and Lois Bell for their assistance with survey collection and collation.

Disclosures: This study (institutional review board application #11‐3;002635) was deemed exempt by the Mayo Clinic institutional review board on May 16, 2011. The authors report no conflicts of interest.

The advent of work‐hour restrictions and admission limits for teaching services has led many academic hospitals to implement hospitalist‐run staff (ie, nonteaching) services.[1] Although this practice is not new,[2] it is growing in popularity[3] and has been endorsed as a way to protect resident teaching and prevent excessive workload.[4] One potential benefit is the assignment of more educational cases to teaching services, whereas the nonteaching services receive more patients whose care is presumably relatively mundane or routine.[5]

Despite the rapid growth of this system of educational triage,[6] little is known about the factors considered when teaching versus nonteaching decisions are made. Studies of clinical outcomes for patients assigned to teaching versus nonteaching services have understandably used random assignment,[7, 8] whereas a study finding that patients with unhealthy substance use were more likely to be on teaching services than nonteaching services relied on patient assignment based on the identity of the patient's primary care provider or insurer.[9] In 2009, O'Connor et al. reported that implementation of nonteaching services at 2 hospitals had led to unequal distribution of patients in terms of demographics, diagnosis, and illness severity.[10] Triage decisions were made by either a nurse coordinator or a medical chief resident, and sicker patients (and occasionally good teaching cases) were preferentially placed on the teaching services, reportedly out of respect for the comfort level of the midlevel providers who staffed the nonteaching services.

Our institution has used a system of hospitalist educational triage since 1998. Over that time, residents have often expressed concerns about the assignment of patients to the teaching services, reporting in particular that they receive a disproportionate number of complex cases and outside transfers. In 2006, the hospitalist group attempted to address these concerns by collecting real‐time admission data, but the application of the data was limited by suspicion on both sides of a Hawthorne effect (data not published).

If trainee and hospitalist expectations for what constitutes a great teaching case differ substantially, that difference can have significant implications for resident and medical student teaching, self‐perceived roles, and satisfaction. More significantly, an understanding of what faculty perceive as ideal teaching cases would provide valuable information about the strengths and weaknesses of the teachingnonteaching model, which may prove useful to other academic institutions considering such a system. In this study, we endeavored to understand what residents and hospitalists consider an educational admission and to compare these expectations to the actual triage decisions of hospitalists.

METHODS

Mayo Clinic Hospital (Phoenix, Arizona) has used separate teaching and nonteaching services since opening in 1998. At our institution, like many others,[11] a hospitalist is assigned to take all calls for emergency department (ED) admissions, admissions from outpatient clinics, and transfer requests; this physician directs patients to the teaching or nonteaching service. At the time of our study, the 2 teaching services alternated days in which they admitted up to 7 patients, and the 5 nonteaching services admitted all other patients and provided medicine consultative services for the hospital. Teaching services consisted of 1 hospitalist, 2 senior residents, 2 or 3 first‐year residents, and sometimes 1 third‐ or fourth‐year medical student. Nonteaching services consisted of a hospitalist with intermittent assistance from a physician assistant or nurse practitioner.

Although there are no formal guidelines for the hospitalist triage role, hospitalists are encouraged to assign more educational cases to the teaching services and to allow the residents enough time to address the acute needs of the prior admission before receiving the next admission. Residents are not assigned any patients between 4:00 am and 7:00 am. The goals and objectives for the resident rotation on the medicine teaching service include a list of diagnoses with which residents are expected to become familiar during their residency; triage hospitalists have on‐line access to these goals and objectives.

To assess resident and hospitalist opinions about what types of patients should or should not be admitted to teaching services and to compare those characteristics with those of the patients actually admitted to teaching services, we began by administering a simple, open‐ended survey and asked both groups: (1) In an ideal world, what kinds of patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital? (2) In the real world, what kinds of patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?

Ample space was provided for free‐text entries. Residents were additionally asked their postgraduate year level. The survey was administered in April 2011, at which time all residents would have rotated on the medicine teaching services several times. Survey responses were anonymous and were compiled and retyped by someone unfamiliar with the subjects' handwriting.

Two authors (D.L.R. and H.R.L.) reviewed the results of the first survey and used conventional content analysis to group responses into categories and tally them.[12] Responses from hospitalists and residents were used to determine the content for a second, quantitative survey that asked respondents to rate specific possible factors that affected triage decisions on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission). The second survey, administered to the same residents and hospitalists in May 2011, asked: (1) In an ideal world, how do these factors contribute to the decision about which patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital? (2) In the real world, how do these factors contribute to the decision about which patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?

Assuming a 3:1 ratio of nonteaching to teaching admissions, we calculated that we would need to analyze 1028 admissions to detect a 10% difference in the proportion of a specific trait present in 50% of patients admitted to the nonteaching service, with the use of a 2‐sided test with 80% statistical power and a significance level of 0.05.

We collected data on patient assignment via retrospective chart review to avoid the possibility of a Hawthorne effect. We studied all admissions to the internal medicine services for a 3‐month period before the administration of the first survey (January 1, 2011 through March 31, 2011). The following patient data were collected: service assignment (teaching vs nonteaching), age, sex, source of admission (ED, direct from clinic, outside transfer, internal transfer from another hospital service), first visit to our institution, prior hematology or oncology visit at our institution (as a surrogate for cancer), prior psychiatry visit at our institution (as a surrogate for psychiatric disease), transplantation history, human immunodeficiency virus (HIV) or acquired immune deficiency syndrome (AIDS) history, chronic or functional pain mentioned in ED or admission note, need for translator, and benefactor status. Additionally, an online calculator was used to determine the Charlson Comorbidity Index score for each patient.[13] We collected actual patient data corresponding to factors reported by survey respondents whenever possible and practical, but not every factor reported by survey respondents was amenable to rigorous analysis; for example, no unbiased method could be devised to rigorously categorize patients whose admissions are likely to take more time or difficult patients and families.

Responses to the second (quantitative) survey and patient data were compared using the Pearson [2] and Fisher exact test for categorical variables and the Student t test or Wilcoxon rank sum test for continuous variables. Categorical variables that achieved statistical significance for overall difference were analyzed on a post hoc basis using the Bonferroni method to control for the overall type I error rate. We also examined the differences between actual and ideal triage decisions using the Wilcoxon signed rank test. Data were analyzed using SAS 9.3 (SAS Institute, Inc., Cary, NC). Statistical significance was defined as P<0.05.

The project was deemed exempt by the Mayo Clinic institutional review board.

RESULTS

We surveyed all categorical internal medicine residents (n=30, 10 each from postgraduate year [PGY]‐1, PGY‐2, and PGY‐3) and hospitalists except the authors (n=21; average years since completing training=13.3; range, 129 years). For both surveys, responses were collected from 29 (96.7%) residents. The nonresponding resident was a PGY‐2. The response rate for hospitalists was 20/21 (95.2%) for the first survey and 16/21 (76.2%) for the second survey.

First Survey

Table 1 compares the most frequent resident and faculty responses to the initial, open‐ended survey about what types of patients should or should not be admitted to teaching services. Residents most commonly indicated that ideal patients were traditional medicine cases (ie, bread‐and‐butter admissions, with 13 residents using that exact phrase), and others supplied specific examples of such cases, including chronic obstructive pulmonary disease, pneumonia, diabetic ketoacidosis, congestive heart failure, chest pain, and gastrointestinal tract bleeding. Only 1 faculty member mentioned bread‐and‐butter admissions, although several listed examples like chest pain and pneumonia. A smaller number of residents pointed to the importance of rare cases, whereas faculty considered rare cases to be ideal for teaching services, followed by variety of pathology and complexity.

Most Frequent Resident and Faculty Responses to an Open‐Ended Survey About Types of Patients Admitted (Ideal vs Actual)
 Residents (n=29)Faculty (n=20)
QuestionCharacteristicNo. (%)CharacteristicNo. (%)
  • NOTE: Abbreviations: AIDS, acquired immunodeficiency syndrome; HIV, human immunodeficiency virus.

  • Similar responses were grouped via content analysis.

  • Specific examples cited include chronic obstructive pulmonary disease, pneumonia, diabetic ketoacidosis, congestive heart failure, chest pain, and gastrointestinal tract bleeding.

In an ideal world, what kinds of patients should be admitted to the internal medicine teaching services at Mayo Clinic Hospital?Bread‐and butter admissionsb14 (44.8)Rare cases9 (45.0)
Rare cases9 (31.0)Variety of pathology7 (35.0)
No social admissions7 (24.1)Complex cases5 (25.0)
New diagnoses instead of chronic management4 (13.8)Variety of complexity5 (25.0)
Variety of complexity4 (13.8)Patients with HIV/AIDS3 (15.0)
Diagnostic dilemmas3 (15.0)
New diagnoses instead of chronic management3 (15.0)
In the real world, what kinds of patients are admitted to the internal medicine teaching services at Mayo Clinic Hospital?Patients with cancer11 (37.9)Complex patients6 (30.0)
Complex patients10 (34.5)Difficult patients5 (25.0)
Social admissions9 (31.0)Patients whose admissions are expected to be time consuming5 (25.0)
Acutely ill patients6 (20.7)Rare cases3 (15.0)
Variety of pathology6 (20.7)Cases determined by the time of day3 (15.0)

With regard to actual admissions, residents and faculty agreed that they often were complex, but residents were more likely to suggest high rates of patients with cancer (11 residents vs 2 hospitalists) and social admissions (9 residents vs 2 hospitalists). Four residents each believed that they preferentially received elderly patients, outside transfers, and patients with functional pain, and 2 perceived a disproportionate number of patients making their first visit to Mayo Clinic. One hospitalist believed that residents were more likely to receive non‐English speakers.

Second Survey

Table 2 compares the resident and faculty responses to the second, numerical survey regarding ideal admissions to the teaching services. In contrast to the first survey, residents prioritized rare cases as the feature they most associated with ideal teaching admissions. They also placed a premium on variety of pathology, patients with unique findings, and patients likely to be written up or presented. The patients they believed were least appropriate for a teaching service were social admissions or those with placement issues, patients with functional or chronic pain, and benefactors or public figures.

Resident and Faculty Survey Responses Regarding Ideal Admissions to Teaching Services
FactorResident, n=29Faculty, n=16P Value
  • NOTE: Participants rated each factor on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission), with 3 representing No impact on admission decision. Abbreviations: AIDS, acquired immune deficiency syndrome; HIV, human immunodeficiency virus; SD, standard deviation.

Rare diseases  0.22
Mean (SD)4.8 (0.5)4.9 (0.3) 
Median55 
Variety of pathology  0.22
Mean (SD)4.7 (0.5)4.5 (0.5) 
Median55 
Cases that might be written up or presented  0.35
Mean (SD)4.7 (0.5)4.8 (0.6) 
Median55 
Bread‐and‐butter cases  0.001
Mean (SD)4.6 (0.7)3.7 (0.9) 
Median54 
Unique physical findings  0.67
Mean (SD)4.6 (0.6)4.7 (0.5) 
Median55 
Variety of complexity  0.21
Mean (SD)4.3 (0.7)4.1 (0.6) 
Median44 
Variety of acuity  0.40
Mean (SD)4.2 (0.7)4.1 (0.7) 
Median44 
Spectrum of ages  0.046
Mean (SD)4.1 (0.8)3.6 (0.8) 
Median43 
HIV or AIDS  0.39
Mean (SD)4.1 (0.9)4.4 (0.5) 
Median44 
Acutely ill or unstable  0.54
Mean (SD)4.0 (0.9)3.9 (0.6) 
Median44 
Complex patients  0.94
Mean (SD)4.0 (0.8)3.9 (0.6) 
Median44 
Patients at end of life  0.16
Mean (SD)3.5 (0.8)3.1 (0.6) 
Median33 
First‐time Mayo patients  0.45
Mean (SD)3.5 (0.7)3.3 (0.5) 
Median33 
Younger patients  0.50
Mean (SD)3.5 (0.9)3.3 (0.6) 
Median33 
Stable patients  0.21
Mean (SD)3.3 (0.8)3.1 (0.3) 
Median33 
Patients with cancer  0.67
Mean (SD)3.3 (0.8)3.1 (0.4) 
Median33 
Straightforward patients  0.64
Mean (SD)3.2 (0.8)3.1 (0.8) 
Median33 
Older patients  0.73
Mean (SD)3.2 (0.7)3.1 (0.3) 
Median33 
Patients with a history of transplantation  0.67
Mean (SD)3.1 (1.1)3.3 (0.6) 
Median33 
Time of day of admission  0.71
Mean (SD)3.1 (1.0)3.1 (0.5) 
Median33 
Patients with a history of psychiatric illness  0.59
Mean (SD)3.1 (1.0)3.1 (0.6) 
Median33 
Patients who require a translator  0.49
Mean (SD)3.0 (0.9)3.1 (0.5) 
Median33 
Patients whose admissions are expected to take more time  0.13
Mean (SD)2.9 (0.8)3.2 (0.6) 
Median33 
Difficult patients and families  0.55
Mean (SD)2.8 (1.0)2.6 (0.8) 
Median33 
Transfers from other hospitals  0.11
Mean (SD)2.7 (1.1)3.1 (0.3) 
Median33 
Benefactors and public figures  0.49
Mean (SD)2.7 (1.0)2.5 (0.7) 
Median33 
Patients with functional or chronic pain  0.87
Mean (SD)2.4 (1.1)2.4 (1.0)
Median23 
Social admissions or placement issues  0.99
Mean (SD)2.1 (1.1)2.0 (1.0) 
Median22 

Faculty prioritized many of the same features for ideal teaching cases as residents; 4 of their 5 highest‐scoring factors were the same (rare diseases, patients whose cases might be written up or presented, patients with unique physical findings, and variety of pathology). They also agreed on the least ideal features (social admissions or placement issues, patients with functional or chronic pain, and benefactors or public figures). The only significant differences between resident and faculty ratings for ideal teaching cases were for bread‐and‐butter cases and a spectrum of ages.

Discordance between resident and faculty survey responses on actual admission decisions (Table 3) was starker; residents rated several features significantly higher than faculty as features contributing to triage decisions including older patients; patients with functional or chronic pain, social admissions, or placement issues; patients with cancer; transfers from other hospitals; and difficult patients and families. Relative to residents, faculty reported that patients with HIV or AIDS, and patients whose cases were likely to be written up or presented, were more likely to be admitted to teaching services.

Resident and Faculty Survey Responses Regarding Actual Admissions to Teaching Services
FactorResident, n=29Faculty, n=16P Value
  • NOTE: Participants rated each factor on a Likert scale from 1 (Argues against teaching admission) to 5 (Argues for teaching admission), with 3 representing No impact on admission decision. Abbreviations: AIDS, acquired immune deficiency syndrome; HIV, human immunodeficiency virus; SD, standard deviation.

Rare diseases  0.14
Mean (SD)4.4 (0.6)4.7 (0.6) 
Median45 
Complex patients  0.83
Mean (SD)4.3 (0.6)4.3 (0.6) 
Median44 
Acutely ill or unstable  0.18
Mean (SD)4.3 (0.7)3.9 (0.9) 
Median44 
Unique physical findings  0.18
Mean (SD)4.1 (0.8)4.5 (0.6) 
Median45 
Transfers from other hospitals  0.003
Mean (SD)4.1 (1.0)3.5 (0.5) 
Median43 
Cases that might be written up or presented  0.03
Mean (SD)4.1 (0.7)4.6 (0.6) 
Median45 
Older patients  <0.001
Mean (SD)3.9 (0.8)3.0 (0.7) 
Median43 
Time of day of admission  0.50
Mean (SD)3.9 (1.1)3.7 (0.9) 
Median44 
Patients with cancer  0.01
Mean (SD)3.9 (0.9)3.3 (0.5) 
Median43 
Variety of pathology  0.21
Mean (SD)3.9 (0.8)4.2 (0.7) 
Median44 
Patients whose admissions are expected to take more time  0.13
Mean (SD)3.9 (1.0)3.4 (0.9) 
Median43 
HIV or AIDS  0.008
Mean (SD)3.8 (0.9)4.5 (0.5) 
Median44.5 
Variety of complexity  0.31
Mean (SD)3.7 (0.9)3.9 (0.6) 
Median3.54 
Bread‐and‐butter cases  0.07
Mean (SD)3.6 (1.0)2.9 (1.2) 
Median33 
First‐time Mayo patients  0.82
Mean (SD)3.6 (0.9)3.5 (0.7) 
Median33 
Patients with functional or chronic pain  0.004
Mean (SD)3.6 (1.0)2.8 (0.7) 
Median43 
Social admissions or placement issues  0.03
Mean (SD)3.5 (1.2)2.7 (0.9) 
Median43 
Variety of acuity  0.25
Mean (SD)3.5 (0.8)3.7 (0.6) 
Median34 
Difficult patients and families  0.03
Mean (SD)3.4 (0.9)2.8 (0.7) 
Median33 
Patients at end of life  0.10
Mean (SD)3.4 (0.8)3.0 (0.5) 
Median33 
Spectrum of ages  0.80
Mean (SD)3.3 (0.7)3.3 (0.6) 
Median33 
Patients with a history of psychiatric illness  0.81
Mean (SD)3.3 (0.9)3.1 (0.6) 
Median33 
Patients with a history of transplantation  0.25
Mean (SD)3.2 (0.9)3.5 (0.5) 
Median33 
Patients who require a translator  0.60
Mean (SD)3.2 (0.7)3.2 (0.6) 
Median33 
Younger patients  0.42
Mean (SD)3.0 (0.9)3.1 (0.4) 
Median33 
Benefactors and public figures  0.09
Mean (SD)2.9 (1.0)2.3 (0.7) 
Median32 
Straightforward patients  0.18
Mean (SD)2.8 (1.0)2.4 (1.0) 
Median2.52 
Stable patients  0.53
Mean (SD)2.7 (1.0)2.8 (0.7) 
Median33 

Comparing resident survey ratings for ideal versus actual triage decisions gave some insight into the features that they thought were inappropriately emphasized or ignored when triage decisions were made. Differences in resident scores for ideal versus actual admissions were significantly different for 16 of 28 items (data available upon request), suggesting a degree of perceived discordance. The largest positive differences (ie, features they valued in teaching admissions but thought were less represented in actual admissions) were for bread‐and‐butter admissions, variety of pathology, a spectrum of ages, and variety of acuity. The largest negative differences (ie, features they thought were well represented in actual admissions but were less valuable) were for social admissions or placement issues, transfers from other hospitals, patients with functional or chronic pain, and patients whose admissions were expected to take more time.

In terms of ideal versus actual triage decisions, faculty reported less discordance than residents; ideal and actual triage behavior differed significantly only for 4 of 28 items (data available upon request). They did agree with residents about the relative lack of bread‐and‐butter admissions and the over‐representation of social admissions or placement issues and transfers from other hospitals. They additionally noted a lack of straightforward cases.

We reviewed records of the 1426 patients admitted to the internal medicine services during the study period. Of these, 359 (25.2%) were assigned to the teaching services. Patient characteristics are summarized in Table 4.

Characteristics of Patients Admitted to the Internal Medicine Services (N=1,426)
CharacteristicTeaching Service, n=359Nonteaching Service, n=1,067P Value
  • NOTE: Abbreviations: SD, standard deviation.

Age, y, mean (SD)66.7 (16.5)69.3 (15.7)0.008
Admission type, No. (%)  0.049
Admission from the emergency department315 (87.7)915 (85.8)0.34
Direct admission from Mayo outpatient clinic27 (7.5)114 (10.7)0.08
Transfer from another institution16 (4.5)27 (2.5)0.06
Internal transfer from a different hospital service1 (0.3)11 (1.0)0.31
First‐time Mayo patient, No. (%)61 (17.0)175 (16.4)0.79
Prior hematology or oncology visit, No. (%)86 (24.0)235 (22.0)0.45
History of transplantation, No. (%)20 (5.6)52 (4.9)0.60
Prior psychiatry visit, No. (%)53 (14.8)122 (11.4)0.10
History of chronic or functional pain, No. (%)122 (34.0)330 (30.9)0.28
Required translator, No. (%)5 (1.4)14 (1.3)0.91
Benefactor, No. (%)5 (1.4)24 (2.2)0.32
Charlson comorbidity score, mean (SD)2.7 (2.5)2.6 (2.5)0.49

DISCUSSION

The results of our qualitative and quantitative surveys showed significant differences between resident and staff perceptions of the faculty triage role. Although both groups similarly valued many features, residents expressed a clear preference for more bread‐and‐butter admissions, whereas the staff prioritized selecting the most complex, challenging, and rare cases from among the day's admissions to give to the residents. (Residents were also very interested in rare cases, suggesting that they saw benefit to admitting patients with a variety of degrees of rarity and complexity.) Residents and faculty seemed to agree that the number of social admissions and outside transfers admitted to teaching services was not ideal.

These perceptions have substantial implications. If the current triage process is to continue, there may be benefit to designing a faculty development project focused on the triage process, which previously has been largely unexamined. Efforts to remove or limit time barriers that prevent perceived educational cases from being admitted to teaching services is also a worthy endeavor (eg, structuring the 2 teams to admit simultaneously so that teaching teams can admit patients back to back without exceeding capacity). In addition, residents may benefit from teaching hospitalists who concentrate educational efforts on the learning that can be extracted from the care of any patient, including admissions that initially seem mundane or purely social.[14] A concerted effort to divert more traditional medicine admissions and fewer unusual cases to the teaching service might improve resident perceptions of the triage process. Further, although the care of any patient can have education benefit, the fact that both groups perceived excessive social admissions in the teaching service suggests that a potential benefit of a nonteaching service (ie, absorbing the most mundane admissions) may not yet be fully realized.

Despite the perceived differences noted on the surveys, we found remarkably few differences between patients admitted to the teaching and nonteaching services. Although both groups rated complexity; outside transfers; being seen at the institution for the first time; and histories of transplantation, cancer, chronic or functional pain, and psychiatric disease as increasing the likelihood of admission to a teaching service, no differences were observed for these factors or their quantifiable surrogates. (Although the overall test for admission type achieved marginal statistical significance, none of the individual admission types were significantly different in post hoc analysis.) Residents, but not faculty, thought that older patients were over‐represented on the teaching service, but their assigned patients were significantly younger than those on the nonteaching service.

These findings have several possible explanations. First, although most hospitalists spend time on teaching and nonteaching services (and therefore are familiar with the patient composition of each), residents get very little exposure to the nonteaching services (until they are senior residents with a rotation on a consulting service). Their impression of inequity may be due to misunderstanding the patient composition of the nonteaching services. Second, the mere existence of a triage role may create false expectations about patient composition; that is, simply by knowing that every admission was chosen for its educational merit, residents may have disproportionate perceptions about those cases judged to have less educational value, even ifas our data suggestassignments to teaching versus nonteaching services are occurring fairly equitably.

Study Limitations

We acknowledge several limitations of our study. First, many factors that were reported as important in the qualitative survey did not lend themselves to objective abstraction from patient records. For example, providers did not specifically document when an admission is purely social, nor was there an objective way to identify difficult patients or families or admissions that were expected to take more time. We attempted to limit the analysis to objective patient metrics that were (1) not influenced by the teaching or nonteaching assignment itself (eg, we avoided discharge diagnoses, which might be entered differently by residents and staff hospitalists) and (2) easily available to triage hospitalists. For the latter reason, we used a prior appointment in the hematology or oncology clinic as a surrogate for cancer patients and a prior psychiatry visit as a surrogate for patients with a history of psychiatric disease. These are naturally inexact surrogates, but they reflect the information a busy hospitalist is likely to access when making patient assignment decisions.

Second, it may well be that assigning patients equitably according to a certain trait is not the same as assigning patients ideally for the educational needs of residents. The patients admitted to our medicine services (teaching and nonteaching) were generally older than 60 years, had complex diagnoses, and had substantial pain. Residents on the teaching services potentially would benefit from an intentionally unbalanced admission policy that shunted patients to the teaching services on the basis of features other than individual perceived educational merit. It must also be borne in mind that resident, and for that matter faculty, perceptions of ideal teaching cases are likely inexact correlates of educational best practices; the ideal role of the triage hospitalist is to admit to the teaching services those patients that will best advance the education of the learners, including a consideration of the goals and objectives of the rotation. Future studies correlating different triage practices to actual educational outcomes would be very helpful.

Third, the analysis could not reliably eliminate patients whose admissions did not represent genuine triage decisions (eg, those assigned to the hospitalist service after the teaching service had reached its capacity or immediately after they had received a complex case). Studying admission decisions prospectively could eliminate this variability, but it could introduce a Hawthorne effect, the negative effects of which likely would outweigh this benefit.

CONCLUSION

Triage hospitalists distributed patients fairly evenly between teaching and nonteaching services, but residents and faculty alike perceived that residents would benefit from more bread‐and‐butter cases. Hospitals considering the addition of a nonteaching service may want to incorporate a faculty development project focused on the triage process to ensure that these traditional medicine cases are assigned to resident services and to ensure that the great teaching case is not considered such because of complexity and acuity alone.

Acknowledgements

The authors thank Elizabeth Jones and Lois Bell for their assistance with survey collection and collation.

Disclosures: This study (institutional review board application #11‐3;002635) was deemed exempt by the Mayo Clinic institutional review board on May 16, 2011. The authors report no conflicts of interest.

References
  1. Weinstein DF. Duty hours for resident physicians: tough choices for teaching hospitals. N Engl J Med. 2002;347(16):12751278.
  2. Simmer TL, Nerenz DR, Rutt WM, Newcomb CS, Benfer DW. A randomized, controlled trial of an attending staff service in general internal medicine. Med Care. 1991;29(7 suppl):JS31JS40.
  3. Sehgal NL, Shah HM, Parekh , Roy CL, Williams MV. Non‐housestaff medicine services in academic centers: models and challenges. J Hosp Med. 2008;3(3):247255.
  4. Weinberger SE, Smith LG, Collier VU; Education Committee of the American College of Physicians. Redesigning training for internal medicine. Ann Intern Med. 2006;144(12):927932.
  5. Myers JS, Bellini LM, Rohrbach J, Shofer FS, Hollander JE. Improving resource utilization in a teaching hospital: development of a nonteaching service for chest pain admissions. Acad Med. 2006;81(5):432435.
  6. Howell EE, Bessman ES, Rubin HR. Hospitalists and an innovative emergency department admission process. J Gen Intern Med. 2004;19(3):266268.
  7. Khaliq AA, Huang CY, Ganti AK, Invie K, Smego RA. Comparison of resource utilization and clinical outcomes between teaching and nonteaching medical services. J Hosp Med. 2007;2(3):150157.
  8. Palacio C, Alexandraki I, House J, Mooradian AD. A comparative study of unscheduled hospital readmissions in a resident‐staffed teaching service and a hospitalist‐based service. South Med J. 2009;102(2):145149.
  9. Holt SR, Ramos J, Harma MA, et al. Prevalence of unhealthy substance use on teaching and hospitalist medical services: implications for education. Am J Addict. 2012;21(2):111119.
  10. O'Connor AB, Lang VJ, Lurie SJ, et al. The effect of nonteaching services on the distribution of inpatient cases for internal medicine residents. Acad Med. 2009;84(2):220225.
  11. Darves B. Teaching and nonteaching services: separate no more? Today's Hospitalist website. Available at: http://www.todayshospita list.com/index.php?b=articles_read15(9):12771288.
  12. Charlson comorbidity scoring system: estimating prognosis for dialysis patients. Touchcalc website. Available at: http://www.touchcalc.com/calculators/cci_js#t2_probability. Accessed January 15, 2014.
  13. Fitzgerald FT. Curiosity. Ann Intern Med. 1999;130(1):7071.
References
  1. Weinstein DF. Duty hours for resident physicians: tough choices for teaching hospitals. N Engl J Med. 2002;347(16):12751278.
  2. Simmer TL, Nerenz DR, Rutt WM, Newcomb CS, Benfer DW. A randomized, controlled trial of an attending staff service in general internal medicine. Med Care. 1991;29(7 suppl):JS31JS40.
  3. Sehgal NL, Shah HM, Parekh , Roy CL, Williams MV. Non‐housestaff medicine services in academic centers: models and challenges. J Hosp Med. 2008;3(3):247255.
  4. Weinberger SE, Smith LG, Collier VU; Education Committee of the American College of Physicians. Redesigning training for internal medicine. Ann Intern Med. 2006;144(12):927932.
  5. Myers JS, Bellini LM, Rohrbach J, Shofer FS, Hollander JE. Improving resource utilization in a teaching hospital: development of a nonteaching service for chest pain admissions. Acad Med. 2006;81(5):432435.
  6. Howell EE, Bessman ES, Rubin HR. Hospitalists and an innovative emergency department admission process. J Gen Intern Med. 2004;19(3):266268.
  7. Khaliq AA, Huang CY, Ganti AK, Invie K, Smego RA. Comparison of resource utilization and clinical outcomes between teaching and nonteaching medical services. J Hosp Med. 2007;2(3):150157.
  8. Palacio C, Alexandraki I, House J, Mooradian AD. A comparative study of unscheduled hospital readmissions in a resident‐staffed teaching service and a hospitalist‐based service. South Med J. 2009;102(2):145149.
  9. Holt SR, Ramos J, Harma MA, et al. Prevalence of unhealthy substance use on teaching and hospitalist medical services: implications for education. Am J Addict. 2012;21(2):111119.
  10. O'Connor AB, Lang VJ, Lurie SJ, et al. The effect of nonteaching services on the distribution of inpatient cases for internal medicine residents. Acad Med. 2009;84(2):220225.
  11. Darves B. Teaching and nonteaching services: separate no more? Today's Hospitalist website. Available at: http://www.todayshospita list.com/index.php?b=articles_read15(9):12771288.
  12. Charlson comorbidity scoring system: estimating prognosis for dialysis patients. Touchcalc website. Available at: http://www.touchcalc.com/calculators/cci_js#t2_probability. Accessed January 15, 2014.
  13. Fitzgerald FT. Curiosity. Ann Intern Med. 1999;130(1):7071.
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Address for correspondence and reprint requests: Daniel L. Roberts, MD, Division of Hospital Internal Medicine, Mayo Clinic Hospital, 5777 East Mayo Boulevard, Phoenix, AZ 85054; Telephone: 480‐342‐1387; Fax: 480‐342‐1388; E‐mail: roberts.daniel@mayo.edu
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