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Original Investigation |

Emergency Department Resource Use by Supervised Residents vs Attending Physicians Alone FREE

Stephen R. Pitts, MD, MPH1; Sofie R. Morgan, MD, MBA1,2; Justin D. Schrager, MD, MPH1; Todd J. Berger, MD3
[+] Author Affiliations
1Department of Emergency Medicine, Emory University School of Medicine, Atlanta, Georgia
2Emergency Department, St Vincent Infirmary Medical Center, Little Rock, Arkansas
3Emergency Medicine, University of Texas Southwestern Medical School, Austin
JAMA. 2014;312(22):2394-2400. doi:10.1001/jama.2014.16172.
Text Size: A A A
Published online

Importance  Few studies have evaluated the common assumption that graduate medical education is associated with increased resource use.

Objective  To compare resources used in supervised vs attending-only visits in a nationally representative sample of patient visits to US emergency departments (EDs).

Design, Setting, and Participants  Cross-sectional study of the National Hospital Ambulatory Medical Care Survey (2010), a probability sample of US EDs and ED visits.

Exposures  Supervised visits, defined as visits involving both resident and attending physicians. Three ED teaching types were defined by the proportion of sampled visits that were supervised visits: nonteaching ED, minor teaching ED (half or fewer supervised visits), and major teaching ED (more than half supervised visits).

Main Outcomes and Measures  Association of supervised visits with hospital admission, advanced imaging (computed tomography, ultrasound, or magnetic resonance imaging), any blood test, and ED length of stay, adjusted for visit acuity, demographic characteristics, payer type, and geographic region.

Results  Of 29 182 ED visits to the 336 nonpediatric EDs in the sample, 3374 visits were supervised visits. Compared with the 25 808 attending-only visits, supervised visits were significantly associated with more frequent hospital admission (21% vs 14%; adjusted odds ratio [aOR], 1.42; 95% CI, 1.09-1.85), advanced imaging (28% vs 21%; aOR, 1.27; 95% CI, 1.06-1.51), and a longer median ED stay (226 vs 153 minutes; adjusted geometric mean ratio, 1.32; 95% CI, 1.19-1.45), but not with blood testing (53% vs 45%; aOR, 1.18; 95% CI, 0.96-1.46). Of visits to the sample of 121 minor teaching EDs, a weighted estimate of 9% were supervised visits, compared with 82% of visits to the 34 major teaching EDs. Supervised visits in major teaching EDs compared with attending-only visits were not associated with hospital admission (aOR, 1.15; 95% CI, 0.83-1.58), advanced imaging (aOR, 1.21; 95% CI, 0.96-1.53), or any blood test (aOR, 1.02; 95% CI, 0.79-1.33), but had longer ED stays (adjusted geometric mean ratio, 1.32; 95% CI, 1.14-1.53).

Conclusions and Relevance  In a sample of US EDs, supervised visits were associated with a greater likelihood of hospital admission and use of advanced imaging and with longer ED stays. Whether these associations are different in EDs in which more than half of visits are seen by residents requires further investigation.

Figures in this Article

A common assumption is that care at academic medical centers costs more than care at nonteaching hospitals in part because of a higher frequency of testing and other resource use in teaching settings.1,2 Cost consciousness has not been consistently included in Graduate Medical Education (GME) curricula in the past,3 even though there are cost elements in Systems-Based Practice, the last of the 6 general core competencies required by the Accreditation Council for Graduate Medical Education (ACGME) Outcomes Project.4 Cost-effective care is among the “milestones” now used to evaluate emergency medicine residents and accredit emergency medicine residency programs.5 Although there is evidence that resident supervision may improve some patient outcomes,6 few studies of supervised learning have explicitly evaluated resource use as an outcome. This gap in evidence is underscored by the recent focus of health care reform on increasing the value of care.7 To evaluate this question empirically, we hypothesized that attending physicians in the emergency department (ED) would be more likely to use ED resources during a teaching visit with a resident than an ED attending practicing alone. As outcomes, we chose 4 dimensions of ED resource use: hospital admission, advanced imaging, performance of any blood test, and length of stay in the ED.

For this cross-sectional study, we used the 2010 National Hospital Ambulatory Medical Care Survey ED subfile (NHAMCS-ED), a multistage, stratified probability sample of ED visits in the United States administered by the National Center for Health Statistics (NCHS), a branch of the Centers for Disease Control and Prevention. Our data source was the free public-use version of the data, which is available for download on the NCHS website.8 In this survey, race and ethnicity are abstracted from completed ED records by Census field representatives or local ED staff using US Office of Management and Budget categories. Race and ethnicity were included as covariates because of their potential association with ED resource use. The NHAMCS protocol has been approved by the NCHS research ethics review board. Hospital participation is voluntary, and data collection is authorized by section 306 of the Public Health Service Act without prospective patient consent.

During a random 4-week period, the NHAMCS-ED survey abstracts approximately 100 standard patient record forms from existing medical records in selected EDs. Between 350 and 400 EDs are randomly chosen from a primary sampling unit pool of 1900 county-sized population units. Selection probability is determined in part by hospital size and geographic region, with probability weights adjusted accordingly. The sampling strategy aims to create a nationally representative sample of all US nonmilitary EDs and ED visits, which includes both teaching and nonteaching hospitals. More detailed survey methods are available online.8

Although “teaching hospital” status is identified in nonpublic files, this status may include hospitals without resident participation in ED rotations. Instead, we based our analysis on the visit-level public variable RESINT, defined as “seen by a resident or intern,” and ATTPHY, defined as “seen by attending physician.” No further information on the resident’s specialty or ACGME classification was available. Our analysis compared visits with both the RESINT and ATTPHY boxes checked vs visits with only the ATTPHY box checked.

Variable Definitions

As resource use outcomes, we included hospital admission, advanced imaging (computed tomography, magnetic resonance imaging, or ultrasound), performance of any blood test, and ED length of stay. Visit-level covariates chosen a priori included age category, sex, race, ethnicity, payer status (using the NHAMCS algorithm to classify multiple payers), geographic region, and low acuity at triage (“nonurgent” and “semiurgent,” the 2 least acute of 5 categories described in survey documentation). Unlike disease severity (often measured by a variety of physiology-based scores not available in this survey), there is no uniformly accepted ED triage standard in the United States. Triage is related not only to objective disease severity, but also to chief complaint and subjective urgency, typically determined by a nurse on patient presentation. It is also used to enhance throughput efficiency by streaming patients to different parts of the ED. To operationalize this extremely varied practice, the NHAMCS-ED survey maps responses from EDs that use 3- and 4-level systems to the more conventional 5 levels and imputes the 20% of triage categories that are missing.8 A further 6% of visits occur in EDs that do not perform triage: because these have a lower hospital admission rate, these visits were included in the low acuity category.

Urbanicity (ED located in a metropolitan statistical area as defined by the US Office of Management and Budget on the basis of the 1980 Census) may be associated with visit type (supervised vs attending alone) and with the study outcomes; however, it was not included in the models because the number of supervised visits in the nonurban sample was only 23, considered too small for reliable estimation according to the NCHS.9 Additional ED-level variables chosen a priori included safety-net designation (defined as Medicaid >30%, uninsured >30%, or [Medicaid + uninsured] >40% of visits)10; percentage of admissions boarding longer than 2 hours (“boarding” defined as the time between bed request and ED departure for admitted patients); and ED-level proportions of visits identified as non-Hispanic white, non-Hispanic black, Hispanic, Medicare, and age older than 35 years (the median age).

Analogous to the use of hospital inpatient resident-to-bed ratios to quantify the degree of institutional GME involvement and to calculate the Medicare Indirect Medical Education subsidy,11 we classified EDs by teaching intensity using the ratio of supervised visits to attending-only visits in the visit sample for each ED. The distribution of EDs according to the proportion of visits seen by residents was bimodal, supporting the validity of this approach to classifying teaching intensity (Figure). However, there have been no previous studies confirming the reproducibility and accuracy of the NHAMCS-ED provider checkboxes. Because the nadir of this distribution occurred at about 50% of visits seen by residents, we created 3 categories of ED teaching type: no trainees for any visits (“nonteaching” EDs, 53% of sample EDs), trainees involved in half or fewer visits (“minor teaching” EDs, 36% of sample EDs), and trainees involved in more than half of visits (“major teaching” EDs, 10% of sample EDs). Sample sizes and visit counts for these 3 ED teaching types are shown in Table 1.

Place holder to copy figure label and caption
Figure.
Distribution of Emergency Departments by Proportion of Sampled Visits Seen by Residents

Distribution of supervised visit rates only in the 73 sampled emergency departments (EDs) that had 10% or more supervised visits, excluding the 263 EDs with fewer than 10% of sampled supervised visits, illustrating the bimodal character of this distribution. The histogram plots proportions beginning with 0.1 or greater, in bins of width 0.1.

Graphic Jump Location
Table Graphic Jump LocationTable 1.  Distribution of ED and Visit Counts in the 2010 NHAMCS Survey, by ED Teaching Type

Although the identity of individual EDs is masked to avoid disclosure, since 2005 the survey has included a hospital identifier code and a hospital-level probability weight that enables national ED-level estimation. Because these identifiers are reassigned each year, it is not possible to aggregate individual EDs from year to year. Thus, we limited our analysis to 2010, the most recent survey year available. We defined pediatric EDs as any ED with a mean sample age younger than 20 years. We excluded these EDs because of the low rate of testing and admission but included children seen in general hospitals. For the analyses comparing supervised visits to attending-only visits, we also excluded visits seen by a resident with no documented attending presence and visits with no clinician type recorded or visits seen only by consultants or midlevel practitioners.

Statistical Analysis

For the 3 binary outcomes (hospital admission, advanced imaging, and any blood test), we used logistic regression to measure association. For length of stay, we used linear regression on the log-transformed values, because length of stay is a right-skewed continuous variable. The exponentiated regression parameter is interpreted as the geometric mean length of stay. We generated 2 visit-level models incorporating ED teaching type: a model with the supervised visit as the main exposure and a model with ED teaching type as the main exposure. For bivariate ED-level analyses, we used ED-level probability weights and design variables provided in the NHAMCS public-use file. All statistical analyses were conducted with Stata version 13 (StataCorp), using the SVY suite of programs for complex analysis when appropriate. Significance testing was 2-sided, and the significance threshold was set at P < .05.

Of 388 eligible EDs in the sample, 357 (92%) provided usable data. Of these, 350 remained after a masking process to minimize the risk of disclosure of hospital identity.8 The 2010 NHAMCS survey included 34 936 patient visit records, with 29 182 records remaining after excluding pediatric specialty EDs and visits with no attending physician. The 336 nonpediatric EDs in the sample contributed a mean of 103 patient record forms (interquartile range, 88-114). Table 1 shows the distribution of excluded and included participants in the study sample, by ED teaching type.

Comparison of Supervised and Nonsupervised ED Visits

Among the covariates examined, supervised visits were associated independently with male sex, non-Hispanic black race, Hispanic ethnicity, uninsured payer status, higher acuity, and Northeast geographic region (Table 2). There was a significant unadjusted difference in urbanicity between attending-only encounters (21 731/25 808 visits) and supervised encounters (3351/3374 visits; weighted percentages, 80% vs 99%; odds ratio [OR], 17.5; 95% CI, 3.63-84.0). In unadjusted analysis, supervised visits were significantly more likely to result in hospital admission, the use of advanced imaging, any blood test, and longer ED length of stay when compared with ED visits managed by an attending physician alone (Table 2). This association was attenuated but remained positive for each resource use except performance of any blood test after adjusting for patient age, sex, race/ethnicity, payer status, low triage acuity, and geographic region (Table 2).

Table Graphic Jump LocationTable 2.  Associations Between Teaching Visits and Resource Use, 2010 US Emergency Departmentsa
Analysis by ED Teaching Intensity

Table 1 shows that ED visit volume was higher in EDs with greater resident involvement. Major teaching EDs had on average 3 times as many annual visits (61 522) as nonteaching EDs (21 029). There were significant differences in unadjusted rates between each ED teaching type for all 4 of the resource use categories and for sex, race/ethnicity, low acuity at triage, and geographic region (eTable 1 in the Supplement).

Although only an estimated 9% of visits to minor teaching EDs were supervised visits, they accounted for 38% of all supervised visits because minor teaching EDs are more numerous than major teaching EDs (Table 1). Supervised visits in major teaching EDs (82% of visits) were not significantly associated with increased resource use except for a longer ED stay (Table 3). Minor teaching EDs statistically accounted for most of the overall association for the remaining 3 resources: hospital admission, advanced imaging, and blood testing (Table 3). For example, the adjusted odds ratio (aOR) for hospitalization for teaching visits in minor ED teaching types to all nonteaching visits was 1.97 (95% CI, 1.36-2.86) compared with 1.15 (95% CI, 0.83-1.58) for major ED teaching types. The difference in adjusted resource use between supervised visits at minor and major ED teaching types varied significantly for hospital admission and blood testing, but not for advanced imaging and length of stay (Table 3).

Table Graphic Jump LocationTable 3.  Association of ED Resource Use With Supervised Visits (Model 1) and With ED Teaching Type (Model 2), With the Visit as Unit of Analysis, United States, 2010a

Using ED teaching type as the main exposure, rather than the supervised visit, there were statistically significant unadjusted associations between ED teaching type and each of the resource use variables, as well as with race/ethnicity and low acuity visits, but not with age, sex, payer type, or geographic region (eTable 2 in the Supplement). When resource use was adjusted for each of these covariates, the associations remained significant between minor ED teaching types and each of the resource use variables, compared with nonteaching EDs. Major ED teaching types were not associated with higher adjusted resource use compared with nonteaching EDs, except for length of stay (Table 3). However, the difference between minor and major ED teaching types was statistically significant only for blood testing. For example, the aOR for hospitalization was 1.50 (95% CI, 1.19-1.89) for minor teaching EDs and 1.35 (95% CI, 0.97-1.89) for major teaching EDs, both compared with nonteaching EDs (P = .51 for difference between minor and major teaching EDs).

To determine whether the association of supervised visits with resource use in minor teaching EDs could be attributed to the practice style of minor teaching EDs, rather than being a characteristic of teaching visits, we compared supervised with attending-only visits within the subgroup of minor teaching EDs. Resource use was higher among supervised visits for hospital admission (aOR, 1.67; 95% CI, 1.14-2.43), advanced imaging (aOR, 1.32; 95% CI, 1.01-1.71), any blood test (aOR, 1.40; 95% CI, 1.02-1.92), and length of stay (adjusted geometric mean ratio, 1.18; 95% CI, 1.05-1.32).

ED-Level Analysis

Although statistical power was lower when the ED was the unit of analysis, there were significant differences in bivariate comparisons between the 3 ED teaching types for 2 of the 4 resource use variables (hospital admission and advanced imaging), the proportion of low acuity visits, separately for non-Hispanic white and non-Hispanic black visit composition, and for the Northeast region. There were no significant differences for the mean rate of boarding, median age older than 35 years, safety-net designation, and Medicare or Hispanic visit composition (Table 4).

Table Graphic Jump LocationTable 4.  Association of ED Resource Use With ED Teaching Type Using the ED as Unit of Analysisa

Although formal programs to teach cost awareness are being developed,12 observation in real-life clinical contexts influences learning more than written tests or objective structured clinical examinations.13 Previous studies of actual ED resource use in teaching settings have been limited to single hospitals.14,15 In our study of a nationally representative sample of ED visits, we hypothesized that supervised visits would consume more resources than nonsupervised visits, reasoning that supervised learning favors a more deliberate, reflective decision-making style than nonteaching clinical visits. We confirmed consistently higher use of several ED resources among supervised visits, even after adjustment for several other possible determinants of resource use that were available in the survey.

Our secondary goal of comparing supervised visits between minor and major teaching EDs revealed weaker associations between resource use and supervised visits in major teaching EDs, although these estimates were also less precise due to a smaller sample size. Some ED characteristics undisclosed by the survey might explain this difference. Many major teaching EDs are in public hospitals with relatively limited capacity compared with demand and thus longer queues for fixed resources such as treatment spaces, inpatient beds, and laboratory and imaging capacity.16 A feature of minor teaching EDs is the ability to select “teaching cases” from among a larger pool of visits, while residents see virtually all patients in major teaching EDs. Although we adjusted for biased selection statistically, residual confounding by complexity not captured by the survey could account for some of the apparent higher resource use by teaching cases in minor teaching EDs. Supervised learning could encourage inefficient throughput, but the longer visits for major teaching EDs may also reflect an underresourced public hospital setting or decreased operational efficiency due to an independent effect of larger ED volume,17 both questions for future research. Because the 155 ACGME-accredited emergency medicine residency programs in 2010 involved 3.6 separate hospitals per program on average, it is likely that most emergency medicine residents are exposed to both ED teaching types during their training.18 However, our data source did not distinguish between emergency medicine and other residents on an ED rotation.

We did not evaluate the cost of medical education. Instead we studied the potential relationship between GME and the practice style of new physicians. Many of the excess costs of academic medical centers19 occur after the first-contact care provided by ED residents, such as long inpatient stays or subspecialty referral. Academic medical center hospital EDs are often staffed mainly by faculty physicians rather than residents and are thus defined as minor teaching EDs in our analysis. This does not decrease the relevance of ED supervision to national delivery system reform: emergency physicians nationwide now initiate more than half of all hospitalizations20 and 80% of unscheduled hospitalizations21 and manage a more diverse set of clinical problems than any other specialty, with a disproportionate share of the sickest patients.22

Our analysis differs from previous studies of the economics of medical training in several ways. We used a nationally representative all-payer sample; therefore, these secondary data may be the best available evidence to inform national GME policy. Our approach used visit-level rather than aggregated data, thus allowing adjustment for other determinants of resource use without ecologic bias. We also studied the use of resources rather than dollars as an outcome, reducing biases due to geographic and temporal variation in price or cost.23 Rather than rely on voluntary membership in the Council of Teaching Hospitals and Health Systems, we defined supervised visits directly.

Our study is also limited in a number of ways. First, as with other national surveys of clinical visits, inaccurate documentation of the visit in clinical records and incorrect abstraction to patient record forms from these clinical records are both possible. Second, small cell size precluded adjusting for urbanicity because of lack of reliability; however, there was a major difference in urbanicity in supervised vs attending-only encounters, so that this variable may have confounded our observed associations. Third, the adjustment for acuity depended on triage, which is not a uniform function across EDs.8 However, diagnosis-based schemes also cannot define acuity.24 Fourth, cross-sectional design precludes causal inference; therefore, our findings must be viewed as hypothesis-generating. Fifth, because of data restrictions, we were not able to include important ED-level detail such as ED size or visit volume, nor other information likely to be important in explaining resource use, such as characteristics of the supervisor (eg, board certification), trainee (eg, specialty), and institution (eg, whether a hospital had an emergency medicine residency training program). Sixth, we used the most recent publicly available survey results, but data from 2010 may not reflect resource use patterns in 2014. Seventh, in ED-level analyses, significance tests did not account for sampling error at the visit level, so P values (for example, in Table 4) may not be sufficiently conservative.

In a sample of US EDs, supervised visits were associated with a greater likelihood of hospital admission and use of advanced imaging and with longer ED stays. Whether these associations are different in EDs in which more than half of visits are seen by residents requires further investigation.

Corresponding Author: Stephen R. Pitts, MD, MPH, Department of Emergency Medicine, Emory University School of Medicine, 531 Asbury Circle, Annex Ste N340, Atlanta, GA 30322 (srpitts@emory.edu).

Author Contributions: Dr Pitts had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Pitts, Morgan, Schrager, Berger.

Acquisition, analysis, or interpretation of data: Pitts, Morgan, Schrager, Berger.

Drafting of the manuscript: Pitts, Morgan, Berger.

Critical revision of the manuscript for important intellectual content: Pitts, Morgan, Schrager, Berger.

Statistical analysis: Pitts, Schrager.

Administrative, technical, or material support: Pitts, Morgan.

Study supervision: Pitts, Berger.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. For a period during the study’s inception, Dr Pitts received partial salary support through a contract with the Emergency Care Coordination Center of the US Department of Health and Human Services. Dr Schrager is currently a resident in the Emory University Emergency Medicine residency. Dr Berger is the program director for the University of Texas Southwestern Medical School Emergency Medicine residency in Austin. No other disclosures were reported.

Hackbarth  G, Boccuti  C.  Transforming graduate medical education to improve health care value. N Engl J Med. 2011;364(8):693-695.
PubMed   |  Link to Article
Goodman  DC, Robertson  RG.  Accelerating physician workforce transformation through competitive graduate medical education funding. Health Aff (Millwood). 2013;32(11):1887-1892.
PubMed   |  Link to Article
Cooke  M.  Cost consciousness in patient care: what is medical education’s responsibility? N Engl J Med. 2010;362(14):1253-1255.
PubMed   |  Link to Article
Dyne  PL, Strauss  RW, Rinnert  S.  Systems-based practice: the sixth core competency. Acad Emerg Med. 2002;9(11):1270-1277.
PubMed   |  Link to Article
The emergency medicine milestone project. Accreditation Council for Graduate Medical Education and the American Board of Emergency Medicine. https://www.acgme.org/acgmeweb/Portals/0/PDFs/Milestones/EmergencyMedicineMilestones.pdf. Accessed September 20, 2014.
Farnan  JM, Petty  LA, Georgitis  E,  et al.  A systematic review: the effect of clinical supervision on patient and residency education outcomes. Acad Med. 2012;87(4):428-442.
PubMed   |  Link to Article
Marcotte  L, Moriates  C, Milstein  A.  Professional organizations’ role in supporting physicians to improve value in health care. JAMA. 2014;312(3):231-232.
PubMed   |  Link to Article
2010 NHAMCS micro-data file documentation. National Center for Health Statistics. ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHAMCS/doc2010.pdf. Accessed May 29, 2014.
Reliability of estimates. National Center for Health Statistics ambulatory healthcare data. http://www.cdc.gov/nchs/ahcd/ahcd_estimation_reliability.htm. Accessed November 5, 2014.
Burt  CW, Arispe  IE.  Characteristics of emergency departments serving high volumes of safety-net patients: United States, 2000. Vital Health Stat 13. 2004;(155):1-16.
PubMed
Ayanian  JZ, Weissman  JS.  Teaching hospitals and quality of care: a review of the literature. Milbank Q. 2002;80(3):569-593, v.
PubMed   |  Link to Article
Smith  CD; Alliance for Academic Internal Medicine–American College of Physicians High Value; Cost-Conscious Care Curriculum Development Committee.  Teaching high-value, cost-conscious care to residents: the Alliance for Academic Internal Medicine–American College of Physicians Curriculum. Ann Intern Med. 2012;157(4):284-286.
PubMed
Hodges  BD, Kuper  A.  Theory and practice in the design and conduct of graduate medical education. Acad Med. 2012;87(1):25-33.
PubMed   |  Link to Article
McNamara  RM, Kelly  JJ.  Cost of care in the emergency department: impact of an emergency medicine residency program. Ann Emerg Med. 1992;21(8):956-962.
PubMed   |  Link to Article
Scholer  SJ, Pituch  K, Orr  DP, Clark  D, Dittus  RS.  Effect of health care system factors on test ordering. Arch Pediatr Adolesc Med. 1996;150(11):1154-1159.
PubMed   |  Link to Article
Zaman  OS, Cummings  LC, Laycox  S. America’s safety net hospitals and health systems, 2010. http://essentialhospitals.org/wp-content/uploads/2013/12/NPH214.pdf. Accessed May 29, 2014.
Pitts  SR, Vaughns  FL, Gautreau  MA, Cogdell  MW, Meisel  Z.  A cross-sectional study of emergency department boarding practices in the United States. Acad Emerg Med. 2014;21(5):497-503.
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Data Resource Book, Academic Year 2009-2010. Accreditation Council for Graduate Medical Education. http://www.acgme.org/acgmeweb/Portals/0/PFAssets/PublicationsBooks/2009-2010_ACGME_DATA_RESOURCE_BOOK.pdf. Accessed May 29, 2014.
Newhouse  JP.  Accounting for teaching hospitals’ higher costs and what to do about them. Health Aff (Millwood). 2003;22(6):126-129.
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Morganti  KG, Bauhoff  S, Blanchard  JC,  et al. The evolving role of emergency departments in the United States. RAND research reports. http://www.rand.org/pubs/research_reports/RR280.html. Accessed May 29, 2014.
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Pitts  SR, Carrier  ER, Rich  EC, Kellermann  AL.  Where Americans get acute care: increasingly, it’s not at their doctor’s office. Health Aff (Millwood). 2010;29(9):1620-1629.
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Brunetti  M, Shemilt  I, Pregno  S,  et al.  GRADE guidelines: 10, Considering resource use and rating the quality of economic evidence. J Clin Epidemiol. 2013;66(2):140-150.
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Raven  MC, Lowe  RA, Maselli  J, Hsia  RY.  Comparison of presenting complaint vs discharge diagnosis for identifying ” nonemergency” emergency department visits. JAMA. 2013;309(11):1145-1153.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure.
Distribution of Emergency Departments by Proportion of Sampled Visits Seen by Residents

Distribution of supervised visit rates only in the 73 sampled emergency departments (EDs) that had 10% or more supervised visits, excluding the 263 EDs with fewer than 10% of sampled supervised visits, illustrating the bimodal character of this distribution. The histogram plots proportions beginning with 0.1 or greater, in bins of width 0.1.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 4.  Association of ED Resource Use With ED Teaching Type Using the ED as Unit of Analysisa
Table Graphic Jump LocationTable 3.  Association of ED Resource Use With Supervised Visits (Model 1) and With ED Teaching Type (Model 2), With the Visit as Unit of Analysis, United States, 2010a
Table Graphic Jump LocationTable 2.  Associations Between Teaching Visits and Resource Use, 2010 US Emergency Departmentsa
Table Graphic Jump LocationTable 1.  Distribution of ED and Visit Counts in the 2010 NHAMCS Survey, by ED Teaching Type

References

Hackbarth  G, Boccuti  C.  Transforming graduate medical education to improve health care value. N Engl J Med. 2011;364(8):693-695.
PubMed   |  Link to Article
Goodman  DC, Robertson  RG.  Accelerating physician workforce transformation through competitive graduate medical education funding. Health Aff (Millwood). 2013;32(11):1887-1892.
PubMed   |  Link to Article
Cooke  M.  Cost consciousness in patient care: what is medical education’s responsibility? N Engl J Med. 2010;362(14):1253-1255.
PubMed   |  Link to Article
Dyne  PL, Strauss  RW, Rinnert  S.  Systems-based practice: the sixth core competency. Acad Emerg Med. 2002;9(11):1270-1277.
PubMed   |  Link to Article
The emergency medicine milestone project. Accreditation Council for Graduate Medical Education and the American Board of Emergency Medicine. https://www.acgme.org/acgmeweb/Portals/0/PDFs/Milestones/EmergencyMedicineMilestones.pdf. Accessed September 20, 2014.
Farnan  JM, Petty  LA, Georgitis  E,  et al.  A systematic review: the effect of clinical supervision on patient and residency education outcomes. Acad Med. 2012;87(4):428-442.
PubMed   |  Link to Article
Marcotte  L, Moriates  C, Milstein  A.  Professional organizations’ role in supporting physicians to improve value in health care. JAMA. 2014;312(3):231-232.
PubMed   |  Link to Article
2010 NHAMCS micro-data file documentation. National Center for Health Statistics. ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHAMCS/doc2010.pdf. Accessed May 29, 2014.
Reliability of estimates. National Center for Health Statistics ambulatory healthcare data. http://www.cdc.gov/nchs/ahcd/ahcd_estimation_reliability.htm. Accessed November 5, 2014.
Burt  CW, Arispe  IE.  Characteristics of emergency departments serving high volumes of safety-net patients: United States, 2000. Vital Health Stat 13. 2004;(155):1-16.
PubMed
Ayanian  JZ, Weissman  JS.  Teaching hospitals and quality of care: a review of the literature. Milbank Q. 2002;80(3):569-593, v.
PubMed   |  Link to Article
Smith  CD; Alliance for Academic Internal Medicine–American College of Physicians High Value; Cost-Conscious Care Curriculum Development Committee.  Teaching high-value, cost-conscious care to residents: the Alliance for Academic Internal Medicine–American College of Physicians Curriculum. Ann Intern Med. 2012;157(4):284-286.
PubMed
Hodges  BD, Kuper  A.  Theory and practice in the design and conduct of graduate medical education. Acad Med. 2012;87(1):25-33.
PubMed   |  Link to Article
McNamara  RM, Kelly  JJ.  Cost of care in the emergency department: impact of an emergency medicine residency program. Ann Emerg Med. 1992;21(8):956-962.
PubMed   |  Link to Article
Scholer  SJ, Pituch  K, Orr  DP, Clark  D, Dittus  RS.  Effect of health care system factors on test ordering. Arch Pediatr Adolesc Med. 1996;150(11):1154-1159.
PubMed   |  Link to Article
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eTable 1. Association of ED teaching type with resource use variables and covariates, excluding pediatric specialty EDs and visits with no attending physician, United States, 2010

eTable 2. Association of ED teaching type with resource use variables and covariates, excluding pediatric specialty hospitals but including visits with no ED attending, United States, 2010

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