Figure 1.  Hospital-Level Probability of Receiving at Least 1 Medical Consultation

A, Hospital-level probability of colectomy patients receiving at least 1 medical consultation. Hospitals are ranked along the x-axis according to their estimated probability of having at least 1 medical visit for colectomy patients. Each point of the black line represents the estimated probability for 1 hospital. The gray area above and below each point represents the 95% CI around the estimate for each hospital. B, Hospital-level probability of total hip replacement (THR) patients receiving at least 1 medical consultation. Hospitals are ranked along the x-axis according to their estimated probability of having at least 1 medical consultation for total hip replacement patients. Each point of the black line represents the estimated probability for 1 hospital. The gray area above and below each point represents the 95% CI around the estimate for each hospital.

Figure 2.  Hospital-Level Probability of Receiving at Least 1 Medical Consultation, Stratified by Complications

A, Hospital-level probability of colectomy patients receiving at least 1 medical consultation, stratified by complications. The lower and upper borders of each box indicate the 25th and 75th percentiles, respectively. The middle line of each box indicates the median, and the diamond indicates the mean. The ends of the whiskers represent 1.5 × interquartile range, and the circles (when present) represent outliers. B, Hospital-level probability of total hip replacement (THR) patients receiving at least 1 medical consultation, stratified by complications. The lower and upper borders of each box indicate the 25th and 75th percentiles, respectively. The middle line of each box indicates the median, and the diamond indicates the mean. The ends of the whiskers represent 1.5 × interquartile range, and the circles (when present) represent outliers.

Table 1.  Proportion of Surgical Patientsa Receiving Medical Consultations, by Procedure and Consultation Type
Table 2.  Factors Associated With Ordering at Least 1 Medical Consultation, Adjusteda
1.
Miller  DC, Gust  C, Dimick  JB, Birkmeyer  N, Skinner  J, Birkmeyer  JD.  Large variations in Medicare payments for surgery highlight savings potential from bundled payment programs.  Health Aff (Millwood). 2011;30(11):2107-2115.PubMedGoogle ScholarCrossref
2.
Birkmeyer  JD, Gust  C, Baser  O, Dimick  JB, Sutherland  JM, Skinner  JS.  Medicare payments for common inpatient procedures: implications for episode-based payment bundling.  Health Serv Res. 2010;45(6 Pt 1):1783-1795.PubMedGoogle ScholarCrossref
3.
Sharma  G, Kuo  YF, Freeman  J, Zhang  DD, Goodwin  JS.  Comanagement of hospitalized surgical patients by medicine physicians in the United States.  Arch Intern Med. 2010;170(4):363-368.PubMedGoogle ScholarCrossref
4.
AHA Annual Survey Database Fiscal Year 2007 [CD-ROM]. Chicago, IL: American Hospital Association; 2008.
5.
Centers for Medicare & Medicaid Services. Medicare acute care episode demonstration for orthopedic and cardiovascular surgery. http://www.cms.gov/Medicare/Demonstration-Projects/DemoProjectsEvalRpts/Downloads/ACE_web_page.pdf. Accessed September 8, 2012.
6.
Breslin  TM, Morris  AM, Gu  N,  et al.  Hospital factors and racial disparities in mortality after surgery for breast and colon cancer.  J Clin Oncol. 2009;27(24):3945-3950.PubMedGoogle ScholarCrossref
7.
Iezzoni  LI, Daley  J, Heeren  T,  et al.  Identifying complications of care using administrative data.  Med Care. 1994;32(7):700-715.PubMedGoogle ScholarCrossref
8.
Weingart  SN, Iezzoni  LI, Davis  RB,  et al.  Use of administrative data to find substandard care: validation of the complications screening program.  Med Care. 2000;38(8):796-806.PubMedGoogle ScholarCrossref
9.
Kleinman  LC, Norton  EC.  What’s the risk? a simple approach for estimating adjusted risk measures from nonlinear models including logistic regression.  Health Serv Res. 2009;44(1):288-302.PubMedGoogle ScholarCrossref
10.
Goldman  L, Lee  T, Rudd  P.  Ten commandments for effective consultations.  Arch Intern Med. 1983;143(9):1753-1755.PubMedGoogle ScholarCrossref
11.
Chopra  V, Flanders  SA, Froehlich  JB, Lau  WC, Eagle  KA.  Perioperative practice: time to throttle back.  Ann Intern Med. 2010;152(1):47-51.PubMedGoogle ScholarCrossref
12.
Ford  MK, Beattie  WS, Wijeysundera  DN.  Systematic review: prediction of perioperative cardiac complications and mortality by the revised cardiac risk index.  Ann Intern Med. 2010;152(1):26-35.PubMedGoogle ScholarCrossref
13.
Wijeysundera  DN, Beattie  WS, Austin  PC, Hux  JE, Laupacis  A.  Non-invasive cardiac stress testing before elective major non-cardiac surgery: population based cohort study.  BMJ. 2010;340:b5526.PubMedGoogle ScholarCrossref
14.
Lee  TH, Marcantonio  ER, Mangione  CM,  et al.  Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery.  Circulation. 1999;100(10):1043-1049.PubMedGoogle ScholarCrossref
15.
Cohn  SL, Smetana  GW.  Update in perioperative medicine.  Ann Intern Med. 2007;147(4):263-270.PubMedGoogle ScholarCrossref
16.
Auerbach  AD, Rasic  MA, Sehgal  N, Ide  B, Stone  B, Maselli  J.  Opportunity missed: medical consultation, resource use, and quality of care of patients undergoing major surgery.  Arch Intern Med. 2007;167(21):2338-2344.PubMedGoogle ScholarCrossref
17.
Huddleston  JM, Long  KH, Naessens  JM,  et al; Hospitalist-Orthopedic Team Trial Investigators.  Medical and surgical comanagement after elective hip and knee arthroplasty: a randomized, controlled trial.  Ann Intern Med. 2004;141(1):28-38.PubMedGoogle ScholarCrossref
18.
Wijeysundera  DN, Austin  PC, Beattie  WS, Hux  JE, Laupacis  A.  Outcomes and processes of care related to preoperative medical consultation.  Arch Intern Med. 2010;170(15):1365-1374.PubMedGoogle ScholarCrossref
19.
Wijeysundera  DN, Austin  PC, Beattie  WS, Hux  JE, Laupacis  A.  Variation in the practice of preoperative medical consultation for major elective noncardiac surgery: a population-based study.  Anesthesiology. 2012;116(1):25-34.PubMedGoogle ScholarCrossref
20.
Ghaferi  AA, Birkmeyer  JD, Dimick  JB.  Variation in hospital mortality associated with inpatient surgery.  N Engl J Med. 2009;361(14):1368-1375.PubMedGoogle ScholarCrossref
21.
Chung  KC, Shauver  MJ, Yin  H, Kim  HM, Baser  O, Birkmeyer  JD.  Variations in the use of internal fixation for distal radial fracture in the United States Medicare population.  J Bone Joint Surg Am. 2011;93(23):2154-2162.PubMedGoogle ScholarCrossref
22.
Haymart  MR, Banerjee  M, Stewart  AK, Koenig  RJ, Birkmeyer  JD, Griggs  JJ.  Use of radioactive iodine for thyroid cancer.  JAMA. 2011;306(7):721-728.PubMedGoogle ScholarCrossref
23.
Lin  GA, Dudley  RA, Lucas  FL, Malenka  DJ, Vittinghoff  E, Redberg  RF.  Frequency of stress testing to document ischemia prior to elective percutaneous coronary intervention.  JAMA. 2008;300(15):1765-1773.PubMedGoogle ScholarCrossref
24.
Pichardo-Lowden  A, Gabbay  RA.  Management of hyperglycemia during the perioperative period.  Curr Diab Rep. 2012;12(1):108-118.PubMedGoogle ScholarCrossref
Views 6,334
• Cite This

### Citation

Chen LM, Wilk AS, Thumma JR, Birkmeyer JD, Banerjee M. Use of Medical Consultants for Hospitalized Surgical Patients: An Observational Cohort Study. JAMA Intern Med. 2014;174(9):1470–1477. doi:10.1001/jamainternmed.2014.3376

Original Investigation
September 2014

# Use of Medical Consultants for Hospitalized Surgical Patients: An Observational Cohort Study

Author Affiliations
• 1Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
• 2VA Ann Arbor Healthcare System, Ann Arbor, Michigan
• 3Center for Healthcare Outcomes & Policy, University of Michigan, Ann Arbor
• 4Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
• 5Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor
• 6VA Center for Clinical Management Research, Ann Arbor, Michigan
• 7Department of Surgery, University of Michigan, Ann Arbor
• 8Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor
JAMA Intern Med. 2014;174(9):1470-1477. doi:10.1001/jamainternmed.2014.3376
Abstract

Importance  Payments around episodes of inpatient surgery vary widely among hospitals. As payers move toward bundled payments, understanding sources of variation, including use of medical consultants, is important.

Objective  To describe the use of medical consultations for hospitalized surgical patients, factors associated with use, and practice variation across hospitals.

Design, Setting, and Participants  Observational retrospective cohort study of fee-for-service Medicare patients undergoing colectomy or total hip replacement (THR) between January 1, 2007, and December 31, 2010, at US acute care hospitals.

Main Outcomes and Measures  Number of inpatient medical consultations.

Results  More than half of patients undergoing colectomy (91 684) or THR (339 319) received at least 1 medical consultation while hospitalized (69% and 63%, respectively). Median consultant visits from a medicine physician were 9 (interquartile range [IQR], 4-19) for colectomy and 3 for THR (IQR, 2-5). The likelihood of having at least 1 medical consultation varied widely among hospitals (interquartile range [IQR], 50%-91% for colectomy and 36%-90% for THR). For colectomy, settings associated with greater use included nonteaching (adjusted risk ratio [ARR], 1.14 [95% CI, 1.04-1.26]) and for-profit (ARR, 1.10 [95% CI, 1.01-1.20]). Variation in use of medical consultations was greater for colectomy patients without complications (IQR, 47%-79%) compared with those with complications (IQR, 90%-95%). Results stratified by complications were similar for THR.

Conclusions and Relevance  The use of medical consultations varied widely across hospitals, particularly for surgical patients without complications. Understanding the value of medical consultations will be important as hospitals prepare for bundled payments and strive to enhance efficiency.

Introduction

As the Centers for Medicare & Medicaid Services (CMS) and others move to bundled payments around longitudinal episodes of care, hospitals are facing a greater need to understand practice variation and areas of excess resource use within episodes of care. In the case of inpatient surgery, for example, one recent study suggests that episode-based payments for surgery vary as much as 10% to 40% after adjusting for case mix and price.1 For some procedures, variation in episode-based payments is driven by multiple factors, including readmissions, use of home health, skilled nursing services, and other components of postdischarge care.1,2

Another source of variation is the use of professional services, including the use of medical consultants. Internists and medical subspecialists are frequently called on to provide preoperative assessments of risk and to provide advice on how to reduce these risks. Medical consultants may also be employed for more routine comanagement, caring for surgical patients’ chronic medical conditions such as diabetes and hypertension for the duration of the hospital stay. Finally, medical consultants often assist in the care of patients with certain complications after surgery, including acute kidney injury, surgical site infections, and postoperative myocardial infarction.

Although prior work suggests a long-term trend toward increased use of medical consultants for comanagement of surgical patients,3 variation in the use of consultations for hospitalized surgical patients has not been studied carefully. In this context, we used national Medicare data to explore the use of medical consultations around inpatient surgery, factors associated with increased use, and variation in practice patterns across hospitals.

Methods

This study is part of a larger project that was reviewed by the institutional review board of the University of Michigan, which found this study to be exempt from its oversight.

Data Sources and Study Population

To identify inpatient medical visits, we used the Medicare Provider Analysis and Review (MedPAR) File and the Carrier File (100% for our cohort). We also used the American Hospital Association (AHA) Annual Survey 2007 to identify hospital characteristics.4

From these complete Medicare claims data, we created a cohort of elderly fee-for-service Medicare beneficiaries who underwent colectomy or total hip replacement (THR) at a nonfederal hospital from January 2007 to December 2010. We chose to examine these 2 procedures because they are among the top 10 principal surgical procedures performed on Medicare patients. Colectomy is also performed on patients likely to have multiple medical comorbidities that may be managed with or without a medical consultant. Total hip replacement is one of the procedures included in CMS’ bundled payment demonstration project.5

We used procedure codes from the International Classification of Diseases, Ninth Revision (ICD-9) to define colectomy (procedure codes 45.73-45.76, 45.79, and 45.81-45.83) and THR (procedure code 81.51), identifying 497 655 colectomy patients and 567 646 THR patients. We excluded patients admitted to facilities other than general acute care hospitals for these index procedures and those admitted to hospitals we could not link to AHA data. We also excluded patients not enrolled in Medicare fee-for-service Parts A and B for the duration of their hospitalizations and patients younger than 65 years or older than 99 years at the time of their procedure.

To increase the clinical homogeneity of our samples, we applied several additional exclusion criteria. We excluded colectomy patients with no cancer diagnosis (ie, diagnosis codes 153.0-153.9 and 154.0) and THR patients with a hip fracture diagnosis (ie, diagnosis codes 820.0-820.3, 820.8, and 820.9). Finally, we excluded patients whose inpatient stays spanned 2 calendar years because we did not have complete claims data for these patients (2975 patients for colectomy and 1752 patients for THR).

To increase the reliability of our estimates and because hospitals varied widely in the number of procedures performed during the study period (ie, range of 1-446 for colectomy and 1-5084 for THR), we also excluded patients if their hospitals had fewer than 10 cases in any year during our study period. Similar exclusion criteria have been chosen in prior studies to reduce statistical artifact.6 During the study period, 2186 hospitals with 48 306 patients performed fewer than 10 colectomies per year and 1321 hospitals with 32 434 patients performed fewer than 10 THRs per year. After applying all exclusion criteria, our final analytic samples included 91 684 patients who underwent colectomy at 930 hospitals and 339 319 patients who underwent THR at 1589 hospitals.

Characterizations of Medical Consultations

Our primary outcome was having at least 1 inpatient medical consultation at any time during hospitalization for colectomy or THR. We defined inpatient consultations using Current Procedural Terminology (CPT) codes (99221-99223, 99291-99292, 99251-99255, and 99231-99233). In most cases, these codes do not allow us to distinguish between an attending vs consulting medicine physician. In defining inpatient consultations for our cohort, we included all of these codes because clinical practice and Medicare coding regulations make little distinction between care for a surgical inpatient that is provided by an attending vs consulting medicine physician. We included consultations that had been performed by health care providers in general medicine (general practice, family practice, internal medicine, or geriatric medicine), oncology (medical oncology or hematology oncology), cardiology, endocrinology, gastroenterology, infectious disease, nephrology, physical medicine and rehabilitation, pulmonary disease and/or critical care, or other medical subspecialties (allergy and immunology, dermatology, hematology, neurology, pain management, or rheumatology).

Using a previously validated methodology,7,8 we defined 8 common postoperative, inpatient surgical complications with ICD-9 diagnosis and procedure codes (see eAppendix in the Supplement). These postoperative complications included pulmonary failure, pneumonia, myocardial infarction, deep venous thrombosis and pulmonary embolism, acute renal failure, hemorrhage, surgical site infection, and gastrointestinal tract hemorrhage.

Statistical Analyses

We first characterized the types of consultations ordered for patients undergoing colectomy or THR. For each specialty type, we identified the proportion of patients with at least 1 consultation and the median number of visits observed when at least 1 consultation had been ordered. We also described the proportion of patients who received medical comanagement (using the previously validated definition of 70% or more of inpatient days with an evaluation and management claim from a medicine physician).3

Hierarchical logistic regression analyses were used to identify patient and hospital factors associated with ordering at least 1 perioperative medical consultation (binary outcome). Specifically, we used generalized linear mixed model (GLMMIX) with logit link to account for the clustering of patients within hospitals while assessing the effect of patient characteristics (sex, age group, race, number of comorbidities, elective admission type) and hospital characteristics (hospital beds [≥500, 350-499, 200-349, <200]; teaching [defined as membership in the Council of Teaching Hospitals]; registered nurse to census ratio [ratio of full-time equivalent registered nurses to total inpatient days]; percent Medicaid days [ratio of total facility Medicaid days to total facility inpatient days, multiplied by 100]; rural; profit status [for-profit, nonprofit, other]; and region [South, Northeast, West, Midwest]). In addition to the patient and hospital fixed effects, our model also included a random hospital-specific intercept to capture the unmeasured heterogeneity across hospitals. Let Yij = 1, if for the jth patient seen at the ith hospital at least 1 perioperative medical consultation was ordered, and let Yij = 0 if otherwise. The probability of at least 1 perioperative medical consultation for the jth patient seen at the ith hospital can then be modeled as follows:Level 1: between patients (within hospitals): logit[P(Yij = 1)] = μ0i + θXijLevel 2: between hospitals: μ0i = β00 + β0i + γZiCombined model: logit[P(Yij = 1)] = β00 + β0i + γZi+ θXij,where β00 is the population-averaged log-odds of at least 1 perioperative medical consult; β0i is the hospital-specific random effect, assumed to follow a normal distribution with mean zero and variance σ2hosp (variance of the hospital-specific random effect); Xij is the matrix of patient covariates; θ is the corresponding vector of fixed effects representing changes in the log-odds of medical consultation use corresponding to each unit change in the covariate values; Zi represents the vector of hospital-level covariates for the ith hospital; γ is the corresponding vector of coefficients; and μ0i is the intercept. Model estimates were obtained using a penalized quasi-likelihood–based approach. Adjusted risk ratios (ARRs) based on the model were calculated to aid in the interpretability and intuitiveness of the results.9

We also explored hospital variation in medical consultation use. We were particularly interested in how practices might vary after accounting for complications or elective admission type. For each condition (ie, colectomy and THR), we fitted a hierarchical logistic regression for the entire patient cohort. We then fitted models stratified by the presence or absence of complications or by elective status. Covariates in the overall group model were age, sex, race, and number of comorbidities. The models stratified by complications included elective status as an additional covariate.

Hospital-specific rates of the presence of at least 1 medical consultation among all patients were obtained using empirical Bayes predictions and then plotted by hospital rank, from lowest to highest according to the empirical Bayes predictions. This method shrinks the estimate of the hospital-specific medical consultation rate toward the mean rate as a factor of the number of patients treated at the hospital. Hospitals treating a large number of patients will have less shrinkage, whereas hospitals treating a small number of patients will have more shrinkage toward the mean rate. To display hospital variation in consultation use stratified by complications or elective admission type, we used box plots with ±1.5 times the interquartile range (IQR) as whiskers and points for outliers.

Describing variation in use of visits by medicine physicians is the first step toward understanding when these visits have value for surgical patients. In exploratory analyses, we therefore examined the association between medical consultations and 2 outcomes: 30-day mortality (defined as death within 30 days of admission) and the presence of 1 or more postoperative complications during the hospitalization (as defined earlier). For colectomy and THR, we fitted logit regression models with these outcomes as dependent variables. Covariates in these models were age, sex, race, number of comorbidities, and elective status. For each patient, we used these model results to generate (adjusted) predicted probabilities of mortality and 1 or more complications. We then computed mean predicted probabilities at the hospital level both with and without application of the Bayesian shrinkage method we describe in the preceding paragraph. We also computed mean (unadjusted), hospital-level measures of inpatient medical visit use (≥1 visits vs none) and grouped hospitals into quintiles according to these visit-based means. We report mean hospital-level predicted mortality and complication outcomes by visit-use quintile.

All statistical analyses were performed using SAS software (version 9.3; SAS Institute Inc). Two-sided tests were used, with P < .05 considered statistically significant.

Results

Among colectomy patients, 50% had at least 1 general medicine consultation (Table 1), and approximately one-third were comanaged by a generalist (results not displayed). Fifty-six percent of colectomy patients saw at least 1 medical specialist, most commonly a cardiologist (28%), oncologist (25%), or gastroenterologist (22%). Sixty-nine percent of colectomy patients saw at least 1 medical consultant (generalist or specialist), and for this group of patients, the median number of visits by any consultant was 9, and the median number of specialists seen was 2.

Fifty-three percent of patients who underwent THR had a general medicine consultation (Table 1), and approximately one-third were comanaged by a generalist (results not displayed). However, compared with colectomy, many fewer THR patients received at least 1 specialist consultation (24%), with the most common specialist consultation type being physical medicine and rehabilitation (11%). Among THR patients who saw at least 1 medicine consultant (generalist or specialist), the median number of visits by any consultant was 3, and the median number of specialists seen was 1.

In adjusted analyses, patient factors associated with ordering at least 1 medical consultation for patients undergoing either procedure included older age, more comorbidities, and nonelective admission type (Table 2). For both procedures, hospital factors associated with ordering at least 1 medical consultation included being located in the Midwest. Nonteaching status and for-profit status were also associated with greater use of medical consultations for colectomy patients. Larger hospital size was associated with greater use of medical consultations for THR patients.

The likelihood of ordering at least 1 medical consultation varied widely among hospitals performing colectomy (IQR, 50%-91%; range, 3%-100%) or THR (IQR, 36%-90%; range, 1%-100%) (Figure 1). Hospital variation in use of medical consultations was much wider for colectomy patients without vs with a complication (IQR, 47%-79% among those without complications vs 90%-95% among those with complications) (Figure 2A). Results were similar for THR (IQR, 36%-87% among those without complications vs 89%-94% among those with complications) (Figure 2B). Similarly, for both colectomy and THR, variation was wider among elective compared with nonelective patients (see eAppendix in the Supplement).

In exploratory analyses, the use of medical consultations was not associated with predicted, risk-adjusted 30-day mortality rates for colectomy or THR. At hospitals in the lowest quintile of medical consultations for colectomy patients, the 30-day mortality rate was 4.7%. At hospitals in the highest quintile of medical consultations for colectomy patients, the 30-day mortality rate was 5.9%. However, the trend across quintiles was not statistically significant (P = .40). In contrast, greater use of medical consultations was associated with the predicted presence of at least 1 postoperative complication. At hospitals in the lowest (vs highest) quintile of medical consultations for colectomy patients, 24.5% (vs 28.5%) had at least 1 postoperative complication (P < .001). Results were similar for THR, and with shrunken estimates.

Discussion

We found that use of inpatient perioperative medical consultations for 2 major operative procedures was common but varied widely across hospitals. More than half of patients undergoing colectomy or THR had at least 1 inpatient medical consult. Among those patients who had at least 1 medical consult, the median number of visits was high—9 for colectomy and 3 for THR. Variation in use of medical consultants was wider among patients without complications than among patients with complications.

Prior research on perioperative inpatient medical consultations has examined what constitutes a good consult, the association of consultations with outcomes, and trends in comanagement. To increase the value of consultations provided,10 some have sought to improve risk prediction and guidelines for perioperative testing and therapeutics.11-15 Others have examined outcomes associated with use of perioperative medical consultations in a single hospital,16,17 or region.18 This work has found that medical consultation use has an inconsistent association with length of stay and resource use. Still others have used administrative data to document the trend toward increased comanagement of surgical patients by internists3 or variation in the use of preoperative outpatient consultations.19 However, we are unaware of research that describes variation in inpatient medical consultation use in a national cohort of surgical patients.

We believe our results help identify an area of potential focus for hospitals seeking to deliver higher value care in response to payment reforms such as bundled payments. Episode-based payments are currently being tested by Medicare and commercial payers. With traditional fee-for-service, hospitals, physicians, and post–acute care providers are each paid separately for their services. For example, hospitals receive a diagnosis related group payment for the care provided to a surgical patient, but internists are paid separately for each visit made to that same patient. With bundled payments, a single lump sum is provided for all care provided during a longitudinal episode of care. Our findings of wide variation suggest the need for additional research about when medical consultations provide added value during surgical episodes of care.

In particular, our finding that medical consultation use was frequent and common among patients with complications has implications for hospitals. The training and experience of internists and medical subspecialists equips them to help manage patients with postoperative complications such as renal failure, pneumonia, or acute myocardial infarction. But are certain types of consultations more strongly associated with improved outcomes? Hospitals that “fail to rescue” their surgical patients from complications have been shown to have higher operative mortality rates.20 It is plausible that carefully timed medical consultations may reduce death after complications. For example, it may be that 1 nephrology consultation done when acute kidney injury is first recognized may lead to better outcomes than multiple consultations several days later. It is also possible that for surgical patients with multiple medical comorbidities, an attending medicine physician that makes daily visits throughout the hospital stay will improve outcomes. Additional research on the association between mortality after complications and the type, timing, and number of medical consultations would be valuable.

Our finding of wide variation in medical consultation use for those without complications is similar to variation for several other types of medical and surgical interventions.21-23 The variation that we found suggests a lack of consensus about the value of medical consultations for relatively well patients. For patients without complications, which rate is right? It is possible that routine use of medical consultations for relatively well patients prevents poor outcomes. Routine medical comanagement of patients with recognized or unrecognized diabetes may provide great benefit. For example, hyperglycemia has been associated with increased perioperative morbidity and mortality.24 However, it is also possible that some medical consultations are perfunctory “social visits” ordered for all patients and with little clinical value. Additional research is needed to identify the best use of medical consultations for patients without complications.

In general, one would expect the care provided by nonsurgical physicians to improve outcomes for some surgical patients. However, in exploratory analyses, we found that hospitals with greater use of medical consultations have similar or worse clinical outcomes. Our preliminary results suggest the need for additional work to better understand the relationship between medical consultations and outcomes. It is possible that our findings may be explained in part by confounders such as unmeasured severity of illness (ie, sicker patients are more likely to receive a visit from a medicine physician), hospital selection by patients (ie, sicker patients may be more likely to undergo surgical treatment in hospitals where they expect to receive more intensive medical management), and simultaneity bias (eg, additional medical consultations may follow the identification of a complication, or the medical consultant may identify the complication). Future work should use more robust methodological approaches, such as propensity score matching and instrumental variables, to address these issues.

Our study has several important limitations. First, with administrative claims data, we were unable to ascertain in any detail the clinical indications for medical consultations. This precluded a better understanding of the extent to which surgeons preemptively order medical consultations in relatively well patients vs address a complication with a consultation. Second, our findings may not be broadly generalizable as we examined use of medical consultations among fee-for-service Medicare beneficiaries 65 years or older who underwent 1 of 2 procedures. However, we chose the most relevant population for our study, as elderly patients have a disproportionate number of comorbid conditions and are most likely to experience complications or die after a major procedure. Third, with our data, we were unable to explore the use of preoperative outpatient medical consultations. Fourth, from the perspective of the hospital, medicine physicians who assist in the care of surgical patients may have value beyond any positive impact on outcomes. For example, greater use of medical consultations may allow surgeons to spend more time performing high-margin procedures. We were unable to quantify this potential effect. Fifth, the difference in median number of medical consultations for colectomy and THR patients may reflect differences in length of stay (ie, longer hospitalizations leading to more medical visits). However, it is also possible that additional medical consultations generate follow-up testing and contribute to longer hospitalizations. Finally, there are well-recognized limitations in the clinical specificity of administrative claims data to characterize patient risk or categorize postoperative complications.

Conclusions

There is a growing imperative for hospitals to increase their efficiency. Many policy makers hope that mechanisms such as accountable care organizations and episode-based bundled payments will motivate health care providers to reduce costs without harming quality. Medical consultations are a common component of episodes of inpatient surgical care. Our findings of wide variation in medical consultation use—particularly among patients without complications—suggests that understanding when medical consultations provide value will be important as hospitals seek to increase their efficiency under bundled payments.

Article Information

Accepted for Publication: June 2, 2014.

Corresponding Author: Lena M. Chen, MD, MS, Division of General Medicine, University of Michigan, North Campus Research Complex, 2800 Plymouth Rd, Bldg 16, Room 407E, Ann Arbor, MI 48109-2800 (lenac@umich.edu).

Published Online: August 4, 2014. doi:10.1001/jamainternmed.2014.3376.

Author Contributions: Dr Chen and Mr Wilk had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Chen, Birkmeyer, Banerjee.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Chen, Thumma, Birkmeyer.

Critical revision of the manuscript for important intellectual content: Chen, Wilk, Birkmeyer, Banerjee.

Statistical analysis: Chen, Wilk, Thumma, Banerjee.

Obtained funding: Chen, Birkmeyer.

Study supervision: Banerjee.

Conflict of Interest Disclosures: John Birkmeyer has equity interest in ArborMetrix, a company that profiles hospital quality and episode cost efficiency. The company played no role in the manuscript.

Funding/Support: This work was supported by funding from the National Institute of Aging (grant No. P01AG019783-0751 to Dr Birkmeyer and Jonathan Skinner). It was also supported with funding from a University of Michigan MCubed grant. Dr Chen is supported by a Career Development Grant Award (K08HS020671) from the Agency for Healthcare Research and Quality.

Role of the Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: Edward C. Norton, PhD, provided comments on an earlier version of this manuscript. Natalie J. Lin, BA, provided research assistance and received financial compensation for her work.

References
1.
Miller  DC, Gust  C, Dimick  JB, Birkmeyer  N, Skinner  J, Birkmeyer  JD.  Large variations in Medicare payments for surgery highlight savings potential from bundled payment programs.  Health Aff (Millwood). 2011;30(11):2107-2115.PubMedGoogle ScholarCrossref
2.
Birkmeyer  JD, Gust  C, Baser  O, Dimick  JB, Sutherland  JM, Skinner  JS.  Medicare payments for common inpatient procedures: implications for episode-based payment bundling.  Health Serv Res. 2010;45(6 Pt 1):1783-1795.PubMedGoogle ScholarCrossref
3.
Sharma  G, Kuo  YF, Freeman  J, Zhang  DD, Goodwin  JS.  Comanagement of hospitalized surgical patients by medicine physicians in the United States.  Arch Intern Med. 2010;170(4):363-368.PubMedGoogle ScholarCrossref
4.
AHA Annual Survey Database Fiscal Year 2007 [CD-ROM]. Chicago, IL: American Hospital Association; 2008.
5.
Centers for Medicare & Medicaid Services. Medicare acute care episode demonstration for orthopedic and cardiovascular surgery. http://www.cms.gov/Medicare/Demonstration-Projects/DemoProjectsEvalRpts/Downloads/ACE_web_page.pdf. Accessed September 8, 2012.
6.
Breslin  TM, Morris  AM, Gu  N,  et al.  Hospital factors and racial disparities in mortality after surgery for breast and colon cancer.  J Clin Oncol. 2009;27(24):3945-3950.PubMedGoogle ScholarCrossref
7.
Iezzoni  LI, Daley  J, Heeren  T,  et al.  Identifying complications of care using administrative data.  Med Care. 1994;32(7):700-715.PubMedGoogle ScholarCrossref
8.
Weingart  SN, Iezzoni  LI, Davis  RB,  et al.  Use of administrative data to find substandard care: validation of the complications screening program.  Med Care. 2000;38(8):796-806.PubMedGoogle ScholarCrossref
9.
Kleinman  LC, Norton  EC.  What’s the risk? a simple approach for estimating adjusted risk measures from nonlinear models including logistic regression.  Health Serv Res. 2009;44(1):288-302.PubMedGoogle ScholarCrossref
10.
Goldman  L, Lee  T, Rudd  P.  Ten commandments for effective consultations.  Arch Intern Med. 1983;143(9):1753-1755.PubMedGoogle ScholarCrossref
11.
Chopra  V, Flanders  SA, Froehlich  JB, Lau  WC, Eagle  KA.  Perioperative practice: time to throttle back.  Ann Intern Med. 2010;152(1):47-51.PubMedGoogle ScholarCrossref
12.
Ford  MK, Beattie  WS, Wijeysundera  DN.  Systematic review: prediction of perioperative cardiac complications and mortality by the revised cardiac risk index.  Ann Intern Med. 2010;152(1):26-35.PubMedGoogle ScholarCrossref
13.
Wijeysundera  DN, Beattie  WS, Austin  PC, Hux  JE, Laupacis  A.  Non-invasive cardiac stress testing before elective major non-cardiac surgery: population based cohort study.  BMJ. 2010;340:b5526.PubMedGoogle ScholarCrossref
14.
Lee  TH, Marcantonio  ER, Mangione  CM,  et al.  Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery.  Circulation. 1999;100(10):1043-1049.PubMedGoogle ScholarCrossref
15.
Cohn  SL, Smetana  GW.  Update in perioperative medicine.  Ann Intern Med. 2007;147(4):263-270.PubMedGoogle ScholarCrossref
16.
Auerbach  AD, Rasic  MA, Sehgal  N, Ide  B, Stone  B, Maselli  J.  Opportunity missed: medical consultation, resource use, and quality of care of patients undergoing major surgery.  Arch Intern Med. 2007;167(21):2338-2344.PubMedGoogle ScholarCrossref
17.
Huddleston  JM, Long  KH, Naessens  JM,  et al; Hospitalist-Orthopedic Team Trial Investigators.  Medical and surgical comanagement after elective hip and knee arthroplasty: a randomized, controlled trial.  Ann Intern Med. 2004;141(1):28-38.PubMedGoogle ScholarCrossref
18.
Wijeysundera  DN, Austin  PC, Beattie  WS, Hux  JE, Laupacis  A.  Outcomes and processes of care related to preoperative medical consultation.  Arch Intern Med. 2010;170(15):1365-1374.PubMedGoogle ScholarCrossref
19.
Wijeysundera  DN, Austin  PC, Beattie  WS, Hux  JE, Laupacis  A.  Variation in the practice of preoperative medical consultation for major elective noncardiac surgery: a population-based study.  Anesthesiology. 2012;116(1):25-34.PubMedGoogle ScholarCrossref
20.
Ghaferi  AA, Birkmeyer  JD, Dimick  JB.  Variation in hospital mortality associated with inpatient surgery.  N Engl J Med. 2009;361(14):1368-1375.PubMedGoogle ScholarCrossref
21.
Chung  KC, Shauver  MJ, Yin  H, Kim  HM, Baser  O, Birkmeyer  JD.  Variations in the use of internal fixation for distal radial fracture in the United States Medicare population.  J Bone Joint Surg Am. 2011;93(23):2154-2162.PubMedGoogle ScholarCrossref
22.
Haymart  MR, Banerjee  M, Stewart  AK, Koenig  RJ, Birkmeyer  JD, Griggs  JJ.  Use of radioactive iodine for thyroid cancer.  JAMA. 2011;306(7):721-728.PubMedGoogle ScholarCrossref
23.
Lin  GA, Dudley  RA, Lucas  FL, Malenka  DJ, Vittinghoff  E, Redberg  RF.  Frequency of stress testing to document ischemia prior to elective percutaneous coronary intervention.  JAMA. 2008;300(15):1765-1773.PubMedGoogle ScholarCrossref
24.
Pichardo-Lowden  A, Gabbay  RA.  Management of hyperglycemia during the perioperative period.  Curr Diab Rep. 2012;12(1):108-118.PubMedGoogle ScholarCrossref