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The Ongoing Gap in Availability of Imaging Services at Teaching Versus Nonteaching Hospitals

Rationale and Objectives

This study aimed to characterize associations between availability of imaging services and intensity of teaching among US hospitals.

Materials and Methods

Using the American Hospital Association Annual Survey Database, we studied information regarding the availability of imaging services at general hospitals nationwide in 2007 (4102 hospitals) and in 2012 (3876). Teaching intensity was categorized as Council of Teaching Hospitals (COTH) member, non-COTH teaching hospital (non-COTH member with affiliated medical school and/or residency), and nonteaching hospital. Availability in hospitals of reported basic and advanced imaging modalities, as well as beds, number of employed physicians, and case mix index, was analyzed. Univariable and multivariable trends were assessed.

Results

All 15 assessed modalities showed significant increases in availability with increasing hospital teaching intensity ( P < 0.001). Modalities showing the largest differences between COTH and nonteaching hospitals in 2012 were image-guided radiation therapy (78% vs. 14%), positron emission tomography/computed tomography (74% vs. 17%), and single-photon emission computed tomography (88% vs. 35%). The gap between COTH and nonteaching hospitals increased from 43% in 2007 to 57% in 2012 for positron emission tomography/computed tomography, and from 34% to 48% for virtual colonoscopy. COTH status was a significant predictor, independent of beds and employed physicians, for 10 modalities ( P < 0.001–0.038). Greater case mix index was significantly associated with availability of advanced, although not basic, modalities.

Conclusions

Availability of imaging services increased with greater hospital teaching intensity. Differences were most pronounced and sustained over time for advanced modalities. Our findings reflect the greater advanced imaging resources necessary to support the complexity of care rendered at teaching hospitals. This differential must be considered when exploring adjustments to teaching hospitals’ funding levels.

Introduction

Robust graduate medical education (GME) is vital in ensuring a future supply of well-trained physicians. However, GME is a costly process. Training programs entail considerable direct costs, such as the salaries and benefits of residents and their supervising faculty, as well as the administrative and overhead costs of operating an accredited training program. In addition, teaching hospitals face greater costs relating to offering more advanced and specialized services, as well as caring for a greater fraction of sicker, more complex, and uninsured patients .

GME is largely funded by the Medicare program , which provides teaching hospitals with both a direct GME payment to cover teaching costs as well as an indirect medical education (IME) payment to cover teaching hospitals’ greater overall cost of patient care . Concerns regarding the solvency of the Medicare program have driven continual efforts to curtail Medicare’s GME funding . For instance, the Balanced Budget Act in 1997 capped the number of nationally funded GME positions and substantially reduced the IME add-on percentage . MedPAC, the National Commission on Fiscal Responsibility and Reform, the Congressional Budget Office, as well as several recent annual White House budgets have all called for further large reductions in Medicare’s GME funding, typically targeting IME payments . Some policymakers have even suggested that Medicare cease funding GME altogether .

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Methods

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Results

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TABLE 1

Characteristics of General Hospitals Included in the Study

Hospital Characteristic Nonteaching Non-COTH Teaching COTH Teaching_P_2007n 3084 733 285 Total beds \* 114 ± 114 264 ± 187 541 ± 284 <0.001 FTE physicians \* 7 ± 18 31 ± 63 142 ± 268 <0.001 Case mix index \* 1.41 ± 0.27 1.61 ± 0.27 1.85 ± 0.28 <0.0012012n 2787 822 267 Total beds \* 108 ± 109 274 ± 206 576 ± 321 <0.001 FTE physicians \* 9 ± 21 33 ± 78 189 ± 339 <0.001 Case mix index \* 1.44 ± 0.29 1.62 ± 0.24 1.92 ± 0.26 <0.001

COTH, Council of Teaching Hospitals; FTE, full-time equivalent.

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TABLE 2

Comparison of Availability of Imaging Modalities Among Hospitals with Varying Teaching Intensity in 2007 and in 2012

Modality Nonteaching Non-COTH Teaching COTH Teaching Nonteaching Non-COTH Teaching COTH Teaching Difference (COTH vs. Nonteaching) 2007 2007 2007 2012 2012 2012 2007 2012 CT 93% 98% 100% 96% 98% 99% 7% 3% Multi-slice spiral CT 57% 76% 90% 63% 81% 90% 33% 27% 64-slice spiral CT 23% 47% 72% 41% 72% 94% 49% 53% Electron-beam CT 5% 13% 25% 5% 15% 29% 20% 24% Ultrasound 90% 98% 99% 91% 97% 99% 9% 8% MRI 63% 83% 95% 71% 87% 97% 32% 26% PET 10% 26% 54% 12% 30% 60% 44% 48% PET/CT 11% 28% 54% 17% 37% 74% 43% 57% SPECT 34% 60% 87% 35% 59% 88% 53% 53% Mammography 80% 90% 90% 81% 90% 92% 10% 11% Full-field digital mammography 21% 38% 60% 57% 74% 85% 39% 28% Diagnostic radioisotope facility 56% 82% 94% 59% 84% 93% 38% 34% Intra-operative MRI 2% 6% 19% 3% 7% 21% 17% 18% Image-guided radiation therapy 9% 26% 54% 14% 41% 78% 45% 64% Virtual colonoscopy 12% 23% 46% 13% 28% 61% 34% 48%

COTH, Council of Teaching Hospitals; CT, computed tomography; MRI, magnetic resonance imaging; PET, positron emission tomography; SPECT, single-photon emission computed tomography.

TABLE 3

Comparison of Availability of Imaging Modalities in 2012 Among Hospitals with Varying Teaching Intensity, Stratified by Availability Solely at the Hospital vs. Availability Either at the Hospital or Through the Hospital System, Network, or Joint Venture

Modality Nonteaching Non-COTH Teaching COTH Teaching Nonteaching Non-COTH Teaching COTH Teaching Difference (COTH vs. Nonteaching) Hospital Hospital Hospital All All All Hospital All CT 96% 98% 99% 97% 99% 100% 3% 3% Multi-slice spiral CT 63% 81% 90% 68% 86% 92% 27% 24% 64-slice spiral CT 41% 72% 94% 48% 79% 95% 53% 47% Electron-beam CT 5% 15% 29% 10% 24% 36% 24% 26% Ultrasound 91% 97% 99% 97% 99% 100% 8% 3% MRI 71% 87% 97% 91% 98% 100% 26% 9% PET 12% 30% 60% 32% 59% 81% 48% 49% PET/CT 17% 37% 74% 37% 70% 92% 57% 55% SPECT 35% 59% 88% 43% 69% 93% 53% 50% Mammography 81% 90% 92% 88% 97% 99% 11% 11% Full-field digital mammography 57% 74% 85% 63% 83% 93% 28% 30% Diagnostic radioisotope facility 59% 84% 93% 66% 89% 97% 34% 31% Intra-operative MRI 3% 7% 21% 7% 15% 31% 18% 24% Image-guided radiation therapy 14% 41% 78% 27% 60% 88% 64% 61% Virtual colonoscopy 13% 28% 61% 19% 38% 70% 48% 51%

COTH, Council of Teaching Hospitals; CT, computed tomography; MRI, magnetic resonance imaging; PET, positron emission tomography; SPECT, single-photon emission computed tomography. “All” refers to availability of the modality through the hospital system, network, or joint venture.

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TABLE 4

P Values From Multivariable Logistic Regression to Identify Significant Independent Predictors of Availability of the Imaging Modalities, Based on the 2012 Data \*

Modality COTH Status Total Beds FTE Physicians CT0.030<0.001 0.113 Multi-slice spiral CT0.035<0.001 0.057 64-slice spiral CT 0.740<0.001<0.001 Electron-beam CT 0.150<0.001 0.989 Ultrasound0.015<0.001<0.001 MRI 0.835<0.001 0.469 PET0.038<0.001 0.105 PET/CT0.022<0.0010.003 SPECT 0.284<0.0010.003 Mammography<0.001<0.001 0.818 Full-field digital mammography 0.329<0.001 0.447 Diagnostic radioisotope facility<0.001<0.001<0.001 Intra-operative MRI0.003<0.001 0.767 Image-guided radiation therapy0.001<0.001 0.105 Virtual colonoscopy<0.001<0.0010.016

COTH, Council of Teaching Hospitals; CT, computed tomography; FTE, full-time equivalent; MRI, magnetic resonance imaging; PET, positron emission tomography; SPECT, single-photon emission computed tomography.

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TABLE 5

Comparison of CMI Between Hospitals with and without Availability of the Imaging Modalities \*

Modality Not Available Available_P_ CT 1.63 ± 0.64 1.53 ± 0.300.020 Multi-slice spiral CT 1.41 ± 0.33 1.57 ± 0.30<0.001 64-slice spiral CT 1.40 ± 0.34 1.60 ± 0.27<0.001 Electron-beam CT 1.51 ± 0.31 1.71 ± 0.29<0.001 Ultrasound 1.60 ± 0.66 1.53 ± 0.30 0.075 MRI 1.36 ± 0.39 1.56 ± 0.29<0.001 PET 1.48 ± 0.30 1.70 ± 0.28<0.001 PET/CT 1.46 ± 0.31 1.68 ± 0.27<0.001 SPECT 1.44 ± 0.34 1.60 ± 0.27<0.001 Mammography 1.54 ± 0.51 1.53 ± 0.28 0.643 Full-field digital mammography 1.46 ± 0.38 1.56 ± 0.28<0.001 Diagnostic radioisotope facility 1.40 ± 0.42 1.56 ± 0.28<0.001 Intra-operative MRI 1.52 ± 0.30 1.79 ± 0.34<0.001 Image-guided radiation therapy 1.45 ± 0.31 1.69 ± 0.26<0.001 Virtual colonoscopy 1.49 ± 0.31 1.67 ± 0.29<0.001

CMI, case mix index; CT, computed tomography; MRI, magnetic resonance imaging; PET, positron emission tomography; SPECT, single-photon emission computed tomography.

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Discussion

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References

  • 1. Newhouse J.P., Wilensky G.R.: Paying for graduate medical education: the debate goes on. Health Aff (Millwood) 2001; 20: pp. 136-147.

  • 2. Rich E.C., Liebow M., Srinivasan M., et. al.: Medicare financing of graduate medical education. J Gen Intern Med 2002; 17: pp. 283-292.

  • 3. Young J.Q., Coffman J.M.: Overview of graduate medical education. Funding streams, policy problems, and options for reform. West J Med 1998; 168: pp. 428-436.

  • 4. Health Policy Brief: Graduate Medical Education. Health Affairs; August 16; Available at: http://www.healthaffairs.org/healthpolicybriefs/brief.php?brief_id=73 Accessed September 6, 2015

  • 5. Rye B.: Bloomberg government study. Assessing the impact of potential cuts in Medicare doctor-training subsidies. Available at: http://about.bgov.com/content/uploads/sites/2/2012/03/ryestudy.pdf Accessed September 6, 2015

  • 6. Wilensky G.R., Berwick D.M.: Reforming the financing and governance of GME. N Engl J Med 2014; 371: pp. 792-793.

  • 7. Wray J.L., Sadowski S.M.: Defining teaching hospitals’ GME strategy in response to new financial and market challenges. Acad Med 1998; 73: pp. 370-379.

  • 8. Medicare Payment Advisory Commission : Report to the Congress. Improving Medicare’s payments for inpatient care and for teaching hospitals. Washington, DC: Medicare Payment Advisory Commission; June2000.

  • 9. Levine A.S., Alpern R.J., Andrews N.C., et. al.: Research in academic medical centers: two threats to sustainable support. Sci Transl Med 2015; 7: pp. 289fs22.

  • 10. Otero H.J., Ondategui-Parra S., Erturk S.M., et. al.: Financing radiology graduate medical education: today’s challenges. J Am Coll Radiol 2006; 3: pp. 207-212.

  • 11. Center for American Progress : Erosion of funding for the National Institutes of Health threatens U.S. leadership in biomedical research. Available at: https://www.americanprogress.org/issues/economy/report/2014/03/25/86369/erosion-of-funding-for-the-national-institutes-of-health-threatens-u-s-leadership-in-biomedical-research/ Accessed September 6, 2015

  • 12. Gbadebo A.L., Reinhardt U.E.: Economists on academic medicine: elephants in a porcelain shop?. Health Aff (Millwood) 2001; 20: pp. 148-152.

  • 13. Association of American Medical Colleges : Academic medicine: where patients turn for hope. Available at: https://members.aamc.org/eweb/upload/Academic%20Medicine%20Where%20Patients%20Turn%20for%20Hope.pdf Accessed March 15, 2016

  • 14. US Government Accountability Office : Medicare Part B imaging services: rapid spending growth and shift to physician offices indicate need for CMS to consider additional management practices. Available at: http://www.gao.gov/new.items/d08452.pdf Accessed September 8, 2015

  • 15. Chen Y.A., Gray B.G., Bandiera G., et. al.: Variation in the utilization and positivity rates of CT pulmonary angiography among emergency physicians at a tertiary academic emergency department. Emerg Radiol 2015; 22: pp. 221-229.

  • 16. Makarov D.V., Loeb S., Ulmert D., et. al.: Prostate cancer imaging trends after a nationwide effort to discourage inappropriate prostate cancer imaging. J Natl Cancer Inst 2013; 105: pp. 1306-1313.

  • 17. Safran D.B., Pilati D., Folz E., et. al.: Is appendiceal CT scan overused for evaluating patients with right lower quadrant pain?. Am J Emerg Med 2001; 19: pp. 199-203.

  • 18. American Hospital Association : AHA annual survey database.2012.American Hospital AssociationChicago, IL

  • 19. Shahian D.M., Nordberg P., Meyer G.S., et. al.: Contemporary performance of U.S. teaching and nonteaching hospitals. Acad Med 2012; 87: pp. 701-708.

  • 20. Hsia R.Y., Kellermann A.L., Shen Y.C.: Factors associated with closures of emergency departments in the United States. JAMA 2011; 305: pp. 1978-1985.

  • 21. Rajaram R., Chung J.W., Kinnier C.V., et. al.: Hospital characteristics associated with penalties in the Centers for Medicare and Medicaid Services Hospital-Acquired Condition Reduction Program. JAMA 2015; 314: pp. 375-383.

  • 22. Adler-Milstein J., DesRoches C.M., Furukawa M.F., et. al.: More than half of US hospitals have at least a basic EHR, but stage 2 criteria remain challenging for most. Health Aff (Millwood) 2014; 33: pp. 1664-1671.

  • 23. American Hospital Association : AHA annual survey health forum, L.L.C. Available at: http://www.ahadataviewer.com/Global/survey%20instruments/2014AHAAnnualsurvey.pdf Accessed March 15, 2016

  • 24. Shahian D.M., Liu X., Meyer G.S., et. al.: Hospital teaching intensity and mortality for acute myocardial infarction, heart failure, and pneumonia. Med Care 2014; 52: pp. 38-46.

  • 25. Allison J.J., Kiefe C.I., Weissman N.W., et. al.: Relationship of hospital teaching status with quality of care and mortality for Medicare patients with acute MI. JAMA 2000; 284: pp. 1256-1262.

  • 26. Dimick J.B., Cowan J.A., Colletti L.M., et. al.: Hospital teaching status and outcomes of complex surgical procedures in the United States. Arch Surg 2004; 139: pp. 137-141.

  • 27. Association of American Medical Colleges : Council of Teaching Hospitals and Health Systems (COTH). Member Services and Benefits. Available at: https://www.aamc.org/download/333616/data/cothmemberservices.pdf Accessed September 6, 2015

  • 28. Center for Medicare & Medicaid Services : FY 2016 IPPS Final Rule Home Page. Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/FY2016-IPPS-Final-Rule-Home-Page.html Accessed September 26, 2015

  • 29. Ferreira D.C., Marques R.C.: Should inpatients be adjusted by their complexity and severity for efficiency assessment? Evidence from Portugal. Health Care Manag Sci 2014;

  • 30. Jalisi S., Sanan A., McDonough K., et. al.: Economic impact of a head and neck oncologic surgeon: the case mix index. Head Neck 2014; 36: pp. 1420-1424.

  • 31. Lagman R.L., Walsh D., Davis M.P., et. al.: All patient refined-diagnostic related group and case mix index in acute care palliative medicine. J Support Oncol 2007; 5: pp. 145-149.

  • 32. Langer A.: A systematic review of PET and PET/CT in oncology: a way to personalize cancer treatment in a cost-effective manner?. BMC Health Serv Res 2010; 10: pp. 283.

  • 33. Johnson C.D., Chen M.H., Toledano A.Y., et. al.: Accuracy of CT colonography for detection of large adenomas and cancers. N Engl J Med 2008; 359: pp. 1207-1217.

  • 34. Smith J.M., Fox C.J., Brazaitis M.P., et. al.: Sixty-four-slice CT angiography to determine the three dimensional relationships of vascular and soft tissue wounds in lower extremity war time injuries. Mil Med 2010; 175: pp. 65-67.

  • 35. Ogura I., Kaneda T., Mori S., et. al.: Characterization of mandibular fractures using 64-slice multidetector CT. Dentomaxillofac Radiol 2012; 41: pp. 392-395.

  • 36. Matsubara K., Koshida K., Noto K., et. al.: A head phantom study for intraocular dose evaluation of 64-slice multidetector CT examination in patients with suspected cranial trauma. Eur J Radiol 2011; 79: pp. 283-287.

  • 37. Abernethy L.J., Avula S., Hughes G.M., et. al.: Intra-operative 3-T MRI for paediatric brain tumours: challenges and perspectives. Pediatr Radiol 2012; 42: pp. 147-157.

  • 38. Millward C.P., Da Rosa S.P., Avula S., et. al.: The role of early intra-operative MRI in partial resection of optic pathway/hypothalamic gliomas in children. Childs Nerv Syst 2015; 31: pp. 2055-2062.

  • 39. Ramm-Pettersen J., Berg-Johnsen J., Hol P.K., et. al.: Intra-operative MRI facilitates tumour resection during trans-sphenoidal surgery for pituitary adenomas. Acta Neurochir (Wien) 2011; 153: pp. 1367-1373.

  • 40. Sharpe R.E., Levin D.C., Parker L., et. al.: The recent reversal of the growth trend in MRI: a harbinger of the future?. J Am Coll Radiol 2013; 10: pp. 599-602.

  • 41. Levin D.C., Rao V.M., Parker L., et. al.: Analysis of radiologists’ imaging workload trends by place of service. J Am Coll Radiol 2013; 10: pp. 760-763.

  • 42. Levin D.C., Rao V.M., Parker L.: The recent downturn in utilization of CT: the start of a new trend?. J Am Coll Radiol 2012; 9: pp. 795-798.

  • 43. Sistrom C.L., McKay N.L.: Costs, charges, and revenues for hospital diagnostic imaging procedures: differences by modality and hospital characteristics. J Am Coll Radiol 2005; 2: pp. 511-519.

  • 44. Khorasani R.: Consider hidden IT costs when purchasing an MRI or CT scanner. J Am Coll Radiol 2008; 5: pp. 935-936.

  • 45. Center for Medicare & Medicaid Services : Hospital Value-Based Purchasing Program. Available at: https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNProducts/downloads/Hospital_VBPurchasing_Fact_Sheet_ICN907664.pdf Accessed September 9, 2015

  • 46. Lee W.S., Parks N.A., Garcia A., et. al.: Pan computed tomography versus selective computed tomography in stable, young adults after blunt trauma with moderate mechanism: a cost-utility analysis. J Trauma Acute Care Surg 2014; 77: pp. 527-533. discussion 33

  • 47. Sweet A., Lee D., Gairy K., et. al.: The impact of CT colonography for colorectal cancer screening on the UK NHS: costs, healthcare resources and health outcomes. Appl Health Econ Health Policy 2011; 9: pp. 51-64.

  • 48. Perneger T.V.: What’s wrong with Bonferroni adjustments. BMJ 1998; 316: pp. 1236-1238.

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