The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
CPT fee differentials and visit upcoding under Medicare Part B
Abstract
Medicare Part B pays outpatient physicians according to the billed Current Procedural Terminology (CPT) codes, which differ in procedure and intensity. Since many performed services merely differ by intensity, physicians have an incentive to upcode services to increase profitability of a visit. Using nationally representative data from the 2001 to 2003 Medicare Current Beneficiary Survey, this paper explores the effect of Medicare Part B fee differentials on the upcoding of general office visits (i.e. for established patient visits with CPT codes of 99212-99215). It finds strong evidence that these fee differentials influence physician's coding choice for billing purposes across a variety of specialties. For general office visits, Medicare outlays attributable to upcoding may sum to as much as 15% of total expenditures for such visits. Medicare has much to gain financially by clarifying its classification rules. Until the distinctions between types of Medicare visits are redefined in a way that eliminates ambiguity, upcoding under Medicare Part B is likely to continue.
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In the citing paper
“A change in the way records are coded (e.g., upcoding or changes in coding systems, as described above) may alter the study population [63,75,76].”
From The Reporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) statement. (2015) · cites this paper as [63]
In the citing paper
“For example, the introduction of provider billing incentive codes may change the likelihood of a code being used over time [62,63].”
From The Reporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) statement. (2015) · cites this paper as [63]
In the citing paper
“In addition, changes in coding strategies may impact validity or consistency of data.”
From The Reporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) statement. (2015) · cites this paper as [63]
Citations
Cites
Limited-Dependent and Qualitative Variables in Econometrics
Maddala, G. S. (1983) · Cambridge University Press eBooks · doi:10.1017/cbo9780511810176 · Cited by 13,268
Microeconometrics: Methods and Applications
Cameron, A. C., & Trivedi, P. K. (2005) · doi:10.1017/cbo9780511811241 · Cited by 8,092
Limited-Dependent and Qualitative Variables in Econometrics.
Rees, H., & Maddala, G. S. (1985) · The Economic Journal · doi:10.2307/2233228 · Cited by 1,388
How Do Hospitals Respond to Price Changes?
Dafny, L. (2005) · American Economic Review · doi:10.1257/000282805775014236 · Cited by 402
Medicare upcoding and hospital ownership
Silverman, E. M., & Skinner, J. (2004) · Journal of Health Economics · doi:10.1016/j.jhealeco.2003.09.007 · Cited by 354
Physician manipulation of reimbursement rules for patients: between a rock and a hard place.
Wynia, M. K., Cummins, D. S., VanGeest, J. B., & Wilson, I. B. (2000) · PubMed · doi:10.1001/jama.283.14.1858 · Cited by 238
Medicare RBRVS : the physicians' guide
Smith, S. L., Fischoff, R., & Klemp, T. (2010) · American Medical Association eBooks · Cited by 54
Accuracy of CPT evaluation and management coding by family physicians.
King, M. S., Sharp, L. K., & Lipsky, M. S. (2001) · PubMed · Cited by 54
Chao, J., Gillanders, W. G., Flocke, S. A., Goodwin, M. A., Kikano, G. E., & Stange, K. C. (1998) · PubMed · Cited by 50
Kikano, G. E. (2000) · Archives of Family Medicine · doi:10.1001/archfami.9.1.68 · Cited by 40
Research works printed but not linked: 2
- Gillis, 1993, Assessing the validity of the geographic practic cost indices, Inquiry, 30, 265
- Zuber, 2000, Variability in code selection using the 1995 and 1998 HCFA documentation guidelines for office services, Journal of Family Practice, 49, 642
Cited by
Sorted by citations
Benchimol, E. I., Smeeth, L., Guttmann, A., Harron, K., Moher, D., Petersen, I., Sørensen, H. T., von Elm, E., Langan, S. M., & RECORD Working Committee (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001885 · Cited by 5,749
Poon, S. J., Schuur, J. D., & Mehrotra, A. (2018) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.3205 · Cited by 126
A survey on the state of healthcare upcoding fraud analysis and detection
Bauder, R. A., Khoshgoftaar, T. M., & Seliya, N. (2016) · Health Services and Outcomes Research Methodology · doi:10.1007/s10742-016-0154-8 · Cited by 102
“Overall, Brunt (2011) demonstrates that a large differential increases the likelihood of upcoding services to higher intensity ones and increases the chance of being caught.”
BackgroundMethodInfluentialKalbaugh, C. A., Kucharska‐Newton, A., Wruck, L. M., Lund, J. L., Selvin, E., Matsushita, K., Bengtson, L. G. S., HEISS, G. M., & Loehr, L. R. (2017) · Journal of the American Heart Association · doi:10.1161/jaha.116.003796 · Cited by 101
Big Bad Data: Law, Public Health, and Biomedical Databases
Hoffman, S., & Podgurski, A. (2013) · The Journal of Law Medicine & Ethics · doi:10.1111/jlme.12040 · Cited by 101
Metadata
- Authors
- Brunt, C. S.
- Affiliations
- Lake Superior State University (US)
- Corresponding author
- Brunt, Christopher S.
- Venue
- Health Economics
- Publisher
- Wiley
- Published
- 2011-04-03
- Volume
- 20
- Issue
- 7
- Pages
- 831-841
- ISSN
- 1057-9230 (ISSN-L)
- OpenAlex
- W1983062388
- Cited by
- 59
- References
- 19
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 6 · 2022: 1 · 2021: 5 · 2020: 5 · 2019: 5 · 2018: 3 · 2017: 5 · 2016: 5 · 2015: 5 · 2014: 4 · 2013: 4 · 2012: 2
- FWCI
- 6.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Health Economics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Blue Cross Blue Shield of Michigan Foundation
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Health Professions › General Health Professions › Healthcare cost, quality, practices
- Keywords
- Medicare Part B, physician billing, physician incentives, Medicare reimbursement, Medicare Current Beneficiary Survey
- MeSH terms
- Diagnosis-Related Groups, Fee Schedules, Humans, United States, Medicare Part B, Models, Econometric, Current Procedural Terminology, Clinical Coding
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- CoChat. (2026). Citation check: CPT fee differentials and visit upcoding under Medicare Part B. https://app.cochat.ai/papers/10.1002/hec.1649
- The paper
- Brunt, C. S. (2011). CPT fee differentials and visit upcoding under Medicare Part B. Health Economics. https://doi.org/10.1002/hec.1649
