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The Influence of Provider Characteristics and Market Forces on Response to Financial Incentives
Brock O’Neil, MD; Mark Tyson, MD; Amy J. Graves, SM, MPH; Daniel A. Barocas, MD, MPH; Sam S. Chang, MD, MBA; David F. Penson, MD, MPH; and Matthew J. Resnick, MD, MPH
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The Influence of Provider Characteristics and Market Forces on Response to Financial Incentives

Brock O’Neil, MD; Mark Tyson, MD; Amy J. Graves, SM, MPH; Daniel A. Barocas, MD, MPH; Sam S. Chang, MD, MBA; David F. Penson, MD, MPH; and Matthew J. Resnick, MD, MPH
We determine a specialist physician phenotype responsive to financial incentives that may be leveraged to identify physicians and markets well-suited for participation in alternative payment models.
This study evaluated physician- and market-level characteristics associated with adoption of a financially incentivized change in practice for the diagnosis and management of bladder cancer. Several important relationships were identified that might characterize a phenotype for incentive responsiveness: providers in smaller groups, practicing in dense markets, who are also facile with billing and without competing financial ownership interests. 

The influence of firm size may reflect several possible phenomena. First, small firms are increasingly integrating with larger firms, and incentive-responsive behavior may be a resistive attempt to increase or maintain revenue in the face of consolidation pressures. Second, larger firms may be more likely to have an ownership stake in a facility that may mitigate the net benefit associated with the evaluated modification in the Medicare physician fee schedule. Finally, smaller organizations may be more nimble and adaptable to changes in price structure to maximize profitability.

Market forces appear to have a significant relationship with providers’ responses to changes in professional payment. Markets with a higher density of providers were associated with increased likelihood of incentive-responsive behavior, suggesting that providers in these markets may face disproportionate pressures to modify practice in order to maximize profit. Alternatively, denser provider markets may lead to more physician awareness of incentives.

Although unadjusted analyses suggest a relationship between HHI and incentive responsiveness, this relationship was not maintained after adjustment for patient, practice, and market characteristics including, most notably, provider density. This suggests that providers may more readily respond to financial incentives in highly dense markets irrespective of the structure of the firms within that market. The negotiating power of physicians in markets with higher HHI (ie, less competition) has been shown to result in leveraging increased payment from commercial insurers11,14; however, the payment set by CMS is not negotiable based upon firm size or market share. As a result, CMS may be shielded from this potential unintended consequence of novel payment models that foster healthcare concentration and regionalization. At the same time, providers in highly dense markets may be better suited to respond to changes in the realignment of incentives of novel payment models. In addition, price is not the only factor driving healthcare value. It is possible that providers working closely together to coordinate care can reduce overall spending despite lower competition, even if such declines in competition contribute to higher commercial prices.7,8 

Incentive-responsiveness was also associated with increased provider billing efficiency, as evidenced by utilization of a higher number of unique billing codes and more codes per beneficiary. This increase in billing efficiency, whether appropriate or not, as well as responsiveness to financial incentives may be a reaction to counter the pressure of lower prices in competitive markets.

Limitations

This work has several limitations to consider. The primary data source regarding provider behavior was claims data, and we are unable to confirm important patient and disease characteristics from the medical record. Whether a given provider responded to incentives was determined by utilizing claims data spanning more than a decade (2001-2013), and data regarding loco-regional market and provider characteristics were based on data from 2011 to 2013. Therefore, we cannot determine the effects of changes in market and provider characteristics (eg, acquisition or relocation of physician firms) and assume that such events are random between groups. Finally, the Medicare claims data represents a 5% sample of patients, and the unit of analysis in this study was physicians. We cannot exclude nonrandom effects from this methodological consideration in sampling.

CONCLUSIONS

Managing bladder cancer through office-based, rather than facility-based, procedures should intuitively be in the interest of payers (more cost effective than facility-based management), physicians (more time efficient), and patients (more time efficient and cost effective), but in a FFS environment, payment incentives to adopt this practice have resulted in the delivery of low-value redundant cancer care. Our study results suggest that providers who adopt this practice may be influenced to do so by market forces and that they may also be inclined to implement other profit-maximizing behaviors. Approaches to counter this behavior might be to enact rules to govern the appropriateness of office-based procedures, commit significant resources to investigate and enforce laws against upcoding practices, or enact policies that reduce the variation in concentration of physicians.26 However, such a “whack-a-mole” approach will always face an uphill battle against the incentives in FFS medicine that reward such practices. Instead, adopting a payment model where physicians are paid for providing high-quality care rather than for the volume of billed procedures may result in better aligned incentives for all involved parties. While this is the direction cancer care is moving with the Oncology Care Model, surgeon behavior is largely excluded from such realignment of incentives.

That a large proportion of providers did not respond to this financial incentive with such strong face validity is notable. What is it about providers and firms that they did not or were not able to respond to this incentive that essentially left a large financial windfall on the table for taking care of patients with cancer? Are providers who are resistant to incentives simply unaffected due to status quo bias (ie, a preference for persisting in the current state of behavior) or are there alternative forces at play?27 It may be that identifying an incentive-responsive phenotype can be leveraged to provide high-quality, rather than low-quality, care. Recent work suggests that financial incentives for providers can be used to improve cardiovascular risk.28 Would similar results have been found selecting providers identified in this study as incentive-resistant? With Medicare seeking to tie payment to alternative structures instead of FFS,29 identifying markets and providers that remain responsive to incentives may be a crucial step to ensure provider behavior follows intended novel payment schemes. Or perhaps institutions might look to markets, firms, or providers that promote or match this incentive-responsive phenotype for clues to remain viable in the shifting sands of payment reform.

Author Affiliations: Department of Surgery, Division of Urology, Huntsman Cancer Institute, University of Utah (BO), Salt Lake City, UT; Department of Urology, Mayo Clinic-Scottsdale (MT), Scottsdale, AZ; Department of Urologic Surgery, Vanderbilt University (AJG, DAB, SSC, DFP, MJR), Nashville, TN; Geriatric Research Education and Clinical Center, VA Tennessee Valley Healthcare System (DFP, MJR), Nashville, TN.

Source of Funding: The project was supported by CTSA award No. UL1TR000445 from the National Center for Advancing Translational Sciences. Dr Resnick, the senior author, was also supported by the American Cancer Society (MSRG-15-103-01-CPHPS).

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article. 

Authorship Information: Concept and design (BO, MJR); acquisition of data (BO, AJG, DFP, MJR); analysis and interpretation of data (BO, MT, AJG, DAB, DFP, MJR); drafting of the manuscript (BO, MT, AJG, DAB, SSC, DFP, MJR); critical revision of the manuscript for important intellectual content (DAB, SSC); statistical analysis (BO, AJG, MJR); obtaining funding (BO, MJR); and supervision (MT, SSC, DFP, MJR). 

Address Correspondence to: Brock O’Neil, MD, 1950 Circle of Hope, N6405, Salt Lake City, UT 84112. E-mail: brock.oneil@hci.utah.edu. 
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