Physician Behavior Impact When Revenue Shifted From Drugs to Services | Page 3
Published Online: April 21, 2014
Bruce Feinberg, DO; Scott Milligan, PhD; Tim Olson, MBA; Winston Wong, PharmD; Daniel Winn, MD; Ram Trehan, MD; and Jeffrey Scott, MD
We initiated the Oncology Medical Home program with the intent of further removing financial impact by offering a “white bag” drug delivery system where patient specific medications and supplies are delivered directly to practices from a dedicated specialty pharmacy. Alternatively, practices could continue their legacy buy-and-bill arrangement at a reduced fee schedule, 8% margin over ASP predetermined to be adjusted annually, where they would assume risk for price increases in brand drugs not mitigated by price equilibration for those drugs recently converted to generic. The 8% margin was selected for 2 reasons. First, this was the lowest bid by specialty pharmacy suppliers, as they are unable to purchase drugs at the same discounted prices as oncologists. Second and more importantly, modeling suggested that the 8% margin over ASP, drug utilization from the baseline control period, and the most recent Medicare fee schedule would create no net profit. All practices in the Oncology Medical Home chose to retain their current buy-and-bill practice for drugs. Acceptance of white bagging would have made cohort comparisons less complicated, but the continued buy-and-bill preference by participants, despite profit neutrality and assumed risk, represents an interesting behavioral observation. We recognize that the Oncology Medical Home program was limited to a single payer, which may not have accounted for sufficient per practice volumes to impact behavior. However, that payer represented approximately one-third of the payers of first-generation pathway providers and more than 50% of their profit, making the program financially relevant to participating practices. Although Medicare may contribute the majority of patients to an oncologist’s practice, its contribution to profit is much less significant, making commercial payers increasingly relevant to a practice’s financial integrity.
Finally, we recognize that Oncology Medical Home providers, being mature pathways participants of nearly 3 years, may have had established patterns of care that limited variance, thereby reducing the influence of reimbursement. If this is true, then pathways programs such as the first-generation program described herein may be a more palatable provider solution to an unsustainable cost curve than radical reimbursement reform.
Surprisingly, these findings are not revelatory, as related research into patterns of cancer care has resulted in similar observations. Morden et al found that hospice referral rates, hospitalizations, intensive care unit admissions, and chemotherapy use in the last weeks of life were remarkably uniform regardless of institution; profit versus nonprofit, academic versus community hospital, or small versus large facility.22 These direct observations imply that salaried physicians practice similarly to those reimbursed by fee-for-service methodology, despite vastly different economic incentives.
Observations from Morden and this study suggest that, contrary to prevailing dogma, medical oncology treatment selection and cancer care practice patterns may not be influenced by fee-for-service reimbursement as is often ascribed. Such observations warrant careful consideration as reimbursement methodology is modeled as part of healthcare reform. Research is ongoing to validate these observations and assess additional influences. Other value measures of our Oncology Medical Home that were believed to be both cost-saving and qualityenhancing, included physician commitment to an intensive continuous quality improvement initiative and their participation in an end-of-life care coordination program. The observations related to these components of this Oncology Medical Home pilot were separately reported at the American Society of Clinical Oncology Annual Meeting in 2013 and will be published in the near future.14-17
Author Affiliations: Cardinal Health Specialty Solutions, Dublin, OH (BF, SM, TO, JS); CareFirst BlueCross Blue Shield, Baltimore, MD (WW, DW); Greater Washington Oncology Associates, Rockville, MD (RT).
Source of Funding: None reported.
Author Disclosures: The Pathways Programs, data from which are used in this study, are a business line of Cardinal Health Specialty Solutions (CHSS). Several of the study authors are employed by and own stock in CHSS (BF, SM, TO, JS). The other authors (WW, DW, RT) 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 (BF, WW, RT, JS); acquisition of data (BF, SM, TO, RT, JS); analysis and interpretation of data (BF, SM, TO, DW, JS); drafting of the manuscript (BF, SM, WW); critical revision of the manuscript for important intellectual content (BF, SM, TO, JS); statistical analysis (BF, SM); administrative, technical, or logistic support (RT, JS); supervision (BF).
Address correspondence to: Bruce Feinberg, DO, 7000 Cardinal Pl, Dublin, OH 43017. E-mail: firstname.lastname@example.org
1. Smith TJ, Hillner BE. Bending the cost curve in cancer care. N Engl J Med. 2011;364(21):2060-2065.
2. Farias M, Jenkins K, Lock J, et al. Standardized Clinical Assessment and Management Plans (SCAMPs) provide a better alternative to clinical practice guidelines. Health Aff (Millwood). 2013;32(5):911-920.
3. Hoverman JR, Cartwright T, Patt D, et al. Pathways, outcomes, and costs in colon cancer: retrospective evaluations in 2 distinct databases. Am J Manag Care. 2011;17(suppl 5):SP45-SP52.
4. Neubauer MA, Hoverman JR, Kolodziej M, et al. Cost effectiveness of evidence-based treatment guidelines for the treatment of nonsmall- cell lung cancer in the community setting. J Oncol Pract. 2010; 6(1):12-18.
5. Feinberg B, Lang J, Grzegorczyk J, et al. Implementation of cancer clinical care pathways: a successful model of collaboration between payers and providers. Am J Manag Care. 2012;18(5 spec No. 2): e194-e199.
6. Feinberg B, Milligan S, Cooper J, et al. Third-party validation of observed savings from an oncology pathways program. Am J Manag Care. 2013;19(spec No. 4). Published June 18, 2013. Accessed July 30, 2013.
7. Kreys ED, Koeller JM. Documenting the benefits and cost savings of a large multistate cancer pathway program from a payer’s perspective [published online May 21, 2013]. J Oncol Pract. 2013;9:e241-e247.
8. Scott JA, Wong W, Olson T, et al. Year one evaluation of regional pay for quality (P4Q) oncology program. J Clin Oncol. 2010;28:(suppl 15s):6013.
9. Gesme D, Wiseman M. Strategic use of clinical pathways. J Oncol Pract. 2011;7:54-56.
10. Sprandio JD. Oncology patient-centered medical home. J Oncol Pract. 2012;8(suppl 3):47s-49s.
11. Emanuel EJ. A plan to fix cancer care. New York Times. March 23, 2013. SR14. http://opinionator.blogs.nytimes.com/2013/03/23/a-plan-tofix- cancer-care/?_r=0. Accessed July 20, 2013.
12. Jacobson M, Earle CC, Price M, Newhouse JP. How Medicare’s payment cuts for cancer chemotherapy drugs changed patterns of treatment. Health Aff (Millwood). 2010;29:1391-1399.
13. Office of the Inspector General, US Department of Health and Human Services. Medicare reimbursement of prescription drugs. Philadelphia, PA: US Dept of Health and Human Services; 2001. http:// www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&v ed=0CEYQFjAA&url=http%3A%2F%2Foig.hhs.gov%2Foei%2Freports %2Foei-03-00-00310.pdf&ei=LFTxUa6cGYbI9gSU04HYCg&usg=AFQ jCNHqLM-XAYFF6yE49tOCUKn4VFmM6g&sig2=DQQtNiMPiOCBW_ kefqaNnw&bvm=bv.49784469,d.eWU. Accessed July 20, 2013.
14. Winn D, Wong W, Cooper J, et al. Potential cost savings of a continuous quality improvement (CQI) program as part of an Oncology Medical Home. J Clin Oncol. 2013;31(suppl 15): Abstract e17579.
15. Wong W, Cooper J, Winn D, et al. Oncology Medical Home: payer return on investment (ROI)[ASCO meeting abstracts]. J Clin Oncol. 2013;31(suppl 15); Abstract e17582.
16. Feinberg B, Cooper J, Wong W, et al. Shifting revenue from drug sales to cognitive services: impact on physician prescribing behavior [ASCO meeting abstracts]. J Clin Oncol. 2013;(suppl 15):e6629.
17. Trehan RS, Wong W, Winn D, et al. Financial impact of an Oncology Medical Home on participating providers [ASCO meeting abstracts]. J Clin Oncol. 2013;(suppl 15):e17581.
18. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46:399-424.
19. Charlson ME, Pompei P, Ales, KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383.
20. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613-619.
21. Jacobson M, O’Malley AJ, Earle CC, Pakes J, Gaccione P, Newhouse. Does reimbursement influence chemotherapy treatment for cancer patients? Health Aff (Millwood). 2006;25:437-443.
22. Morden N. The CARE SPAN: end-of-life care for Medicare beneficiaries with cancer is highly intensive overall and varies widely. Health Aff (Millwood). 2012;31:4786-4796.