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The American Journal of Managed Care March 2019
Fragmented Ambulatory Care and Subsequent Emergency Department Visits and Hospital Admissions Among Medicaid Beneficiaries
Lisa M. Kern, MD, MPH; Joanna K. Seirup, MPH; Mangala Rajan, MBA; Rachel Jawahar, PhD, MPH; and Susan S. Stuard, MBA
Incorrect and Missing Author Initials in Affiliations and Authorship Information
From the Editorial Board: Austin Frakt, PhD
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Implications of Eligibility Category Churn for Pediatric Payment in Medicaid
Deena J. Chisolm, PhD; Sean P. Gleeson, MD, MBA; Kelly J. Kelleher, MD, MPH; Marisa E. Domino, PhD; Emily Alexy, MPH; Wendy Yi Xu, PhD; and Paula H. Song, PhD
Factors Influencing Primary Care Providers’ Decisions to Accept New Medicaid Patients Under Michigan’s Medicaid Expansion
Renuka Tipirneni, MD, MSc; Edith C. Kieffer, PhD, MPH; John Z. Ayanian, MD, MPP; Eric G. Campbell, PhD; Cengiz Salman, MA; Sarah J. Clark, MPH; Tammy Chang, MD, MPH, MS; Adrianne N. Haggins, MD, MSc; Erica Solway, PhD, MPH, MSW; Matthias A. Kirch, MS; and Susan D. Goold, MD, MHSA, MA
Did Medicaid Expansion Matter in States With Generous Medicaid?
Alina Denham, MS; and Peter J. Veazie, PhD
Access to Primary and Dental Care Among Adults Newly Enrolled in Medicaid
Krisda H. Chaiyachati, MD, MPH, MSHP; Jeffrey K. Hom, MD, MSHP; Charlene Wong, MD, MSHP; Kamyar Nasseh, PhD; Xinwei Chen, MS; Ashley Beggin, BS; Elisa Zygmunt, MSW; Marko Vujicic, PhD; and David Grande, MD, MPA
Medicare Annual Wellness Visit Association With Healthcare Quality and Costs
Adam L. Beckman, BS; Adan Z. Becerra, PhD; Anna Marcus, BS; C. Annette DuBard, MD, MPH; Kimberly Lynch, MPH; Emily Maxson, MD; Farzad Mostashari, MD, ScM; and Jennifer King, PhD
Common Elements in Opioid Use Disorder Guidelines for Buprenorphine Prescribing
Timothy J. Atkinson, PharmD, BCPS, CPE; Andrew J.B. Pisansky, MD, MS; Katie L. Miller, PharmD, BCPS; and R. Jason Yong, MD, MBA
Specialty Care Access for Medicaid Enrollees in Expansion States
Justin W. Timbie, PhD; Ashley M. Kranz, PhD; Ammarah Mahmud, MPH; and Cheryl L. Damberg, PhD
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Cost Differential of Immuno-Oncology Therapy Delivered at Community Versus Hospital Clinics
Lucio Gordan, MD; Marlo Blazer, PharmD, BCOP; Vishal Saundankar, MS; Denise Kazzaz; Susan Weidner, MS; and Michael Eaddy, PharmD, PhD

Cost Differential of Immuno-Oncology Therapy Delivered at Community Versus Hospital Clinics

Lucio Gordan, MD; Marlo Blazer, PharmD, BCOP; Vishal Saundankar, MS; Denise Kazzaz; Susan Weidner, MS; and Michael Eaddy, PharmD, PhD
Administration of immuno-oncology therapy for cancer diagnoses in the community clinic setting is associated with lower costs compared with administration in a hospital-based clinic setting.

Our study results suggest that the cost of cancer care for patients treated with I-O therapy in the CC setting is significantly lower than that for patients treated in the HC setting and that this is irrespective of I-O agent utilized. Further, costs were lower regardless of evaluated tumor type.

Our data are consistent with previous reports of site of care being significantly associated with cost of care delivery. For example, a commercial claims database analysis demonstrated a 20% to 39% higher mean cost per member per month for patients treated at a hospital-based practice, which was irrespective of cancer type, geographic location, patient age, and number of chemotherapy sessions.7 Further, a systematic literature review (n = 10 studies of Medicare or commercial claims) revealed that the average cost of cancer care was 38% higher for patients treated in hospital-based practices versus those treated at community-based practices.5 A previous matched cohort analysis by Gordan et al revealed that the cost of cancer care for patients with breast, lung, or colorectal cancer treated in the CC setting was approximately $8000 less PPPM than for patients treated in the hospital-based outpatient setting, and this cost differential was irrespective of chemotherapy regimen, branded versus generic agents used, or tumor type.6 Our analysis expands on this previous work by evaluating the newer and costlier I-O agents and including Medicare enrollees, while still matching patients on specific tumor types, treatments, and other possible confounders, such as presence of metastatic disease, surgery, radiation, and geographic region.

It has been proposed that healthcare systems are shaped by their reimbursement design.8 Until very recently in the United States, this has meant delivery of healthcare services defined by transactional payments (ie, a given service is identified by a Current Procedural Terminology code, which has an assigned value relative to a standard reference service, and a fee is paid for each service delivered).8 This volume-based fee-for-service (FFS) system stimulated a wide array of sites of service in which oncology patients receive their care.8 Services that are provided in an oncology physician’s office have been repeatedly shown to be less costly than those delivered in a hospital setting.5-8 However, the FFS system has not recognized many of the services that oncology practices provide, and historically, these services were covered through the margins on chemotherapy drugs.8 In 2003, the marginal revenues from these agents were substantially reduced with the implementation of reimbursement based on average sales price, and there began a consistent trend in community oncology practice closures.8,9 Notably, since 2008, community-based practice clinic closures have increased by 121%, and acquisition of community practices by hospitals has increased by 172%.9

The FFS system can no longer be sustained in an era of rising costs, specifically in oncology care, and in this time of healthcare reform, value-based payment systems have been aimed toward models that incentivize provision of care delivered more efficiently, at a higher quality, and for less cost to the healthcare system. It is imperative that these new payment models support the provision of care in lower-cost sites of service, such as community oncology practices, and promote innovation in practice structure and care delivery.8

In our analysis, cost was captured at the point of first I-O therapy administration, and the cost differential was noted despite the fact that the durations of therapy with the I-O agents were similar between the matched cohorts. This indicates that the difference in cost associated with I-O therapy treatment is not due to disproportionately shorter treatment in the CC cohort. In other words, for the same therapy, given for the same length of time and for the same indication, the reimbursement received was different (lower for the CC cohort) based on the site of care delivery. Further, although the cost differential is not as high as that reported in previous studies, it should be noted that further evaluation may be needed as these are relatively new agents with unique adverse effect profiles. As such, as comfort builds and indications expand with these I-O agents, further evaluation of contributors to increased cost with these already costly agents should be explored.


Limitations of this study include those inherent in any retrospective study. Despite the frequent use of ICD-9-CM/ICD-10-CM coding similar to our analyses to identify cancer and metastases in claims-based studies, the sensitivity and specificity associated with these methods10 may have led to misclassification of patients; however, we would anticipate that this would affect the CC and HC cohorts equally. Further, in spite of robust matching for anticipated confounding factors, other potential confounders, such as socioeconomic data, were not available for any patient. In addition, there are certain aspects within general oncology care that are specific to the use of these agents (ie, biomarker testing, genetic testing/counseling, pain management consult services) that cannot be evaluated using these types of data. Also, indirect costs, such as inability to work or cost of travel, could not be captured from this database.


This study indicates that treatment with immunotherapies for cancer in the community practice setting is associated with a lower total cost of care compared with similar treatment in the hospital-based outpatient practice setting. These data provide real-world insight to payers, the oncology workforce, policy makers, and other health-system stakeholders to examine contributors to total cost of cancer care in this turbulent time of innovative therapies that both improve outcomes and add to an increasing cost trajectory. Due to the time frame of these data and the expanding indications of these agents, future research is needed.

Author Affiliations: Florida Cancer Specialists & Research Institute (LG), Gainesville, FL; Xcenda (MB, VS, DK, ME), Palm Harbor, FL; IntrinsiQ (SW), Frisco, TX.

Source of Funding: This study was supported by the Community Oncology Alliance (COA).

Author Disclosures: Dr Gordan is a board member of Florida Cancer Specialists, COA, and American Oncology Network. Dr Blazer, Mr Saundankar, Ms Kazzaz, and Dr Eaddy are employees of Xcenda, a consulting firm, which received funding for conducting this analysis and preparing the manuscript. Ms Weidner is employed by a drug wholesaler distributer, has attended meetings of COA, and owns stock via mutual funds.

Authorship Information: Concept and design (LG, MB, VS, DK, SW, ME); acquisition of data (LG); analysis and interpretation of data (LG, MB, VS, DK, SW, ME); drafting of the manuscript (LG, MB, VS, DK, SW, ME); critical revision of the manuscript for important intellectual content (LG, MB, VS, DK, SW, ME); statistical analysis (LG, VS); and supervision (LG).

Address Correspondence to: Lucio Gordan, MD, Division of Quality and Informatics, Florida Cancer Specialists & Research Institute, 6420 W Newberry Rd, Ste 100, Gainesville, FL 32605. Email:

1. Pharma trends / dealmaking and R&D: immuno-oncology deal trends, 2012-16; 2017. Datamonitor Healthcare website. Accessed August 30, 2018.

2. Nishijima TF, Shachar SS, Nyrop KA, Muss HB. Safety and tolerability of PD-1/PD-L1 inhibitors compared with chemotherapy in patients with advanced cancer: a meta-analysis. Oncologist. 2017;22(4):470-479. doi: 10.1634/theoncologist.2016-0419.

3. Dranitsaris G, Zhu X, Adunlin G, Vincent MD. Cost effectiveness vs affordability in the age of immuno-oncology cancer drugs. Expert Rev Pharmacoecon Outcomes Res. 2018;18(4):351-357. doi: 10.1080/14737167.2018.1467270.

4. Nardi EA, Wolfson JA, Rosen ST, et al. Value, access, and cost of cancer care delivery at academic medical centers. J Natl Compr Canc Netw. 2016;14(7):837-847. doi: 10.6004/jnccn.2016.0088.

5. Winfield L, Muhlestein D. Cancer treatment costs are consistently lower in the community setting versus the hospital outpatient department: a systematic review of the evidence. Leavitt Partners website. Published March 30, 2017. Accessed August 30, 2018.

6. Gordan L, Blazer M, Saundankar V, Kazzaz D, Weidner S, Eaddy M. Cost differences associated with oncology care delivered in a community setting versus a hospital setting: a matched claims analysis of patients with breast, colorectal, and lung cancers. J Onc Pract. 2018;14(12):e729-e738. doi: 10.1200/JOP.17.00040.

7. Hayes J, Hoverman JR, Brow ME, et al. Cost differential by site of service for cancer patients receiving chemotherapy. Am J Manag Care. 2015;21(3):e189-e196.

8. Cox JV, Ward JC, Hornberger JC, Temel JS, McAneny BL. Community oncology in an era of payment reform. Am Soc Clin Oncol Educ Book. 2014:e447-e452. doi: 10.14694/EdBook_AM.2014.34.e447.

9. 2016 COA practice impact report. Community Oncology Alliance website. Published October 4, 2016. Accessed October 29, 2018.

10. Whyte JL, Engel-Nitz NM, Teitelbaum A, Gomez Rey G, Kallich JD. An evaluation of algorithms for identifying metastatic breast, lung, or colorectal cancer in administrative claims data. Med Care. 2015;53(7):e49-e57. doi: 10.1097/MLR.0b013e318289c3fb.
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