Currently Viewing:
The American Journal of Managed Care March 2015
Evaluation of Care Management Intensity and Bariatric Surgical Weight Loss
Sarit Polsky, MD, MPH; William T. Donahoo, MD; Ella E. Lyons, MS; Kristine L. Funk, MS, RD; Thomas E. Elliott, MD; Rebecca Williams, DrPh, MPH; David Arterburn, MD, MPH; Jennifer D. Portz, PhD, MSW; and Elizabeth Bayliss, MD, MSPH
Potential Savings From Increasing Adherence to Inhaled Corticosteroid Therapy in Medicaid-Enrolled Children
George Rust, MD, MPH, FAAFP, FACPM; Shun Zhang, MD, MPH; Luceta McRoy, PhD; and Maria Pisu, PhD
Innovation in Plain Sight
Karen Ignagni, MBA, President and Chief Executive Officer, America's Health Insurance Plans
Early Changes in VA Medical Home Components and Utilization
Jean Yoon, PhD, MHS; Chuan-Fen Liu, PhD, MPH; Jeanie Lo, MPH; Gordon Schectman, MD; Richard Stark, MD; Lisa V. Rubenstein, MD, MSPH; and Elizabeth M. Yano, PhD, MSPH
Are Healthcare Quality "Report Cards" Reaching Consumers? Awareness in the Chronically Ill Population
Dennis P. Scanlon, PhD; Yunfeng Shi, PhD; Neeraj Bhandari, MD; and Jon B. Christianson, PhD
Developing a Composite Weighted Quality Metric to Reflect the Total Benefit Conferred by a Health Plan
Glen B. Taksler, PhD; and R. Scott Braithwaite, MD, MSc, FACP
Insurance Impact on Nonurgent and Primary Care-Sensitive Emergency Department Use
Weiwei Chen, PhD; Teresa M. Waters, PhD; and Cyril F. Chang, PhD
Currently Reading
Cost Differential by Site of Service for Cancer Patients Receiving Chemotherapy
Jad Hayes, MS, ASA, MAAA; J. Russell Hoverman, MD, PhD; Matthew E. Brow, BA; Dana C. Dilbeck, BA; Diana K. Verrilli, MS; Jody Garey, PharmD; Janet L. Espirito, PharmD; Jorge Cardona, BS; and Roy Beveridge, MD
Strategy for a Transparent, Accessible, and Sustainable National Claims Database
Robin Gelburd, JD, BA
Treatment Patterns, Healthcare Utilization, and Costs of Chronic Opioid Treatment for Non-Cancer Pain in the United States
David M. Kern, MS; Siting Zhou, PhD; Soheil Chavoshi, MS; Ozgur Tunceli, PhD; Mark Sostek, MD; Joseph Singer, MD; and Robert J. LoCasale, PhD
Trends in Mortality Following Hip Fracture in Older Women
Joan C. Lo, MD; Sowmya Srinivasan, MD; Malini Chandra, MS, MBA; Mary Patton, MD; Amer Budayr, MD; Lucy H. Liu, MD; Gene Lau, MD; and Christopher D. Grimsrud, MD, PhD
Long-Term Outcomes of Analogue Insulin Compared With NPH for Patients With Type 2 Diabetes Mellitus
Julia C. Prentice, PhD; Paul R. Conlin, MD; Walid F. Gellad, MD, MPH; David Edelman, MD; Todd A. Lee, PharmD, PhD; and Steven D. Pizer, PhD
Factors Affecting Medication Adherence Trajectories for Patients With Heart Failure
Deborah Taira Juarez, ScD; Andrew E. Williams, PhD; Chuhe Chen, PhD; Yihe Goh Daida, MS; Sara K. Tanaka, MPH; Connie Mah Trinacty, PhD; and Thomas M. Vogt, MD, MPH

Cost Differential by Site of Service for Cancer Patients Receiving Chemotherapy

Jad Hayes, MS, ASA, MAAA; J. Russell Hoverman, MD, PhD; Matthew E. Brow, BA; Dana C. Dilbeck, BA; Diana K. Verrilli, MS; Jody Garey, PharmD; Janet L. Espirito, PharmD; Jorge Cardona, BS; and Roy Beveridge, MD
The cost of care for patients receiving chemotherapy in community oncology clinics is lower than for comparable patients receiving chemotherapy in the hospital outpatient setting.
ABSTRACT
Objectives:
To compare the costs of: 1) chemotherapy treatment across clinical, demographic, and geographic variables; and 2) various cancer care-related cost categories between patients receiving chemotherapy in a community oncology versus a hospital outpatient setting.

Study Design: Data from the calendar years 2008 to 2010 from the Truven Health Analytics MarketScan Commercial Claims and Encounters Database were analyzed. During 2010, the data set contained approximately 45 million unique commercially insured patients with 70,984 cancer patients receiving chemotherapy. These patients were assigned to cohorts depending on whether they received chemotherapy at a community oncology or hospital outpatient setting.

Methods: Cost data for 9 common cancer types were extracted from the database and analyzed on a per member per month basis to normalize costs; costs included amounts paid by the payer and patient payment. Community oncology and hospital outpatient setting chemotherapy treatment costs were categorized and examined according to cancer diagnosis, patient demographics, and geographic location.

Results: Patients receiving chemotherapy treatment in the community oncology clinic had a 20% to 39% lower mean per member per month cost of care, depending on diagnosis, compared with those receiving chemotherapy in the hospital outpatient setting. This cost differential was consistent across cancer type, geographic location, patient age, and number of chemotherapy sessions. Various cost categories examined were also higher for those treated in the hospital outpatient setting.

Conclusions: The cost of care for patients receiving chemotherapy was consistently lower in the community oncology clinic compared with the hospital outpatient setting, controlling for the clinical, demographic, and geographic variables analyzed.

Am J Manag Care. 2015;21(3):e189-e196
This study demonstrates that cost of care for chemotherapy patients is lower in the community oncology clinic than the hospital outpatient setting.
  • Mean per member per month cost of care, depending on diagnosis, was 20% to 39% lower for those receiving chemotherapy in a community oncology clinic compared with the hospital outpatient setting.
  • Cost differential was consistent across diagnosis, geography, patient age, and number of chemotherapy sessions.
  • As a larger proportion of oncology services are being provided in the hospital outpatient setting, policy makers and payers should be aware that shifts in sites of service may negatively impact cancer spending.
Although cancer death rates have consistently decreased because of improved early detection, prevention, and treatment, the cost of cancer care has significantly increased in conjunction with these accomplishments.1 The National Institutes of Health estimated that the United States spent $89 billion on the treatment of cancer in 2007.1 Given the total 2011 national health expenditure of $2.7 trillion—which is more than 10 times the $256 billion spent in 1980—cancer represents approximately 4% of all healthcare costs in the country.2,3 As cancer patients live longer and consume more healthcare dollars, this percentage will likely increase.2 Within a system of limited resources, maximizing patient outcomes and minimizing costs are primary concerns. Chemotherapy is a common cancer treatment modality that contributes significantly to the overall high cost of cancer treatment. Within the population diagnosed with cancer, approximately 22% of patients will receive chemotherapy in a given year.4 In a commercial population, cancer patients make up about 0.68% of a population but account for about 10% of the overall healthcare cost.4

Chemotherapy is administered in a variety of settings, although the majority is administered as outpatient treatment.5 For outpatient sites of care, patients predominantly receive treatment at a hospital outpatient (HOP) department or community oncology clinic (COC). In recent years, market conditions have caused some medical oncologists to shift from community to hospital sites of service, and as a result, a larger proportion of oncology services are being provided in the HOP setting.2,6 In a review of CMS claim payments, it was noted that the share of fee-for-service chemotherapy administration procedure claims in the HOP increased considerably over time—from 13.5% in 2005, to 33% in 2011.6 In a time of scarce healthcare resources and increased scrutiny around healthcare spending, how this shift in the site of care impacts oncology costs bears consideration.

The objectives of this study were to compare the costs of: 1) chemotherapy across clinical, demographic, and geographic variables; and 2) various cancer care-related cost categories between patients receiving chemotherapy in a COC setting with those receiving chemotherapy in an HOP setting.

METHODS

Data

This study is based on data culled from the Truven Health Analytics MarketScan Commercial Claims and Encounters Database, which contains eligibility, demographic, and medical and pharmacy claims data for commercially insured members (patients). During 2010, the data set contained 45,239,752 unique lives covered by commercial insurance plans. The data analyzed for this study included patient demographic, geographic, facility, physician claims, pharmacy claims, and plan eligibility information for calendar years 2008 to 2010.

Member Identification and Exclusion

To be included in the study, a patient had to first have 1 facility or 2 physician claims with an International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis code for 1 of the cancer types listed in Table 1. All diagnosis codes (eg, primary diagnosis, secondary diagnosis) were used. Laboratory and radiology claims, however, were not used. Patients with a diagnosis of multiple cancer types were assigned to 1 type, according to the hierarchical list in Table 1. Patients were also required to have at least 1 chemotherapy drug claim, defined according to the Health Care Financing Administration Common Procedural Coding System and National Drug Codes. Study participants were identified if they met these criteria in calendar years 2008 to 2009; claims were accrued for 2008 to 2010 to allow for a larger exposure period.

Patients were excluded if they did not have cancer (n = 43,854,833); were not concurrently receiving chemotherapy (n = 1,244,899); had HIV/AIDS or an organ transplant (n = 20,937); had <2 physician cancer claims and no facility cancer claims (n = 37,804); had <90 days of insurance eligibility beginning with the first date of service (DOS) for chemotherapy (n = 874); had chemotherapy administration at both HOP and COC facilities (n = 7659); or had leukemia (these patients were excluded because of a large difference in age between cohorts) (n = 1762). We did not exclude based on age. The oldest patients we found (commercially-insured, no Medicare) were born in 1943 and the youngest were born in 2009; 2008 and 2009 were used for identification, so some patients were aged ~1 year (albeit very few).

Eligible patients were grouped into 2 cohorts depending on the site of service (ie, COC vs HOP) for their chemotherapy administration. Place of service (POS) from the claims was used to determine the setting, with a POS of 11 used to indicate claims at a physician's office, and a POS of either 22 or 95 used to indicate a claim in the outpatient setting. Patients with chemotherapy in both settings were excluded, as parsing the data would have been challenging.

Claims Mapping and Accrual

Costs—the amount paid by the payer and excluding patient payment—including chemotherapy drug costs, were accrued for calendar years 2008 to 2010, beginning with the first DOS for chemotherapy. Claims with a trauma diagnosis were excluded; this was a claims-level exclusion, not a member-level exclusion. Member months were calculated beginning with the first DOS for chemotherapy and continuing for as long as a member maintained his or her plan eligibility or if no more data were available. Months were included on a fractional basis (ie, number of days included/ number of days in that month), allowing for analysis of partial months.

The per member per month (PMPM) costs (adjusted for disease mix between the HOP and the COC cohorts) were evaluated according to cancer type, geographic location (ie, urban, suburban, rural), patient age, and number of chemotherapy sessions. Other cost categories, including inpatient, outpatient/physician office, or emergency department site of service; chemotherapy drugs; supportive care drugs (eg, anti-emetics, anti-infectives); other drug costs; and other medical expenses were also evaluated according to the setting of chemotherapy drug administration (ie, COC vs HOP). Costs associated with inpatient and/or emergency department sites of service may have reflected treatment- or disease-related complications, adverse reactions to chemotherapy, practice patterns, patient frailty, or other effects.

Geographical Considerations

The Truven Health Analytics MarketScan Database contains the Metropolitan Statistical Area (MSA) in which each member resides. To group patients into urban, suburban, and rural, we used the US Census Bureau’s estimate of the population of the MSA as of July 2011. MSAs with ≥1,000,000 inhabitants were classified as urban, those with >100,000 but <1,000,000 were classified as suburban, and those with ≤100,000 were classified as rural. Any patients living outside of the MSA areas were classified as rural.

Statistical Considerations

Statistical analysis for difference in mean PMPM cost was performed using the Mann-Whitney U test. A linear regression was fitted to determine whether or not a variety of covariates impacted cost, and how much of the total variation was explained by these covariates. The covariates evaluated were cancer type, gender, number of chemotherapy sessions, and geographic location. Covariate analysis included only data available through claims. Differences in populations according to clinical risk profile or severity of illness were not captured in the claims data and therefore could not be analyzed.

RESULTS

The analysis was computed on a PMPM basis to normalize costs. Conditions included 9 common cancer types (Table 1). These types represented approximately 80% of all patients diagnosed with cancer in the database, providing a comprehensive view of spending while avoiding examination of very small patient populations. A total of 70,984 patients were identified and grouped into either the COC or HOP cohorts. Eighty percent (n = 56,649) of patients received their treatment in a COC setting, whereas 20% (n = 14,335) received treatment in a HOP setting.

Gender distribution between the COC and HOP cohorts was similar. However, the mean age in the COC cohort was higher for all disease states, with the largest being a 4.9-year difference for lymphoma patients. All other disease states had mean age differences within 2 years (Table 1).

Costs and Utilization

The COC cohort had an overall mean PMPM cost of $6578—30% lower than the HOP cohort’s overall mean PMPM cost of $9412 (P <.001). This difference was 20% to 39% lower in the COC cohort, depending on diagnosis, and was statistically significant for each cancer type evaluated (P <.001) (Table 2). The cost differential was consistently higher for patients receiving chemotherapy in the HOP cohort across each cancer type (Table 2), regardless of whether a patient was in an urban, suburban, or rural area (data not shown). The cost differential was also consistently higher in the HOP cohort across year of birth (Figure 1A) and number of chemotherapy sessions (Figure 1B). Interestingly, the mean number of chemotherapy administrations per member was higher for the COC cohort (16.9) than the HOP cohort (14.6), whereas the mean number of eligible months was lower for the COC cohort (18.2) than the HOP cohort (18.7). All else being equal, we would have expected more administrations in less time to result in higher PMPM chemotherapy treatment cost.

Differences in cost between the COC and HOP cohorts were also evident across numerous cost categories (Table 3); categories examined were: inpatient, outpatient/physician office, and emergency department site of service; chemotherapy drugs; supportive care drugs; other drugs; and other medical expenses. For all cancer types, the PMPM cost for the HOP cohort was higher in inpatient and outpatient/physician office sites of service and chemotherapy drug costs. Eight of 9 cancer types also had a higher PMPM cost for supportive care drugs in the HOP cohort (Table 4).

Regression Results

All covariates used in the model were statistically significant when used in a multivariate analysis with the exception of prostate cancer patients and patients living in an urban setting. The variables in the model only explain a small amount of the variation in PMPM cost, with R2 = 0.118 and F significance <.001 (Table 4). This means that our site-of-service model is able to explain 12% of the variation in cost from our data alone. The implication is that the variables we incorporated are significant, although other cost determinants exist that should be further evaluated in subsequent studies.

DISCUSSION

 
Copyright AJMC 2006-2018 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up