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The American Journal of Managed Care July 2018
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Differences in Spending on Provider-Administered Chemotherapy by Site of Care in Medicare
Yamini Kalidindi, MHA; Jeah Jung, PhD; and Roger Feldman, PhD
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Differences in Spending on Provider-Administered Chemotherapy by Site of Care in Medicare

Yamini Kalidindi, MHA; Jeah Jung, PhD; and Roger Feldman, PhD
Spending on chemotherapy drugs was lower among Medicare beneficiaries who received chemotherapy in hospital outpatient departments than among comparable beneficiaries receiving chemotherapy in physician offices.
Outcome Measures

We constructed 2 outcome measures: (1) chemotherapy drug spending per beneficiary and (2) chemotherapy administration spending per beneficiary. These spending variables are allowed payments, including both Medicare reimbursements and patient out-of-pocket spending. We constructed chemotherapy drug spending by summing the allowed payments across each patient’s chemotherapy claims with a cancer diagnosis code. Chemotherapy administration spending was created as the sum of the allowed payments across each patient’s claims with chemotherapy administration codes and a cancer diagnosis.


We began with a descriptive analysis of 6 cancer types (prostate, breast, lymphoma, colon, lung, and leukemia) for which Part B chemotherapy is frequently used. First, we compared the distribution of cancer types between HOPDs and physician offices. Second, we compared chemotherapy drug and administration spending per beneficiary between the 2 settings for the entire sample and for each cancer type.

We used a linear regression model with clustered standard errors within a zip code. Our unit of analysis was a patient-year. The dependent variables were chemotherapy drug spending and chemotherapy drug administration spending. The key explanatory variable was a binary indicator equal to 1 if the patient received provider-administered chemotherapy only in HOPDs and 0 if she/he received chemotherapy only in physician offices. Key control variables were cancer type indicators, an indicator of cancer metastasis, and the number of cancer-related hospitalizations and outpatient visits in the prior year. To identify metastasis, we used the criterion of at least 2 diagnosis codes of metastatic disease (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes 196-199) separated by 30 days or more.11-13

The regression also controlled for patient age, gender, race, state buy-in status (an indicator of whether Medicaid pays the patient’s Part B premium), indicators of chronic conditions (ischemic heart disease, diabetes, hypertension, hyperlipidemia, depression, heart failure, chronic pulmonary disease, and cataract), and number of chronic conditions. Area-level variables were average income, percent college educated, and unemployment rates at the zip code level. Finally, we used year dummies to control for year-specific effects that are common to all patients.

Using the regression results, we obtained risk-adjusted spending in each setting. To calculate risk-adjusted chemotherapy drug and administration spending in physician offices, we computed predicted spending by setting the HOPD indicator to 0 and all other covariates to their mean values. Similarly, we obtained risk-adjusted spending in HOPDs by computing predicted spending with the HOPD indicator equal to 1 and the means of all other covariates.

To explore whether chemotherapy utilization patterns differed between HOPDs and physician offices, we compared the number of chemotherapy and administration claims per beneficiary by cancer type. We also assessed spending per claim for chemotherapy drug and administration by cancer type.

Sensitivity Checks

We performed the following sensitivity checks. First, we performed the regression analysis by year to check if differences in a particular year were driving the overall regression results. We used the same variables as in the primary analysis (except year-specific dummies) and calculated risk-adjusted spending in HOPDs versus physician offices for each year.

Second, we performed the regression analysis separately for each of the 6 cancers (prostate, breast, lymphoma, colon, lung, and leukemia) to check if the results were consistent across major cancer types.

Third, we limited the analysis to separately reimbursable chemotherapy drugs (drugs that are not bundled into a payment group under the Medicare Hospital Outpatient prospective payment system). Medicare determines separately reimbursable drugs based on a threshold daily cost (>$80 in 2013). Chemotherapy drugs whose daily costs are below the threshold are considered a dependent or ancillary service to the drug administration. Their cost is “bundled” into an Ambulatory Payment Classification14 and arbitrarily allocated by hospitals. Including them in the analysis may lower the estimates of chemotherapy drug spending per beneficiary in HOPDs. We thus excluded nonseparately reimbursable drugs from both the Carrier and Hospital Outpatient files and checked the sensitivity of the results.

Last, we identified patients with ICD-9 codes of surgeries for certain cancers for which there is evidence of better outcomes.15 Individuals who underwent these surgeries are likely to use chemotherapy drugs as adjuvant therapy. We conducted the regression analysis on this subpopulation, who were relatively homogenous in terms of cancer severity, and checked the sensitivity of the results.

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