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The American Journal of Managed Care April 2017
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Physician Variation in Lung Cancer Treatment at the End of Life
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Physician Variation in Lung Cancer Treatment at the End of Life

Jonas B. Green, MD, MPH, MSHS; Martin F. Shapiro, MD, PhD; Susan L. Ettner, PhD; Jennifer Malin, MD, PhD; Alfonso Ang, PhD; and Mitchell D. Wong, MD, PhD
Patients receiving care for advanced non—small cell lung cancer in small, independent oncology practices are more likely to receive chemotherapy in the last 30 days of life.
ABSTRACT

Objectives:
To determine whether a treating oncologist’s characteristics are associated with variation in use of chemotherapy for patients with advanced non–small cell lung cancer (aNSCLC) at the end of life.

Study Design: Retrospective cohort.

Methods: Using the 2009 Surveillance, Epidemiology, and End Results–Medicare database, we studied chemotherapy receipt within 30 days of death among Medicare enrollees who were diagnosed with aNSCLC between 1999 and 2006, received chemotherapy, and died within 3 years of diagnosis. A multilevel model was constructed to assess the contribution of patient and physician characteristics and geography to receiving chemotherapy within 30 days of death.

Results: Among 21,894 patients meeting eligibility criteria, 43.1% received chemotherapy within 30 days of death. In unadjusted bivariate analyses, female sex, Asian or black race, older age, and a greater number of comorbid diagnoses predicted lower likelihood of receiving chemotherapy at the end of life (P ≤.038 for all comparisons). Adjusting for patient and physician characteristics, physicians in small independent practices were substantially more likely than those employed in other practice models, particularly academic practices or nongovernment hospitals, to order chemotherapy for a patient in the last 30 days of life (P <.001 for all comparisons); female physicians were less likely than males to prescribe such treatment (P = .04).

Conclusions: Patients receiving care for aNSCLC in small independent oncology practices are more likely to receive chemotherapy in the last 30 days of life.

Am J Manag Care. 2017;23(4):216-223
Takeaway Points

Oncologists’ characteristics explain significant variation in patients’ receipt of chemotherapy in the last 30 days of life:
  • Patients should understand the variation in practices among oncologists treating the same condition.
  • Awareness of such variation may influence an individual oncologist’s practice decisions and eventually lead to consensus practices at end of life; practices may already have changed since the period under study.
  • Less variation is likely to yield better alignment between patient goals and treatment received, and result in higher value care at the end of life.
  • Payers may wish to consider oncologist practice type in determining network participation.
Despite a half century of treatment advances, lung cancer—the most common solid tumor in the United States—remains among the cancers least responsive to treatment.1 A majority of patients are diagnosed at an advanced stage and, even with the newest therapies, barely 1 in 10 are alive a year after diagnosis.2,3 In the final weeks of life, many patients with advanced non–small cell lung cancer (aNSCLC) undergo aggressive treatment that can include repeated emergency department visits, prolonged hospitalizations, intensive care, and additional lines of chemotherapy that contravene guidelines.4-8 Attendant effects on quality of life are well documented, and the value of such expensive treatment is debated in the lay, clinical, and policy realms.9-11

Why aggressive end-of-life treatment occurs is not clearly understood. Regional variations in the aggressiveness of cancer treatment have been well established and patient factors have been explored12,13; however, the degree of variation between individual physicians is not known.14,15 We conducted this study to determine the extent to which physician characteristics explain patients’ receipt of chemotherapy in the 30 days prior to death among patients with aNSCLC.

METHODS

Sources of Data

We used the 2009 Surveillance, Epidemiology, and End Results (SEER) cancer registry and linked Medicare claims16 to identify patients and describe treatment patterns. SEER regions include 28% of the US population. Approximately 68% of lung cancers diagnosed in SEER regions are in Americans older than 65 years.2 Using the Unique Physician Identification Number Registry, we linked the physician submitting a Medicare claim to their characteristics in the American Medical Association (AMA) Masterfile.17

Study Cohort

The Figure details the initial sample and number of patients dropped due to each exclusion criterion. We first identified all patients in the SEER registry diagnosed with lung cancer between 1999 and 2006. We selected 1999 due to changes in physicians’ unique identification codes that year and 2006 to allow for up to 3 years of data after diagnosis. We limited the sample to those 65 years or older at diagnosis who were enrolled in traditional Medicare Part A and Part B from at least 12 months prior to a first diagnosis of lung cancer until 3 years after diagnosis or until death. Patients with other incident cancers were excluded to avoid erroneously counting chemotherapy directed toward another cancer.

Among 193,200 subjects satisfying all conditions (ie, lung cancer, age ≥65, continuous enrollment in Medicare A and B, no other cancer), we excluded 4518 subjects who died on unknown dates and 123 subjects with charges for chemotherapy after their recorded date of death. Our cohort was then limited to 155,794 patients with stage 3b or 4 aNSCLC; an additional 38,311 were excluded for diagnosis dates out of range. We excluded 89,069 who had not received chemotherapy within 3 years of initial diagnosis and compared their characteristics with those who received chemotherapy. To avoid insufficient data biasing interpretation of physicians’ practice patterns, subjects were excluded if not treated by an identifiable oncologist who provided care to 5 or more patients in the sample. In sensitivity analyses, we evaluated the impact of physician characteristics on receipt of chemotherapy in the last 30 days of life for all physicians, irrespective of the number of patients seen, and physicians with 10 or more patients. Our final analytic sample comprised 21,894 aNSCLC subjects.

Construction of the Dependent Variable

Chemotherapy use was established by Medicare charges in outpatient, inpatient, or physician claims for chemotherapy-related encounters (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] diagnosis codes V58.1, V66.2, and V67.2), chemotherapy administration (ICD-9-CM procedure code 99.25; Current Procedural Terminology codes 96400-96549; Health Care Common Procedure Coding System codes J8530, J8560, J8600, J8610, J8999, Q0083-Q0085, and G0921-G0932; and Revenue Center Codes 0331, 0332, and 0335), or chemotherapy agents (J Codes other than diethylstilbestrol and leuprolide). The primary outcome was whether a patient who ever received chemotherapy received a final dose during the last 30 days of life.

Patient–Physician Link

Administration of chemotherapy at the end of life was attributed to the oncologist submitting a Medicare claim with the latest date of service rendered prior to a patient’s death. Sensitivity analysis was performed, attributing the patient to the oncologist with the most visits. Physicians were considered oncologists if the billing physician’s specialties in either Medicare claims or AMA-linked physician files included oncology, hematology-oncology, or hematology.

Independent Variables

Patient were classified by race (white, black, Hispanic, Asian, other), sex, age at diagnosis (65-69, 70-74, 75-79, 80-84, ≥85 years), last known marital status, median income by zip code (by quartile, as a proxy for socioeconomic status), and year of diagnosis. Time between diagnosis and last chemotherapy was calculated and grouped (<1, 1, 2-3, 4-5, 6-7, 8-9, 10-11, 12-23, 24-36 months), as it was hypothesized that a recent diagnosis might be associated with receiving treatment at the end of life. We also included the proportion of blacks in the patient’s residential zip code and birthplace outside of the United States.

We calculated a modified Charlson Comorbidity Index score for each patient using ICD-9-CM–coded diagnoses from inpatient claims, carrier claims, and outpatient claims using the Wang method.18 In order to approximate patients’ health leading up to death, comorbidity scores were calculated from claims for services provided during the 12 months prior to the month of death.

Physician characteristics included in the model were sex and year that medical training was completed. Age was strongly correlated with year of training completion and thus excluded. We examined the type of practice based on the present employer variable from the AMA Masterfile and classified this variable into 6 categories: small independent (physician-owned, 1-2 physicians), group practice (physician-owned, >2 physicians), government (employed by city, county, state, or federal government), academic (employed by medical schools), hospital (employed by non–government-owned hospital), and other.

As there is good evidence supporting geographic variations in treatment practices, we sought to control for such variation based on SEER registry sites; however, because of its size and previously demonstrated practice variation,12 California was split by county into 4 zones: Los Angeles, non-LA Metro-South (San Diego, Riverside, San Bernardino, Orange, Ventura), Metro-North (San Francisco, Alameda, Santa Clara, Contra Costa, San Mateo, Marin), and Other. Rural Georgia, with just 47 eligible cases, was combined with Atlanta, yielding a single site for all of Georgia. SEER sites were otherwise categorized according to the SEER 17 registry.19

Statistical Analysis

Frequency distributions were calculated for patient, oncologist, and geographic variables. We used a multilevel logistic regression mixed model with dichotomous outcomes to estimate the probability of receiving chemotherapy treatment in the last 30 days of life. Patients were nested within physicians, who, in turn, were nested within geographic locations (SEER site, modified as above) as a random intercept at the highest level. The model adjusted for the patient and physician covariates, as described above. To facilitate interpretation of the magnitude of the effects, adjusted relative risks are presented along with the coefficient estimates and P values from the regression.

To calculate the marginal effect of the physician’s type of practice on receiving chemotherapy at the end of life, each patient’s probability of receiving treatment was recalculated as if all received treatment under a uniform type of practice, adjusting for patient variables and other physician variables. This was repeated for each type of practice.

University of California, Los Angeles, Institutional Review Board approved the study.

 

RESULTS


We identified 23,687 continuously enrolled Medicare (parts A and B) patients diagnosed with aNSCLC between 1999 and 2006. Table 1 shows the distribution of patient characteristics and associated probability of receiving chemotherapy within 30 days of death, among the 21,894 (92.4%) patients receiving chemotherapy within 3 years of diagnosis. Of these, 9447 (43.1%) received chemotherapy within 30 days of death.

In bivariate analyses, men were more likely than women to receive chemotherapy near the end of their lives (45.9% vs 39.5%; P <.001) (Table 1). Patients were less likely to receive chemotherapy at the end of life if they were Asian (33.3%) or black (40.0%) compared with whites (43.9%; P <.001), older (40.8% among those aged ≥85 vs 44.4% among those aged 65-69; P = .04), had more comorbidities (P = .001), or diagnosed in 2005 (37.8%) or 2006 (37.5%) compared with 1999 (43.9%) (P <.001). Despite these differences in treatment, none of these variables were associated with a difference in survival (data not shown).

Characteristics of the 89,069 patients excluded for nonreceipt of chemotherapy matched closely on race, sex, year of diagnosis, and SEER site categories. Younger patients and those with low comorbidity scores were more likely to have started chemotherapy than those who were older and sicker; females were slightly more likely than males to have never received chemotherapy.

Physician characteristics and the numbers of patients attributed to physicians with each characteristic are shown in Table 2. Oncologists were primarily male (77.4%) and in group practices (61.2%). Physicians in small independent practices were significantly more likely to administer chemotherapy during the last 30 days of life (Table 2). Adjusting for all patient and provider covariates, the predicted probability of receiving chemotherapy in the last 30 days of life was 1.4-fold greater (0.56) for patients receiving care in small independent practices relative to those seeing oncologists in academic centers (0.40; P <.001) (Table 3). Predicted probabilities for patients receiving care in group practices, government facilities, hospitals, and other types of practice, were 0.55, 0.46, 0.42, and 0.52, respectively. Female oncologists were significantly less likely to administer chemotherapy at end of life (P <.001). Magnitude and direction of predictors were not meaningfully changed when analyses were repeated for patients of physicians treating at least 10 patients.

 
Copyright AJMC 2006-2017 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
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