Using claims data to attribute patients with breast, lung, or colorectal cancer to prescribing oncologists.

BACKGROUND

Alternative payment models frequently require attribution of patients to individual physicians to assign cost and quality outcomes. Our objective was to examine the performance of three methods for attributing a patient with cancer to the likeliest physician prescriber of anticancer drugs for that patient using administrative claims data.

METHODS

We used the HealthCore Integrated Research Environment to identify patients who had claims for anticancer medication along with diagnosis codes for breast, lung, or colorectal lung cancer between July 2013 and September 2017. The index date was the first date with a record for anticancer medication and cancer diagnosis code. Included patients had continuous medical coverage from 6 months before index to at least 7 days after index. Patients who received anticancer drugs during the 6 months prior to index were excluded. The three methods attributed each patient to the physician with whom the patient had the most evaluation and management (E&M) visits within a 90-day window around the index date (Method 1); the most E&M visits with no time window (Method 2); or the E&M visit nearest in time to the index date (Method 3). We assessed the performance of the methods using the percentage of the study cohort successfully attributed to a physician, and the positive predictive value (PPV) relative to available physician-reported data on patient(s) they treat.

RESULTS

In total, 70,641 patients were available for attribution to physicians. Percentages of the study cohort attributed to a physician were: Method 1, 92.6%; Method 2, 96.9%; and Method 3, 96.9%. PPVs for each method were 84.4%, 80.6%, and 75.8%, respectively.

CONCLUSION

We found that a claims-based algorithm - specifically, a plurality method with a 90-day time window - correctly attributed nearly 85% of patients to a prescribing physician. Claims data can reliably identify prescribing physicians in oncology.

Déclaration de conflit d'intérêts

Disclosure Ezra Fishman, John Barron, Ying Liu, and Gosia Sylwestrzak are employees of HealthCore, Inc., a wholly owned, independently operated subsidiary of Anthem, Inc. Santosh Gautam at the time of this study was employed by HealthCore, Inc. Michael J Fisch is an employee of AIM Specialty Health, a wholly owned subsidiary of Anthem, Inc. Ann Nguyen is an employee of Anthem, Inc. Amol S Navathe reported grants from Hawaii Medical Service Association, Anthem Public Policy Institute, Cigna, and Oscar Health; personal fees from Navvis and Company, Navigant Inc., Lynx Medical, Indegene Inc., Sutherland Global Services, and Agathos, Inc.; personal fees and equity from NavaHealth; speaking fees from the Cleveland Clinic; serving as a board member of Integrated Services Inc. without compensation, and an honorarium from Elsevier Press, none of which are related to this manuscript. The authors report no other conflicts of interest in this work.