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Sensitivity of Medicare Data to Identify Oncologists

Sensitivity of Medicare Data to Identify Oncologists Background: Health services researchers have studied how care from oncologists impacts treatment and outcomes for cancer patients. These studies frequently identify physician specialty using files from the Center for Medicare and Medicaid Services (CMS) or the American Medical Association (AMA). The completeness of the CMS data resources, individually or combined, to identify oncologists is unknown. This study assessed the sensitivity of CMS data to capture oncologists included in the AMA Physician Masterfile. Methods: Oncologists were identified from three CMS data resources: physician claims, the National Plan and Provider Enumeration System Registry, and the Medicare Data on Provider Practice and Specialty file. CMS files and AMA data were linked using a unique physician identifier. Sensitivity to identify any oncologists, radiation oncologists (ROs), surgical oncologists (SOs), and medical oncologists (MOs) was calculated for individual and combined CMS files. For oncologists in the AMA data not identified as oncologists in the CMS data, their CMS specialty was assessed. Results: Individual CMS files each captured approximately 83% of the 17 934 oncologists in the AMA Masterfile; combined CMS files captured 90.4%. By specialty, combined CMS data captured 98.2% of ROs, 89.3% of MOs, and 70.1% of SOs. For ROs and SOs in the AMA data not identified as oncologists in the CMS data, their CMS specialty was usually similar to the AMA subspecialty; ROs were radiologists and SOs were surgeons. Conclusion: Using combined files from CMS identified most ROs and MOs found in the AMA, but not most SOs. Determining whether to use the AMA data or CMS files for a particular research project will depend on the specific research question and the type of oncologist included in the study. Researchers frequently use health data, such as Medicare Individual physicians can be identified from Medicare claims claims or the linked Surveillance, Epidemiology, and End by using the National Provider Identifier (NPI), a unique number Results (SEER) cancer registry-Medicare files, to study treat- assigned to each physician by the Center for Medicare and ment and outcomes for cancer patients. These data can be Medicaid Services (CMS) that is used as the required identifier used to assess the role of physicians in population-based can- on health-care claims. Some researchers analyzing the cer care by determining how physician specialty impacts the Medicare data will determine if a physician is an oncologist by type of treatment and outcomes for patients (1–11). For exam- linking the NPIs on the Medicare claims to the American ple, a prior SEER-Medicare study demonstrated that individual Medical Association (AMA) Physician Masterfile, which includes radiation oncologists had a statistically significant role in de- physician specialty (12). However, data from the AMA Masterfile termining if women with breast cancer received hypofractio- are expensive, limiting its accessibility to some researchers. To nated radiation therapy (1). Another study reported that overcome the cost of the AMA data, some researchers have African American patients with pancreatic cancer were less used files available from CMS to determine physician specialty. likely to consult a cancer specialist and receive recommended The availability of specialty information on CMS files varies by treatment than white patients (5). the data resource. Physician claims from CMS include the Received: November 19, 2019; Revised: November 4, 2019; Accepted: November 19, 2019 Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US. 60 Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 J. L. Warren et al. |61 performing physician’s self-reported specialty, and they are percent of the US population. Each registry collects information readily accessible to researchers who have obtained claims. on all newly diagnosed cancers occurring in a defined geo- CMS also maintains two other data resources that have infor- graphic region. The SEER-Medicare data link persons in the mation about physician specialty, including oncology: the SEER data to their Medicare files, if they are eligible for and en- National Plan and Provider Enumeration System (NPPES) rolled in Medicare (17). The Medicare data include information Registry (13), which can be downloaded for free, and the for each beneficiary about Medicare eligibility (parts A and B) Medicare Data on Provider Practice and Specialty (MD-PPAS) file and health maintenance organization or fee-for-service enroll- (14), which is available at a nominal annual cost. ment. For beneficiaries with fee-for-service coverage, the SEER- The availability of different data resources that include in- Medicare data include claims submitted by providers. Medicare formation about physician specialty presents researchers with claims from physicians include the NPI and self-reported spe- uncertainty about which files are the best to identify oncolo- cialty for the treating physician. gists. Prior studies have found that the AMA Masterfile includes more oncologists than are identified from Medicare claims NPPES Registry. (15,16). However, these prior studies did not assess the other, The NPPES Registry, maintained by CMS, is a complete reposi- aforementioned, CMS data resources to identify oncologists. tory of NPIs for individual providers, physicians, other health- The purpose of this study was to assess the utility of all data care providers, and health-care organizations. NPIs have been resources available from CMS—Medicare claims, the NPPES the standard identifier for all health-care providers covered by Registry, and the MD-PPAS file—to identify oncologists. The the Health Insurance Portability and Accountability Act since analysis used the AMA data specialty classification compared 2007 (13). NPIs are assigned when a health-care provider enrolls with individual CMS data resources, as well as combinations of in the NPPES Registry. Medical specialty is self-reported by the CMS data resources, to determine the sensitivity of the CMS physicians at the time that they apply for an NPI. Physicians data to identify oncologists reported in the AMA data. For physi- may report one primary specialty and up to 14 secondary spe- cians who were correctly identified as oncologists in the CMS cialties. Specialties are coded in the NPPES data using standard- data, we compared the listed oncology specialty (radiation, sur- ized Healthcare Provider Taxonomy Codes established by the gical, or medical oncologist) in the AMA and CMS data. For National Uniform Claim Committee (18). Data as of June 2017 oncologists in the AMA data who were not identified as oncolo- were included in this analysis. gists in any CMS data resource, we examined the specialty that was reported on the CMS files. The composite of this informa- MD-PPAS File. tion will provide researchers with an in-depth understanding of The MD-PPAS file has been produced annually by CMS since each CMS data resource’s utility to identify oncologists for stud- 2008. The goal of the file is to provide enhanced information ies related to practice patterns and outcomes. about individual provider’s practice and specialty. The annual MD-PPAS files contain a record for any provider who had a valid NPI and submitted a part B noninstitutional claim for evaluation Methods and management services, procedures, imaging, or nonlabora- tory testing during the year (14). For this analysis, the MD-PPAS Data Resources files from 2008 to 2015 were included. The annual files include AMA Physician Masterfile. each provider’s NPI, demographic information, and specialty. The AMA Physician Masterfile (AMA data) is a database that Specialty is self-reported when the provider enrolls in maintains current and historical information for all physicians, Medicare’s Provider Enrollment, Chain and Ownership System medical residents, and students in the United States, including (PECOS), using the same specialty codes as those on the physi- doctors of medicine and doctors of osteopathy (12). The AMA cian claims. Providers are required to enroll in the PECOS sys- data contain more than 1.4 million US physicians, including tem to receive payment from Medicare, and they must more than 400 000 foreign medical graduates who are certified revalidate their PECOS data annually. The PECOS system allows to practice in the United States. Information about each physi- providers to report two specialties, but almost all physicians re- cian in the AMA data is compiled from multiple sources. The port only one. A small number of physicians do not report a spe- AMA assigns a unique number to every student entering a US cialty on the PECOS file. For physicians who do not have a medical school and verifies his or her graduation with the specialty on the PECOS file, their specialty is determined from Association of American Medical Colleges. Physician specialty the physician claims used to create the MD-PPAS file. In cases information is obtained from residency programs and the where more than one type of specialty is reported on the claims, American Board of Medical Specialty certification. The the PECOS file includes the most frequently reported specialty American Board of Medical Specialty captures graduates of US on the claims. and international medical schools. Physicians may update their practice data through self-report to the AMA at any time. The Identification of Oncologists and Other Physician AMA data include information such as the physician’s NPI, Specialties medical school and residency training, state where the physi- cian’s practice is located, primary and, if reported, secondary Study Population. specialty, and type of practice (primary physician activity is di- Physicians were eligible for inclusion in the study if they were rect patient care, teaching, administration, etc.). included in the AMA data and either their primary or secondary specialty was oncology per the AMA as of July 2017. If more Physician Claims Included on the SEER-Medicare Data. than one oncology specialty was reported on the AMA data, the The SEER registries are funded by the National Cancer Institute specialty was assigned in the following hierarchical order: radi- and include population-based cancer registries that, at the time ation oncologist (RO), surgical oncologist (SO), and medical on- of data analysis, captured all incident cancers occurring in 28% cologist (MO). Furthermore, physicians were only included if Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 62 | J Natl Cancer Inst Monogr, 2020, Vol. 2020, No. 55 Table 1. Codes used to define oncologists in the AMA and CMS data resources Medicare physician claims and AMA data* MD-PPAS NPPES Category† Oncology specialty Codes Codes Codes Any oncologist Any of the specialties below See below See below See below Radiation oncologist Radiation oncology RO 92 2085R0001X Surgical oncologist Surgical oncology SO 91 2086X0206X Advanced surgical oncology ASO N/A N/A Gynecological oncology GO 98 207VX0201X Medical oncologist Medical oncology MO, ON 90 207RX0202X Hematology HEM, HMP 82 207RH0000X Hematology/Oncology HO 83 207RH0003X *Only physicians whose type of practice was listed as direct patient care were included. AMA ¼ American Medical Association; CMS ¼ Center for Medicare and Medicaid Services; MD-PPAS ¼ Medicare Data on Provider Practice and Specialty; NPPES ¼ National Plan and Provider Enumeration System; N/A ¼ no applicable code. †If more than one oncology specialty was listed within each data resource, oncology specialty was assigned using a hierarchical approach: 1) radiation oncologist; 2) surgical oncologist, and 3) medical oncologist. their type of practice listed in the AMA data was direct patient studies of cancer treatment and outcomes (19–25). We calcu- care because these physicians were likely to submit claims to lated the sensitivity of each of the CMS data resources to cap- Medicare and, thus, be included in the other files being ture any oncologist, ROs, SOs, and MOs, respectively. In addition assessed. Of the AMA oncologists, 19.5% (n¼ 4338) were ex- to assessing the sensitivity of the individual CMS data resour- cluded because they did not provide direct patient care. ces, we also assessed the sensitivity when these files were com- bined (ie, the physician claims and NPPES Registry, the physician claims and the MD-PPAS file, the NPPES Registry and the MD-PPAS file, or all of the CMS files). Classification of Physician Specialty Oncology and oncology specialties (ROs, SOs, and MOs) were identified as shown in Table 1. Nononcology physician special- Results ties were also possible in the CMS data resources; these special- There were 17 934 oncologists identified from the AMA data ties were identified as shown in the Supplementary Appendix (Table 2). Of these, 23.0% were ROs, 8.8% were SOs, and 68.2% (available online). On all CMS files, physician specialty was self- were MOs per the AMA data. Using only CMS physician claims, reported. For the physician claims and the MD-PPAS file, we 84.0% of all AMA oncologists were identified, although the sen- used codes developed by CMS for the performing provider spe- sitivity of the claims to capture oncologists varied by specialty. cialty variable and primary specialty, respectively. On the Physician claims identified 95.4% of ROs, 53.0% of SOs, and NPPES file, specialty was identified from taxonomy codes. 83.3% of MOs. Similar results were observed for the NPPES Some of the data resources allowed for multiple specialties to Registry and the MD-PPAS file, which captured 82.8% and 82.5% be listed creating the possibility for different specialties to be of all oncologists, respectively. Both the NPPES Registry and the reported within a file or between files. To assign a physician spe- MD-PPAS file captured more than 90% of ROs and 82% of MOs. cialty for the CMS data resources, we developed a hierarchical ap- Ascertainment of SOs varied between the NPPES Registry proach. First, within each data resource, if there was any (59.8%) and the MD-PPAS file (46.0%). The utility of the CMS data indication that a physician was an oncologist, he or she was clas- resources to identify type of oncologist improved when files sified as such. Then, among the physicians who were identified were combined. Using a combination of the three CMS data as oncologist, oncology specialty was assigned in the following resources to identify any oncologists improved sensitivity to hierarchical order: RO, SO, and MO. For example, if two oncology more than 90% and resulted in identification of 98.2% of ROs, specialties (RO and SO) were listed in a file for the same physi- 70.1% of SOs, and 89.3% of MOs. The ability to identify oncolo- cian, then the higher-ranked specialty (RO) was assigned. This gists using the physician claims combined with the NPPES file same hierarchical approach was used to consolidate oncology was similar to the combination of all three CMS data resources. specialties across CMS data resources. Within the CMS data We compared the AMA and CMS files for agreement about resources, there were physician specialties other than oncolo- oncology specialty. There were 128 physicians who were classi- gists. We wanted to classify these nononcologists into groups. To fied as oncologists in both the AMA and at least one CMS data consolidate physicians’ information within and across the CMS resource, but there was disagreement between the two data data resources, we extended our hierarchical approach for non- sources about the specific oncology specialty. This accounted oncology specialties in the following order: radiology, surgery, for less than 1% of all physicians (data not shown). In addition, “other” medical specialty, hospital-based, and primary care (see there were 84 physicians (<0.5%) who had conflicting types of Supplementary Appendix, available online) These physicians oncology specialties between the CMS files, independent of were only identified from the CMS data resources. their AMA specialty. For the 1730 physicians (RO: 70; SO: 461; MO: 1199) who were identified as an oncologist in the AMA data but not determined to be an oncologist in any CMS data re- Analysis source, we identified their specialties as reported in the CMS The AMA data were considered the gold standard to identify files (Table 3). For these 1730 AMA-classified oncologists, the oncologists because of the extent that it has been used in most frequent specialties listed in the CMS data for these Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 J. L. Warren et al. |63 Table 2. Sensitivity of different CMS data resources to identify oncologists reported in the AMA Physician Masterfile* Type of Oncology Specialty† Radiation Surgical Medical Any oncologist oncologists oncologists oncologists (n¼ 17 934) (n¼ 4123) (n¼ 1575) (n¼ 12 236) n (%)‡ n (%)‡ n (%)‡ n (%)‡ Using Single CMS File Physician Claims only 15 073 (84.0) 3935 (95.4) 834 (53.0) 10 188 (83.3) NPPES Registry 14 844 (82.8) 3730 (90.5) 942 (59.8) 10 098 (82.5) MD-PPAS File only 14 802 (82.5) 3958 (96.0) 724 (46.0) 10 041 (82.1) Combined Files Using Physician Claims and NPPES Registry 16 136 (90.0) 4043 (98.1) 1095 (69.5) 10 872 (88.9) Physician Claims and MD-PPAS file 15 470 (86.3) 4017 (97.4) 873 (55.4) 10 458 (85.5) NPPES Registry and MD-PPAS 16 061 (89.6) 4041 (98.0) 1059 (67.2) 10 879 (88.9) All of the CMS Files 16 204 (90.4) 4048 (98.2) 1104 (70.1) 10 924 (89.3) *The Physician Masterfile served as the gold standard for identifying oncologists. AMA¼ American Medical Association; CMS¼ Center for Medicare and Medicaid Services; MD-PPAS¼ Medicare Data on Provider Practice and Specialty; NPPES¼ National Plan and Provider Enumeration System. †Oncologic specialties classified in hierarchical order (radiation, surgical, medical). ‡Number and percent of oncologists identified in the AMA Masterfile who were found to have concordant specialty in the CMS data. physicians were hospital-based specialty, surgery, and primary specialty on the AMA data (eg, ROs reported as radiologists, SOs care. There were 3.6% AMA oncologists who had a NPPES taxon- reported as surgeons). There was a small percent of physicians omy code of “specialist” (174400000X), which was outside the in the NPPES file who had a taxonomy code for “specialty.” We typical range of taxonomy codes for physicians (eg, codes that manually reviewed a subset of 25 providers with the taxonomy begin with 20). code for “specialty” and searched for their type of practice on The CMS-reported specialty varied when stratified by the the internet. These providers were found to be involved in a AMA-defined oncology specialty. For physicians who were ROs range of medical services, including oncologists, prosthetic in the AMA data, radiology was the most frequently reported designers, and counselors. The numerous types of services in- specialty in the CMS data, although the frequency varied by cluded under this taxonomy code means that it is not useful for CMS data resource. A similar pattern was observed for AMA- imputing that a physician is an oncologist. defined SOs, with more than 85% having a surgery specialty in Some investigators using Medicare claims alone to study each of the CMS files. For medical oncologists in the AMA data, cancer care have assigned physician specialty through the CMS the most common specialties in the CMS data were hospital- specialty codes or by looking at services that are specific to can- based and primary care. Of the doctors identified as providing cer (3,5). Using this approach, if there is a claim for chemother- primary care, 90% or more reported an internal medicine spe- apy or radiation therapy, the physician is considered a medical cialty in all CMS files (data not shown). oncologist or radiation oncologist, respectively, regardless of the CMS specialty code. Such an approach may be an option for chemotherapy and radiation therapy, however, it is more com- Discussion plex for surgical treatment. Many surgeries are not specific to cancer (eg, hemicolectomy) and are commonly performed by Our analysis demonstrated that individual CMS data resources have more than 80% sensitivity to capture any oncologists as both surgeons and surgical oncologists. For surgeries that are specific to cancer, it may be possible to identify from the claims reported in the AMA data. The completeness of the CMS data to identify any oncologist is improved by combining files. the frequency that a specific physician is performing these pro- cedures and develop a minimal threshold above which that Although using combined files from CMS can identify 90.4% of all oncologists, the files varied in sensitivity to identify specific physician is imputed to be a surgical oncologist. More evalua- tion of this approach and whether it would improve the ability oncology specialties. The CMS data, especially combined files, captured 98% of ROs and 89% of MOs. However, CMS data of Medicare claims to identify surgical oncologists is needed. We used the AMA data as the standard against which to com- resources, individually or combined, did not identify a sizeable portion of the SOs. Therefore, researchers who want to use CMS pare CMS data. The AMA data appear to include the vast majority of oncologists. A prior study that used Medicare claims, the CMS data to study treatment and outcomes for patients receiving care from SOs should consider linkage to the AMA data. These NPI Directory, and the AMA data to identify oncologists found that only 6% of oncologists were in the Medicare claims and the findings are similar to a prior study that found that using Medicare claims with the CMS NPI Directory (precursor to the CMS NPI Directory but not in the AMA data (16). The number of medical and radiation oncologists that we reported is consistent NPPES Registry) increased the percent of all oncologists identi- fied in Medicare claims by 36.1% (16). The same study also found with prior studies that have used the AMA data to report on the oncology workforce (26,27). However the number of SOs that we that the addition of AMA data markedly increased the identifi- cation of SOs. identified is nearly double that reported in these earlier studies. We attribute our higher number to the inclusion of both primary For physicians who were identified as oncologists in the AMA data but were not found to be oncologists in the CMS data, and secondary specialties reported on the AMA data. If we limited the identification of SOs to those with a primary specialty code, many had a CMS specialty that was similar to the oncology Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 64 | J Natl Cancer Inst Monogr, 2020, Vol. 2020, No. 55 our numbers would be similar to those in the prior reports. Becauseweusedboth primary andsecondary specialty inour analysis, there is the possibility that there could be conflicting on- cology specialties reported in the AMA data. This occurred in 101 oncologists in the AMA data (0.56% of physicians), 90 of whom were radiation oncologists who also listed medical oncology. ROs are required to complete an initial year of residency in specialties other than RO before beginning their RO training. In determining which data resource is most accurate and complete to identify oncologists, it is important to consider how physician specialties are initially assigned. The specialty infor- mation for each physician in the AMA data is obtained from the American Association of Medical Colleges, the American Board of Medical Specialties, and self-report from a survey of individual physicians. Data on specialty from CMS are self-reported at the time when a physician applies for an NPI or enrolls in the PECOS system, with regular updates to the PECOS system (14). Our anal- ysis assessed only those physicians who were oncologists. We did not have access to the entirety of AMA data or CMS data. Therefore, we were not able to assess the specificity of the CMS data to identify physicians who were not oncologists. Our findings support several recommendations regarding which data resources are best suited for researchers who are us- ing Medicare data to study the role of physician specialty in on- cology care. We conclude that researchers who want to identify any oncologist can use a combination of the assessed CMS data resources to capture 90% of oncologists. If a researcher opts to use only CMS data resources to identify oncologists, it appears that using Medicare claims and the NPPES Registry will capture almost the same number of oncologists as the combination of the Medicare claims, the NPPES Registry, and the MD-PPAS data. The NPPES data are public use and can be downloaded without charge from the CMS website (13). The MD-PPAS data are classi- fied by CMS as identifiable data and are released to researchers after a review process and payment for the file. In addition, our findings support the use of combined CMS data resources or even Medicare claims alone to identify ROs. If the focus of the analysis is on MOs, a researcher would need to consider whether the 89% sensitivity of the combined CMS data resour- ces for identifying MOs was sufficient and if the additional cost to obtain the AMA was worthwhile. Researchers involved in studies that require identification of SOs should use the AMA data to have more complete ascertainment of this specialty. In conclusion, this study has shown that in some situations, researchers can use combined CMS data resources to identify the vast majority of oncologists included in the AMA data. In these situations, researchers can forego the expense and the ad- ministrative process of acquiring the AMA data. However, stud- ies focusing on SOs and perhaps MOs should incorporated data from the AMA. The determination of which data are needed to identify oncologists will depend on the specific research ques- tion and the type of oncologist included in the study. Notes Affiliations of authors: National Cancer Institute, Division of Cancer Control and Population Science, Bethesda, MD (JLW, DPW, LE); Information Management Services, Calverton, MD (MJB, RB); Center for Medicare and Medicaid Services, Baltimore, MD (SC). The authors have no conflicts of interest to declare. The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views Table 3. Center for Medicare and Medicaid Services (CMS) Specialty for physicians identified as oncologists in the AMA data* but not in the CMS data All oncologists Radiation oncologists Surgical oncologists Medical oncologists (n¼ 1730) (n¼ 70) (n¼ 461) (n¼ 1199) Specialty per the Physician NPPES MD-PPAS Physician NPPES MD-PPAS Physician NPPES MD-PPAS Physician NPPES MD-PPAS CMS data† claims, % Registry, % file, % claims, % Registry, % file, % claims, % Registry, % file, % claims, % Registry, % file, % Radiology 2.6 2.3 2.5 52.9 44.3 52.9 0.2 0.2 0.0 0.6 0.6 0.6 Surgery 29.5 28.3 29.8 10.0 10.0 10.0 89.6 85.2 89.8 7.5 7.5 7.8 Medical specialty 4.2 4.6 4.0 8.6 10.0 8.6 0.9 1.1 0.9 5.2 5.6 4.9 Hospital-based 31.1 31.7 30.7 7.1 10.0 7.1 0.9 0.9 0.9 44.1 44.8 43.5 Primary care 28.5 27.7 33.0 20.0 17.1 21.4 6.5 6.3 8.5 37.4 36.5 43.1 Specialist‡ — 3.6 — — 5.7 — — 6.1 — — 2.5 — Missing/Other 4.2 1.9 0.0 1.4 2.9 0.0 2.0 0.2 0.0 5.2 2.5 0.0 *Only AMA Direct Patient Care Physicians were included. 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Sensitivity of Medicare Data to Identify Oncologists

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Oxford University Press
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Copyright © 2022 Oxford University Press
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1052-6773
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1745-6614
DOI
10.1093/jncimonographs/lgz030
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Abstract

Background: Health services researchers have studied how care from oncologists impacts treatment and outcomes for cancer patients. These studies frequently identify physician specialty using files from the Center for Medicare and Medicaid Services (CMS) or the American Medical Association (AMA). The completeness of the CMS data resources, individually or combined, to identify oncologists is unknown. This study assessed the sensitivity of CMS data to capture oncologists included in the AMA Physician Masterfile. Methods: Oncologists were identified from three CMS data resources: physician claims, the National Plan and Provider Enumeration System Registry, and the Medicare Data on Provider Practice and Specialty file. CMS files and AMA data were linked using a unique physician identifier. Sensitivity to identify any oncologists, radiation oncologists (ROs), surgical oncologists (SOs), and medical oncologists (MOs) was calculated for individual and combined CMS files. For oncologists in the AMA data not identified as oncologists in the CMS data, their CMS specialty was assessed. Results: Individual CMS files each captured approximately 83% of the 17 934 oncologists in the AMA Masterfile; combined CMS files captured 90.4%. By specialty, combined CMS data captured 98.2% of ROs, 89.3% of MOs, and 70.1% of SOs. For ROs and SOs in the AMA data not identified as oncologists in the CMS data, their CMS specialty was usually similar to the AMA subspecialty; ROs were radiologists and SOs were surgeons. Conclusion: Using combined files from CMS identified most ROs and MOs found in the AMA, but not most SOs. Determining whether to use the AMA data or CMS files for a particular research project will depend on the specific research question and the type of oncologist included in the study. Researchers frequently use health data, such as Medicare Individual physicians can be identified from Medicare claims claims or the linked Surveillance, Epidemiology, and End by using the National Provider Identifier (NPI), a unique number Results (SEER) cancer registry-Medicare files, to study treat- assigned to each physician by the Center for Medicare and ment and outcomes for cancer patients. These data can be Medicaid Services (CMS) that is used as the required identifier used to assess the role of physicians in population-based can- on health-care claims. Some researchers analyzing the cer care by determining how physician specialty impacts the Medicare data will determine if a physician is an oncologist by type of treatment and outcomes for patients (1–11). For exam- linking the NPIs on the Medicare claims to the American ple, a prior SEER-Medicare study demonstrated that individual Medical Association (AMA) Physician Masterfile, which includes radiation oncologists had a statistically significant role in de- physician specialty (12). However, data from the AMA Masterfile termining if women with breast cancer received hypofractio- are expensive, limiting its accessibility to some researchers. To nated radiation therapy (1). Another study reported that overcome the cost of the AMA data, some researchers have African American patients with pancreatic cancer were less used files available from CMS to determine physician specialty. likely to consult a cancer specialist and receive recommended The availability of specialty information on CMS files varies by treatment than white patients (5). the data resource. Physician claims from CMS include the Received: November 19, 2019; Revised: November 4, 2019; Accepted: November 19, 2019 Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US. 60 Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 J. L. Warren et al. |61 performing physician’s self-reported specialty, and they are percent of the US population. Each registry collects information readily accessible to researchers who have obtained claims. on all newly diagnosed cancers occurring in a defined geo- CMS also maintains two other data resources that have infor- graphic region. The SEER-Medicare data link persons in the mation about physician specialty, including oncology: the SEER data to their Medicare files, if they are eligible for and en- National Plan and Provider Enumeration System (NPPES) rolled in Medicare (17). The Medicare data include information Registry (13), which can be downloaded for free, and the for each beneficiary about Medicare eligibility (parts A and B) Medicare Data on Provider Practice and Specialty (MD-PPAS) file and health maintenance organization or fee-for-service enroll- (14), which is available at a nominal annual cost. ment. For beneficiaries with fee-for-service coverage, the SEER- The availability of different data resources that include in- Medicare data include claims submitted by providers. Medicare formation about physician specialty presents researchers with claims from physicians include the NPI and self-reported spe- uncertainty about which files are the best to identify oncolo- cialty for the treating physician. gists. Prior studies have found that the AMA Masterfile includes more oncologists than are identified from Medicare claims NPPES Registry. (15,16). However, these prior studies did not assess the other, The NPPES Registry, maintained by CMS, is a complete reposi- aforementioned, CMS data resources to identify oncologists. tory of NPIs for individual providers, physicians, other health- The purpose of this study was to assess the utility of all data care providers, and health-care organizations. NPIs have been resources available from CMS—Medicare claims, the NPPES the standard identifier for all health-care providers covered by Registry, and the MD-PPAS file—to identify oncologists. The the Health Insurance Portability and Accountability Act since analysis used the AMA data specialty classification compared 2007 (13). NPIs are assigned when a health-care provider enrolls with individual CMS data resources, as well as combinations of in the NPPES Registry. Medical specialty is self-reported by the CMS data resources, to determine the sensitivity of the CMS physicians at the time that they apply for an NPI. Physicians data to identify oncologists reported in the AMA data. For physi- may report one primary specialty and up to 14 secondary spe- cians who were correctly identified as oncologists in the CMS cialties. Specialties are coded in the NPPES data using standard- data, we compared the listed oncology specialty (radiation, sur- ized Healthcare Provider Taxonomy Codes established by the gical, or medical oncologist) in the AMA and CMS data. For National Uniform Claim Committee (18). Data as of June 2017 oncologists in the AMA data who were not identified as oncolo- were included in this analysis. gists in any CMS data resource, we examined the specialty that was reported on the CMS files. The composite of this informa- MD-PPAS File. tion will provide researchers with an in-depth understanding of The MD-PPAS file has been produced annually by CMS since each CMS data resource’s utility to identify oncologists for stud- 2008. The goal of the file is to provide enhanced information ies related to practice patterns and outcomes. about individual provider’s practice and specialty. The annual MD-PPAS files contain a record for any provider who had a valid NPI and submitted a part B noninstitutional claim for evaluation Methods and management services, procedures, imaging, or nonlabora- tory testing during the year (14). For this analysis, the MD-PPAS Data Resources files from 2008 to 2015 were included. The annual files include AMA Physician Masterfile. each provider’s NPI, demographic information, and specialty. The AMA Physician Masterfile (AMA data) is a database that Specialty is self-reported when the provider enrolls in maintains current and historical information for all physicians, Medicare’s Provider Enrollment, Chain and Ownership System medical residents, and students in the United States, including (PECOS), using the same specialty codes as those on the physi- doctors of medicine and doctors of osteopathy (12). The AMA cian claims. Providers are required to enroll in the PECOS sys- data contain more than 1.4 million US physicians, including tem to receive payment from Medicare, and they must more than 400 000 foreign medical graduates who are certified revalidate their PECOS data annually. The PECOS system allows to practice in the United States. Information about each physi- providers to report two specialties, but almost all physicians re- cian in the AMA data is compiled from multiple sources. The port only one. A small number of physicians do not report a spe- AMA assigns a unique number to every student entering a US cialty on the PECOS file. For physicians who do not have a medical school and verifies his or her graduation with the specialty on the PECOS file, their specialty is determined from Association of American Medical Colleges. Physician specialty the physician claims used to create the MD-PPAS file. In cases information is obtained from residency programs and the where more than one type of specialty is reported on the claims, American Board of Medical Specialty certification. The the PECOS file includes the most frequently reported specialty American Board of Medical Specialty captures graduates of US on the claims. and international medical schools. Physicians may update their practice data through self-report to the AMA at any time. The Identification of Oncologists and Other Physician AMA data include information such as the physician’s NPI, Specialties medical school and residency training, state where the physi- cian’s practice is located, primary and, if reported, secondary Study Population. specialty, and type of practice (primary physician activity is di- Physicians were eligible for inclusion in the study if they were rect patient care, teaching, administration, etc.). included in the AMA data and either their primary or secondary specialty was oncology per the AMA as of July 2017. If more Physician Claims Included on the SEER-Medicare Data. than one oncology specialty was reported on the AMA data, the The SEER registries are funded by the National Cancer Institute specialty was assigned in the following hierarchical order: radi- and include population-based cancer registries that, at the time ation oncologist (RO), surgical oncologist (SO), and medical on- of data analysis, captured all incident cancers occurring in 28% cologist (MO). Furthermore, physicians were only included if Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 62 | J Natl Cancer Inst Monogr, 2020, Vol. 2020, No. 55 Table 1. Codes used to define oncologists in the AMA and CMS data resources Medicare physician claims and AMA data* MD-PPAS NPPES Category† Oncology specialty Codes Codes Codes Any oncologist Any of the specialties below See below See below See below Radiation oncologist Radiation oncology RO 92 2085R0001X Surgical oncologist Surgical oncology SO 91 2086X0206X Advanced surgical oncology ASO N/A N/A Gynecological oncology GO 98 207VX0201X Medical oncologist Medical oncology MO, ON 90 207RX0202X Hematology HEM, HMP 82 207RH0000X Hematology/Oncology HO 83 207RH0003X *Only physicians whose type of practice was listed as direct patient care were included. AMA ¼ American Medical Association; CMS ¼ Center for Medicare and Medicaid Services; MD-PPAS ¼ Medicare Data on Provider Practice and Specialty; NPPES ¼ National Plan and Provider Enumeration System; N/A ¼ no applicable code. †If more than one oncology specialty was listed within each data resource, oncology specialty was assigned using a hierarchical approach: 1) radiation oncologist; 2) surgical oncologist, and 3) medical oncologist. their type of practice listed in the AMA data was direct patient studies of cancer treatment and outcomes (19–25). We calcu- care because these physicians were likely to submit claims to lated the sensitivity of each of the CMS data resources to cap- Medicare and, thus, be included in the other files being ture any oncologist, ROs, SOs, and MOs, respectively. In addition assessed. Of the AMA oncologists, 19.5% (n¼ 4338) were ex- to assessing the sensitivity of the individual CMS data resour- cluded because they did not provide direct patient care. ces, we also assessed the sensitivity when these files were com- bined (ie, the physician claims and NPPES Registry, the physician claims and the MD-PPAS file, the NPPES Registry and the MD-PPAS file, or all of the CMS files). Classification of Physician Specialty Oncology and oncology specialties (ROs, SOs, and MOs) were identified as shown in Table 1. Nononcology physician special- Results ties were also possible in the CMS data resources; these special- There were 17 934 oncologists identified from the AMA data ties were identified as shown in the Supplementary Appendix (Table 2). Of these, 23.0% were ROs, 8.8% were SOs, and 68.2% (available online). On all CMS files, physician specialty was self- were MOs per the AMA data. Using only CMS physician claims, reported. For the physician claims and the MD-PPAS file, we 84.0% of all AMA oncologists were identified, although the sen- used codes developed by CMS for the performing provider spe- sitivity of the claims to capture oncologists varied by specialty. cialty variable and primary specialty, respectively. On the Physician claims identified 95.4% of ROs, 53.0% of SOs, and NPPES file, specialty was identified from taxonomy codes. 83.3% of MOs. Similar results were observed for the NPPES Some of the data resources allowed for multiple specialties to Registry and the MD-PPAS file, which captured 82.8% and 82.5% be listed creating the possibility for different specialties to be of all oncologists, respectively. Both the NPPES Registry and the reported within a file or between files. To assign a physician spe- MD-PPAS file captured more than 90% of ROs and 82% of MOs. cialty for the CMS data resources, we developed a hierarchical ap- Ascertainment of SOs varied between the NPPES Registry proach. First, within each data resource, if there was any (59.8%) and the MD-PPAS file (46.0%). The utility of the CMS data indication that a physician was an oncologist, he or she was clas- resources to identify type of oncologist improved when files sified as such. Then, among the physicians who were identified were combined. Using a combination of the three CMS data as oncologist, oncology specialty was assigned in the following resources to identify any oncologists improved sensitivity to hierarchical order: RO, SO, and MO. For example, if two oncology more than 90% and resulted in identification of 98.2% of ROs, specialties (RO and SO) were listed in a file for the same physi- 70.1% of SOs, and 89.3% of MOs. The ability to identify oncolo- cian, then the higher-ranked specialty (RO) was assigned. This gists using the physician claims combined with the NPPES file same hierarchical approach was used to consolidate oncology was similar to the combination of all three CMS data resources. specialties across CMS data resources. Within the CMS data We compared the AMA and CMS files for agreement about resources, there were physician specialties other than oncolo- oncology specialty. There were 128 physicians who were classi- gists. We wanted to classify these nononcologists into groups. To fied as oncologists in both the AMA and at least one CMS data consolidate physicians’ information within and across the CMS resource, but there was disagreement between the two data data resources, we extended our hierarchical approach for non- sources about the specific oncology specialty. This accounted oncology specialties in the following order: radiology, surgery, for less than 1% of all physicians (data not shown). In addition, “other” medical specialty, hospital-based, and primary care (see there were 84 physicians (<0.5%) who had conflicting types of Supplementary Appendix, available online) These physicians oncology specialties between the CMS files, independent of were only identified from the CMS data resources. their AMA specialty. For the 1730 physicians (RO: 70; SO: 461; MO: 1199) who were identified as an oncologist in the AMA data but not determined to be an oncologist in any CMS data re- Analysis source, we identified their specialties as reported in the CMS The AMA data were considered the gold standard to identify files (Table 3). For these 1730 AMA-classified oncologists, the oncologists because of the extent that it has been used in most frequent specialties listed in the CMS data for these Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 J. L. Warren et al. |63 Table 2. Sensitivity of different CMS data resources to identify oncologists reported in the AMA Physician Masterfile* Type of Oncology Specialty† Radiation Surgical Medical Any oncologist oncologists oncologists oncologists (n¼ 17 934) (n¼ 4123) (n¼ 1575) (n¼ 12 236) n (%)‡ n (%)‡ n (%)‡ n (%)‡ Using Single CMS File Physician Claims only 15 073 (84.0) 3935 (95.4) 834 (53.0) 10 188 (83.3) NPPES Registry 14 844 (82.8) 3730 (90.5) 942 (59.8) 10 098 (82.5) MD-PPAS File only 14 802 (82.5) 3958 (96.0) 724 (46.0) 10 041 (82.1) Combined Files Using Physician Claims and NPPES Registry 16 136 (90.0) 4043 (98.1) 1095 (69.5) 10 872 (88.9) Physician Claims and MD-PPAS file 15 470 (86.3) 4017 (97.4) 873 (55.4) 10 458 (85.5) NPPES Registry and MD-PPAS 16 061 (89.6) 4041 (98.0) 1059 (67.2) 10 879 (88.9) All of the CMS Files 16 204 (90.4) 4048 (98.2) 1104 (70.1) 10 924 (89.3) *The Physician Masterfile served as the gold standard for identifying oncologists. AMA¼ American Medical Association; CMS¼ Center for Medicare and Medicaid Services; MD-PPAS¼ Medicare Data on Provider Practice and Specialty; NPPES¼ National Plan and Provider Enumeration System. †Oncologic specialties classified in hierarchical order (radiation, surgical, medical). ‡Number and percent of oncologists identified in the AMA Masterfile who were found to have concordant specialty in the CMS data. physicians were hospital-based specialty, surgery, and primary specialty on the AMA data (eg, ROs reported as radiologists, SOs care. There were 3.6% AMA oncologists who had a NPPES taxon- reported as surgeons). There was a small percent of physicians omy code of “specialist” (174400000X), which was outside the in the NPPES file who had a taxonomy code for “specialty.” We typical range of taxonomy codes for physicians (eg, codes that manually reviewed a subset of 25 providers with the taxonomy begin with 20). code for “specialty” and searched for their type of practice on The CMS-reported specialty varied when stratified by the the internet. These providers were found to be involved in a AMA-defined oncology specialty. For physicians who were ROs range of medical services, including oncologists, prosthetic in the AMA data, radiology was the most frequently reported designers, and counselors. The numerous types of services in- specialty in the CMS data, although the frequency varied by cluded under this taxonomy code means that it is not useful for CMS data resource. A similar pattern was observed for AMA- imputing that a physician is an oncologist. defined SOs, with more than 85% having a surgery specialty in Some investigators using Medicare claims alone to study each of the CMS files. For medical oncologists in the AMA data, cancer care have assigned physician specialty through the CMS the most common specialties in the CMS data were hospital- specialty codes or by looking at services that are specific to can- based and primary care. Of the doctors identified as providing cer (3,5). Using this approach, if there is a claim for chemother- primary care, 90% or more reported an internal medicine spe- apy or radiation therapy, the physician is considered a medical cialty in all CMS files (data not shown). oncologist or radiation oncologist, respectively, regardless of the CMS specialty code. Such an approach may be an option for chemotherapy and radiation therapy, however, it is more com- Discussion plex for surgical treatment. Many surgeries are not specific to cancer (eg, hemicolectomy) and are commonly performed by Our analysis demonstrated that individual CMS data resources have more than 80% sensitivity to capture any oncologists as both surgeons and surgical oncologists. For surgeries that are specific to cancer, it may be possible to identify from the claims reported in the AMA data. The completeness of the CMS data to identify any oncologist is improved by combining files. the frequency that a specific physician is performing these pro- cedures and develop a minimal threshold above which that Although using combined files from CMS can identify 90.4% of all oncologists, the files varied in sensitivity to identify specific physician is imputed to be a surgical oncologist. More evalua- tion of this approach and whether it would improve the ability oncology specialties. The CMS data, especially combined files, captured 98% of ROs and 89% of MOs. However, CMS data of Medicare claims to identify surgical oncologists is needed. We used the AMA data as the standard against which to com- resources, individually or combined, did not identify a sizeable portion of the SOs. Therefore, researchers who want to use CMS pare CMS data. The AMA data appear to include the vast majority of oncologists. A prior study that used Medicare claims, the CMS data to study treatment and outcomes for patients receiving care from SOs should consider linkage to the AMA data. These NPI Directory, and the AMA data to identify oncologists found that only 6% of oncologists were in the Medicare claims and the findings are similar to a prior study that found that using Medicare claims with the CMS NPI Directory (precursor to the CMS NPI Directory but not in the AMA data (16). The number of medical and radiation oncologists that we reported is consistent NPPES Registry) increased the percent of all oncologists identi- fied in Medicare claims by 36.1% (16). The same study also found with prior studies that have used the AMA data to report on the oncology workforce (26,27). However the number of SOs that we that the addition of AMA data markedly increased the identifi- cation of SOs. identified is nearly double that reported in these earlier studies. We attribute our higher number to the inclusion of both primary For physicians who were identified as oncologists in the AMA data but were not found to be oncologists in the CMS data, and secondary specialties reported on the AMA data. If we limited the identification of SOs to those with a primary specialty code, many had a CMS specialty that was similar to the oncology Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 64 | J Natl Cancer Inst Monogr, 2020, Vol. 2020, No. 55 our numbers would be similar to those in the prior reports. Becauseweusedboth primary andsecondary specialty inour analysis, there is the possibility that there could be conflicting on- cology specialties reported in the AMA data. This occurred in 101 oncologists in the AMA data (0.56% of physicians), 90 of whom were radiation oncologists who also listed medical oncology. ROs are required to complete an initial year of residency in specialties other than RO before beginning their RO training. In determining which data resource is most accurate and complete to identify oncologists, it is important to consider how physician specialties are initially assigned. The specialty infor- mation for each physician in the AMA data is obtained from the American Association of Medical Colleges, the American Board of Medical Specialties, and self-report from a survey of individual physicians. Data on specialty from CMS are self-reported at the time when a physician applies for an NPI or enrolls in the PECOS system, with regular updates to the PECOS system (14). Our anal- ysis assessed only those physicians who were oncologists. We did not have access to the entirety of AMA data or CMS data. Therefore, we were not able to assess the specificity of the CMS data to identify physicians who were not oncologists. Our findings support several recommendations regarding which data resources are best suited for researchers who are us- ing Medicare data to study the role of physician specialty in on- cology care. We conclude that researchers who want to identify any oncologist can use a combination of the assessed CMS data resources to capture 90% of oncologists. If a researcher opts to use only CMS data resources to identify oncologists, it appears that using Medicare claims and the NPPES Registry will capture almost the same number of oncologists as the combination of the Medicare claims, the NPPES Registry, and the MD-PPAS data. The NPPES data are public use and can be downloaded without charge from the CMS website (13). The MD-PPAS data are classi- fied by CMS as identifiable data and are released to researchers after a review process and payment for the file. In addition, our findings support the use of combined CMS data resources or even Medicare claims alone to identify ROs. If the focus of the analysis is on MOs, a researcher would need to consider whether the 89% sensitivity of the combined CMS data resour- ces for identifying MOs was sufficient and if the additional cost to obtain the AMA was worthwhile. Researchers involved in studies that require identification of SOs should use the AMA data to have more complete ascertainment of this specialty. In conclusion, this study has shown that in some situations, researchers can use combined CMS data resources to identify the vast majority of oncologists included in the AMA data. In these situations, researchers can forego the expense and the ad- ministrative process of acquiring the AMA data. However, stud- ies focusing on SOs and perhaps MOs should incorporated data from the AMA. The determination of which data are needed to identify oncologists will depend on the specific research ques- tion and the type of oncologist included in the study. Notes Affiliations of authors: National Cancer Institute, Division of Cancer Control and Population Science, Bethesda, MD (JLW, DPW, LE); Information Management Services, Calverton, MD (MJB, RB); Center for Medicare and Medicaid Services, Baltimore, MD (SC). The authors have no conflicts of interest to declare. The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views Table 3. Center for Medicare and Medicaid Services (CMS) Specialty for physicians identified as oncologists in the AMA data* but not in the CMS data All oncologists Radiation oncologists Surgical oncologists Medical oncologists (n¼ 1730) (n¼ 70) (n¼ 461) (n¼ 1199) Specialty per the Physician NPPES MD-PPAS Physician NPPES MD-PPAS Physician NPPES MD-PPAS Physician NPPES MD-PPAS CMS data† claims, % Registry, % file, % claims, % Registry, % file, % claims, % Registry, % file, % claims, % Registry, % file, % Radiology 2.6 2.3 2.5 52.9 44.3 52.9 0.2 0.2 0.0 0.6 0.6 0.6 Surgery 29.5 28.3 29.8 10.0 10.0 10.0 89.6 85.2 89.8 7.5 7.5 7.8 Medical specialty 4.2 4.6 4.0 8.6 10.0 8.6 0.9 1.1 0.9 5.2 5.6 4.9 Hospital-based 31.1 31.7 30.7 7.1 10.0 7.1 0.9 0.9 0.9 44.1 44.8 43.5 Primary care 28.5 27.7 33.0 20.0 17.1 21.4 6.5 6.3 8.5 37.4 36.5 43.1 Specialist‡ — 3.6 — — 5.7 — — 6.1 — — 2.5 — Missing/Other 4.2 1.9 0.0 1.4 2.9 0.0 2.0 0.2 0.0 5.2 2.5 0.0 *Only AMA Direct Patient Care Physicians were included. MD-PPAS ¼ Medicare Data on Provider Practice and Specialty; NPPES ¼ National Plan and Provider Enumeration System. AMA ¼ American Medical Association; CMS ¼ Center for Medicare and Medicaid Services; MD-PPAS ¼ Medicare Data on Provider Practice and Specialty; NPPES ¼ National Plan and Provider Enumeration System. †Specialties reported in hierarchical order (radiation, surgical, medical). ‡Specialist category only available in the NPPES file based on taxonomy code of 174400000X. Downloaded from https://academic.oup.com/jncimono/article/2020/55/60/5837289 by DeepDyve user on 14 August 2022 J. L. Warren et al. |65 Version 2.3, 2018. https://www.resdac.org/cms-data/files/md-ppas/data-doc- of the US Department of Health and Human Services or any of umentation. Accessed January 18, 2019. its agencies. 15. Baldwin LM, Adamache W, Klabunde CN, Kenward K, Dahlman C, L Warren J. Linking physician characteristics and Medicare claims data: issues in data availability, quality, and measurement. 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Journal

JNCI MonographsOxford University Press

Published: May 1, 2020

Keywords: medicare; oncologists; rosiglitazone; reactive oxygen species; myelofibrosis; mos pp39 serine/threonine kinase; radiation oncologists

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