Nancy L Keating1,2, Jessica L F Cleveland3, Alexi A Wright4,5, Gabriel A Brooks6, Laurie Meneades1, Lauren Riedel1, Jose R Zubizarreta1,7,8, Mary Beth Landrum1. 1. Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts. 2. Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts. 3. Department of Informatics and Analytics, Dana-Farber Cancer Institute, Boston, Massachusetts. 4. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts. 5. Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts. 6. Section of Medical Oncology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire. 7. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. 8. Department of Statistics, Harvard Faculty of Arts and Sciences, Cambridge, Massachusetts.
Abstract
Importance: Measurement of the quality of care is important for alternative payment models in oncology, yet the ability to distinguish high-quality from low-quality care across oncology practices remains uncertain. Objective: To assess the reliability of cancer care quality measures across oncology practices using registry and claims-based measures of process, utilization, end-of-life (EOL) care, and survival, and to assess the correlations of practice-level performance across measure and cancer types. Design, Setting, and Participants: This cross-sectional study used the Surveillance, Epidemiology, and End Results (SEER) Program registry linked to Medicare administrative data to identify individuals with lung cancer, breast cancer, or colorectal cancer (CRC) that was newly diagnosed between January 1, 2011, and December 31, 2015, and who were treated in oncology practices with 20 or more patients. Data were analyzed from January 2018 to December 2020. Main Outcomes and Measures: Receipt of guideline-recommended treatment and surveillance, hospitalizations or emergency department visits during 6-month chemotherapy episodes, care intensity in the last month of life, and 12-month survival were measured. Summary measures for each domain in each cohort were calculated. Practice-level rates for each measure were estimated from hierarchical linear models with practice-level random effects; practice-level reliability (reproducibility) for each measure based on the between-measure variance, within-measure variance, and distribution of patients treated in each practice; and correlations of measures across measure and cancer types. Results: In this study of SEER registry data linked to Medicare administrative data from 49 715 patients with lung cancer treated in 502 oncology practices, 21 692 with CRC treated in 347 practices, and 52 901 with breast cancer treated in 492 practices, few practices had 20 or more patients who were eligible for most process measures during the 5-year study period. Patients were 65 years or older; approximately 50% of the patients with lung cancer and CRC and all of the patients with breast cancer were women. Most measures had limited variability across practices. Among process measures, 0 of 6 for lung cancer, 0 of 6 for CRC, and 3 of 11 for breast cancer had a practice-level reliability of 0.75 or higher for the median-sized practice. No utilization, EOL care, or survival measure had reliability across practices of 0.75 or higher. Correlations across measure types were low (r ≤ 0.20 for all) except for a correlation between the CRC process and 1-year survival summary measures (r = 0.35; P < .001). Summary process measures had limited or no correlation across lung cancer, breast cancer, and CRC (r ≤ 0.16 for all). Conclusions and Relevance: This study found that quality measures were limited by the small numbers of Medicare patients with newly diagnosed cancer treated in oncology practices, even after pooling 5 years of data. Measures had low reliability and had limited to no correlation across measure and cancer types, suggesting the need for research to identify reliable quality measures for practice-level quality assessments.
Importance: Measurement of the quality of care is important for alternative payment models in oncology, yet the ability to distinguish high-quality from low-quality care across oncology practices remains uncertain. Objective: To assess the reliability of cancer care quality measures across oncology practices using registry and claims-based measures of process, utilization, end-of-life (EOL) care, and survival, and to assess the correlations of practice-level performance across measure and cancer types. Design, Setting, and Participants: This cross-sectional study used the Surveillance, Epidemiology, and End Results (SEER) Program registry linked to Medicare administrative data to identify individuals with lung cancer, breast cancer, or colorectal cancer (CRC) that was newly diagnosed between January 1, 2011, and December 31, 2015, and who were treated in oncology practices with 20 or more patients. Data were analyzed from January 2018 to December 2020. Main Outcomes and Measures: Receipt of guideline-recommended treatment and surveillance, hospitalizations or emergency department visits during 6-month chemotherapy episodes, care intensity in the last month of life, and 12-month survival were measured. Summary measures for each domain in each cohort were calculated. Practice-level rates for each measure were estimated from hierarchical linear models with practice-level random effects; practice-level reliability (reproducibility) for each measure based on the between-measure variance, within-measure variance, and distribution of patients treated in each practice; and correlations of measures across measure and cancer types. Results: In this study of SEER registry data linked to Medicare administrative data from 49 715 patients with lung cancer treated in 502 oncology practices, 21 692 with CRC treated in 347 practices, and 52 901 with breast cancer treated in 492 practices, few practices had 20 or more patients who were eligible for most process measures during the 5-year study period. Patients were 65 years or older; approximately 50% of the patients with lung cancer and CRC and all of the patients with breast cancer were women. Most measures had limited variability across practices. Among process measures, 0 of 6 for lung cancer, 0 of 6 for CRC, and 3 of 11 for breast cancer had a practice-level reliability of 0.75 or higher for the median-sized practice. No utilization, EOL care, or survival measure had reliability across practices of 0.75 or higher. Correlations across measure types were low (r ≤ 0.20 for all) except for a correlation between the CRC process and 1-year survival summary measures (r = 0.35; P < .001). Summary process measures had limited or no correlation across lung cancer, breast cancer, and CRC (r ≤ 0.16 for all). Conclusions and Relevance: This study found that quality measures were limited by the small numbers of Medicare patients with newly diagnosed cancer treated in oncology practices, even after pooling 5 years of data. Measures had low reliability and had limited to no correlation across measure and cancer types, suggesting the need for research to identify reliable quality measures for practice-level quality assessments.
Authors: Jason B Liu; Kristopher M Huffman; Bryan E Palis; Lawrence N Shulman; David P Winchester; Clifford Y Ko; Bruce L Hall Journal: J Am Coll Surg Date: 2016-12-12 Impact factor: 6.113
Authors: Elizabeth A Nardi; James McCanney; Katy Winckworth-Prejsnar; Alyssa A Schatz; Kerin Adelson; Marcus Neubauer; Mary Lou Smith; Ronald Walters; Robert W Carlson Journal: J Natl Compr Canc Netw Date: 2018-05 Impact factor: 11.908
Authors: Lawrence N Shulman; Bryan E Palis; Ryan McCabe; Kathy Mallin; Ashley Loomis; David Winchester; Daniel McKellar Journal: J Oncol Pract Date: 2017-11-01 Impact factor: 3.840
Authors: Michael N Neuss; Jennifer L Malin; Stephanie Chan; Pamela J Kadlubek; John L Adams; Joseph O Jacobson; Douglas W Blayney; Joseph V Simone Journal: J Clin Oncol Date: 2013-03-11 Impact factor: 44.544
Authors: Jane C Weeks; Hajime Uno; Nathan Taback; Gladys Ting; Angel Cronin; Thomas A D'Amico; Jonathan W Friedberg; Deborah Schrag Journal: Ann Intern Med Date: 2014-07-01 Impact factor: 25.391
Authors: Elizabeth A Luth; Adoma Manful; Joel S Weissman; Amanda Reich; Keren Ladin; Robert Semco; Ishani Ganguli Journal: J Gen Intern Med Date: 2022-01-26 Impact factor: 5.128
Authors: Brandon L Ellsworth; Allan K Metz; Nicole M Mott; Ruby Kazemi; Michael Stover; Tasha Hughes; Lesly A Dossett Journal: Ann Surg Oncol Date: 2022-02-06 Impact factor: 5.344