Percentage of patients, aged 18 years and older, who died with cancer and were enrolled in hospice for at least 3 days immediately before death
This denominator has been broadened to capture all adult patients who died with cancer instead of solely looking at patients admitted to hospice. This change harmonizes this measure with ASCO’s other end-of-life measures.
The intent of the numerator has not changed, but the language has been modified to encourage hospice, which now makes the measure proportional instead of inverse.
Measure Specs
General Information
Hospice is the most established model of palliative care for patients with a prognosis of <6 months and is eligible for coverage by third-party payers and Medicare (National Comprehensive Cancer Network [NCCN], 2026). Between 2022 and 2023, the median length of hospice stay amongst Medicare beneficiaries was ~18 days (Medicare Payment Advisory Commission [MedPAC], 2025) and ~one-quarter of patients received care for 5 days or less before passing away (MedPAC, 2025). This is even though the hospice benefit is at least six months or longer if needed. This short length of stay means that the patient and family are not receiving the full benefit of hospice services such as spiritual counseling, social work, and complex symptom management (MedPAC, 2025) and the care team has limited time to get a plan of care in place before death. Patients who use hospice, compared with those who do not use hospice, have markedly improved symptoms, less caregiver distress, reduced costs of approximately $8,700 per Medicare beneficiary, and, according to two published reports, actually live longer (Ferrell et al., 2017). ASCO’s End of Life Measures Technical Expert Panel emphasized that performance is not expected to be perfect on this quality measure. A margin of error should be expected to account for scenarios such as patient refusal of hospice and barriers to access hospice.
REFERENCES:
- Ferrell, B. R., Temel, J. S., Temin, S., Alesi, E. R., Balboni, T. A., Basch, E. M., Firn, J. I., Paice, J. A., Peppercorn, J. M., Phillips, T., Stovall, E. L., Zimmermann, C., & Smith, T. J. (2017). Integration of Palliative Care Into Standard Oncology Care: American Society of Clinical Oncology Clinical Practice Guideline Update. Journal of Clinical Oncology, 35(1), 96–112. Retrieved from https://doi.org/10.1200/jco.2016.70.1474.
- Medicare Payment Advisory Commission. (2025, March). Hospice Services (Chapter 9). Report to the Congress: Medicare Payment Policy. https://www.medpac.gov/wp-content/uploads/2025/03/Mar25_Ch9_MedPAC_Report_To_Congress_SEC.pdf
- National Comprehensive Cancer Network. (2026). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®): Palliative Care (Version 1.2026). https://www.nccn.org/professionals/physician_gls/pdf/palliative.pdf
This registry-based measure is currently operationalized within the Merit-based Incentive Payment System (MIPS). As a registry-based instrument, it supports a flexible data architecture encompassing Electronic Health Record (EHR) data, Qualified Clinical Data Registry (QCDR) inputs, and manual chart abstraction from paper records.
While CMS maintains confidentiality regarding which specific entities utilize these measures for MIPS reporting, it is established that registries are not subject to licensure requirements for submission. To date, ASCO has received no formal inquiries or concerns regarding administrative burden through official CMS channels. However, through rigorous measure testing and development, ASCO has verified the measure’s active implementation within the US Oncology Network (USON)/McKesson registry, which has successfully achieved full electronic specification within their EHR system.
Numerator
Patients enrolled in hospice for at least 3 days immediately before death
NUMERATOR:
Patients enrolled in hospice for at least 3 days immediately before death
Numerator Instruction:
Enrolled in hospice for at least 3 days immediately before death can be calculated as follows:
(Date of death minus Most Recent Date of Hospice Admission) ≥ 3 days
Numerator Options:
Performance Met: Patient enrolled in hospice for at least 3 days immediately before death (GXXXX)
OR
Denominator Exception: Patient not enrolled in hospice due to 1) receipt or in process of receipt of bone marrow or peripheral blood stem cell transplant (transplant status) in the last 60 days of life, or 2) receipt or in process of receipt of CAR T cell therapy in the last 60 days of life (GXXXX)
Note: The above treatments are not covered in hospice, but may be appropriate for select patients at the end of life.
OR
Denominator Exception: Patients given hydroxyurea or BTK inhibitors (GXXXX)
Note: Hydroxyurea and BTK inhibitors may be inappropriate to withdraw at the end of life and/or are used for palliative purposes, however these are not covered by hospice.
OR Performance Not Met: Patient enrolled in hospice less than 3 days immediately before death (GXXXX)
Note: GXXXX is a placeholder for HCPCS codes used to report Numerator Options
Denominator
Patients, aged 18 years and older, who died with cancer
Patients, aged 18 years and older, who died with cancer
Denominator Criteria (Eligible Cases):
Patients aged ≥ 18 years on date of any of the eligible patient encounters
AND
Encounter diagnosis of cancer (ICD-10-CM): C00.0, C00.1, C00.2, C00.3, C00.4, C00.5, C00.6, C00.8, C00.9, C01, C02.0, C02.1, C02.2, C02.3, C02.4, C02.8, C02.9, C03.0, C03.1, C03.9, C04.0, C04.1, C04.8, C04.9, C05.0, C05.1, C05.2, C05.8, C05.9, C06.0, C06.1, C06.2, C06.80, C06.89, C06.9, C07, C08.0, C08.1, C08.9, C09.0, C09.1, C09.8, C09.9, C10.0, C10.1, C10.2, C10.3, C10.4, C10.8, C10.9, C11.0, C11.1, C11.2, C11.3, C11.8, C11.9, C12, C13.0, C13.1, C13.2, C13.8, C13.9, C14.0, C14.2, C14.8, C15.3, C15.4,
C15.5, C15.8, C15.9, C16.0, C16.1, C16.2, C16.3, C16.4, C16.5, C16.6, C16.8, C16.9, C17.0, C17.1, C17.2,
C17.3, C17.8, C17.9, C18.0, C18.1, C18.2, C18.3, C18.4, C18.5, C18.6, C18.7, C18.8, C18.9, C19, C20,
C21.0, C21.1, C21.2, C21.8, C22.0, C22.1, C22.2, C22.3, C22.4, C22.7, C22.8, C22.9, C23, C24.0, C24.1,
C24.8, C24.9, C25.0, C25.1, C25.2, C25.3, C25.4, C25.7, C25.8, C25.9, C26.0, C26.1, C26.9, C30.0,
C30.1, C31.0, C31.1, C31.2, C31.3, C31.8, C31.9, C32.0, C32.1, C32.2, C32.3, C32.8, C32.9, C33, C34.00, C34.01, C34.02, C34.10, C34.11, C34.12, C34.2, C34.30, C34.31, C34.32, C34.80, C34.81, C34.82, C34.90, C34.91, C34.92, C37, C38.0, C38.1, C38.2, C38.3, C38.4, C38.8, C39.0, C39.9, C40.00, C40.01, C40.02, C40.10, C40.11, C40.12, C40.20, C40.21, C40.22, C40.30, C40.31, C40.32, C40.80, C40.81, C40.82, C40.90, C40.91, C40.92, C41.0, C41.1, C41.2, C41.3, C41.4, C41.9, C43.0, C43.10, C43.111, C43.112, C43.121, C43.122, C43.20, C43.21, C43.22, C43.30, C43.31, C43.39, C43.4, C43.51, C43.52, C43.59, C43.60, C43.61, C43.62, C43.70, C43.71, C43.72, C43.8, C43.9, C44.00, C44.01, C44.02, C44.09, C44.101, C44.1021, C44.1022, C44.1091, C44.1092, C44.111, C44.1121, C44.1122, C44.1191, C44.1192, C44.121, C44.1221, C44.1222, C44.1291, C44.1292, C44.131, C44.1321, C44.1322, C44.1391, C44.1392, C44.191, C44.1921, C44.1922, C44.1991, C44.1992, C44.201, C44.202, C44.209, C44.211, C44.212, C44.219, C44.221, C44.222, C44.229, C44.291, C44.292, C44.299, C44.300, C44.301, C44.309, C44.310, C44.311, C44.319, C44.320, C44.321, C44.329, C44.390, C44.391, C44.399, C44.40, C44.41, C44.42, C44.49, C44.500, C44.501, C44.509, C44.510, C44.511, C44.519, C44.520, C44.521, C44.529, C44.590, C44.591, C44.599, C44.601, C44.602, C44.609, C44.611, C44.612, C44.619, C44.621, C44.622, C44.629, C44.691, C44.692, C44.699, C44.701, C44.702, C44.709, C44.711, C44.712, C44.719, C44.721, C44.722, C44.729, C44.791, C44.792, C44.799, C44.80, C44.81, C44.82, C44.89, C44.90, C44.91, C44.92, C44.99, C45.0, C45.1, C45.2, C45.7, C45.9, C46.0, C46.1, C46.2, C46.3, C46.4, C46.50, C46.51, C46.52, C46.7, C46.9, C47.0, C47.10, C47.11, C47.12, C47.20, C47.21, C47.22, C47.3, C47.4, C47.5, C47.6, C47.8,
C47.9, C48.0, C48.1, C48.2, C48.8, C49.0, C49.10, C49.11, C49.12, C49.20, C49.21, C49.22, C49.3,
C49.A0, C49.A1, C49.A2, C49.A3, C49.A4, C49.A5, C49.A9, C49.4, C49.5, C49.6, C49.8, C49.9, C4A.0, C4A.10, C4A.111, C4A.112, C4A.121, C4A.122, C4A.20, C4A.21, C4A.22, C4A.30, C4A.31, C4A.39, C4A.4, C4A.51, C4A.52, C4A.59, C4A.60, C4A.61, C4A.62, C4A.70, C4A.71, C4A.72, C4A.8, C4A.9, C50.011, C50.012, C50.019, C50.021, C50.022, C50.029, C50.111, C50.112, C50.119, C50.121, C50.122, C50.129, C50.211, C50.212, C50.219, C50.221, C50.222, C50.229, C50.311, C50.312, C50.319, C50.321, C50.322, C50.329, C50.411, C50.412, C50.419, C50.421, C50.422, C50.429, C50.511, C50.512, C50.519, C50.521, C50.522, C50.529, C50.611, C50.612, C50.619, C50.621, C50.622, C50.629, C50.811, C50.812, C50.819, C50.821, C50.822, C50.829, C50.911, C50.912, C50.919, C50.921, C50.922, C50.929, C51.0, C51.1, C51.2, C51.8, C51.9, C52, C53.0, C53.1, C53.8, C53.9, C54.0, C54.1, C54.2, C54.3, C54.8, C54.9, C55, C56.1, C56.2, C56.3, C56.9, C57.00, C57.01, C57.02, C57.10, C57.11, C57.12, C57.20, C57.21, C57.22, C57.3, C57.4, C57.7, C57.8, C57.9, C58, C60.0, C60.1, C60.2, C60.8, C60.9, C61, C62.00, C62.01, C62.02, C62.10, C62.11, C62.12, C62.90, C62.91, C62.92, C63.00, C63.01, C63.02, C63.10, C63.11, C63.12, C63.2, C63.7, C63.8, C63.9, C64.1, C64.2, C64.9, C65.1, C65.2, C65.9, C66.1, C66.2,
C66.9, C67.0, C67.1, C67.2, C67.3, C67.4, C67.5, C67.6, C67.7, C67.8, C67.9, C68.0, C68.1, C68.8, C68.9, C69.00, C69.01, C69.02, C69.10, C69.11, C69.12, C69.20, C69.21, C69.22, C69.30, C69.31, C69.32, C69.40, C69.41, C69.42, C69.50, C69.51, C69.52, C69.60, C69.61, C69.62, C69.80, C69.81, C69.82, C69.90, C69.91, C69.92, C70.0, C70.1, C70.9, C71.0, C71.1, C71.2, C71.3, C71.4, C71.5, C71.6,
C71.7, C71.8, C71.9, C72.0, C72.1, C72.20, C72.21, C72.22, C72.30, C72.31, C72.32, C72.40, C72.41, C72.42, C72.50, C72.59, C72.9, C73, C74.00, C74.01, C74.02, C74.10, C74.11, C74.12, C74.90, C74.91, C74.92, C75.0, C75.1, C75.2, C75.3, C75.4, C75.5, C75.8, C75.9, C76.0, C76.1, C76.2, C76.3, C76.40,
C76.41, C76.42, C76.50, C76.51, C76.52, C76.8, C77.0, C77.1, C77.2, C77.3, C77.4, C77.5, C77.8, C77.9,
C78.00, C78.01, C78.02, C78.1, C78.2, C78.30, C78.39, C78.4, C78.5, C78.6, C78.7, C78.80, C78.89, C79.00, C79.01, C79.02, C79.10, C79.11, C79.19, C79.2, C79.31, C79.32, C79.40, C79.49, C79.51, C79.52, C79.60, C79.61, C79.62, C79.63, C79.70, C79.71, C79.72, C79.81, C79.82, C79.89, C79.9, C7A.00, C7A.010, C7A.011, C7A.012, C7A.019, C7A.020, C7A.021, C7A.022, C7A.023, C7A.024, C7A.025, C7A.026, C7A.029, C7A.090, C7A.091, C7A.092, C7A.093, C7A.094, C7A.095, C7A.096, C7A.098, C7A.1, C7A.8, C7B.00, C7B.01, C7B.02, C7B.03, C7B.04, C7B.09, C7B.1, C7B.8, C80.0, C80.1, C80.2, C81.00, C81.01, C81.02, C81.03, C81.04, C81.05, C81.06, C81.07, C81.08, C81.09, C81.10, C81.11, C81.12, C81.13, C81.14, C81.15, C81.16, C81.17, C81.18, C81.19, C81.20, C81.21, C81.22, C81.23, C81.24, C81.25, C81.26, C81.27, C81.28, C81.29, C81.30, C81.31, C81.32, C81.33, C81.34, C81.35, C81.36, C81.37, C81.38, C81.39, C81.40, C81.41, C81.42, C81.43, C81.44, C81.45, C81.46, C81.47, C81.48, C81.49, C81.70, C81.71, C81.72, C81.73, C81.74, C81.75, C81.76, C81.77, C81.78, C81.79, C81.90, C81.91, C81.92, C81.93, C81.94, C81.95, C81.96, C81.97, C81.98, C81.99, C82.00, C82.01, C82.02, C82.03, C82.04, C82.05, C82.06, C82.07, C82.08, C82.09, C82.10, C82.11, C82.12, C82.13, C82.14, C82.15, C82.16, C82.17, C82.18, C82.19, C82.20, C82.21, C82.22, C82.23, C82.24, C82.25, C82.26, C82.27, C82.28, C82.29, C82.30, C82.31, C82.32, C82.33, C82.34, C82.35, C82.36, C82.37, C82.38, C82.39, C82.40, C82.41, C82.42, C82.43, C82.44, C82.45, C82.46, C82.47, C82.48, C82.49, C82.50, C82.51, C82.52, C82.53, C82.54, C82.55, C82.56, C82.57, C82.58, C82.59, C82.60, C82.61, C82.62, C82.63, C82.64, C82.65, C82.66, C82.67, C82.68, C82.69, C82.80, C82.81, C82.82, C82.83, C82.84, C82.85, C82.86, C82.87, C82.88, C82.89, C82.90, C82.91, C82.92, C82.93, C82.94, C82.95, C82.96, C82.97, C82.98, C82.99, C83.00, C83.01, C83.02, C83.03, C83.04, C83.05, C83.06, C83.07, C83.08, C83.09, C83.10, C83.11, C83.12, C83.13, C83.14, C83.15, C83.16, C83.17, C83.18, C83.19, C83.30, C83.31, C83.32, C83.33, C83.34, C83.35, C83.36, C83.37, C83.38, C83.39, C83.50, C83.51, C83.52, C83.53, C83.54, C83.55, C83.56, C83.57, C83.58, C83.59, C83.70, C83.71, C83.72, C83.73, C83.74, C83.75, C83.76, C83.77, C83.78, C83.79, C83.80, C83.81, C83.82, C83.83, C83.84, C83.85, C83.86, C83.87, C83.88, C83.89, C83.90, C83.91, C83.92, C83.93, C83.94, C83.95, C83.96, C83.97, C83.98, C83.99, C84.00, C84.01, C84.02, C84.03, C84.04, C84.05, C84.06, C84.07, C84.08, C84.09, C84.10, C84.11, C84.12, C84.13, C84.14, C84.15, C84.16, C84.17, C84.18, C84.19, C84.40, C84.41, C84.42, C84.43, C84.44, C84.45, C84.46, C84.47, C84.48, C84.49, C84.60, C84.61, C84.62, C84.63, C84.64, C84.65, C84.66, C84.67, C84.68, C84.69, C84.7A, C84.70, C84.71, C84.72, C84.73, C84.74, C84.75, C84.76, C84.77, C84.78, C84.79, C84.90, C84.91, C84.92, C84.93, C84.94, C84.95, C84.96, C84.97, C84.98, C84.99, C84.A0, C84.A1, C84.A2, C84.A3, C84.A4, C84.A5, C84.A6, C84.A7, C84.A8, C84.A9, C84.Z0, C84.Z1, C84.Z2, C84.Z3, C84.Z4, C84.Z5, C84.Z6, C84.Z7, C84.Z8, C84.Z9, C85.10, C85.11, C85.12, C85.13, C85.14, C85.15, C85.16, C85.17, C85.18, C85.19, C85.20, C85.21, C85.22, C85.23, C85.24, C85.25, C85.26, C85.27, C85.28, C85.29, C85.80, C85.81, C85.82, C85.83, C85.84, C85.85, C85.86, C85.87, C85.88, C85.89, C85.90, C85.91, C85.92, C85.93, C85.94, C85.95, C85.96, C85.97, C85.98, C85.99, C86.0, C86.1, C86.2, C86.3, C86.4, C86.5, C86.6, C88.0, C88.2, C88.3, C88.4, C88.8, C88.9, C90.00, C90.01, C90.02, C90.10, C90.11, C90.12, C90.20, C90.21, C90.22, C90.30, C90.31, C90.32, C91.00, C91.01, C91.02, C91.10, C91.11, C91.12, C91.30, C91.31, C91.32, C91.40, C91.41, C91.42, C91.50, C91.51, C91.52, C91.60, C91.61, C91.62, C91.90, C91.91, C91.92, C91.A0, C91.A1, C91.A2, C91.Z0, C91.Z1, C91.Z2, C92.00, C92.01, C92.02, C92.10, C92.11, C92.12, C92.20, C92.21, C92.22, C92.30, C92.31, C92.32, C92.40, C92.41, C92.42, C92.50, C92.51, C92.52, C92.60, C92.61, C92.62, C92.90, C92.91, C92.92, C92.A0, C92.A1, C92.A2, C92.Z0, C92.Z1, C92.Z2, C93.00, C93.01, C93.02, C93.10, C93.11, C93.12, C93.30, C93.31, C93.32, C93.90, C93.91, C93.92, C93.Z0, C93.Z1, C93.Z2, C94.00, C94.01, C94.02, C94.20, C94.21, C94.22, C94.30, C94.31, C94.32, C94.40, C94.41, C94.42, C94.6, C94.80, C94.81, C94.82, C95.00, C95.01, C95.02, C95.10, C95.11, C95.12, C95.90, C95.91, C95.92, C96.0, C96.20, C96.21, C96.22, C96.29, C96.4, C96.5, C96.6, C96.9, C96.A, C96.Z, D37.01, D37.02, D37.030, D37.031, D37.032, D37.039, D37.04, D37.05, D37.09, D37.1, D37.2, D37.3, D37.4, D37.5, D37.6, D37.8, D37.9, D38.0, D38.1, D38.2, D38.3, D38.4, D38.5, D38.6, D39.0,
D39.10, D39.11, D39.12, D39.2, D39.8, D39.9, D40.0, D40.10, D40.11, D40.12, D40.8, D40.9, D41.00,
D41.01, D41.02, D41.10, D41.11, D41.12, D41.20, D41.21, D41.22, D41.3, D41.4, D41.8, D41.9, D42.0,
D42.1, D42.9, D43.0, D43.1, D43.2, D43.3, D43.4, D43.8, D43.9, D44.0, D44.10, D44.11, D44.12, D44.2,
D44.3, D44.4, D44.5, D44.6, D44.7, D44.9, D45, D46.0, D46.1, D46.20, D46.21, D46.22, D46.4, D46.9,
D46.A, D46.B, D46.C, D46.Z, D47.01, D47.02, D47.09, D47.1, D47.2, D47.3, D47.4, D47.9, D47.Z1,
D47.Z2, D47.Z9, D48.0, D48.2, D48.3, D48.4, D48.5, D48.60, D48.61, D48.62, D48.7, D48.9, D49.0, D49.1, D49.2, D49.3, D49.4, D49.511, D49.512, D49.519, D49.59, D49.6, D49.7, D49.81, D49.89, D49.9
AND
At least two patient encounters during performance period (CPT): 98000, 98001, 98002, 98003, 98004, 98005, 98006, 98007, 98008, 98009, 98010, 98011, 98012, 98013, 98014, 98015, 99202, 99203, 99204, 99205, 99212, 99213, 99214, 99215, 99242, 99243, 99244, 99245, 99495, 99496, 99441, 99442, 99443
NOTE: Both eligible patient encounters must include a diagnosis of cancer.
AND
Patients who died during performance period: G9859
Exclusions
This quality measure has no denominator exclusions, but does have denominator exceptions as noted above in section 1.14a.
This quality measure has no denominator exclusions, but does have denominator exceptions as noted above in section 1.14a.
Measure Calculation
The developer provided a Measure Calculation Diagram:
This measure is not stratified.
Minimum of five (5) patients.
Supplemental Attachment
Measure Record
Point of Contact
COPYRIGHT:
The Measure is not a clinical guideline, does not establish a standard of medical care, and has not been tested for all potential applications.
The Measure, while copyrighted, can be reproduced and distributed, without modification, for noncommercial purposes, e.g., use by health care providers in connection with their practices. Commercial use is defined as the sale, license, or distribution of the Measures for commercial gain, or incorporation of the Measure into a product or service that is sold, licensed or distributed for commercial gain.
Commercial uses of the Measure require a license agreement between the user and the American Society of Clinical Oncology (ASCO) and prior written approval of ASCO. Contact [email protected] for licensing this measure. Neither ASCO nor its members shall be responsible for any use of the Measure.
ASCO encourages use of the Measures by other health care professionals, where appropriate.
THE MEASURE AND SPECIFICATIONS ARE PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND.
© 2026 American Society of Clinical Oncology. All Rights Reserved.
Limited proprietary coding is contained in the Measure specifications for user convenience. Users of proprietary code sets should obtain all necessary licenses from the owners of the code sets. ASCO disclaims all liability for use or accuracy of any third party codes contained in the specifications.
CPT® contained in the Measure specifications is copyright 2004-2026 American Medical Association. LOINC® copyright 2004-2026 Regenstrief Institute, Inc. This material contains SNOMED Clinical Terms® (SNOMED CT®) copyright 2004-2026 International Health Terminology Standards Development Organisation. ICD-10 copyright 2026 World Health Organization. All Rights Reserved.
Neha Agrawal
Alexandria, VA
United States
Neha Agrawal
ASCO
Alexandria, VA
United States
Importance
Evidence
In the United States, cancer is the second leading cause of death overall and the leading cause of death among people younger than 85 years (Siegel et al., 2026). It is projected that in 2026 there will be approximately 2.1 million new cancer cases and over half a million cancer deaths (Siegel et al., 2026). While individual patients have their own preferences that can change over time, consistently across various populations, most patients nearing end of life wish to die at home (Gomes et al., 2013). In one national study, family caregivers gave significantly higher EOL care quality ratings for care at home under hospice than to EOL care received in a hospital palliative care unit, hospice inpatient unit, or residential hospice (Zhu et al., 2024).
The goal of Percentage of Patients who Died with Cancer Enrolled in Hospice For at Least 3 Days Immediately Before Death is to encourage earlier hospice enrollment and encourage timely enrollment in palliative care that focuses on symptom management, rather than low utility and aggressive treatments, among people dying with cancer. This results in a reduction of aggressive interventions and more time in hospice, which ultimately improves patient, family, and caregiver satisfaction. Timely enrollment in palliative care and hospice also reduces resource utilization costs and aligns with MedPAC’s goal to reduce high-intensity, low-value care at the end of life by promoting hospice and palliative care (MedPAC, 2025). Studies show that the integration of palliative care into the cancer care continuum improves patient outcomes in many ways, including quality of life, symptoms intensity, and end-of-life care (NCCN, 2026). The seminal NAM report Dying in America states that a palliative approach often offers the best chance of maintaining the highest possible quality of life for those living with advanced serious illness (Institute of Medicine [IOM], 2015) and proposes, as a core component to quality end-of-life care, to offer palliative care services and a personalized revision of the care plan, as well as access to services based on the changing needs of the patient and family (IOM, 2015). Community-based or home-based palliative care services have been associated with a reduced need for end-of-life emergency department visits, reduced length and frequency of hospitalizations, and fewer ICU admissions and in-hospital deaths (NCCN, 2026). A recent systematic review looked at peer-reviewed observational/experimental advance care planning and cancer patient-specific studies published between 1990-2022 and found that across ~33,500 patients advance care planning was associated with significantly lower odds of chemotherapy, intensive care, hospital admissions, hospice use fewer than seven days, hospital death, and aggressive care composite measures (Levoy et al., 2023). An analysis of men with advanced prostate cancer who were enrolled in hospice were less likely to receive high-intensity care, including ICU admissions and inpatient hospital stays at the end of life (NCCN, 2026). Another analysis of ~3000 deceased patients showed that hospice enrollment significantly decreased hospitalizations, non-hospice healthcare utilization, and costs of care (NCCN, 2026).
ASCO and NCCN palliative care guidelines contain the following recommendations:
- Clinicians should refer patients with advanced solid tumors and hematologic malignancies to specialized interdisciplinary palliative care teams that provide inpatient and outpatient care early in the course of disease, alongside active treatment of their cancer (Moderate, Strong)
- Palliative care for patients with advanced cancer should be delivered through interdisciplinary palliative care teams, with consultation available in both outpatient and inpatient settings (Intermediate, Moderate)
- Patients with advanced cancer should receive palliative care services, which may include a referral to a palliative care provider. Essential components of palliative care include (Intermediate, Moderate)
- Rapport and relationship building with patient and family caregivers
- Symptom, distress, and functional status management (eg, pain, dyspnea, fatigue, sleep disturbance, mood, nausea, or constipation)
- Exploration of understanding and education about illness and prognosis
- Clarification of treatment goals
- Assessment and support of coping and spiritual needs
- Assistance with medical decision making
- Coordination with other care providers
- Provision of referrals to other care providers as indicated
- Patients with months to weeks to live should be provided with guidance regarding the anticipated course of the disease. Physicians should reassess prognostic awareness and goals of therapy. As functional status worsens, these patients may become more concerned about the side effects of cancer-directed treatment and consider focusing their care on maintaining quality of life. The option of discontinuing anticancer treatment aligned with goals of care and initiating goal-directed supportive care should be discussed. (Category 2A)
- In general, patients with weeks to days to live (eg, dying patients) and comfort-oriented goals should discontinue all treatments not directly contributing to patient comfort. Intensive palliative care focusing on symptom management should be provided in addition to preparation for the dying process. Referral for hospice care should be placed, if not already done. (Category 2A)
Definitions of Categories of Evidence and Ratings:
- Category 2A: Based upon lower-level evidence, there is uniform NCCN consensus (≥85% support of the Panel) that the intervention is appropriate. Note there are no Category 1 recommendations within NCCN’s guidelines on Palliative Care.
- Strong Strength of Recommendation: In recommendations for an intervention, the desirable effects of an intervention outweigh its undesirable effects. In recommendations against an intervention, the undesirable effects of an intervention outweigh its desirable effects. All or almost all informed people would make the recommended choice for or against an intervention
- Moderate Quality of Evidence: We are moderately confident in the effect estimate: The true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different
In addition to the literature, ASCO received positive feedback on measure importance via its May 2025 public comment; almost all respondents strongly agreed or agreed with the following statements across all of ASCO’s updated EOL measures: “I believe this measure captures what it intends to capture, i.e., promoting early palliative care among dying patients and reducing aggressive interventions at the end of patients’ lives” and “I believe this measure differentiates good from poor quality care among providers of healthcare services.”
References:
- Gomes, B., Calanzani, N., Gysels, M., Hall, S., & Higginson, I. J. (2013). Heterogeneity and changes in preferences for dying at home: a systematic review. BMC palliative care, 12, 7. https://doi.org/10.1186/1472-684X-12-7
- Institute of Medicine. (2015). Dying in America: Improving Quality and Honoring Individual Preferences Near The End of Life. National Academies Press. https://doi.org/10.17226/18748
- Levoy, K., Sullivan, S. S., Chittams, J., Myers, R. L., Hickman, S. E., & Meghani, S. H. (2023). Don't throw the baby out with the bathwater: Meta-analysis of advance care planning and end-of-life cancer care. Journal of Pain and Symptom Management, 65(6), e715–e743. https://doi.org/10.1016/j.jpainsymman.2023.02.003
- National Comprehensive Cancer Network. (2026). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®): Palliative Care (Version 1.2026). https://www.nccn.org/professionals/physician_gls/pdf/palliative.pdf
- Sanders, J. J., Temin, S., Ghoshal, A., Alesi, E. R., Ali, Z. V., Chauhan, C., Cleary, J. F., Epstein, A. S., Firn, J. I., Jones, J. A., Litzow, M. R., Lundquist, D. M., Mardones, M. A., Nipp, R. D., Rabow, M. W., Rosa, W. E., Zimmermann, C., & Ferrell, B. R. (2024). Palliative Care for Patients with Cancer: ASCO guideline Update. Journal of Clinical Oncology, 42(19), 2336–2357. https://doi.org/10.1200/JCO.24.00542
- Siegel, R. L., Kratzer, T. B., Wagle, N. S., Sung, H., & Jemal, A. (2026). Cancer statistics, 2026. CA: A Cancer Journal for Clinicians, 76(1), Article e70043. https://doi.org/10.3322/caac.70043
- Zhu, E., McCreedy, E., & Teno, J. M. (2024). Bereaved Respondent Perceptions of Quality of Care by Inpatient Palliative Care Utilization in the Last Month of Life. Journal of general internal medicine, 39(6), 893–901. https://doi.org/10.1007/s11606-023-08588-4
Measure Impact
ASCO’s end-of-life quality measures were originally developed in 2003 using a patient-centered methodology to capture outcomes meaningful to those with advanced illness (Earle et al., 2003). This included:
- Focus groups consisting of patients with incurable cancer and family members of deceased patients. These participants identified and vetted potential EOL quality measures to ensure they reflected patient-centered priorities.
- Expert Consensus: A multidisciplinary expert panel applied a modified Delphi approach to rank the importance and meaningfulness of potential measures based on the focus group input. Measures that did not resonate with patient and family values (such as those focused solely on economic efficiency) were excluded.
- Literature searches.
ASCO has continued to integrate the patient and caregiver voice into the current versions of these measures:
- Expert Panel Participation: A family caregiver representative served as a formal member of the 2023–2024 ASCO EOL Expert Panel, providing direct input during the review and updating of the measures.
- May 2025 Public Comment Period: Following the updates, ASCO held a public comment period to ensure the measures remained valuable to stakeholders. Of the respondents, which included a patient representative, a significant majority agreed that the measures effectively differentiate between high- and low-quality care and assess what they intend to assess (i.e., quality of end-of-life care).
References:
Earle, C. C., Park, E. R., Lai, B., Weeks, J. C., Ayanian, J. Z., & Block, S. (2003). Identifying potential indicators of the quality of end-of-life cancer care from administrative data. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 21(6), 1133–1138. https://doi.org/10.1200/JCO.2003.03.059
Performance Gap
Individual Clinician Performance (158 Entities)
ASCO evaluated performance on the "Percentage of Patients who Died with Cancer Enrolled in Hospice For at Least 3 Days Immediately Before Death (Registry version)" measure. Using combined data from January 2023 to December 2024, the study included 158 physicians who met the minimum requirement of five eligible patients (refer to Sections 1.26 and 5.1.1 for details on sample size and testing).
Because this measure tracks hospice utilization, a higher percentage reflects stronger performance in end-of-life care. Results spanned from 0% to 78%, showing a broad spectrum in how individual physicians coordinate these transitions. The mean performance was 37% (±17%) with a 95% confidence level of ±3%; the median was slightly higher at 38%.
The distribution shows a negligible negative skew of -0.02, indicating that performance is relatively balanced around the mean, though it still leans slightly toward higher values. Notably, the mode is 17%, meaning that the most frequent individual performance level among physicians was significantly lower than the average. These results show that the highest-performing physician (78%) outperformed the median by 105% (2.05 times), while those at the bottom (0%) represent a significant gap in service. For the physicians performing below the median, these results highlight a clear opportunity to improve the timing of hospice referrals and ensure vulnerable patients receive the full benefit of palliative services.
Practice Performance (10 Entities)
ASCO evaluated performance on the "Percentage of Patients who Died with Cancer Enrolled in Hospice For at Least 3 Days Immediately Before Death (Registry version)" measure. Using combined data from January 2023 to December 2024, the study included 10 practices who met the minimum requirement of five eligible patients (refer to Sections 1.26 and 5.1.1 for details on sample size and testing).
Because this measure tracks hospice utilization, a higher percentage reflects stronger performance in end-of-life care. Results spanned from 21% to 52%, showing a spectrum in how individual practices coordinate these transitions. The mean performance was 38% (±11%) with a 95% confidence level of ± 8%; the median was higher at 41%.
The distribution shows a negative skew of -0.29, indicating that performance leans toward higher values, with more practices performing above the mean. Notably, there was no single mode identified in this sample, meaning no individual performance level occurred more than once. These results show that the highest-performing practice (52%) outperformed the median by 27% (1.27 times), while those at the bottom (21%) represent a significant gap in service. For the practices performing below the median, these results highlight a clear opportunity to improve the timing of hospice referrals and ensure vulnerable patients receive the full benefit of palliative services.
Mean Performance Score by Decile (Percentage of Patients who Died with Cancer Enrolled in Hospice For at Least 3 Days Immediately Before Death) - Clinician Level
Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Mean Performance Score | 35.21% | 0.00% | 8.41% | 16.51% | 21.65% | 26.60% | 33.15% | 37.89% | 41.77% | 46.12% | 51.52% | 64.55% | 77.78% |
| Number of Entities | 153 | 1 | 16 | 16 | 16 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 1 |
| Number of Persons | 10,250 | 9 | 1,085 | 920 | 1,061 | 1,180 | 1,027 | 1,003 | 1,159 | 983 | 948 | 874 | 9 |
Mean Performance Score by Decile (Percentage of Patients who Died with Cancer Enrolled in Hospice For at Least 3 Days Immediately Before Death) - Practice Level
| Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Mean Performance Score | 37.6% | 21.0% | 21.0% | 22.0% | 29.0% | 30.0% | 40.0% | 41.0% | 45.0% | 45.0% | 51.0% | 52.0% | 52.0% |
| Number of Entities | 10 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Number of Persons | 9,023 | 458 | 458 | 2,155 | 813 | 609 | 894 | 668 | 654 | 655 | 436 | 1,681 | 1,681 |
Care Gaps
Closing Care Gaps
A recent systematic review and meta-analysis looked at aggressive EOL cancer care among ~2.7 million patients across 129 studies and found that aggressive EOL care is a common global practice (Ma et al., 2024):
- Repeated hospital admissions (>1) in the last 30 days of life: 17.9%.
- Repeated emergency room visits (>1) in the last 30 days of life: 14.8%.
- Intensive care unit (ICU) stays in the last 30 days of life: 14.4%.
- Hospice enrollment less than 3 days before death: 14.4%.
- Chemotherapy in the last 14 days of life: 11.6%.
Additionally, of the studies using a composite score, more than half of the patients experienced at least one measure of aggressive care at the end of their lives. The research also showed that patients with hematologic malignancies were significantly more likely to receive aggressive care, including higher rates of late hospice enrollment, ICU stays, and chemotherapy in the last weeks of life, compared to those with solid tumors (Ma et al., 2024).
There is evidence of gaps in care among lower-level studies as well. A retrospective review evaluated 2,844 patients in a multistate, community-based hospital network with stage IV NSCLC and found that only 8 percent of patients were referred for outpatient palliative care (Meggyesy et al., 2022).
CMS launched the Enhancing Oncology Model (EOM) in July 2023. EOM is a voluntary, episode-based model that 44 oncology practices treating patients with high-risk cancer participate in. Per the 2025 Enhancing Oncology Model – First Evaluation Report, only 51.1% of EOM patients who died were admitted to hospice for at least 3 days before their death, indicating much room for improvement on this measure (CMS, 2025).
References:
- Centers for Medicare & Medicaid Services. (2025). EOM First Evaluation Main Report. https://www.cms.gov/priorities/innovation/data-and-reports/2025/eom-1st-eval-report
- Ma, Z., Li, H., Zhang, Y., Zhang, L., Huang, G., Zhang, Y., Shi, L., Liu, W., An, Z., & Guan, X. (2024). Prevalence of aggressive care among patients with cancer near the end of life: a systematic review and meta-analysis. EClinicalMedicine, 71, 102561. https://doi.org/10.1016/j.eclinm.2024.102561
- Meggyesy, A. M., Buehler, K. E., Wilshire, C. L., Chiu, S. T., Chang, S.-C., Rayburn, J. R., Gilbert, C. R., & Gorden, J. A. (2022). Utilization of palliative care resource remains low, consuming potentially avoidable hospital admissions in stage IV non-small cell lung cancer: A community-based retrospective review. Supportive Care in Cancer, 30(12), 10117–10126. https://doi.org/10.1007/s00520-022-07364-0
There are also disparities in hospice utilization and length of stay (LOS) by race/ethnicity. A 2023 original investigation analyzed hospice use among Medicaid-only and dual beneficiaries in the Connecticut Medicaid program who died over a 4-year period. In both populations, Hispanic and non-Hispanic African Americans decedents had significantly lower odds of using hospice compared to non-Hispanic White decedents (OR Medicaid-only = .76 & .77 and OR duals = .89 & .74). The study also found that Hispanic decedents were more likely to have a short hospice stay (defined by the study as 1-7 LOS days per the study) compared to non-Hispanic White decedents (OR Medicaid-only = 2.32 and OR duals = 1.25). (Robison et al.)
Another recent study evaluated hospice utilization among Medicare decedents with advanced cancers and found that non-Hispanic African American beneficiaries had 8.56 percentage points lower hospice enrollment than non-Hispanic White beneficiaries, and Hispanic beneficiaries had 2.62 percentage points lower enrollment than non-Hispanic White beneficiaries. (Xu et al., 2026)
References:
- Robison J, Shugrue N, Dillon E, et al. Racial and Ethnic Differences in Hospice Use Among Medicaid-Only and Dual-Eligible Decedents. JAMA Health Forum. 2023;4(12):e234240. doi:10.1001/jamahealthforum.2023.4240
- Hu X, Jiang C, Kwon Y, et al. Medicare Plan Switching and Hospice Care Among Decedents With Advanced Cancer. JAMA Netw Open. 2026;9(3):e260755. doi:10.1001/jamanetworkopen.2026.0755
Feasibility
Feasibility
The measure is designated as a Clinical Quality Measure (CQM), with all underlying data elements fully aligned with USCDI (United States Core Data for Interoperability) and USCDI+ Quality standard definitions. Calculation is performed via digital methodology, utilizing electronic sources where key data elements are captured within defined, structured fields.
The measure’s high level of utilization and successful reporting within the Merit-based Incentive Payment System (MIPS) demonstrate its low administrative burden and overall ease of reporting. By adhering to the national interoperability standards and leveraging existing electronic data fields, the measure ensures high data fidelity and standardized reporting across clinical environments.
Data collection for this measure is conducted in strict accordance with HIPAA Privacy and Security Rules. Confidentiality is maintained because the measure utilizes de-identified Electronic Health Record (EHR) data sourced from clinical systems. Direct identifiers are removed or masked prior to the data being made available for measure calculation, ensuring that the analysis remains focused on clinical patterns and outcomes rather than individual patient identities.
To mitigate the risk of re-identification in small patient populations (the "Small N" problem), a minimum threshold of five (5) patients is suggested for performance reporting. This recommended suppression guideline is intended to prevent "deductive disclosure," where an individual’s identity could potentially be inferred from a very small data set or outlier results within a specific clinical facility. By suggesting this minimum volume, the measure balances the need for transparent, data-driven reporting with the highest standards of patient privacy.
Finally, confidentiality risks associated with patient surveys are not applicable to this measure, as it relies entirely on clinical data extracted from EHRs with no direct patient interaction or survey-based data collection.
The continued use of the measure reflects a mature, data-driven tool that leverages existing electronic health record capabilities to ensure efficient reporting and reliable performance. This long-standing measure is fully optimized for contemporary clinical environments.
Proprietary Information
As the world’s leading professional organization for physicians and others engaged in clinical cancer research and cancer patient care, American Society of Clinical Oncology, Inc. (“Society”) and its affiliates1 publishes and presents a wide range of oncologist‐approved cancer information, educational and practice tools, and other content. The ASCO trademarks, including without limitation ASCO®, American Society of Clinical Oncology®, JCO®, Journal of Clinical Oncology®, Cancer.Net™, QOPI®, QOPI Certification Program™, and Conquer Cancer®, are among the most highly respected trademarks in the fields of cancer research, oncology education, patient information, and quality care. This outstanding reputation is due in large part to the contributions of ASCO members and volunteers. Any goodwill or commercial benefit from the use of ASCO content and trademarks will therefore accrue to the Society and its respective affiliates and further their tax‐exempt charitable missions. Any use of ASCO content and trademarks that may depreciate their reputation and value will be prohibited.
ASCO does not charge a licensing fee to not-for-profit hospitals, healthcare systems, or practices to use the measure for quality improvement, research or reporting to federal programs. ASCO encourage all of these not-for-profit users to obtain a measure library license so ASCO can:
- Keep users informed about measure updates and/or changes
- Learn from measure users about any implementation challenges to inform future measure updates and/or changes
- Track measure utilization (outside of federal reporting programs) and performance rates
ASCO has adopted the Council of Medical Specialty Society’s Code for Interactions with Companies (https://cmss.org/wp-content/uploads/2026/04/CMSS-Code-for-Interactions-…), which provides guidance on interactions with for‐profit entities that develop produce, market or distribute drugs, devices, services or therapies used to diagnose, treat, monitor, manage, and alleviate health conditions. The Society’s Board of Directors has set Licensing Standards of American Society of Clinical Oncology ( https://cdn.bfldr.com/KOIHB2Q3/as/bsrth8mwgbsrpvrsbt6gxqb/2023-ASCO-Lic…) to guide all licensing arrangements.
In addition, ASCO has adopted the Council of Medical Specialty Society’s Policy on Antitrust Compliance (https://cmss.org/statements/cmss-policy-on-antitrust-compliance/), which provided guidance on compliance with all laws applicable to its programs and activities, specifically including federal and state antitrust laws, including guidance to not discuss, communicate, or make announcements about fixing prices, allocating customers or markets, or unreasonably restraining trade.
Scientific Acceptability
Testing Data
Testing for this measure was conducted using Electronic Health Record (EHR) data sourced from The US Oncology Network (USON)/McKesson databases. This data provided comprehensive national geographic coverage, spanning urban, suburban, and rural regions. The analysis included a total of 158 physicians and 10 practices identified within the USON network.
The testing period for both data sources encompassed the timeframe from January 1, 2023, to December 31, 2024. This two-year window ensures the measure was validated against the most current coding standards and clinical practice patterns, providing a stable and contemporary baseline for analysis.
There are specific differences in the sample sizes used for various aspects of testing, driven by the clinical sensitivity of the measure and the statistical requirements of the analysis:
Performance Gap and Validity Testing
Threshold: Entities with a minimum of five (5) patients meeting the measure denominator.
Sample Size:
- At the individual clinician level, the analysis included 158 reporting entities (derived from USON/McKesson Electronic Health Record (EHR) data, Jan 1, 2023 – Dec 31, 2024).
- At the practice level, the analysis included 10 reporting entities (derived from USON/McKesson Electronic Health Record (EHR) data, Jan 1, 2023 – Dec 31, 2024).
Rationale: This is an end-of-life hospice utilization measure. Because hospice enrollment is a critical quality indicator in oncology, ASCO determined that "each patient matters" in the assessment of care delivery. A lower threshold of N ≥ 5 was utilized to prioritize “Visibility over Volatility.”
- Health Equity: Utilizing a broader inclusion criteria prevents quality "blind spots" in community-based or rural oncology settings where EOL events are significant but may occur less frequently. High thresholds would effectively penalize these practices by making their care invisible to the measure.
- Clinical Significance: While smaller denominators inherently have a higher standard error, the clinical priority of ensuring timely hospice access outweighs the statistical risk of "noisy" scores at the individual entity level.
Reliability Testing
Threshold: Entities with a minimum of twelve (12) patients meeting the measure denominator.
Sample Size:
- At the individual clinician level, the analysis included 147 reporting entities (a subset of the EHR dataset described above).
- For practice-level reporting, 10 entities were identified. This group represents the full aggregate of the aforementioned cohort, as all practices met or exceeded the 12-patient minimum threshold.
Rationale: A higher threshold of N ≥ 12 was applied specifically for reliability testing to maintain psychometric rigor.
- Signal-to-Noise Ratio: For a measure’s reliability coefficient (Beta) to be stable, there must be enough patient volume to distinguish true clinical variation from random statistical noise.
- Instrument Validation: Using these 147 higher-volume entities ensures that the reliability of the "measurement instrument" itself is validated on a stable data set before being applied to the broader clinical population.
Exclusions and Risk Adjustment
No other differences in data sources or timeframes were utilized for exclusions or risk-adjustment testing.
Performance on this measure was assessed for a cohort of 158 physicians and 10 practices affiliated with the US Oncology Network (USON)/McKesson across the United States.
To ensure patient privacy, characteristics of the eligible population were not attributed to specific practices or physicians. We obtained aggregate demographic data from USON for patients who reported gender and race; the demographic profile for the overall sample is detailed in the tables below.
| Characteristic | Category | Patient Count (n) | Percentage (%) |
|---|---|---|---|
| Gender (N=9,023) | Male | 4,999 | 55.4% |
| Female | 4,024 | 44.6% | |
| Race (N=8,468) | White | 7,010 | 82.8% |
| Black or African American | 436 | 5.1% | |
| Other | 305 | 3.6% | |
| Asian | 149 | 1.8% | |
| American Indian or Alaska Native | 30 | 0.4% | |
| Native Hawaiian or Other Pacific Islander | 11 | 0.1% | |
| Declined to Specify | 520 | 6.1% | |
| Unknown | 7 | 0.1% |
Note: Race data was available for 93.8% (n=8,468) of the total eligible population (N=9,023). The discrepancy reflects instances of missing or undocumented values in the source dataset and does not impact the statistical integrity of the overall analysis.
Reliability
Firstly, to verify the reliability of the data elements in this measure, a random sample of 105 patients was selected across 8 different test sites. Scoring for each data element was performed by both a measure abstractor and an automated algorithm, with the Kappa statistic used to evaluate the level of agreement between the two methods. The denominator, numerator, denominator exception, and numerator exception data elements were assessed for all 105 patients.
Secondly, an assessment of the measure's reliability was performed through the utilization of signal-to-noise analysis, a method that determines the precision of the actual construct in comparison to the random variation. The signal-to-noise ratio is determined by calculating the ratio of between-unit variance to total variance. This analysis provides valuable insight into the measure's reliability and its ability to produce consistent results by describing how well one can confidently distinguish the performance of one clinician from another.
Based on the hierarchical modeling approach for provider profiling, the following steps were taken:
- Data Aggregation: Patient-level data were captured as binary (pass/fail) events and aggregated to the clinician level to determine the numerator and denominator for each physician.
- Model Selection: We utilized a Beta-Binomial model, which is the natural fit for estimating the reliability of simple pass/fail rate measures.
- Variance Partitioning: The model partitioned the total observed variability in practice scores into two components: between-unit variance (the "signal," or true differences in physician quality) and within-unit variance (the "noise," or random sampling error).
- Reliability Calculation: For each clinician, a reliability coefficient (R) was calculated using the ratio of the estimated provider-to-provider variance to the sum of the provider-to-provider variance and the binomial error variance (p(1-p)/n).
- Threshold Application: The analysis focused on identifying the stability of these scores for physicians meeting a minimum patient count of 12.
Person or Encounter Level (Data Element) Testing
Percentage of Patients who Died with Cancer Enrolled in Hospice For at Least 3 Days Immediately Before Death
| Measure Data Element | Kappa Estimate | Standard Error | 95% Confidence Limits | |
| Denominator | 1.0000 | 0.0000 | 1.0000 | 1.0000 |
| Numerator | 1.0000 | 0.0000 | 1.0000 | 1.0000 |
| Denominator Exception | 1.0000 | 0.0000 | 1.0000 | 1.0000 |
| Numerator Exception | 1.0000 | 0.0000 | 1.0000 | 1.0000 |
Accountable Entity Level (Measure Score) Testing
Reliability was assessed at the clinician level using a beta-binomial signal-to-noise analysis, which partitions total observed variation into true performance differences and random sampling error. Across 147 entities and 8,919 persons, the measure yielded an overall mean reliability of 0.818, significantly exceeding the >0.60 target threshold. Results confirmed that statistical stability scales with patient volume: while the first decile averaged 0.64, the second reached 0.747, further validating the 12-patient minimum for consistently distinguishing performance. Entities in the highest decile achieved a reliability of 0.922, confirming that the measure provides a highly stable performance signal with minimal influence from random noise.
Additionally, reliability was assessed at the practice level using a beta-binomial signal-to-noise analysis, which partitions total observed variation into true performance differences and random sampling error. Across 10 practices and 9,023 persons, the measure yielded an overall mean reliability of 0.974, significantly exceeding the >0.60 target threshold. Results confirmed exceptional statistical stability across all cohorts; while the first decile averaged 0.952, the second reached 0.969, validating that the measure maintains a highly consistent signal even at the observed 436-patient minimum. Practices in the highest decile achieved a reliability of 0.993, confirming the measure provides a near-perfect performance signal with negligible influence from random noise.
Person or Encounter Level (Data Element) Testing
The inter-rater reliability analysis yielded a Kappa Estimate of 1.0000 across all key data elements, including the numerator and exception logic. This result represents absolute concordance and serves as definitive evidence of the measure’s technical and operational stability.
Such a perfect level of agreement is directly attributable to the long-standing operationalization of these measures. Rather than relying on subjective clinical interpretation or manual abstraction, these measures are built upon highly specific, structured data fields that have been refined over several years of active use. By utilizing standardized coding sets and discrete data elements, the measure eliminates the "noise" typically associated with human error or varying clinical documentation styles.
Clinician Level Interpretation (Based on 147 entities and 8,919 persons)
The results support a strong inference of reliability, as the mean coefficient of 0.818 indicates that the 'signal' of true performance differences significantly outweighs random sampling error. Because high reliability is essential for confidently distinguishing the performance of one provider from another, these scores demonstrate the measure's suitability for comparative profiling. The decile distribution further supports this inference, as 100% of the sample deciles met or exceeded the >0.60 benchmark. Specifically, reaching a mean reliability of 0.640 in the first decile and 0.747 in the second validates that a 12-patient minimum threshold provides a sufficient sample to mitigate the probability of misclassifying clinicians due to random noise. Collectively, these findings demonstrate that the measure provides a stable, repeatable, and precise assessment of clinician performance.
Practice Level Interpretation (Based on 10 practices and 9,023 persons)
The results support a superior inference of reliability, as the mean coefficient of 0.974 indicates that the 'signal' of true performance differences almost entirely outweighs random sampling error. Because high reliability is essential for confidently distinguishing the performance of one practice from another, these scores demonstrate the measure's exceptional suitability for comparative profiling. The decile distribution further supports this inference, as 100% of the sample deciles vastly exceeded the >0.60 benchmark, with every decile scoring above 0.95. Specifically, reaching a mean reliability of 0.952 in the first decile validates that the measure provides a near-perfect assessment with negligible influence from random noise at this scale. Collectively, these findings demonstrate that the measure provides a highly stable, repeatable, and precise assessment of practice-level performance.
Reliability and Performance Score by Denominator Decile: Percentage of Patients who Died with Cancer Enrolled in Hospice for At Least 3 Days Immediately Before Death (Registry version), Clinician Level, Jan 2023 – Dec 2024
| Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Reliability | 0.818 | 0.533 | 0.64 | 0.747 | 0.764 | 0.801 | 0.836 | 0.84 | 0.856 | 0.893 | 0.888 | 0.922 | 0.973 |
| Mean Performance Score | 29.9% | 26.0% | 27.0% | 28.7% | 25.9% | 29.3% | 32.7% | 30.1% | 29.9% | 29.9% | 33.0% | 32.2% | 44.0% |
| Number of Entities | 147 | 3 | 15 | 15 | 14 | 15 | 15 | 14 | 15 | 14 | 15 | 15 | 1 |
| Number of Persons | 8,919 | 12 | 270 | 414 | 486 | 652 | 819 | 866 | 1,067 | 1,163 | 1,380 | 1,802 | 193 |
Reliability and Performance Score by Denominator Decile: Percentage of Patients who Died with Cancer Enrolled in Hospice for At Least 3 Days Immediately Before Death (Registry version), Practice Level, Jan 2023 – Dec 2024
| Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Reliability | 0.974 | 0.952 | 0.952 | 0.969 | 0.971 | 0.968 | 0.968 | 0.969 | 0.978 | 0.977 | 0.987 | 0.993 | 0.993 |
| Mean Perf. Score | 37.6% | 51.1% | 51.1% | 21.0% | 29.6% | 45.0% | 44.9% | 41.0% | 28.9% | 40.5% | 52.0% | 22.5% | 22.5% |
| Num. of Entities | 10 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Num. of Persons | 9,023 | 436 | 436 | 458 | 609 | 654 | 655 | 668 | 813 | 894 | 1,681 | 2,155 | 2,155 |
Reliability by Reliability Score: Percentage of Patients who Died with Cancer Enrolled in Hospice for At Least 3 Days Immediately Before Death (Registry version), Clinician Level, Jan 2023 – Dec 2024
| Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Reliability | 0.818 | 0.49 | 0.619 | 0.722 | 0.776 | 0.813 | 0.833 | 0.847 | 0.865 | 0.882 | 0.9 | 0.93 | 0.973 |
Reliability by Reliability Score: Percentage of Patients who Died with Cancer Enrolled in Hospice for At Least 3 Days Immediately Before Death (Registry version), Practice Level, Jan 2023 – Dec 2024
| Overall | Min | Decile 1 | Decile 2 | Decile 3 | Decile 4 | Decile 5 | Decile 6 | Decile 7 | Decile 8 | Decile 9 | Decile 10 | Max | |
| Reliability | 0.974 | 0.952 | 0.952 | 0.968 | 0.968 | 0.969 | 0.969 | 0.971 | 0.977 | 0.978 | 0.987 | 0.993 | 0.993 |
Validity
We evaluated the construct validity of three oncology performance measures focused on end-of-life care at both the physician and practice levels. By examining the Pearson correlation coefficients and their statistical significance, we determined whether the empirical relationships reliably align with expected clinical logic and theoretical frameworks regarding end-of-life care pathways.
Measures Evaluated
- Hospice ≥ 3 Days: Percentage of patients who died with cancer enrolled in hospice for at least 3 days immediately before death.
- Therapy Last 14 Days: Percentage of patients who died with cancer receiving systemic cancer-directed therapy in the last 14 days of life.
- Therapy Last 30 Days: Percentage of patients who died with cancer receiving systemic cancer-directed therapy in the last 30 days of life.
Physician-Level Analysis (N = 158)
Hypothesized Relationships
At the individual provider level, we expect a convergent (positive) relationship between the two aggressive systemic therapy measures, and a divergent/inverse (negative) relationship between meaningful hospice enrollment and end-of-life systemic therapy.
Practice-Level Analysis (N = 10)
Hypothesized Relationships
Consistent with the physician-level analysis, we expect practices with a high propensity to administer late systemic therapy to show strong positive correlations between the two therapy timelines, and strong negative correlations regarding timely hospice enrollment, as meaningful hospice care requires the cessation of curative therapies.
Physician-Level Analysis (N = 158)
Empirical Findings & Significance
- Evidence of Convergent Validity (Therapy vs. Therapy)
- Result: A strong, highly significant positive correlation (r = 0.6669, p < 0.0001) exists between Therapy Last 14 Days and Therapy Last 30 Days.
- Interpretation: Individual physicians who tend to prescribe systemic therapy within the last month of life are also highly likely to prescribe it within the final two weeks of life. The incredibly low p-value confirms with near absolute certainty that these two measures are capturing the same underlying physician behavioral construct regarding aggressive end-of-life treatment.
- Evidence of Divergent/Inverse Validity (Hospice vs. Therapy)
- Result: Statistically significant negative correlations were observed between Hospice ≥ 3 Days and both systemic therapy measures (r = -0.2478, p = 0.0017 for 14 Days; r = -0.1950, p = 0.0141 for 30 Days).
- Interpretation: The relationships are highly statistically significant due to the large sample size. This confirms the clinical trade-off holds true at the provider level: physicians with a higher tendency to utilize late-stage systemic treatments systematically display lower rates of effectively transitioning patients to hospice care for at least 3 days prior to death.
Practice-Level Analysis (N = 10)
Empirical Findings & Significance
- Evidence of Convergent Validity (Therapy vs. Therapy)
- Result: A strong, highly significant positive correlation (r = 0.7998, p = 0.0055) was observed between Therapy Last 14 Days and Therapy Last 30 Days.
- Interpretation: As expected, practices that frequently administer systemic therapy in the final month of life also frequently administer it in the final two weeks. The high statistical significance indicates there is less than a 1% probability that this strong alignment occurred by random chance.
- Evidence of Divergent/Inverse Validity (Hospice vs. Therapy)
- Result: Strong, significant negative correlations were observed between the Hospice ≥ 3 Days measure and both therapy measures (r = -0.8045, p = 0.0050 for Therapy Last 30 Days; r = -0.6446, p = 0.0442 for Therapy Last 14 Days).
- Interpretation: This inverse relationship provides excellent, statistically backed validation. It demonstrates that the measures successfully capture the clinical trade-off between palliative/hospice care and aggressive systemic treatment at the aggregate organizational level. Practices with higher utilization of end-of-life systemic therapy are demonstrably and non-randomly delaying or underutilizing hospice care.
Physician-Level Analysis (N = 158)
The analysis of 158 individual providers strongly supports the construct validity of these measures. The empirical data reliably reflects expected clinical pathways, demonstrating that timely hospice enrollment and late-stage systemic therapy act as competing, inverse clinical priorities at the physician level.
Practice-Level Analysis (N = 10)
The correlation data provides robust, statistically significant evidence for the construct validity of these three performance measures. Even with a smaller sample size of 10 practices, the strength of the clinical relationships drives highly significant results.
- Overall Summary
Across both individual physician behaviors (N=158) and aggregated practice patterns (N=10), these three measures interact exactly as predicted by established clinical pathways. The empirical data mathematically and significantly reflects the reality that aggressive systemic treatment and timely hospice enrollment are competing clinical events. Stakeholders can be highly confident that these measures are accurately and reliably capturing valid dimensions of end-of-life oncology care quality across different levels of attribution.
Risk Adjustment
The decision to maintain unadjusted performance scores for these end-of-life measures is rooted in the philosophy that quality palliative care and clinical stewardship represent universal standards that should not fluctuate based on patient complexity. Unlike outcomes heavily influenced by biological variance, metrics such as systemic therapy administration and ICU utilization reflect direct clinical decision-making and provider agency; therefore, risk adjustment could inadvertently "normalize" aggressive care by suggesting that medical complexity justifies a departure from palliative best practices. Furthermore, because these measures are calculated using a denominator of patients who have already deceased, the cohort is inherently characterized by high clinical risk, making additional adjustment statistically redundant and potentially misleading. By prioritizing unadjusted data, ASCO maintains a transparent view of the raw clinical reality, ensuring that gaps in service and health inequities remain visible rather than being masked by statistical smoothing. Ultimately, this approach upholds the principle that every patient, regardless of their diagnosis or comorbidities, deserves a timely transition to hospice and a coordinated, comfort-focused end-of-life experience.
Use & Usability
Use
As the measure steward, ASCO is committed to the broad implementation of this measure across the national quality landscape. We are in ongoing consultations with CMS regarding its inclusion in programs such as MIPS, PCHQR and IQR. Our roadmap includes finalizing the technical specifications required for federal uptake while simultaneously promoting the measure for use in private payer quality initiatives, VBPs and ASCO’s own quality improvement portfolio.
This updated CBE 0216 quality measure will be used in MIPS beginning PY 2027; the annual update process is currently underway. It will also be used in ASCO Certified in the future.
MIPS takes a comprehensive approach to payment by basing consideration of quality on a set of evidence-based measures that were primarily developed by clinicians, thus encouraging improvement in clinical practice and supporting advances in technology that allow for easy exchange of information.
MIPS eligible providers may earn performance-based payment adjustments for the services provided to Medicare patients in the USA. For the 2023 MIPS reporting year, 3,035 individual clinicians reported on MIPS 457. Of these, 3,010 practice in urban or suburban locations, while 25 practice in rural locations. The Northeast has the highest overall volume of reporting clinicians (1,846), led by New York (NY) with 1,314 practitioners and New Jersey (NJ) with 507. Following the Northeast in total volume are the West (837), the South (289), and the Midwest (63). Notably, the Midwest has the highest number of clinicians practicing at rural locations with 19, a concentration entirely driven by Indiana (19).
Individual Clinician/Group Level; Registry Data Source; Outpatient Services/Ambulatory Care Setting
1. Target Populations
The measure is applicable to adult patients (aged 18 and older) with a confirmed diagnosis of cancer.
2. Accountable Entities
Accountability is attributed at the level of the individual clinician or physician.
- Attribution Logic: Patients are attributed to the entity that provides the plurality of oncology-related services or manages the "episode of care" (e.g., the six-month period following the initiation of chemotherapy).
- Responsibility: The entity is held accountable for the patient’s clinical outcomes, resource utilization (such as avoidable ER visits), and adherence to evidence-based pathways.
3. Care Settings
The primary care setting is the Outpatient Oncology Clinic, including:
- Community-based oncology practices.
- Hospital Outpatient Departments (HOPDs).
- Infusion Centers.
Note on Care Settings: Clinical oncologists provide care within the outpatient setting; however, this measure set monitors related clinical outcomes across multiple sites of service. Evaluated events include, but are not limited to, inpatient/outpatient hospital infusions, ICU stays, and emergency department encounters stemming from complications of the outpatient treatment.
Usability
There is evidence that there are interventions that can be put in place to increase time spent in hospice, therefore improving the performance on the measure score:
- In general, patients with weeks to days to live (eg, dying patients) and comfort-oriented goals should discontinue all treatments not directly contributing to patient comfort. Intensive palliative care focusing on symptom management should be provided in addition to preparation for the dying process. Referral for hospice care should be placed, if not already done. (Category 2A) (NCCN, 2026)
- Clinicians should refer patients with advanced solid tumors and hematologic malignancies to specialized interdisciplinary palliative care teams that provide inpatient and outpatient care early in the course of disease, alongside active treatment of their cancer (Moderate, Strong) (Sanders et al., 2024)
- Palliative care for patients with advanced cancer should be delivered through interdisciplinary palliative care teams, with consultation available in both outpatient and inpatient settings (Intermediate, Moderate) (Sanders et al., 2024)
- Patients with advanced cancer should receive palliative care services, which may include a referral to a palliative care provider. Essential components of palliative care include (Intermediate, Moderate) (Sanders et al., 2024)
- Rapport and relationship building with patient and family caregivers
- Symptom, distress, and functional status management (eg, pain, dyspnea, fatigue, sleep disturbance, mood, nausea, or constipation)
- Exploration of understanding and education about illness and prognosis
- Clarification of treatment goals
- Assessment and support of coping and spiritual needs
- Assistance with medical decision making
- Coordination with other care providers
- Provision of referrals to other care providers as indicated
- Patients with months to weeks to live should be provided with guidance regarding the anticipated course of the disease. Physicians should reassess prognostic awareness and goals of therapy. As functional status worsens, these patients may become more concerned about the side effects of cancer-directed treatment and consider focusing their care on maintaining quality of life. The option of discontinuing anticancer treatment aligned with goals of care and initiating goal-directed supportive care should be discussed. (Category 2A) (NCCN, 2026)
The below outlines the difficulty of the actions described above and how measures entities can overcome those difficulties:
| Action | Difficulty Level | Why it is Difficult | How to Overcome |
| Early Referral | Moderate | Shortage of specialist palliative care clinicians and the stigma that palliative care means "giving up." Clinician reluctance to initiate "hospice" talk, often due to a desire to pursue further curative lines of therapy. | In addition to physicians, oncology nurses can be positioned to provide primary palliative care and provide increased advance care planning with patients with advanced cancer (NCCN, 2026). The <NCCN> Panel emphasizes the importance of initiating or continuing advance care planning conversations and systematically reviewing advance care plans to ensure ongoing accuracy as illness or situation evolves. To avoid demeaning the value of end of life care, palliative and/or hospice care should not be framed as “giving up” but instead refocusing the care plan to achieve a better quality of life (NCCN, 2026) Frame hospice as an "extra layer of support" that maximizes quality of life (QOL) alongside or following treatment. |
| ACP Documentation | High | These conversations are time-intensive and clinicians often lack training in high-stakes communication. | Embed ACP templates in the EHR. Use a "primary care/oncology" shared model where social workers or nurses lead initial goals of care discussions. |
| Prognostication Accuracy | High | Difficulty accurately predicting a <6 month life expectancy, particularly in cancers with fluctuating trajectories. | Use prognostic tools and multidisciplinary team reviews (doctors, nurses, social workers) to assess decline more holistically. |
| Patient/Family Resistance | High | Misperception that hospice is "giving up" or only for the actively dying. | Provide education on the broad palliative services covered, including symptom management and bereavement support for the family. |
References:
- National Comprehensive Cancer Network. (2026). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®): Palliative Care (Version 1.2026). https://www.nccn.org/guidelines/guidelines-detail?id=1454
- Sanders, J. J., Temin, S., Ghoshal, A., Alesi, E. R., Ali, Z. V., Chauhan, C., Cleary, J. F., Epstein, A. S., Firn, J. I., Jones, J. A., Litzow, M. R., Lundquist, D. M., Mardones, M. A., Nipp, R. D., Rabow, M. W., Rosa, W. E., Zimmermann, C., & Ferrell, B. R. (2024). Palliative Care for Patients with Cancer: ASCO guideline Update. Journal of Clinical Oncology, 42(19), 2336–2357. https://doi.org/10.1200/JCO.24.00542
ASCO has not received any feedback on measure performance or implementation from measured entities within MIPS. The updated measure will be used beginning with CY 2027 within the MIPS program. ASCO’s EOL Measures TEP did discuss that there is extensive literature showing that hematology patients are much less likely to receive hospice care or use it meaningfully, i.e., for an appropriate amount of time. In speaking with referring physicians, there is a clear indication that transfusions are a barrier to hospice care. Though there is not a ban on transfusions, there is a per diem that the hospice benefit will pay to hospice agencies and some hospices will refuse care for patients seeking transfusion support. This leads to those patients not enrolling in hospice or enrolling late. However, the panel wanted to keep hematology patients in this measure to track performance. ASCO also received feedback from its May 2025 public comment to increase the number of days to 2 weeks or 30 days for this hospice measure; however the TEP did not want to make too many changes at once so opted to retain the three-day timeframe.
See above in 6.2.2.
As this updated measure now looks at both time spent in and admittance to hospice among patients who died with cancer, ASCO does not have data on performance trends from MIPS reporting entities at this time. Changes to the denominator should show an increased gap in care, since the original measure looked only at time spent in hospice among deceased cancer patients admitted to hospice, and this updated measure looks at admittance to AND time spent in hospice, among patients with cancer who died. Therefore MIPS benchmarking will be affected, but otherwise there are no unintended consequences ASCO is aware of.
As part of its May 2025 call for public comments on ASCO’s updated EOL measures, ASCO did receive feedback from respondents to add more exclusions and exceptions for treatment intent, clinical trial enrollment, patient preferences, and barriers to access palliative care and hospice. ASCO’s End of Life Measures Technical Expert Panel emphasizes that performance is not expected to be perfect on these quality measures. A margin of error should be expected to account for the above.
Comments
Staff Preliminary Assessment
CBE #0216 Staff Assessment
Importance
Strengths:
- A clear logic model is provided, depicting the relationships between inputs (e.g., access to an interdisciplinary palliative care team, hospital liaison agreements, and educational tools), activities (e.g., proactive screening, standardized goals of care discussions, and timely referral), and desired outcomes (e.g., reductions in emergency department visits, hospitalizations, and intensive care unit [ICU] visits, increase in the percentage of patients enrolled in hospice for at least three days before death, and improved symptom control, comfort, quality of life, and patient and caregiver satisfaction). This model demonstrates how the measure's implementation will lead to the anticipated outcomes.
- The problem this measure addresses presents a significant concern for patients dying with cancer, families, and caregivers. Evidence suggests that most patients nearing the end of life wish to die at home and caregivers give higher end of life care quality ratings for home hospice care compared to other end of life care. Timely hospice and palliative care enrollment reduces aggressive interventions and high-intensity care, thus improving patient and caregiver satisfaction, and reduces resource utilization costs.
- The measure is supported by a comprehensive literature review, including a systematic review with high evidence quality, clinical practice guidelines with evidence grading of strong, and five high quality empirical studies demonstrating a clear net benefit in terms of improved quality of life and satisfaction and reduced resource utilization including lower odds of chemotherapy and reduced hospitalizations.
- Data from January 2023 to December 2024 show a performance gap, with decile ranges from 8.41% to 64.55% at the clinician level and 21% to 52% at the practice level indicating variation in measure performance across the target population.
- Description of patient input supports the conclusion that the measured intermediate outcome is meaningful with at least moderate certainty. Patient input was obtained through focus groups, expert consensus, and public comments which included patients with incurable cancer, family members, and caregivers.
Limitations:
- Although the developer indicated they had gathered patient and caregiver input through a technical expert panel and public comment period, direct engagement with and feedback from patients themselves is limited.
Rationale:
- This maintenance measure meets all criteria for ‘Met’ for importance due to the significance of the problem it addresses, anticipated impact, robust evidence base, a documented performance gap in late hospice referral patterns, and well-articulated logic model, making it essential for addressing quality and appropriateness of end-of-life care. There is at least moderate confidence that the business case is adequate, i.e., the anticipated impacts of the measure on patient outcomes and resource use justify use of the measure.
Closing Care Gaps
Strengths:
- The developer provided some evidence of gaps in care related to the measure's focus for subgroups, including evidence from a literature review.
Limitations:
- While the developer presented some evidence of gaps in care through a limited literature review, they did not empirically test differences in performance across identified subgroup variables as required for maintenance endorsement.
Rationale:
- While the developer attempted to assess gaps in care for end of life cancer care by presenting evidence from existing literature, they did not empirically test differences in the measure’s performance across identified subgroup variables. This limits the ability to provide a comprehensive understanding of the differences in performance across different populations.
Feasibility Assessment
Strengths:
- All required data elements are routinely generated during care delivery, and required elements are available from digital or electronic sources.
- The developer indicated that the denominator has been broadened to capture all patients aged 18 and older who died with cancer, rather than only considering patients who were admitted to hospice.
- The developer stated that no feasibility issues were found requiring adjustment of the final measure specifications.
- The developer indicated that there are no significant costs and burden associated with data collection and data entry, validation, and analysis. They indicated that high utilization and successful reporting within the Merit-based Incentive Payment System (MIPS) demonstrates its low administrative burden and ease of reporting. They also noted that the measure adheres to the national interoperability standards and leverages existing electronic data fields to ensure high data fidelity and standardized reporting.
The developer described how all required data elements can be collected without risk to patient confidentiality, including suggesting a minimum volume of five patients for performance reporting to prevent the potential re-identification in small patient populations. - Any fees, licensing, or other requirements to use any aspect of the measure (e.g., value/code set, risk model, programming code, algorithm) are clearly described and justified.
Limitations:
- The fee for entities that are not non-profits is not stated. There is an outstanding question if the fee structure places the measure out of reach for rural and safety net clinicians and group practices.
- The developer states that, the measure relies entirely on clinical data extracted from EHRs with no direct patient interaction or survey-based data collection. It seems that this is the case for the measure implemented within the McKesson Oncology Network Registry. It is unclear if these findings are the same with entities reporting the measure that are not reporting in the McKesson Oncology Network Registry. The fact that the measure can be reported using EHR data raises the question why the measure is not specified as a digital measure (eCQM, Fast Health Interoperability Resources (FHIR) digital quality measure), which may reduce reporting burden.
- The measure specification is embedded in the measure submission, which makes review challenging. In addition, there is not a corresponding file with codes used in the measure specification, for ease of review. The developer may consider including the complete specification as an attachment, to ease review by endorsement and maintenance committee members.
Rationale:
- The maintenance measure is rated as ‘Not Met, but Addressable’ for feasibility due to lack of clarity in the following areas: 1) Cost for use by clinicians and group practices that are NOT non-profits and if this is manageable for rural and safety net systems; and 2) Question regarding the electronic implementation by entities not reporting to the McKesson registry.
Scientific Acceptability
Strengths:
- The developer performed the required reliability testing for this maintenance measure, namely, they conducted accountable entity-level (“measure score”) reliability testing at the level(s) for which the measure is specified. Data sources used for reliability analysis are adequately described and include electronic health record (EHR) data sourced from the US Oncology Network (USON)/McKesson databases consisting of a national representation of 9,023 patients across 147 clinicians and 10 practices during the period of 2023 and 2024.
- The developer conducted signal-to-noise reliability testing at the accountable entity-level, both for clinicians and practices. More than 70% of accountable entities meet the expected threshold of 0.6 and 100% of entities meet the expected threshold of 0.4 for signal-to-noise testing at both the clinician and practice levels.
Limitations:
- Data used for reliability testing were sourced from a two-year period of performance. If this measure is intended to be calculated over shorter periods of performance, the accountable-entity level reliability will be lower. Even for a one-year period of performance, at least 70% of the entities are still likely to have a reliability greater than 0.6. However, it is possible that some of the entities could have a reliability below 0.4.
Rationale:
- This maintenance measure is rated as ‘Met’ for reliability because the developer performed the required reliability testing for this measure and results demonstrate sufficient reliability at all specified accountable entity levels.
Strengths:
- The developer performed the required validity testing for this maintenance measure, namely, they conducted accountable entity-level (“measure score”) validity testing at the levels for which the measure is specified (physician and practice). Data sources used for validity analysis were adequately described and include EHR data from January 2023 through December 2024 for 158 physicians and 10 practices affiliated with USON.
- The developer conducted empirical validity testing at both accountable entity-levels using Pearson correlation to compare the measure score with the percentage of patients who died with cancer receiving systematic cancer-directed therapy in the last 14 or 30 days of life (CBE ID 0210). The developer hypothesized negative relationships between the hospice measure and both strata of the therapy measure (14 days and 30 days), reasoning that these measures reflect opposing clinical priorities near end of life. Pearson correlation coefficients confirmed the expected direction and significance of associations with the hospice measure with the therapy measure at both the physician level (therapy at 14 days: r = -0.2478, p = 0.0017; therapy at 30 days: r = -0.1950, p = 0.0141; n=158) and practice level (therapy at 14 days: r = -0.6446, p = 0.0442; therapy at 30 days: -0.8045, p = 0.0050; n=10). While the developer did not state this, it may be reasonable to expect the stronger negative relationship between the hospice measure and therapy in the last 14 days of life vs. therapy in the last 30 days of life, as was observed at the physician level, due to the tighter time frame within which to potentially make a shift in clinical direction from aggressive treatment to hospice.
- A well-grounded, thorough logic model and acceptable reliability support an inference of validity for the measure.
Limitations:
- Given the small sample of facilities and providers, there may be gaps in the overall representativeness of accountable entities. As noted by the developer, the small sample size of the practice level correlation analysis may result in less precise estimates than at the physician level.
- While the direction of the relationship between the hospice measure and both therapy measures aligns with their hypothesis at both levels of analysis, the developer could provide additional interpretation for the stronger relationships at the practice level compared with the physician level. Another limitation of the testing presented is that the developer did not report testing relationships of the hospice measure with one or more independent measures, which could help establish discriminant validity or provide more robust evidence of a shared quality mechanism.
The developer did not conduct risk adjustment or stratification, but provided the rationale that quality palliative care is a universal standard that should not vary based on patient complexity and that adjustment could normalize departures from palliative care best practices. The developer did not provide supporting literature, a conceptual model, or empirical analysis demonstrating that differences in patient characteristics do not affect measure results or inhibit fair comparisons.
Rationale:
- This maintenance measure is rated as ‘Not Met, But Addressable’ for validity; measure score testing results partially support an inference of validity, suggesting that the measure somewhat accurately reflects performance on quality and can distinguish good from poor performance to a limited extent.
- The developer did not conduct risk adjustment or stratification and provided a rationale for the decision, but did not support the rationale with supporting literature or empirical analysis.
Use and Usability
Strengths:
- The measure is not currently in use, but the developer described a plan for use in the MIPS reporting program beginning performance year (PY) 2027. A version of the measure without the recent material changes is currently in use in the MIPS reporting program.
- Attributes of a suitable program for this measure are described, and these include target population, accountable entities, and care settings.
- The developer provided a summary of how accountable entities can use the measure results to improve performance. Specifically, in providing timely referral to hospice care, referral to specialized, interdisciplinary palliative care, and clear goals of care.
- Stakeholders have provided feedback about the measure through public comments which were considered alongside a technical expert panel (TEP) for updating the measure. The developer noted that feedback from the public comment period suggested increasing the number of days to 2 weeks or 30 days; however, the TEP determined it would be best to minimize changes to the measure at this point.
Limitations:
- The developer did not provide performance data showing improvement in measure scores over time as they do not have data on performance trends from MIPS reporting entities at this time.
Rationale:
- This maintenance measure is rated ‘Not Met, But Addressable’ for use and usability, because while there is a plan for use in at least one accountability application, the developer did not present evidence of improvement in the measure score as required for maintenance endorsement.
Committee Independent Review
Although this is an…
Importance
Closing Care Gaps
Feasibility Assessment
Scientific Acceptability
Summary
Although this is an important conversation for providers to have patients and families. Three days gives a person very little time to prepare and accomplish little in their remaining days.
0216 Review
Importance
I agree with the staff assessment
Closing Care Gaps
I agree with the staff assessment
Feasibility Assessment
The staff assessment brought up some good questions: 1) Cost for use by clinicians and group practices that are NOT non-profits and if this is manageable for rural and safety net systems; and 2) Question regarding the electronic implementation by entities not reporting to the McKesson registry.
Scientific Acceptability
I am not a subject matter expert in this area and will rely on the staff assessment
I am not a subject matter expert in this area and will rely on the staff assessment
Use and Usability
I agree with the staff assessment: the developer did not present evidence of improvement in the measure score as required for maintenance endorsement.
Summary
As a patient partner, I was hoping the developer provided additional data on why a patient did not go onto Hospice earlier. Could it be the age of the patient (younger versus older), geographic location, beliefs, religion, family/caregiver having to administer the meds, maybe they consider it euthanasia (not enough education)? Should these decisions be excluded from the measure?
(No subject)
Importance
While it is valuable to capture hospice enrollment >3 days, it would also be valuable to capture hospice enrollment >7 days or >14 days.
Closing Care Gaps
Hospice is utilized very late in the clinical course for many patients with advanced disease. This would increase the attention of wanting patients to have at least a minimal exposure to hospice care. Ultimately, much of the benefit clinically comes after weeks to months of hospice utilization.
Public Comments
Comment on End-of-Life and Hospice Cancer Care Measures
Dear Partnership for Quality Measurement:
On behalf of the more than 5,000 members of the American Academy of Hospice and Palliative Medicine (AAHPM), we appreciate the opportunity to submit comments in response to the Partnership for Quality Measurement (PQM) Spring 2026 Endorsement and Maintenance (E&M) cycle. AAHPM is the professional organization for physicians specializing in Hospice and Palliative Medicine (HPM). Our membership also includes nurses, social workers, spiritual care providers, pharmacists, and other health professionals deeply committed to improving quality of life for the expanding population of patients facing serious illness as well as their families and caregivers. Together, we strive to advance the field and ensure that patients across all communities and geographies have access to high-quality palliative and hospice care.
We appreciate PQM’s review of several measures focused on hospice and end-of-life care for patients with cancer. These measures address a meaningful gap in quality measurement and support patient-centered care at the end of life. We offer the following comments on the individual measures.
Percentage of Patients who Died with Cancer Enrolled in Hospice For At Least 3 Days Immediately Before Death measure (Registry version (CBE ID 0216) / Claims version (CBE ID 5595))
AAHPM supports the measure’s intent to incentivize earlier referral to and initiation of hospice care for patients at end of life. However, we urge the PQM and measure steward to consider extending the time period that this measure captures. A 3-day window captures only the most extreme cases of late referral and sets a low bar for "timely" hospice enrollment. There is strong and consistent evidence that longer hospice stays are associated with better outcomes, including improved symptom control, higher patient and family satisfaction, fewer in-hospital deaths, and lower end-of-life expenditures., Shorter stays are repeatedly identified as a marker of poorer-quality care. Extending the window for this measure beyond three days would more accurately distinguish timely, high-value hospice enrollment, as opposed to enrollment that occurs too late to deliver its intended benefit. AAHPM would welcome the opportunity to work with the PQM and the measure steward to define a more appropriate length of time.
Conclusion
AAHPM appreciates the opportunity to provide comment on these measures and supports adoption of measures that continue to support high-value, patient-centered end-of-life care. Please direct questions or requests for additional information to Katherine Ast, AAHPM Director of Quality and Research, at [email protected].
^
Kumar P, Wright AA, Hatfield LA, Temel JS, Keating NL. Family Perspectives on Hospice Care Experiences of Patients with Cancer. J Clin Oncol. 2017 Feb;35(4):432-439. doi: 10.1200/JCO.2016.68.9257. Epub 2016 Dec 19.https://pmc.ncbi.nlm.nih.gov/articles/PMC5455697/
^
Adams CE, Bader J, Horn KV. Timing of Hospice Referral: Assessing Satisfaction While the Patient Receives Hospice Services. Home Health Care Manag Pract. 2009 Feb 1;21(2):109-116. doi: 10.1177/1084822308323440. https://pmc.ncbi.nlm.nih.gov/articles/PMC2802336/
^
Sedhom R, Gupta A, Smith TJ. Short Hospice Length of Service in a Comprehensive Cancer Center. J Palliat Med. 2021 Feb;24(2):257-260. doi: 10.1089/jpm.2019.0634. Epub 2020 Apr 17.https://pmc.ncbi.nlm.nih.gov/articles/PMC5695752/