Abstract
BackgroundA critical barrier to improving the quality of end-of-life (EOL) cancer care is our lack of understanding of the mechanisms underlying variation in EOL treatment intensity. This study aims to fill this gap by identifying 1) organizational and provider practice norms at major US cancer centers, and 2) how these norms influence provider decision making heuristics and patient expectations for EOL care, particularly for minority patients with advanced cancer.MethodsThis is a multi-center, qualitative case study at six National Comprehensive Cancer Network (NCCN) and National Cancer Institute (NCI) Comprehensive Cancer Centers. We will theoretically sample centers based upon National Quality Forum (NQF) endorsed EOL quality metrics and demographics to ensure heterogeneity in EOL intensity and region. A multidisciplinary team of clinician and non-clinician researchers will conduct direct observations, semi-structured interviews, and artifact collection. Participants will include: 1) cancer center and clinical service line administrators; 2) providers from medical, surgical, and radiation oncology; palliative or supportive care; intensive care; hospital medicine; and emergency medicine who see patients with cancer and have high clinical practice volume or high local influence (provider interviews and observations); and 3) adult patients with metastatic solid tumors and whom the provider would not be surprised if they died in the next 12 months and their caregivers (patient and caregiver interviews). Leadership interviews will probe about EOL institutional norms and organization. We will observe inpatient and outpatient care for two weeks. Provider interviews will use vignettes to probe explicit and implicit motivations for treatment choices. Semi-structured interviews with patients near EOL, or their family members and caregivers will explore past, current, and future decisions related to their cancer care. We will import transcribed field notes and interviews into Dedoose software for qualitative data management and analysis, and we will develop and apply a deductive and inductive codebook to the data.DiscussionThis study aims to improve our understanding of organizational and provider practice norms pertinent to EOL care in U.S. cancer centers. This research will ultimately be used to inform a provider-oriented intervention to improve EOL care for racial and ethnic minority patients with advanced cancer.Trial registrationClinicaltrials.gov; NCT03780816; December 19, 2018.
Highlights
A critical barrier to improving the quality of end-of-life (EOL) cancer care is our lack of understanding of the mechanisms underlying variation in EOL treatment intensity
Since centers serving a higher proportion of minority patients have systematically higher EOL intensity than centers serving a higher proportion of white patients, [11] these variations in practice patterns may contribute to racial disparities in burdensome treatment near death
We will employ qualitative case study research methods in this study, including inpatient observation procedures and provider, patient, and leadership semistructured interviews, that have been previously developed and piloted [23, 24, 37,38,39]. We will augment these methods with outpatient and tumor board observation procedures, which we developed and tested at a nonstudy National Cancer Institute (NCI)-designated cancer center serving a white, rural population
Summary
A critical barrier to improving the quality of end-of-life (EOL) cancer care is our lack of understanding of the mechanisms underlying variation in EOL treatment intensity. The American Society of Clinical Oncology and National Quality Forum (NQF) define aggressive, burdensome, and expensive EOL treatment in cancer as the receipt of chemotherapy in the last 14 days of life (NQF #0210), intensive care unit (ICU) admission in the last 30 days of life (NQF #0213), and non (NQF #0215) or late (NQF #0216) hospice referral [2]. Such treatment adversely affects patient quality of life, quality of dying, and caregiver bereavement outcomes [3,4,5,6]. Despite efforts to attribute such variation to differences in patient preferences rather than racial disparities, [19] region-level analyses suggest that the impact of these preferences on variation are likely very small [10, 20]
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