11587 Background: The Commission on Cancer (CoC) Standard 3.2 requires distress screening and indicated action for cancer patients. NCCN and ASCO supportive care and age-related guidelines include patient reported concerns beyond distress. This study compares PHQ4 scores to other patient reported concerns. Methods: The Coleman Supportive Oncology Collaborative aggregated “best of” screening tools to assess patient reported needs and concerns aligned with CoC, NCCN and ASCO guidance. This supportive care screening tool was implemented at 8 sites from July 2015 thru July 2018. Analysis used chi squared test. Results: Most patients, 86% (10,635/12,295), reported one plus concerns and/or above threshold scores on PHQ4, PROMIS Pain, Fatigue or Physical Function. A chi squared comparison of patients with at least mild distress on PHQ4 to patients with no distress resulted in p values < .0001 for every screening category. Conclusions: Patients with a PHQ4 distress score of mild, moderate or severe also reported statistically significant levels of practical, family, physical, nutrition and treatment concerns. These patients also scored threshold levels for PROMIS Pain, Fatigue, and Physical Function. Screening only for distress without screening for other patient concerns may direct patients to services that do not address or focus on the underlying cause of the distress. [Table: see text]
47 Background: The IOM 2013 Report recommends that supportive oncology care start at cancer diagnosis; the Commission on Cancer (CoC) Standard 3.2 requires distress screening and indicated action. Screening tools are not standardized across institutions and often address only a portion of patients’ supportive oncology needs. Methods: A collaborative of 100+ clinicians, funded by The Coleman Foundation, developed a patient-centric consolidated screening tool based on validated instruments (NCCN Distress, PHQ-4, PROMIS) and IOM and CoC. The screening tool was piloted at 6 practice-improvement cancer centers in the Chicago area (3 academic, 2 safety-net, 1 public). Patients, providers assessing patients’ screening results (assessors), and providers receiving referrals (providers) were surveyed after use of the screening tool. Descriptive statistics were used to assess effectiveness of the tool. Results: Responders included 175 patients, 81 assessors, and 26 referral providers (social workers, chaplains, subspecialists). The majority of patients (160/175, 91%) completed the screening in <10 minutes, across all patients the screening tool averaged 4 ½ minutes. Most assessors (59/77, 76%) spent <5 minutes reviewing screening results. Most patients, assessors, and providers reported the screening tool asked the “right questions”. Assessors reporting partial relevance of some screening questions for 34% (26/77) of patients, uncovered ≥ 1 relevant needs for 96% (25/26) of those patients (p = 0.002). Conclusions: Use of a consolidated supportive oncology screening tool across multiple institutions is feasible, identified unmet patient needs, and was beneficial for assessors and providers. As the tool is adopted by collaborating institutions, variability in supportive oncology screening practices may decline, thus improving patient care. The tool has implications for quality improvements and national dissemination. [Table: see text]
61 Background: The Institute of Medicine (IOM) 2013 Report recommends that supportive oncology care start at cancer diagnosis; the Commission on Cancer (CoC) Standard 3.2 requires distress screening and indicated action. Screening tools are not standardized and often address only a portion of patients’ supportive oncology needs. Methods: A collaborative of 100+ clinicians, funded by The Coleman Foundation, developed a patient-centric screening tool adapted from NCCN Distress Problem List, IOM report and CoC standards, with validated sub-tools: PHQ-4 for anxiety and depression and PROMIS short forms for pain, fatigue and physical function. Novel treatment/care and other concerns were included. The screening tool was implemented at 4 cancer centers (2 academic, 1 public & 1 safety-net). End points included correlation of PHQ-4 score with other supportive oncology needs. Descriptive statistics, Fisher’s exact test were used. Results: 2805 patients were screened. Average scores were: PHQ4 – Anxiety and Depression 1.8 (mild > 3), Pain 4.5 (mild > 4), Fatigue 8.8 (mild > 6), Physical Function 20.2 (mild < 20), see table for additional items. Higher scores on the PHQ-4 were significantly associated with each of the following: greater pain, fatigue, , nutritional and specific treatment/care concerns, and lower physical function (p<.0001). (See Table). Conclusions: Patients with higher anxiety and depression also have many other supportive oncology concerns. Our results support the use of a comprehensive tool capturing a spectrum of each patient’s unique concerns. This may enable earlier interventions and personalized delivery of supportive care. [Table: see text]
Background: Through its various provisions, the Patient Protection and Affordable Care Act (ACA) has the potential to increase access to cancer care, particularly among the most vulnerable, and reduce disparities in cancer care and outcomes. The ACA might ameliorate disparities in cancer stage by improving access to health care coverage and preventative care, such as screening. The purpose of the present analysis is to examine the change in the percent uninsured and early-stage diagnosis among nonelderly breast cancer patients who receive care in an urban safety-net institution. Methods: We conducted a retrospective, observational study using medical record and cancer registry data from an urban minority-serving hospital. Patients were identified through the cancer registry and included if they were non-Latina (nL) black, or Latina; diagnosed or treated with stage I-IV breast cancer between 2008-2016; and aged 18-64 years at diagnosis. The pre- and post-ACA periods of the expanded health care coverage provision were identified as 2008-2013 and 2014-2016, respectively. Descriptive statistics were calculated to compare patient demographic, insurance, health care use, and tumor characteristics between the pre- and post-ACA periods, overall and across racial/ethnic groups. Logistic regression models, with model-based standardization (predictive margins), were used to estimate proportion differences (PDs) with bias-corrected bootstrapped 95% confidence intervals. Results: A total of 174 nL black and 160 Latina patients were identified. Between pre- and post-ACA, the overall proportion of uninsured at the time of diagnosis decreased from 36.6% to 20.9% (p=0.00). The decrease in the uninsured population was statistically significant only for Latina women (p=0.00). There was a small shift in early-stage diagnoses. Post-ACA, the overall proportion of Stage I cancers increased from 26.8% to 31.8% (PD=5.0; p=0.33). However, this shift occurred among nL black women (PD=9.6%, p=0.18) but not among Latina women (PD=0.0, p=0.91). This pattern remained even after adjusting for age, insurance status, and history of outpatient preventative care use. Of note, compared with women diagnosed pre-ACA, those diagnosed post-ACA were less likely to have had a preventative care visit during the 24 months prior to diagnosis (26% versus 51%, p=0.00). Conclusion: Early results suggest that the ACA has increased access to insurance for underserved nL-black and Latina breast cancer patients. However, its impact on preventative care utilization and early cancer diagnosis is unclear. Post-ACA patients might be newly entering the health care system, due to having obtained insurance, and so may need assistance navigating to obtain preventative care, such as mammograms. Next steps include examining changes in screen-detected versus symptom-detected cancer, time to treatment, and conducting semistructured interviews to examine women's experiences with breast cancer care pre- and post-ACA. Citation Format: Abigail Silva, Arielle Guzman, Charlotte Picard, Yamile Molina, Alexandrina Balanean, Paramjeet Khosla. Did the Affordable Care Act improve insurance coverage and stage at diagnosis among nonelderly underserved breast cancer patients? [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr B076.
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