11011Background: Managing cancer care can be highly demanding, consuming time and energy. Measuring this time has been limited to date. We sought to comprehensively measure the time spent on cancer...

11084Background: Natural disasters are increasingly common in the U.S., causing significant localized disruptions to cancer care. The American Society of Clinical Oncology (ASCO) examines the suppl...

11011Background: Managing cancer care can be highly demanding, consuming time and energy. Measuring this time has been limited to date. We sought to comprehensively measure the time spent on cancer...

Over 8 million patients experiencing cancer face health-related social needs (HRSN) challenges, such as food, housing, and financial insecurity, that directly impact their health outcomes. While patients may participate in the screening of unmet social needs with their healthcare provider, it is not well understood if patients will self-screen and act on referrals to community services. Therefore, we conducted a mixed-methods study in which we pilot-tested a patient-centered oncology-focused digital social care referral platform, ConnectedNest. We recruited 13 cancer-focused community-based organizations (CBOs) and 41 individuals (e.g., patients, survivors, and caregivers) affected by cancer to participate in the study. Individuals used the application on their phones for 3 months. They completed a social needs assessment and were provided with a personalized list of local CBO programs that could address these unmet needs. Quantitative analyses described participant HRSN and connections to referred programs. User experience surveys were collected over 30 and 60 days to understand their experience. Individuals were also invited to participate in an a semi-structured interview to understand barriers and facilitators for social care referrals. Participants reported needs across 14 categories, with an average of 4.5 HRSN per participants. The top 3 reported needs were physical activity, financial strain, and mental health. Using our social care referral platform, approximately 39% of participants were able to connect with local CBOs. Three topic areas emerged from the participant interviews, highlighting that personal motivation, the participant's role, and the interest in services affected the participant's use of the technology. This study demonstrates the potential for digital social care referral platforms to bridge individuals affected by cancer with vital CBO resources to address HRSNs.

Over 8 million patients experiencing cancer face health-related social needs (HRSN) challenges, such as food, housing, and financial insecurity, that directly impact their health outcomes. While patients may participate in the screening of unmet social needs with their healthcare provider, it is not well understood if patients will self-screen and act on referrals to community services. Therefore, we conducted a mixed-methods study in which we pilot-tested a patient-centered oncology-focused digital social care referral platform, ConnectedNest. We recruited 13 cancer-focused community-based organizations (CBOs) and 41 individuals (e.g., patients, survivors, and caregivers) affected by cancer to participate in the study. Individuals used the application on their phones for 3 months. They completed a social needs assessment and were provided with a personalized list of local CBO programs that could address these unmet needs. Quantitative analyses described participant HRSN and connections to referred programs. User experience surveys were collected over 30 and 60 days to understand their experience. Individuals were also invited to participate in an a semi-structured interview to understand barriers and facilitators for social care referrals. Participants reported needs across 14 categories, with an average of 4.5 HRSN per participants. The top 3 reported needs were physical activity, financial strain, and mental health. Using our social care referral platform, approximately 39% of participants were able to connect with local CBOs. Three topic areas emerged from the participant interviews, highlighting that personal motivation, the participant's role, and the interest in services affected the participant's use of the technology. This study demonstrates the potential for digital social care referral platforms to bridge individuals affected by cancer with vital CBO resources to address HRSNs.

We assessed the effect of the time requirements of cancer care on other life activities and time burden reduction priorities among breast and gynecologic cancer survivors. A total of 224 participants with gynecologic or breast cancer from two cohort studies completed a cross-sectional survey regarding logistic and time burdens of cancer care. We compared agreement with the importance of minimizing travel time, wait time, and trips to the cancer center as well as whether cancer care visits interfered with other activities (dependent care, chores, leisure activities) by employment, education, cancer type, cancer treatment status, dependent status, rural-urban residence, and income. About half (108/217, 49.8%) of participants agreed minimizing time burdens was important. Some agreed that cancer care visits interfered with leisure time (31/215, 14.4%) or impacted their ability to care for dependents (17/215, 7.9% [15.9% among those with dependents, 7/44]). Retired participants, compared to working participants, less often agreed with the importance of minimizing travel time (36.5% [31/85] versus 58.0% [58/100]), trips to the cancer center (34.5% [30/87] versus 58.0% [58/100]), and wait time (35.8% [29/81] versus 56.0% [56/100]). Participants with incomes <$50,000 and those receiving maintenance treatment most often agreed that minimizing wait time was important. Those not working (and not retired or on disability) and those receiving active treatment most often agreed that care interfered with leisure activities. Minimizing the time needed for cancer care-related tasks matters to patients, especially to those with lower incomes, receiving treatment, and working. In-depth research among demographically diverse populations is needed to evaluate specific time use patterns within cancer care and their association with objective and subjective burden.

<p>Cannabis use among individuals with cancer is best understood using survey self-report. As cannabis remains federally illegal, surveys could be subject to nonresponse and measurement issues impacting data quality. We surveyed individuals using medical cannabis for a cancer-related condition in the Minnesota Medical Cannabis Program (MCP). Although survey responders are older, there are no differences by race and ethnicity, gender, or receipt of reduced cannabis registry enrollment fee. Responders made a more recent purchase and more recently completed an independent symptom assessment for the registry than nonresponders, suggesting some opportunity for nonresponse error. Among responders, self-report and MCP administrative data with respect to age, race, gender, registry certification, and cannabis purchase history were similar. Responders were less likely to report receipt of Medicaid than would be expected based on registry low-income enrollment eligibility. Although attention should be paid to potential for nonresponse error, surveys are a reliable tool to ascertain cannabis behavior patterns in this population.</p>

<h3>Importance</h3><p>Medicare Advantage (MA) plans receive capitated per enrollee payments that create financial incentives to provide care more efficiently than traditional Medicare (TM); however, incentives could be associated with MA plans reducing use of beneficial services. Postacute care can improve functional status, but it is costly, and thus may be provided differently to Medicare beneficiaries by MA plans compared with TM.</p><h3>Objective</h3><p>To estimate the association of MA compared with TM enrollment with postacute care use and postdischarge outcomes.</p><h3>Design, Setting, and Participants</h3><p>This was a cohort study using Medicare data on 4613 hospitalizations among retired Ohio state employees and 2 comparison groups in 2015 and 2016. The study investigated the association of a policy change with use of postacute care and outcomes. The policy changed state retiree health benefits in Ohio from a mandatory MA plan to subsidies for either supplemental TM coverage or an MA plan. After policy implementation, approximately 75% of retired Ohio state employees switched to TM. Hospitalizations for 3 high-volume conditions that usually require postacute rehabilitation were assessed. Data from the Medicare Provider Analysis and Review files were used to identify all hospitalizations in short-term acute care hospitals. Difference-in-difference regressions were used to estimate changes for retired Ohio state employees compared with other 2015 MA enrollees in Ohio and with Kentucky public retirees who were continuously offered a mandatory MA plan. Data analyses were performed from September 1, 2019, to November 30, 2023.</p><h3>Exposures</h3><p>Enrollment in Ohio state retiree health benefits in 2015, after which most members shifted to TM.</p><h3>Main Outcomes and Measures</h3><p>Received care in an inpatient rehabilitation facility, skilled nursing facility, or home health, or any postacute care; the occurrence of any hospital readmission; the number of days in the community during the 30 days after hospital discharge; and mortality.</p><h3>Results</h3><p>The study sample included 2373 hospitalizations for Ohio public retirees, 1651 hospitalizations for other Humana MA enrollees in Ohio, and 589 hospitalizations for public retirees in Kentucky. After the 2016 policy implementation, the percentage of hospitalizations covered by MA decreased by 70.1 (95% CI, −74.2 to −65.9) percentage points (pp), inpatient rehabilitation facility admissions increased by 9.7 (95% CI, 4.7 to 14.7) pp, use of only home health or skilled nursing facility care fell by 8.6 (95% CI, −14.6 to −2.6) pp, and days in the community fell by 1.6 (95% CI, −2.9 to −0.3) days for Ohio public retirees compared with other Humana MA enrollees in Ohio. There was no change in 30-day mortality or hospital readmissions; similar results were found by comparisons using Kentucky public retirees as a control group.</p><h3>Conclusions and Relevance</h3><p>The findings of this cohort study indicate that after a change in retiree health benefits, most Ohio public retirees shifted from MA to TM and received more intensive postacute care with no significant change in measured short-term postdischarge outcomes. Future work should consider additional measures of postacute functional status over a longer follow-up period.</p>

<p>Introduction: Adolescents and young adults (AYAs), particularly those 19-34, are the most highly uninsured age group in the United States. AYAs lacking any insurance or having public health insurance have been consistently found to have worse survival after a cancer diagnosis than those with private insurance, highlighting the need to better understand survival disparities and improve outcomes in this population. We examined the association of health insurance with stage at diagnosis, cancer treatment, location of cancer care, healthcare utilization, and chronic medical conditions/late effects (e.g., cardiovascular, respiratory, and endocrine diseases) and survival.</p>

11071Background: The cost of cancer care has increased dramatically over the past decades, increasing the financial burden on patients. However, current estimates of...

<p>Patients with stage IV GI cancer spent 1 in 4 days alive with health care contact!</p>

Background: Multimorbidity is associated with premature mortality and excess health care costs. The burden of multimorbidity is highest among patients with cancer, yet trends and determinants of multimorbidity over time are poorly understood. Methods: Via Medicare claims linked to Cancer Prevention Study II data, group-based trajectory modeling was used to compare National Cancer Institute comorbidity index score trends for cancer survivors and older adults without a cancer history. Among cancer survivors, multinomial logistic regression analyses evaluated associations between demographics, health behaviors, and comorbidity trajectories. Results: In 82,754 participants (mean age, 71.6 years [SD, 5.1 years]; 56.9% female), cancer survivors (n = 11,265) were more likely than older adults without a cancer history to experience the riskiest comorbidity trajectories: (1) steady, high comorbidity scores (remain high; odds ratio [OR], 1.36; 95% CI, 1.29–1.45), and (2) high scores that increased over time (start high and increase; OR, 1.51; 95% CI, 1.38–1.65). Cancer survivors who were physically active postdiagnosis were less likely to fall into these two trajectories (OR, 0.73; 95% CI, 0.64–0.84, remain high; OR, 0.42; 95% CI, 0.33–0.53, start high and increase) compared to inactive survivors. Cancer survivors with obesity were more likely to have a trajectory that started high and increased (OR, 2.83; 95% CI, 2.32–3.45 vs. normal weight), although being physically active offset some obesity-related risk. Cancer survivors who smoked postdiagnosis were also six times more likely to have trajectories that started high and increased (OR, 6.86; 95% CI, 4.41–10.66 vs. never smokers). Conclusions: Older cancer survivors are more likely to have multiple comorbidities accumulated at a faster pace than older adults without a history of cancer. Weight management, physical activity, and smoking avoidance postdiagnosis may attenuate that trend.

Background: Multimorbidity is associated with premature mortality and excess health care costs. The burden of multimorbidity is highest among patients with cancer, yet trends and determinants of multimorbidity over time are poorly understood. Methods: Via Medicare claims linked to Cancer Prevention Study II data, group-based trajectory modeling was used to compare National Cancer Institute comorbidity index score trends for cancer survivors and older adults without a cancer history. Among cancer survivors, multinomial logistic regression analyses evaluated associations between demographics, health behaviors, and comorbidity trajectories. Results: In 82,754 participants (mean age, 71.6 years [SD, 5.1 years]; 56.9% female), cancer survivors (n = 11,265) were more likely than older adults without a cancer history to experience the riskiest comorbidity trajectories: (1) steady, high comorbidity scores (remain high; odds ratio [OR], 1.36; 95% CI, 1.29–1.45), and (2) high scores that increased over time (start high and increase; OR, 1.51; 95% CI, 1.38–1.65). Cancer survivors who were physically active postdiagnosis were less likely to fall into these two trajectories (OR, 0.73; 95% CI, 0.64–0.84, remain high; OR, 0.42; 95% CI, 0.33–0.53, start high and increase) compared to inactive survivors. Cancer survivors with obesity were more likely to have a trajectory that started high and increased (OR, 2.83; 95% CI, 2.32–3.45 vs. normal weight), although being physically active offset some obesity-related risk. Cancer survivors who smoked postdiagnosis were also six times more likely to have trajectories that started high and increased (OR, 6.86; 95% CI, 4.41–10.66 vs. never smokers). Conclusions: Older cancer survivors are more likely to have multiple comorbidities accumulated at a faster pace than older adults without a history of cancer. Weight management, physical activity, and smoking avoidance postdiagnosis may attenuate that trend.

<h3>Importance</h3><p>The number of cancer survivors living in the US is projected to be 26.1 million by 2040. Cancer survivors may be at increased risk of bone fractures, but research is limited in several important ways.</p><h3>Objective</h3><p>To investigate the associations of cancer diagnoses, including time since diagnosis and stage at diagnosis, with risks of pelvic, radial, and vertebral fractures (separately and combined) among older cancer survivors and compared with fracture risk among older adults without a history of cancer. Secondarily, to examine differences in risk of fracture stratified by modifiable behaviors, treatment, and cancer type.</p><h3>Design, Setting, and Participants</h3><p>This longitudinal cohort study used data from 92 431 older adults in the US Cancer Prevention Study II Nutrition Cohort linked with 1999 to 2017 Medicare claims. Data were analyzed from July 15, 2021, to May 3, 2022.</p><h3>Exposures</h3><p>Cancer history, time since cancer diagnosis, and stage at cancer diagnosis.</p><h3>Main Outcomes and Measures</h3><p>Hazard ratios (HRs) and 95% CIs for the risk of pelvic, radial, vertebral, and total frailty-related fractures were estimated using multivariate Cox proportional hazards regression. Stratification was used for secondary aims.</p><h3>Results</h3><p>Among 92 431 participants (mean [SD] age, was 69.4 [6.0] years, 51 820 [56%] women, and 90 458 [97.9%] White], 12 943 participants experienced a frailty-related bone fracture. Compared with participants without a history of cancer, cancer survivors who were diagnosed 1 to less than 5 years earlier with advanced stage cancer had higher risk of fracture (HR, 2.12; 95% CI, 1.75-2.58). The higher fracture risk in cancer survivors with recent advanced stage diagnosis (vs no cancer) was driven largely by vertebral (HR, 2.46; 95% CI, 1.93-3.13) and pelvic (HR, 2.46; 95% CI, 1.84-3.29) fracture sites. Compared with cancer survivors who did not receive chemotherapy, survivors who received chemotherapy were more likely to have a fracture; this association was stronger within 5 years of diagnosis (HR, 1.31; 95% CI, 1.09-1.57) than 5 or more years after diagnosis (HR, 1.22; 95% CI, 0.99-1.51). Although the HR for risk of fracture was lower among physically active cancer survivors 5 or more years after diagnosis (HR, 0.76; 95% CI, 0.54-1.07), this result was not statistically significant, whereas current smoking was significantly associated with higher risk of fracture (HR, 2.27; 95% CI, 1.55-3.33).</p><h3>Conclusions and Relevance</h3><p>Findings from this cohort study suggest that older adults with a history of cancer may benefit from clinical guidance on prevention of frailty-related fractures. If study findings are replicated, fracture prevention programs for survivors might include referrals for physical activity with cancer exercise professionals and smoking cessation programs.</p>

Having a mental illness increases risk of mortality for women with breast cancer, partly due to barriers to accessing recommended care (e.g., cancer screening). Early detection is one important factor in breast cancer survival. To further understand this disparity in survival, we examined whether older women with mental illness are more likely to be diagnosed with later-staged breast cancers compared to women without mental illnesses. We used 2005–2015 SEER-Medicare data to identify AJCC stage I–IV breast cancer patients with and without a history of mental illness prior to cancer diagnosis. We used generalized ordinal regression to examine associations between mental illness diagnoses and stage at diagnosis, controlling for age, race/ethnicity, income, comorbidities, primary care use, rurality, and marital status. Among 96,034 women with breast cancer, 1.7% have a serious mental illness (SMI), 19.9% depression or anxiety, and 7.0% other mental illness. Those with SMI have 40% higher odds of being diagnosed with AJCC Stages II, III than Stage I; women with depression/anxiety have 25% lower odds of being diagnosed with Stage IV cancer than Stage I; and women with other mental illnesses have similar odds of being diagnosed in later stages. Women with SMI have higher odds of being diagnosed at later stages, which likely contributes to higher mortality after breast cancer. Surprisingly, women with depression and anxiety have a lower risk of being diagnosed with Stage IV cancer. Earlier breast cancer diagnosis in women with SMI is an important goal for reducing disparities breast cancer survival.

Background: This study aims to quantify the extent and diversity of the cancer care workforce, beyond medical oncologists, to inform future demand because the number of cancer survivors is expected to grow in the United States. Methods: Surveillance, Epidemiology, and End Results-Medicare data were used to evaluate health-care use of cancer survivors diagnosed between 2000 and 2014, enrolled in fee-for-service Medicare Parts A and B, and 65 years or older in 2008-2015. We calculated percentage of cancer survivors who saw each clinician specialty and their average annual number of visits in each phase of care. We projected the national number of individuals receiving care and number of annual visits by clinician specialty and phase of care through 2040. Results: Cancer survivors had higher care use in the first year after diagnosis and last year of life phases. During the initial year after cancer diagnosis, most survivors were seen for cancer-related care by a medical oncologist (59.1%), primary care provider (55.9%), and/or other cancer-treating physicians (42.2%). The percentage of survivors with cancer-related visits to each specialty declined after the first year after diagnosis, plateauing after year 6-7. However, at 10 or more years after diagnosis, approximately 20% of cancer survivors had visits to medical oncologists and an average of 4 visits a year. Conclusions: Cancer survivors had higher care use in the first year after diagnosis and last year of life. High levels of care use across specialties in all phases of care have important implications for models of survivorship care coordination and workforce planning.

Background: Innovative treatments have improved cancer survival but also increased financial hardship for patients. While demographic factors associated with financial hardship among cancer survivors are known in the USA, the role of geography is less clear. Methods: We evaluated prevalence of forgoing care due to cost within 12 months by US Census region (Northeast, North Central/Midwest [NCMW], South, West) by demographic factors (age, sex, race/ethnicity) among 217,981 cancer survivors aged 18 to 82 years from the 2015–2019 Behavioral Risk Factor Surveillance System survey. We summarized region- and group-specific prevalence of forgoing physician visits due to cost and used multilevel logistic regression models to compare regions. Results: The prevalence of forgoing physician visits due to cost was highest in the South (aged < 65 years: 19–38%; aged ≥ 65: 4–21%; adjusted odds ratios [OR], NCMW versus South, OR: 0.63 [0.56–0.71]; Northeast versus South, OR: 0.63 [0.55–0.73]; West versus South, OR: 0.73 [0.64–0.84]). Across the USA, including regions with broad Medicaid expansion, younger, female, and persons of color most often reported cost-related forgoing physician visits. Conclusion: Forgoing physician visits due to cost among cancer survivors is regionally clustered, raising concerns for concentrated poor long-term cancer outcomes. Underlying factors likely include variation in regional population compositions and contextual factors, such as Medicaid expansion and social policies. Disproportionate cost burden among survivors of color in all regions highlight systemic barriers, underscoring the need to improve access to the entire spectrum of care for cancer survivors, and especially for those most vulnerable.