The impact of outpatient supportive oncology on cancer care cost and utilization.

BACKGROUND: Supportive oncology (SO) care reduces symptom severity, admissions, and costs in patients with advanced cancer. This study examines the impact of SO care on utilization and costs. METHODS: Retrospective analysis of utilization and costs comparing patients enrolled in SO versus three comparison cohorts who did not receive SO. Using claims, the authors estimated differences in health care utilization and cost between the treatment group and comparison cohorts. The treatment group consisting of patients treated for cancer at an National Cancer Institute-designated cancer center who received SO between January 2018 and December 2019 were compared to an asynchronous cohort that received cancer care before January 2018 (n = 60), a contemporaneous cohort with palliative care receiving SO care from other providers in the Southeastern Pennsylvania region during the program period (n = 86), and a contemporaneous cohort without palliative care consisting of patients at other cancer centers who were eligible for but did not receive SO care (n = 393). RESULTS: At 30, 60, and 90 days post-enrollment into SO, the treatment group had between 27% and 70% fewer inpatient admissions and between 16% and 54% fewer emergency department visits (p < .05) compared to non-SO cohorts. At 90 days following enrollment in SO care, total medical costs were between 4.4% and 24.5% lower for the treatment group across all comparisons (p < .05). CONCLUSIONS: SO is associated with reduced admissions, emergency department visits, and total costs in advanced cancer patients. Developing innovative reimbursement models could be a cost-effective approach to improve care of patients with advanced cancer.

A descriptive study of the connections between social risk and healthcare utilization with supportive oncology care.

OBJECTIVE: This study utilized social risk data in the electronic heath record collected as part of routine clinical practice and examined relationships with supportive oncology care contacts and healthcare utilization. METHODS: A total of 2,807 cancer patients were screened for four social determinants of health (SDOH) domains (financial resource strain, housing instability, food insecurity, and transportation need) and categorized to low or high risk SDOH groups. The number of patient contacts with supportive oncology was compared amongst the groups. The data were analyzed for demographic and outcome differences including emergency department visits, inpatient admissions, and appointment adherence. RESULTS: Heightened social risk was associated with more total contacts with supportive oncology care. Patients with high SDOH risk had more contacts across all outcomes examined including emergency department visits (M = 13), inpatient admissions (M = 14), and missed appointments (M = 11). CONCLUSIONS: Patients with both greater social risks and acute care utilization are associated with more psychosocial interventions in supportive oncology follow-up. These findings highlight the need for comprehensive action to respond to social risk factors identified in SDOH screening.

Increasing equitable access to telehealth oncology care in the COVID-19 National Emergency: Creation of a telehealth task force.

INTRODUCTION: Telehealth (TH) utilization in cancer care prior to COVID-19 was variable. Research highlights disparities in access determined by socioeconomic factors including education, income, race, and age. In response to COVID-19 and these disparities, we assessed the impact of a personalized digital support structure, the Telehealth Task Force (TTF), to reduce disparities in TH. METHODS: We performed a retrospective review of cohorts between January 1, 2020 and August 30, 2020: Pre (TH use with basic telephone support), Intervention (TH access with TTF), and Post (TH access after TTF initiation and educational material dissemination). Data collected included successful TH access, health literacy (HL), and Area Deprivation Index, a ranking of neighborhoods by socioeconomic disadvantage (ADI). The data were analyzed in univariate ordinary least squares model and adjacent categories ratio model using statistical software R to understand the relationship between TTF, HL, ADI, and TH access. RESULTS: We included 555 patients from January 1, 2020 to August 30, 2020 (90 preintervention, 194 intervention, and 271 postintervention), excluding patients without ADI/HL. TTF support successfully engaged older, racially, and socioeconomically diverse patients in TH; ADI is significantly higher in the postintervention group vs. preintervention (mean difference = 7.66, 95% CI 1.00-4.32, p = 0.024) and more patients had low HL during intervention compared with preintervention (adjacent categories ratio = 0.62, 95% CI 0.41-0.93, p = 0.021). DISCUSSION: COVID-19 created an immediate need for TH. Implementation of the TTF helped close the digital divide, increasing TH access for vulnerable patients. Attention to digital readiness can mitigate disparities in access to care. Future research should explore the implementation of widespread routine digital support initiatives.

COVID-19 Pandemic Influence on Medical Oncology Provider Perceptions of Telehealth Video Visits.

PURPOSE: The COVID-19 pandemic necessitated a rapid expansion of telehealth use in oncology, a specialty in which prior utilization was low in part because of barriers perceived by providers. Understanding the changing perceptions of medical oncology providers during the pandemic is critical for continued expansion and improvement of telehealth in cancer care. This study was designed to identify medical oncology providers' perceptions of telehealth video visits as influenced by the COVID-19 pandemic. METHODS: We conducted semi-structured interviews with medical oncology providers from November 20, 2020, to January 27, 2021, at the Sidney Kimmel Cancer Center at Thomas Jefferson University, a National Cancer Institute-designated cancer center in an urban, academic health system in Philadelphia, PA. We assessed provider perceptions of the impact of the COVID-19 pandemic on (1) provider-level comfort and willingness for telehealth, (2) provider-perceived patient comfort and willingness to engage in telehealth, and (3) continued barriers to successful telehealth use. RESULTS: Volunteer and convenience sampling resulted in the participation of 25 medical oncology providers, including 18 physicians and seven advanced practice providers, in semi-structured interviews. Of the 25 participants, 13 (52%) were female and 19 (76%) were White, with an average age of 48.5 years (standard deviation = 12.6). Respondents largely stated an increased comfort level and willingness for use of video visits. In addition, respondents perceived a positive change in patient comfort and willingness, mostly driven by convenience, accessibility, and reduced risk of COVID-19 exposure. However, several reported technologic issues and limited physical examination capability as remaining barriers to telehealth adoption. CONCLUSION: The rapid adoption of telehealth necessitated by the COVID-19 pandemic has increased provider-level and provider-perceived patient comfort and willingness to engage in video visits for cancer care. As both providers and patients increasingly accept telehealth across many use cases, future work should focus on further addressing technology and physical examination barriers and ensuring continued reimbursement for telehealth as a routine part of covered care.

Engaging Patients with Late-Stage Non-Small Cell Lung Cancer in Shared Decision Making about Treatment.

Few treatment decision support interventions (DSIs) are available to engage patients diagnosed with late-stage non-small cell lung cancer (NSCLC) in treatment shared decision making (SDM). We designed a novel DSI that includes care plan cards and a companion patient preference clarification tool to assist in shared decision making. The cards answer common patient questions about treatment options (chemotherapy, chemotherapy plus immunotherapy, targeted therapy, immunotherapy, clinical trial participation, and supportive care). The form elicits patient treatment preference. We then conducted interviews with clinicians and patients to obtain feedback on the DSI. We also trained oncology nurse educators to implement the prototype. Finally, we pilot tested the DSI among five patients with NSCLC at the beginning of an office visit scheduled to discuss treatment with an oncologist. Analyses of pilot study baseline and exit survey data showed that DSI use was associated with increased patient awareness of the alternatives' treatment options and benefits/risks. In contrast, patient concern about treatment costs and uncertainty in treatment decision making decreased. All patients expressed a treatment preference. Future randomized controlled trials are needed to assess DSI implementation feasibility and efficacy in clinical care.

Digital Literacy at an Urban Cancer Center: Implications for Technology Use and Vulnerable Patients.

PURPOSE: eHealth literacy, or the ability to seek, find, understand, and appraise health information from electronic sources, has become increasingly relevant in the era of COVID-19, when so many aspects of patient care became dependent on technology. We aimed to understand eHealth literacy among a diverse sample of patients with cancer and discuss ways for health systems and cancer centers to ensure that all patients have access to high-quality care. METHODS: A cross-sectional survey of patients with cancer and caregivers was conducted at an NCI-designated cancer center to assess access to the Internet, smartphone ownership, use of mobile apps, willingness to engage remotely with the health care team, and use of the patient portal. Descriptive statistics and bivariate analyses were used to assess frequencies and significant differences between variables. RESULTS: Of 363 participants, 55% (n = 201) were female, 71% (n = 241) identified as non-Hispanic White, and 29% (n = 85) reported that their highest level of education was a high school diploma. Most (90%, n = 323) reported having access to the Internet and most (82%, n = 283) reported owning a smartphone. Younger patients or those with a college degree were significantly more likely to own a smartphone, access health information online, know how to download an app on their own, have an interest in communicating with their health care team remotely, or have an account on the electronic patient portal. CONCLUSION: As cancer centers increasingly engage patients through electronic and mobile applications, patients with low or limited digital literacy may be excluded, exacerbating current cancer health disparities. Patient-, provider- and system-level technology barriers must be understood and mitigated.

Validity of the screener and opioid assessment for patients with pain-revised (SOAPP-R) in patients with cancer.

OBJECTIVE: To determine the utility of the screener and opioid assessment for patients with pain-revised (SOAPP-R) for patients with cancer-related pain. DESIGN: The authors performed a retrospective analysis of cancer patients screened with the SOAPP-R. Opiate abuse was determined using a combination of urine drug screens and analysis of patients' electronic medical records. SETTING/PATIENTS: Patients who were seen at a palliative care clinic presenting with pain or needing an opioid prescription at an academic medical center with any type of cancer were screened using the SOAPP-R (N = 69). OUTCOME MEASURES: Aberrant opioid-related behavior was determined using a combination of provider notes and urine drug screens. RESULTS: A positive SOAPP-R score (⩾18) was observed in 27 participants (39.1 percent). The sensitivity and specificity of the SOAPP-R in the study population was 0.75 and 0.80, respectively. CONCLUSIONS: The SOAPP-R, in its current form, may have value in screening patients with cancer for substance abuse. Incorporation of the screening tool in palliative and oncology settings may help reduce opioid abuse in cancer patients.