Background. Many cancer survivors struggle to choose a health insurance plan that meets their needs because of high costs, limited health insurance literacy, and lack of decision support. We developed a web-based decision aid, Improving Cancer Patients' Insurance Choices (I Can PIC), and evaluated it in a randomized trial. Materials and Methods. Eligible individuals (18-64 years, diagnosed with cancer for ≤5 years, English-speaking, not Medicaid or Medicare eligible) were randomized to I Can PIC or an attention control health insurance worksheet. Primary outcomes included health insurance knowledge, decisional conflict, and decision self-efficacy after completing I Can PIC or the control. Secondary outcomes included knowledge, decisional conflict, decision self-efficacy, health insurance literacy, financial toxicity, and delayed care at a 3-6-month follow-up. Results. A total of 263 of 335 eligible participants (79%) consented and were randomized; 206 (73%) completed the initial survey (106 in I Can PIC; 100 in the control), and 180 (87%) completed a 3-6 month follow-up. After viewing I Can PIC or the control, health insurance knowledge and a health insurance literacy item assessing confidence understanding health insurance were higher in the I Can PIC group. At follow-up, the I Can PIC group retained higher knowledge than the control; confidence understanding health insurance was not reassessed. There were no significant differences between groups in other outcomes. Results did not change when controlling for health literacy and employment. Both groups reported having limited health insurance options. Conclusion. I Can PIC can improve cancer survivors' health insurance knowledge and confidence using health insurance. System-level interventions are needed to lower financial toxicity and help patients manage care costs. The Oncologist 2020;25:609-619 Implications for Practice: Inadequate health insurance compromises cancer treatment and impacts overall and cancerspecific mortality. Uninsured or underinsured survivors report fewer recommended cancer screenings and may delay or avoid needed follow-up cancer care because of costs. Even those with adequate insurance report difficulty managing care costs. Health insurance decision support and resources to help manage care costs are thus paramount to cancer survivors' health and care management. We developed a web-based decision aid, Improving Cancer Patients' Insurance Choices (I Can PIC), and evaluated it in a randomized trial. I Can PIC provides health insurance information, supports patients through managing care costs, offers a list of financial and emotional support resources, and provides a personalized cost estimate of annual health care expenses across plan types.

This qualitative study explored cancer survivors’ experiences selecting and using health insurance and anticipating out-of-pocket care costs. Thirty individuals participated in semistructured interviews. On average, participants were 54 years ( SD ± 8.85, range 34-80) and diagnosed with cancer about 5 years prior (range 0.5-10 years). About 57% were female, 77% were non-Hispanic White, and 53% had less than a college education. Participants struggled to access information about health insurance and costs. Lack of cost transparency made it difficult to anticipate expenses and increased anxiety. Many participants were surprised that after cancer, care that was once preventive with no out-of-pocket costs became diagnostic with associated fees. They discussed the cognitive burden of managing finances on top of treatment and overseeing communication between doctors and insurance. Interventions are needed to clearly communicate information about insurance coverage and care costs to improve cancer survivors’ confidence in selecting health insurance and anticipating out-of-pocket expenses.

Rural-residing cancer patients often do not participate in clinical trials. Many patients misunderstand cancer clinical trials and their rights as participant. The purpose of this study is to modify a previously developed cancer clinical trials decision aid (DA), incorporating the unique needs of rural populations, and test its impact on knowledge and decision outcomes. The study was conducted in two phases. Phase I recruited 15 rural-residing cancer survivors in a qualitative usability study. Participants navigated the original DA and provided feedback regarding usability and implementation in rural settings. Phase II recruited 31 newly diagnosed rural-residing cancer patients. Patients completed a survey before and after using the revised DA, R-CHOICES. Primary outcomes included decisional conflict, decision self-efficacy, knowledge, communication self-efficacy, and attitudes towards and willingness to consider joining a trial. In phase I, the DA was viewed positively by rural-residing cancer survivors. Participants provided important feedback about factors rural-residing patients consider when thinking about trial participation. In phase II, after using R-CHOICES, participants had higher certainty about their choice (mean post-test = 3.10 vs. pre-test = 2.67; P = 0.025) and higher trial knowledge (mean percentage correct at post-test = 73.58 vs. pre-test = 57.77; P < 0.001). There was no significant change in decision self-efficacy, communication self-efficacy, and attitudes towards or willingness to join trials. The R-CHOICES improved rural-residing patients' knowledge of cancer clinical trials and reduced conflict about making a trial decision. More research is needed on ways to further support decisions about trial participation among this population.

Objective. Numerous electronic tools help consumers select health insurance plans based on their estimated health care utilization. However, the best way to personalize these tools is unknown. The purpose of this study was to compare two common methods of personalizing health insurance plan displays: 1) quantitative healthcare utilization predictions using nationally representative Medical Expenditure Panel Survey (MEPS) data and 2) subjective-health status predictions. We also explored their relations to self-reported health care utilization. Methods. Secondary data analysis was conducted with responses from 327 adults under age 65 considering health insurance enrollment in the Affordable Care Act (ACA) marketplace. Participants were asked to report their subjective health, health conditions, and demographic information. MEPS data were used to estimate predicted annual expenditures based on age, gender, and reported health conditions. Self-reported health care utilization was obtained for 120 participants at a 1-year follow-up. Results. MEPS-based predictions and subjective-health status were related (P < 0.0001). However, MEPS-predicted ranges within subjective-health categories were large. Subjective health was a less reliable predictor of expenses among older adults (age × subjective health, P = 0.04). Neither significantly related to subsequent self-reported health care utilization (P = 0.18, P = 0.92, respectively). Conclusions. Because MEPS data are nationally representative, they may approximate utilization better than subjective health, particularly among older adults. However, approximating health care utilization is difficult, especially among newly insured. Findings have implications for health insurance decision support tools that personalize plan displays based on cost estimates.

BackgroundRecent advances in treatment have given patients with chronic kidney disease (CKD) access to safer and more effective medications to treat comorbid hepatitis C virus (HCV) infection. Given the variety and complexity of treatment options that depend on patients’ clinical characteristics and personal preferences, education and decision support are needed to prepare patients better to discuss treatment options with their clinicians.MethodsDrawing on International Patient Decision Aids Standards guidelines, literature reviews, and guidance from a diverse expert advisory group of nephrologists, hepatologists, and patients, we will develop and test a HCV and CKD decision support tool. Named Project HELP (Helping Empower Liver and kidney Patients), this tool will support patients with HCV and CKD during decisions about whether, when, and how to treat each illness. The tool will (1) explain information using plain language and graphics; (2) provide a step-by-step process for thinking about treating HCV and CKD; (3) tailor relevant information to each user by asking about the individual’s stage of CKD, stage of fibrosis, prior treatment, and comorbidities; (4) assess user knowledge and values for treatment choices; and (5) help individuals use and consider information appropriate to their values and needs to discuss with a clinician. A pilot study including 70 individuals will evaluate the tool’s efficacy, usability, and likelihood of using it in clinical practice. Eligibility criteria will include individuals who understand and read English, who are at least 18 years old, have a diagnosis of HCV (any genotype) and CKD (any stage), and are considering treatment options.DiscussionThis study can identify particular characteristics of individuals or groups that might experience challenges initiating treatment for HCV in the CKD population. This tool could provide a resource to facilitate patient-clinician discussions regarding HCV and CKD treatment options.