A multi-dimensional assessment of financial hardship of cancer patients using existing health system data.

BACKGROUND: Existing financial hardship screening does not capture the multifaceted and dynamic nature of the problem. The use of existing health system data is a promising way to enable scalable and sustainable financial hardship screening. METHODS: We used existing data from 303 adult patients with cancer at the University of Virginia Comprehensive Cancer Center (2016-2018). All received distress screening and had a valid financial assistance screening based solely on household size-adjusted income. We constructed a composite index that integrates multiple existing health system data (Epic, distress screening, and cancer registry) to assess comprehensive financial hardship (e.g., material conditions, psychological responses, and coping behaviors). We examined differences of at-risk patients identified by our composite index and by existing single-dimension criterion. Dynamics of financial hardship over time, by age, and cancer type, were examined by fractional probit models. RESULTS: At-risk patients identified by the composite index were generally younger, better educated, and had a higher annual household income, though they had lower health insurance coverage. Identified periods to intervene for most patients are before formal diagnosis, 2 years, and 6 years after diagnosis. Within 2 years of diagnosis and more than 4 years after diagnosis appear critical for subgroups of patients who may suffer from financial hardship disparities. CONCLUSION: Existing health system data provides opportunities to systematically measure and track financial hardship in a systematic, scalable and sustainable way. We find that the dimensions of financial hardship can exhibit different patterns over time and across patient subgroups, which can guide targeted interventions. The scalability of the algorithm is limited by existing data availability.

Evaluating the impact of patients' psychological and physical problems on their interest in participating in research at a cancer center with a rural catchment area.

BACKGROUND: Cancer patients' participation in research trials is essential to improving their care and treatment. In a large sample of adults recently diagnosed with cancer, the aim of the current study is to investigate the relationship between cancer patients' interest in research and the psychological and physical problems they experience resulting from their cancer diagnosis. METHOD: We analyzed data from 906 cancer patients collected during routine clinical care. Correlational analyses focused on the relationship between patients' psychological and physical problems and their interest in research. Hierarchical binary logistic regression analyses tested whether patients' psychological/physical problems as a block predicted their interest in research, above and beyond their sociodemographic characteristics. RESULTS: Higher levels of patients' anxiety, fear of cancer treatment, difficulty managing emotions, worry, suicidal/homicidal ideation, fatigue, problems related to physical appearance, sleep difficulty, and changes to weight/appetite, were associated with a greater interest in research. Patients' psychological/physical problems, as a block, incrementally predicted their interest in research (Δχ2 = 24.34, df = 14, p = .04, Δr2=0.05), though none of the individual psychological/physical problems were found to be significant predictors. A higher level of education was significantly positively associated with an increased likelihood of being interested in research (OR = 1.26, 95%CI = 1.09, 1.46, p = .001). CONCLUSION: Cancer patients' problems stemming from their diagnosis can be important factors in their decision to participate in research. Depending on the needs of the trial in question, researchers may want to account for patients' level of symptom burden in deciding who to approach for enrollment in a research trial.

An Evaluation of the Process and Quality Improvement Measures of the University of Virginia Cancer Center Tobacco Treatment Program.

Tobacco use after a cancer diagnosis can increase risk of disease recurrence, increase the likelihood of a second primary cancer, and negatively impact treatment efficacy. The implementation of system-wide comprehensive tobacco cessation in the oncology setting has historically been low, with over half of cancer clinicians reporting that they do not treat or provide a referral to cessation resources. This quality improvement study evaluated the procedures for assessing and documenting tobacco use among cancer survivors and referring current smokers to cessation resources at the University of Virginia Cancer Center. Process mapping revealed 20 gaps across two major domains: electronic health record (EHR), and personnel barriers. The top identified priority was inconsistent documentation of tobacco use status as it impacted several downstream gaps. Eleven of the 20 gaps were deemed a high priority, and all were addressed during the implementation of the resulting Tobacco Treatment Program. Prioritized gaps were addressed using a combination of provider training, modifications to clinical workflow, and EHR modifications. Since implementation of solutions, the number of unique survivors receiving cessation treatment has increased from 284 survivors receiving cessation support during Year 1 of the initiative to 487 in Year 3. The resulting Tobacco Treatment Program provides a systematic, personalized, and sustainable comprehensive cessation program that optimizes the multifaceted workflow of the Cancer Center and has the potential to reduce tobacco use in a population most in need of cessation support.

Examining the feasibility, acceptability, and potential utility of mobile distress screening in adult cancer patients.

OBJECTIVE: A common method of distress monitoring in cancer patients relies on static and retrospective data collected in-person at the time of a health care provider appointment. Relatively little work has examined the potential usefulness of mobile distress monitoring using cancer patients' smartphones. The current study deployed longitudinal distress monitoring using secure text messaging. METHODS: In an observational study, a total of 52 cancer patients receiving active cancer treatment (Mage  = 58, 62% female) received a text message once a week for 4 weeks. Text messages contained a secure link to complete online the Patient Health Questionnaire-4 (PHQ-4), a commonly used distress screener. RESULTS: Cancer patients completed a distress screener 75% of the time they received a text message. On average, it took less than a minute to complete each mobile distress screener. Geolocation data indicated that cancer patients completed distress screeners across a range of locations. Analyses of model fit of distress scores indicated significant heterogeneity in variability of distress scores over time and across cancer patients (AIC = 630.5). Quantitative feedback from cancer patients at the end of the study indicated high ease of use, ease of learning, and satisfaction of completing mobile distress screeners. CONCLUSIONS: These findings support the use of secure text messaging to monitor longitudinal, out of clinic, distress in cancer patients. Findings also highlight the importance of mobile-based approaches to distress screening in order to maximize opportunities to intervene.