Cancer-Related Financial Hardship Screening as Part of Practice Transformation

BACKGROUND

Data on financial hardship, an "adverse event" in individuals with cancer, are needed to inform policy and supportive care interventions and reduce adverse economic outcomes.

METHODS

Lay navigator-led financial hardship screening was piloted among University of Alabama at Birmingham oncology patients initiating treatment in October 2020. Financial hardship screening, including reported financial distress and difficulty, was added to a standard-of-care treatment planning survey. Screening feasibility and completion and proportions of reported financial distress and difficulty were calculated overall and by patient race and rurality. The risk of financial distress by patient sociodemographics was estimated.

RESULTS

Patients who completed a treatment planning survey (N=2741) were 18% Black, Indigenous, or persons of color (BIPOC) and 16% rural dwelling. The majority of patients completed financial hardship screening (90%), surpassing the target feasibility completion rate of 75%. The screening revealed 34% of patients were experiencing financial distress, including 49% of BIPOC and 30% of White patients. Adjusted models revealed BIPOC patients had a 48% higher risk of financial distress compared with those who were White (risk ratio 1.48, 95% CI, 1.31-1.66). Large differences in reported financial difficulties were seen comparing patients who were BIPOC and White (utilities: 33% vs. 10%, upfront medical payments: 44% vs. 23%, transportation: 28% vs. 12%, respectively).

CONCLUSIONS

The collection of patient-reported financial hardship data via routine clinical care was feasible and identified racial inequities at treatment initiation. Efforts to collect patient economic data should support the design, implementation, and evaluation of patient-centered interventions to improve equity and reduce the impact of financial hardship.

Introduction of a pilot program to measure and improve the clinical care of melanoma patients in the Lower Silesian Voivodeship in Poland: a report of 20 months experience

BACKGROUND

In recent years, benchmarking and assessment methods to improve the quality of care have become increasingly important. Such approaches allow for a uniform assessment, comparisons between centers or over time, and the identification of weaknesses. In this study, the results of a 20-month pilot program to assess, monitor and improve the quality of care in melanoma patients primarily treated surgically are presented.

METHODS

The pilot program started in May 2020 at the Lower Silesian Oncology, Pulmonology and Hematology Center (LSOPHC) in Wroclaw, Poland (Lower Silesian Voivodeship, southwestern province of Poland with a population of 2,9 million). The program involved the introduction of a synoptic histopathological protocol, medical coordinators, and a set of measures to assess oncological care. In total, 11 Skin Cancer Unit (SCU) measures were introduced to analyze clinical outcomes, diagnostic quality, and duration. Data from 352 patients covered by the program were analyzed. In addition, the completeness of diagnostics from external sites was compared to our own results. Furthermore, the timeliness of the initial diagnostic tests and in-depth diagnostics were assessed and compared to the timeliness before implementation of the pilot program.

RESULTS

The introduced measures assessed the mortality related to oncological treatment, the rate of complications, advanced stages of melanoma, the completeness and duration of diagnostics, the involved nodes after lymphadenectomy, and melanoma screening. During the study period, the timeliness of the initial diagnostics was maintained at 87.8%, and the timeliness of the in-depth diagnostics at 89.5%. Compared to a similar period before the program, these values were 36.1% and 67.5%, respectively.

CONCLUSION

The introduced measures seem to be effective and practical tools for benchmarking clinical and diagnostic aspects. They also allowed for a sensitive assessment of individual issues and indicated sensitive points. Furthermore, the actions undertaken in this pilot program allowed for a shortening of the duration of diagnostics.

Building Sustainable Practice Transformation Through Payment Reform Initiatives

PURPOSE

Novel value-based payment approaches provide an opportunity to deploy and sustain health care delivery interventions, such as treatment planning documentation. However, limited data are available on implementation costs.

METHODS

We described key factors affecting the cost of implementing care improvements under value-based payments, using treatment planning and Medicare's Oncology Care Model as examples. We estimated expected costs of implementing treatment plans for years 1 and 2-6 under (1) different staffing models, (2) use of technology, and (3) differences in the patients engaged. We compared costs to the payment amounts under the Oncology Care Model.

RESULTS

Team-based models where staffing is aligned with skills needed for key tasks (eg, a combination of lay navigator, nurse, and physician) are more financially feasible when compared with using physicians or nurses alone. When existing staff are at or near capacity, hiring new staff focused on practice transformation activities allows adequate time for new initiatives without negative impacts on existing services. Investments in information technology can enhance staff productivity, but initial costs may be high. Interventions may not be financially feasible if implemented for a small patient volume or only for patients insured by a particular payer. Finally, costs may be higher for disadvantaged populations, and equity in care delivery may require higher payments from payers.

CONCLUSION

Estimating the cost of implementing an intervention in different types of practice settings with various types of patients is essential to ensure that a value-based payment system will adequately support desired improvements in quality of care for all patients.

Implementation of the Institute of Medicine Treatment Plan in Oncology Practice

Participation in the Centers for Medicare & Medicaid Services (CMS) value-based payment reform, the Oncology Care Model (OCM), requires that every beneficiary has a documented 13-point Institute of Medicine treatment plan (TP) when commencing antineoplastic therapy. The intent is to enhance shared decision-making between the patient and care team by providing transparent treatment recommendations and engaging patients and caregivers in meaningful discussion. There is limited discussion in the literature about how to adapt the CMS recommendations to diverse practice settings while maintaining fidelity to the intent of the TP. Here, the authors compare how 3 clinically and geographically unique OCM participating institutions implemented the TP in their respective institutions within the domains of the Consolidated Framework for Implementation Research. Similar themes in implementation are identified, including engaging stakeholders, leveraging information technology, and considering scalability. Adaptations that are unique to the culture and setting of each site are also described.

Importance of quality-of-life priorities and preferences surrounding treatment decision making in patients with cancer and oncology clinicians

BACKGROUND

Shared decision-making (SDM) occurs when a patient partners with their oncologist to integrate personal preferences and values into treatment decisions. A key component of SDM is the elicitation of patient preferences and values, yet little is known about how and when these are elicited, communicated, prioritized, and documented within clinical encounters.

METHODS

This cross-sectional study evaluated nationwide data collected by CancerCare to better understand current patterns of SDM between patients and their oncology clinicians. Patient surveys included questions about the importance of quality-of-life preferences and discussions regarding quality-of-life priorities with their clinicians. Clinician surveys included questions about the discussion of quality-of-life priorities and preferences with patients, the effect of quality-of-life priorities on treatment recommendations, and quality-of-life priority documentation in practice.

RESULTS

Patient survey completers (n = 320; 33% response rate) were predominantly women (95%), had a diagnosis of breast cancer (59%), or were receiving active cancer treatment (59%). Clinician survey completers (n = 112; 5% response rate) predominately identified as hematologists or oncologists (66%). Although 67% of clinicians reported knowing their patients' personal quality-of-life priorities and preferences before finalizing treatment plans, only 37% of patients reported that these discussions occurred before treatment initiation. Most patients (95%) considered out-of-pocket expenses important during treatment planning, yet only 59% reported discussing out-of-pocket expenses with their clinician before finalizing treatment plans. A majority of clinicians (52%) considered clinic questionnaires as feasible to document quality-of-life priorities and preferences.

CONCLUSIONS

Patients and clinicians reported that preferences related to quality-of-life should be considered in treatment decision making, yet barriers to SDM, preference elicitation, and documentation remain.

How Do We Align Health Services Research and Quality Improvement?

Quality improvement (QI) initiatives and health services research (HSR) are commonly used to target health care quality. These disciplines are increasingly important because of the movement toward value-based health care as alternative payment and care delivery models drive institutions and investigators to focus on reducing unnecessary health care use and improving care coordination. QI efforts frequently target medical error and/or efficiency of care through the Plan-Do-Study-Act methodology. Within the QI framework, strategies for data display (e.g., Pareto charts, run charts, histograms, scatter plots) are leveraged to identify opportunities for intervention and improvement. HSR is a multidisciplinary field of study that seeks to identify the most effective way to organize, deliver, and finance health care to maximize the quality and value of care at both the individual and population levels. HSR uses a diverse set of quantitative and qualitative methodologies, such as case-control studies, cohort studies, randomized control trials, and semistructured interview/focus group evaluations. This manuscript provides examples of methodologic approaches for QI and HSR, discusses potential challenges associated with concurrent quality efforts, and identifies strategies to successfully leverage the strengths of each discipline in care delivery.