Practice-Changing Strategies to Deliver Affordable, High-Quality Cancer Care: Summary of an Institute of Medicine Workshop

The Financial Burden of Cancer on Families in the United States

This study examined the relationship between a diagnosis of cancer and the likelihood of having any out-of-pocket costs (OOPC) and medical debt, and the amounts of OOPC and medical debt, at the household level. We used the 2013 Panel Study of Income Dynamics, a continuous, representative panel survey that collects demographic, economic, and social data in the United States. The analytic sample included head of households and their spouse (if married), 18–64 years old. Two-part models were used. The first part consisted of logistic regression models and the second part consisted of generalized linear models with logarithmic link and a gamma distribution. Logistic regression results showed odds of 2.13 (CI: 1.27, 3.57, p < 0.01) for any OOPC and odds of 1.55 (CI: 0.93, 2.58, p < 0.1) for any medical debt for households in which either the head or spouse (if married) reported a diagnosis of cancer compared to those that did not report a diagnosis of cancer. Likewise, results from the second part of the model for households with a positive amount of OOPC showed an exponentiated coefficient of 1.73 (CI: 1.33, 2.25, p < 0.01) for households in which either the head or spouse (if married) reported a diagnosis of cancer compared to households without a diagnosis of cancer. This study shows that a diagnosis of cancer places a financial burden on families, particularly with all types of debt, in the United States even after controlling for differences between households with a diagnosis of cancer and those without a diagnosis of cancer.

Cure at what (systemic) financial cost? Integrating novel therapies into first-line Hodgkin lymphoma treatment

Classic Hodgkin lymphoma (cHL) stands out as success story in the field of medical oncology, with multiagent chemotherapy with or without radiation leading to durable remission for most patients. Large-scale clinical trials during the past 40 years have sought to minimize toxicities while maintaining strong efficacy, including efforts to reduce the size of radiation fields, minimize alkylator chemotherapy, reduce the number of chemotherapy cycles, and omit radiation in select populations. The last decade has also ushered in novel therapies, including brentuximab vedotin (BV), that have improved clinical outcomes for patients with cHL resistant to standard cytotoxic therapies. More recently, a large randomized trial compared BV plus chemotherapy with chemotherapy alone for first-line treatment of advanced stage cHL. With ∼24 months of available follow-up, the BV containing regimen was found to be associated with a reduction in the risk of progression, death, or incomplete response to first-line treatment (modified progression-free survival). Whether this early signal of improved efficacy is worth the additional acute toxicities and added drug-related expenses associated with incorporating BV into first-line treatment remains controversial. This chapter provides historical background; reviews the cost-effectiveness of available cHL therapies; and summarizes potential ways to balance innovation, affordability, and patient access to novel therapeutics.

Value-Based Medicine and Integration of Tumor Biology

Clinical oncology is in the midst of a genomic revolution, as molecular insights redefine our understanding of cancer biology. Greater awareness of the distinct aberrations that drive carcinogenesis is also contributing to a growing armamentarium of genomically targeted therapies. Although much work remains to better understand how to combine and sequence these therapies, improved outcomes for patients are becoming manifest. As we welcome this genomic revolution in cancer care, oncologists also must grapple with a number of practical problems. Costs of cancer care continue to grow, with targeted therapies responsible for an increasing proportion of spending. Rising costs are bringing the concept of value into sharper focus and challenging the oncology community with implementation of value-based cancer care. This article explores the ways that the genomic revolution is transforming cancer care, describes various frameworks for considering the value of genomically targeted therapies, and outlines key challenges for delivering on the promise of personalized cancer care. It highlights practical solutions for the implementation of value-based care, including investment in biomarker development and clinical trials to improve the efficacy of targeted therapy, the use of evidence-based clinical pathways, team-based care, computerized clinical decision support, and value-based payment approaches.

Health information technology in oncology practice: a literature review

The adoption and implementation of information technology are dramatically remodeling healthcare services all over the world, resulting in an unstoppable and sometimes overwhelming process. After the introduction of the main elements of electronic health records and a description of what every cancer-care professional should be familiar with, we present a narrative review focusing on the current use of computerized clinical information and decision systems in oncology practice. Following a detailed analysis of the many coveted goals that oncologists have reached while embracing informatics progress, the authors suggest how to overcome the main obstacles for a complete physicians' engagement and for a full information technology adoption, and try to forecast what the future holds.

Measuring the use of examination room time in oncology clinics: a novel approach to assessing clinic efficiency and patient flow

PURPOSE

The use of time in outpatient cancer clinics is a marker of quality and efficiency. Inefficiencies such as excessive patient wait times can have deleterious effects on clinic flow, functioning, and patient satisfaction. We propose a novel method of objectively measuring patient time in cancer clinic examination rooms and evaluating its impact on overall system efficiency.

METHODS

We video-recorded patient visits (N = 55) taken from a larger study to determine patient occupancy and flow in and out of examination rooms in a busy urban clinic in a National Cancer Institute-designated comprehensive cancer center. Coders observed video recordings and assessed patient occupancy time, patient wait time, and physician-patient interaction time. Patient occupancy time was compared with scheduled occupancy time to determine discrepancy in occupancy time. Descriptive and correlational analyses were conducted.

RESULTS

Mean patient occupancy time was 94.8 minutes (SD = 36.6), mean wait time was 34.9 minutes (SD = 28.8), and mean patient-physician interaction time was 29.0 minutes (SD = 13.5). Mean discrepancy in occupancy time was 40.3 minutes (range, 0.75 to 146.5 minutes). We found no correlation between scheduled occupancy time and patient occupancy time, patient-physician interaction time, and patient wait time, or between discrepancy in occupancy time and patient-physician interaction time.

CONCLUSION

The method is useful for assessing clinic efficiency and patient flow. There was no relationship between scheduled and actual time patients spend in exam rooms. Such data can be used in the design of interventions that reduce patient wait times, increase efficient use of resources, and improve scheduling patterns.

Community oncology in an era of payment reform

Patients and payers (government and private) are frustrated with the fee-for-service system (FFS) of payment for outpatient health services. FFS rewards volume and highly valued services, including expensive diagnostics and therapeutics, over lesser valued cognitive services. Proposed payment schemes would incent collaboration and coordination of care among providers and reward quality. In oncology, new payment schemes must address the high costs of all services, particularly drugs, while preserving the robust distribution of sites of service available to patients in the United States. Information technology and personalized cancer care are changing the practice of oncology. Twenty-first century oncology will require increasing cognitive work and shared decision making, both of which are not well regarded in the FFS model. A high proportion of health care dollars are consumed in the final months of life. Effective delivery of palliative and end-of-life care must be addressed by practice and by new models of payment. Value-based reimbursement schemes will require oncology practices to change how they are structured. Lessons drawn from the principles of primary care's Patient Centered Medical Home (PCMH) will help oncology practice to prepare for new schemes. PCMH principles place a premium on proactively addressing toxicities of therapies, coordinating care with other providers, and engaging patients in shared decision making, supporting the ideal of value defined in the triple aim-to measurably improve patient experience and quality of care at less cost. Payment reform will be disruptive to all. Oncology must be engaged in policy discussions and guide rational shifts in priorities defined by new payment models.