Radiology as the Point of Cancer Patient and Care Team Engagement: Applying the 4R Model at a Patient's Breast Cancer Care Initiation

Timeliness of Breast Diagnostic Imaging and Biopsy in Practice: 15 Years of Collecting, Comparing, and Defining Quality Breast Cancer Care

BACKGROUND

The literature lacks well-established benchmarks for expected time between screening mammogram to diagnostic imaging and then to core needle breast biopsy.

METHODS

Timeliness of diagnostic imaging workup was evaluated using aggregate data from 2005 to 2019 submitted to The National Quality Measures for Breast Centers (NQMBC).

RESULTS

A total of 419 breast centers submitted data for 1,805,515 patients on the time from screening mammogram to diagnostic imaging. The overall time was 7 days with 75th, 25th, and 10th percentile values of 5, 10, and 13.5 days, respectively. The average time in business days decreased from 9.1 to 7.1 days (p < 0.001) over the study period with the greatest gains in poorest-performing quartiles. Screening centers and centers in the Midwest had significantly shorter time to diagnostic imaging. Time from diagnostic imaging to core needle biopsy was submitted by 406 facilities representing 386,077 patients. The average time was 6 business days, with 75th, 25th, and 10th percentiles of 4, 9, and 13.7 days, respectively. Time to biopsy improved from a mean of 9.0 to 6.3 days (p < 0.001) with the most improvement in the poorest-performing quartiles. Screening centers, centers in the Midwest, and centers in metropolitan areas had significantly shorter time to biopsy.

CONCLUSIONS

In a robust dataset, the time from screening mammogram to diagnostic imaging and from diagnostic imaging to biopsy decreased from 2005 to 2019. On average, patients could expect to have diagnostic imaging and biopsies within 1 week of abnormal results. Monitoring and comparing performance with reported data may improve quality in breast care.

Advance Directives for Patients With Breast Cancer: Applying the Right Info/Right Care/Right Patient/Right Time Oncology Model

Background Advance directives (AD) are an important component of life care planning for patients undergoing treatment for cancer; however, there are few effective interventions to increase AD rates. In this quality improvement project, the authors integrated AD counseling into a novel right info/right care/right patient/right time (4R) sequence of care oncology delivery intervention for breast cancer patients in an integrated health care delivery system. Methods The authors studied two groups of patients with newly diagnosed breast cancer who attended a multidisciplinary clinic and underwent definitive surgery at a single facility. The usual care (UC) cohort (N = 139) received care from October 1, 2019 to September 30, 2020. The 4R cohort (N = 141) received care from October 1, 2020 to September 30, 2121 that included discussing AD completion with a health educator prior to surgery. The authors used bivariate analyses to assess whether the AD intervention increased AD completion rates and to identify factors influencing AD completion. Results The UC and 4R cohorts were similar in age, gender, race/ethnicity, interpreter need, Elixhauser comorbidity index, National Comprehensive Cancer Network distress score ≥ 5, surgery type, stage, histology, grade, and Estrogen receptor/Progesterone receptor/ human epidermal growth factor receptor 2 (ER/PR/HER2) status. AD completion rates prior to surgery were significantly higher for the 4R vs UC cohort (73.8%, 95% confidence interval [CI] [66.5%-81.0%] vs 15.1%, 95% CI [9.2%-21.1%], p < .01) and did not significantly differ by age, race, need for interpreter, or distress scores. Conclusion Incorporation of a health educator discussion into a 4R care sequence plan significantly increased rates of time-sensitive AD completion.

Fostering a High-Functioning Team in Cancer Care Using the 4R Oncology Model: Assessment in a Large Health System and a Blueprint for Other Institutions

PURPOSE

Delivering cancer care by high-functioning multidisciplinary teams promises to address care fragmentation, which threatens care quality, affects patient outcomes, and strains the oncology workforce. We assessed whether the 4R Oncology model for team-based interdependent care delivery and patient self-management affected team functioning in a large community-based health system.

METHODS

4R was deployed at four locations in breast and lung cancers and assessed along four characteristics of high-functioning teams: recognition as a team internally and externally; commitment to an explicit shared goal; enablement of interdependent work to achieve the goal; and engagement in regular reflection to adapt objectives and processes.

RESULTS

We formed an internally and externally recognized team of 24 specialties committed to a shared goal of delivering multidisciplinary care at the optimal time and sequence from a patient-centric viewpoint. The team conducted 40 optimizations of interdependent care (22 for breast, seven for lung, and 11 for both cancers) at four points in the care continuum and established an ongoing teamwork adaptation process. Half of the optimizations entailed low effort, while 30% required high level of effort; 78% resulted in improved process efficiency.

CONCLUSION

4R facilitated development of a large high-functioning team and enabled 40 optimizations of interdependent care along the cancer care continuum in a feasible way. 4R may be an effective approach for fostering high-functioning teams, which could contribute to improving viability of the oncology workforce. Our intervention and taxonomy of results serve as a blueprint for other institutions motivated to strengthen teamwork to improve patient-centered care.

Patient-centered Care and Integrated Practice Units: Embracing the Breast Care Continuum

Patient-centered care is a health care approach optimized for the needs of the patient. As patients have sought more autonomy in recent years, this model has been more frequently adopted. Breast radiologists aspiring to advance patient-centered care should seek greater ownership of the breast diagnostic imaging and intervention workflows, helping their patients navigate the complex breast care landscape with patients' preferences taken into account. Applying this approach to breast radiology will increase patient satisfaction and compliance while also limiting wasted health care dollars, unnecessary diagnostic delays, and overall confusion. Herein, the benefits of patient-centered breast radiology are discussed, and numerous suggestions and case examples are provided to help readers reshape their practice toward the priorities of their patients.

Evaluation of the Novel 4R Oncology Care Planning Model in Breast Cancer: Impact on Patient Self-Management and Care Delivery in Safety-Net and Non-Safety-Net Centers

PURPOSE

Optimal cancer care requires patient self-management and coordinated timing and sequence of interdependent care. These are challenging, especially in safety-net settings treating underserved populations. We evaluated the 4R Oncology model (4R) of patient-facing care planning for impact on self-management and delivery of interdependent care at safety-net and non-safety-net institutions.

METHODS

Ten institutions (five safety-net and five non-safety-net) evaluated the 4R intervention from 2017 to 2020 with patients with stage 0-III breast cancer. Data on self-management and care delivery were collected via surveys and compared between the intervention cohort and the historical cohort (diagnosed before 4R launch). 4R usefulness was assessed within the intervention cohort.

RESULTS

Survey response rate was 63% (422/670) in intervention and 47% (466/992) in historical cohort. 4R usefulness was reported by 79.9% of patients receiving 4R and was higher for patients in safety-net than in non-safety-net centers (87.6%, 74.2%, P = .001). The intervention cohort measured significantly higher than historical cohort in five of seven self-management metrics, including clarity of care timing and sequence (71.3%, 55%, P < .001) and ability to manage care (78.9%, 72.1%, P = .02). Referrals to interdependent care were significantly higher in the intervention than in the historical cohort along all six metrics, including primary care consult (33.9%, 27.7%, P = .045) and flu vaccination (38.6%, 27.9%, P = .001). Referral completions were significantly higher in four of six metrics. For safety-net patients, improvements in most self-management and care delivery metrics were similar or higher than for non-safety-net patients, even after controlling for all other variables.

CONCLUSION

4R Oncology was useful to patients and significantly improved self-management and delivery of interdependent care, but gaps remain. Model enhancements and further evaluations are needed for broad adoption. Patients in safety-net settings benefited from 4R at similar or higher rates than non-safety-net patients, indicating that 4R may reduce care disparities.

Systematic Patient Navigation Strategies to Scale Breast Cancer Disparity Reduction by Improved Cancer Prevention and Care Delivery Processes

PURPOSE

Patient navigation uses trained personnel to eliminate barriers to timely care across all phases of the health care continuum, thereby reducing health disparities. However, patient navigation has yet to be systematized in implementation models to improve processes of care at scale rather than remain a band-aid approach focused solely on improving care for the individual patient. The 4R systems engineering approach (right information and right treatment to the right patient at the right time) uses project management discipline principles to develop care sequence templates that serve as patient-centered project plans guiding patients and their care team.

METHODS

A case-study approach focused on the underserved patient shows how facilitators to timely breast cancer screening and care pragmatically identified as emergent data by patient navigators can be actionized by iteratively revising 4R care sequence templates to incorporate new insights as they emerge.

RESULTS

Using a case study of breast cancer screening of a low-income patient, we illustrate how 4R care sequence templates can be revised to incorporate emergent facilitators to care identified through patient navigation.

CONCLUSION

Use of care sequence templates can inform the care team to optimize a particular patient's care, while functioning as a learning health care system for process improvement of patient care and patient navigation scaling. A learning health care system approach that systematically integrates data patterns emerging from multiple patient navigation experiences through in-person navigators and 4R care sequence templates may improve processes of care and allow patient navigation scaling to reduce cancer disparities.

Associations of County-level Radiologist and Mammography Facility Supply with Screening Mammography Rates in the United States

RATIONALE AND OBJECTIVES

The present study aims to assess associations of Medicare beneficiary screening mammography rates with local mammography facility and radiologist availability.

MATERIALS AND METHODS

Mammography screening rates for Medicare fee-for-service beneficiaries were obtained for US counties using the County Health Rankings data set. County-level certified mammography facility counts were obtained from the United States Food and Drug Administration. County-level mammogram-interpreting radiologist and breast imaging subspecialist counts were determined using Centers for Medicare & Medicaid Services fee-for-service claims files. Spearman correlations and multivariable linear regressions were performed using counties' facility and radiologist counts, as well as counts normalized to counties' Medicare fee-for-service beneficiary volume and land area.

RESULTS

Across 3035 included counties, average screening mammography rates were 60.5% ± 8.2% (range 26%-88%). Correlations between county-level screening rates and total mammography facilities, facilities per 100,000 square mile county area, total mammography-interpreting radiologists, and mammography-interpreting radiologists per 100,000 county-level Medicare beneficiaries were all weak (r = 0.22-0.26). Correlations between county-level screening rates and mammography rates per 100,000 Medicare beneficiaries, total breast imaging subspecialist radiologists, and breast imaging subspecialist radiologists per 100,000 Medicare beneficiaries were all minimal (r = 0.06-0.16). Multivariable analyses overall demonstrated radiologist supply to have a stronger independent effect than facility supply, although effect sizes remained weak for both.

CONCLUSION

Mammography facility and radiologist supply-side factors are only weakly associated with county-level Medicare beneficiary screening mammography rates, and as such, screening mammography may differ from many other health-care services. Although efforts to enhance facility and radiologist supply may be helpful, initiatives to improve screening mammography rates should focus more on demand-side factors, such as patient education and primary care physician education and access.

Capacity for Cancer Care Delivery Research in National Cancer Institute Community Oncology Research Program Community Practices: Availability of Radiology and Primary Care Research Partners

PURPOSE

Cancer care spans the spectrum from screening and diagnosis through therapy and into survivorship. Delivering appropriate care requires patient transitions across multiple specialties, such as primary care, radiology, and oncology. From the program's inception, the National Cancer Institute Community Oncology Research Program (NCORP) sites were tasked with conducting cancer care delivery research (CCDR) that evaluates structural, organizational, and social factors, including care transitions that determine patient outcomes. The aim of this study is to describe the capacity of the NCORP to conduct multidisciplinary CCDR that includes radiology and primary care practices.

METHODS

The NCORP includes 34 community and 12 minority and underserved community sites. The Landscape Capacity Assessment was conducted in 2015 across these 46 sites, composed of the 401 components and subcomponents designated to conduct CCDR. Each respondent had the opportunity to designate an operational practice group, defined as a group of components and subcomponents with common care practices and resources. The primary outcomes were the proportion of adult oncology practice groups with affiliated radiology and primary care practices. The secondary outcomes were the proportion of those affiliated radiology and primary care groups that participate in research.

RESULTS

Eighty-seven percent of components and subcomponents responded to at least some portion of the assessment, representing 230 practice groups. Analyzing the 201 adult oncology practice groups, 85% had affiliated radiologists, 69% of whom participate in research. Seventy-nine percent had affiliated primary care practitioners, 31% of whom participate in research. Institutional size, multidisciplinary group practice, and ownership by large regional or multistate health systems was associated with research participation by affiliated radiology and primary care groups. Research participation by these affiliated specialists was not significantly different between the community and the minority and underserved community sites.

CONCLUSIONS

Research relationships exist between the majority of community oncology sites and affiliated radiology practices. Research relationships with affiliated primary care practices lagged. NCORP as a whole has the opportunity to encourage continued and expanded engagement where relationships exist. Where no relationship exists, the NCORP can encourage recruitment, particularly of primary care practices as partners.