Promoting High-Quality Cancer Care and Equity Through Disciplinary Diversity in Team Composition

Importance of primary care for underserved cancer patients with multiple chronic conditions

PURPOSE

To understand the impact of pre-existing conditions on healthcare utilization among under- and uninsured patients in the transition from cancer treatment to post-treatment survivorship.

METHODS

Using electronic health record data, we constructed a cohort of patients seen in an integrated county health system between 1/1/2010 and 12/31/2016. Six hundred thirty-one adult patients diagnosed with non-metastatic breast or colorectal cancer during this period (cases) were matched 1:1 on sex and Charlson comorbidity index to non-cancer patients who had at least two chronic conditions and with at least one visit to the health system during the study period (controls). Conditional fixed effects Poisson regression models compared number of primary care and emergency department (ED) visits and completed [vs. no show or missed] appointments between cancer and non-cancer patients.

RESULTS

Cancer patients had significantly lower number of visits compared with non-cancer patients (N = 46,965 vs. 85,038). Cancer patients were less likely to have primary care (IRR = 0.25; 95% CI: 0.24, 0.27) and ED visits (IRR = 0.57; 95% CI: 0.50, 0.64) but more likely to complete a scheduled appointment (AOR = 4.83; 95% CI: 4.32, 5.39) compared with non-cancer patients. Cancer patients seen in primary care at a higher rate were more likely to visit the ED (IRR = 2.06; 95% CI: 1.52, 2.80) than those seen in primary care at a lower rate.

CONCLUSION

Health systems need to find innovative, effective solutions to increase primary care utilization among cancer patients with chronic care conditions to ensure optimal management of both chronic conditions and cancer.

IMPLICATIONS FOR CANCER SURVIVORS

Maintaining regular connections with primary care providers during active cancer treatment should be promoted.

Risk Management Activities in a Lung Cancer Multidisciplinary Team at a Comprehensive Cancer Center: Results of a Prospective Analysis

PURPOSE

The objective of the study was to highlight sources of harm that could negatively affect the lung cancer multidisciplinary team (MDT) activities to reduce the level of risk of each factor.

METHODS

A modified Delphi approach was used by a board of multi-health care professionals of the lung cancer MDT to identify the main processes, subprocesses, and risk factors of the multidisciplinary pathway of patients with lung cancer. A semiquantitative matrix was built with a five-point scale for probability of harm (likelihood) and severity of harm (consequences) according to the international risk management standards (ISO 31000-2018). The risk level was calculated by multiplying likelihood × consequences. Mitigation strategies have been identified and applied by the MDT to reduce risks to acceptable levels.

RESULTS

Three main processes (outpatient specialist visit, MDT discussion, and MDT program implementation), eight related subprocesses, and 16 risk factors were identified. Four risk factors (25%) were related to outpatient specialist visit, seven (43.75%) to case discussion, and five (31.25%) to program implementation. Overall, two risk factors were assigned a low-risk level (12.5%), 11 a moderate-risk level (68.75%), one (6.25%) a high-risk level, and two (12.5%) a very high-risk level. After the implementation of mitigation measures, the new semiquantitative risk analysis showed a reduction in almost all hazardous situations: two risk factors (12.5%) were given a very low level, six (37.5%) a low level, seven (43.75%) a moderate level, and one (6.25%) a very high level.

CONCLUSION

An interdisciplinary risk assessment analysis is applicable to MDT activities by using an ad hoc risk matrix: if the hazard is identified and monitored, the risk could be reduced and managed in a short time.

Timeliness of Treatment Initiation in Newly Diagnosed Patients With Breast Cancer

BACKGROUND

Evidence-based timeliness benchmarks have been established to assess quality of breast cancer care, as delays in treatment are associated with poor clinical outcomes. However, few studies have evaluated how current breast cancer care meets these benchmarks and what factors may delay the timely initiation of treatment.

PATIENTS AND METHODS

Demographic and disease characteristics of 377 newly diagnosed patients with breast cancer who initiated treatment at Tufts Medical Center (2009-2015) were extracted from electronic medical records. Time from diagnosis to initial surgery and time from diagnosis to initiation of hormone therapy were estimated with Kaplan-Meier curves. Multivariable regression analysis was used to identify factors associated with treatment delays. Thematic analysis was performed to categorize reasons for delay.

RESULTS

Of 319 patients who had surgery recommended as the first treatment, 248 (78%) met the 45-day benchmark (median, 28 days; 25th-75th %, 19-43). After adjusting for potential confounders, multivariable regression analysis revealed that negative hormone receptor status (odds ratio, 3.48; 95% confidence interval, 1.44-8.43) and mastectomy (odds ratio, 4.07; 95% confidence interval, 2.10-8.06) were significantly associated with delays in surgery. Delays were mostly owing to clinical complexity or logistical/financial reasons. Of 241 patients eligible for hormone therapy initiation, 232 (96%) met the 1-year benchmark (median, 147 days; 25th-75th %, 79-217).

CONCLUSION

Most patients met timeliness guidelines for surgery and initiation of hormone therapy, although risk factors for delay were identified. Knowledge of reasons for breast cancer treatment delay, including clinical complexity and logistical/financial issues, may allow targeting interventions for patients at greatest risk of care delays.

Successful multidisciplinary treatment of uterine serous carcinoma in a patient who had previously undergone renal transplantation

OBJECTIVE

Renal transplantation is a risk factor for premalignant and malignant changes of the endometrium. Thus, prompt and aggressive treatment of postoperative complications remains a major issue. We report the case of an asymptomatic postmenopausal woman with a history of renal transplantation who underwent surgery for uterine serous carcinoma (USC).

CASE REPORT

An asymptomatic 59-year-old woman who had undergone renal transplantation presented with elevated serum CA-125 levels. Cancer screening revealed uterine serous carcinoma, for which she underwent total hysterectomy and bilateral salpingo-oophorectomy. Unfortunately, the postoperative course was complicated by cardiogenic shock and decompensated heart failure. The complexities of the cardiac problems and renal transplantation required a multidisciplinary approach involving different specialists. She was successfully discharged 48 days after the surgery.

CONCLUSION

Gynecologic cancer screening in asymptomatic postmenopausal women after renal transplantation is warranted. If postoperative complications occur in this population, a multidisciplinary approach is recommended.

Cost Differences Associated With Oncology Care Delivered in a Community Setting Versus a Hospital Setting: A Matched-Claims Analysis of Patients With Breast, Colorectal, and Lung Cancers

PURPOSE:

Access to high-quality cancer care remains a challenge for many patients. One such barrier is the increasing cost of treatment. With recent shifts in cancer care delivery from community-based to hospital-based clinics, we examined whether this shift could result in increased costs for patients with three common tumor types.

METHODS:

Cost data for 6,675 patients with breast, lung, and colorectal cancer were extracted from the IMS LifeLink database and analyzed as cost per patient per month (PPPM). Patients treated within a community setting were matched (2 to 1) with those treated at a hospital clinic on the basis of cancer type, chemotherapy regimen, receipt of radiation therapy, presence of metastatic disease, sex, prior surgery, and geographic region. Approximately 84% of patients were younger than 65 years of age.

RESULTS:

Mean total PPPM cost was significantly lower for patients treated in a community- versus hospital-based clinic ($12,548 [standard deviation {SD}, $10,507] v $20,060 [SD, $16,555]; P < .001). The PPPM chemotherapy cost was also significantly lower in the community setting ($4,933 [SD, $4,983] v $8,443 [SD, $10,391]; P < .001). The lower cost observed in community practice was irrespective of chemotherapy regimen and tumor type.

CONCLUSION:

We observed significantly increased costs of care for our patient population treated at hospital-based clinics versus those treated at community-based clinics, largely driven by the increased cost of chemotherapy and provider visits in hospital-based clinics. If the site of cancer care delivery continues to shift toward hospital-based clinics, the increased health care spending for payers and patients should be better elucidated and addressed.

Oncology Pharmacist Opportunities: Closing the Gap in Quality Care

PURPOSE

ASCO has worked to facilitate the improvement in quality oncology care via the development of the Quality Oncology Practice Initiative (QOPI). The extent to which the ASCO QOPI identifies areas in which pharmacists may enhance care is not known. These findings are important, as pharmacists are an integral part of the care team, providing direct clinical care in addition to medication use guidelines and practice-based policies. In addition, high-performing practices may receive reimbursement from the Centers for Medicare and Medicaid Services.

METHODS

Three pharmacists reviewed 200 QOPI measures for potential pharmacist involvement. We used the Hematology/Oncology Pharmacy Association Scope of Practice document and a validated summary of services provided by board-certified oncology pharmacists to identify which practice domains and pharmacy services would best fit the care provided by the selected QOPI measures.

RESULTS

A total of 177 QOPI measures were analyzed. Potential areas of pharmacist impact were identified in 67 (38%) of the included metrics. Measures largely related to optimizing drug therapy through the development and implementation of pharmacy guidelines. Patient counseling and symptom management are services that best described the majority of QOPI measures deemed actionable by a pharmacist. We also found that several QOPI measures pharmacists can intervene upon overlap with metrics currently assessed for reimbursement via the Centers for Medicare and Medicaid Services Merit-Based Incentive Payment System.

CONCLUSION

Oncology pharmacists are uniquely positioned to improve the quality of care provided to patients with cancer within the team-based setting.

Cancer Center Clinic and Research Team Perceptions of Identity and Interactions

PURPOSE

Conduct of cancer clinical trials requires coordination and cooperation among research and clinic teams. Diffusion of and confusion about responsibility may occur if team members' perceptions of roles and objectives do not align. These factors are critical to the success of cancer centers but are poorly studied.

METHODS

We developed a survey adapting components of the Adapted Team Climate Inventory, Measure of Team Identification, and Measure of In-Group Bias. Surveys were administered to research and clinic staff at a National Cancer Institute-designated comprehensive cancer center. Data were analyzed using descriptive statistics, t tests, and analyses of variance.

RESULTS

Responses were received from 105 staff (clinic, n = 55; research, n = 50; 61% response rate). Compared with clinic staff, research staff identified more strongly with their own group ( P < .01) but less strongly with the overall cancer center ( P = .02). Both clinic staff and research staff viewed their own group's goals as clearer than those of the other group ( P < .01) and felt that members of their groups interacted and shared information within ( P < .01) and across ( P < .01) groups more than the other group did. Research staff perceived daily outcomes as more important than did clinic staff ( P = .05), specifically research-related outcomes ( P = .07).

CONCLUSION

Although there are many similarities between clinic and research teams, we also identified key differences, including perceptions of goal clarity and sharing, understanding and alignment with cancer center goals, and importance of outcomes. Future studies should examine how variation in perceptions and group dynamics between clinic and research teams may impact function and processes of cancer care.