The COVID-19 pandemic has drastically affected the traditional methods residency programs use to train their residents. Chief residents serve a unique role as part of the residency leadership to foster the education and development of the residents. Given the rapid shift in demands on physicians in the face of the pandemic, the responsibilities of the chief residents have also shifted to help prepare the residents to meet these demands as frontline providers. There is not a precedent for how residency programs respond to this crisis while maintaining their primary role to develop and train physicians. The authors have identified 5 questions chief residents can ask to guide their program’s response to the demands of COVID-19 during this uncertain time in health care.
PURPOSE Oral chemotherapy challenges providers' abilities to safely monitor patients' symptoms, adherence, and financial toxicity. COVID-19 has increased the urgency of caring for patients remotely. Collection of electronic patient-reported outcomes (ePROs) has demonstrated efficacy for patients on intravenous chemotherapy, but limited data support their use in oral chemotherapy. We undertook a pilot project to assess the feasibility of implementing an ePRO system for patients starting oral chemotherapy at our cancer center, which includes both an academic site and a community site. METHODS Patients initiating oral chemotherapy were asked to participate. A five-question tool was built in REDCap. Concerning responses triggered outreach within one business day. The primary outcome was time to first symptom assessment. For comparison, we used a historical cohort of patients who had been prescribed oral chemotherapies by providers in the same disease groups at the cancer center. RESULTS Twenty-five of 62 (40%) patients completed ePRO assessments. Fifty historical charts were reviewed. Time to first symptom assessment was 7 days (IQR, 4-14 days) in the historical group compared with 3 days (IQR, 2-4 days) in the ePRO group. Time to clinical action was 14 days (7-35 days) in the historical group compared with 8 days (4-19 days) in the ePRO group. No statistically significant differences were detected in 30-day emergency department visit or hospitalization (12% for both groups) or 90-day emergency department visit or hospitalization rates (historical 28% and ePRO 20%). CONCLUSION An ePRO tool monitoring patient concerns about adherence, cost, and toxicities for patients with new oral chemotherapy regimens is feasible and improves time to symptom assessment. Further investigation is needed to improve patient engagement with ePROs and evaluate the long-term impacts for patients on oral chemotherapy.
BACKGROUND: Continuity clinics are a critical component of outpatient internal medicine training. Little is known about the population of patients cared for by residents and how these physicians perform. OBJECTIVES: To compare resident and faculty performance on standard population health measures. To identify potential associations with differences in performance, specifically medical complexity, psychosocial vulnerability, and rates of patient loss. SETTING AND PARTICIPANTS: Large academic primary care clinic caring for 40,000 patients. One hundred ten internal medicine residents provide primary care for 9,000 of these patients; the remainder are cared for by faculty. STUDY DESIGN: Descriptive analysis using review of the medical record and hospital administrative data. MAIN MEASURES: We compared resident and faculty performance on standard population health measures, including cancer screening rates, chronic disease care, acute and chronic medical complexity, psychosocial vulnerability, and rates of patient loss. We evaluated the success of resident transition by measuring rates of kept continuity visits 18 months after graduation. KEY RESULTS: Performance on all clinical outcomes was significantly better for faculty compared to residents. Despite similar levels of medical complexity compared to faculty patients, resident patients had significantly higher levels of psychosocial vulnerability across all measured domains, including health literacy, economic vulnerability, psychiatric illness burden, high-risk behaviors, and patient engagement. Resident patients experienced higher rates of patient loss than faculty patients (38.5 vs. 18.8%) with only 46.5% of resident patients with a kept continuity appointment in the practice 18 months after graduation. CONCLUSIONS: In this large academic practice, resident performance on standard population health measures was significantly lower than faculty. This may be explained in part by the burden of psychosocial vulnerability of their patients and systems that do not effectively transition patients after graduation. These findings present an opportunity to improve structural equity for these vulnerable patients and developing physicians.
318 Background: Malpractice cases may contain valuable information to inform safety improvement efforts in cancer care. No analyses of malpractice cases have been published focusing on medical oncologists as the primary defendant. The recent development of a new safety incident taxonomy for medical oncology enabled us to classify malpractice cases and identify patient safety improvements.1. Methods: We conducted a qualitative analysis of case vignettes naming medical oncologists as the primary defendant. Case vignettes were obtained from CRICO’s Candello database. Of 452 cases against medical oncologists, a random sample of 100 cases was selected. Cases were coded for the type of safety incident, and whether a system solution could plausibly reduce the risk of a future event. Coding was performed by 3 physicians with experience caring for patients with cancer. Two reviewers reviewed each case; discrepancies were resolved by the third reviewer. Results: Ninety-nine cases were included in the final analysis; 1 was determined to be misassigned to medical oncology as the primary defendant when the case vignette was entirely about radiation oncology treatment and side effects. The most frequent cancer types were breast (16%), acute leukemia (9%), aggressive lymphoma (8%), and gynecologic malignancies (7%). The most common safety incidents identified were provider clinical management errors (41%), adverse drug reactions (20%), relational issues among providers, patients, and other healthcare staff (13%), and prescriber ordering errors (6%). 47 case vignettes described safety incidents that might have been prevented by a systems intervention. The most common interventions were “tumor board or expert review of rare or uncertain cases” (19%), “pharmacist review for safe prescribing of chemotherapy” (17%), “cancer navigator for appointment scheduling in high-risk settings” (9%), “closed loop communication with radiology” (6%), and “electronic patient portal access to all test results” (6%). Conclusions: Using a new medical oncology-focused incident coding taxonomy, we were able to classify all 99 malpractice cases. Human factors issues accounted for the majority of claims. We determined that more comprehensive use of existing improvement interventions might substantially reduce the risk of future events. 1 Jacobson, J. et al. Development of a taxonomy for characterizing medical oncology-related patient safety and quality incidents: A novel approach. BMJ Open Quality. [Manuscript in press]. Accepted June 10, 2022. DOI 10.1136/bmjoq-2022-001828.R2.
283 Background: Monitoring of toxicity and adherence is often lacking for patients recently started on oral chemotherapy. National guidelines recommend active outreach to patients within a week after treatment start. We developed an online tool to actively reach out to patients newly started on oral chemotherapy at one academic medical center and community practice. Methods: A multi-disciplinary team, including patients, developed an online oral chemotherapy adherence, symptom, and financial toxicity assessment tool within REDCap. We implemented this tool for new oral chemotherapy prescriptions in May 2018 in the gastrointestinal oncology group of an academic medical center and a general community practice. To quantify the impact of this tool on symptom management, we completed a retrospective analysis of patients receiving new oral chemotherapy prescriptions at these same sites, in the 13 months immediately preceding clinical implementation of the online tool, May 2017 to May 2018. Results: In the pre-intervention historical cohort (n = 58) the median time to first symptom assessment by a clinician was 7 days (range 1 – 41 days, SD 7 days), median time to identifying a new or worsening symptom was 10 days (range 1-55 days, SD 10 days), and median time to clinical action regarding a new or worsening symptom was 10 days (range 1-104, SD 20 days). Our first intervention patient used the online tool in May 2018 to report symptoms of “nausea and fatigue,” 4 days after starting oral chemotherapy. This resulted in an oncology clinical nurse calling the patient to review symptom management by phone. Conclusions: The median time to first symptom assessment in our historical control cohort is 7 days, with standard deviation of 7 days, suggesting potential room for improvement. Thus far, the online tool has been completed by one patient. Further data will be reported regarding the uptake of this tool, the tool’s impact on quality measures, and patient reported symptoms, adherence, and financial toxicity.
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