ABSTRACT
BACKGROUND: In-hospital consultation is essential for patient care. We previously proposed a framework of seven specific consultation types to classify consult requests to improve communication, workflow, and provider satisfaction. METHODS: This multimethods study's aim was to evaluate the applicability of the consult classification framework to real internal medicine (IM) consults. We sought validity evidence using Kane's validity model with focus groups and classifying consult requests from five IM specialties. Participants attended five 1 h semi-structured focus groups that were recorded, transcribed, and coded for thematic saturation. For each specialty, three specialists and three hospitalists categorized 100 (total 500) random anonymized consult requests. The primary outcome was concordance in the classification of consult requests, defined as the sum of partial concordance and perfect concordance, where respectively 4-5/6 and 6/6 participants classified a consult in the same category. We used χ2 tests to compare concordance rates across specialties and between specialists and hospitalists. RESULTS: Five major themes were identified in the qualitative analysis of the focus groups: (1) consult question, (2) interpersonal interactions, (3) value, (4) miscommunication, (5) consult framework application, barriers, and iterative development. In the quantitative analysis, the overall concordance rate was 88.8% (95% confidence interval [CI]: 85.7-91.4), and perfect concordance was 46.6% (95% CI: 42.2-51.1). Concordance differed significantly between hospitalists and specialists overall (p = .01), with a higher proportion of hospitalists having perfect concordance compared to specialists (67.2% vs. 57.8%, p = .002). CONCLUSIONS: The consult classification framework was found to be applicable to consults from five different IM specialties, and could improve communication and education.
Subject(s)
Internal Medicine , Referral and Consultation , Humans , Focus GroupsABSTRACT
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.
