Telemedicine Use for Oncology Clinic Visits at a Large Medical Center During the Onset of COVID-19

The association between telemedicine, advance care planning, and unplanned hospitalizations among high-risk patients with cancer

BACKGROUND

Despite the widespread implementation of telemedicine, there are limited data regarding its impact on key components of care for patients with incurable or high-risk cancer. For these patients, high-quality care requires detailed conversations regarding treatment priorities (advance care planning) and clinical care to minimize unnecessary acute care (unplanned hospitalizations). Whether telemedicine affects these outcomes relative to in-person clinic visits was examined among patients with cancer at high risk for 6-month mortality.

METHODS

This retrospective cohort study included adult patients with cancer with any tumor type treated at the University of Pennsylvania who were newly identified between April 1 and December 31, 2020, to be at high risk for 6-month mortality via a validated machine learning algorithm. Separate modified Poisson regressions were used to assess the occurrence of advance care planning and unplanned hospitalizations for telemedicine as compared to in-person visits. Additional analyses were done comparing telemedicine type (video or phone) as compared to in-person clinic visits.

RESULTS

The occurrence of advance care planning was similar between telemedicine and in-person visits (6.8% vs. 6.0%; adjusted risk ratio [aRR], 1.25; 95% CI, 0.92-1.69). In regard to telemedicine subtype, patients exposed to video encounters were modestly more likely to have documented advance care planning in comparison to those seen in person (7.5% vs. 6.0%; aRR, 1.48; 95% CI, 1.03-2.11). The 3-month risk for unplanned hospitalization was comparable for telemedicine compared to in-person clinic encounters (21% vs. 18%; aRR, 1.06; 95% CI, 0.81-1.38).

CONCLUSIONS

In this study, care delivered by telemedicine, compared to in-person clinic visits, produced comparable rates of advance care planning conversations without increasing hospitalizations, which suggests that vulnerable patients can be managed safely by telemedicine.

Examining disparities in large-scale patient-reported data capture using digital tools among cancer patients at clinical intake

BACKGROUND

Patient-reported data can improve quality of healthcare delivery and patient outcomes. Moffitt Cancer Center ("Moffitt") administers the Electronic Patient Questionnaire (EPQ) to collect data on demographics, including sexual orientation and gender identity (SOGI), medical history, cancer risk factors, and quality of life. Here we investigated differences in EPQ completion by demographic and cancer characteristics.

METHODS

An analysis including 146,142 new adult patients at Moffitt in 2009-2020 was conducted using scheduling, EPQ and cancer registry data. EPQ completion was described by calendar year and demographics. Logistic regression was used to estimate associations between demographic/cancer characteristics and EPQ completion. More recently collected information on SOGI were described.

RESULTS

Patient portal usage (81%) and EPQ completion rates (79%) were consistently high since 2014. Among patients in the cancer registry, females were more likely to complete the EPQ than males (odds ratio [OR] = 1.17, 95% confidence interval [CI] = 1.14-1.20). Patients ages 18-64 years were more likely to complete the EPQ than patients aged ≥65. Lower EPQ completion rates were observed among Black or African American patients (OR = 0.59, 95% CI = 0.56-0.63) as compared to Whites and among patients whose preferred language was Spanish (OR = 0.40, 95% CI = 0.36-0.44) or another language as compared to English. Furthermore, patients with localized (OR = 1.16, 95% CI = 1.12-1.19) or regional (OR = 1.16, 95% CI = 1.12-1.20) cancer were more likely to complete the EPQ compared to those with metastatic disease. Less than 3% of patients self-identified as being lesbian, gay, or bisexual and <0.1% self-identified as transgender, genderqueer, or other.

CONCLUSIONS

EPQ completion rates differed across demographics highlighting opportunities for targeted process improvement. Healthcare organizations should evaluate data acquisition methods to identify potential disparities in data completeness that can impact quality of clinical care and generalizability of self-reported data.