Factors Influencing Telemedicine Use at a Northern New England Cancer Center During the COVID-19 Pandemic.

PURPOSE: To characterize the use of telemedicine for oncology care over the course of the COVID-19 pandemic in Northern New England with a focus on factors affecting trends. METHODS: We performed a retrospective observational study using patient visit data from electronic health records from hematology-oncology and radiation-oncology service lines spanning the local onset of the pandemic from March 18, 2020, through March 31, 2021. This period was subdivided into four phases designated as lockdown, transition, stabilization, and second wave. Generalized linear mixed regression models were used to estimate the effects of patient characteristics on trends for rates of telemedicine use across phases and the effects of visit type on patient satisfaction and postvisit ER or hospital admissions within 2 weeks. RESULTS: A total of 19,280 patients with 102,349 visits (13.1% audio-only and 1.4% video) were studied. Patient age (increased use in age < 45 and 85 years and older) and urban residence were associated with higher use of telemedicine, especially after initial lockdown. Recent cancer therapy, ER use, and hospital admissions in the past year were all associated with lower telemedicine utilization across pandemic phases. Provider clinical department corresponded to the largest differences in telemedicine use across all phases. ER and hospital admission rates in the 2 weeks after a telehealth visit were lower than those in in-person visits (0.7% v 1.3% and 1.2% v 2.7% for ER and hospital use, respectively; P < .001). Patient satisfaction did not vary across visit types. CONCLUSION: Telemedicine use in oncology during the COVID-19 pandemic varied according to the phase and patient, medical, and health system factors, suggesting opportunities for standardization of care and need for attention to equitable telemedicine access.

Patient-specific factors associated with pressure injuries revealed by electronic health record analyses.

Hospital-acquired pressure injuries (HAPIs) are a major source of unintended patient harm and unnecessary costs. The Braden Scale is widely used for risk assessment, yet it lacks specificity and clinical applications. This study used the electronic health record to examine associations between patient-specific factors and pressure injury. Adult patients (age >18) with 3-day length of stay from April 2011 to December 2016 were included. Pressure injuries were identified by ICD-9/ICD-10 codes. Longitudinal multivariate logistic regression was used to evaluate the association between patient-specific factors and HAPIs. This included 57,227 hospital encounters and 241 HAPIs. We observed 2-3 times increased likelihood of acquiring a pressure injury among patients who were malnourished or who had increased intraoperative time. The Braden subscales of nutrition, mobility, and friction showed significant predictive value. Future work is needed to assess the clinical applicability of this work.

A clinical care pathway to improve the acute care of patients with glioma.

BACKGROUND: Patients with glioma are at increased risk for tumor-related and treatment-related complications. Few guidelines exist to manage complications through supportive care. Our prior work suggests that a clinical care pathway can improve the care of patients with glioma. METHODS: We designed a quality improvement (QI) project to address the acute care needs of patients with gliomas. We formed a multidisciplinary team and selected 20 best-practice measures from the literature. Using a plan-do-study-act framework, we brainstormed and implemented various improvement strategies starting in October 2013. Statistical process control charts were used to assess progress. RESULTS: Retrospective data were available for 12 best practice measures. The baseline population consisted of 98 patients with glioma. Record review suggested wide variation in performance, with compliance ranging from 30% to 100%. The team hypothesized that lack of process standardization may contribute to less-than-ideal performance. After implementing improvement strategies, we reviewed the records of 63 consecutive patients with glioma. The proportion of patients meeting criteria for 12 practice measures modestly improved (65% pre-QI; 76% post-QI, P > .1). Unexpectedly, a higher proportion of patients were readmitted within 30 days of hospital discharge (pre-QI: 10%; post-QI: 17%, P > .1). Barriers to pathway development included difficulties with transforming manual measures into electronic data sets. CONCLUSIONS: Creating evidence-based clinical care pathways for addressing the acute care needs of patients with glioma is feasible and important. There are many challenges, however, to developing sustainable systems for measuring and reporting performance outcomes overtime.

Improving the quality of care for patients diagnosed with glioma during the perioperative period.

PURPOSE: Although there is agreement on the oncologic management of patients with glioma, few guidelines exist to standardize other aspects of care, including supportive care. METHODS: A quality improvement (QI) project was chartered to improve the care provided to patients with glioma. A multidisciplinary team was convened and identified 10 best-practice measures. Using a plan-do-study-act framework, the team brainstormed and implemented various improvement interventions between June 2011 and October 2012. Statistical process control charts were used to evaluate progress. A dashboard of quality measures was generated to allow for ongoing measurement and reporting. RESULTS: The retrospective assessment phase consisted of 43 patients with diagnosis of glioma. A manual medical record review for these patients showed that compliance with 10 best-practice measures ranged from 23% to 100%. Several factors contributed to less-than-ideal process performance, including poor communication among disciplines and lack of familiarity with the larger system of care. After implementing improvement interventions, performance was measured in 96 consecutive patients with glioma. The proportion of patients who met criteria for 10 practice measures significantly improved (pre-QI work, 63%; post-QI work, 85%; P = .003). The largest improvement was observed in the measure assessing for preoperative notification of the neuro-oncology program (pre-QI work, 39%; post-QI work, 97%; P < .001). CONCLUSION: QI principles were used by a multidisciplinary team to improve the quality of care for patients with glioma during the perioperative period. Leadership involvement, ongoing dialogue across departments, and reporting of system performance were important for sustaining process improvements.