Digitally Enabled Transitional Care Management in Oncology.

PURPOSE: Improving care transitions for patients with cancer discharged from the hospital is considered an important component of quality care. Digital monitoring has the potential to better the delivery of transitional care through improved patient-provider communication and enhanced symptom management. However, remote patient monitoring (RPM) interventions have not been widely implemented for oncology patients after discharge, an innovative setting in which to apply this technology. METHODS: We implemented a RPM intervention which identifies medical oncology patients at discharge, monitors their symptoms for 10 days, and intervenes as necessary to manage symptoms. We evaluated the feasibility (>50% patient engagement with symptom assessment), appropriateness (symptom alerts), and acceptability (net promoter score >0.7) of the intervention and the initial effect on acute care visits and return on investment. RESULTS: During the study period, January 1, 2021, to December 31, 2022, we evaluated 2,257 medical oncology discharges representing 1,857 unique patients. We found that 65.9% of patients discharged (N = 1,489) completed at least one symptom assessment postdischarge and of them, 45.5% (n = 678) generated a severe symptom alert that we helped to manage. Patients expressed high satisfaction with the intervention with a net promoter score of 84%. In preliminary analysis of patients with GI malignancies (n = 449), we found a nonsignificant decrease in 30-day readmissions for the intervention cohort (n = 269) by 5.8% as compared with the control (n = 180; from 33.3% to 27.5%; P = .22). CONCLUSION: Digital transitional care management was feasible and demonstrated that patients transitioning from the hospital to home have a substantial symptom burden. The intervention was associated with high patient satisfaction but will require further refinement and evaluation to increase its impact on 30-day readmission.

Association Between Remote Monitoring and Acute Care Visits in High-Risk Patients Initiating Intravenous Antineoplastic Therapy.

PURPOSE: Traditional oncology care models have not effectively identified and managed at-risk patients to prevent acute care. A next step is to harness advances in technology to enable patients to report symptoms any time, enabling digital hovering-intensive symptom monitoring and management. Our objective was to evaluate a digital platform that identifies and remotely monitors high-risk patients initiating antineoplastic therapy with the goal of preventing acute care visits. METHODS: This was a single-institution matched cohort quality improvement study conducted at a National Cancer Institute-designated cancer center between January 1, 2019, and March 31, 2020. Eligible patients were those initiating intravenous antineoplastic therapy who were identified as high risk for seeking acute care. Enrolled patients' symptoms were monitored using a digital platform. A dedicated team of clinicians managed reported symptoms. The primary outcomes of emergency department visits and hospitalizations within 6 months of treatment initiation were analyzed using cumulative incidence analyses with a competing risk of death. RESULTS: Eighty-one patients from the intervention arm were matched by stage and disease with contemporaneous high-risk control patients. The matched cohort had similar baseline characteristics. The cumulative incidence of an emergency department visit for the intervention cohort was 0.27 (95% CI, 0.17 to 0.37) at six months compared with 0.47 (95% CI, 0.36 to 0.58) in the control (P = .01) and of an inpatient admission was 0.23 (95% CI, 0.14 to 0.33) in the intervention cohort versus 0.41 (95% CI, 0.30 to 0.51) in the control (P = .02). CONCLUSION: The narrow employment of technology solutions to complex care delivery challenges in oncology can improve outcomes and innovate care. This program was a first step in using a digital platform and a remote team to improve symptom care for high-risk patients.

Analysis of a Remote Monitoring Program for Symptoms Among Adults With Cancer Receiving Antineoplastic Therapy.

IMPORTANCE: Electronic patient-reported outcomes (ePROs) may have the potential to improve cancer care delivery by enhancing patient quality of life, reducing acute care visits, and extending overall survival. However, the optimal cadence of ePRO assessments is unknown. OBJECTIVE: To determine patient response preferences and the clinical value associated with a daily cadence for ePROs for patients receiving antineoplastic treatment. DESIGN, SETTING, AND PARTICIPANTS: This quality improvement study of adult patients undergoing antineoplastic treatment assessed a remote monitoring program using ePROs that was developed to manage cancer therapy-related symptoms. ePRO data submitted between October 16, 2018 to February 29, 2020, from a single regional site within the Memorial Sloan Kettering Cancer Center network were included. Data were analyzed from April 2020 to January 2022. EXPOSURE: While undergoing active treatment, patients received a daily ePRO assessment that, based on patient responses, generated yellow (moderate) or red (severe) symptom alerts that were sent to clinicians. MAIN OUTCOMES AND MEASURES: The main outcomes assessed included patient response rate, symptom alert frequency, and an analysis of the clinical value of daily ePROs. RESULTS: A total of 217 patients (median [range] age, 66 [31-92] years; 103 [47.5%] women and 114 [52.5%] men) initiating antineoplastic therapy at high risk for symptoms were monitored for a median (range) of 91 (2-369) days. Most patients had thoracic (59 patients [27.2%]), head and neck (48 patients [22.1%]), or gastrointestinal (43 patients [19.8%]) malignant neoplasms. Of 14 603 unique symptom assessments completed, 7349 (50.3%) generated red or yellow symptom alerts. Symptoms commonly generating alerts included pain (665 assessments [23.0%]) and functional status (465 assessments [16.1%]). Most assessments (8438 assessments [57.8%]) were completed at home during regular clinic hours (ie, 9 am-5 pm), with higher response rates on weekdays (58.4%; 95% CI, 57.5%-59.5%) than on weekend days (51.3%; 95% CI, 49.5%-53.1%). Importantly, 284 of 630 unique red alerts (45.1%) surfaced without a prior yellow alert for the same symptom within the prior 7 days; symptom severity fluctuated over the course of a week, and symptom assessments generating a red alert were followed by an acute care visit within 7 days 8.7% of the time compared with 2.9% for assessments without a red alert. CONCLUSIONS AND RELEVANCE: These findings suggest that daily ePRO assessments were associated with increased insight into symptom management in patients undergoing antineoplastic treatment and symptom alerts were associated with risk of acute care.

Oncology Patients' Perspectives on Remote Patient Monitoring for COVID-19.

PURPOSE: Oncology patients are vulnerable to adverse outcomes associated with COVID-19, and clinical deterioration must be identified early. Several institutions launched remote patient monitoring programs (RPMPs) to care for patients with COVID-19. We describe patients' perspectives on a COVID-19 RPMP at a National Comprehensive Cancer Center. METHODS: Patients who tested positive for COVID-19 were eligible. Enrolled patients received a daily electronic COVID-19 symptom assessment, and a subset of high-risk patients also received a pulse oximeter. Monitoring was provided by a centralized team and was discontinued 14 days after a patient's positive test result and following 3 days without worsening symptoms. Patients who completed at least one assessment and exited the program were sent a patient engagement survey to evaluate the patient's experience with digital monitoring for COVID-19. RESULTS: The survey was distributed to 491 patients, and 257 responded (52% completion rate). The net promoter score was 85%. Most patients agreed that the RPMP was worthwhile, enabled better management of their COVID-19 symptoms, made them feel more connected to their healthcare team, and helped prevent emergency room visits. Identified themes regarding patient-perceived value of a RPMP included (1) security: a clinical safety net; (2) connection: a link to their clinical team during a period of isolation; and (3) empowerment: an education on the virus and symptom management. CONCLUSION: RPMPs are perceived to be of value to oncology patients with COVID-19. Policymakers should consider how these programs can be reimbursed to keep vulnerable patients at home and out of the acute care setting.

InSight Care Pilot Program: Redefining Seeing a Patient.

PURPOSE: Early detection and management of symptoms in patients with cancer improves outcomes. However, the optimal approach to symptom monitoring and management is unknown. InSight Care is a mobile health intervention that captures symptom data and facilitates patient-provider communication to mitigate symptom escalation. PATIENTS AND METHODS: Patients initiating antineoplastic treatment at a Memorial Sloan Kettering regional location were eligible. Technology supporting the program included the following: a predictive model that identified patient risk for a potentially preventable acute care visit; a secure patient portal enabling communication, televisits, and daily delivery of patient symptom assessments; alerts for concerning symptoms; and a symptom-trending application. The main outcomes of the pilot were feasibility and acceptability evaluated through enrollment and response rates and symptom alerts, and perceived value evaluated on the basis of qualitative patient and provider interviews. RESULTS: The pilot program enrolled 100 high-risk patients with solid tumors and lymphoma (29% of new treatment starts v goal of 25%). Over 6 months of follow-up, the daily symptom assessment response rate was 56% (the goal was 50%), and 93% of patients generated a severe symptom alert. Patients and providers perceived value in the program, and archetypes were developed for program improvement. Enrolled patients were less likely to use acute care than were other high-risk patients. CONCLUSION: InSight Care was feasible and holds the potential to improve patient care and decrease facility-based care. Future work should focus on optimizing the cadence of patient assessments, the workforce supporting remote symptom management, and the return of symptom data to patients and clinical teams.

Building a Clinically Relevant Risk Model: Predicting Risk of a Potentially Preventable Acute Care Visit for Patients Starting Antineoplastic Treatment.

PURPOSE: To create a risk prediction model that identifies patients at high risk for a potentially preventable acute care visit (PPACV). PATIENTS AND METHODS: We developed a risk model that used electronic medical record data from initial visit to first antineoplastic administration for new patients at Memorial Sloan Kettering Cancer Center from January 2014 to September 2018. The final time-weighted least absolute shrinkage and selection operator model was chosen on the basis of clinical and statistical significance. The model was refined to predict risk on the basis of 270 clinically relevant data features spanning sociodemographics, malignancy and treatment characteristics, laboratory results, medical and social history, medications, and prior acute care encounters. The binary dependent variable was occurrence of a PPACV within the first 6 months of treatment. There were 8,067 observations for new-start antineoplastic therapy in our training set, 1,211 in the validation set, and 1,294 in the testing set. RESULTS: A total of 3,727 patients experienced a PPACV within 6 months of treatment start. Specific features that determined risk were surfaced in a web application, riskExplorer, to enable clinician review of patient-specific risk. The positive predictive value of a PPACV among patients in the top quartile of model risk was 42%. This quartile accounted for 35% of patients with PPACVs and 51% of potentially preventable inpatient bed days. The model C-statistic was 0.65. CONCLUSION: Our clinically relevant model identified the patients responsible for 35% of PPACVs and more than half of the inpatient beds used by the cohort. Additional research is needed to determine whether targeting these high-risk patients with symptom management interventions could improve care delivery by reducing PPACVs.

Misery Loves Company: Presenting Symptom Clusters to Urgent Care by Patients Receiving Antineoplastic Therapy.

PURPOSE: The Centers for Medicare & Medicaid Services (CMS) identifies suboptimal management of treatment toxicities as a care gap and proposes the measurement of hospital performance on the basis of emergency department visits for 10 common symptoms. Current management strategies do not address symptom co-occurrence. METHODS: We evaluated symptom co-occurrence in three patient cohorts that presented to a cancer hospital urgent care center in 2016. We examined both the CMS-identified symptoms and an expanded clinician-identified set defined as symptoms that could be safely managed in the outpatient setting if identified early and managed proactively. The cohorts included patients who presented with a CMS-defined symptom within 30 days of treatment, patients who presented within 30 days of treatment with a symptom from the expanded set, and patients who presented with a symptom from the expanded set within 30 days of treatment start. Symptom co-occurrence was measured by Jaccard index. A community detection algorithm was used to identify symptom clusters on the basis of a random walk process, and network visualizations were used to illustrate symptom dynamics. RESULTS: There were 6,429 presentations in the CMS symptom-defined cohort. The network analysis identified two distinct symptom clusters centered around pain and fever. In the expanded symptom cohort, there were 5,731 visits and six symptom clusters centered around fever, emesis/nausea, fatigue, deep vein thrombosis, pain, and ascites. For patients who newly initiated treatment, there were 1,154 visits and four symptom clusters centered around fever, nausea/emesis, fatigue, and deep vein thrombosis. CONCLUSION: Uncontrolled symptoms are associated with unplanned acute care. Recognition of the complexity of symptom co-occurrence can drive improved management strategies.