Risk stratification and daily symptom monitoring for oncology patients.

Authors

Robert Daly

Robert Michael Daly

Memorial Sloan Kettering Cancer Center, New York, NY

Robert Michael Daly , Claire Perry , Yeneat O. Chiu , Lauren L. Katzen , Margarita Rozenshteyn , Gilad Kuperman , Amandeep K Dhami , Rori Salvaggio , Abigail Baldwin , Jessie C. Holland , Kimberly Chow , Chau T. Dang , Rachel N. Grisham , Stephen R. Veach , Alice Zervoudakis , Isaac Wagner , Brett A Simon , Diane Lauren Reidy , Wendy Perchick

Organizations

Memorial Sloan Kettering Cancer Center, New York, NY, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY, Memor Sloan-Kettering Cancer Ctr, New York, NY, Winthrop Oncology Hematology Associates, Mineola, NY

Research Funding

Other

Background: Monitoring and managing patient reported outcomes (PROs) has been recommended for oncology patients on active treatment but can be time and resource intensive. Identifying patients likely to benefit and the optimal frequency of PRO capture is still under investigation. We tested the feasibility of monitoring patients who are high-risk risk for acute care with daily PROs. Methods: Using data from our institution, we developed a model that employs over 400 clinical variables to calculate a patient’s risk of an emergency room visit within 6 months following the onset of treatment. From October 15, 2018 to January 23, 2019, we enrolled patients identified as high risk through a technology-enabled program to monitor and manage those patients’ symptoms. Enrolled patients entered PRO assessments daily via an online portal. Symptoms were monitored and managed by a centralized clinical team. Tiered notifications informed the team of concerning or escalating symptoms. We assessed how frequently patients completed symptom assessments and the frequency of symptom notifications. Results: During the pilot, 28 patients were identified as high risk and enrolled in the program (median age 65; 64% percent female). Disease types were: 15 (54%) thoracic, 7 (25%) gynecologic, 6 (21%) gastrointestinal. Median time in the program was 50 (6-98) days. Patients completed 840 of 1,350 assessments (62%). There were 328 assessments that triggered moderate alerts (39%) and 220 that triggered severe alerts (26%). The table describes the prevalence of symptoms at the patient-level. Conclusions: A model can be employed to identify high-risk patients in collaboration with clinicians. Our adherence rate with a daily symptom assessment was similar to those found in studies of less frequent PRO capture. Future work will expand to a larger patient population with other cancer types, evaluate impact on outcomes, and assess optimal frequency for PRO collection and alert thresholds.

Prevalence of symptoms reported at moderate or severe levels one or more days % (n=28).

SymptomModerateSevere
Anxiety86%11%
Pain75%54%
Fatigue71%54%
Nausea50%14%
Constipation46%0%
Diarrhea46%0%
Dyspnea43%7%
Decreased oral intake39%11%
Emesis21%4%

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Abstract Details

Meeting

2019 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Health Services Research, Clinical Informatics, and Quality of Care

Track

Quality Care/Health Services Research

Sub Track

Care Delivery/Models of Care

Citation

J Clin Oncol 37, 2019 (suppl; abstr 6535)

DOI

10.1200/JCO.2019.37.15_suppl.6535

Abstract #

6535

Poster Bd #

226

Abstract Disclosures

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