Remote Symptom Monitoring With Electronic Patient-Reported Outcomes in Clinical Cancer Populations
Bibliographic record
Abstract
Importance: Value-based health care increasingly requires electronic patient-reported outcome-based remote symptom monitoring (RSM) to improve health care utilization in patients with cancer. However, data on the impact of RSM in clinical practice are lacking. Objective: To evaluate the association of RSM with 3- and 6-month health care utilization among patients receiving systemic cancer treatment. Design, Setting, and Participants: This nonrandomized controlled trial used a hybrid, type 2 implementation-effectiveness design. Participants were patients with cancer at 2 Alabama-based academic institutions receiving chemotherapy, targeted therapy, or immunotherapy; the exposure group received standard-of-care delivered RSM from 2021 to 2024, and historical controls were patients who received cancer treatment prior to RSM implementation from 2017 to 2021. Data were analyzed from May to October 2024. Exposure: RSM using electronic patient-reported outcomes. Main Outcomes and Measures: Health care utilization at 3 and 6 months after RSM enrollment (intensive care unit [ICU] admissions, hospitalizations, emergency department [ED] visits). Adjusted modified Poisson models estimated the relative risk (RR) and 95% CI of health care utilization overall. Penalized logistic regression was used for stratified analyses by patient race, residence, neighborhood deprivation, insurance type, and comorbid conditions. Results: A total of 5949 patients were assessed. From May 2021 to May 2024, 1392 patients (median [IQR] age at index date, 61 [51-69] years; 933 [67%] female) were enrolled in RSM, including 378 Black patients (27%) and 922 White patients (66%), with 262 patients (19%) living in rural areas and 372 patients (27%) living in areas with high neighborhood disadvantage; RSM patients were compared with 4557 controls (median [IQR] age at index date, 62 [53-69] years; 2654 [58%] female), including 1177 Black patients (26%) and 3151 White patients (69%), with 1012 patients (22%) living in rural areas, and 1281 patients (28%) living in areas with high neighborhood disadvantage. Compared with historical controls, hospitalizations among patients receiving RSM were 19% lower at 3 months (RR, 0.81; 95% CI, 0.73-0.91) and 13% lower at 6 months (RR, 0.87; 95% CI, 0.80-0.96). ICU admissions were not significantly different among the RSM populations compared with controls (3 months: RR, 0.82; 95% CI, 0.59-1.13; 6 months: RR, 0.83; 95% CI, 0.65-1.06). ED visits were similar for both groups (3 months: RR, 1.02; 95% CI, 0.89-1.16; 6 months: RR, 1.03; 95% CI, 0.92-1.15). Subset analyses showed similar patterns in 3- and 6-month RR for hospitalizations, ED visits, and ICU admissions. Conclusions and Relevance: In this nonrandomized controlled trial, RSM implementation was associated with reduced risk of hospitalizations for patients with cancer, supporting the need to expand implementation nationally.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".