Evaluating the cost, cost-effectiveness and survival of an eHealth-facilitated integrated care model for allogeneic stem cell transplantation: Results of the German SMILe randomized, controlled implementation science trial
Bibliographic record
Abstract
PURPOSE: eHealth-facilitated integrated care models (eICMs) have proved effective in improving outcomes for chronically ill patients. However, evidence on cost-effectiveness of eICMs is scarce so far. Allogeneic stem cell transplantation (alloSCT) recipients' post-discharge treatment costs and mortality are greatly influenced by complications. Within the international, multicentric SMILe implementation science project, the eHealth-facilitated SMILe integrated care model (SMILe-ICM) was developed to support patients minimize complications' effects within the first year post-alloSCT. Using initial effectiveness findings from the first center that implemented the SMILe-ICM, this study provides a cost and cost-effectiveness evaluation considering one-year and long-term survival effects, post-discharge costs, and patient-related factors. METHODS: A single-center hybrid effectiveness implementation randomized controlled trial was conducted at a German university hospital from 2/2020 to 8/2022. Eligible alloSCT patients were randomized to the SMILe-ICM or usual care, i.e., one pre-transplant educational nursing visit followed by a physician-led follow-up. The intervention group received usual care plus the SMILe-ICM's four intervention modules (i.e., monitoring of medical/symptom-related parameters, medication adherence, infection prevention, physical activity). All modules were delivered by Advanced Practice Nurses (APNs) in face-to-face visits, combined with continuous online support. Daily, patients entered seventeen medical and symptom-related parameters to the SMILe App, so that APNs could monitor for and investigate possible pre-complication signs. Healthcare utilization costs were assessed at eight time-points (d+30 post-alloSCT-d365) on fourteen self-reported cost indicators and validated against health records. To calculate costs, we applied German standardized unit costs. Cost- and cost-effectiveness were analyzed in five steps: 1.) Calculate total costs, including for the alloSCT inpatient stay and post-discharge follow-up. 2.) Determine life-years gained (survival) as a health benefit unit. 3.) Calculate overall and rehospitalization-free survival estimates. 4.) Calculate the intervention's long-term cost-effectiveness, including extended follow-up, rate of survival until day 1000, and restricted mean survival time. 5.) Contrast these long-term estimates to current post-discharge costs with comparable patient-related factors (age ≥ or < 65, living alone, gender). RESULTS: Seventy-two patients participated (n = 36/group). Total intergroup healthcare utilization and post-discharge costs differed, but non-significantly. Survival rates improved with the SMILe-ICM (88% vs. 80%) at least until day +1000. Rehospitalization-free survival showed improvement (38% vs. 30%); however, considering this sample size, both findings were nonsignificant. Cost-effectiveness analysis showed an overall post-discharge cost-effectiveness of 35,364.01€/patient and 6,742€/life year gained - a mean of 79.21 additional days of life for an intervention investment of 1.464€/patient in the first year post-alloSCT. One-year cost-effectiveness was highest for patients living alone. Younger age correlated with longer survival but higher costs. CONCLUSION: The SMILe-ICM appears to offer survival and rehospitalization benefits, particularly for vulnerable groups, e.g., patients living alone. Larger, adequately powered studies are needed to validate these findings.
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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 | 0.014 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".