JMIR Publications

ABSTRACT

Background:

Chemotherapy cycle prescription is generally carried out through a manual process. ICT tools with data analytics could streamline this process and limit human errors.

Objective:

We aim to assess the feasibility of a novel decision support system in chemotherapy cycle pre-evaluation and prescription.

Methods:

A one-arm multicenter prospective clinical trial ECHO 7/2019-1/2021 (NCT04081558) investigated the use of a novel Kaiku Health ePRO tool in cancer care. The most important patient inclusion criteria were colorectal cancer (CRC) planned to be treated with oxaliplatin-based chemotherapy as an adjuvant therapy or in the first or second line setting of advanced disease, age ≥18 years, ECOG performance score of 0-2, and internet access. A decision support tool consisting of a digital symptom monitoring, laboratory value interface, and treatment schedule integration for a semi-automatized chemotherapy cycle prescribing was created for the trial.

Results:

The dataset included CRC patients (n=43) treated with doublet or triplet chemotherapy in adjuvant or metastatic setting, and 339 prescribed chemotherapy cycles. For the 77% of the new chemotherapy cycles, ePRO questionnaire data was available. 65% of cycles had symptom questionnaires grading at ≤ 1 while 67% of the cycles had laboratory values at pre-set range. The recommendation by the tool for a new chemotherapy cycle was (green/go) in 42.8%, two (yellow/evaluate) in 24.5%, and three (red/hold) 32.7% of the cycles. HCPs valued the improved workflow, faster patient evaluation, and direct messaging option the most.

Conclusions:

In this study, we investigated the feasibility of a decision support system in chemotherapy cycle pre-evaluation and prescription. The study shows that the functionalities of the investigated tool were feasible, and an automated approach to chemotherapy cycle prescription was possible for nearly half of the cycles. Clinical Trial: NCT04081558 9th Sep 2019