Web-Based Patient-Reported Outcome Measures for Personalized Treatment and Care (PROMPT-Care): Multicenter Pragmatic Nonrandomized Trial
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Abstract
Background: Despite the acceptability and efficacy of e–patient-reported outcome (ePRO) systems, implementation in routine clinical care remains challenging. Objective: This pragmatic trial implemented the PROMPT-Care (Patient Reported Outcome Measures for Personalized Treatment and Care) web-based system into existing clinical workflows and evaluated its effectiveness among a diverse population of patients with cancer. Methods: Adult patients with solid tumors receiving active treatment or follow-up care in four cancer centers were enrolled. The PROMPT-Care intervention supported patient management through (1) monthly off-site electronic PRO physical symptom and psychosocial well-being assessments, (2) automated electronic clinical alerts notifying the care team of unresolved clinical issues following two consecutive assessments, and (3) tailored online patient self-management resources. Propensity score matching was used to match controls with intervention patients in a 4:1 ratio for patient age, sex, and treatment status. The primary outcome was a reduction in emergency department presentations. Secondary outcomes were time spent on chemotherapy and the number of allied health service referrals. Results: From April 2016 to October 2018, 328 patients from four public hospitals received the intervention. Matched controls (n=1312) comprised the general population of patients with cancer, seen at the participating hospitals during the study period. Emergency department visits were significantly reduced by 33% (P=.02) among patients receiving the intervention compared with patients in the matched controls. No significant associations were found in allied health referrals or time to end of chemotherapy. At baseline, the most common patient reported outcomes (above-threshold) were fatigue (39%), tiredness (38.4%), worry (32.9%), general wellbeing (32.9%), and sleep (24.1%), aligning with the most frequently accessed self-management domain pages of physical well-being (36%) and emotional well-being (23%). The majority of clinical feedback reports were reviewed by nursing staff (729/893, 82%), largely in response to the automated clinical alerts (n=877). Conclusions: Algorithm-supported web-based systems utilizing patient reported outcomes in clinical practice reduced emergency department presentations among a diverse population of patients with cancer. This study also highlighted the importance of (1) automated triggers for reviewing above-threshold results in patient reports, rather than passive manual review of patient records; (2) the instrumental role nurses play in managing alerts; and (3) providing patients with resources to support guided self-management, where appropriate. Together, these factors will inform the integration of web-based PRO systems into future models of routine cancer care. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12616000615482; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370633 International Registered Report Identifier (IRRID): RR2-10.1186/s12885-018-4729-3
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Digital tools could add to clinician workload when alerts were excessive, outputs were not actionable, or responsibilities for responding were unclear.
“Several studies showed that digital tools could add to clinician workload when alerts were excessive, outputs were not actionable, or responsibilities for responding were unclear [23,45,50,55].”
From Digital health technologies in oncology services: A scoping review of clinical implementation, organisational evidence gaps, and policy implications (2026) · cites this paper as [55]
The Discussion (Strengths and Limitations; page unavailable) says alerts were limited to reduce false positives and that balancing screening burden against timely alerts is challenging. But the Discussion (Integration and Clinical Use; page unavailable) says this trial’s low alert volume fit existing workflows without onerous additional work. The paper does not report nonactionable outputs or unclear response responsibilities; its Methods instead describe recommended actions and a designated reviewer. (LLM, conf=0.78)
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- Authors
- Girgis, A., Durcinoska, I., Arnold, A., Descallar, J., Kaadan, N., Koh, E.-S., Miller, A., Ng, W., Carolan, M., Della-Fiorentina, S. A., Avery, S., & Delaney, G. P.
- Affiliations
- UNSW Sydney (AU)
- Wollongong Hospital (AU)
- Liverpool Hospital (AU)
- University of Wollongong (AU)
- Corresponding author
- Girgis, Afaf
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2020-10-29
- Volume
- 22
- Issue
- 10
- Pages
- e19685
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7661255
- OpenAlex
- W3062879892
- Cited by
- 92
- References
- 30
- Citations by year
- 2026: 10 · 2025: 10 · 2024: 18 · 2023: 25 · 2022: 19 · 2021: 10
- FWCI
- 4.88
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Online (University of Wollongong) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion)
- Funders
- Cancer Institute NSW
- Topics
- Health Sciences › Medicine › Oncology › Cancer survivorship and care
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- patient-reported outcomes, electronic patient-reported outcomes, cancer care, emergency department presentation, clinical alerts, automated alerts, personalized treatment, fatigue, psychosocial well-being, nursing role, clinical workflow integration, solid tumors, chemotherapy duration, implementation in routine care, electronic health records, shared decision-making
- MeSH terms
- Patient Reported Outcome Measures, Adult, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Internet, Precision Medicine
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