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Cited by 50Mobile Health and mHealth ApplicationsTelemedicine and Telehealth ImplementationCancer survivorship and care

Digital Monitoring and Management of Patients With Advanced or Metastatic Non-Small Cell Lung Cancer Treated With Cancer Immunotherapy and Its Impact on Quality of Clinical Care: Interview and Survey Study Among Health Care Professionals and Patients

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Schmalz, Oliver, Jacob, Christine, Ammann, Johannes, Liss, Blasius, Iivanainen, Sanna, Kammermann, Manuel, Koivunen, Jussi, Klein, Alexander +1 more·2020·Journal of Medical Internet Research
DOI 10.2196/18655PMC PMC7781800

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Abstract

Background: Cancer immunotherapy (CIT), as a monotherapy or in combination with chemotherapy, has been shown to extend overall survival in patients with locally advanced or metastatic non-small cell lung cancer (NSCLC). However, patients experience treatment-related symptoms that they are required to recall between hospital visits. Digital patient monitoring and management (DPMM) tools may improve clinical practice by allowing real-time symptom reporting. Objective: This proof-of-concept pilot study assessed patient and health care professional (HCP) adoption of our DPMM tool, which was designed specifically for patients with advanced or metastatic NSCLC treated with CIT, and the tool’s impact on clinical care. Methods: Four advisory boards were assembled in order to co-develop a drug- and indication-specific CIT (CIT+) module, based on a generic CIT DPMM tool from Kaiku Health, Helsinki, Finland. A total of 45 patients treated with second-line single-agent CIT (ie, atezolizumab or otherwise) for advanced or metastatic NSCLC, as well as HCPs, whose exact number was decided by the clinics, were recruited from 10 clinics in Germany, Finland, and Switzerland between February and May 2019. All clinics were provided with the Kaiku Health generic CIT DPMM tool, including our CIT+ module. Data on user experience, overall satisfaction, and impact of the tool on clinical practice were collected using anonymized surveys—answers ranged from 1 (low agreement) to 5 (high agreement)—and HCP interviews; surveys and interviews consisted of closed-ended Likert scales and open-ended questions, respectively. The first survey was conducted after 2 months of DPMM use, and a second survey and HCP interviews were conducted at study end (ie, after ≥3 months of DPMM use); only a subgroup of HCPs from each clinic responded to the surveys and interviews. Survey data were analyzed quantitatively; interviews were recorded, transcribed verbatim, and translated into English, where applicable, for coding and qualitative thematic analysis. Results: Among interim survey respondents (N=51: 13 [25%] nurses, 11 [22%] physicians, and 27 [53%] patients), mean rankings of the tool’s seven usability attributes ranged from 3.2 to 4.4 (nurses), 3.7 to 4.5 (physicians), and 3.7 to 4.2 (patients). At the end-of-study survey (N=48: 19 [40%] nurses, 8 [17%] physicians, and 21 [44%] patients), most respondents agreed that the tool facilitated more efficient and focused discussions between patients and HCPs (nurses and patients: mean rating 4.2, SD 0.8; physicians: mean rating 4.4, SD 0.8) and allowed HCPs to tailor discussions with patients (mean rating 4.35, SD 0.65). The standalone tool was well integrated into HCP daily clinical workflow (mean rating 3.80, SD 0.75), enabled workflow optimization between physicians and nurses (mean rating 3.75, SD 0.80), and saved time by decreasing phone consultations (mean rating 3.75, SD 1.00) and patient visits (mean rating 3.45, SD 1.20). Workload was the most common challenge of tool use among respondents (12/19, 63%). Conclusions: Our results demonstrate high user satisfaction and acceptance of DPMM tools by HCPs and patients, and highlight the improvements to clinical care in patients with advanced or metastatic NSCLC treated with CIT monotherapy. However, further integration of the tool into the clinical information technology data flow is required. Future studies or registries using our DPMM tool may provide insights into significant effects on patient quality of life or health-economic benefits.

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  • Problems connecting digital technologies with electronic health records and existing oncology information systems were reported across ePRO systems, telehealth platforms, mobile applications, and decision-support tools.

    “Problems connecting digital technologies with electronic health records and existing oncology information systems were reported across ePRO systems, telehealth platforms, mobile applications, and decision-support tools [8,32,41,45].”

    From Digital health technologies in oncology services: A scoping review of clinical implementation, organisational evidence gaps, and policy implications (2026) · cites this paper as [45]

    The Discussion (Limitations of the Study; page not available) says the study’s digital monitoring tool was not integrated with local electronic health records or patient-management IT systems, requiring clinicians to record information twice. This supports an integration problem for the studied ePRO-type tool, but the paper does not report such problems across telehealth platforms, mobile applications, and decision-support tools. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • 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 [45]

    The Results section (‘Exploration of HCP Needs, Expectations, and Perceived Value’) reports that workload was the most prominent challenge and that managing the standalone tool and entering data sometimes offset time savings. It links the extra time chiefly to interoperability and system-integration issues, not excessive alerts, nonactionable outputs, or unclear responsibility for responding. Page numbers are unavailable in our copy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

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Authors
Schmalz, O., Jacob, C., Ammann, J., Liss, B., Iivanainen, S., Kammermann, M., Koivunen, J., Klein, A., & Popescu, R. A.
Affiliations
  • Helios Universitätsklinikum Wuppertal (DE)
  • FHNW University of Applied Sciences and Arts Northwestern Switzerland (CH)
  • F. Hoffmann-La Roche AG (CH)
  • Oulu University Hospital (FI)
  • Hirslanden Klinik Aarau (CH)
Corresponding author
Ammann, Johannes
ORCID
Venue
Journal of Medical Internet Research
Publisher
JMIR Publications Inc.
Published
2020-12-21
Volume
22
Issue
12
Pages
e18655
ISSN
1438-8871 (ISSN-L)
DOI
10.2196/18655
PMC
PMC7781800
OpenAlex
W3118043451
Cited by
50
References
12
Citations by year
2026: 7 · 2025: 7 · 2024: 12 · 2023: 11 · 2022: 7 · 2021: 4 · 2020: 2
FWCI
6.27
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
  • Health Sciences › Medicine › Oncology › Cancer survivorship and care
Keywords
metastatic non-small cell lung cancer, cancer immunotherapy, atezolizumab, symptom reporting, usability, patient satisfaction, quality of clinical care, clinical decision support, patient-reported outcomes, digital health tools, treatment-related symptoms, healthcare professionals' perspectives, patient perspectives
MeSH terms
Proof of Concept Study, Carcinoma, Non-Small-Cell Lung, Female, Health Personnel, Humans, Immunotherapy, Lung Neoplasms, Male, Pilot Projects, Quality of Life, Surveys and Questionnaires

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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