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Feasibility and accessibility of electronic patient-reported outcome measures using a smartphone during routine chemotherapy: a pilot study

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Abstract

Purpose

There is growing interest in integrating electronic patient-reported outcome (PRO) measures into routine oncology practice for symptom monitoring. Here, we evaluated the feasibility and accessibility of electronic PRO measures using a smartphone (PRO-SMART) for cancer patients receiving routine chemotherapy.

Methods

The proposed PRO-SMART application obtains daily personal health record (PHR) data from cancer patients via a smartphone. An analysis report of cumulative PHR data is provided to the clinician in a format suitable for upload to electronic medical records (EMRs). Cancer outpatients who had received at least two cycles of chemotherapy and who were scheduled for two more cycles were enrolled.

Results

Between February 2015 and December 2016, 111 patients were screened and 101 of these were included. One-hundred patients used PRO-SMART at least once and were included in the final analysis (90.1% overall accessibility among all screened patients). The number of symptomatic adverse events (AEs) related to chemotherapy recorded in EMRs (mean ± standard deviation [SD]) increased from 0.92 ± 0.80 to 2.26 ± 1.80 (P < 0.001), and grading of AEs increased from 0.81 ± 0.69 to 1.00 ± 0.62 (P = 0.029). After using PRO-SMART, the numeric rating scale for pain (mean ± SD) increased from 0.20 ± 0.72 to 0.99 ± 1.55 (P < 0.001). A patient-reported questionnaire revealed that 64.2% of patients found it useful and 83% found it easy to use.

Conclusions

This study suggests that the proposed PRO-SMART is feasible and accessible for assessment of symptomatic AEs in cancer patients receiving chemotherapy for a prospective randomized trial.

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Acknowledgements

We appreciate the role of the company-affiliated research team in PRO-SMART development (Babylon Division at Turbosoft Inc.; Cheongwon, Republic of Korea).

Funding

This research was supported by a Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education, Science and Technology (2017R1A5A2015541).

Author information

Author notes

  1. Woo Kyun Bae and Jihyun Kwon contributed equally to this work.

Authors and Affiliations

  1. Department of Internal Medicine, Chonnam National University Hwasun Hospital, Hwasun-Gun, South Korea

    Woo Kyun Bae

  2. Department of Internal Medicine, Chungbuk National University Hospital, Cheongju, South Korea

    Jihyun Kwon, Yaewon Yang, Ki Hyeong Lee & Hye Sook Han

  3. Department of Internal Medicine, Ajou University School of Medicine, Suwon, South Korea

    Hyun Woo Lee

  4. Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, South Korea

    Sang-Cheol Lee

  5. Department of Internal Medicine, Chonbuk National University Medical School, Jeonju, South Korea

    Eun-Kee Song

  6. Department of Internal Medicine, School of Medicine, Wonkwang University, Iksan, South Korea

    Hyeok Shim

  7. Database/Bioinformatics Laboratory, College of Electrical & Computer Engineering, Chungbuk National University, Cheongju, South Korea

    Keun Ho Ryu

  8. Turbosoft Inc., Cheongwon, South Korea

    Jemin Song & Sungbo Seo

  9. College of Medicine/Graduate School of Health Science Business Convergence, Chungbuk National University, Cheongju, South Korea

    Jong-Hyock Park

  10. Department of Internal Medicine, College of Medicine, Chungbuk National University, Chungdae-ro 1, Seowon-gu, Cheongju, 28644, South Korea

    Ki Hyeong Lee & Hye Sook Han

Authors
  1. Woo Kyun Bae
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  2. Jihyun Kwon
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  3. Hyun Woo Lee
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  6. Hyeok Shim
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  7. Keun Ho Ryu
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  8. Jemin Song
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  9. Sungbo Seo
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  10. Yaewon Yang
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  11. Jong-Hyock Park
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  12. Ki Hyeong Lee
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  13. Hye Sook Han
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Contributions

Bae WK and Kwon J are the first authors; Han HS is the corresponding author. Bae WK, Kwon J, and Han HS contributed to study design, recruitment of patients, data analysis, data interpretation, and manuscript writing. Ryu KH, Song J, and Seo S were involved in the development of PRO-SMART. Lee SC, Song EK, Shim H, and Lee KH contributed to recruitment of patients and data analysis and interpretation. Yang Y and Park JH contributed to data analysis and interpretation. All authors helped to write and gave final approval to the manuscript.

Corresponding author

Correspondence to Hye Sook Han.

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Conflict of interest

The authors declare that they have no conflict of interest.

Electronic supplementary material

Figure S1

Flow diagram of the patients. PRO-SMART, patient-reported outcome measures using a smartphone. (GIF 132 kb)

High Resolution Image (TIF 308 kb)

Figure S2

User interface for patient-reported outcome measures using a smartphone (PRO-SMART). (A) User interface of the smartphone application. The input personal health record (PHR) information is classified into four parts: pain, symptomatic adverse events (AEs), diet, and exercise. The pain input portion includes position, intensity, number of breakthrough pains, or sleep disturbance due to pain. The symptomatic AEs input section supports nine common symptomatic AEs related to chemotherapy. (B) User interface of the web service. The patient’s PHR information is provided to the clinician through the PHR gateway in a text format used in medical records and graphs. (GIF 17 kb)

High Resolution Image (TIF 35 kb)

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Bae, W.K., Kwon, J., Lee, H.W. et al. Feasibility and accessibility of electronic patient-reported outcome measures using a smartphone during routine chemotherapy: a pilot study. Support Care Cancer 26, 3721–3728 (2018). https://doi.org/10.1007/s00520-018-4232-z

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  • DOI: https://doi.org/10.1007/s00520-018-4232-z

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