Multimodal machine learning to predict surgical site infection with healthcare workload impact assessment
Remote monitoring is essential for healthcare digital transformation, however, this poses greater burdens on healthcare providers to review and respond as the data collected expands. This study developed a multimodal neural network to automate assessments of patient-generated data from remote postoperative wound monitoring. Two interventional studies including adult gastrointestinal surgery patients collected wound images and patient-reported outcome measures (PROMs) for 30-days postoperatively. Neural networks for PROMs and images were combined to predict surgical site infection (SSI) diagnosis within 48 h. The multimodal neural network model to predict confirmed SSI within 48 h remained comparable to clinician triage (0.762 [0.690-0.835] vs 0.777 [0.721-0.832]), with an excellent performance on external validation. Simulated usage indicated an 80% reduction in staff time (51.5 to 9.1 h) without compromising diagnostic accuracy. This multimodal approach can effectively support remote monitoring, alleviating provider burden while ensuring high-quality postoperative care.
Authors
- Mark A. Potter (ORCID: https://orcid.org/0000-0002-1417-7515)
- David Henshall (ORCID: https://orcid.org/0000-0001-7377-3969)
- Aya Riad (ORCID: https://orcid.org/0000-0003-3296-9353)
- Katie E. Mountain
- Amfiana Gherman
- Leo R. Brown (ORCID: https://orcid.org/0000-0001-6181-7020)
- C. Leavy
- Wendy Wilson
- Matt-Mouley Bouamrane (ORCID: https://orcid.org/0000-0002-1416-751X)
- L. Green
- Courtney Gent
- Darja Kremel
- Julia Grewar (ORCID: https://orcid.org/0000-0001-9544-8016)
- Chris Johnston (ORCID: https://orcid.org/0000-0001-9935-7365)
- Brent I. Fox (ORCID: https://orcid.org/0000-0003-1593-0449)
- J. Liu
- S. Jayasangaran (ORCID: https://orcid.org/0000-0002-6301-0682)
- C. Iiuoma
- K. Czyzykowska
- Zhan Herr Ng (ORCID: https://orcid.org/0000-0003-4428-0916)
- A Sgrò (ORCID: https://orcid.org/0000-0001-5151-8342)
- Sean Heelan
- Louis F. Buijs
- Monisha Edirisooriya (ORCID: https://orcid.org/0000-0001-7736-2542)
- Janice Y. Kung (ORCID: https://orcid.org/0000-0001-8676-8675)
- K. Baweja
- S. Mowitt
- Kenneth A McLean (ORCID: https://orcid.org/0000-0001-6482-9086)
- Ewan D. Kennedy (ORCID: https://orcid.org/0000-0002-0115-4488)
- Ben M. Stutchfield
- Stephen R Knight (ORCID: https://orcid.org/0000-0003-0448-3719)
- Sotirios A. Tsaftaris (ORCID: https://orcid.org/0000-0002-8795-9294)
- Catherine A. Shaw (ORCID: https://orcid.org/0000-0002-2381-7879)
- James Chih‐Hsin Yang (ORCID: https://orcid.org/0000-0002-5586-5138)
- Anna Forsyth (ORCID: https://orcid.org/0000-0002-3283-2691)
- Thomas M Drake (ORCID: https://orcid.org/0000-0002-9334-6494)
- Riinu Pius (ORCID: https://orcid.org/0000-0002-8738-4902)
- Mark Wojtowicz (ORCID: https://orcid.org/0000-0003-2892-9404)
- Stephen J. Wigmore (ORCID: https://orcid.org/0000-0002-3614-8002)
- L. Steven
- Ewen M. Harrison (ORCID: https://orcid.org/0000-0002-5018-3066)
- E. Musenga
- J. Fretwell
- Joey S.W. Kwong (ORCID: https://orcid.org/0000-0002-7473-3827)
- Richard J. E. Skipworth (ORCID: https://orcid.org/0000-0003-1428-4078)
- William Cambridge (ORCID: https://orcid.org/0000-0001-7560-7905)
- Mark Ramage (ORCID: https://orcid.org/0000-0003-2741-0424)
- Nathan Ng (ORCID: https://orcid.org/0000-0001-7063-6870)
- Sinéad M. O’Neill (ORCID: https://orcid.org/0000-0001-9787-4609)
- Shauna L. Tominey (ORCID: https://orcid.org/0000-0003-0448-0817)
- Catherine M. Scott (ORCID: https://orcid.org/0000-0001-9959-3288)
- Vinod K. Chauhan (ORCID: https://orcid.org/0000-0001-5929-4988)
- Vinay Sehgal (ORCID: https://orcid.org/0000-0002-5700-8252)
- A F MacNamara
- J Reed
- Cameron J Fairfield
- Seonaid Mackay
Institutions
- Western General Hospital (GB)
- The Queen's Medical Research Institute (GB)
- University of Edinburgh (GB)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2025-02-23
- DOI
- https://doi.org/10.1038/s41746-024-01419-8
- Citations
- 13
- Primary Topic
- Surgical site infection prevention
- Type
- article
- Field-Weighted Citation Impact
- 26.08
Funders
- Royal College of Surgeons of Edinburgh
- Medical Research Council