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  • Review Article
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Digital health technologies: opportunities and challenges in rheumatology

Nature Reviews Rheumatology volume 16, pages 525–535 (2020)Cite this article

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Abstract

The past decade in rheumatology has seen tremendous innovation in digital health technologies, including the electronic health record, virtual visits, mobile health, wearable technology, digital therapeutics, artificial intelligence and machine learning. The increased availability of these technologies offers opportunities for improving important aspects of rheumatology, including access, outcomes, adherence and research. However, despite its growth in some areas, particularly with non-health-care consumers, digital health technology has not substantially changed the delivery of rheumatology care. This Review discusses key barriers and opportunities to improve application of digital health technologies in rheumatology. Key topics include smart design, voice enablement and the integration of electronic patient-reported outcomes. Smart design involves active engagement with the end users of the technologies, including patients and clinicians through focus groups, user testing sessions and prototype review. Voice enablement using voice assistants could be critical for enabling patients with hand arthritis to effectively use smartphone apps and might facilitate patient engagement with many technologies. Tracking many rheumatic diseases requires frequent monitoring of patient-reported outcomes. Current practice only collects this information sporadically, and rarely between visits. Digital health technology could enable patient-reported outcomes to inform appropriate timing of face-to-face visits and enable improved application of treat-to-target strategies. However, best practice standards for digital health technologies do not yet exist. To achieve the potential of digital health technology in rheumatology, rheumatology professionals will need to be more engaged upstream in the technology design process and provide leadership to effectively incorporate the new tools into clinical care.

Key points

  • Digital health technology (DHT) offers enormous potential to improve rheumatology care but this potential has so far been largely unrealized.

  • The electronic health record, virtual visits, mobile health, wearable technology, digital therapeutics, artificial intelligence and machine learning could all have a role individually and in combination to reshape rheumatology practice.

  • Increased use of user-centred design in the development of digital rheumatology tools is needed and will facilitate electronic patient-reported outcomes becoming a cornerstone of rheumatology.

  • As rheumatology patients often have difficulties using their hands, voice-enabled technology might be particularly critical in this field.

  • A more concerted effort on the part of rheumatology professionals to participate in shaping the development and implementation of DHTs could make the benefits realized sooner and more effectively.

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Fig. 1: Overview of digital health technologies as they relate to rheumatoid arthritis.
Fig. 2: Integrated system of digital health technologies in a possible future rheumatology clinic.

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Acknowledgements

D.H.S. received support from NIH P30-AR072577 (VERITY) to support this review. He has also received research support for digital health technology development from Pfizer and Janssen. R.S.R. received support from AHRQ 1R18HS026432-01.

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  1. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Daniel H. Solomon

  2. RAND Corporation, Boston, MA, USA

    Robert S. Rudin

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Glossary

Artificial intelligence and machine learning

(AI/ML). Artificial intelligence is the broader concept of machines (computers or other) being able to carry out tasks in a way that we would consider ‘smart’. Machine learning is a current application of artificial intelligence based around the idea that machines with access to data can learn for themselves.

Clinical decision support

A support system used in health information technology designed to provide clinicians with decision support around clinical issues. It usually involves accessing information in an electronic health record (for example, laboratory tests, diagnoses, medications, allergies and vaccination record) and uses logic based on medical guidelines.

Best practice alerts

A type of clinical decision support used in many electronic health records, where the results of the clinical decision support are displayed as alerts to clinicians.

Health Level Seven

(HL7). HL7 refers to standards for the transfer of data between software applications used by various health-care providers. The standards are most applicable to the software application level, which is described as ‘layer 7’.

Fast Healthcare Interoperability Resources

(FHIR). A standard developed by Health Level 7 for describing data formats and elements and an application programming interface that facilitates exchange of electronic health record data.

Health Insurance Portability and Accountability Act

An act signed into law by the US government in 1996 that was created to specify the appropriate flow of health-care information. It specifically stipulates how personally identifiable information should be maintained and protected from fraud and theft.

Software as a Medical Device

(SaMD). Software intended to be used for medical purposes that performs its functions without being part of a hardware medical device.

510(k)

A premarket submission made to the FDA to demonstrate that a medical device (or digital health technology) to be marketed is at least as safe and substantially equivalent to a legally marketed device that is not subject to premarket approval.

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Solomon, D.H., Rudin, R.S. Digital health technologies: opportunities and challenges in rheumatology. Nat Rev Rheumatol 16, 525–535 (2020). https://doi.org/10.1038/s41584-020-0461-x

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