Redesigning the Frontline: Human-Centred Digital Innovation for the Future of Nursing and Midwifery

In the digital health revolution, success isn’t just about smarter technologies; it’s about meaningful integration into the daily lives of those who use them. For nurses and midwives, whose workflows, decisions, and emotional labour are deeply human, the digital future must be more than efficient. It must be empathetic, usable, and co-designed (Topaz et al., 2022).

Human-centred digital innovation places end-users, such as frontline healthcare professionals, at the heart of every stage of development. In contrast to top-down technology rollouts that often disrupt care, this approach invites nurses and midwives to become co-creators of the very tools they will use (Cresswell et al., 2019).

Reimagining Workflow through Co-Design

Traditional clinical systems are known to have usability issues, adding to cognitive load and frustration. Emerging projects are flipping this script by involving nurses and midwives in iterative design workshops, testing prototypes, and even defining success metrics (Gagnon et al., 2021).

Some of the innovations include:

• Mobile documentation interfaces are designed around real-time workflow rather than after-the-fact reporting
• Context-aware digital dashboards that highlight the most relevant data for patient care
• Voice-assisted systems that allow hands-free charting in maternity or critical care environments

Studies have shown that involving clinicians in the early phases of digital tool development increases acceptance, usability scores, and sustained adoption rates (Greenhalgh et al., 2017).

Interoperability as a Foundation, Not a Feature

Fragmented data continues to challenge timely and safe care. Midwives working across antenatal, child delivery, and postnatal settings often juggle disparate platforms that don’t communicate. Nurses in aged care or primary health often repeat assessments due to the lack of integration (Walker et al., 2020).

Next-generation health information systems are now prioritizing standards-based interoperability. Using protocols like FHIR (Fast Healthcare Interoperability Resources) and SNOMED CT, digital ecosystems are being built to allow seamless exchange of information across settings (Mandal et al., 2022).

But interoperability isn’t just technical, it’s cultural. Success depends on engaging clinical end-users in conversations about what data matters most, how it should be visualized, and when it should be shared (Vest et al., 2021).

AI for Clinician Support, Not Surveillance

Artificial Intelligence (AI) and machine learning are being introduced across hospitals and health systems, but concerns remain. Will algorithms replace judgment? Will data be used to monitor performance rather than support care?

Human-centred digital health turns that fear on its head. By embedding AI into nurse and midwife-led workflows, technologies can:

• Predict patient deterioration and flag early alerts (Rajpurkar et al., 2022)
• Recommend evidence-based interventions tailored to local protocols
• Free up cognitive space by auto-filling routine data fields based on context

Rather than replacing clinicians, these tools are intended to enhance human intuition and reduce burden, while ensuring that decisions remain with those closest to the patient (Sutton et al., 2020).

Education and Digital Confidence

For digital innovation to be sustainable, it must be accompanied by a shift in mindset. That means preparing nurses and midwives with not just technical skills, but digital confidence and critical agency (Booth et al., 2021).

Professional development programs are emerging that include:

• Data literacy and AI fundamentals
• Ethical and safe use of digital platforms
• Co-design methods for clinical technology

These programs reframe clinicians as active agents in digital transformation, not passive recipients of change.

Measuring What Matters

It’s not enough for a tool to function; it must add value. Human-centred approaches demand meaningful evaluation frameworks that include:

• End-user satisfaction and usability ratings (Zhou et al., 2019)
• Impact on clinical workflow efficiency
• Influence on staff wellbeing and burnout metrics
• Safety and patient outcome indicators

In particular, midwives and nurses working in remote or resource-limited areas have emphasized the importance of resilience and offline access as core performance metrics (Fahy et al., 2021).

Designing with, not for

Digital health can fail if it is imposed. But it can thrive if it is co-created. Nurses and midwives bring deep contextual knowledge, empathy, and practical wisdom to care delivery. Their involvement in shaping digital solutions is not optional; it is essential.

Human-centred innovation isn’t just about making better tools. It’s about designing a system where clinicians are empowered, patients are safer, and technology works in the service of the human experience.

The future of healthcare is being built from the bedside out.

References

Booth R, Strudwick G, McBride S, O'Connor S, Solano Lopez AL. How the nursing profession should adapt for a digital future. BMJ. 2021;373:n1190.

Cresswell K, Bates DW, Sheikh A. Ten key considerations for the successful implementation and adoption of large-scale health information technology. J Am Med Inform Assoc. 2019;26(11):1221–1224.

Fahy K, Hastie C, Bisits A, et al. Holistic physiological care compared with standard hospital care for women at low risk of birth complications: a randomised controlled trial. BMJ Open. 2021;11(9):e047352.

Gagnon MP, Ghandour EK, Talla PK, et al. Electronic health record acceptance by physicians: Testing an integrated theoretical model. J Biomed Inform. 2021;116:103758.

Greenhalgh T, Wherton J, Papoutsi C, et al. Beyond adoption: A new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. J Med Internet Res. 2017;19(11):e367.

Mandal S, Roehrs A, da Costa CA, Righi R da RS. Interoperability in healthcare: a systematic review of technologies and frameworks. Health Informatics J. 2022;28(1):14604582221075344.

Rajpurkar P, Chen E, Banerjee O, Topol EJ. AI in healthcare: the future is now. Nat Med. 2022;28(5):1149–1155.

Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digit Med. 2020;3:17.

Topaz M, Ronquillo C, Peltonen L-M, et al. Advancing nursing informatics in the post-COVID era. J Am Med Inform Assoc. 2022;29(1):167–175.

Vest JR, Jung HY, Wiley K, Kooreman H, Pettit L, Menachemi N. Adoption and use of health information technology by community health centers. Med Care Res Rev. 2021;78(3):267–277.

Walker J, Pan E, Johnston D, Adler-Milstein J, Bates DW, Middleton B. The value of health care information exchange and interoperability. Health Aff (Millwood). 2020;29(3):357–363.

Zhou L, Parmanto B, Saptono A, et al. Usability evaluation of a mHealth intervention for persons with disabilities and chronic conditions. J Med Syst. 2019;43(5):135.