Transforming Healthcare with AI and Deviceless Remote Patient Monitoring

The following is a guest article by Darren Challender, Client Engagement Partner (Healthcare) at Hitachi Digital Services

As healthcare systems around the world continue to face increasing demands and resource constraints, innovative solutions are becoming critical in ensuring that care delivery is both efficient and effective. The recent webinar by Hitachi Digital Services focused on population health and deviceless remote patient monitoring (RPM), shedding light on how artificial intelligence (AI) and digital solutions are driving transformation in healthcare management. This article highlights the key insights and takeaways from the discussion, offering a glimpse into the future of healthcare and the role of AI in optimizing patient outcomes.

Shifting to Proactive and Preventive Care

One of the central themes of the webinar was the shift from reactive care to proactive and preventive healthcare. Traditionally, healthcare systems have been structured around treating patients when they become ill, but there is a growing consensus that preventive care is key to improving health outcomes at scale.

Vitor Domingo from Hitachi DS emphasized this shift, “We want to explore how innovation in digital solutions and artificial intelligence is transforming healthcare management on a large scale.” Moving to a proactive model means leveraging data and AI to prevent health issues before they occur, helping reduce the burden on healthcare systems and improving patient well-being.

Addressing Overlooked Non-Clinical Risk Factors

A critical insight shared by Patrick Burton of Lightbeam Health Solutions was the importance of non-clinical risk factors—also known as social determinants of health (SDOH). These factors include where patients live, their employment status, social support, and access to food and transportation. Although often overlooked, these elements significantly impact both health and clinical outcomes.

According to Patrick, “Non-clinical risk factors… have a market impact on health outcomes and clinical outcomes.” In fact, Lightbeam’s AI-driven models have demonstrated that it’s possible to predict the likelihood of hospitalization with 75% accuracy using just basic demographic information like age, gender, and zip code. This underscores the importance of considering social factors in healthcare management.

Tackling Data Fragmentation

Data fragmentation remains one of the biggest barriers to effective healthcare delivery. As Patrick Burton noted, “Every time we introduce a new silo of data, we force consumers of that data to manually overcome gaps.” This fragmentation creates inefficiencies, making it harder for healthcare providers to deliver coordinated care at scale. To address this, a 360-degree view of the patient, integrating clinical, non-clinical, and financial data, is essential for improving care coordination and enabling population-level health analysis.

Global Trends in Healthcare

Eratha Poongkuntran, Healthcare Research Leader at Avasant shared valuable insights on key global healthcare trends, including the aging population, the rising burden of chronic diseases, and the global healthcare workforce shortage. These trends are driving the need for more integrated care models, preventive health programs, and new technologies like AI to help improve healthcare efficiency. Countries like Japan and Germany have already implemented programs that focus on lifestyle modifications and integrated care, providing useful lessons for other nations to follow.

The Role of Integrated Care Systems (ICS) in the UK

In the UK, the formation of Integrated Care Systems (ICS) is a significant step toward better healthcare coordination. Paul Watson from Hitachi Digital Services discussed how ICSs are promoting collaboration between healthcare providers, local governments, and social services. Despite challenges such as system fragmentation, national initiatives like the Federated Data Platform are working to solve data integration issues, paving the way for large-scale digital interventions that improve health outcomes.

The Transformative Power of AI in Healthcare

AI is playing an increasingly important role in healthcare, from streamlining administrative tasks to enhancing diagnostic processes. Paul Watson emphasized the potential of AI in improving productivity and efficiency, which can free up valuable time for healthcare professionals. AI applications, such as automation of administrative tasks, medical coding, and even diagnostics, are transforming the healthcare landscape.

For instance, AI is being used to assist in mammogram screenings, helping reduce the need for two radiologists to one. This not only increases screening capacity but also demonstrates AI’s potential to address critical issues like healthcare workforce shortages.

Challenges in AI Implementation

Despite its promise, AI adoption in healthcare faces several challenges. There is often a lack of clear strategy, with organizations focusing on point solutions rather than long-term integration. Data security and sharing concerns remain, and there is a need for a unified approach to technology to reduce duplication of efforts. AI also requires high-quality data, and addressing data quality issues is crucial for ensuring the effectiveness of AI solutions.

Lightbeam’s Approach to Automated Care Orchestration

Lightbeam Health Solutions is leading the charge in automated care orchestration, which helps optimize the workforce and improve care delivery. Through AI-driven solutions, Lightbeam’s platform aggregates data from various sources, provides prescriptive AI modeling, and enables deviceless RPM. This approach allows for continuous patient monitoring using simple devices, such as phones, making it more accessible for patients who might otherwise be unable to use traditional medical devices.

A use case involving a patient with COPD demonstrates how Lightbeam’s system identifies rising risk factors, such as lack of transportation, and engages the patient proactively. This system has led to significant outcomes, such as a 39% reduction in hospital admissions in a rural US organization.

Future Impact of Healthcare Innovation

The future of healthcare is rapidly evolving, with a focus on centralized care management that integrates both clinical and non-clinical activities. Digital care models are poised to transform healthcare delivery with virtual hospitals, smart devices, and real-time tracking of patient conditions. These innovations promise to improve early interventions, optimize resource allocation, and provide personalized care.

Conclusion

The Hitachi Digital Services webinar highlighted the importance of embracing innovation to address the growing challenges in healthcare. The shift from reactive to proactive care, addressing social determinants of health, and overcoming data fragmentation are all critical steps in creating a more efficient healthcare system. AI and deviceless RPM are transforming the way care is delivered, offering significant improvements in efficiency and patient outcomes. As healthcare organizations develop digital strategies and integrate AI solutions, they will be better equipped to meet the demands of the future and drive meaningful improvements in population health.

By adopting solutions like automated care orchestration and focusing on data integration, healthcare providers can position themselves at the forefront of the digital health revolution, delivering better, more personalized care to patients around the world.