Imagine a hospital’s AI-powered analytics systems that forecasts stocking of medical supplies with accuracy — and even prescribes purposing of beds, consultation rooms and operation theatres — based on real-time patterns and trends of both external and internal events.
Let’s move to another possibility. Imagine a digital front door for patients seeking admission — with healthcare provider information, online patient forms, patient education, and self-service check-in. And behind the scenes, imagine a unified back-office with technology purpose-designed for data-driven computing, which is both patient-friendly and efficiently accurate for provider organizations.
From hypothetical possibilities, here is a real example. Researchers from Mount Sinai Health System Hospital, pulled data from seven of their hospitals to create a large language model (LLM) GPT-4, that could predict the likelihood of patients in emergency departments needing hospitalization — with ~83% accuracy.
Today, such an integrated, efficient, and patient-centered scenario is as possible as it is urgently needed. Over the last 5 to 10 years, the practice of value-based care has assumed predominant importance, focusing on delivering high-quality patient outcomes at optimal cost. We also see a shift to a hybrid approach of virtual and in-facility care that aims to enhance both patient engagement and clinical outcomes.
The call for a connected ‘bedside to back-office’ ecosystem cannot be more relevant than it is today. Let’s see how we can create this holistic continuum that brings together the components of better outcomes, scalable innovation and cost-efficiency.
Creating a seamless continuum of trust-driven care
As a critical bedrock of the healthcare system that drives an efficient care continuum and business growth, the back office is a prime candidate for healthcare modernization and digital transformation. Trust and technology are two critical pillars of back-office operational excellence and impact to ensure trust in the bedside experience.
AI- and Cloud-driven automation is a huge transformative force for healthcare data management. Today, healthcare enterprises have access to ballooning volumes of healthcare data from not only electronic health records (EHR), but also from remote devices, telehealth information and other medical imaging devices. AI-led Cloud platforms with multi-tiered architectures provide just the right means of data access, management and compliance — at speed and scale.
By ensuring a seamless and direct integration of digital devices and systems in the patient care environment, healthcare providers can deliver timely and precise interventions, while simultaneously empowering patients with greater control over their hospital experience. Multi-dimensional aspects of hardware and software systems can be unified to deliver patient monitoring, data management, communication, and decision support in real-time.
Stepping beyond the clinical domain, smart technologies (AI assistants, robotic process automation, etc.) bring about phenomenal efficiencies in infrastructure, facility and energy management to generate substantial cost saving — which, in turn, can be ploughed back into enhancing the quality of care.
In fact, a HealthTech Magazine survey reports 25% improvement in patient recovery times with 15% enhanced satisfaction levels in hospitals that integrated back-office and bedside technologies.
How back-office efficiencies bubble up to bedside experiences
AI-led predictive and prescriptive analytics, reinforced by intelligent automation, can transform stored healthcare data into an active clinical resource to streamline operations with effective risk management and meticulous regulatory compliance.
These technologies can also lend great efficiency and simplify the way healthcare organizations manage critical financial operations (accounts payable and receivables, cash management, fixed assets, and revenue recognition), as well as enterprise functions of planning, budgeting, investments, and more.
From an operational perspective, the integration of AI, automation and analytics can deliver significant efficiencies in the areas of utilization of beds and operating rooms, staff scheduling, infection control, patient flow management, regulatory compliance, etc.
When it comes to supply chain teams, automation can track inventory levels in real time, analyze usage, and predict supply needs. Covering the gamut of procurement, inventory, warehousing, forecasting and planning, it can eliminate both disruptions and overstocking — with the right materials at the right time and right cost.
And then there is the vital function of workforce planning and management. From core HR operations (payroll, benefits, etc.), absence, time & labor, talent acquisition and management, and learning — it allows HR teams to focus on higher-value tasks while it takes care of routine processes in the background.
A seamless handshake for impactful outcomes
An effectively connected healthcare technology platform of front-, middle-, and back-office operations can deliver immense outcomes, including the following:
- 1. AI-led analytics, embedded within bedside systems and patient care settings, enable greater personalization and accuracy of medical services — plus ensure early detection and proactive intervention of potential health issues
- 2. Integrated Electronic Health Records (EHR) at the bedside significantly reduces medication administration errors, enhances patient safety and minimizes liability risks.
- 3. A digital ecosystem of patient-owned health data collection, teleconsultations and remote monitoring, and AI-driven diagnostics elevates patient care beyond the hospital setting.
- 4. Automation of routine patient tasks such as vital signs monitoring, through connected devices, frees up nurses’ time and allows them to attend to more critical, qualitative and judgement-intensive patient needs.
- 5. Smart alerts and AI-based monitoring systems continuously analyze patient vitals to safeguard their safety and control infections
- 6. Innovative bedside technologies also give patients greater control over their treatment, thereby enhancing engagement and satisfaction regarding informed decision-making
The potential of Gen AI in redefining continuity of care and clinical operations cannot be underestimated. However, it is equally important to credibly address the concerns of providers and patients about its risks, especially in the area of privacy. Effective data governance frameworks and interoperability between patient devices and clinical systems is thus a non-negotiable demand.
Creating effective partnerships for ‘bedside-to-backoffice’ transformation
Delivering such digital intelligence and innovation in health systems demands new ways of working. This can be achieved through reimagined clinical workflows and care models, and structural changes to create empowered and cross-functional teams. From a technology standpoint, it is important to build cloud-based data environments that enhance data quality and accessibility — and end-user-driven platforms to simplify stakeholder engagement. Plus, scale has to be achieved.
What healthcare enterprises need is a true innovation partner who has in-depth industry knowledge and expertise — and who, as a domain-technology expert, can bridge the gap between intent and execution. Such partnerships will ensure swift access to the right capabilities to achieve speed-to-market and operational efficiencies. Through central command centers that deploy AI, automation, and analytics in the areas of resource management, supply chain operations, and smart revenue cycle management, they can bring in tremendous value of co-innovation and co-solutioning.
I say this with conviction, as I have been involved first-hand in my organization’s partnerships with global healthcare enterprises to create integrated solutions that enable them to reduce costs, drive customer satisfaction, deliver quality care, and make smart hospitals a reality. From digital maturity assessments to data migration to the Cloud, development of digital front doors and interoperable solutions, intelligent analytics for data-based decision making, and managed services — we have opened a wide world of digital healthcare transformation for global enterprises.
The road to such transformational change is not without its challenges. Integration with legacy systems and achieving efficient system interoperability, high investments in technology and infrastructure systems, uncertainty about the ROI of investments, cybersecurity risks, and achieving patient trust — these are real issues to be addressed. Yet, within this lies an exciting opportunity to architect a smartly connected, data-first and technology-driven healthcare ecosystem that is committed to patient well-being, and industry growth and sustainability.
Let’s join hands to create this reality.
