By Rahul Patel, EVP of digital products and services, Persistent Systems.
There is a growing interest among healthcare organizations to leverage actionable analytics solutions to derive valuable insights from data. Advanced, AI-driven predictive modeling is working to build healthier populations that meet the demands of value-based care, and new digital experiences are reaching providers and patients through a diverse array of touchpoints. Digital health solutions, driven by new and emerging data sources, are creating a unique combination of high-touch care management complemented by automated, virtual care.
This digital transformation in healthcare is being driven by the changing nature of the healthcare landscape, as well as the demands from consumers for more say in their care. The healthcare industry is making significant investments in IT to engage and empower patients, enable caregivers and improve operating efficiencies. However, the industry is also facing pushback from the caregiver community, with many physicians feeling that interacting with an EMR reduces their productivity. Physician burnout and unrealized expectations from technology investments have created a mood of caution in digital investments.
However, the digital transformation wave is still coming, since the proven patient health benefits, as well as industry improvements, are simply too great to ignore. Given the abundance of software-driven tools, technology professionals face the crucial task of integrating applications and data among the various players in the healthcare ecosystem including doctors, hospitals, government, device makers, insurers, employers, pharmaceutical companies and patients. Seamless transitions of care between these constituencies, however, are still a major hurdle, and positive patient experience is decided by the totality of patient care carried out by all those — both within and outside — of a health system. Shared processes between clinical entities are only possible if the data can journey smoothly from one system to another.
The problem today is that there is over-engineering in healthcare with overlapping and rich data standards and formats, and implementations that stay locked tightly in proprietary strongholds.
How to Make Interoperability Work
It is imperative that digital transformation initiatives focus on interoperability and integrations through well-defined application programming interfaces (APIs). APIs are designed so that systems with validated credentials can query and access systems widely available on the internet. Systems are then designed to respond to queries from programs with data that is machine-readable.
APIs deliver the ability to securely and efficiently access repositories of big data from wearable devices, social media, curated public datasets, research, and episodic care. They are the key to better understanding patients’ financial, social and behavioral context, and through predictive and prescriptive analytics can reveal trends across populations and micro-populations. With the explosion of disparate technologies, it will be about connecting them all quickly and efficiently to gain a competitive edge in healthcare.
To ensure API-enabled systems can be scaled up, protocols should be built and managed efficiently in a distributed fashion rather than through a restrictive, centrally-managed model. Data must move from expensive on-premise data centers to robust cloud platforms. A reference architecture based on data integration, curation, and API management will rapidly bring new healthcare experiences and capabilities to market.
Tearing down silos and honing data into a cloud-consumable, scalable format will bring speed to digital. It will create new revenue channels and improve user experiences for researchers, clinicians, and patients, and drive innovative new capabilities for all three.
Digital transformation enabled by APIs, however, is not a one-off project. It is an ongoing philosophy that should inform all initiatives in the healthcare enterprise. With users expecting compelling and pervasive experiences, enterprises must establish a rhythm to build and deploy the experiences that users need, and this will only happen if these experiences are built on interfaces that combine data from internal enterprise systems, external online sources and data collected from sensors in real-time. Modern systems must learn continuously from user behavior and other available signals, and this will only happen when systems are effectively sharing and communicating with each other to enhance the lives of everyone within the healthcare ecosystem.